a owl:Class ;
+ rdfs:label "4 Hz Modulation Harmonic Coefficients",
+ "4HzModulationHarmonicCoefficients" ;
+ af:application_domain af:AudioSegmentation ;
+ af:computation af:Autocorrelation,
+ af:BandpassFilterBank,
+ af:DiscreteCosineTransform,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "4 Hz Modulation Harmonic Coefficients feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:AmplitudeDescriptor a owl:Class ;
+ rdfs:label "Amplitude Descriptor",
+ "AmplitudeDescriptor" ;
+ af:application_domain af:EnvironmentalSoundRecognition ;
+ af:computation af:Mean,
+ af:Median,
+ af:Spectralbinning,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 9 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Amplitude Descriptor feature" ;
+ rdfs:subClassOf af:TemporalFeature ;
+ vs:term_status "testing" .
+
+af:AuditoryFilterBankTemporalEnvelopes a owl:Class ;
+ rdfs:label "Auditory Filter Bank Temporal Envelopes",
+ "AuditoryFilterBankTemporalEnvelopes" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:BandpassFilterBank,
+ af:EnergySpectralDensity,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 62 ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Auditory Filter Bank Temporal Envelopes feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:AutocorrelationMFCCs a owl:Class ;
+ rdfs:label "Autocorrelation MFCCs",
+ "AutocorrelationMFCCs" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:Autocorrelation,
+ af:DiscreteCosineTransform,
+ af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:LowpassFilter,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Autocorrelation MFCCs feature" ;
+ rdfs:subClassOf af:CepstralFeature ;
+ vs:term_status "testing" .
+
+af:BandPeriodicity a owl:Class ;
+ rdfs:label "Band Periodicity",
+ "BandPeriodicity" ;
+ af:application_domain af:AudioSegmentation ;
+ af:computation af:Autocorrelation,
+ af:BandpassFilterBank,
+ af:RootMeanSquare,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 4 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Band Periodicity feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:Bandwidth a owl:Class ;
+ rdfs:label "Bandwidth" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:Median,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Bandwidth feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:BarkscaleFrequencyCepstralCoefficients a owl:Class ;
+ rdfs:label "Bark-scale Frequency Cepstral Coefficients",
+ "BarkscaleFrequencyCepstralCoefficients" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteCosineTransform,
+ af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Bark-scale Frequency Cepstral Coefficients feature" ;
+ rdfs:subClassOf af:CepstralFeature ;
+ vs:term_status "testing" .
+
+af:BeatHistogram a owl:Class ;
+ rdfs:label "Beat Histogram",
+ "BeatHistogram" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:Autocorrelation,
+ af:DiscreteWaveletTransform,
+ af:LowpassFilter,
+ af:RootMeanSquare,
+ af:Spectralbinning,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 6 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Beat Histogram feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:BeatSpectrum a owl:Class ;
+ rdfs:label "Beat Spectrum",
+ "BeatSpectrum" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:Autocorrelation,
+ af:CrossCorrelation,
+ af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:LowpassFilter,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Beat Spectrum feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:BeatTracker a owl:Class ;
+ rdfs:label "Beat Tracker",
+ "BeatTracker" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:BandpassFilterBank,
+ af:CombFilterBank,
+ af:DerivationDifference,
+ af:LowpassFilter,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Beat Tracker feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:ChromaCENSFeatures a owl:Class ;
+ rdfs:label "Chroma CENS Features",
+ "ChromaCENSFeatures" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:BandpassFilterBank,
+ af:LowpassFilter,
+ af:Normalization,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 12 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Chroma CENS Features feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:Chromagram a owl:Class ;
+ rdfs:label "Chromagram" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 12 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Chromagram feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:CyclicBeatSpectrum a owl:Class ;
+ rdfs:label "Cyclic Beat Spectrum",
+ "CyclicBeatSpectrum" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:CombFilterBank,
+ af:DerivationDifference,
+ af:DiscreteFourierTransform,
+ af:LowpassFilter,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Cyclic Beat Spectrum feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:DWPTbasedRhythmFeature a owl:Class ;
+ rdfs:label "DWPT-based Rhythm Feature",
+ "DWPTbasedRhythmFeature" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:Autocorrelation,
+ af:DiscreteWaveletTransform,
+ af:RootMeanSquare,
+ af:Spectralbinning,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "DWPT-based Rhythm Feature feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:DaubechiesWaveletCoefficientHistogram a owl:Class ;
+ rdfs:label "Daubechies Wavelet Coefficient Histogram",
+ "DaubechiesWaveletCoefficientHistogram" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteWaveletTransform,
+ af:Spectralbinning,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 28 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Daubechies Wavelet Coefficient Histogram feature" ;
+ rdfs:subClassOf af:FrequencyDomainPhysicalFeature ;
+ vs:term_status "testing" .
+
+af:DistortionDiscriminantAnalysis a owl:Class ;
+ rdfs:label "Distortion Discriminant Analysis",
+ "DistortionDiscriminantAnalysis" ;
+ af:application_domain af:Fingerprinting ;
+ af:computation af:Logarithm,
+ af:ModulatedComplexLappedTransform,
+ af:PrincipalComponentAnalysis,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions 64 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Distortion Discriminant Analysis feature" ;
+ rdfs:subClassOf af:EigendomainFeature ;
+ vs:term_status "testing" .
+
+af:HarmonicCoefficient a owl:Class ;
+ rdfs:label "Harmonic Coefficient",
+ "HarmonicCoefficient" ;
+ af:application_domain af:AudioSegmentation ;
+ af:computation af:Autocorrelation,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Harmonic Coefficient feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:HarmonicConcentration a owl:Class ;
+ rdfs:label "Harmonic Concentration",
+ "HarmonicConcentration" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:EnergySpectralDensity,
+ af:LevelCrossingDetector,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Harmonic Concentration feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:HarmonicDerivate a owl:Class ;
+ rdfs:label "Harmonic Derivate",
+ "HarmonicDerivate" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DerivationDifference,
+ af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Harmonic Derivate feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:HarmonicEnergyEntropy a owl:Class ;
+ rdfs:label "Harmonic Energy Entropy",
+ "HarmonicEnergyEntropy" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:Entropy,
+ af:LevelCrossingDetector,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Harmonic Energy Entropy feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:HarmonicProminence a owl:Class ;
+ rdfs:label "Harmonic Prominence",
+ "HarmonicProminence" ;
+ af:application_domain af:EnvironmentalSoundRecognition ;
+ af:computation af:Autocorrelation,
+ af:LevelCrossingDetector,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Harmonic Prominence feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:Inharmonicity a owl:Class ;
+ rdfs:label "Inharmonicity" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:Autocorrelation,
+ af:LevelCrossingDetector,
+ af:Median,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Inharmonicity feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:IntegralLoudness a owl:Class ;
+ rdfs:label "Integral Loudness",
+ "IntegralLoudness" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:ExponentialFunction,
+ af:Logarithm,
+ af:NonLinearWeightingFunction,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Integral Loudness feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:JointAcousticandModuluationFrequency a owl:Class ;
+ rdfs:label "Joint Acoustic and Moduluation Frequency",
+ "JointAcousticandModuluationFrequency" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteFourierTransform,
+ af:DiscreteWaveletTransform,
+ af:LowpassFilter,
+ af:Regression,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Joint Acoustic and Moduluation Frequency feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:LineSpectralFrequencies a owl:Class ;
+ rdfs:label "Line Spectral Frequencies",
+ "LineSpectralFrequencies" ;
+ af:application_domain af:Several ;
+ af:computation af:AutoregressionLinearPredictionAnalysis,
+ af:Percentile,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Line Spectral Frequencies feature" ;
+ rdfs:subClassOf af:FrequencyDomainPhysicalFeature ;
+ vs:term_status "testing" .
+
+af:LinearPredictionCepstralCoefficients a owl:Class ;
+ rdfs:label "Linear Prediction Cepstral Coefficients",
+ "LinearPredictionCepstralCoefficients" ;
+ af:abbreviation "LPCC" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:AutoregressionLinearPredictionAnalysis,
+ af:BandpassFilterBank,
+ af:CepstralRecursionFormula,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Linear Prediction Cepstral Coefficients feature" ;
+ rdfs:subClassOf af:CepstralFeature ;
+ vs:term_status "testing" .
+
+af:LinearPredictionZCR a owl:Class ;
+ rdfs:label "Linear Prediction ZCR",
+ "LinearPredictionZCR" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:AutoregressionLinearPredictionAnalysis,
+ af:Spectralbinning,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Linear Prediction ZCR feature" ;
+ rdfs:subClassOf af:TemporalFeature ;
+ vs:term_status "testing" .
+
+af:LinearPredictiveCoding a owl:Class ;
+ rdfs:label "Linear Predictive Coding",
+ "LinearPredictiveCoding" ;
+ af:abbreviation "LPC" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:AutoregressionLinearPredictionAnalysis,
+ af:BandpassFilterBank,
+ af:DiscreteFourierTransform,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Linear Predictive Coding feature" ;
+ rdfs:subClassOf af:FrequencyDomainPhysicalFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7AudioFundamentalFrequency a owl:Class ;
+ rdfs:label "MPEG-7 Audio Fundamental Frequency",
+ "MPEG7AudioFundamentalFrequency" ;
+ af:application_domain af:Several ;
+ af:computation af:Autocorrelation,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 2 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "MPEG-7 Audio Fundamental Frequency feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7AudioHarmonicity a owl:Class ;
+ rdfs:label "MPEG-7 Audio Harmonicity",
+ "MPEG7AudioHarmonicity" ;
+ af:application_domain af:Several ;
+ af:computation af:Autocorrelation,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 2 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "MPEG-7 Audio Harmonicity feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7AudioSpectrumBasis a owl:Class ;
+ rdfs:label "MPEG-7 Audio Spectrum Basis",
+ "MPEG7AudioSpectrumBasis" ;
+ af:application_domain af:EnvironmentalSoundRecognition ;
+ af:computation af:DiscreteFourierTransform,
+ af:IndependentComponentAnalysis,
+ af:Logarithm,
+ af:Normalization,
+ af:Regression,
+ af:SingularValueDecomposition,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "MPEG-7 Audio Spectrum Basis feature" ;
+ rdfs:subClassOf af:EigendomainFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7AudioSpectrumCentroid a owl:Class ;
+ rdfs:label "MPEG-7 Audio Spectrum Centroid",
+ "MPEG7AudioSpectrumCentroid" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:Mean,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "MPEG-7 Audio Spectrum Centroid feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7AudioSpectrumSpread a owl:Class ;
+ rdfs:label "MPEG-7 Audio Spectrum Spread",
+ "MPEG7AudioSpectrumSpread" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:Median,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "MPEG-7 Audio Spectrum Spread feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7AudioWaveform a owl:Class ;
+ rdfs:label "MPEG-7 Audio Waveform",
+ "MPEG7AudioWaveform" ;
+ af:computation af:Histogram,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 2 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "MPEG-7 Audio Waveform feature" ;
+ rdfs:subClassOf af:TemporalFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7HarmonicSpectralCentroid a owl:Class ;
+ rdfs:label "MPEG-7 Harmonic Spectral Centroid",
+ "MPEG7HarmonicSpectralCentroid" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:LevelCrossingDetector,
+ af:Mean,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "MPEG-7 Harmonic Spectral Centroid feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7HarmonicSpectralDeviation a owl:Class ;
+ rdfs:label "MPEG-7 Harmonic Spectral Deviation",
+ "MPEG7HarmonicSpectralDeviation" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:LevelCrossingDetector,
+ af:Logarithm,
+ af:Mean,
+ af:Median,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "MPEG-7 Harmonic Spectral Deviation feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7HarmonicSpectralSpread a owl:Class ;
+ rdfs:label "MPEG-7 Harmonic Spectral Spread",
+ "MPEG7HarmonicSpectralSpread" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:LevelCrossingDetector,
+ af:Median,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "MPEG-7 Harmonic Spectral Spread feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7HarmonicSpectralVariation a owl:Class ;
+ rdfs:label "MPEG-7 Harmonic Spectral Variation",
+ "MPEG7HarmonicSpectralVariation" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:CrossCorrelation,
+ af:DiscreteFourierTransform,
+ af:LevelCrossingDetector,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "MPEG-7 Harmonic Spectral Variation feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7LogAttackTime a owl:Class ;
+ rdfs:label "MPEG-7 Log Attack Time",
+ "MPEG7LogAttackTime" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:Logarithm,
+ af:Power,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:Global ;
+ rdfs:comment "MPEG-7 Log Attack Time feature" ;
+ rdfs:subClassOf af:TemporalFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7SpectralCentroid a owl:Class ;
+ rdfs:label "MPEG-7 Spectral Centroid",
+ "MPEG7SpectralCentroid" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:Mean ;
+ af:computational_complexity af:LowComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:Global ;
+ rdfs:comment "MPEG-7 Spectral Centroid feature" ;
+ rdfs:subClassOf af:FrequencyDomainPhysicalFeature ;
+ vs:term_status "testing" .
+
+af:MPEG7TemporalCentroid a owl:Class ;
+ rdfs:label "MPEG-7 Temporal Centroid",
+ "MPEG7TemporalCentroid" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:Mean,
+ af:Power,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:computedIn "MPEG-7" ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "MPEG-7 Temporal Centroid feature" ;
+ rdfs:subClassOf af:TemporalFeature ;
+ vs:term_status "testing" .
+
+af:Maximum a owl:Class ;
+ rdfs:label "Maximum" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:MelscaleFrequencyCepstralCoefficients a owl:Class ;
+ rdfs:label "Mel-scale Frequency Cepstral Coefficients",
+ "MelscaleFrequencyCepstralCoefficients" ;
+ af:abbreviation "MFCC" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteCosineTransform,
+ af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Mel-scale Frequency Cepstral Coefficients feature" ;
+ rdfs:subClassOf af:CepstralFeature ;
+ vs:term_status "testing" .
+
+af:Minimum a owl:Class ;
+ rdfs:label "Minimum" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:ModifiedGroupDelay a owl:Class ;
+ rdfs:label "Modified Group Delay",
+ "ModifiedGroupDelay" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:DiscreteCosineTransform,
+ af:DiscreteFourierTransform,
+ af:GroupDelayFunction,
+ af:LowpassFilter,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Modified Group Delay feature" ;
+ rdfs:subClassOf af:FrequencyDomainPhysicalFeature ;
+ vs:term_status "testing" .
+
+af:MultiresolutionEntropy a owl:Class ;
+ rdfs:label "Multi-resolution Entropy",
+ "MultiresolutionEntropy" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:DiscreteFourierTransform,
+ af:Entropy,
+ af:Normalization,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Multi-resolution Entropy feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:NoiseRobustAuditoryFeature a owl:Class ;
+ rdfs:label "Noise-Robust Auditory Feature",
+ "NoiseRobustAuditoryFeature" ;
+ af:application_domain af:EnvironmentalSoundRecognition ;
+ af:computation af:BandpassFilterBank,
+ af:DerivationDifference,
+ af:DiscreteCosineTransform,
+ af:Logarithm,
+ af:LowpassFilter,
+ af:NonLinearWeightingFunction,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions 256 ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Noise-Robust Auditory Feature feature" ;
+ rdfs:subClassOf af:CepstralFeature ;
+ vs:term_status "testing" .
+
+af:PerceptualLinearPrediction a owl:Class ;
+ rdfs:label "Perceptual Linear Prediction",
+ "PerceptualLinearPrediction" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:AutoregressionLinearPredictionAnalysis,
+ af:CepstralRecursionFormula,
+ af:DiscreteCosineTransform,
+ af:DiscreteFourierTransform,
+ af:NonLinearWeightingFunction,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Perceptual Linear Prediction feature" ;
+ rdfs:subClassOf af:CepstralFeature ;
+ vs:term_status "testing" .
+
+af:PhaseSpaceFeatures a owl:Class ;
+ rdfs:label "Phase Space Features",
+ "PhaseSpaceFeatures" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:PhaseSpaceEmbedding,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Phase Space Features feature" ;
+ rdfs:subClassOf af:PhasespaceFeature ;
+ vs:term_status "testing" .
+
+af:Pitch a owl:Class ;
+ rdfs:label "Pitch" ;
+ af:application_domain af:Several ;
+ af:computation af:Autocorrelation,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Pitch feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:PitchHistogram a owl:Class ;
+ rdfs:label "Pitch Histogram",
+ "PitchHistogram" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:Autocorrelation,
+ af:RootMeanSquare,
+ af:Spectralbinning,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Pitch Histogram feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:PitchProfile a owl:Class ;
+ rdfs:label "Pitch Profile",
+ "PitchProfile" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:ConstantQTransform,
+ af:RootMeanSquare,
+ af:Spectralbinning,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions 12 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Pitch Profile feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:PitchSynchronousZCPA a owl:Class ;
+ rdfs:label "Pitch Synchronous ZCPA",
+ "PitchSynchronousZCPA" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:Autocorrelation,
+ af:BandpassFilterBank,
+ af:Logarithm,
+ af:RootMeanSquare,
+ af:Spectralbinning,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Pitch Synchronous ZCPA feature" ;
+ rdfs:subClassOf af:TemporalFeature ;
+ vs:term_status "testing" .
+
+af:PsychoacousticalPitch a owl:Class ;
+ rdfs:label "Psychoacoustical Pitch",
+ "PsychoacousticalPitch" ;
+ af:application_domain af:Several ;
+ af:computation af:Autocorrelation,
+ af:BandpassFilterBank,
+ af:NonLinearWeightingFunction,
+ af:RootMeanSquare ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Psychoacoustical Pitch feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:PulseMetric a owl:Class ;
+ rdfs:label "Pulse Metric",
+ "PulseMetric" ;
+ af:application_domain af:AudioSegmentation ;
+ af:computation af:Autocorrelation,
+ af:BandpassFilterBank,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Pulse Metric feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:RatescalefrequencyFeatures a owl:Class ;
+ rdfs:label "Rate-scale-frequency Features",
+ "RatescalefrequencyFeatures" ;
+ af:application_domain af:EnvironmentalSoundRecognition ;
+ af:computation af:BandpassFilterBank,
+ af:DerivationDifference,
+ af:DiscreteWaveletTransform,
+ af:LowpassFilter,
+ af:NonLinearWeightingFunction,
+ af:PrincipalComponentAnalysis,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions 256 ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Rate-scale-frequency Features feature" ;
+ rdfs:subClassOf af:EigendomainFeature ;
+ vs:term_status "testing" .
+
+af:RelativeSpectralPLP a owl:Class ;
+ rdfs:label "Relative Spectral PLP",
+ "RelativeSpectralPLP" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:AutoregressionLinearPredictionAnalysis,
+ af:BandpassFilterBank,
+ af:CepstralRecursionFormula,
+ af:DiscreteCosineTransform,
+ af:DiscreteFourierTransform,
+ af:ExponentialFunction,
+ af:Logarithm,
+ af:NonLinearWeightingFunction,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Relative Spectral PLP feature" ;
+ rdfs:subClassOf af:CepstralFeature ;
+ vs:term_status "testing" .
+
+af:RhythmPatterns a owl:Class ;
+ rdfs:label "Rhythm Patterns",
+ "RhythmPatterns" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:HarmonicPeakDetection,
+ af:Logarithm,
+ af:LowpassFilter,
+ af:NonLinearWeightingFunction,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions 80 ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Rhythm Patterns feature" ;
+ rdfs:subClassOf af:ModulationfrequencyFeature ;
+ vs:term_status "testing" .
+
+af:Sharpness a owl:Class ;
+ rdfs:label "Sharpness" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteFourierTransform,
+ af:Mean,
+ af:NonLinearWeightingFunction,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Sharpness feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:ShortTimeEnergy a owl:Class ;
+ rdfs:label "Short-Time Energy",
+ "ShortTimeEnergy" ;
+ af:application_domain af:Several ;
+ af:computation af:DeviationSumofDifferences,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Short-Time Energy feature" ;
+ rdfs:subClassOf af:TemporalFeature ;
+ vs:term_status "testing" .
+
+af:Sone a owl:Class ;
+ rdfs:label "Sone" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:LowpassFilter,
+ af:NonLinearWeightingFunction,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:HighComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Sone feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:SpectralCenter a owl:Class ;
+ rdfs:label "Spectral Center",
+ "SpectralCenter" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:EnergySpectralDensity,
+ af:HarmonicPeakDetection,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Spectral Center feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:SpectralCentroid a owl:Class ;
+ rdfs:label "Spectral Centroid",
+ "SpectralCentroid" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:Mean,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Spectral Centroid feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:SpectralCrest a owl:Class ;
+ rdfs:label "Spectral Crest",
+ "SpectralCrest" ;
+ af:application_domain af:Fingerprinting ;
+ af:computation af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:Mean,
+ af:Regression,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Spectral Crest feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:SpectralDispersion a owl:Class ;
+ rdfs:label "Spectral Dispersion",
+ "SpectralDispersion" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DiscreteFourierTransform,
+ af:EnergySpectralDensity,
+ af:HarmonicPeakDetection,
+ af:Median,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Spectral Dispersion feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:SpectralFlatness a owl:Class ;
+ rdfs:label "Spectral Flatness",
+ "SpectralFlatness" ;
+ af:application_domain af:Fingerprinting ;
+ af:computation af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:Mean,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Spectral Flatness feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:SpectralFlux a owl:Class ;
+ rdfs:label "Spectral Flux",
+ "SpectralFlux" ;
+ af:abbreviation "SF" ;
+ af:application_domain af:Several ;
+ af:computation af:DerivationDifference,
+ af:DiscreteFourierTransform,
+ af:RootMeanSquare,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Spectral Flux feature" ;
+ rdfs:subClassOf af:FrequencyDomainPhysicalFeature ;
+ vs:term_status "testing" .
+
+af:SpectralPeakStructure a owl:Class ;
+ rdfs:label "Spectral Peak Structure",
+ "SpectralPeakStructure" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DerivationDifference,
+ af:DiscreteFourierTransform,
+ af:Entropy,
+ af:LevelCrossingDetector,
+ af:Spectralbinning,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Spectral Peak Structure feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:SpectralPeaks a owl:Class ;
+ rdfs:label "Spectral Peaks",
+ "SpectralPeaks" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:DerivationDifference,
+ af:DiscreteFourierTransform,
+ af:SumWeightedSum,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:InterFrame ;
+ rdfs:comment "Spectral Peaks feature" ;
+ rdfs:subClassOf af:FrequencyDomainPhysicalFeature ;
+ vs:term_status "testing" .
+
+af:SpectralRolloff a owl:Class ;
+ rdfs:label "Spectral Rolloff",
+ "SpectralRolloff" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteFourierTransform,
+ af:PolynomialRootFinding,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Spectral Rolloff feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:SpectralSlope a owl:Class ;
+ rdfs:label "Spectral Slope",
+ "SpectralSlope" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteFourierTransform,
+ af:PeakDetection,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 4 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Spectral Slope feature" ;
+ rdfs:subClassOf af:FrequencyDomainPhysicalFeature ;
+ vs:term_status "testing" .
+
+af:SubbandEnergyRatio a owl:Class ;
+ rdfs:label "Subband Energy Ratio",
+ "SubbandEnergyRatio" ;
+ af:application_domain af:Several ;
+ af:computation af:DiscreteFourierTransform,
+ af:EnergySpectralDensity,
+ af:Normalization,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Subband Energy Ratio feature" ;
+ rdfs:subClassOf af:FrequencyDomainPhysicalFeature ;
+ vs:term_status "testing" .
+
+af:SubbandSpectralFlux a owl:Class ;
+ rdfs:label "Subband Spectral Flux",
+ "SubbandSpectralFlux" ;
+ af:application_domain af:EnvironmentalSoundRecognition ;
+ af:computation af:DerivationDifference,
+ af:DiscreteFourierTransform,
+ af:Logarithm,
+ af:Mean,
+ af:Normalization,
+ af:Regression,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 8 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PerceptualFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Subband Spectral Flux feature" ;
+ rdfs:subClassOf af:FrequencyDomainPerceptualFeature ;
+ vs:term_status "testing" .
+
+af:Volume a owl:Class ;
+ rdfs:label "Volume" ;
+ af:application_domain af:Several ;
+ af:computation af:Power,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Volume feature" ;
+ rdfs:subClassOf af:TemporalFeature ;
+ vs:term_status "testing" .
+
+af:ZeroCrossingPeakAmplitudes a owl:Class ;
+ rdfs:label "Zero Crossing Peak Amplitudes",
+ "ZeroCrossingPeakAmplitudes" ;
+ af:application_domain af:SpeechRecognition ;
+ af:computation af:BandpassFilterBank,
+ af:Logarithm,
+ af:RootMeanSquare,
+ af:Spectralbinning,
+ af:Windowing ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions af:ParametrizedDimensions ;
+ af:psychoacoustic_model true ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Zero Crossing Peak Amplitudes feature" ;
+ rdfs:subClassOf af:TemporalFeature ;
+ vs:term_status "testing" .
+
+af:ZeroCrossingRate a owl:Class ;
+ rdfs:label "Zero Crossing Rate",
+ "ZeroCrossingRate" ;
+ af:abbreviation "ZCR" ;
+ af:application_domain af:Several ;
+ af:computation af:Spectralbinning,
+ af:Windowing ;
+ af:computational_complexity af:LowComplexity ;
+ af:dimensions 1 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:IntraFrame ;
+ rdfs:comment "Zero Crossing Rate feature" ;
+ rdfs:subClassOf af:TemporalFeature ;
+ vs:term_status "testing" .
+
+af:application_domain a rdf:Property ;
+ rdfs:comment "application domain property" ;
+ rdfs:range af:ApplicationDomain ;
+ vs:term_status "testing" .
+
+af:computational_complexity a rdf:Property ;
+ rdfs:range af:ComputationalComplexity ;
+ vs:term_status "testing" .
+
+af:dimensions a rdf:Property ;
+ rdfs:range af:ParametrizedDimensions,
+ xsd:Integer .
+
+af:psychoacoustic_model a rdf:Property ;
+ rdfs:range xsd:Boolean ;
+ vs:term_status "testing" .
+
+af:semantic_interpretation a rdf:Property ;
+ vs:term_status "testing" .
+
+af:temporal_scale a rdf:Property ;
+ rdfs:range af:TemporalScale .
+
+vs:term_status a owl:AnnotationProperty .
+
+af:AdaptiveTimeFrequencyTransform a owl:Class ;
+ rdfs:label "Adaptive Time Frequency Transform",
+ "Adaptive Time-Frequency Transform",
+ "AdaptiveTimeFrequencyTransform" ;
+ af:application_domain af:MusicInformationRetrieval ;
+ af:computation af:AdaptiveTimeFrequencyTransform,
+ af:Spectralbinning ;
+ af:computational_complexity af:MediumComplexity ;
+ af:dimensions 42 ;
+ af:psychoacoustic_model false ;
+ af:semantic_interpretation af:PhysicalFeature ;
+ af:temporal_scale af:Global ;
+ rdfs:comment "Adaptive Time-Frequency Transform feature" ;
+ rdfs:subClassOf af:FrequencyDomainPhysicalFeature,
+ af:Transformation ;
+ vs:term_status "testing" .
+
+af:ConstantQTransform a owl:Class ;
+ rdfs:label "Constant Q Transform" ;
+ rdfs:subClassOf af:Transformation .
+
+af:DeviationSumofDifferences a owl:Class ;
+ rdfs:label "Deviation, Sum of Differences" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:GroupDelayFunction a owl:Class ;
+ rdfs:label "Group Delay Function" ;
+ rdfs:subClassOf af:Filter .
+
+af:Histogram a owl:Class ;
+ rdfs:label "Histogram" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:IndependentComponentAnalysis a owl:Class ;
+ rdfs:label "Independent Component Analysis" ;
+ rdfs:subClassOf af:Transformation .
+
+af:ModulatedComplexLappedTransform a owl:Class ;
+ rdfs:label "Modulated Complex Lapped Transform" ;
+ rdfs:subClassOf af:Transformation .
+
+af:PeakDetection a owl:Class ;
+ rdfs:label "Peak Detection" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:Percentile a owl:Class ;
+ rdfs:label "Percentile" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:PhaseSpaceEmbedding a owl:Class ;
+ rdfs:label "Phase Space Embedding" ;
+ rdfs:subClassOf af:Transformation .
+
+af:PhasespaceFeature a owl:Class ;
+ rdfs:subClassOf af:Feature .
+
+af:PolynomialRootFinding a owl:Class ;
+ rdfs:label "Polynomial Root Finding" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:Signal a owl:Class .
+
+af:SingularValueDecomposition a owl:Class ;
+ rdfs:label "Singular Value Decomposition" ;
+ rdfs:subClassOf af:Transformation .
+
+af:CombFilterBank a owl:Class ;
+ rdfs:label "Comb Filter (Bank)" ;
+ rdfs:subClassOf af:Filter .
+
+af:CrossCorrelation a owl:Class ;
+ rdfs:label "Cross-Correlation" ;
+ rdfs:subClassOf af:Transformation .
+
+af:ExponentialFunction a owl:Class ;
+ rdfs:label "Exponential Function" ;
+ rdfs:subClassOf af:Filter .
+
+af:FrequencyFeature a owl:Class ;
+ rdfs:subClassOf af:Feature .
+
+af:PrincipalComponentAnalysis a owl:Class ;
+ rdfs:label "Principal Component Analysis" ;
+ rdfs:subClassOf af:Transformation .
+
+af:CepstralRecursionFormula a owl:Class ;
+ rdfs:label "Cepstral Recursion Formula" ;
+ rdfs:subClassOf af:Filter .
+
+af:EigendomainFeature a owl:Class ;
+ rdfs:subClassOf af:Feature .
+
+af:Entropy a owl:Class ;
+ rdfs:label "Entropy" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:Fingerprinting a owl:Class ;
+ rdfs:subClassOf af:ApplicationDomain .
+
+af:Global a owl:Class ;
+ rdfs:subClassOf af:TemporalScale .
+
+af:HarmonicPeakDetection a owl:Class ;
+ rdfs:label "Harmonic Peak Detection" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:MathematicalOperation a owl:Class .
+
+af:Power a owl:Class ;
+ rdfs:label "Power" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:ComputationalComplexity a owl:Class .
+
+af:TemporalScale a owl:Class .
+
+af:AudioSegmentation a owl:Class ;
+ rdfs:subClassOf af:ApplicationDomain .
+
+af:DiscreteWaveletTransform a owl:Class ;
+ rdfs:label "Discrete Wavelet Transform" ;
+ rdfs:subClassOf af:Transformation .
+
+af:AutoregressionLinearPredictionAnalysis a owl:Class ;
+ rdfs:label "Autoregression (Linear Prediction Analysis)" ;
+ rdfs:subClassOf af:Filter .
+
+af:EnergySpectralDensity a owl:Class ;
+ rdfs:label "Energy Spectral Density" ;
+ rdfs:subClassOf af:Filter .
+
+af:EnvironmentalSoundRecognition a owl:Class ;
+ rdfs:subClassOf af:ApplicationDomain .
+
+af:Normalization a owl:Class ;
+ rdfs:label "Normalization" ;
+ rdfs:subClassOf af:Filter .
+
+af:ApplicationDomain a owl:Class .
+
+af:CepstralFeature a owl:Class ;
+ rdfs:subClassOf af:Feature .
+
+af:Median a owl:Class ;
+ rdfs:label "Median" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:DiscreteCosineTransform a owl:Class ;
+ rdfs:label "Discrete Cosine Transform" ;
+ rdfs:subClassOf af:Transformation .
+
+af:Feature a owl:Class ;
+ owl:subClassOf af:Signal .
+
+af:DerivationDifference a owl:Class ;
+ rdfs:label "Derivation, Difference" ;
+ rdfs:subClassOf af:Filter .
+
+af:LevelCrossingDetector a owl:Class ;
+ rdfs:label "Level Crossing Detector" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:NonLinearWeightingFunction a owl:Class ;
+ rdfs:label "(Non-) Linear Weighting Function" ;
+ rdfs:subClassOf af:Filter .
+
+af:FrequencyDomainPhysicalFeature a owl:Class ;
+ rdfs:subClassOf af:FrequencyFeature ;
+ owl:equivalentClass af:PhysicalFeature .
+
+af:TemporalFeature a owl:Class ;
+ rdfs:subClassOf af:Feature .
+
+af:Mean a owl:Class ;
+ rdfs:label "Mean" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:SpeechRecognition a owl:Class ;
+ rdfs:subClassOf af:ApplicationDomain .
+
+af:SumWeightedSum a owl:Class ;
+ rdfs:label "Sum, Weighted Sum" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:LowpassFilter a owl:Class ;
+ rdfs:label "Low-pass Filter" ;
+ rdfs:subClassOf af:Filter .
+
+af:ModulationfrequencyFeature a owl:Class ;
+ rdfs:subClassOf af:Feature .
+
+af:Spectralbinning a owl:Class ;
+ rdfs:label "Spectral binning" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:Filter a owl:Class ;
+ rdfs:subClassOf af:MathematicalOperation .
+
+af:Transformation a owl:Class ;
+ rdfs:subClassOf af:MathematicalOperation .
+
+af:BandpassFilterBank a owl:Class ;
+ rdfs:label "Band-pass Filter (Bank)",
+ "Band-pass Filter Bank" ;
+ rdfs:subClassOf af:Filter,
+ af:Transformation .
+
+af:Autocorrelation a owl:Class ;
+ rdfs:label "Autocorrelation" ;
+ rdfs:subClassOf af:Transformation .
+
+af:InterFrame a owl:Class ;
+ rdfs:subClassOf af:TemporalScale .
+
+af:Aggregation a owl:Class ;
+ rdfs:subClassOf af:MathematicalOperation .
+
+af:HighComplexity a owl:Class ;
+ rdfs:subClassOf af:ComputationalComplexity .
+
+af:Regression a owl:Class ;
+ rdfs:label "Regression" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:Several a owl:Class ;
+ rdfs:subClassOf af:ApplicationDomain .
+
+af:RootMeanSquare a owl:Class ;
+ rdfs:label "Root Mean Square" ;
+ rdfs:subClassOf af:Aggregation .
+
+af:LowComplexity a owl:Class ;
+ rdfs:subClassOf af:ComputationalComplexity .
+
+af:Logarithm a owl:Class ;
+ rdfs:label "Logarithm" ;
+ rdfs:subClassOf af:Filter .
+
+af:ParametrizedDimensions a owl:Class .
+
+af:MusicInformationRetrieval a owl:Class ;
+ rdfs:subClassOf af:ApplicationDomain .
+
+af:FrequencyDomainPerceptualFeature a owl:Class ;
+ rdfs:subClassOf af:FrequencyFeature ;
+ owl:equivalentClass af:PerceptualFeature .
+
+af:MediumComplexity a owl:Class ;
+ rdfs:subClassOf af:ComputationalComplexity .
+
+af:PhysicalFeature a owl:Class ;
+ rdfs:subClassOf af:Feature .
+
+af:DiscreteFourierTransform a owl:Class ;
+ rdfs:label "Discrete Fourier Transform" ;
+ rdfs:subClassOf af:Transformation .
+
+af:PerceptualFeature a owl:Class ;
+ rdfs:subClassOf af:Feature .
+
+af:IntraFrame a owl:Class ;
+ rdfs:subClassOf af:TemporalScale .
+
+af:Windowing a owl:Class ;
+ rdfs:label "Windowing" ;
+ rdfs:subClassOf af:Filter .
+
diff -r 000000000000 -r 62d2c72e4223 baseOnto.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/baseOnto.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,1808 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ JointAcousticandModuluationFrequency
+ Joint Acoustic and Moduluation Frequency
+
+ Joint Acoustic and Moduluation Frequency feature
+ testing
+
+
+
+
+
+
+
+ Singular Value Decomposition
+
+
+
+
+
+
+
+
+ Derivation, Difference
+
+
+
+
+ testing
+
+
+
+
+ 256
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ Rate-scale-frequency Features
+ RatescalefrequencyFeatures
+
+ Rate-scale-frequency Features feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+
+ true
+
+
+ MPEG-7 Audio Spectrum Centroid
+ MPEG7AudioSpectrumCentroid
+
+ MPEG-7 Audio Spectrum Centroid feature
+ MPEG-7
+ testing
+
+
+
+ 2
+
+
+
+
+
+ false
+
+
+ MPEG7AudioHarmonicity
+ MPEG-7 Audio Harmonicity
+
+ MPEG-7 Audio Harmonicity feature
+ MPEG-7
+ testing
+
+
+
+
+
+
+
+ 28
+
+
+
+
+
+ false
+
+
+ Daubechies Wavelet Coefficient Histogram
+ DaubechiesWaveletCoefficientHistogram
+
+ Daubechies Wavelet Coefficient Histogram feature
+ testing
+
+
+ Percentile
+
+
+
+
+
+ 2
+
+
+
+
+
+ false
+
+ MPEG-7 Audio Waveform
+ MPEG7AudioWaveform
+
+ MPEG-7 Audio Waveform feature
+ MPEG-7
+ testing
+
+
+ testing
+
+
+
+
+
+ 1
+
+
+
+
+
+
+ false
+
+
+ Inharmonicity
+
+ Inharmonicity feature
+ testing
+
+
+
+ 42
+
+
+
+
+
+ false
+
+
+ Adaptive Time Frequency Transform
+ Adaptive Time-Frequency Transform
+ AdaptiveTimeFrequencyTransform
+
+ Adaptive Time-Frequency Transform feature
+ testing
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ Multi-resolution Entropy
+ MultiresolutionEntropy
+
+ Multi-resolution Entropy feature
+ testing
+
+
+
+
+
+
+
+
+ false
+
+
+ PhaseSpaceFeatures
+ Phase Space Features
+
+ Phase Space Features feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+
+
+ false
+
+
+ MPEG7HarmonicSpectralDeviation
+ MPEG-7 Harmonic Spectral Deviation
+
+ MPEG-7 Harmonic Spectral Deviation feature
+ MPEG-7
+ testing
+
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ Spectral Crest
+ SpectralCrest
+
+ Spectral Crest feature
+ testing
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ LPCC
+ Linear Prediction Cepstral Coefficients
+ LinearPredictionCepstralCoefficients
+
+ Linear Prediction Cepstral Coefficients feature
+ testing
+
+
+ Modulated Complex Lapped Transform
+
+
+
+
+
+
+
+
+
+ 1
+
+
+
+
+
+
+
+ false
+
+
+ Harmonic Concentration
+ HarmonicConcentration
+
+ Harmonic Concentration feature
+ testing
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ Harmonic Derivate
+ HarmonicDerivate
+
+ Harmonic Derivate feature
+ testing
+
+
+ Principal Component Analysis
+
+
+
+
+
+ 62
+
+
+
+
+
+
+ true
+
+
+ AuditoryFilterBankTemporalEnvelopes
+ Auditory Filter Bank Temporal Envelopes
+
+ Auditory Filter Bank Temporal Envelopes feature
+ testing
+
+
+ Mean
+
+
+
+
+ Root Mean Square
+
+
+
+
+ Autocorrelation
+
+
+
+
+ Maximum
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ LineSpectralFrequencies
+ Line Spectral Frequencies
+
+ Line Spectral Frequencies feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+
+ false
+
+
+ Spectral Centroid
+ SpectralCentroid
+
+ Spectral Centroid feature
+ testing
+
+
+ Discrete Wavelet Transform
+
+
+
+
+
+ 1
+
+
+
+
+
+
+ false
+
+
+ PulseMetric
+ Pulse Metric
+
+ Pulse Metric feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+ false
+
+
+ SF
+ SpectralFlux
+ Spectral Flux
+
+ Spectral Flux feature
+ testing
+
+
+ Harmonic Peak Detection
+
+
+
+
+
+ 12
+
+
+
+
+
+
+
+ false
+
+
+ ChromaCENSFeatures
+ Chroma CENS Features
+
+ Chroma CENS Features feature
+ testing
+
+
+ Regression
+
+
+
+
+
+
+
+
+
+
+ 1
+
+
+
+
+
+
+
+
+ false
+
+
+ Beat Tracker
+ BeatTracker
+
+ Beat Tracker feature
+ testing
+
+
+ Exponential Function
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ PsychoacousticalPitch
+ Psychoacoustical Pitch
+
+ Psychoacoustical Pitch feature
+ testing
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ DWPT-based Rhythm Feature
+ DWPTbasedRhythmFeature
+
+ DWPT-based Rhythm Feature feature
+ testing
+
+
+ Spectral binning
+
+
+
+
+
+ 1
+
+
+
+
+
+ false
+
+
+ HarmonicCoefficient
+ Harmonic Coefficient
+
+ Harmonic Coefficient feature
+ testing
+
+
+
+
+
+
+ 12
+
+
+
+
+
+
+
+ false
+
+
+ PitchProfile
+ Pitch Profile
+
+ Pitch Profile feature
+ testing
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ Pitch Histogram
+ PitchHistogram
+
+ Pitch Histogram feature
+ testing
+
+
+ Sum, Weighted Sum
+
+
+
+
+
+ 1
+
+
+
+
+
+ false
+
+
+ HarmonicProminence
+ Harmonic Prominence
+
+ Harmonic Prominence feature
+ testing
+
+
+ Cepstral Recursion Formula
+
+
+
+
+
+ 1
+
+
+
+
+ false
+
+
+ ShortTimeEnergy
+ Short-Time Energy
+
+ Short-Time Energy feature
+ testing
+
+
+ Independent Component Analysis
+
+
+
+
+
+ 1
+
+
+
+
+
+ false
+
+
+ Linear Prediction ZCR
+ LinearPredictionZCR
+
+ Linear Prediction ZCR feature
+ testing
+
+
+
+
+
+
+
+ 1
+
+
+
+
+ false
+
+
+ MPEG-7 Spectral Centroid
+ MPEG7SpectralCentroid
+
+ MPEG-7 Spectral Centroid feature
+ MPEG-7
+ testing
+
+
+
+
+
+
+
+
+
+
+
+ 64
+
+
+
+
+
+
+ false
+
+
+ Distortion Discriminant Analysis
+ DistortionDiscriminantAnalysis
+
+ Distortion Discriminant Analysis feature
+ testing
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ Perceptual Linear Prediction
+ PerceptualLinearPrediction
+
+ Perceptual Linear Prediction feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+ false
+
+
+ MPEG7LogAttackTime
+ MPEG-7 Log Attack Time
+
+ MPEG-7 Log Attack Time feature
+ MPEG-7
+ testing
+
+
+ This is a base ontology for the Audio Features engineering process collected from literature
+ Audio Features Base Ontology
+ Version 0.1
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ SpectralPeaks
+ Spectral Peaks
+
+ Spectral Peaks feature
+ testing
+
+
+
+
+
+
+ Phase Space Embedding
+
+
+
+
+
+ 2
+
+
+
+
+
+ false
+
+
+ MPEG-7 Audio Fundamental Frequency
+ MPEG7AudioFundamentalFrequency
+
+ MPEG-7 Audio Fundamental Frequency feature
+ MPEG-7
+ testing
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ Modified Group Delay
+ ModifiedGroupDelay
+
+ Modified Group Delay feature
+ testing
+
+
+ Low-pass Filter
+
+
+
+
+ Median
+
+
+
+
+
+ 6
+
+
+
+
+
+
+
+
+ false
+
+
+ BeatHistogram
+ Beat Histogram
+
+ Beat Histogram feature
+ testing
+
+
+
+
+
+
+ Polynomial Root Finding
+
+
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ SpectralFlatness
+ Spectral Flatness
+
+ Spectral Flatness feature
+ testing
+
+
+
+
+
+
+ Logarithm
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ Pitch Synchronous ZCPA
+ PitchSynchronousZCPA
+
+ Pitch Synchronous ZCPA feature
+ testing
+
+
+ Windowing
+
+
+
+
+ testing
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ MPEG7AudioSpectrumBasis
+ MPEG-7 Audio Spectrum Basis
+
+ MPEG-7 Audio Spectrum Basis feature
+ MPEG-7
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+
+ true
+
+
+ MPEG7AudioSpectrumSpread
+ MPEG-7 Audio Spectrum Spread
+
+ MPEG-7 Audio Spectrum Spread feature
+ MPEG-7
+ testing
+
+
+
+ 8
+
+
+
+
+
+
+
+
+
+ false
+
+
+ SubbandSpectralFlux
+ Subband Spectral Flux
+
+ Subband Spectral Flux feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+ false
+
+
+ Spectral Rolloff
+ SpectralRolloff
+
+ Spectral Rolloff feature
+ testing
+
+
+
+
+
+
+ 1
+
+
+
+
+
+
+ false
+
+
+ HarmonicEnergyEntropy
+ Harmonic Energy Entropy
+
+ Harmonic Energy Entropy feature
+ testing
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ SubbandEnergyRatio
+ Subband Energy Ratio
+
+ Subband Energy Ratio feature
+ testing
+
+
+
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ Autocorrelation MFCCs
+ AutocorrelationMFCCs
+
+ Autocorrelation MFCCs feature
+ testing
+
+
+
+ 80
+
+
+
+
+
+
+
+
+
+ true
+
+
+ Rhythm Patterns
+ RhythmPatterns
+
+ Rhythm Patterns feature
+ testing
+
+
+
+
+
+
+ Entropy
+
+
+
+
+
+ 1
+
+
+
+
+ false
+
+
+ ZCR
+ ZeroCrossingRate
+ Zero Crossing Rate
+
+ Zero Crossing Rate feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+
+
+ false
+
+
+ SpectralPeakStructure
+ Spectral Peak Structure
+
+ Spectral Peak Structure feature
+ testing
+
+
+
+
+
+
+ 1
+
+
+
+
+
+
+
+
+ true
+
+
+ Integral Loudness
+ IntegralLoudness
+
+ Integral Loudness feature
+ testing
+
+
+ Comb Filter (Bank)
+
+
+
+
+ testing
+
+ application domain property
+
+
+
+
+
+
+
+ Minimum
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ Cyclic Beat Spectrum
+ CyclicBeatSpectrum
+
+ Cyclic Beat Spectrum feature
+ testing
+
+
+ Band-pass Filter (Bank)
+ Band-pass Filter Bank
+
+
+
+
+
+
+ 1
+
+
+
+
+
+
+ false
+
+
+ SpectralCenter
+ Spectral Center
+
+ Spectral Center feature
+ testing
+
+
+
+
+
+
+ (Non-) Linear Weighting Function
+
+
+
+
+ Normalization
+
+
+
+
+
+
+
+
+ Constant Q Transform
+
+
+
+
+
+ 256
+
+
+
+
+
+
+
+
+
+ true
+
+
+ NoiseRobustAuditoryFeature
+ Noise-Robust Auditory Feature
+
+ Noise-Robust Auditory Feature feature
+ testing
+
+
+ Autoregression (Linear Prediction Analysis)
+
+
+
+
+
+ 1
+
+
+
+
+
+ false
+
+
+ MPEG-7 Temporal Centroid
+ MPEG7TemporalCentroid
+
+ MPEG-7 Temporal Centroid feature
+ MPEG-7
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+
+ false
+
+
+ Bandwidth
+
+ Bandwidth feature
+ testing
+
+
+
+ 9
+
+
+
+
+
+
+ false
+
+
+ AmplitudeDescriptor
+ Amplitude Descriptor
+
+ Amplitude Descriptor feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+
+ true
+
+
+ Sharpness
+
+ Sharpness feature
+ testing
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ Sone
+
+ Sone feature
+ testing
+
+
+
+
+
+
+
+ 1
+
+
+
+
+ false
+
+
+ Volume
+
+ Volume feature
+ testing
+
+
+
+
+
+
+ Power
+
+
+
+
+
+ 4
+
+
+
+
+
+ false
+
+
+ Spectral Slope
+ SpectralSlope
+
+ Spectral Slope feature
+ testing
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ BarkscaleFrequencyCepstralCoefficients
+ Bark-scale Frequency Cepstral Coefficients
+
+ Bark-scale Frequency Cepstral Coefficients feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+
+ false
+
+
+ Spectral Dispersion
+ SpectralDispersion
+
+ Spectral Dispersion feature
+ testing
+
+
+
+
+
+
+
+ 1
+
+
+
+
+
+
+ false
+
+
+ MPEG7HarmonicSpectralVariation
+ MPEG-7 Harmonic Spectral Variation
+
+ MPEG-7 Harmonic Spectral Variation feature
+ MPEG-7
+ testing
+
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ Zero Crossing Peak Amplitudes
+ ZeroCrossingPeakAmplitudes
+
+ Zero Crossing Peak Amplitudes feature
+ testing
+
+
+
+
+
+ Discrete Fourier Transform
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ Relative Spectral PLP
+ RelativeSpectralPLP
+
+ Relative Spectral PLP feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+
+
+
+ true
+
+
+ 4 Hz Modulation Energy
+ 4HzModulationEnergy
+
+ 4 Hz Modulation Energy feature
+ testing
+
+
+ Energy Spectral Density
+
+
+
+
+ Peak Detection
+
+
+
+
+
+ 1
+
+
+
+
+
+
+
+ false
+
+
+ 4 Hz Modulation Harmonic Coefficients
+ 4HzModulationHarmonicCoefficients
+
+ 4 Hz Modulation Harmonic Coefficients feature
+ testing
+
+
+
+
+
+
+ 1
+
+
+
+
+
+ false
+
+
+ Pitch
+
+ Pitch feature
+ testing
+
+
+ Discrete Cosine Transform
+
+
+
+
+ Histogram
+
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ LPC
+ LinearPredictiveCoding
+ Linear Predictive Coding
+
+ Linear Predictive Coding feature
+ testing
+
+
+
+ 4
+
+
+
+
+
+
+
+ false
+
+
+ BandPeriodicity
+ Band Periodicity
+
+ Band Periodicity feature
+ testing
+
+
+
+
+
+
+
+
+
+
+
+ true
+
+
+ MFCC
+ Mel-scale Frequency Cepstral Coefficients
+ MelscaleFrequencyCepstralCoefficients
+
+ Mel-scale Frequency Cepstral Coefficients feature
+ testing
+
+
+ Cross-Correlation
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ false
+
+
+ BeatSpectrum
+ Beat Spectrum
+
+ Beat Spectrum feature
+ testing
+
+
+ Deviation, Sum of Differences
+
+
+
+
+ Group Delay Function
+
+
+
+
+ Level Crossing Detector
+
+
+
+
+
+ 1
+
+
+
+
+
+
+ false
+
+
+ MPEG7HarmonicSpectralSpread
+ MPEG-7 Harmonic Spectral Spread
+
+ MPEG-7 Harmonic Spectral Spread feature
+ MPEG-7
+ testing
+
+
+
+ 12
+
+
+
+
+
+
+ false
+
+
+ Chromagram
+
+ Chromagram feature
+ testing
+
+
+
+ 1
+
+
+
+
+
+
+ false
+
+
+ MPEG-7 Harmonic Spectral Centroid
+ MPEG7HarmonicSpectralCentroid
+
+ MPEG-7 Harmonic Spectral Centroid feature
+ MPEG-7
+ testing
+
+
+
+
+
+
+
+
+
diff -r 000000000000 -r 62d2c72e4223 fca/fca.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/fca/fca.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,97 @@
+
+#formal concept analysis
+
+import rdflib
+from rdflib import plugin, OWL, URIRef
+from rdflib.graph import Graph
+from rdflib.namespace import Namespace
+
+plugin.register(
+ 'sparql', rdflib.query.Processor,
+ 'rdfextras.sparql.processor', 'Processor')
+plugin.register(
+ 'sparql', rdflib.query.Result,
+ 'rdfextras.sparql.query', 'SPARQLQueryResult')
+
+graph = Graph()
+graph.parse('/Users/alo/MusicOntology/features/featuresCatalogue.rdf')
+
+
+execfile('/Users/alo/MusicOntology/features/fca/writeHTML.py')
+
+# conceptual scaling of many-valued feature attributes: complexity - low, medium, high
+# must be transformed into one-valued context: complexity-low, complexity-medium, complexity-high
+atmatrix = []
+
+#which attributes/categories to include
+cat = ["appdomain", "complexity", "domain", "level", "temporalscale", "dimensions"]
+catdict = {}
+
+for name in cat:
+ catdict[name] = []
+
+atcols = []
+atrows = []
+
+#traverse all items of type OWL.Class and then for each class the attributes in the dictionary and enumerate all the possible values
+
+res = graph.query(
+ """
+ SELECT DISTINCT ?feature (COUNT(?tool) as ?tcount)
+ WHERE {
+ ?feature rdfs:subClassOf ?ob .
+ ?feature af:computedIn ?tool
+ }
+ GROUP BY ?feature
+ HAVING(COUNT(?tool)>1)
+ ORDER BY ?feature
+ """,
+ initNs=dict(
+ af=Namespace("http://sovarr.c4dm.eecs.qmul.ac.uk/features/"))
+)
+
+for ns, value in graph.namespaces():
+ if ns == 'local':
+ local = value
+
+
+for it in res:
+ atrows.append(it[0])
+ for su, pr, ob in graph.triples((URIRef(local+it[0]), None, None)):
+ col = pr.split('/')[-1]
+ if cat.count(col) != 0:
+ if catdict[col].count(ob) == 0:
+ atcols.append(col+"-"+ob)
+ catdict[col].append(ob)
+
+
+
+atrows.sort()
+atcols.sort()
+
+#construct the matrix
+for i in range(len(atrows)):
+ atrow = []
+ for j in range(len(atcols)):
+ atrow.append(0)
+ atmatrix.append(atrow)
+
+
+for ns, value in graph.namespaces():
+ if ns == 'local':
+ local = value
+
+index = 0
+for feature in atrows:
+ for s, p, o in graph.triples((URIRef(local+feature), None, None)):
+ col = p.split('/')[-1]
+ if cat.count(col) != 0:
+ atmatrix[index][atcols.index(col+"-"+o)] = 1
+ index += 1
+
+writeHTML('subset.html', atmatrix, atcols, atrows)
+writeWikiTable('subset.txt', atmatrix, atcols, atrows)
+
+writeCXT('subset.cxt', atmatrix, atcols, atrows)
+#writeFIMI('atmatrix.fimi', atmatrix, atcols, atrows)
+os.system("fcastone -bc "+path+name+".cxt "+path+name+".dot")
diff -r 000000000000 -r 62d2c72e4223 fca/fcaDotGen.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/fca/fcaDotGen.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,150 @@
+import rdflib, os
+from rdflib import plugin, OWL, URIRef, RDF, RDFS, Literal
+from rdflib.graph import Graph
+from rdflib.namespace import Namespace
+
+plugin.register(
+ 'sparql', rdflib.query.Processor,
+ 'rdfextras.sparql.processor', 'Processor')
+plugin.register(
+ 'sparql', rdflib.query.Result,
+ 'rdfextras.sparql.query', 'SPARQLQueryResult')
+
+afuri = "http://sovarr.c4dm.eecs.qmul.ac.uk/features/"
+cataloguePath = '/Users/alo/MusicOntology/features/af-catalogue.rdf'
+
+graph = Graph()
+graph.parse(cataloguePath)
+
+execfile('/Users/alo/MusicOntology/features/fca/writeHTML.py')
+
+def getFeaturesByTool( name ):
+ qry = 'SELECT DISTINCT ?feature WHERE { ?x af:computedIn "' + name + '" . ?x af:feature ?feature} ORDER BY ?feature'
+
+ return graph.query(qry,
+ initNs=dict(
+ af=Namespace(afuri))
+ )
+
+def getBaseFeatures():
+ features = []
+ ns = URIRef(u'http://sovarr.c4dm.eecs.qmul.ac.uk/features/computedIn')
+ for su in graph.subjects(RDF.type, OWL.Class):
+ count = sum(1 for _ in graph.objects(su,ns))
+ if count > 1:
+ features.append(su.split('/')[-1])
+
+ return features.sort()
+
+def getTools():
+ return graph.query(
+ """SELECT DISTINCT ?tool
+ WHERE {
+ ?x local:computedIn ?tool .
+ ?x local:feature ?feature
+ }
+ ORDER BY ?tool""",
+ initNs=dict(
+ af=Namespace(afuri))
+ )
+
+def constructMatrix( name, path ):
+ rows = []
+ columns = []
+ matrix = []
+
+ cat = ["appdomain", "complexity", "domain", "level", "temporalscale", "dimensions"]
+ catdict = {}
+
+ for nm in cat:
+ catdict[nm] = []
+
+ for ns, value in graph.namespaces():
+ if ns == 'local':
+ local = value
+
+ for it in getFeaturesByTool(name):
+ rows.append(it[0])
+ for su, pr, ob in graph.triples((URIRef(local+it[0]), None, None)):
+ col = pr.split('/')[-1]
+ if cat.count(col) != 0:
+ if catdict[col].count(ob) == 0:
+ columns.append(col+"-"+ob)
+ catdict[col].append(ob)
+
+ rows.sort()
+ columns.sort()
+
+ for i in range(len(rows)):
+ row = []
+ for j in range(len(columns)):
+ row.append(0)
+ matrix.append(row)
+
+ index = 0
+ for feature in rows:
+ for s, p, o in graph.triples((URIRef(local+feature), None, None)):
+ col = p.split('/')[-1]
+ if cat.count(col) != 0:
+ matrix[index][columns.index(col+"-"+o)] = 1
+
+ index += 1
+
+ writeCXT(path+name+'.cxt', matrix, columns, rows)
+ print ("wrote cxt data to "+path+name+".cxt")
+ name = name.replace(' ', '\ ')
+ os.system("fcastone -bc "+path+name+".cxt "+path+name+".dot")
+
+def constructBaseMatrix( name, path ):
+ rows = []
+ columns = []
+ matrix = []
+
+ cat = ["domain", "level", "temporalscale", "dimensions", "output", "tag"]
+ catdict = {}
+
+ for nm in cat:
+ catdict[nm] = []
+
+ for ns, value in graph.namespaces():
+ if ns == 'af':
+ local = value
+
+ features = []
+ ns = URIRef(u'http://sovarr.c4dm.eecs.qmul.ac.uk/features/computedIn')
+ for su in graph.subjects(RDF.type, OWL.Class):
+ count = sum(1 for _ in graph.objects(su,ns))
+ if count > 1:
+ features.append(su.split('/')[-1])
+
+ for it in features:
+ rows.append(it)
+ for su, pr, ob in graph.triples((URIRef(local+it), None, None)):
+ col = pr.split('/')[-1]
+ if cat.count(col) != 0:
+ if catdict[col].count(ob) == 0:
+ columns.append(ob.replace(' ', '-')+"-"+col.replace(' ', '-'))
+ catdict[col].append(ob)
+
+ rows.sort()
+ columns.sort()
+
+ for i in range(len(rows)):
+ row = []
+ for j in range(len(columns)):
+ row.append(0)
+ matrix.append(row)
+
+ index = 0
+ for feature in rows:
+ for s, p, o in graph.triples((URIRef(local+feature), None, None)):
+ col = p.split('/')[-1]
+ if cat.count(col) != 0:
+ matrix[index][columns.index(o.replace(' ', '-')+"-"+col.replace(' ', '-'))] = 1
+
+ index += 1
+
+ writeCXT(path+name+'.cxt', matrix, columns, rows)
+ print ("wrote cxt data to "+path+name+".cxt")
+ name = name.replace(' ', '\ ')
+ os.system("fcastone -bc "+path+name+".cxt "+path+name+".dot")
diff -r 000000000000 -r 62d2c72e4223 fca/featureCompareMatrices.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/fca/featureCompareMatrices.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,111 @@
+#formal concept analysis
+
+import rdflib
+from rdflib import plugin, OWL, URIRef
+from rdflib.graph import Graph
+from rdflib.namespace import Namespace
+
+execfile('/Users/alo/MusicOntology/features/fca/writeHTML.py')
+
+plugin.register(
+ 'sparql', rdflib.query.Processor,
+ 'rdfextras.sparql.processor', 'Processor')
+plugin.register(
+ 'sparql', rdflib.query.Result,
+ 'rdfextras.sparql.query', 'SPARQLQueryResult')
+
+graph = Graph()
+graph.parse('/Users/alo/MusicOntology/features/featuresCatalogue.rdf')
+
+tools = []
+
+res = graph.query(
+ """SELECT DISTINCT ?tool
+ WHERE {
+ ?x local:computedIn ?tool .
+ ?x local:feature ?feature
+ }
+ ORDER BY ?tool""",
+ initNs=dict(
+ local=Namespace("http://sovarr.c4dm.eecs.qmul.ac.uk/features/"))
+)
+
+for it in res:
+ tools.append(it[0])
+
+tools.sort()
+
+features = []
+
+for s, p, o in graph.triples((None, None, OWL.Class)):
+ features.append(s.split('/')[-1])
+
+features.sort()
+
+for ns, value in graph.namespaces():
+ if ns == 'local':
+ local = value
+
+similarity = {}
+
+for feature in features:
+ mtrx = []
+ for i in range(len(tools)):
+ row = []
+ for j in range(len(tools)):
+ row.append(0)
+ mtrx.append(row)
+ similarity[feature] = mtrx
+ for s, p, o in graph.triples((URIRef(local+feature), URIRef(local+'computedIn'), None)):
+ if tools.count(o) != 0:
+ similarity[feature][tools.index(o)][tools.index(o)] = 1
+
+
+html = ''
+for feature in features:
+ count = 0
+ for i in range(len(similarity[feature])):
+ count += similarity[feature][i].count(1)
+ if count > 1:
+ html += ''
+ html += feature + '
'
+ html += writeHTML('', similarity[feature], tools, tools)
+ html += '
'
+
+path = 'similarityMatrices.html'
+file = open(path, 'w')
+file.write(html)
+file.close()
+
+
+wiki = ''
+for feature in features:
+ count = 0
+ for i in range(len(similarity[feature])):
+ count += similarity[feature][i].count(1)
+ if count > 1:
+ wiki += '\n'
+ wiki += '====' + feature + '====\n'
+ wiki += writeWikiTable('', similarity[feature], tools, tools)
+ wiki += '
\n'
+
+path = 'similarityMatricesWiki.txt'
+file = open(path, 'w')
+file.write(wiki)
+file.close()
+
+latex = ''
+for feature in features:
+ count = 0
+ for i in range(len(similarity[feature])):
+ count += similarity[feature][i].count(1)
+ if count > 1:
+ latex += '\n'
+ latex += '{\large \\bfseries ' + feature + '}\n'
+ latex += writeLatexTable('', similarity[feature], tools, tools)
+ latex += '\n'
+
+path = 'similarityMatricesLatex.txt'
+file = open(path, 'w')
+file.write(latex)
+file.close()
diff -r 000000000000 -r 62d2c72e4223 fca/featureToolMatrix.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/fca/featureToolMatrix.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,89 @@
+#formal concept analysis
+
+import rdflib
+from rdflib import plugin, OWL
+from rdflib.graph import Graph
+from rdflib.namespace import Namespace
+
+execfile('/Users/alo/MusicOntology/features/fca/writeHTML.py')
+
+plugin.register(
+ 'sparql', rdflib.query.Processor,
+ 'rdfextras.sparql.processor', 'Processor')
+plugin.register(
+ 'sparql', rdflib.query.Result,
+ 'rdfextras.sparql.query', 'SPARQLQueryResult')
+
+graph = Graph()
+graph.parse('/Users/alo/MusicOntology/features/featuresCatalogue.rdf')
+
+res = graph.query(
+ """SELECT DISTINCT ?tool
+ WHERE {
+ ?x local:computedIn ?tool .
+ ?x local:feature ?feature
+ }
+ ORDER BY ?tool""",
+ initNs=dict(
+ local=Namespace("http://sovarr.c4dm.eecs.qmul.ac.uk/features/"))
+)
+
+cols = []
+
+for it in res:
+ cols.append(it[0])
+
+res = graph.query(
+ """SELECT DISTINCT ?feature
+ WHERE {
+ ?x local:computedIn ?tool .
+ ?x local:feature ?feature
+ }
+ ORDER BY ?feature""",
+ initNs=dict(
+ local=Namespace("http://sovarr.c4dm.eecs.qmul.ac.uk/features/"))
+)
+
+rows = []
+
+for it in res:
+ rows.append(it[0])
+
+colmap = {}
+
+for i in range(len(cols)):
+ it = cols[i]
+ colmap[it] = i
+
+rowmap = {}
+
+for i in range(len(rows)):
+ it = rows[i]
+ rowmap[it] = i
+
+res = graph.query(
+ """SELECT DISTINCT ?feature ?tool
+ WHERE {
+ ?x local:computedIn ?tool .
+ ?x local:feature ?feature
+ }
+ ORDER BY ?feature""",
+ initNs=dict(
+ local=Namespace("http://sovarr.c4dm.eecs.qmul.ac.uk/features/")))
+
+afmatrix = []
+
+for i in range(len(rows)):
+ row = []
+ for j in range(len(cols)):
+ row.append(0)
+ afmatrix.append(row)
+
+for it in res:
+ afmatrix[rowmap[it[0]]][colmap[it[1]]] = 1
+
+
+#writeHTML('afmatrix.html', afmatrix, cols, rows )
+#writeWikiTable('featureToolWiki.txt', afmatrix, cols, rows )
+writeLatexTable('featureToolLatex.txt', afmatrix, cols, rows)
+
diff -r 000000000000 -r 62d2c72e4223 fca/formalConceptAnalysis.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/fca/formalConceptAnalysis.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,76 @@
+#formal concept analysis
+
+import rdflib
+from rdflib import plugin, OWL, URIRef
+from rdflib.graph import Graph
+from rdflib.namespace import Namespace
+
+execfile('/Users/alo/MusicOntology/features/fca/writeHTML.py')
+
+plugin.register(
+ 'sparql', rdflib.query.Processor,
+ 'rdfextras.sparql.processor', 'Processor')
+plugin.register(
+ 'sparql', rdflib.query.Result,
+ 'rdfextras.sparql.query', 'SPARQLQueryResult')
+
+graph = Graph()
+graph.parse('/Users/alo/MusicOntology/features/featuresCatalogue.rdf')
+
+# conceptual scaling of many-valued feature attributes: complexity - low, medium, high
+# must be transformed into one-valued context: complexity-low, complexity-medium, complexity-high
+atmatrix = []
+
+#which attributes/categories to include
+cat = ["appdomain", "complexity", "computation", "dimensions", "domain", "level", "temporalscale", "computedIn", "tag"]
+catdict = {}
+
+for name in cat:
+ catdict[name] = []
+
+atcols = []
+atrows = []
+
+#traverse all items of type OWL.Class and then for each class the attributes in the dictionary and enumerate all the possible values
+for s, p, o in graph.triples((None, None, OWL.Class)):
+ row = s.split('/')[-1]
+ if atrows.count(row) == 0:
+ atrows.append(row)
+ for su, pr, ob in graph.triples((s, None, None)):
+ col = pr.split('/')[-1]
+ if cat.count(col) != 0:
+ if catdict[col].count(ob) == 0:
+ atcols.append(col+"-"+ob)
+ catdict[col].append(ob)
+
+
+atrows.sort()
+atcols.sort()
+
+#construct the matrix
+for i in range(len(atrows)):
+ atrow = []
+ for j in range(len(atcols)):
+ atrow.append(0)
+ atmatrix.append(atrow)
+
+
+for ns, value in graph.namespaces():
+ if ns == 'local':
+ local = value
+
+index = 0
+for feature in atrows:
+ for s, p, o in graph.triples((URIRef(local+feature), None, None)):
+ col = p.split('/')[-1]
+ if cat.count(col) != 0:
+ atmatrix[index][atcols.index(col+"-"+o)] = 1
+ index += 1
+
+#writeHTML('atmatrix.html', atmatrix, atcols, atrows)
+#writeWikiTable('fcamatrixWiki.txt', atmatrix, atcols, atrows)
+
+#writeCXT('atmatrix.cxt', atmatrix, atcols, atrows)
+writeFIMI('atmatrix.fimi', atmatrix, atcols, atrows)
+
+
diff -r 000000000000 -r 62d2c72e4223 fca/run.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/fca/run.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,9 @@
+import os, fnmatch
+
+basedir = '/Users/alo/MusicOntology/features/'
+rdfdir = basedir + 'rdf/'
+fcadir = basedir + 'fcadata/'
+
+for name in os.listdir(rdfdir):
+ if fnmatch.fnmatch(name, '*.rdf'):
+ constructMatrix( name.replace('af-', '').replace('.rdf', ''), fcadir )
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 fca/writeFCA.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/fca/writeFCA.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,25 @@
+def writeCTX( path, matrix, cols, rows ):
+ ctx = "B\n\n" + len(rows) + "\n" + len(cols) + "\n\n"
+
+ for it in columns:
+ ctx += it + "\n"
+
+ for it in columns:
+ ctx += it + "\n"
+
+ ctx += "\n"
+
+ for i in range(len(rows)):
+ for j in range(len(columns)):
+ if matrix[i][j] == 1:
+ ctx += "X"
+ else:
+ html += "."
+ html += "\n"
+
+ if path != '':
+ file = open(path, 'w')
+ file.write(ctx)
+ file.close()
+
+ return ctx
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 fca/writeHTML.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/fca/writeHTML.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,131 @@
+def writeHTML(path, matrix, columns, rows):
+ html = " | "
+
+ for it in columns:
+ html += "" + it + " | "
+
+ html += "
|---|
"
+
+ for i in range(len(rows)):
+ html += "| " + rows[i] + " | "
+ for j in range(len(columns)):
+ if matrix[i][j] == 1:
+ html += "x | "
+ else:
+ html += " | "
+ html += "
"
+
+ html += "
"
+
+ if path != '':
+ file = open(path, 'w')
+ file.write(html)
+ file.close()
+
+ return html
+
+
+def writeWikiTable(path, matrix, columns, rows):
+ wiki = "{| class='wikitable' \n"
+
+ wiki += ("! align='left'| \n")
+
+ for it in columns:
+ wiki += ("! " + it + "\n")
+
+ for i in range(len(rows)):
+ wiki += "|-\n"
+ wiki += "| align='left'| " + rows[i] + "\n"
+ for j in range(len(columns)):
+ if matrix[i][j] == 1:
+ wiki += "| align='center'| x\n"
+ else:
+ wiki += "| \n"
+
+ wiki += "|}\n"
+
+ if path != '':
+ file = open(path, 'w')
+ file.write(wiki)
+ file.close()
+
+ return wiki
+
+
+def writeLatexTable(path, matrix, columns, rows):
+ latex = "\\begin{center} \n\\begin{tabular}{ | l |"
+
+ for it in columns:
+ latex += (" l |")
+
+ latex += "}\n\hline\n & "
+
+ for i in range(len(columns)):
+ latex += columns[i]
+ if i < len(columns)-1:
+ latex += " & "
+
+ latex += " \\\ \hline\n"
+
+ for i in range(len(rows)):
+ latex += rows[i].replace("_", "") + " & "
+ for j in range(len(columns)):
+ if matrix[i][j] == 1:
+ latex += "x"
+ else:
+ latex += " "
+ if j < len(columns)-1:
+ latex += " & "
+
+ latex += " \\\ \hline\n"
+
+ latex += "\end{tabular}\n\end{center}"
+
+ if path != '':
+ file = open(path, 'w')
+ file.write(latex)
+ file.close()
+
+ return latex
+
+
+def writeCXT( path, matrix, cols, rows ):
+ cxt = "B\n\n" + str(len(rows)) + "\n" + str(len(cols)) + "\n\n"
+
+ for it in rows:
+ cxt += it + "\n"
+
+ for it in cols:
+ cxt += it + "\n"
+
+ for i in range(len(rows)):
+ for j in range(len(cols)):
+ if matrix[i][j] == 1:
+ cxt += "X"
+ else:
+ cxt += "."
+ cxt += "\n"
+
+ if path != '':
+ file = open(path, 'w')
+ file.write(cxt)
+ file.close()
+
+ return cxt
+
+def writeFIMI( path, matrix, cols, rows ):
+
+ fimi = ""
+
+ for i in range(len(rows)):
+ for j in range(len(cols)):
+ if matrix[i][j] == 1:
+ fimi += str(j)+" "
+ fimi += "\n"
+
+ if path != '':
+ file = open(path, 'w')
+ file.write(fimi)
+ file.close()
+
+ return fimi
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdf/af-CLAM.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-CLAM.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,113 @@
+
+
+
+
+ the mean value of the absolute value of the audio samples amplitude
+ Audio
+
+
+
+ the variance of audio samples amplitude
+ Audio
+
+
+
+ time where signal energy is "concentrated"
+ Audio
+
+
+
+ the base 10 logarithm of the rise time
+ Audio
+
+
+
+ the squared sum of audio samples amplitudes
+ Audio
+
+
+
+ a measure of the number of time the signal value cross the zero axe, averaged over the whole signal
+ Audio
+
+
+
+ the time duration between the signal reached 2% of it maximum value to the time it reaches 80% of its maximum value
+ Audio
+
+
+
+ a measure of the amount of decrease in the signal energy
+ Audio
+
+
+
+ the spectral power mean value.
+ Spectral
+
+
+
+ the geometric mean for the spectral power values sequence
+ Spectral
+
+
+
+ the squared sum of spectral power distribution values
+ Spectral
+
+
+
+ the frequency where the center of mass of the spectral power distribution lies
+ Spectral
+
+
+
+ Spectral
+
+
+
+ Spectral
+
+
+
+ Spectral
+
+
+
+ frequency of the maximum magnitude of the spectrum
+ Spectral
+
+
+
+ the ratio between the energy over 0-100 Hz band and the whole spectrum energy
+ Spectral
+
+
+
+ the variation of the spectrum around its mean value.
+ Spectral
+
+
+
+ Spectral
+
+
+
+ The spectral roll-off point is the frequency value so that the 85% of the spectral energy is contained below it
+ Spectral
+
+
+
+ the amount of decreasing of the spectral magnitude
+ Spectral
+
+
+
+ sum of the squared spectrum magnitude multiplied by the wave number of the bin
+ Spectral
+
+
diff -r 000000000000 -r 62d2c72e4223 rdf/af-MIREX.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-MIREX.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,135 @@
+
+
+
+
+ Principal Mel-spectrum Components
+ MIREX
+ Philippe Hamel
+
+
+
+ Fluctuation Patterns
+ MIREX
+ Franz de Leon
+
+
+
+ Decorrelated Filter Banks
+ MIREX
+ Shin-Cheol Lim
+
+
+
+ Octave-based Spectral Contrast
+ MIREX
+ Shin-Cheol Lim
+
+
+
+ Spectral Pattern
+ MIREX
+ Klaus Seyerlehner
+
+
+
+ Delta Spectral Pattern
+ MIREX 2012
+ Klaus Seyerlehner
+
+
+
+ Variance Delta Spectral Pattern
+ MIREX 2012
+ Klaus Seyerlehner
+
+
+
+ Logarithmic Fluctuation Pattern
+ MIREX 2012
+ Klaus Seyerlehner
+
+
+
+ Correlation Pattern
+ MIREX 2012
+ Klaus Seyerlehner
+
+
+
+ Spectral Contrast Pattern
+ MIREX 2012
+ Klaus Seyerlehner
+
+
+
+ Local Single Gaussian Model
+ MIREX 2012
+ Klaus Seyerlehner
+
+
+
+ George Tzanetakis Model
+ MIREX 2012
+ Klaus Seyerlehner
+
+
+
+ Rhythm Pattern
+ MIREX 2008
+ T. Lidy
+
+
+
+ Rhythm Histogram
+ MIREX 2008
+ T. Lidy
+
+
+
+ Temporal Rhythm Histogram
+ MIREX 2008
+ T. Lidy
+
+
+
+ Statistical Spectrum Descriptor
+ MIREX 2008
+ T. Lidy
+
+
+
+ Temporal Statistical Spectrum Descriptor
+ MIREX 2008
+ T. Lidy
+
+
+
+ Modulation Frequency Variance Descriptor
+ MIREX 2008
+ T. Lidy
+
+
+
+ Modulation Frequency Variance Descriptor
+ MIREX 2008
+ Ponce
+
+
+
+ Modulation Frequency Variance Descriptor
+ MIREX 2008
+ T. Lidy
+
+
+
+ Modulation Frequency Variance Descriptor
+ MIREX 2008
+ T. Lidy
+
+
+
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdf/af-MIRToolbox.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-MIRToolbox.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,149 @@
+
+
+
+ derived from calculated onsets with ACF, spectrum or both
+
+ Rhythm
+
+
+ the amount of partials that are not multiples of the fundamental frequency, takes into account the amount of energy outside the ideal harmonic series
+
+ Pitch
+
+
+ The proportion of energy above a given frequency
+
+ Timbre
+
+
+ shows the distribution of energy along the pitches or pitch classes
+
+ Tonality
+
+
+ The frequency below which 85% of the energy is contained. The percentage may be user-chosen
+
+ Timbre
+
+
+ Rhythmic periodicity along auditory channels
+
+ Rhythm
+
+
+ The degree of variation of the successive peaks of the spectrum
+
+ Timbre
+
+
+
+ Timbre
+
+
+ Use peaks of spectral flux to detect onsets
+
+ Rhythm
+
+
+ root mean square energy
+
+ Dynamics
+
+
+ Major vs. Minor, calculated as the strength difference between the best major and best minor key candidates
+
+ Tonality
+
+
+ estimates the beginning of the attack phase of a note by locating the local minimum before the maximum corresponding to the onset
+ These can have start time *and end time*
+
+ Timbre
+
+
+
+ Timbre
+
+
+ average slope of attack phase, computed either as a simple ratio, or a Gaussian-weighted average to emphasise the middle of the attack
+
+ Timbre
+
+
+ The best candidate key
+
+ Tonality
+
+
+ note onset times
+
+ Rhythm
+
+
+ The probability distribution across possible keys
+
+ Tonality
+
+
+ The average dissonance between all pairs of peaks in the spectrum
+
+ Timbre
+
+
+ Pitch estimated via ACF, autocorrelation spectrum or cepstrum, or a combination
+
+ Pitch
+
+
+ percentage of frames showing less than average energy
+
+ Dynamics
+
+
+ a measure of acoustic self-similarity as a function of time lag, computed from the similarity matrix
+
+ Rhythm
+
+
+ estimates the average frequency of events, i.e., the number of note onsets per second
+
+ Rhythm
+
+
+ estimates the rhythmic clarity, indicating the strength of the beats estimated by the tempo function
+
+ Rhythm
+
+
+ estimates the amplitude difference between the beginning and the end of the attack phase
+
+ Timbre
+
+
+ estimates MIDI note value based on segmentation and pitch detection
+
+ Pitch
+
+
+ Projects the chromagram into a self-organizing map
+
+ Tonality
+
+
+ Calculates the 6-dimensional tonal centroid vector from the chromagram
+
+ Tonality
+
+
+ the flux of the tonal centroid
+
+ Tonality
+
+
+
+
diff -r 000000000000 -r 62d2c72e4223 rdf/af-Marsyas.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-Marsyas.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,254 @@
+
+
+
+
+ Rms energy of realvec
+
+
+
+ Rolloff of each time slice of observations
+
+
+
+ Calculate k minimums and their positions
+
+
+
+ Compute SNR and variations
+
+
+
+ PowerToAverageRatio (or Power-to-Average Ratio) of a window
+
+
+
+ Calculates a single spectral flatness value.
+
+
+
+ Vector quantization for dense to sparse features
+
+
+
+ Gathers the running average, variance, standard deviation, etc.
+
+
+
+ StereoSpectrumFeatures capture panning information
+
+
+
+ PowerSpectrum computes the magnitude/power of the complex spectrum
+
+
+
+ Pitch detection using the YIN algorithm
+
+
+
+ BeatHistogramFromPeaks
+
+
+
+ Average Magnitude Difference Function
+
+
+
+ Azimuth Discrimination and Resynthesis (ADRess) implementation,which takes a stereo input (i.e. input is expected to be the output of a
+
+
+
+ Takes the output of the ADRess (i.e. the panning-frequency maps)and outputs the panning coefficient for each spectral bin (N/2+1 bins).
+
+
+
+ Time-domain AimPZFC
+
+
+
+ Halfwave rectification, compression and lowpass filtering
+
+
+
+ Compute Linear Spectral Pair (LSP) coefficientsTakes the output of ::LPC() and calculates the corresponding LSP values.
+
+
+
+ Standard Deviation of each row of observations
+
+
+
+ Centroid of each time slice of observations
+
+
+
+ Convert LPC coefficients to Cepstrum coefficients.
+
+
+
+ Flux calculate the flux between the current and prev. spectrum (e.g. output of PowerSpectrum)
+
+
+
+ Slaney's gammatone filterbank
+
+
+
+ Triangular FilterBankTakes as input the N/2+1 spectrum Magnitude points output by PowerSpectrum.
+
+
+
+ Calculates the mean absolute deviation
+
+
+
+ MFCC Mel-Frequency Cepstral Coefficients.Takes as input the N/2+1 spectrum Magnitude points output by PowerSpectrum.
+
+
+
+ Difference between detected and expected pitch
+
+
+
+ Pitch detection using the YIN algorithm
+
+
+
+ 'Box-cutting' routine to generate dense features
+
+
+
+ MeddisHairCell for auditory models
+
+
+
+ Halfwave rectification, compression and lowpass filtering
+
+
+
+ Time-domain AimPZFC2
+
+
+
+ Mean calculate the mean of each row of observations
+
+
+
+ Pyramid wavelet algorithm
+
+
+
+ Calculate the maximum absolute value for each observationsignal (per slice).
+
+
+
+ Daubechies4 WaveletStep
+
+
+
+ Local maximum strobe criterion: decaying threshold with timeout
+
+
+
+ Calculate k maximums and their positions
+
+
+
+ Takes the output of the enhADRessand outputs the panning coefficient for each spectral bin (N/2+1 bins).
+
+
+
+ Takes the output of the ADRess (i.e. the stereo azimuth-frequencymaps) and outputs a single channel spectrum of the part of the freq-azimuth
+
+
+
+ Pick peaks out of signal
+
+
+
+ Azimuth Discrimination and Resynthesis (EnhADRess) implementation,which takes a stereo input (i.e. input is expected to be the output of a
+
+
+
+ Detects if input contains a onset point
+
+
+
+ BeatHistogram
+
+
+
+ Compute the complex spectrum of input window
+
+
+
+ Computes the cross correlation of an input.
+
+
+
+ Size-shape image (aka the 'sscAI')
+
+
+
+ Compute Warped LPC coefficients, Pitch and Power [STILL UNDER TESTING!].
+
+
+
+ Stabilised auditory image
+
+
+
+ Krumhansl-Schmuckler Key-Finding Algorithm
+
+
+
+ StereoSpectrum computes the panning index for each spectrumbin of a stereo input (i.e. input is expected to be the output of a
+
+
+
+ compute the RMS Power of the input observations into one column*/
+
+
+
+ Calculate the maximum and minimum values for each observationsignal (per slice).
+
+
+
+ Convert spectrum magnitude (e.g. output from PowerSpectrum MarSystem)into Mel frequency scale.
+
+
+
+ Kurtosis
+
+
+
+ compute the Energy of the input observations into one column*/
+
+
+
+ Running calculation (across slices) of the autocorrelation values.
+
+
+
+ Convert spectrum magnitude (e.g. output from PowerSpectrum MarSystem)into a Chroma vector representation.
+
+
+
+ StereoSpectrumSources estimates the number of sources placed into different stereo positions.
+
+
+
+ Time-domain ZeroCrossings
+
+
+
+ Median calculate the median of each row of observations
+
+
+
+ Compute the generalized autocorrelation of input window
+
+
diff -r 000000000000 -r 62d2c72e4223 rdf/af-PsySound3.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-PsySound3.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,29 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdf/af-SuperCollider.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-SuperCollider.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,71 @@
+
+
+
+ Autocorrelation based beat tracker
+
+
+
+ based on exhaustively testing particular template patterns against feature streams
+
+
+
+ measures the energy at particular chroma within an nTET tuning system
+
+
+
+ a power spectrum's geometric mean divided by its arithmetic mean
+
+
+
+ calculates the cumulative distribution of the frequency spectrum, and outputs the frequency value which corresponds to the desired percentile
+
+
+
+ the weighted mean frequency, or the "centre of mass" of the spectrum
+
+
+
+ Outputs a frequency based upon the distance between interceptions of the X axis. The X intercepts are determined via linear interpolation so this gives better than just integer wavelength resolution. This is a very crude pitch follower, but can be useful in some situations.
+
+
+
+ Generates a set of MFCCs; these are obtained from a band-based frequency representation (using the Mel scale by default), and then a discrete cosine transform (DCT). The DCT is an efficient approximation for principal components analysis, so that it allows a compression, or reduction of dimensionality, of the data, in this case reducing 42 band readings to a smaller set of MFCCs. A small number of features (the coefficients) end up describing the spectrum. The MFCCs are commonly used as timbral descriptors.
+
+
+
+ An onset detector for musical audio signals
+
+
+
+
+
+
+ A perceptual loudness function which outputs loudness in sones; this is a variant of an MP3 perceptual model, summing excitation in ERB bands. It models simple spectral and temporal masking, with equal loudness contour correction in ERB bands to obtain phons (relative dB), then a phon to sone transform. The final output is typically in the range of 0 to 64 sones, though higher values can occur with specific synthesised stimuli.
+
+
+
+ A (12TET major/minor) key tracker based on a pitch class profile of energy across FFT bins and matching this to templates for major and minor scales in all transpositions. It assumes a 440 Hz concert A reference. Output is 0-11 C major to B major, 12-23 C minor to B minor.
+
+
+
+ produces the spectral crest measure, which is an indicator of the "peakiness" of the spectral energy distribution
+
+
+
+ measures the spectral spread, which is the magnitude-weighted variance
+
+
+
+ measures the spectral slope, which is the slope of the linear correlation line derived from the spectral magnitudes
+
+
+
+ measures the "crest factor" of a time-domain signal, i.e. the ratio of the absolute peak to the absolute mean over a certain time period
+
+
+
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdf/af-Vamp.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-Vamp.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,906 @@
+
+
+
+ Estimates beat locations and tempo (off-line [default] and on-line modes of operation)
+ frequency
+ Marsyas Plugins
+
+ Sparse
+ IBT - INESC Beat Tracker
+
+
+
+ frequency
+ Local Tuning (Tuning)
+ Dense
+ Matthias Mauch
+
+
+
+ time
+ Feature Means (Similarity)
+ Dense
+ Queen Mary, University of London
+
+
+ Extract the tonality an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Tonality
+
+
+ Extract the DCT of an audio signal
+ time
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Discrete Cosine Transform
+
+
+ Extract the skewness of a range of values
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Skewness
+
+
+
+ time
+ Beat Count (Bar and Beat Tracker)
+ Sparse
+ Queen Mary, University of London
+
+
+
+ frequency
+ Means of Coefficients (Mel-Frequency Cepstral Coefficients)
+ Dense
+ Queen Mary, University of London
+
+
+ Extract the highest value from a given range
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Highest Value
+
+
+ Estimate note onset times
+ time
+ Paul Brossier (plugin by Chris Cannam)
+
+ Sparse
+ Aubio Onset Detector
+
+
+ Extract the variance of a range of values
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Variance
+
+
+ Calculate a series of MFCC vectors from the audio
+ Extract MFCC from an audio spectrum
+ Marsyas - Batch Feature Extract - Mel-Frequency Cepstral Coefficients
+ time
+ frequency
+ Queen Mary, University of London
+ Marsyas Plugins
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Marsyas - Batch Feature Extract - Mel-Frequency Cepstral Coefficients
+ Mel-Frequency Cepstral Coefficients
+
+
+ Extract the spectral centroid of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Centroid
+
+
+ Extract the sum of the values in a given range
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Sum of Values
+
+
+
+ frequency
+ Note Representation of Chord Estimate (Chordino)
+ Sparse
+ Matthias Mauch
+
+
+
+ frequency
+ Onset Detection Function (Tempo and Beat Tracker)
+ Onset Detection Function (Note Onset Detector)
+ Dense
+ Queen Mary, University of London
+
+
+
+ Return a distance matrix for similarity between the input audio channels
+ time
+ Similarity
+ Queen Mary, University of London
+
+
+
+ Chordino provides a simple chord transcription based on NNLS Chroma (as in the NNLS Chroma plugin). Chord profiles given by the user in the file chord.dict are used to calculate frame-wise chord similarities. A simple (non-state-of-the-art!) algorithm smoothes these to provide a chord transcription using a standard HMM/Viterbi approach.
+ frequency
+ Chordino
+ Matthias Mauch
+
+
+ Estimate note onset positions, pitches and durations
+ time
+ Paul Brossier (plugin by Chris Cannam)
+
+ Sparse
+ Aubio Note Tracker
+
+
+
+ Detect and return the positions of harmonic changes such as chord boundaries
+ time
+ Tonal Change
+ Queen Mary, University of London
+
+
+ Extract the standard deviation of a range of values
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Standard Deviation
+
+
+
+ frequency
+ Chroma Means (Chromagram)
+ Dense
+ Queen Mary, University of London
+
+
+ Extract the mean of a range of values
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Mean
+
+
+ Extract the spectral peaks from an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Peak Spectrum
+
+
+ Return the instantaneous evolution of HPCP (Harmonic Pitch Class Profile) of a signal.
+ frequency
+ Music Technology Group, Universitat Pompeu Fabra
+
+ Dense
+ HPCP
+
+
+ Extract the spectral sharpness of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Sharpness
+
+
+
+ time
+ Transform to 6D Tonal Content Space (Tonal Change)
+ Dense
+ Queen Mary, University of London
+
+
+ Extract the fundamental frequency of an audio signal
+ time
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Fundamental Frequency
+
+
+
+ frequency
+ Log-Frequency Spectrum (NNLS Chroma)
+ Dense
+ Matthias Mauch
+
+
+
+ This plugin provides a number of features derived from a DFT-based log-frequency amplitude spectrum: some variants of the log-frequency spectrum, including a semitone spectrum derived from approximate transcription using the NNLS algorithm; and based on this semitone spectrum, different chroma features.
+ frequency
+ NNLS Chroma
+ Matthias Mauch
+
+
+ Extract the irregularity (type I) of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Irregularity I
+
+
+ Extract the average deviation of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Average Deviation
+
+
+ Extract the lowest value from a given range
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Lowest Value
+
+
+
+ time
+ Beat Spectra (Similarity)
+ Sparse
+ Queen Mary, University of London
+
+
+
+ time
+ Key Mode (Key Detector)
+ Sparse
+ Queen Mary, University of London
+
+
+
+ frequency
+ Note Onsets (Note Onset Detector)
+ Sparse
+ Queen Mary, University of London
+
+
+ Track estimated note pitches
+ time
+ Paul Brossier (plugin by Chris Cannam)
+
+ Sparse
+ Aubio Pitch Detector
+
+
+ Extract the spectral slope of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Slope
+
+
+
+ Estimate individual note onset positions
+ frequency
+ Note Onset Detector
+ Queen Mary, University of London
+
+
+ Estimates the melody pitch in polyphonic music (also good for homophonic and monophonic music). Segments without melody are indicated by zero or negative values. For further details please read: J. Salamon and E. Gomez, "Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics", IEEE Transactions on Audio, Speech and Language Processing, 20(6):1759-1770, 2012. We would highly appreciate the above reference being cited in publications of work in which this plug-in was used.
+ time
+ Music Technology Group, Universitat Pompeu Fabra
+
+ Dense
+ MELODIA - Melody Extraction
+
+
+
+ The tuning plugin can estimate the local and global tuning of piece. The same tuning method is used for the NNLS Chroma and Chordino plugins.
+ frequency
+ Tuning
+ Matthias Mauch
+
+
+ Extract the kurtosis of a range of values
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Kurtosis
+
+
+ Extract the fundamental frequency of an audio signal (failsafe)
+ time
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Fundamental Frequency (failsafe)
+
+
+ Extract the RMS amplitude of an audio signal
+ time
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ RMS Amplitude
+
+
+ Extract the tristimulus (type II) of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Tristimulus II
+
+
+
+ time
+ Distance from First Channel (Similarity)
+ Dense
+ Queen Mary, University of London
+
+
+ Extract the ASDF of an audio signal
+ time
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Average Squared Difference Function
+
+
+
+ Estimate the musical tempo and track beat positions
+ time
+ Aubio Beat Tracker
+ Paul Brossier (method by Matthew Davies, plugin by Chris Cannam)
+
+
+
+ frequency
+ Semitone Spectrum (NNLS Chroma)
+ Dense
+ Matthias Mauch
+
+
+ Extract the number of non-zero elements in an input spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Non-zero count
+
+
+ Extract the kurtosis of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Kurtosis
+
+
+
+ frequency
+ Smoothed Detection Function (Note Onset Detector)
+ Sparse
+ Queen Mary, University of London
+
+
+
+ time
+ Feature Variances (Similarity)
+ Dense
+ Queen Mary, University of London
+
+
+ Extract bark coefficients from an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Bark Coefficients
+
+
+
+ frequency
+ Coefficients (Mel-Frequency Cepstral Coefficients)
+ Dense
+ Queen Mary, University of London
+
+
+ Marsyas - Batch Feature Extract - Centroid
+ time
+ Marsyas Plugins
+
+ Dense
+ Marsyas - Batch Feature Extract - Centroid
+
+
+ Extract the autocorrelation of an audio signal
+ time
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Autocorrelation
+
+
+ Extract the standard deviation of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Standard Deviation
+
+
+ Divide the track into a sequence of consistent segments
+ time
+ Queen Mary, University of London
+
+ Sparse
+ Segmenter
+
+
+ Extract the AMDF of an audio signal
+ time
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Average Magnitude Difference Function
+
+
+
+ Detect levels below a certain threshold
+ time
+ Aubio Silence Detector
+ Paul Brossier (plugin by Chris Cannam)
+
+
+ Marsyas - Batch Feature Extract - Spectral Flatness Measure
+ time
+ Marsyas Plugins
+
+ Dense
+ Marsyas - Batch Feature Extract - Spectral Flatness Measure
+
+
+ Extract the tristimulus (type III) of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Tristimulus III
+
+
+
+ frequency
+ Chord Estimate (Chordino)
+ Sparse
+ Matthias Mauch
+
+
+
+ time
+ frequency
+ Tempo (Aubio Beat Tracker)
+ Tempo (Tempo and Beat Tracker)
+ Dense
+ Sparse
+ Queen Mary, University of London
+ Paul Brossier (method by Matthew Davies, plugin by Chris Cannam)
+
+
+
+ frequency
+ Chromagram and Bass Chromagram (NNLS Chroma)
+ Dense
+ Matthias Mauch
+
+
+
+ frequency
+ Tuned Log-Frequency Spectrum (NNLS Chroma)
+ Dense
+ Matthias Mauch
+
+
+ Extract the zero crossing rate of an audio signal
+ time
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Zero Crossing Rate
+
+
+ Extract the inharmonicity of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Inharmonicity
+
+
+
+ time
+ Pitch Contours: Melody (MELODIA - Melody Extraction (intermediate steps))
+ Dense
+ Music Technology Group, Universitat Pompeu Fabra
+
+
+ Extract the odd-to-even harmonic ratio of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Odd/even Harmonic Ratio
+
+
+
+ time
+ Distance Matrix (Similarity)
+ Dense
+ Queen Mary, University of London
+
+
+ Extract the skewness of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Skewness
+
+
+ Extract the spectral flatness of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Flatness
+
+
+
+ time
+ Pitch Contours: All (MELODIA - Melody Extraction (intermediate steps))
+ Dense
+ Music Technology Group, Universitat Pompeu Fabra
+
+
+
+ frequency
+ Log-Likelihood of Chord Estimate (Chordino)
+ Dense
+ Matthias Mauch
+
+
+
+ Estimate beat locations and tempo
+ frequency
+ Tempo and Beat Tracker
+ Queen Mary, University of London
+
+
+
+ time
+ Key (Key Detector)
+ Sparse
+ Queen Mary, University of London
+
+
+
+ time
+ Key Strength Plot (Key Detector)
+ Dense
+ Queen Mary, University of London
+
+
+
+ time
+ Tonic Pitch (Key Detector)
+ Sparse
+ Queen Mary, University of London
+
+
+
+ time
+ Bars (Bar and Beat Tracker)
+ Sparse
+ Queen Mary, University of London
+
+
+ Detect and count zero crossing points
+ Marsyas - Batch Feature Extract - Zero Crossings
+ time
+ Marsyas Plugins
+
+ Dense
+ Zero Crossings
+ Marsyas - Batch Feature Extract - Zero Crossings
+
+
+ Produce an adaptive spectrogram by adaptive selection from spectrograms at multiple resolutions
+ time
+ Queen Mary, University of London
+
+ Dense
+ Adaptive Spectrogram
+
+
+
+ time
+ Beat Spectral Difference (Bar and Beat Tracker)
+ Sparse
+ Queen Mary, University of London
+
+
+ Extract a spectrogram with constant ratio of centre frequency to resolution from the input audio
+ frequency
+ Queen Mary, University of London
+
+ Dense
+ Constant-Q Spectrogram
+
+
+
+ Provides visualisations of the intermediate steps calculated by the melody extraction algorithm implemented in the MELODIA - Melody Extraction plug-in. For further details please read: J. Salamon and E. Gomez, "Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics", IEEE Transactions on Audio, Speech and Language Processing, 20(6):1759-1770, 2012. We would highly appreciate the above reference being cited in publications of work in which this plug-in was used.
+ time
+ MELODIA - Melody Extraction (intermediate steps)
+ Music Technology Group, Universitat Pompeu Fabra
+
+
+
+ time
+ Salience Function (MELODIA - Melody Extraction (intermediate steps))
+ Dense
+ Music Technology Group, Universitat Pompeu Fabra
+
+
+ Extract a series of tonal chroma vectors from the audio
+ frequency
+ Queen Mary, University of London
+ Matthias Mauch
+
+ Dense
+ Chromagram (NNLS Chroma)
+ Chromagram
+
+
+ Marsyas - Batch Feature Extract - Line Spectral Pairs
+ time
+ Marsyas Plugins
+
+ Dense
+ Marsyas - Batch Feature Extract - Line Spectral Pairs
+
+
+ Extract the irregularity (type II) of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Irregularity II
+
+
+
+ time
+ Silent Regions (Aubio Silence Detector)
+ Sparse
+ Paul Brossier (plugin by Chris Cannam)
+
+
+
+ time
+ Tonal Change Positions (Tonal Change)
+ Sparse
+ Queen Mary, University of London
+
+
+
+ time
+ Tonal Change Detection Function (Tonal Change)
+ Sparse
+ Queen Mary, University of London
+
+
+
+ time
+ Silence Test (Aubio Silence Detector)
+ Sparse
+ Paul Brossier (plugin by Chris Cannam)
+
+
+ Extract the loudness of an audio signal from its spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Loudness
+
+
+ Extract the variance of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Variance
+
+
+ Extract the spectral smoothness of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Smoothness
+
+
+ Extract the average deviation of a range of values
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Average Deviation
+
+
+ Marsyas - Batch Feature Extract - Linear Prediction Cepstral Coefficients
+ time
+ Marsyas Plugins
+
+ Dense
+ Marsyas - Batch Feature Extract - Linear Prediction Cepstral Coefficients
+
+
+
+ Estimate the key of the music
+ time
+ Key Detector
+ Queen Mary, University of London
+
+
+ Extract the spectrum of an audio signal
+ time
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectrum
+
+
+ Extract the rolloff point of an audio spectrum
+ Marsyas - Batch Feature Extract - Spectral Rolloff
+ time
+ frequency
+ Marsyas Plugins
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Rolloff
+ Marsyas - Batch Feature Extract - Spectral Rolloff
+
+
+
+ frequency
+ Bass Chromagram (NNLS Chroma)
+ Dense
+ Matthias Mauch
+
+
+
+ Estimate bar and beat locations
+ time
+ Bar and Beat Tracker
+ Queen Mary, University of London
+
+
+ Extract the spectral crest measure of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Crest Measure
+
+
+ Extract the spectral spread of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Spectral Spread
+
+
+ Marsyas - Batch Feature Extract - Spectral Crest Factor
+ time
+ Marsyas Plugins
+
+ Dense
+ Marsyas - Batch Feature Extract - Spectral Crest Factor
+
+
+ Transcribe the input audio to estimated notes
+ time
+ Queen Mary, University of London
+
+ Sparse
+ Polyphonic Transcription
+
+
+
+ time
+ Non-Silent Regions (Aubio Silence Detector)
+ Sparse
+ Paul Brossier (plugin by Chris Cannam)
+
+
+
+ frequency
+ Harmonic Change Value (Chordino)
+ Dense
+ Matthias Mauch
+
+
+
+ time
+ frequency
+ Beats (Tempo and Beat Tracker)
+ Beats (Aubio Beat Tracker)
+ Beats (Bar and Beat Tracker)
+ Sparse
+ Queen Mary, University of London
+ Paul Brossier (method by Matthew Davies, plugin by Chris Cannam)
+
+
+ Extract the tristimulus (type I) of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Tristimulus I
+
+
+ Visualisation by scalogram
+ time
+ Queen Mary, University of London
+
+ Dense
+ Discrete Wavelet Transform
+
+
+ Extract the noisiness of an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Noisiness
+
+
+ Extract the harmonics from an audio spectrum
+ frequency
+ libxtract by Jamie Bullock (plugin by Chris Cannam)
+
+ Dense
+ Harmonic Spectrum
+
+
+
+ time
+ Ordered Distances from First Channel (Similarity)
+ Dense
+ Queen Mary, University of London
+
+
diff -r 000000000000 -r 62d2c72e4223 rdf/af-Yaafe.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-Yaafe.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,142 @@
+
+
+
+ Extract amplitude envelope using hilbert transform, low-pass filtering and decimation.
+
+
+
+ Compute shape statistics of :class:MagnitudeSpectrum, (see [GR2004]_).
+
+
+
+ Feature transform that compute cepstrum coefficients of input feature frames. (use DCT II)
+
+
+
+ Compute energy as root mean square of an audio Frame.
+
+
+
+ SpectralVariation is the normalized correlation of :class:spectrum MagnitudeSpectrum between consecutive frames. (see [GP2004]_)
+
+
+
+ SpectralSlope is computed by linear regression of the spectral amplitude. (see [GP2004]_)
+
+
+
+ Compute onset detection using a complex domain spectral flux method [CD2003]_.
+
+
+
+ Compute :ref:shape statistics shapestatistics of signal frames.
+
+
+
+ Compute autocorrelation coefficients *ac* on each frames.
+
+
+
+ The loudness coefficients are the energy in each Bark band, normalized by the overall sum. see [GP2004]_ and [MG1997]_ for more details.
+
+
+
+ Compute frame's magnitude spectrum, using an analysis window (Hanning or Hamming), or not.
+
+
+
+ Feature transform that compute peaks of the autocorrelation function, outputs peaks and amplitude.
+
+
+
+ Spectral roll-off is the frequency so that 99% of the energy is contained below. see [SS1997]_.
+
+
+
+ Compute the sharpness of :class:Loudness coefficients, according to [GP2004]_.
+
+
+
+ Compute spectral flatness per log-spaced band of 1/4 octave, as proposed in MPEG7 standard.
+
+
+
+ Feature transform that compute the temporal mean and variance of input feature over the given number of frames.
+
+
+
+ Compute zero-crossing rate in frames. see [SS1997]_.
+
+
+
+ Compute the spread of :class:Loudness coefficients, according to [GP2004]_.
+
+
+
+ Compute temporal derivative of input feature. The derivative is approximated by
+
+
+
+ Compute spectral decrease accoding to [GP2004]_.
+
+
+
+ Compute log of :class:OBSI ratio between consecutive octave.
+
+
+
+ Compute the Line Spectral Frequency (LSF) coefficients of a signal frame. Algorithm was adapted from ([TB2006]_, [SH1976]_).
+
+
+
+ Compute Octave band signal intensity using a trigular octave filter bank ([SE2005]_).
+
+
+
+ Compute the Linear Predictor Coefficients (LPC) of a signal frame. It uses autocorrelation and Levinson-Durbin algorithm. see [JM1975]_.
+
+
+
+ Feature transform that compute the slope of input feature over the given number of frames.
+
+
+
+ Centroid, spread, skewness and kurtosis of each frame's amplitude envelope. For more details about moments, see :ref:Shape Statistics shapestatistics.
+
+
+
+ Compute spectral crest factor per log-spaced band of 1/4 octave.
+
+
+
+ Compute the Mel-frequencies cepstrum coefficients [DM1980]_.
+
+
+
+ Compute the Mel-frequencies spectrum [DM1980]_.
+
+
+
+ Compute global spectral flatness using the ratio between geometric and arithmetic mean.
+
+
+
+ Tremelo and Grain description, according to [SE2005]_ and [AE2001]_.
+
+
+
+ Segment input signal into frames.
+
+
+
+ Compute flux of :class:spectrum MagnitudeSpectrum between consecutives frames.
+
+
+
+ Feature transform that compute histogram of input values
+
+
+
diff -r 000000000000 -r 62d2c72e4223 rdf/af-aubio.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-aubio.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,136 @@
+
+
+
+ Computes the onset detection function and detect peaks in these functions. When onsets are found above a given silence threshold, and after a minimum inter-onset interval, the output vector returned by aubio_onset_do is filled with 1. Otherwise, the output vector remains 0
+
+
+
+ Peak picking utilities function
+
+
+
+ Generic method for pitch detection
+
+
+
+ Pitch detection using a fast harmonic comb filter
+
+
+
+ Pitch detection using multiple-comb filter
+
+
+
+ Pitch detection using a Schmitt trigger
+
+
+
+ Pitch detection using the YIN algorithm
+
+
+
+ Pitch detection using a spectral implementation of the YIN algorithm
+
+
+
+ Mel frequency filter bank coefficients. Set filter bank coefficients to Mel frequency bands
+
+
+
+ Mel frequency filter bank coefficients. Set filter bank coefficients to Mel frequency bands
+
+
+
+ Mel-frequency cepstrum coefficients object
+
+
+
+ Transient / Steady-state Separation (TSS)
+
+
+
+ These functions are designed to raise at notes attacks in music signals.
+
+
+
+ This function calculates the local energy of the input spectral frame.
+
+
+
+ This method computes the High Frequency Content (HFC) of the input spectral frame. The resulting function is efficient at detecting percussive onsets
+
+
+
+ Complex Domain Method onset detection function.
+
+
+
+ Phase Based Method onset detection function.
+
+
+
+ Spectral difference method onset detection function.
+
+
+
+ Kullback-Liebler onset detection function.
+
+
+
+ Modified Kullback-Liebler onset detection function.
+
+
+
+ Modified Kullback-Liebler onset detection function.
+
+
+
+ Spectral Flux
+
+
+
+ Spectral shape descriptors
+
+
+
+ The spectral centroid represents the barycenter of the spectrum.
+
+
+
+ The spectral spread is the variance of the spectral distribution around its centroid.
+
+
+
+ The skewness is computed from the third order moment of the spectrum. A negative skewness indicates more energy on the lower part of the spectrum. A positive skewness indicates more energy on the high frequency of the spectrum.
+
+
+
+ The kurtosis is a measure of the flatness of the spectrum, computed from the fourth order moment.
+
+
+
+ The spectral slope represents decreasing rate of the spectral amplitude, computed using a linear regression.
+
+
+
+ The spectral decrease is another representation of the decreasing rate, based on perceptual criteria.
+
+
+
+ This function returns the bin number below which 95% of the spectrum energy is found.
+
+
+
+ Beat tracking using a context dependant model.
+
+
+
+ Tempo detection driver. This object stores all the memory required for tempo detection algorithm and returns the estimated beat locations.
+
+
+
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdf/af-comirva.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-comirva.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,26 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdf/af-jMIR.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-jMIR.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,192 @@
+
+
+
+ Spectral Variability
+ The standard deviation of the magnitude spectrum. This is a measure of the variance of a signal's magnitude spectrum.
+
+
+
+ Spectral Rolloff Point
+ The fraction of bins in the power spectrum at which 85% // System.getProperty(line.separator) of the power is at lower frequencies. This is a measure // System.getProperty(line.separator) // of the right-skewedness of the power spectrum.
+
+
+
+ Area Method of Moments
+ 2D statistical method of moments
+
+
+
+ Zero Crossings
+ The number of times the waveform changed sign. An indication of frequency as well as noisiness.
+
+
+
+ ConstantQ
+ signal to frequency transform using exponential-spaced frequency bins.
+
+
+
+ Peak Based Spectral Smoothness
+ Peak Based Spectral Smoothness is calculated from partials, not frequency bins. It is implemented accortding to McAdams 99 System.getProperty(line.separator) System.getProperty(line.separator) McAdams, S. 1999.
+
+
+
+ 2D Polynomial Approximation
+ coeffecients of 2D polynomial best describing the input matrtix.
+
+
+
+ Log of ConstantQ
+ logarithm of each bin of exponentially-spaced frequency bins.
+
+
+
+ Spectral Centroid
+ The centre of mass of the power spectrum.
+
+
+
+ MFCC
+ MFCC calculations based upon Orange Cow code
+
+
+
+ Partial Based Spectral Centroid
+ Spectral Centroid calculated based on the center of mass of partials instead of center of mass of bins.
+
+
+
+ Partial Based Spectral Flux
+ Cacluate the correlation bettween adjacent frames based peaks instead of spectral bins. Peak tracking is primitive - whe the number of bins changes, the bottom bins are matched sequentially and the extra unmatched bins are ignored.) definition = new FeatureDefinition(name, description, true, 1) dependencies = new String[] { Peak Detection, Peak Detection } offsets = new int[] { 0, -1 } } /** * Extract the peak based spectral flux from the window. * @param samples * The samples to extract the feature from. * @param sampling_rate * The sampling rate that the samples are encoded with. * @param other_feature_values * The values of other features that are needed to calculate this * value. The order and offsets of these features must be the * same as those returned by this class's getDependencies and * getDependencyOffsets methods respectively. The first indice * indicates the feature/window and the second indicates the * value. * @return The extracted feature value(s). * @throws Exception * Throws an informative exception if the feature cannot be * calculated. * @see jAudioFeatureExtractor.AudioFeatures.FeatureExtractor#extractFeature(double[], * double, double[][]) */ public double[] extractFeature(double[] samples, double sampling_rate, double[][] other_feature_values) { double[] result = new double[1] double[] old = other_feature_values[1] double[] now = other_feature_values[0] double x, y, xy, x2, y2 x = y = xy = x2 = y2 = 0.0 int peakCount = Math.min(old.length, now.length) for (int i = 0 i < peakCount i) { x = old[i] y = now[i] xy = old[i] * now[i] x2 = old[i] * old[i] y2 = now[i] * now[i] } double top = xy - (x * y) / peakCount double bottom = Math.sqrt(Math.abs((x2 - ((x * x) / peakCount)) * (y2 - ((y * y) / peakCount)))) result[0] = top / bottom return result } /** * Proviede a complete copy of this feature. Used to implement the prottype * pattern */ public Object clone() { return new HarmonicSpectralFlux() } }
+
+
+
+ Method of Moments
+ Statistical Method of Moments of the Magnitude Spectrum.
+
+
+
+ Relative Difference Function
+ Relative Difference Function
+
+
+
+ FFT Bin Frequency Labels
+ The bin label, in Hz, of each power spectrum or magnitude spectrum bin. Not useful as a feature in itself, but useful for calculating other features from the magnitude spectrum and power spectrum.
+
+
+
+ LPC
+ Linear Prediction Coeffecients calculated using autocorrelation and Levinson-Durbin recursion.
+
+
+
+ Beat Sum
+ The sum of all entries in the beat histogram. This is a good measure of the importance of regular beats in a signal.
+
+
+
+ Beat Histogram
+ A histogram showing the relative strength of different rhythmic periodicities (tempi) in a signal. Found by calculating the auto-correlation of the RMS.
+
+
+
+ 2D Polynomial Approximation ConstantQ MFCC
+ coeffecients of 2D polynomial best describing the input matrtix.
+
+
+
+ Beat Histogram Bin Labels
+ The bin label, in beats per minute, of each beat histogram bin. Not useful as a feature in itself, but useful for calculating other features from the beat histogram.
+
+
+
+ 2D Polynomial Approximation of Log of ConstantQ
+ coeffecients of 2D polynomial best describing the input matrix.
+
+
+
+ Magnitude Spectrum
+ A measure of the strength of different frequency components.
+
+
+
+ Area Method of Moments of Log of ConstantQ transform
+ 2D statistical method of moments of the log of the ConstantQ transform
+
+
+
+ Area Method of Moments of MFCCs
+ 2D statistical method of moments of MFCCs
+
+
+
+ Power Spectrum
+ A measure of the power of different frequency components.
+
+
+
+ Strongest Beat
+ The strongest beat in a signal, in beats per minute, found by finding the strongest bin in the beat histogram.
+
+
+
+ Strength Of Strongest Beat
+ How strong the strongest beat in the beat histogram is compared to other potential beats.
+
+
+
+ Root Mean Square
+ A measure of the power of a signal.
+
+
+
+ Fraction Of Low Energy Windows
+ The fraction of the last 100 windows that has an RMS less than the mean RMS in the last 100 windows. This can indicate how much of a signal is quiet relative to the rest of the signal.
+
+
+
+ Spectral Flux
+ A measure of the amount of spectral change in a signal. //\n Found by calculating the change in the magnitude spectrum //\n from frame to frame.
+
+
+
+ Strongest Frequency Via Zero Crossings
+ The strongest frequency component of a signal, in Hz, found via the number of zero-crossings.
+
+
+
+ ConstantQ derived MFCCs
+ MFCCs directly caluclated from ConstantQ exponential bins
+
+
+
+ Compactness
+ A measure of the noisiness of a signal. Found by comparing the components of a window's magnitude spectrum with the magnitude spectrum of its neighbouring windows.
+
+
+
+ Strongest Frequency Via FFT Maximum
+ The strongest frequency component of a signal, in Hz, found via finding the FFT bin with the highest power.
+
+
+
+ Strongest Frequency Via Spectral Centroid
+ The strongest frequency component of a signal, in Hz, found via the spectral centroid.
+
+
+
+ Area Method of Moments of ConstantQ-based MFCCs
+ 2D statistical method of moments of ConstantQ-based MFCCs
+
+
+
+ Peak Detection
+ All peaks that are within an order of magnitude of the highest point
+
+
+
diff -r 000000000000 -r 62d2c72e4223 rdf/af-libXtract.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-libXtract.rdf Mon Feb 25 14:40:54 2013 +0000
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+
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+
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+
+
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+
+
+
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+
+
+
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+
+
+
+
+
+
+
+
+
+
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+
+
+
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+
+
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+
+
+
+
+
+
+
+
+
+
+
+
+
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+
+
diff -r 000000000000 -r 62d2c72e4223 rdf/af-sMIRk.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/af-sMIRk.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,32 @@
+
+
+
+
+
+
+
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+
+
+
+
+
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+
+
+
+
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+
+
+
+
+
+
+
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdf/base.rdf
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdf/base.rdf Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,1155 @@
+
+
+
+ low
+ environmental sound recognition
+ AmplitudeDescriptor
+ intraframe
+ physical
+ temporal
+ Spectral binning
+ Mean
+ Median
+ Windowing
+
+ 9
+
+
+ medium
+ music information retrieval
+ Inharmonicity
+ intraframe
+ perceptual
+ frequency
+ Zero-/Level Crossing Detector
+ Autocorrelation
+ Median
+ Windowing
+
+ 1
+
+
+ medium
+ music information retrieval
+ SpectralPeakStructure
+ intraframe
+ perceptual
+ frequency
+ Spectral binning
+ Zero-/Level Crossing Detector
+ Derivation, Difference
+ Entropy
+ Discrete Fourier Transform
+ Windowing
+
+ 1
+
+
+ low
+ music information retrieval
+ SpectralDispersion
+ intraframe
+ perceptual
+ frequency
+ Energy Spectral Density
+ Harmonic Peak Detection
+ Discrete Fourier Transform
+ Median
+ Windowing
+
+ 1
+
+
+ high
+ music information retrieval
+ psychoacoustic
+ IntegralLoudness
+ intraframe
+ perceptual
+ frequency
+ Exponential Function
+ (Non-) Linear Weighting Function
+ Logarithm
+ Discrete Fourier Transform
+ Root Mean Square
+ Windowing
+
+ 1
+
+
+ medium
+ music information retrieval
+ Chromagram
+ intraframe
+ perceptual
+ frequency
+ Discrete Fourier Transform
+ Logarithm
+ Root Mean Square
+ Windowing
+
+ 12
+
+
+ high
+ several
+ psychoacoustic
+ PsychoacousticalPitch
+ intraframe
+ perceptual
+ frequency
+ Root Mean Square
+ Band-pass Filter (Bank)
+ (Non-) Linear Weighting Function
+ Autocorrelation
+
+ parameterized
+
+
+ high
+ music information retrieval
+ psychoacoustic
+ RhythmPatterns
+ interframe
+ physical
+ modulation frequency
+ (Non-) Linear Weighting Function
+ Low-pass Filter
+ Logarithm
+ Regression
+ Harmonic Peak Detection
+ Discrete Fourier Transform
+ Windowing
+
+ 80
+
+
+ low
+ music information retrieval
+ MPEG-7
+ MPEG7LogAttackTime
+ global
+ physical
+ temporal
+ Power
+ Logarithm
+ Root Mean Square
+ Windowing
+
+ 1
+
+
+ high
+ several
+ psychoacoustic
+ JointAcousticandModuluationFrequency
+ interframe
+ physical
+ modulation frequency
+ Discrete Wavelet Transform
+ Low-pass Filter
+ Regression
+ Discrete Fourier Transform
+ Root Mean Square
+ Windowing
+
+ parameterized
+
+
+ medium
+ fingerprinting
+ SpectralFlatness
+ intraframe
+ perceptual
+ frequency
+ Mean
+ Discrete Fourier Transform
+ Logarithm
+ Regression
+ Windowing
+
+ parameterized
+
+
+ high
+ several
+ psychoacoustic
+ BarkscaleFrequencyCepstralCoefficients
+ intraframe
+ physical
+ cepstral
+ Discrete Fourier Transform
+ Logarithm
+ Regression
+ Discrete Cosine Transform
+ Windowing
+
+ parameterized
+
+
+ high
+ music information retrieval
+ BeatTracker
+ interframe
+ perceptual
+ modulation frequency
+ Comb Filter (Bank)
+ Low-pass Filter
+ Derivation, Difference
+ Band-pass Filter (Bank)
+ Root Mean Square
+ Windowing
+
+ 1
+
+
+ high
+ music information retrieval
+ CyclicBeatSpectrum
+ interframe
+ perceptual
+ modulation frequency
+ Comb Filter (Bank)
+ Low-pass Filter
+ Derivation, Difference
+ Discrete Fourier Transform
+ Root Mean Square
+ Windowing
+
+ parameterized
+
+
+ medium
+ music information retrieval
+ psychoacoustic
+ AuditoryFilterBankTemporalEnvelopes
+ intraframe
+ physical
+ modulation frequency
+ Energy Spectral Density
+ Band-pass Filter (Bank)
+ Root Mean Square
+ Windowing
+
+ 62
+
+
+ medium
+ music information retrieval
+ DaubechiesWaveletCoefficientHistogram
+ intraframe
+ physical
+ frequency
+ Spectral binning
+ Discrete Wavelet Transform
+ Windowing
+
+ 28
+
+
+ medium
+ audio segmentation
+ psychoacoustic
+ 4HzModulationEnergy
+ interframe
+ physical
+ modulation frequency
+ Energy Spectral Density
+ Normalization
+ Regression
+ Band-pass Filter (Bank)
+ Discrete Fourier Transform
+ Root Mean Square
+ Windowing
+
+ 1
+
+
+ low
+ fingerprinting
+ SpectralCrest
+ intraframe
+ perceptual
+ frequency
+ Sum, Weighted Sum
+ Mean
+ Logarithm
+ Regression
+ Discrete Fourier Transform
+ Windowing
+
+ parameterized
+
+
+ low
+ several
+ SpectralSlope
+ intraframe
+ physical
+ frequency
+ Peak Detection
+ Discrete Fourier Transform
+ Windowing
+
+ 4
+
+
+ medium
+ music information retrieval
+ MPEG-7
+ MPEG7HarmonicSpectralDeviation
+ intraframe
+ perceptual
+ frequency
+ Median
+ Zero-/Level Crossing Detector
+ Mean
+ Logarithm
+ Discrete Fourier Transform
+ Windowing
+
+ 1
+
+
+ medium
+ music information retrieval
+ MPEG-7
+ MPEG7HarmonicSpectralSpread
+ intraframe
+ perceptual
+ frequency
+ Zero-/Level Crossing Detector
+ Discrete Fourier Transform
+ Median
+ Windowing
+
+ 1
+
+
+ medium
+ several
+ LineSpectralFrequencies
+ intraframe
+ physical
+ frequency
+ Percentile
+ Autoregression (Linear Prediction Analysis)
+ Windowing
+
+ parameterized
+
+
+ low
+ several
+ MPEG-7
+ MPEG7AudioFundamentalFrequency
+ intraframe
+ perceptual
+ frequency
+ Sum, Weighted Sum
+ Autocorrelation
+ Windowing
+
+ 2
+
+
+ high
+ environmental sound recognition
+ psychoacoustic
+ NoiseRobustAuditoryFeature
+ intraframe
+ physical
+ cepstral
+ Discrete Cosine Transform
+ (Non-) Linear Weighting Function
+ Band-pass Filter Bank
+ Low-pass Filter
+ Logarithm
+ Derivation, Difference
+ Windowing
+
+ 256
+
+
+ low
+ several
+ SpectralFlux
+ intraframe
+ SF
+ physical
+ frequency
+ Derivation, Difference
+ Discrete Fourier Transform
+ Root Mean Square
+ Windowing
+
+ 1
+
+
+ low
+ speech recognition
+ LinearPredictiveCoding
+ intraframe
+ LPC
+ physical
+ frequency
+ Discrete Fourier Transform
+ Band-pass Filter (Bank)
+ Autoregression (Linear Prediction Analysis)
+ Windowing
+
+ parameterized
+
+
+ medium
+ speech recognition
+ psychoacoustic
+ PitchSynchronousZCPA
+ intraframe
+ physical
+ temporal
+ Spectral binning
+ Sum, Weighted Sum
+ Logarithm
+ Band-pass Filter (Bank)
+ Windowing
+ Root Mean Square
+ Autocorrelation
+
+ parameterized
+
+
+ high
+ speech recognition
+ PhaseSpaceFeatures
+ intraframe
+ physical
+ phase space
+ Phase Space Embedding
+ Windowing
+
+ parameterized
+
+
+ medium
+ music information retrieval
+ HarmonicDerivate
+ intraframe
+ perceptual
+ frequency
+ Derivation, Difference
+ Discrete Fourier Transform
+ Logarithm
+ Windowing
+
+ parameterized
+
+
+ low
+ speech recognition
+ LinearPredictionZCR
+ intraframe
+ physical
+ temporal
+ Spectral binning
+ Autoregression (Linear Prediction Analysis)
+ Windowing
+
+ 1
+
+
+ medium
+ music information retrieval
+ HarmonicConcentration
+ intraframe
+ perceptual
+ frequency
+ Energy Spectral Density
+ Zero-/Level Crossing Detector
+ Discrete Fourier Transform
+ Root Mean Square
+ Windowing
+
+ 1
+
+
+ high
+ several
+ psychoacoustic
+ MelscaleFrequencyCepstralCoefficients
+ intraframe
+ MFCC
+ physical
+ cepstral
+ Discrete Fourier Transform
+ Logarithm
+ Regression
+ Discrete Cosine Transform
+ Windowing
+
+ parameterized
+
+
+ low
+ several
+ SpectralCentroid
+ intraframe
+ perceptual
+ frequency
+ Mean
+ Discrete Fourier Transform
+ Logarithm
+ Regression
+ Windowing
+
+ 1
+
+
+ medium
+ audio segmentation
+ 4HzModulationHarmonicCoefficients
+ interframe
+ physical
+ modulation frequency
+ Sum, Weighted Sum
+ Band-pass Filter (Bank)
+ Autocorrelation
+ Discrete Cosine Transform
+ Windowing
+
+ 1
+
+
+ medium
+ music information retrieval
+ DWPTbasedRhythmFeature
+ interframe
+ perceptual
+ modulation frequency
+ Spectral binning
+ Root Mean Square
+ Discrete Wavelet Transform
+ Autocorrelation
+ Windowing
+
+ parameterized
+
+
+ medium
+ music information retrieval
+ BeatHistogram
+ interframe
+ perceptual
+ modulation frequency
+ Spectral binning
+ Autocorrelation
+ Discrete Wavelet Transform
+ Low-pass Filter
+ Root Mean Square
+ Windowing
+
+ 6
+
+
+ low
+ several
+ Bandwidth
+ intraframe
+ perceptual
+ frequency
+ Discrete Fourier Transform
+ Logarithm
+ Regression
+ Median
+ Windowing
+
+ 1
+
+
+ high
+ speech recognition
+ psychoacoustic
+ PerceptualLinearPrediction
+ intraframe
+ physical
+ cepstral
+ Discrete Cosine Transform
+ Autoregression (Linear Prediction Analysis)
+ Cepstral Recursion Formula
+ (Non-) Linear Weighting Function
+ Regression
+ Discrete Fourier Transform
+ Windowing
+
+ parameterized
+
+
+ medium
+ several
+ psychoacoustic
+ Sharpness
+ intraframe
+ perceptual
+ frequency
+ (Non-) Linear Weighting Function
+ Mean
+ Discrete Fourier Transform
+ Regression
+ Windowing
+
+ 1
+
+
+ low
+ music information retrieval
+ SpectralCenter
+ intraframe
+ perceptual
+ frequency
+ Energy Spectral Density
+ Harmonic Peak Detection
+ Discrete Fourier Transform
+ Windowing
+
+ 1
+
+
+ medium
+ several
+ psychoacoustic
+ MPEG7AudioSpectrumSpread
+ intraframe
+ MPEG-7
+ perceptual
+ frequency
+ Discrete Fourier Transform
+ Logarithm
+ Regression
+ Median
+ Windowing
+
+ 1
+
+
+ low
+ several
+ ZeroCrossingRate
+ intraframe
+ ZCR
+ physical
+ temporal
+ Spectral binning
+ Windowing
+
+ 1
+
+
+ high
+ speech recognition
+ psychoacoustic
+ RelativeSpectralPLP
+ intraframe
+ physical
+ cepstral
+ Exponential Function
+ Discrete Cosine Transform
+ Autoregression (Linear Prediction Analysis)
+ Cepstral Recursion Formula
+ (Non-) Linear Weighting Function
+ Logarithm
+ Regression
+ Band-pass Filter (Bank)
+ Discrete Fourier Transform
+ Windowing
+
+ parameterized
+
+
+ high
+ speech recognition
+ psychoacoustic
+ AutocorrelationMFCCs
+ intraframe
+ physical
+ cepstral
+ Autocorrelation
+ Discrete Cosine Transform
+ Low-pass Filter
+ Logarithm
+ Regression
+ Discrete Fourier Transform
+ Windowing
+
+ parameterized
+
+
+ medium
+ several
+ psychoacoustic
+ MPEG7AudioSpectrumCentroid
+ intraframe
+ MPEG-7
+ perceptual
+ frequency
+ Mean
+ Discrete Fourier Transform
+ Logarithm
+ Regression
+ Windowing
+
+ 1
+
+
+ high
+ music information retrieval
+ PitchProfile
+ intraframe
+ perceptual
+ frequency
+ Constant Q Transform
+ Spectral binning
+ Sum, Weighted Sum
+ Root Mean Square
+ Windowing
+
+ 12
+
+
+ medium
+ speech recognition
+ ModifiedGroupDelay
+ intraframe
+ physical
+ frequency
+ Low-pass Filter
+ Discrete Fourier Transform
+ Discrete Cosine Transform
+ Group Delay Function
+ Windowing
+
+ parameterized
+
+
+ medium
+ speech recognition
+ MultiresolutionEntropy
+ intraframe
+ perceptual
+ frequency
+ Normalization
+ Entropy
+ Discrete Fourier Transform
+ Regression
+ Windowing
+
+ parameterized
+
+
+ medium
+ environmental sound recognition
+ HarmonicProminence
+ intraframe
+ perceptual
+ frequency
+ Zero-/Level Crossing Detector
+ Autocorrelation
+ Windowing
+
+ 1
+
+
+ high
+ environmental sound recognition
+ MPEG-7
+ MPEG7AudioSpectrumBasis
+ interframe
+ physical
+ eigendomain
+ Independent Component Analysis
+ Normalization
+ Logarithm
+ Regression
+ Singular Value Decomposition
+ Discrete Fourier Transform
+ Windowing
+
+ parameterized
+
+
+ medium
+ several
+ MPEG-7
+ MPEG7AudioHarmonicity
+ intraframe
+ perceptual
+ frequency
+ Sum, Weighted Sum
+ Autocorrelation
+ Windowing
+
+ 2
+
+
+ medium
+ music information retrieval
+ MPEG-7
+ MPEG7HarmonicSpectralVariation
+ intraframe
+ perceptual
+ frequency
+ Zero-/Level Crossing Detector
+ Discrete Fourier Transform
+ Cross-Correlation
+ Windowing
+
+ 1
+
+
+ medium
+ music information retrieval
+ MPEG-7
+ MPEG7HarmonicSpectralCentroid
+ intraframe
+ perceptual
+ frequency
+ Mean
+ Zero-/Level Crossing Detector
+ Discrete Fourier Transform
+ Windowing
+
+ 1
+
+
+ high
+ music information retrieval
+ psychoacoustic
+ Sone
+ intraframe
+ perceptual
+ frequency
+ (Non-) Linear Weighting Function
+ Low-pass Filter
+ Logarithm
+ Regression
+ Discrete Fourier Transform
+ Windowing
+
+ parameterized
+
+
+ low
+ several
+ ShortTimeEnergy
+ intraframe
+ physical
+ temporal
+ Deviation, Sum of Differences
+ Windowing
+
+ 1
+
+
+ low
+ music information retrieval
+ MPEG-7
+ MPEG7SpectralCentroid
+ global
+ perceptual
+ frequency
+ Discrete Fourier Transform
+ Mean
+
+ 1
+
+
+ medium
+ music information retrieval
+ HarmonicEnergyEntropy
+ intraframe
+ perceptual
+ frequency
+ Zero-/Level Crossing Detector
+ Discrete Fourier Transform
+ Entropy
+ Windowing
+
+ 1
+
+
+ medium
+ music information retrieval
+ ChromaCENSFeatures
+ intraframe
+ perceptual
+ frequency
+ Normalization
+ Low-pass Filter
+ Root Mean Square
+ Band-pass Filter Bank
+ Windowing
+
+ 12
+
+
+ high
+ environmental sound recognition
+ psychoacoustic
+ RatescalefrequencyFeatures
+ interframe
+ physical
+ eigendomain
+ Discrete Wavelet Transform
+ (Non-) Linear Weighting Function
+ Band-pass Filter Bank
+ Principal Component Analysis
+ Low-pass Filter
+ Derivation, Difference
+ Root Mean Square
+ Windowing
+
+ 256
+
+
+ high
+ music information retrieval
+ BeatSpectrum
+ interframe
+ perceptual
+ modulation frequency
+ Autocorrelation
+ Low-pass Filter
+ Cross-Correlation
+ Logarithm
+ Discrete Fourier Transform
+ Windowing
+
+ parameterized
+
+
+ low
+ several
+ Volume
+ intraframe
+ physical
+ temporal
+ Power
+ Windowing
+
+ 1
+
+
+ low
+ music information retrieval
+ SpectralPeaks
+ interframe
+ physical
+ frequency
+ Derivation, Difference
+ Discrete Fourier Transform
+ Sum, Weighted Sum
+ Windowing
+
+ parameterized
+
+
+ medium
+ environmental sound recognition
+ SubbandSpectralFlux
+ intraframe
+ perceptual
+ frequency
+ Mean
+ Normalization
+ Logarithm
+ Regression
+ Derivation, Difference
+ Discrete Fourier Transform
+ Windowing
+
+ 8
+
+
+ medium
+ audio segmentation
+ PulseMetric
+ intraframe
+ perceptual
+ modulation frequency
+ Autocorrelation
+ Band-pass Filter (Bank)
+ Root Mean Square
+ Windowing
+
+ 1
+
+
+ medium
+ music information retrieval
+ PitchHistogram
+ interframe
+ perceptual
+ frequency
+ Spectral binning
+ Root Mean Square
+ Autocorrelation
+ Windowing
+
+ parameterized
+
+
+ low
+ several
+ SubbandEnergyRatio
+ intraframe
+ physical
+ frequency
+ Energy Spectral Density
+ Normalization
+ Discrete Fourier Transform
+ Regression
+ Windowing
+
+ parameterized
+
+
+ low
+ several
+ SpectralRolloff
+ intraframe
+ perceptual
+ frequency
+ Polynomial Root Finding
+ Discrete Fourier Transform
+ Windowing
+
+ 1
+
+
+ medium
+ audio segmentation
+ BandPeriodicity
+ interframe
+ perceptual
+ modulation frequency
+ Sum, Weighted Sum
+ Root Mean Square
+ Band-pass Filter (Bank)
+ Autocorrelation
+ Windowing
+
+ 4
+
+
+ medium
+ music information retrieval
+ AdaptiveTimeFrequencyTransform
+ global
+ physical
+ frequency
+ Spectral binning
+ Adaptive Time Frequency Transform
+
+ 42
+
+
+ low
+ audio segmentation
+ HarmonicCoefficient
+ intraframe
+ perceptual
+ frequency
+ Sum, Weighted Sum
+ Autocorrelation
+ Windowing
+
+ 1
+
+
+ medium
+ speech recognition
+ LinearPredictionCepstralCoefficients
+ intraframe
+ LPCC
+ physical
+ cepstral
+ Band-pass Filter (Bank)
+ Autoregression (Linear Prediction Analysis)
+ Cepstral Recursion Formula
+ Windowing
+
+ parameterized
+
+
+ high
+ fingerprinting
+ DistortionDiscriminantAnalysis
+ interframe
+ physical
+ eigendomain
+ Modulated Complex Lapped Transform
+ Logarithm
+ Principal Component Analysis
+ Windowing
+
+ 64
+
+
+ low
+ Histogram
+ Sum, Weighted Sum
+ Windowing
+ MPEG-7
+ MPEG7AudioWaveform
+ intraframe
+ physical
+ temporal
+
+ 2
+
+
+ low
+ music information retrieval
+ MPEG-7
+ MPEG7TemporalCentroid
+ interframe
+ physical
+ temporal
+ Power
+ Mean
+ Windowing
+
+ 1
+
+
+ low
+ several
+ Pitch
+ intraframe
+ perceptual
+ frequency
+ Sum, Weighted Sum
+ Autocorrelation
+ Windowing
+
+ 1
+
+
+ medium
+ speech recognition
+ psychoacoustic
+ ZeroCrossingPeakAmplitudes
+ intraframe
+ physical
+ temporal
+ Spectral binning
+ Band-pass Filter (Bank)
+ Logarithm
+ Root Mean Square
+ Windowing
+
+ parameterized
+
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-CLAM.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-CLAM.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,87 @@
+@prefix CLAM: .
+@prefix dc: .
+@prefix local: .
+@prefix rdfs: .
+
+CLAM:Decrease a rdfs:Resource ;
+ dc:description "a measure of the amount of decrease in the signal energy" ;
+ local:tag "Audio" .
+
+CLAM:Energy a rdfs:Resource ;
+ dc:description "the squared sum of audio samples amplitudes",
+ "the squared sum of spectral power distribution values" ;
+ local:tag "Audio",
+ "Spectral" .
+
+CLAM:GeometricMean a rdfs:Resource ;
+ dc:description "the geometric mean for the spectral power values sequence" ;
+ local:tag "Spectral" .
+
+CLAM:HighFrequencyContent a rdfs:Resource ;
+ dc:description "sum of the squared spectrum magnitude multiplied by the wave number of the bin" ;
+ local:tag "Spectral" .
+
+CLAM:LogAttackTime a rdfs:Resource ;
+ dc:description "the base 10 logarithm of the rise time" ;
+ local:tag "Audio" .
+
+CLAM:LowFreqEnergyRelation a rdfs:Resource ;
+ dc:description "the ratio between the energy over 0-100 Hz band and the whole spectrum energy" ;
+ local:tag "Spectral" .
+
+CLAM:MFCC a rdfs:Resource ;
+ local:tag "Spectral" .
+
+CLAM:MagnitudeKurtosis a rdfs:Resource ;
+ local:tag "Spectral" .
+
+CLAM:MagnitudeSkewness a rdfs:Resource ;
+ local:tag "Spectral" .
+
+CLAM:MaxMagFreq a rdfs:Resource ;
+ dc:description "frequency of the maximum magnitude of the spectrum" ;
+ local:tag "Spectral" .
+
+CLAM:Mean a rdfs:Resource ;
+ dc:description "the mean value of the absolute value of the audio samples amplitude" ;
+ local:tag "Audio" .
+
+CLAM:RiseTime a rdfs:Resource ;
+ dc:description "the time duration between the signal reached 2% of it maximum value to the time it reaches 80% of its maximum value" ;
+ local:tag "Audio" .
+
+CLAM:Rolloff a rdfs:Resource ;
+ dc:description "The spectral roll-off point is the frequency value so that the 85% of the spectral energy is contained below it" ;
+ local:tag "Spectral" .
+
+CLAM:SpectralCentroid a rdfs:Resource ;
+ dc:description "the frequency where the center of mass of the spectral power distribution lies" ;
+ local:tag "Spectral" .
+
+CLAM:SpectralFlatness a rdfs:Resource ;
+ local:tag "Spectral" .
+
+CLAM:SpectralMean a rdfs:Resource ;
+ dc:description "the spectral power mean value." ;
+ local:tag "Spectral" .
+
+CLAM:SpectralSlope a rdfs:Resource ;
+ dc:description "the amount of decreasing of the spectral magnitude" ;
+ local:tag "Spectral" .
+
+CLAM:SpectralSpread a rdfs:Resource ;
+ dc:description "the variation of the spectrum around its mean value." ;
+ local:tag "Spectral" .
+
+CLAM:TemporalCentroid a rdfs:Resource ;
+ dc:description "time where signal energy is \"concentrated\"" ;
+ local:tag "Audio" .
+
+CLAM:Variance a rdfs:Resource ;
+ dc:description "the variance of audio samples amplitude" ;
+ local:tag "Audio" .
+
+CLAM:ZeroCrossingRate a rdfs:Resource ;
+ dc:description "a measure of the number of time the signal value cross the zero axe, averaged over the whole signal" ;
+ local:tag "Audio" .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-MIREX.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-MIREX.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,95 @@
+@prefix MIREX: .
+@prefix local: .
+@prefix rdfs: .
+
+MIREX:CorrelationPattern a rdfs:Resource ;
+ local:author "Klaus Seyerlehner" ;
+ local:feature "Correlation Pattern" ;
+ local:source "MIREX 2012" .
+
+MIREX:DecorrelatedFilterBanks a rdfs:Resource ;
+ local:author "Shin-Cheol Lim" ;
+ local:feature "Decorrelated Filter Banks" ;
+ local:source "MIREX" .
+
+MIREX:DeltaSpectralPattern a rdfs:Resource ;
+ local:author "Klaus Seyerlehner" ;
+ local:feature "Delta Spectral Pattern" ;
+ local:source "MIREX 2012" .
+
+MIREX:FluctuationPatterns a rdfs:Resource ;
+ local:author "Franz de Leon" ;
+ local:feature "Fluctuation Patterns" ;
+ local:source "MIREX" .
+
+MIREX:GeorgeTzanetakisModel a rdfs:Resource ;
+ local:author "Klaus Seyerlehner" ;
+ local:feature "George Tzanetakis Model" ;
+ local:source "MIREX 2012" .
+
+MIREX:LocalSingleGaussianModel a rdfs:Resource ;
+ local:author "Klaus Seyerlehner" ;
+ local:feature "Local Single Gaussian Model" ;
+ local:source "MIREX 2012" .
+
+MIREX:LogarithmicFluctuationPattern a rdfs:Resource ;
+ local:author "Klaus Seyerlehner" ;
+ local:feature "Logarithmic Fluctuation Pattern" ;
+ local:source "MIREX 2012" .
+
+MIREX:ModulationFrequencyVarianceDescriptor a rdfs:Resource ;
+ local:author "Ponce",
+ "T. Lidy" ;
+ local:feature "Modulation Frequency Variance Descriptor" ;
+ local:source "MIREX 2008" .
+
+MIREX:OctaveBasedSpectralContrast a rdfs:Resource ;
+ local:author "Shin-Cheol Lim" ;
+ local:feature "Octave-based Spectral Contrast" ;
+ local:source "MIREX" .
+
+MIREX:PrincipalMelSpectrumComponents a rdfs:Resource ;
+ local:author "Philippe Hamel" ;
+ local:feature "Principal Mel-spectrum Components" ;
+ local:source "MIREX" .
+
+MIREX:RhythmHistogram a rdfs:Resource ;
+ local:author "T. Lidy" ;
+ local:feature "Rhythm Histogram" ;
+ local:source "MIREX 2008" .
+
+MIREX:RhythmPattern a rdfs:Resource ;
+ local:author "T. Lidy" ;
+ local:feature "Rhythm Pattern" ;
+ local:source "MIREX 2008" .
+
+MIREX:SpectralContrastPattern a rdfs:Resource ;
+ local:author "Klaus Seyerlehner" ;
+ local:feature "Spectral Contrast Pattern" ;
+ local:source "MIREX 2012" .
+
+MIREX:SpectralPattern a rdfs:Resource ;
+ local:author "Klaus Seyerlehner" ;
+ local:feature "Spectral Pattern" ;
+ local:source "MIREX" .
+
+MIREX:StatisticalSpectrumDescriptor a rdfs:Resource ;
+ local:author "T. Lidy" ;
+ local:feature "Statistical Spectrum Descriptor" ;
+ local:source "MIREX 2008" .
+
+MIREX:TemporalRhythmHistogram a rdfs:Resource ;
+ local:author "T. Lidy" ;
+ local:feature "Temporal Rhythm Histogram" ;
+ local:source "MIREX 2008" .
+
+MIREX:TemporalStatisticalSpectrumDescriptor a rdfs:Resource ;
+ local:author "T. Lidy" ;
+ local:feature "Temporal Statistical Spectrum Descriptor" ;
+ local:source "MIREX 2008" .
+
+MIREX:VarianceDeltaSpectralPattern a rdfs:Resource ;
+ local:author "Klaus Seyerlehner" ;
+ local:feature "Variance Delta Spectral Pattern" ;
+ local:source "MIREX 2012" .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-MIRToolbox.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-MIRToolbox.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,116 @@
+@prefix MIRToolbox: .
+@prefix dc: .
+@prefix local: .
+@prefix rdfs: .
+
+MIRToolbox:Attack a rdfs:Resource ;
+ dc:description "estimates the beginning of the attack phase of a note by locating the local minimum before the maximum corresponding to the onset" ;
+ local:tag "Timbre" ;
+ rdfs:comment "These can have start time *and end time*" .
+
+MIRToolbox:AttackLeap a rdfs:Resource ;
+ dc:description "estimates the amplitude difference between the beginning and the end of the attack phase" ;
+ local:tag "Timbre" .
+
+MIRToolbox:AttackSlope a rdfs:Resource ;
+ dc:description "average slope of attack phase, computed either as a simple ratio, or a Gaussian-weighted average to emphasise the middle of the attack" ;
+ local:tag "Timbre" .
+
+MIRToolbox:BeatSpectrum a rdfs:Resource ;
+ dc:description "a measure of acoustic self-similarity as a function of time lag, computed from the similarity matrix" ;
+ local:tag "Rhythm" .
+
+MIRToolbox:Brightness a rdfs:Resource ;
+ dc:description "The proportion of energy above a given frequency" ;
+ local:tag "Timbre" .
+
+MIRToolbox:Chromagram a rdfs:Resource ;
+ dc:description "shows the distribution of energy along the pitches or pitch classes" ;
+ local:tag "Tonality" .
+
+MIRToolbox:EventDensity a rdfs:Resource ;
+ dc:description "estimates the average frequency of events, i.e., the number of note onsets per second" ;
+ local:tag "Rhythm" .
+
+MIRToolbox:HarmonicChangeDetectionFunction a rdfs:Resource ;
+ dc:description "the flux of the tonal centroid" ;
+ local:tag "Tonality" .
+
+MIRToolbox:Inharmonicity a rdfs:Resource ;
+ dc:description "the amount of partials that are not multiples of the fundamental frequency, takes into account the amount of energy outside the ideal harmonic series" ;
+ local:tag "Pitch" .
+
+MIRToolbox:Irregularity a rdfs:Resource ;
+ dc:description "The degree of variation of the successive peaks of the spectrum" ;
+ local:tag "Timbre" .
+
+MIRToolbox:Key a rdfs:Resource ;
+ dc:description "The best candidate key" ;
+ local:tag "Tonality" .
+
+MIRToolbox:KeySOM a rdfs:Resource ;
+ dc:description "Projects the chromagram into a self-organizing map" ;
+ local:tag "Tonality" .
+
+MIRToolbox:KeyStrength a rdfs:Resource ;
+ dc:description "The probability distribution across possible keys" ;
+ local:tag "Tonality" .
+
+MIRToolbox:LowEnergy a rdfs:Resource ;
+ dc:description "percentage of frames showing less than average energy" ;
+ local:tag "Dynamics" .
+
+MIRToolbox:MFCC a rdfs:Resource ;
+ local:tag "Timbre" .
+
+MIRToolbox:MIDI a rdfs:Resource ;
+ dc:description "estimates MIDI note value based on segmentation and pitch detection" ;
+ local:tag "Pitch" .
+
+MIRToolbox:Mode a rdfs:Resource ;
+ dc:description "Major vs. Minor, calculated as the strength difference between the best major and best minor key candidates" ;
+ local:tag "Tonality" .
+
+MIRToolbox:NoteOnset a rdfs:Resource ;
+ dc:description "note onset times" ;
+ local:tag "Rhythm" .
+
+MIRToolbox:Pitch a rdfs:Resource ;
+ dc:description "Pitch estimated via ACF, autocorrelation spectrum or cepstrum, or a combination" ;
+ local:tag "Pitch" .
+
+MIRToolbox:PulseClarity a rdfs:Resource ;
+ dc:description "estimates the rhythmic clarity, indicating the strength of the beats estimated by the tempo function" ;
+ local:tag "Rhythm" .
+
+MIRToolbox:RMSEnergy a rdfs:Resource ;
+ dc:description "root mean square energy" ;
+ local:tag "Dynamics" .
+
+MIRToolbox:RhythmicFluctuation a rdfs:Resource ;
+ dc:description "Rhythmic periodicity along auditory channels" ;
+ local:tag "Rhythm" .
+
+MIRToolbox:Rolloff a rdfs:Resource ;
+ dc:description "The frequency below which 85% of the energy is contained. The percentage may be user-chosen" ;
+ local:tag "Timbre" .
+
+MIRToolbox:Roughness a rdfs:Resource ;
+ dc:description "The average dissonance between all pairs of peaks in the spectrum" ;
+ local:tag "Timbre" .
+
+MIRToolbox:SpectralFluxOnsetDetectionFunction a rdfs:Resource ;
+ dc:description "Use peaks of spectral flux to detect onsets" ;
+ local:tag "Rhythm" .
+
+MIRToolbox:Tempo a rdfs:Resource ;
+ dc:description "derived from calculated onsets with ACF, spectrum or both" ;
+ local:tag "Rhythm" .
+
+MIRToolbox:TonalCentroid a rdfs:Resource ;
+ dc:description "Calculates the 6-dimensional tonal centroid vector from the chromagram" ;
+ local:tag "Tonality" .
+
+MIRToolbox:ZeroCrossingRate a rdfs:Resource ;
+ local:tag "Timbre" .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-Marsyas.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-Marsyas.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,207 @@
+@prefix dc: .
+@prefix rdfs: .
+
+ a rdfs:Resource ;
+ dc:description "Azimuth Discrimination and Resynthesis (ADRess) implementation, which takes a stereo input (i.e. input is expected to be the output of a parallel of two Spectrum MarSystems, one for each stereo channel), and outputs the phase vector and frequency dependent nulls matrix for each channel using the following format: [bin_phases_l][AZl] [bin_phases_r][AZr] This algorithm was proposed by Dan Barry et al at the DAfX04, \"Sound Source Separation: azimuth discrimination and resynthesis\". The algorithm exploits the use of pan pot as a means to achieve image localisation within stereophonic recordings, assuming only an interaural intensity difference exists between left and right channels for a single source. A gain scaling and phase cancellation technique is then used to expose frequency dependent nulls across the azimuth domain, from which source separation and resynthesis may be carried out. Controls: - \\b mrs_natural/beta [w] : Sets the azimuth resolution" .
+
+ a rdfs:Resource ;
+ dc:description "Takes the output of the ADRess (i.e. the stereo azimuth-frequency maps) and outputs a single channel spectrum of the part of the freq-azimuth plane selected by the d and H controls. This can then be inverse transformed back into time domain for resynthesis purposes. Controls: - \\b mrs_real/d [w] : value between 0.0~1.0, used for selecting the portion of the azimuth-frequency plane to be extracted - \\b mrs_real/H [w] : sets the azimuth subspace width (in percentage of total width of the azimuth plane)" .
+
+ a rdfs:Resource ;
+ dc:description "Takes the output of the ADRess (i.e. the panning-frequency maps) and outputs the panning coefficient for each spectral bin (N/2+1 bins)." .
+
+ a rdfs:Resource ;
+ dc:description "Average Magnitude Difference Function Computer the average magnitude difference function which can then be used for pitch detection by detecting the location of valleys." .
+
+ a rdfs:Resource ;
+ dc:description "Calculate the maximum absolute value for each observation signal (per slice). For each observation channel in each given slice, the maximum absolute value is calculated. This MarSystem has no extra controls." .
+
+ a rdfs:Resource ;
+ dc:description "'Box-cutting' routine to generate dense features Author : Thomas Walters Ported to Marsyas by Steven Ness The original source code for these functions in AIM-C can be found at: http://code.google.com/p/aimc/" .
+
+ a rdfs:Resource ;
+ dc:description "Slaney's gammatone filterbank Author : Thomas Walters Ported to Marsyas by Steven Ness This is the version of the IIR gammatone used in Slaney's Auditory toolbox. The original verison as described in Apple Tech. Report #35 has a problem with the high-order coefficients at low centre frequencies and high sample rates. Since it is important that AIM-C can deal with these cases (for example for the Gaussian features), I've reiplemeted Slaney's alternative version which uses a cascade of four second-order filters in place of the eighth-order filter. The original source code for these functions in AIM-C can be found at: http://code.google.com/p/aimc/" .
+
+ a rdfs:Resource ;
+ dc:description "Halfwave rectification, compression and lowpass filtering Author Thomas Walters Ported to Marsyas by Steven Ness The original source code for these functions in AIM-C can be found at: http://code.google.com/p/aimc/" .
+
+ a rdfs:Resource ;
+ dc:description "Halfwave rectification, compression and lowpass filtering Author Thomas Walters Ported to Marsyas by Steven Ness Made more Marsyas like by George Tzanetakis The original source code for these functions in AIM-C can be found at: http://code.google.com/p/aimc/" .
+
+ a rdfs:Resource ;
+ dc:description "Local maximum strobe criterion: decaying threshold with timeout Author : Thomas Walters Ported to Marsyas by Steven Ness The original source code for these functions in AIM-C can be found at: http://code.google.com/p/aimc/" .
+
+ a rdfs:Resource ;
+ dc:description "Time-domain AimPZFC Dick Lyon's Pole-Zero Filter Cascade - implemented in C++ by Tom Walters from the AIM-MAT module based on Dick Lyon's code. Ported to Marsyas from AIM-C by Steven Ness (sness@sness.net). The original source code for these functions in AIM-C can be found at: http://code.google.com/p/aimc/" .
+
+ a rdfs:Resource ;
+ dc:description "Time-domain AimPZFC2 Dick Lyon's Pole-Zero Filter Cascade - implemented in C++ by Tom Walters from the AIM-MAT module based on Dick Lyon's code. Ported to Marsyas from AIM-C by Steven Ness (sness@sness.net). AimPZFC2 is a re-write of the AimPZFC to be more Marsyas like. The original source code for these functions in AIM-C can be found at: http://code.google.com/p/aimc/" .
+
+ a rdfs:Resource ;
+ dc:description "Stabilised auditory image Author : Thomas Walters Ported to Marsyas by Steven Ness The original source code for these functions in AIM-C can be found at: http://code.google.com/p/aimc/" .
+
+ a rdfs:Resource ;
+ dc:description "Size-shape image (aka the 'sscAI') Author : Thomas Walters Ported to Marsyas by Steven Ness The original source code for these functions in AIM-C can be found at: http://code.google.com/p/aimc/" .
+
+ a rdfs:Resource ;
+ dc:description "Vector quantization for dense to sparse features Author : Thomas Walters Ported to Marsyas by Steven Ness The original source code for these functions in AIM-C can be found at: http://code.google.com/p/aimc/" .
+
+ a rdfs:Resource ;
+ dc:description "Pitch detection using the YIN algorithm This algorithm was developped by A. de Cheveigne and H. Kawahara and published in: De Cheveigne, A., Kawahara, H. (2002) \"YIN, a fundamental frequency estimator for speech and music\", J. Acoust. Soc. Am. 111, 1917-1930. See http://recherche.ircam.fr/equipes/pcm/pub/people/cheveign.html This code was adapted from aubio (http://aubio.org) by sness. Controls: - \\b mrs_real/tolerance [w] : sets the tolerance of the yin algorithm" .
+
+ a rdfs:Resource ;
+ dc:description "Compute the generalized autocorrelation of input window Computes the generalized autocorrelation (with optional magnitude compression) using the Fast Fourier Transform (FFT). Controls: - \\b mrs_bool/aliasedOutput [w] : by default, this control is set to true and the output of AutoCorrelation will be an alised time domain signal (as used by the original Marsyas0.1 code implemented by George Tzanetakis - MUST CHECK IF THIS MAKES SENSE!). Setting this control to false, the FFTs will be computed using the next power of 2 of the inSamples*2+1, which avoids alising in the iFFT step. In this mode, only the first inSamples of the autocorrleation function will be output (since the remaining ones are mirrored versions or zero valued). - \\b mrs_bool/setr0to1\" [w]: if set to true, the output will be normalized so that r_xx(0) = 1 Had to use a weird name because there already was a normalize control [AL]" .
+
+ a rdfs:Resource ;
+ dc:description "BeatHistogram Calculate Beat Histogram. The input should be the autocorrelation of either the time waveform or some kind of onset detection function." .
+
+ a rdfs:Resource ;
+ dc:description "BeatHistogramFromPeaks Calculate BeatHistograms from peaks represented as pairs of periodicity/amplitude (typically from an autocorrelation function)." .
+
+ a rdfs:Resource ;
+ dc:description "Given a periodicity calculate best matching phase" .
+
+ a rdfs:Resource ;
+ dc:description "Centroid of each time slice of observations Centroid computes the centroid of the observations for each time sample. The center is defined as the normalized first moment (center of gravity) of the observation vector." .
+
+ a rdfs:Resource ;
+ dc:description "Computes the cross correlation of an input. Accepts N observations and returns N-1 observations, with each observation being the cross correlation of the inputs n and n-1. Controls: \"mrs_string/mode\" : This control sets the type of cross correlation. \"general\" is the default, and will compute the generalized cross correlation. \"phat\" will compute the generalized cross correlation with phase transform \"ml\" will compute a maximum likelihood cross correlation. This works well specifically for time delay estimation in noisy or reverberant environments. Note: inSamples should be 2^k or fft will not work properly. \\author Gabrielle Odowichuk" .
+
+ a rdfs:Resource ;
+ dc:description "Daubechies4 WaveletStep Applies the Daubechies 4-coefficient wavelet filter as a WaveletStep for the WaveletPyramid algorithm. The code is is based on the Numerical Recipies wavelet code." .
+
+ a rdfs:Resource ;
+ dc:description "compute the Energy of the input observations into one column" .
+
+ a rdfs:Resource ;
+ dc:description "Azimuth Discrimination and Resynthesis (EnhADRess) implementation, which takes a stereo input (i.e. input is expected to be the output of a parallel of two Spectrum MarSystems, one for each stereo channel), and outputs the magnitudes, phases and panning indexes for N/2+1 bins, stacked vertically: [Mag] [Phases] [Pan] This enhanced version of the ADRess algorithm was proposed by Cooney et al, \"An Enhanced implemantation of the ADRess Music Source Separation Algorithm\", 121st AES Convention, October 2006." .
+
+ a rdfs:Resource ;
+ dc:description "Takes the output of the enhADRess and outputs the panning coefficient for each spectral bin (N/2+1 bins)." .
+
+ a rdfs:Resource ;
+ dc:description "Compute F0s in input spectrum \\author Matthias Varewyck \\date 20090518 Controls: - \\b mrs_natural NrOfHarmonics [rw] : nr. of harmonics taken into account (excl. F0) - \\b mrs_real F0Weight [rw] : balance between F0 and higher harmonics - \\b mrs_real Attenuation [rw] : attenuation of higher harmonics - \\b mrs_real Tolerance_ [rw] : tolerance for harmonics to be assigned to F0 - \\b mrs_real LowestFo_ [rw] : lowest possible F0 - \\b mrs_real ChordEvidence_ [r] : evidence that input spectrum includes chord" .
+
+ a rdfs:Resource ;
+ dc:description "Flux calculate the flux between the current and prev. spectrum (e.g. output of PowerSpectrum) The flux is defined as the norm of the difference vector between two successive magnitue/power spectra, although different implementations are possible. Controls: - \\b mrs_string/mode [w]: select from the different available implementations for Flux: \"marsyas\" and \"DixonDAFX06\" - \\b mrs_bool/reset [rw] : clear and reset the memory buffer" .
+
+ a rdfs:Resource ;
+ dc:description "Krumhansl-Schmuckler Key-Finding Algorithm Performs simple chord detection using the Krumhansl-Schmuckler Key-Finding Algorithm. The input is a pitch class profile or chroma vector with 12 values one for each chromatic note. Controls:" .
+
+ a rdfs:Resource ;
+ dc:description "Kurtosis Calculate the Kurtosis of the input observations. Typically used for characterizing the magnitude spectrum." .
+
+ a rdfs:Resource ;
+ dc:description "Compute Warped LPC coefficients, Pitch and Power [STILL UNDER TESTING!]. Linear Prediction Coefficients (LPC). Features commonly used in Speech Recognition research. This class is a modification of the original Marsyas0.1 LPC class. The following differences apply: - order now reflects the LPC order (and returns \\ coefficients plus pitch and gain) - It is possible to define a pole-shifting parameter, gamma (default value = 1.0 => no shifting) - It is possible to define a warping factor, lambda (defualt value = 0.0 => no warping) Code by Lus Gustavo Martins - lmartins@inescporto.pt May 2006" .
+
+ a rdfs:Resource ;
+ dc:description "Convert LPC coefficients to Cepstrum coefficients. This MarSystem is expecting to receive at its input LPC coefficients + Pitch + Power, as output by the LPC MarSystem (see LPC.cpp/.h). It only converts the LPC coefficients to cepstral coefficients and ignores the pitch value received from LPC. Code by: Lus Gustavo Martins - lmartins@inescporto.pt November 2006" .
+
+ a rdfs:Resource ;
+ dc:description "Compute Linear Spectral Pair (LSP) coefficients Takes the output of ::LPC() and calculates the corresponding LSP values. See the LPC class implementation. Cobe by Lus Gustavo Martins - lmartins@inescporto.pt May 2006" .
+
+ a rdfs:Resource ;
+ dc:description "MFCC Mel-Frequency Cepstral Coefficients. Takes as input the N/2+1 spectrum Magnitude points output by PowerSpectrum. Mel-Frequency cepstral coefficients are features frequently used in Speech Recognition. The code is based on the corresponding function in the Auditory Toolbox by Malcolm Slaney. \\see Spectrum, PowerSpectrum Controls: - \\b mrs_natural/coefficients [w]: the number of cepstral coefficients to calculate." .
+
+ a rdfs:Resource ;
+ dc:description "Calculate k maximums and their positions The output is : max1, argmax1, max2, argmax2, ...." .
+
+ a rdfs:Resource ;
+ dc:description "Calculate the maximum and minimum values for each observation signal (per slice). For each observation channel in each given slice, the maximum and minimum values is calculated. This MarSystem has no extra controls." .
+
+ a rdfs:Resource ;
+ dc:description "Mean calculate the mean of each row of observations" .
+
+ a rdfs:Resource ;
+ dc:description "Calculates the mean absolute deviation" .
+
+ a rdfs:Resource ;
+ dc:description "MeddisHairCell for auditory models Directed port from the Auditory toolbox by Malcolm Slaney" .
+
+ a rdfs:Resource ;
+ dc:description "Median calculate the median of each row of observations" .
+
+ a rdfs:Resource ;
+ dc:description "Calculate k minimums and their positions The output is : min1, argmin1, min2, argmin2, ...." .
+
+ a rdfs:Resource ;
+ dc:description "Perform Principal Component Analysis Perform Principal Component Analysis (PCA) on all samples of the incoming realvec of data. The correlation method is taken, with a correlation matrix computed over all samples within the single input realvec. Eigenvalue/Eigenvector calculation is by the QL algorithm (ie. not suitable when the correlation matrix is singular or near singular). Output is the set of input samples projected onto the top \"npc\" (a MarSystem control) principal components." .
+
+ a rdfs:Resource ;
+ dc:description "Compute peaks in observation vector \\author Matthias Varewyck \\date 20090518 Controls: - \\b mrs_natural/HystLength [rw] : .. - \\b mrs_real/HystFactor [rw] : .." .
+
+ a rdfs:Resource ;
+ dc:description "Pick peaks out of signal Peaker is used to select peaks(or valleys) from the input vector. Various parameters of the peak selection process can be adjusted. Controls: - \\b mrs_real/peakSpacing [w] : expressed in percentage of total vector length and is how much spacing you allow between the peaks - \\b mrs_real/peakStrength [w] : threshold compared to the RMS of the vector (should be renamed to peakStrengthRelRms to keep naming consistent, but this might break existing systems) - \\b mrs_real/peakStrengthAbs [w] : absolute threshold (might make sense e.g. for normalized spectra) - \\b mrs_real/peakStrengthRelMax [w] : threshold compared to global max of the vector (range: 0...1, example: 0.001 if all peaks with a level of more than 60dB below the maximum should be discarded - \\b mrs_real/peakStrengthRelThresh [w] : threshold compared to an adaptive threshold of the vector (lp filtered version of the signal); value is a factor that moves threshold up and down, e.g. value = 2 means that the lp filtered signal is moved up by 6dB - \\b mrs_real/peakStrengthTreshLpParam [w] : coefficient for the single pole lowpass for computing the adaptive threshold (between 0...1) - \\b mrs_natural/peakStart [w] : expressed in absolute positions of the vector and it just to adjust what part of the vector will be considered - \\b mrs_natural/peakEnd [w] : expressed in absolute positions of the vector length and it just to adjust what part of the vector will be considered - \\b mrs_natural/interpolation [w] : TODO - mlagrange? [!] - \\b mrs_real/peakGain [w] : TODO - mlagrange? [!]" .
+
+ a rdfs:Resource ;
+ dc:description "Detects if input contains a onset point PeakerOnset is based on the onset peak picking algorithm presented in: Dixon, S. (2006). Onset detection revisited. In Proc. International Conference on Digital Audio Effects (DAFx), Montreal, Canada. It takes as input an onset function over time (i.e. a row vector with the times series of a onset function like flux) and evaluates a specific point for onset presence, as below: Input = [zzzzzzzzzXyyy] Point \"X\" at the input will be evaluated. The onsetWinSize control specifies a \"look ahead\" parameter, i.e. how many samples (represented above as \"y\") after \"X\" will be used for evaluating if it is an onset or not (i.e. look ahead samples). Controls: - \\b mrs_natrual/lookAheadSamples [w]: specifies the \"look ahead\" nr of \"samples\" (the number of \"y\"s in the above example ) for the detection of an onset at the input. - \\b mrs_real/threshold [w]: specifies threshold (in % of local mean) for onset detection - \\b mrs_real/confidence [r]: outputs the confidence that point \"X\" is an onset (it will 0.0 if it is not detected as an onset) - \\b mrs_bool/onsetDetected [r]: flags if an onset was detected on point \"X\"." .
+
+ a rdfs:Resource ;
+ dc:description "Transform pitch to chroma - input = amplitude spectrum with peaks at frequency bins that represent pitches and values that represent evidences - output = chroma profile with chroma values ordered according to the circle of fifths, i.e. A, E,.. D \\author Matthias Varewyck \\date 20090518 Controls: - \\b mrs_real/SampleRate [rw] : sample rate of the input spectrum - \\b mrs_real/LowestPitch [rw] : lowest pitch taken into account - \\b mrs_natural/NotesPerOctave [rw] : nr. of notes per octave ([f 2*f]) - \\b mrs_natural/NrOfNotes [rw] : total nr. of notes to be taken into account - \\b mrs_natural/RefChromaIndex [rw] : index in chroma vector of the ref. pitch (= 440Hz)" .
+
+ a rdfs:Resource ;
+ dc:description "Difference between detected and expected pitch Place this in a series after Yin (or any other pitch-detection MarSystem), and feed it the expected pitch as a control. Outputs the difference as a midi pitch value. Controls: - \\b mrs_real/expectedPitch [w] : expected pitch - \\b mrs_bool/ignoreOctaves [w] : useful if the pitch detection algorithm has octave errors, but is otherwise relatively accurate (default false) - \\b mrs_bool/absoluteValue [w] : outputs the absolute difference (default false)" .
+
+ a rdfs:Resource ;
+ dc:description "compute the RMS Power of the input observations into one column" .
+
+ a rdfs:Resource ;
+ dc:description "PowerSpectrum computes the magnitude/power of the complex spectrum Computes the magnitude/power/decibels/powerdensity of a complex spectrum (as output from the Spectrum MarSystem - see its documentation for info about the spectrum format used in Marsyas). PowerSpectrum takes N/2+1 complex spectrum bins and computes the corresponding N/2+1 power/magnitude/decibels/powerdensity real values. Controls: - \\b mrs_string/spectrumType [w] : choose between \"power\", \"magnitude\", \"decibels\", \"logmagnitude\" (for 1+log(magnitude*1000), \"logmagnitude2\" (for 1+log10(magnitude)) and \"powerdensity\" computations \\see Spectrum" .
+
+ a rdfs:Resource ;
+ dc:description "PowerToAverageRatio (or Power-to-Average Ratio) of a window This calculates the PAR for a complete window of samples; it is similar to SCF (Spectral Crest Factor), however SCF calculates the PAR in various frequency bands of observations." .
+
+ a rdfs:Resource ;
+ dc:description "Rms energy of realvec Simple MarSystem example. Calculate the RMS energy of a realvec" .
+
+ a rdfs:Resource ;
+ dc:description "Rolloff of each time slice of observations Rolloff computes the rolloff of the observations for each time samle. It is defined as the frequency for which the sum of magnitudes of its lower frequencies are equal to percentage of the sum of magnitudes of its higher frequencies." .
+
+ a rdfs:Resource ;
+ dc:description "Running calculation (across slices) of the autocorrelation values. This MarSystem calculates the autocorrelation function of the input signal defined by successive input slices. Unlike the AutoCorrelation MarSystem, the calculations are done across slice boundaries in a seamless fashion (RunningAutocorrelation keeps an internal buffer of the appropriate number of samples from previous slices to implement this feature). Calculations are done in time domain for time lags from 0 to a user defined maximum lag (in number of samples). Note that this assumes that the input slices are non overlapping slices. The autocorrelation values are laid out in the output slice along the time/samples dimension from lag zero to the maximum lag. Multiple input observation channels are supported. For example, if there are two input channels and the maximum lag is 4, the output slice will have two rows and five (not four) columns: \\f[\\begin{array}{ccccc} R_{xx}[0] & R_{xx}[1] & R_{xx}[2] & R_{xx}[3] & R_{xx}[4] \\\\ R_{yy}[0] & R_{yy}[1] & R_{yy}[2] & R_{yy}[3] & R_{yy}[4] \\\\ \\end{array}\\f] with \\f$R_{xx}[n]\\f$ the autocorrelation of the first channel for lag \\f$n\\f$ and \\f$R_{yy}[n]\\f$ the autocorrelation of the second channel. TODO: support overlap between slices (e.g. provide a control for skipping a certain amount of samples). Controls: - \\b mrs_natural/maxLag: the maximum time lag (in samples) to calculate - \\b mrs_bool/normalize: normalize the autocorrelation values on the value for lag = 0 (which is the energy of the signal). Note that the autocorrelation value for lag 0 will consequently be always 1 (unless the input signal is 0 everywhere). - \\b mrs_bool/doNotNormalizeForLag0: when normalizing the autocorrelation values, do not normalize the value for lag 0. - \\b mrs_bool/clear: clear the internal buffers to start fresh. - \\b mrs_bool/unfoldToObservations: instead of putting the autocorrelation values along the time/samples axis in the slice, they can also be laid out along the observation axis. Using the example from above, the output slice will have one column and 10 rows with values \\f$R_{xx}[0], R_{xx}[1], \\ldots, R_{xx}[4], R_{yy}[0], R_{yy}[1], \\ldots, R_{yy}[4] \\f$" .
+
+ a rdfs:Resource ;
+ dc:description "Gathers the running average, variance, standard deviation, etc. Outputs the running average and standard deviation of all the input so far. Controls: - \\b mrs_bool/enableMean: enable outputting of the mean values (on by default). - \\b mrs_bool/enableStddev: enable outputting of the standard deviation values (on by default). - \\b mrs_bool/enableSkewness: enable outputting of the skewness values (off by default). - \\b mrs_bool/clear: clear the internal buffers to start fresh. - \\b mrs_book/clearPerTick: clear the buffers at the start of each tick. This disables the \"running\" property of the calculations. \\todo: add kurtosis \\todo: add option to output running energy (we're calculating it anyway)" .
+
+ a rdfs:Resource ;
+ dc:description "Compute SNR and variations Computes the SNR between two mono audio signals. One signal is observation 0 and the other is observation 1. The output is: observation 0 is the Signal/Noise ratio in dB 10 * log10(\\frac{\\sum A^2}{\\sum A-B}) observation 1 is the SNR with optimized gain factor 10 * log10(\\frac{1}{1 - (\\frac{sum A B}{\\sqrt{\\sum A^2 \\sum B^2}})}) Controls: - \\b mrs_string/mode [rw] : sets the gain multiplier." .
+
+ a rdfs:Resource ;
+ dc:description "Calculates a single spectral flatness value. Similar to SFM, but that marsystem splits the observations into bands, whereas this one uses the whole range of observations to generate one number. It may be used to 'narrow in' on a specific range by putting a RemoveObservations marsystem before it." .
+
+ a rdfs:Resource ;
+ dc:description "Compute the complex spectrum of input window Computes the complex spectrum (N/2+1 points) of the input window using the Fast Fourier Transform (FFT). The output is a N-sized column vector (where N is the size of the input audio vector), using the following format: [Re(0), Re(N/2), Re(1), Im(1), Re(2), Im(2), ..., Re(N/2-1), Im(N/2-1)] Note that the DC and Nyquist frequencies only have real part, and are output as the two first coefficients in the vector. Overall, the output spectrum has N/2+1 unique points, corresponding to the positive half of the complex spectrum. \\note Only the first observation input channel is processed, the rest (if any) is ignored. \\see PowerSpectrum, fft" .
+
+ a rdfs:Resource ;
+ dc:description "Transform an (amplitude) spectrum to a chroma profile \\author Matthias Varewyck \\date 20090518 \\todo - Check if parameters are independent on input sample rate (~= 8kHz) - Include check if provided (amplitude) spectrum was correctly computed - Include correct error handling (conform Marsyas rules) - Let the lowest F0 be higher than the diapason - Introduce a highest F0 additional to a lowest F0 - Add \"fan in combinator\" to simplify actual chroma profile computation This class implements the conversion of an (amplitude) spectrum to a chroma profile as described in \"a novel chroma representation of polyphonic music based on multiple pitch tracking techniques\" which was presented at the 16th ACM International Conference on Multimedia. The method computes the set of pitches that best explains the salient frequencies present in the (amplitude) spectrum. The method results in (1) a chroma profile and (2) a chord evidence. (1) The chroma profile represents the normalized pitches after they were folded to one octave (2) The chord evidence represents the probability that a chord occurs in the examined frame. For an example, see the function \"toy_with_chroma\" in the mudbox. Controls: - \\b mrs_natural/NrOfHarmonics [rw] : adjust the number of harmonics in F0 detection (should be >0) - \\b mrs_real/F0Weight [rw] : adjust the balance between F0 and its harmonics (between 0 and 1) - \\b mrs_real/LowestF0 [rw] : adjust the lowest F0 to be detected (between 0 and Nyquist frequency) - \\b mrs_real/ChordEvidence [r] : store the chord evidence of the last examined frame" .
+
+ a rdfs:Resource ;
+ dc:description "Convert spectrum magnitude (e.g. output from PowerSpectrum MarSystem) into a Chroma vector representation. Based in the fft2chromamx.m MATLAB script by Dan Ellis: http://www.ee.columbia.edu/~dpwe/resources/matlab/chroma-ansyn/#1 Controls: - \\b mrs_natural/nbins [w] : sets the number of chroma bins to output (default = 12, i.e. chromatic diatonic) - \\b mrs_real/middleAfreq [w] : sets the frequency (in Hz) to be used for the middle A pitch (A4) - \\b mrs_real/weightCenterFreq [w] : sets the Gaussian weighting center frequency (in Hz) - \\b mrs_real/weightStdDev [w] : sets the Gaussian weighting StdDev (in octaves)" .
+
+ a rdfs:Resource ;
+ dc:description "Convert spectrum magnitude (e.g. output from PowerSpectrum MarSystem) into Mel frequency scale. In order to duplicate the mel matrix in Slaney's mfcc.m use the following parameters: - fftsize = 512 - srate = 8000Hz - melBands = 40 - bandWidth = 1.0 - bandLowEdge = 133.33 - bandHighEdge = 6855.5 - constAmp = false Based in the fft2melmx.m MATLAB script by Dan Ellis: http://labrosa.ee.columbia.edu/projects/coversongs/ Controls: - \\b mrs_natural/melBands [w] : sets the number of Mel bands to output (default = 40, i.e. one per bark) - \\b mrs_real/bandWidth [w] : sets the constant width of each band relative to standard Mel (default 1.0) - \\b mrs_real/bandLowEdge [w] : sets the frequency (in Hz) of the lowest band edge (default 0.0, but 133.33 is a common standard (to skip LF)) - \\b mrs_real/bandHighEdge [w] : sets frequency in Hz of upper edge (default audio srate/2) - \\b mrs_bool/htkMel [w] : use HTK's version of the mel curve, not Slaney's - \\b mrs_bool/constAmp [w] : make integration windows peak at 1, not sum to 1" .
+
+ a rdfs:Resource ;
+ dc:description "Standard Deviation of each row of observations Calculates the standard deviation of each row of observations. The resulting standard deviations are returned as a column vector." .
+
+ a rdfs:Resource ;
+ dc:description "StereoSpectrum computes the panning index for each spectrum bin of a stereo input (i.e. input is expected to be the output of a parallel of two Spectrum MarSystems, one for each stereo channel)." .
+
+ a rdfs:Resource ;
+ dc:description "StereoSpectrumFeatures capture panning information After computing the Stereo Spectrum we can summarize it by extracting features using the StereoSpectrumFeatures." .
+
+ a rdfs:Resource ;
+ dc:description "StereoSpectrumSources estimates the number of sources placed into different stereo positions. After computing the Stereo Spectrum we can try to estimate the number of sources playing in different stereo positions." .
+
+ a rdfs:Resource ;
+ dc:description "Triangular FilterBank Takes as input the N/2+1 spectrum Magnitude points output by PowerSpectrum. For example it can be used to compute a Mel-scale or Constant-Q filterbank. \\see Spectrum, PowerSpectrum Controls: - \\b mrs_natural/coefficients [w]: the number of cepstral coefficients to calculate." .
+
+ a rdfs:Resource ;
+ dc:description "Pyramid wavelet algorithm Discrete Wavelet Transform (DWT) pyramid algorithm. Based on the Numerical Recipies wavelet code." .
+
+ a rdfs:Resource ;
+ dc:description "Pitch detection using the YIN algorithm This algorithm was developped by A. de Cheveigne and H. Kawahara and published in: De Cheveigne, A., Kawahara, H. (2002) \"YIN, a fundamental frequency estimator for speech and music\", J. Acoust. Soc. Am. 111, 1917-1930. See http://recherche.ircam.fr/equipes/pcm/pub/people/cheveign.html This code was adapted from aubio (http://aubio.org) by sness. THIS MARSYSTEM IS VERY SIMILAR TO AUBIO_YIN, BUT DO NOT DELETE IT BECAUSE I NEED IT. - Graham Controls: - \\b mrs_real/tolerance [w] : sets the tolerance of the yin algorithm - \\b mrs_real/frequency_min [w] : limits the search to frequencies above or equal to this - \\b mrs_real/frequency_max [w] : limits the search to frequencies below or equal to this (set to 0 to disable)" .
+
+ a rdfs:Resource ;
+ dc:description "Time-domain ZeroCrossings Basically counts the number of times the input signal crosses the zero line." .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-PsySound3.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-PsySound3.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,17 @@
+@prefix PsySound3: .
+@prefix rdfs: .
+
+PsySound3:Loudness a rdfs:Resource .
+
+PsySound3:Multiplicity a rdfs:Resource .
+
+PsySound3:PureTonalness a rdfs:Resource .
+
+PsySound3:Sharpness a rdfs:Resource .
+
+PsySound3:SpectralDissonance a rdfs:Resource .
+
+PsySound3:TimbralWidth a rdfs:Resource .
+
+PsySound3:TonalDissonance a rdfs:Resource .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-SuperCollider.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-SuperCollider.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,51 @@
+@prefix SuperCollider: .
+@prefix dc: .
+@prefix rdfs: .
+
+SuperCollider:BeatTrack a rdfs:Resource ;
+ dc:description "Autocorrelation based beat tracker" .
+
+SuperCollider:BeatTrack2 a rdfs:Resource ;
+ dc:description "based on exhaustively testing particular template patterns against feature streams" .
+
+SuperCollider:Chromagram a rdfs:Resource ;
+ dc:description "measures the energy at particular chroma within an nTET tuning system" .
+
+SuperCollider:Crest a rdfs:Resource ;
+ dc:description "measures the \"crest factor\" of a time-domain signal, i.e. the ratio of the absolute peak to the absolute mean over a certain time period" .
+
+SuperCollider:KeyTrack a rdfs:Resource ;
+ dc:description "A (12TET major/minor) key tracker based on a pitch class profile of energy across FFT bins and matching this to templates for major and minor scales in all transpositions. It assumes a 440 Hz concert A reference. Output is 0-11 C major to B major, 12-23 C minor to B minor." .
+
+SuperCollider:Loudness a rdfs:Resource ;
+ dc:description "A perceptual loudness function which outputs loudness in sones; this is a variant of an MP3 perceptual model, summing excitation in ERB bands. It models simple spectral and temporal masking, with equal loudness contour correction in ERB bands to obtain phons (relative dB), then a phon to sone transform. The final output is typically in the range of 0 to 64 sones, though higher values can occur with specific synthesised stimuli." .
+
+SuperCollider:MFCC a rdfs:Resource ;
+ dc:description "Generates a set of MFCCs; these are obtained from a band-based frequency representation (using the Mel scale by default), and then a discrete cosine transform (DCT). The DCT is an efficient approximation for principal components analysis, so that it allows a compression, or reduction of dimensionality, of the data, in this case reducing 42 band readings to a smaller set of MFCCs. A small number of features (the coefficients) end up describing the spectrum. The MFCCs are commonly used as timbral descriptors." .
+
+SuperCollider:Onsets a rdfs:Resource ;
+ dc:description "An onset detector for musical audio signals" .
+
+SuperCollider:Pitch a rdfs:Resource .
+
+SuperCollider:SpectralCentroid a rdfs:Resource ;
+ dc:description "the weighted mean frequency, or the \"centre of mass\" of the spectrum" .
+
+SuperCollider:SpectralCrest a rdfs:Resource ;
+ dc:description "produces the spectral crest measure, which is an indicator of the \"peakiness\" of the spectral energy distribution" .
+
+SuperCollider:SpectralFlatness a rdfs:Resource ;
+ dc:description "a power spectrum's geometric mean divided by its arithmetic mean" .
+
+SuperCollider:SpectralPercentile a rdfs:Resource ;
+ dc:description "calculates the cumulative distribution of the frequency spectrum, and outputs the frequency value which corresponds to the desired percentile" .
+
+SuperCollider:SpectralSlope a rdfs:Resource ;
+ dc:description "measures the spectral slope, which is the slope of the linear correlation line derived from the spectral magnitudes" .
+
+SuperCollider:SpectralSpread a rdfs:Resource ;
+ dc:description "measures the spectral spread, which is the magnitude-weighted variance" .
+
+SuperCollider:ZeroCrossingRate a rdfs:Resource ;
+ dc:description "Outputs a frequency based upon the distance between interceptions of the X axis. The X intercepts are determined via linear interpolation so this gives better than just integer wavelength resolution. This is a very crude pitch follower, but can be useful in some situations." .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-Vamp.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-Vamp.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,788 @@
+@prefix Vamp: .
+@prefix dc: .
+@prefix local: .
+@prefix rdfs: .
+
+ a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Pitch Contours: All (MELODIA - Melody Extraction (intermediate steps))" ;
+ local:output "Dense" ;
+ local:source "Music Technology Group, Universitat Pompeu Fabra" .
+
+ a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Pitch Contours: Melody (MELODIA - Melody Extraction (intermediate steps))" ;
+ local:output "Dense" ;
+ local:source "Music Technology Group, Universitat Pompeu Fabra" .
+
+Vamp:AdaptiveSpectrogram a rdfs:Resource ;
+ dc:description "Produce an adaptive spectrogram by adaptive selection from spectrograms at multiple resolutions" ;
+ local:domain "time" ;
+ local:feature "Adaptive Spectrogram" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:AubioBeatTracker a rdfs:Resource ;
+ dc:description "Estimate the musical tempo and track beat positions" ;
+ local:domain "time" ;
+ local:feature "Aubio Beat Tracker" ;
+ local:source "Paul Brossier (method by Matthew Davies, plugin by Chris Cannam)" .
+
+Vamp:AubioNoteTracker a rdfs:Resource ;
+ dc:description "Estimate note onset positions, pitches and durations" ;
+ local:domain "time" ;
+ local:feature "Aubio Note Tracker" ;
+ local:output "Sparse" ;
+ local:source "Paul Brossier (plugin by Chris Cannam)" .
+
+Vamp:AubioOnsetDetector a rdfs:Resource ;
+ dc:description "Estimate note onset times" ;
+ local:domain "time" ;
+ local:feature "Aubio Onset Detector" ;
+ local:output "Sparse" ;
+ local:source "Paul Brossier (plugin by Chris Cannam)" .
+
+Vamp:AubioPitchDetector a rdfs:Resource ;
+ dc:description "Track estimated note pitches" ;
+ local:domain "time" ;
+ local:feature "Aubio Pitch Detector" ;
+ local:output "Sparse" ;
+ local:source "Paul Brossier (plugin by Chris Cannam)" .
+
+Vamp:AubioSilenceDetector a rdfs:Resource ;
+ dc:description "Detect levels below a certain threshold" ;
+ local:domain "time" ;
+ local:feature "Aubio Silence Detector" ;
+ local:source "Paul Brossier (plugin by Chris Cannam)" .
+
+Vamp:Autocorrelation a rdfs:Resource ;
+ dc:description "Extract the autocorrelation of an audio signal" ;
+ local:domain "time" ;
+ local:feature "Autocorrelation" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:AverageDeviation a rdfs:Resource ;
+ dc:description "Extract the average deviation of a range of values" ;
+ local:domain "frequency" ;
+ local:feature "Average Deviation" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:AverageMagnitudeDifferenceFunction a rdfs:Resource ;
+ dc:description "Extract the AMDF of an audio signal" ;
+ local:domain "time" ;
+ local:feature "Average Magnitude Difference Function" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:AverageSquaredDifferenceFunction a rdfs:Resource ;
+ dc:description "Extract the ASDF of an audio signal" ;
+ local:domain "time" ;
+ local:feature "Average Squared Difference Function" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:BarandBeatTracker a rdfs:Resource ;
+ dc:description "Estimate bar and beat locations" ;
+ local:domain "time" ;
+ local:feature "Bar and Beat Tracker" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:BarkCoefficients a rdfs:Resource ;
+ dc:description "Extract bark coefficients from an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Bark Coefficients" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:Bars a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Bars (Bar and Beat Tracker)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:BassChromagram a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Bass Chromagram (NNLS Chroma)" ;
+ local:output "Dense" ;
+ local:source "Matthias Mauch" .
+
+Vamp:BeatCount a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Beat Count (Bar and Beat Tracker)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:BeatSpectra a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Beat Spectra (Similarity)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:BeatSpectralDifference a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Beat Spectral Difference (Bar and Beat Tracker)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:Beats a rdfs:Resource ;
+ local:domain "frequency",
+ "time" ;
+ local:feature "Beats (Aubio Beat Tracker)",
+ "Beats (Bar and Beat Tracker)",
+ "Beats (Tempo and Beat Tracker)" ;
+ local:output "Sparse" ;
+ local:source "Paul Brossier (method by Matthew Davies, plugin by Chris Cannam)",
+ "Queen Mary, University of London" .
+
+Vamp:Centroid a rdfs:Resource ;
+ dc:description "Marsyas - Batch Feature Extract - Centroid" ;
+ local:domain "time" ;
+ local:feature "Marsyas - Batch Feature Extract - Centroid" ;
+ local:output "Dense" ;
+ local:source "Marsyas Plugins" .
+
+Vamp:ChordEstimate a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Chord Estimate (Chordino)" ;
+ local:output "Sparse" ;
+ local:source "Matthias Mauch" .
+
+Vamp:Chordino a rdfs:Resource ;
+ dc:description "Chordino provides a simple chord transcription based on NNLS Chroma (as in the NNLS Chroma plugin). Chord profiles given by the user in the file chord.dict are used to calculate frame-wise chord similarities. A simple (non-state-of-the-art!) algorithm smoothes these to provide a chord transcription using a standard HMM/Viterbi approach." ;
+ local:domain "frequency" ;
+ local:feature "Chordino" ;
+ local:source "Matthias Mauch" .
+
+Vamp:ChromaMeans a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Chroma Means (Chromagram)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:Chromagram a rdfs:Resource ;
+ dc:description "Extract a series of tonal chroma vectors from the audio" ;
+ local:domain "frequency" ;
+ local:feature "Chromagram",
+ "Chromagram (NNLS Chroma)" ;
+ local:output "Dense" ;
+ local:source "Matthias Mauch",
+ "Queen Mary, University of London" .
+
+Vamp:ChromagramandBassChromagram a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Chromagram and Bass Chromagram (NNLS Chroma)" ;
+ local:output "Dense" ;
+ local:source "Matthias Mauch" .
+
+Vamp:Coefficients a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Coefficients (Mel-Frequency Cepstral Coefficients)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:Constant-QSpectrogram a rdfs:Resource ;
+ dc:description "Extract a spectrogram with constant ratio of centre frequency to resolution from the input audio" ;
+ local:domain "frequency" ;
+ local:feature "Constant-Q Spectrogram" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:DiscreteCosineTransform a rdfs:Resource ;
+ dc:description "Extract the DCT of an audio signal" ;
+ local:domain "time" ;
+ local:feature "Discrete Cosine Transform" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:DiscreteWaveletTransform a rdfs:Resource ;
+ dc:description "Visualisation by scalogram" ;
+ local:domain "time" ;
+ local:feature "Discrete Wavelet Transform" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:DistanceMatrix a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Distance Matrix (Similarity)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:DistancefromFirstChannel a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Distance from First Channel (Similarity)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:FeatureMeans a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Feature Means (Similarity)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:FeatureVariances a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Feature Variances (Similarity)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:FundamentalFrequency a rdfs:Resource ;
+ dc:description "Extract the fundamental frequency of an audio signal" ;
+ local:domain "time" ;
+ local:feature "Fundamental Frequency" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+ a rdfs:Resource ;
+ dc:description "Extract the fundamental frequency of an audio signal (failsafe)" ;
+ local:domain "time" ;
+ local:feature "Fundamental Frequency (failsafe)" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:HPCP a rdfs:Resource ;
+ dc:description "Return the instantaneous evolution of HPCP (Harmonic Pitch Class Profile) of a signal." ;
+ local:domain "frequency" ;
+ local:feature "HPCP" ;
+ local:output "Dense" ;
+ local:source "Music Technology Group, Universitat Pompeu Fabra" .
+
+Vamp:HarmonicChangeValue a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Harmonic Change Value (Chordino)" ;
+ local:output "Dense" ;
+ local:source "Matthias Mauch" .
+
+Vamp:HarmonicSpectrum a rdfs:Resource ;
+ dc:description "Extract the harmonics from an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Harmonic Spectrum" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:HighestValue a rdfs:Resource ;
+ dc:description "Extract the highest value from a given range" ;
+ local:domain "frequency" ;
+ local:feature "Highest Value" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:IBT-INESCBeatTracker a rdfs:Resource ;
+ dc:description "Estimates beat locations and tempo (off-line [default] and on-line modes of operation)" ;
+ local:domain "frequency" ;
+ local:feature "IBT - INESC Beat Tracker" ;
+ local:output "Sparse" ;
+ local:source "Marsyas Plugins" .
+
+Vamp:Inharmonicity a rdfs:Resource ;
+ dc:description "Extract the inharmonicity of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Inharmonicity" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:IrregularityI a rdfs:Resource ;
+ dc:description "Extract the irregularity (type I) of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Irregularity I" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:IrregularityII a rdfs:Resource ;
+ dc:description "Extract the irregularity (type II) of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Irregularity II" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:Key a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Key (Key Detector)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:KeyDetector a rdfs:Resource ;
+ dc:description "Estimate the key of the music" ;
+ local:domain "time" ;
+ local:feature "Key Detector" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:KeyMode a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Key Mode (Key Detector)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:KeyStrengthPlot a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Key Strength Plot (Key Detector)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:Kurtosis a rdfs:Resource ;
+ dc:description "Extract the kurtosis of a range of values" ;
+ local:domain "frequency" ;
+ local:feature "Kurtosis" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:LineSpectralPairs a rdfs:Resource ;
+ dc:description "Marsyas - Batch Feature Extract - Line Spectral Pairs" ;
+ local:domain "time" ;
+ local:feature "Marsyas - Batch Feature Extract - Line Spectral Pairs" ;
+ local:output "Dense" ;
+ local:source "Marsyas Plugins" .
+
+Vamp:LinearPredictionCepstralCoefficients a rdfs:Resource ;
+ dc:description "Marsyas - Batch Feature Extract - Linear Prediction Cepstral Coefficients" ;
+ local:domain "time" ;
+ local:feature "Marsyas - Batch Feature Extract - Linear Prediction Cepstral Coefficients" ;
+ local:output "Dense" ;
+ local:source "Marsyas Plugins" .
+
+Vamp:LocalTuning a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Local Tuning (Tuning)" ;
+ local:output "Dense" ;
+ local:source "Matthias Mauch" .
+
+Vamp:Log-FrequencySpectrum a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Log-Frequency Spectrum (NNLS Chroma)" ;
+ local:output "Dense" ;
+ local:source "Matthias Mauch" .
+
+Vamp:Log-LikelihoodofChordEstimate a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Log-Likelihood of Chord Estimate (Chordino)" ;
+ local:output "Dense" ;
+ local:source "Matthias Mauch" .
+
+Vamp:Loudness a rdfs:Resource ;
+ dc:description "Extract the loudness of an audio signal from its spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Loudness" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:LowestValue a rdfs:Resource ;
+ dc:description "Extract the lowest value from a given range" ;
+ local:domain "frequency" ;
+ local:feature "Lowest Value" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:MELODIA-MelodyExtraction a rdfs:Resource ;
+ dc:description "Estimates the melody pitch in polyphonic music (also good for homophonic and monophonic music). Segments without melody are indicated by zero or negative values. For further details please read: J. Salamon and E. Gomez, \"Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics\", IEEE Transactions on Audio, Speech and Language Processing, 20(6):1759-1770, 2012. We would highly appreciate the above reference being cited in publications of work in which this plug-in was used." ;
+ local:domain "time" ;
+ local:feature "MELODIA - Melody Extraction" ;
+ local:output "Dense" ;
+ local:source "Music Technology Group, Universitat Pompeu Fabra" .
+
+ a rdfs:Resource ;
+ dc:description "Provides visualisations of the intermediate steps calculated by the melody extraction algorithm implemented in the MELODIA - Melody Extraction plug-in. For further details please read: J. Salamon and E. Gomez, \"Melody Extraction from Polyphonic Music Signals using Pitch Contour Characteristics\", IEEE Transactions on Audio, Speech and Language Processing, 20(6):1759-1770, 2012. We would highly appreciate the above reference being cited in publications of work in which this plug-in was used." ;
+ local:domain "time" ;
+ local:feature "MELODIA - Melody Extraction (intermediate steps)" ;
+ local:source "Music Technology Group, Universitat Pompeu Fabra" .
+
+Vamp:Mean a rdfs:Resource ;
+ dc:description "Extract the mean of a range of values" ;
+ local:domain "frequency" ;
+ local:feature "Mean" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:MeansofCoefficients a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Means of Coefficients (Mel-Frequency Cepstral Coefficients)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:Mel-FrequencyCepstralCoefficients a rdfs:Resource ;
+ dc:description "Calculate a series of MFCC vectors from the audio",
+ "Extract MFCC from an audio spectrum",
+ "Marsyas - Batch Feature Extract - Mel-Frequency Cepstral Coefficients" ;
+ local:domain "frequency",
+ "time" ;
+ local:feature "Marsyas - Batch Feature Extract - Mel-Frequency Cepstral Coefficients",
+ "Mel-Frequency Cepstral Coefficients" ;
+ local:output "Dense" ;
+ local:source "Marsyas Plugins",
+ "Queen Mary, University of London",
+ "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:NNLSChroma a rdfs:Resource ;
+ dc:description "This plugin provides a number of features derived from a DFT-based log-frequency amplitude spectrum: some variants of the log-frequency spectrum, including a semitone spectrum derived from approximate transcription using the NNLS algorithm; and based on this semitone spectrum, different chroma features." ;
+ local:domain "frequency" ;
+ local:feature "NNLS Chroma" ;
+ local:source "Matthias Mauch" .
+
+Vamp:Noisiness a rdfs:Resource ;
+ dc:description "Extract the noisiness of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Noisiness" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:Non-SilentRegions a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Non-Silent Regions (Aubio Silence Detector)" ;
+ local:output "Sparse" ;
+ local:source "Paul Brossier (plugin by Chris Cannam)" .
+
+Vamp:Non-zerocount a rdfs:Resource ;
+ dc:description "Extract the number of non-zero elements in an input spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Non-zero count" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:NoteOnsetDetector a rdfs:Resource ;
+ dc:description "Estimate individual note onset positions" ;
+ local:domain "frequency" ;
+ local:feature "Note Onset Detector" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:NoteOnsets a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Note Onsets (Note Onset Detector)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:NoteRepresentationofChordEstimate a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Note Representation of Chord Estimate (Chordino)" ;
+ local:output "Sparse" ;
+ local:source "Matthias Mauch" .
+
+ a rdfs:Resource ;
+ dc:description "Extract the odd-to-even harmonic ratio of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Odd/even Harmonic Ratio" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:OnsetDetectionFunction a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Onset Detection Function (Note Onset Detector)",
+ "Onset Detection Function (Tempo and Beat Tracker)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:OrderedDistancesfromFirstChannel a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Ordered Distances from First Channel (Similarity)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:PeakSpectrum a rdfs:Resource ;
+ dc:description "Extract the spectral peaks from an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Peak Spectrum" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:PolyphonicTranscription a rdfs:Resource ;
+ dc:description "Transcribe the input audio to estimated notes" ;
+ local:domain "time" ;
+ local:feature "Polyphonic Transcription" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:RMSAmplitude a rdfs:Resource ;
+ dc:description "Extract the RMS amplitude of an audio signal" ;
+ local:domain "time" ;
+ local:feature "RMS Amplitude" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SalienceFunction a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Salience Function (MELODIA - Melody Extraction (intermediate steps))" ;
+ local:output "Dense" ;
+ local:source "Music Technology Group, Universitat Pompeu Fabra" .
+
+Vamp:Segmenter a rdfs:Resource ;
+ dc:description "Divide the track into a sequence of consistent segments" ;
+ local:domain "time" ;
+ local:feature "Segmenter" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:SemitoneSpectrum a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Semitone Spectrum (NNLS Chroma)" ;
+ local:output "Dense" ;
+ local:source "Matthias Mauch" .
+
+Vamp:SilenceTest a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Silence Test (Aubio Silence Detector)" ;
+ local:output "Sparse" ;
+ local:source "Paul Brossier (plugin by Chris Cannam)" .
+
+Vamp:SilentRegions a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Silent Regions (Aubio Silence Detector)" ;
+ local:output "Sparse" ;
+ local:source "Paul Brossier (plugin by Chris Cannam)" .
+
+Vamp:Similarity a rdfs:Resource ;
+ dc:description "Return a distance matrix for similarity between the input audio channels" ;
+ local:domain "time" ;
+ local:feature "Similarity" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:Skewness a rdfs:Resource ;
+ dc:description "Extract the skewness of a range of values" ;
+ local:domain "frequency" ;
+ local:feature "Skewness" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SmoothedDetectionFunction a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Smoothed Detection Function (Note Onset Detector)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:SpectralAverageDeviation a rdfs:Resource ;
+ dc:description "Extract the average deviation of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Average Deviation" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralCentroid a rdfs:Resource ;
+ dc:description "Extract the spectral centroid of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Centroid" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralCrestFactor a rdfs:Resource ;
+ dc:description "Marsyas - Batch Feature Extract - Spectral Crest Factor" ;
+ local:domain "time" ;
+ local:feature "Marsyas - Batch Feature Extract - Spectral Crest Factor" ;
+ local:output "Dense" ;
+ local:source "Marsyas Plugins" .
+
+Vamp:SpectralCrestMeasure a rdfs:Resource ;
+ dc:description "Extract the spectral crest measure of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Crest Measure" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralFlatness a rdfs:Resource ;
+ dc:description "Extract the spectral flatness of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Flatness" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralFlatnessMeasure a rdfs:Resource ;
+ dc:description "Marsyas - Batch Feature Extract - Spectral Flatness Measure" ;
+ local:domain "time" ;
+ local:feature "Marsyas - Batch Feature Extract - Spectral Flatness Measure" ;
+ local:output "Dense" ;
+ local:source "Marsyas Plugins" .
+
+Vamp:SpectralKurtosis a rdfs:Resource ;
+ dc:description "Extract the kurtosis of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Kurtosis" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralRolloff a rdfs:Resource ;
+ dc:description "Extract the rolloff point of an audio spectrum",
+ "Marsyas - Batch Feature Extract - Spectral Rolloff" ;
+ local:domain "frequency",
+ "time" ;
+ local:feature "Marsyas - Batch Feature Extract - Spectral Rolloff",
+ "Spectral Rolloff" ;
+ local:output "Dense" ;
+ local:source "Marsyas Plugins",
+ "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralSharpness a rdfs:Resource ;
+ dc:description "Extract the spectral sharpness of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Sharpness" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralSkewness a rdfs:Resource ;
+ dc:description "Extract the skewness of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Skewness" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralSlope a rdfs:Resource ;
+ dc:description "Extract the spectral slope of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Slope" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralSmoothness a rdfs:Resource ;
+ dc:description "Extract the spectral smoothness of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Smoothness" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralSpread a rdfs:Resource ;
+ dc:description "Extract the spectral spread of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Spread" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralStandardDeviation a rdfs:Resource ;
+ dc:description "Extract the standard deviation of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Standard Deviation" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SpectralVariance a rdfs:Resource ;
+ dc:description "Extract the variance of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Spectral Variance" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:Spectrum a rdfs:Resource ;
+ dc:description "Extract the spectrum of an audio signal" ;
+ local:domain "time" ;
+ local:feature "Spectrum" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:StandardDeviation a rdfs:Resource ;
+ dc:description "Extract the standard deviation of a range of values" ;
+ local:domain "frequency" ;
+ local:feature "Standard Deviation" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:SumofValues a rdfs:Resource ;
+ dc:description "Extract the sum of the values in a given range" ;
+ local:domain "frequency" ;
+ local:feature "Sum of Values" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:Tempo a rdfs:Resource ;
+ local:domain "frequency",
+ "time" ;
+ local:feature "Tempo (Aubio Beat Tracker)",
+ "Tempo (Tempo and Beat Tracker)" ;
+ local:output "Dense",
+ "Sparse" ;
+ local:source "Paul Brossier (method by Matthew Davies, plugin by Chris Cannam)",
+ "Queen Mary, University of London" .
+
+Vamp:TempoandBeatTracker a rdfs:Resource ;
+ dc:description "Estimate beat locations and tempo" ;
+ local:domain "frequency" ;
+ local:feature "Tempo and Beat Tracker" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:TonalChange a rdfs:Resource ;
+ dc:description "Detect and return the positions of harmonic changes such as chord boundaries" ;
+ local:domain "time" ;
+ local:feature "Tonal Change" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:TonalChangeDetectionFunction a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Tonal Change Detection Function (Tonal Change)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:TonalChangePositions a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Tonal Change Positions (Tonal Change)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:Tonality a rdfs:Resource ;
+ dc:description "Extract the tonality an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Tonality" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:TonicPitch a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Tonic Pitch (Key Detector)" ;
+ local:output "Sparse" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:Transformto6DTonalContentSpace a rdfs:Resource ;
+ local:domain "time" ;
+ local:feature "Transform to 6D Tonal Content Space (Tonal Change)" ;
+ local:output "Dense" ;
+ local:source "Queen Mary, University of London" .
+
+Vamp:TristimulusI a rdfs:Resource ;
+ dc:description "Extract the tristimulus (type I) of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Tristimulus I" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:TristimulusII a rdfs:Resource ;
+ dc:description "Extract the tristimulus (type II) of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Tristimulus II" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:TristimulusIII a rdfs:Resource ;
+ dc:description "Extract the tristimulus (type III) of an audio spectrum" ;
+ local:domain "frequency" ;
+ local:feature "Tristimulus III" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:TunedLog-FrequencySpectrum a rdfs:Resource ;
+ local:domain "frequency" ;
+ local:feature "Tuned Log-Frequency Spectrum (NNLS Chroma)" ;
+ local:output "Dense" ;
+ local:source "Matthias Mauch" .
+
+Vamp:Tuning a rdfs:Resource ;
+ dc:description "The tuning plugin can estimate the local and global tuning of piece. The same tuning method is used for the NNLS Chroma and Chordino plugins." ;
+ local:domain "frequency" ;
+ local:feature "Tuning" ;
+ local:source "Matthias Mauch" .
+
+Vamp:Variance a rdfs:Resource ;
+ dc:description "Extract the variance of a range of values" ;
+ local:domain "frequency" ;
+ local:feature "Variance" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:ZeroCrossingRate a rdfs:Resource ;
+ dc:description "Extract the zero crossing rate of an audio signal" ;
+ local:domain "time" ;
+ local:feature "Zero Crossing Rate" ;
+ local:output "Dense" ;
+ local:source "libxtract by Jamie Bullock (plugin by Chris Cannam)" .
+
+Vamp:ZeroCrossings a rdfs:Resource ;
+ dc:description "Detect and count zero crossing points",
+ "Marsyas - Batch Feature Extract - Zero Crossings" ;
+ local:domain "time" ;
+ local:feature "Marsyas - Batch Feature Extract - Zero Crossings",
+ "Zero Crossings" ;
+ local:output "Dense" ;
+ local:source "Marsyas Plugins" .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-Yaafe.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-Yaafe.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,106 @@
+@prefix Yaafe: .
+@prefix dc: .
+@prefix rdfs: .
+
+Yaafe:AmplitudeModulation a rdfs:Resource ;
+ dc:description "Tremelo and Grain description, according to [SE2005]_ and [AE2001]_." .
+
+Yaafe:AutoCorrelation a rdfs:Resource ;
+ dc:description "Compute autocorrelation coefficients *ac* on each frames." .
+
+Yaafe:AutoCorrelationPeaksIntegrator a rdfs:Resource ;
+ dc:description "Feature transform that compute peaks of the autocorrelation function, outputs peaks and amplitude." .
+
+Yaafe:Cepstrum a rdfs:Resource ;
+ dc:description "Feature transform that compute cepstrum coefficients of input feature frames. (use DCT II)" .
+
+Yaafe:ComplexDomainOnsetDetection a rdfs:Resource ;
+ dc:description "Compute onset detection using a complex domain spectral flux method [CD2003]_." .
+
+Yaafe:Derivate a rdfs:Resource ;
+ dc:description "Compute temporal derivative of input feature. The derivative is approximated by" .
+
+Yaafe:Energy a rdfs:Resource ;
+ dc:description "Compute energy as root mean square of an audio Frame." .
+
+Yaafe:Envelope a rdfs:Resource ;
+ dc:description "Extract amplitude envelope using hilbert transform, low-pass filtering and decimation." .
+
+Yaafe:EnvelopeShapeStatistics a rdfs:Resource ;
+ dc:description "Centroid, spread, skewness and kurtosis of each frame's amplitude envelope. For more details about moments, see :ref:Shape Statistics shapestatistics." .
+
+Yaafe:Frames a rdfs:Resource ;
+ dc:description "Segment input signal into frames." .
+
+Yaafe:HistogramIntegrator a rdfs:Resource ;
+ dc:description "Feature transform that compute histogram of input values" .
+
+Yaafe:LPC a rdfs:Resource ;
+ dc:description "Compute the Linear Predictor Coefficients (LPC) of a signal frame. It uses autocorrelation and Levinson-Durbin algorithm. see [JM1975]_." .
+
+Yaafe:LSF a rdfs:Resource ;
+ dc:description "Compute the Line Spectral Frequency (LSF) coefficients of a signal frame. Algorithm was adapted from ([TB2006]_, [SH1976]_)." .
+
+Yaafe:Loudness a rdfs:Resource ;
+ dc:description "The loudness coefficients are the energy in each Bark band, normalized by the overall sum. see [GP2004]_ and [MG1997]_ for more details." .
+
+Yaafe:MFCC a rdfs:Resource ;
+ dc:description "Compute the Mel-frequencies cepstrum coefficients [DM1980]_." .
+
+Yaafe:MagnitudeSpectrum a rdfs:Resource ;
+ dc:description "Compute frame's magnitude spectrum, using an analysis window (Hanning or Hamming), or not." .
+
+Yaafe:MelSpectrum a rdfs:Resource ;
+ dc:description "Compute the Mel-frequencies spectrum [DM1980]_." .
+
+Yaafe:OBSI a rdfs:Resource ;
+ dc:description "Compute Octave band signal intensity using a trigular octave filter bank ([SE2005]_)." .
+
+Yaafe:OBSIR a rdfs:Resource ;
+ dc:description "Compute log of :class:OBSI ratio between consecutive octave." .
+
+Yaafe:PerceptualSharpness a rdfs:Resource ;
+ dc:description "Compute the sharpness of :class:Loudness coefficients, according to [GP2004]_." .
+
+Yaafe:PerceptualSpread a rdfs:Resource ;
+ dc:description "Compute the spread of :class:Loudness coefficients, according to [GP2004]_." .
+
+Yaafe:SlopeIntegrator a rdfs:Resource ;
+ dc:description "Feature transform that compute the slope of input feature over the given number of frames." .
+
+Yaafe:SpectralCrestFactorPerBand a rdfs:Resource ;
+ dc:description "Compute spectral crest factor per log-spaced band of 1/4 octave." .
+
+Yaafe:SpectralDecrease a rdfs:Resource ;
+ dc:description "Compute spectral decrease accoding to [GP2004]_." .
+
+Yaafe:SpectralFlatness a rdfs:Resource ;
+ dc:description "Compute global spectral flatness using the ratio between geometric and arithmetic mean." .
+
+Yaafe:SpectralFlatnessPerBand a rdfs:Resource ;
+ dc:description "Compute spectral flatness per log-spaced band of 1/4 octave, as proposed in MPEG7 standard." .
+
+Yaafe:SpectralFlux a rdfs:Resource ;
+ dc:description "Compute flux of :class:spectrum MagnitudeSpectrum between consecutives frames." .
+
+Yaafe:SpectralRolloff a rdfs:Resource ;
+ dc:description "Spectral roll-off is the frequency so that 99% of the energy is contained below. see [SS1997]_." .
+
+Yaafe:SpectralShapeStatistics a rdfs:Resource ;
+ dc:description "Compute shape statistics of :class:MagnitudeSpectrum, (see [GR2004]_)." .
+
+Yaafe:SpectralSlope a rdfs:Resource ;
+ dc:description "SpectralSlope is computed by linear regression of the spectral amplitude. (see [GP2004]_)" .
+
+Yaafe:SpectralVariation a rdfs:Resource ;
+ dc:description "SpectralVariation is the normalized correlation of :class:spectrum MagnitudeSpectrum between consecutive frames. (see [GP2004]_)" .
+
+Yaafe:StatisticalIntegrator a rdfs:Resource ;
+ dc:description "Feature transform that compute the temporal mean and variance of input feature over the given number of frames." .
+
+Yaafe:TemporalShapeStatistics a rdfs:Resource ;
+ dc:description "Compute :ref:shape statistics shapestatistics of signal frames." .
+
+Yaafe:ZCR a rdfs:Resource ;
+ dc:description "Compute zero-crossing rate in frames. see [SS1997]_." .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-aubio.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-aubio.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,94 @@
+@prefix aubio: .
+@prefix dc: .
+@prefix rdfs: .
+
+aubio:BeatTracking a rdfs:Resource ;
+ dc:description "Beat tracking using a context dependant model." .
+
+aubio:ComplexDomainMethodOnsetDetectionFunction a rdfs:Resource ;
+ dc:description "Complex Domain Method onset detection function." .
+
+aubio:EnergyBasedOnsetDetectionFunction a rdfs:Resource ;
+ dc:description "This function calculates the local energy of the input spectral frame." .
+
+aubio:FilterbankMel a rdfs:Resource ;
+ dc:description "Mel frequency filter bank coefficients. Set filter bank coefficients to Mel frequency bands" .
+
+aubio:HighFrequencyContentOnsetDetectionFunction a rdfs:Resource ;
+ dc:description "This method computes the High Frequency Content (HFC) of the input spectral frame. The resulting function is efficient at detecting percussive onsets" .
+
+aubio:KullbackLieblerOnsetDetectionFunction a rdfs:Resource ;
+ dc:description "Kullback-Liebler onset detection function." .
+
+aubio:MFCC a rdfs:Resource ;
+ dc:description "Mel-frequency cepstrum coefficients object" .
+
+aubio:ModifiedKullbackLieblerOnsetDetectionFunction a rdfs:Resource ;
+ dc:description "Modified Kullback-Liebler onset detection function." .
+
+aubio:Onset a rdfs:Resource ;
+ dc:description "Computes the onset detection function and detect peaks in these functions. When onsets are found above a given silence threshold, and after a minimum inter-onset interval, the output vector returned by aubio_onset_do is filled with 1. Otherwise, the output vector remains 0" .
+
+aubio:OnsetDetectionFunction a rdfs:Resource ;
+ dc:description "These functions are designed to raise at notes attacks in music signals." .
+
+aubio:PeakPicker a rdfs:Resource ;
+ dc:description "Peak picking utilities function" .
+
+aubio:PhaseBasedMethodOnsetDetectionFunction a rdfs:Resource ;
+ dc:description "Phase Based Method onset detection function." .
+
+aubio:Pitch a rdfs:Resource ;
+ dc:description "Generic method for pitch detection" .
+
+aubio:PitchFastComb a rdfs:Resource ;
+ dc:description "Pitch detection using a fast harmonic comb filter" .
+
+aubio:PitchFftYin a rdfs:Resource ;
+ dc:description "Pitch detection using a spectral implementation of the YIN algorithm" .
+
+aubio:PitchMultiComb a rdfs:Resource ;
+ dc:description "Pitch detection using multiple-comb filter" .
+
+aubio:PitchSchmitt a rdfs:Resource ;
+ dc:description "Pitch detection using a Schmitt trigger" .
+
+aubio:PitchYin a rdfs:Resource ;
+ dc:description "Pitch detection using the YIN algorithm" .
+
+aubio:SpectralCentroid a rdfs:Resource ;
+ dc:description "The spectral centroid represents the barycenter of the spectrum." .
+
+aubio:SpectralDecrease a rdfs:Resource ;
+ dc:description "The spectral decrease is another representation of the decreasing rate, based on perceptual criteria." .
+
+aubio:SpectralDifferenceMethodOnsetDetectionFunction a rdfs:Resource ;
+ dc:description "Spectral difference method onset detection function." .
+
+aubio:SpectralFlux a rdfs:Resource ;
+ dc:description "Spectral Flux" .
+
+aubio:SpectralKurtosis a rdfs:Resource ;
+ dc:description "The kurtosis is a measure of the flatness of the spectrum, computed from the fourth order moment." .
+
+aubio:SpectralRolloff a rdfs:Resource ;
+ dc:description "This function returns the bin number below which 95% of the spectrum energy is found." .
+
+aubio:SpectralShapeDescriptors a rdfs:Resource ;
+ dc:description "Spectral shape descriptors" .
+
+aubio:SpectralSkewness a rdfs:Resource ;
+ dc:description "The skewness is computed from the third order moment of the spectrum. A negative skewness indicates more energy on the lower part of the spectrum. A positive skewness indicates more energy on the high frequency of the spectrum." .
+
+aubio:SpectralSlope a rdfs:Resource ;
+ dc:description "The spectral slope represents decreasing rate of the spectral amplitude, computed using a linear regression." .
+
+aubio:SpectralSpread a rdfs:Resource ;
+ dc:description "The spectral spread is the variance of the spectral distribution around its centroid." .
+
+aubio:Tempo a rdfs:Resource ;
+ dc:description "Tempo detection driver. This object stores all the memory required for tempo detection algorithm and returns the estimated beat locations." .
+
+aubio:TransientSteadyStateSeparation a rdfs:Resource ;
+ dc:description "Transient / Steady-state Separation (TSS)" .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-comirva.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-comirva.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,15 @@
+@prefix comirva: .
+@prefix rdfs: .
+
+comirva:FluctuationPattern a rdfs:Resource .
+
+comirva:FluctuationPatternCent a rdfs:Resource .
+
+comirva:MFCC a rdfs:Resource .
+
+comirva:MandelEllis a rdfs:Resource .
+
+comirva:SpectralPatternCent a rdfs:Resource .
+
+comirva:TimbreDistribution a rdfs:Resource .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-jMIR.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-jMIR.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,153 @@
+@prefix dc: .
+@prefix jMIR: .
+@prefix local: .
+@prefix rdfs: .
+
+jMIR:AreaMoments a rdfs:Resource ;
+ dc:description "2D statistical method of moments" ;
+ local:name "Area Method of Moments" .
+
+jMIR:AreaMomentsConstantQMFCC a rdfs:Resource ;
+ dc:description "2D statistical method of moments of ConstantQ-based MFCCs" ;
+ local:name "Area Method of Moments of ConstantQ-based MFCCs" .
+
+jMIR:AreaMomentsLogConstantQ a rdfs:Resource ;
+ dc:description "2D statistical method of moments of the log of the ConstantQ transform" ;
+ local:name "Area Method of Moments of Log of ConstantQ transform" .
+
+jMIR:AreaMomentsMFCC a rdfs:Resource ;
+ dc:description "2D statistical method of moments of MFCCs" ;
+ local:name "Area Method of Moments of MFCCs" .
+
+jMIR:AreaPolynomialApproximation a rdfs:Resource ;
+ dc:description "coeffecients of 2D polynomial best describing the input matrtix." ;
+ local:name "2D Polynomial Approximation" .
+
+jMIR:AreaPolynomialApproximationConstantQMFCC a rdfs:Resource ;
+ dc:description "coeffecients of 2D polynomial best describing the input matrtix." ;
+ local:name "2D Polynomial Approximation ConstantQ MFCC" .
+
+jMIR:AreaPolynomialApproximationLogConstantQ a rdfs:Resource ;
+ dc:description "coeffecients of 2D polynomial best describing the input matrix." ;
+ local:name "2D Polynomial Approximation of Log of ConstantQ" .
+
+jMIR:BeatHistogram a rdfs:Resource ;
+ dc:description "A histogram showing the relative strength of different rhythmic periodicities (tempi) in a signal. Found by calculating the auto-correlation of the RMS." ;
+ local:name "Beat Histogram" .
+
+jMIR:BeatHistogramLabels a rdfs:Resource ;
+ dc:description "The bin label, in beats per minute, of each beat histogram bin. Not useful as a feature in itself, but useful for calculating other features from the beat histogram." ;
+ local:name "Beat Histogram Bin Labels" .
+
+jMIR:BeatSum a rdfs:Resource ;
+ dc:description "The sum of all entries in the beat histogram. This is a good measure of the importance of regular beats in a signal." ;
+ local:name "Beat Sum" .
+
+jMIR:Compactness a rdfs:Resource ;
+ dc:description "A measure of the noisiness of a signal. Found by comparing the components of a window's magnitude spectrum with the magnitude spectrum of its neighbouring windows." ;
+ local:name "Compactness" .
+
+jMIR:ConstantQ a rdfs:Resource ;
+ dc:description "signal to frequency transform using exponential-spaced frequency bins." ;
+ local:name "ConstantQ" .
+
+jMIR:ConstantQMFCC a rdfs:Resource ;
+ dc:description "MFCCs directly caluclated from ConstantQ exponential bins" ;
+ local:name "ConstantQ derived MFCCs" .
+
+jMIR:FFTBinFrequencies a rdfs:Resource ;
+ dc:description "The bin label, in Hz, of each power spectrum or magnitude spectrum bin. Not useful as a feature in itself, but useful for calculating other features from the magnitude spectrum and power spectrum." ;
+ local:name "FFT Bin Frequency Labels" .
+
+jMIR:FractionOfLowEnergyWindows a rdfs:Resource ;
+ dc:description "The fraction of the last 100 windows that has an RMS less than the mean RMS in the last 100 windows. This can indicate how much of a signal is quiet relative to the rest of the signal." ;
+ local:name "Fraction Of Low Energy Windows" .
+
+jMIR:HarmonicSpectralCentroid a rdfs:Resource ;
+ dc:description "Spectral Centroid calculated based on the center of mass of partials instead of center of mass of bins." ;
+ local:name "Partial Based Spectral Centroid" .
+
+jMIR:HarmonicSpectralFlux a rdfs:Resource ;
+ dc:description "Cacluate the correlation bettween adjacent frames based peaks instead of spectral bins. Peak tracking is primitive - whe the number of bins changes, the bottom bins are matched sequentially and the extra unmatched bins are ignored.) definition = new FeatureDefinition(name, description, true, 1) dependencies = new String[] { Peak Detection, Peak Detection } offsets = new int[] { 0, -1 } } /** * Extract the peak based spectral flux from the window. * @param samples * The samples to extract the feature from. * @param sampling_rate * The sampling rate that the samples are encoded with. * @param other_feature_values * The values of other features that are needed to calculate this * value. The order and offsets of these features must be the * same as those returned by this class's getDependencies and * getDependencyOffsets methods respectively. The first indice * indicates the feature/window and the second indicates the * value. * @return The extracted feature value(s). * @throws Exception * Throws an informative exception if the feature cannot be * calculated. * @see jAudioFeatureExtractor.AudioFeatures.FeatureExtractor#extractFeature(double[], * double, double[][]) */ public double[] extractFeature(double[] samples, double sampling_rate, double[][] other_feature_values) { double[] result = new double[1] double[] old = other_feature_values[1] double[] now = other_feature_values[0] double x, y, xy, x2, y2 x = y = xy = x2 = y2 = 0.0 int peakCount = Math.min(old.length, now.length) for (int i = 0 i < peakCount i) { x = old[i] y = now[i] xy = old[i] * now[i] x2 = old[i] * old[i] y2 = now[i] * now[i] } double top = xy - (x * y) / peakCount double bottom = Math.sqrt(Math.abs((x2 - ((x * x) / peakCount)) * (y2 - ((y * y) / peakCount)))) result[0] = top / bottom return result } /** * Proviede a complete copy of this feature. Used to implement the prottype * pattern */ public Object clone() { return new HarmonicSpectralFlux() } }" ;
+ local:name "Partial Based Spectral Flux" .
+
+jMIR:HarmonicSpectralSmoothness a rdfs:Resource ;
+ dc:description "Peak Based Spectral Smoothness is calculated from partials, not frequency bins. It is implemented accortding to McAdams 99 System.getProperty(line.separator) System.getProperty(line.separator) McAdams, S. 1999." ;
+ local:name "Peak Based Spectral Smoothness" .
+
+jMIR:LPC a rdfs:Resource ;
+ dc:description "Linear Prediction Coeffecients calculated using autocorrelation and Levinson-Durbin recursion." ;
+ local:name "LPC" .
+
+jMIR:LogConstantQ a rdfs:Resource ;
+ dc:description "logarithm of each bin of exponentially-spaced frequency bins." ;
+ local:name "Log of ConstantQ" .
+
+jMIR:MFCC a rdfs:Resource ;
+ dc:description "MFCC calculations based upon Orange Cow code" ;
+ local:name "MFCC" .
+
+jMIR:MagnitudeSpectrum a rdfs:Resource ;
+ dc:description "A measure of the strength of different frequency components." ;
+ local:name "Magnitude Spectrum" .
+
+jMIR:Moments a rdfs:Resource ;
+ dc:description "Statistical Method of Moments of the Magnitude Spectrum." ;
+ local:name "Method of Moments" .
+
+jMIR:PeakFinder a rdfs:Resource ;
+ dc:description "All peaks that are within an order of magnitude of the highest point" ;
+ local:name "Peak Detection" .
+
+jMIR:PowerSpectrum a rdfs:Resource ;
+ dc:description "A measure of the power of different frequency components." ;
+ local:name "Power Spectrum" .
+
+jMIR:RMS a rdfs:Resource ;
+ dc:description "A measure of the power of a signal." ;
+ local:name "Root Mean Square" .
+
+jMIR:RelativeDifferenceFunction a rdfs:Resource ;
+ dc:description "Relative Difference Function" ;
+ local:name "Relative Difference Function" .
+
+jMIR:SpectralCentroid a rdfs:Resource ;
+ dc:description "The centre of mass of the power spectrum." ;
+ local:name "Spectral Centroid" .
+
+jMIR:SpectralFlux a rdfs:Resource ;
+ dc:description "A measure of the amount of spectral change in a signal. //\\n Found by calculating the change in the magnitude spectrum //\\n from frame to frame." ;
+ local:name "Spectral Flux" .
+
+jMIR:SpectralRolloffPoint a rdfs:Resource ;
+ dc:description "The fraction of bins in the power spectrum at which 85% // System.getProperty(line.separator) of the power is at lower frequencies. This is a measure // System.getProperty(line.separator) // of the right-skewedness of the power spectrum." ;
+ local:name "Spectral Rolloff Point" .
+
+jMIR:SpectralVariability a rdfs:Resource ;
+ dc:description "The standard deviation of the magnitude spectrum. This is a measure of the variance of a signal's magnitude spectrum." ;
+ local:name "Spectral Variability" .
+
+jMIR:StrengthOfStrongestBeat a rdfs:Resource ;
+ dc:description "How strong the strongest beat in the beat histogram is compared to other potential beats." ;
+ local:name "Strength Of Strongest Beat" .
+
+jMIR:StrongestBeat a rdfs:Resource ;
+ dc:description "The strongest beat in a signal, in beats per minute, found by finding the strongest bin in the beat histogram." ;
+ local:name "Strongest Beat" .
+
+jMIR:StrongestFrequencyViaFFTMax a rdfs:Resource ;
+ dc:description "The strongest frequency component of a signal, in Hz, found via finding the FFT bin with the highest power." ;
+ local:name "Strongest Frequency Via FFT Maximum" .
+
+jMIR:StrongestFrequencyViaSpectralCentroid a rdfs:Resource ;
+ dc:description "The strongest frequency component of a signal, in Hz, found via the spectral centroid." ;
+ local:name "Strongest Frequency Via Spectral Centroid" .
+
+jMIR:StrongestFrequencyViaZeroCrossings a rdfs:Resource ;
+ dc:description "The strongest frequency component of a signal, in Hz, found via the number of zero-crossings." ;
+ local:name "Strongest Frequency Via Zero Crossings" .
+
+jMIR:ZeroCrossings a rdfs:Resource ;
+ dc:description "The number of times the waveform changed sign. An indication of frequency as well as noisiness." ;
+ local:name "Zero Crossings" .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-libXtract.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-libXtract.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,121 @@
+@prefix libXtract: .
+@prefix rdfs: .
+
+libXtract:Amdf a rdfs:Resource .
+
+libXtract:Asdf a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Autocorrelation a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Crest a rdfs:Resource .
+
+libXtract:Dct a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:F0 a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Flatness a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Flux a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Hps a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Kurtosis a rdfs:Resource .
+
+libXtract:Lnorm a rdfs:Resource .
+
+libXtract:Loudness a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Lpc a rdfs:Resource .
+
+libXtract:Lpcc a rdfs:Resource .
+
+libXtract:Mean a rdfs:Resource .
+
+libXtract:Mfcc a rdfs:Resource .
+
+libXtract:Noisiness a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Power a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Rolloff a rdfs:Resource .
+
+libXtract:Sharpness a rdfs:Resource .
+
+libXtract:Skewness a rdfs:Resource .
+
+libXtract:Smoothness a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Spectrum a rdfs:Resource .
+
+libXtract:Spread a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Subbands a rdfs:Resource .
+
+libXtract:Sum a rdfs:Resource .
+
+libXtract:Tonality a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+ a rdfs:Resource .
+
+libXtract:Variance a rdfs:Resource .
+
+libXtract:Zcr a rdfs:Resource .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/af-sMIRk.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/af-sMIRk.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,19 @@
+@prefix rdfs: .
+@prefix sMIRk: .
+
+sMIRk:AutoCorrelation a rdfs:Resource .
+
+sMIRk:CrossCorrelation a rdfs:Resource .
+
+sMIRk:LPC a rdfs:Resource .
+
+sMIRk:RMS a rdfs:Resource .
+
+sMIRk:SpectralCentroid a rdfs:Resource .
+
+sMIRk:SpectralFlux a rdfs:Resource .
+
+sMIRk:SpectralRolloff a rdfs:Resource .
+
+sMIRk:ZeroCrossing a rdfs:Resource .
+
diff -r 000000000000 -r 62d2c72e4223 rdfn3/base.n3
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfn3/base.n3 Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,1076 @@
+@prefix local: .
+@prefix owl: .
+
+ a owl:Class ;
+ local:appdomain "audio segmentation" ;
+ local:complexity "medium" ;
+ local:computation "Band-pass Filter (Bank)",
+ "Discrete Fourier Transform",
+ "Energy Spectral Density",
+ "Normalization",
+ "Regression",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "modulation frequency" ;
+ local:feature "4HzModulationEnergy" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "interframe" .
+
+ a owl:Class ;
+ local:appdomain "audio segmentation" ;
+ local:complexity "medium" ;
+ local:computation "Autocorrelation",
+ "Band-pass Filter (Bank)",
+ "Discrete Cosine Transform",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "modulation frequency" ;
+ local:feature "4HzModulationHarmonicCoefficients" ;
+ local:level "physical" ;
+ local:temporalscale "interframe" .
+
+local:AdaptiveTimeFrequencyTransform a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Adaptive Time Frequency Transform",
+ "Spectral binning" ;
+ local:dimensions "42" ;
+ local:domain "frequency" ;
+ local:feature "AdaptiveTimeFrequencyTransform" ;
+ local:level "physical" ;
+ local:temporalscale "global" .
+
+local:AmplitudeDescriptor a owl:Class ;
+ local:appdomain "environmental sound recognition" ;
+ local:complexity "low" ;
+ local:computation "Mean",
+ "Median",
+ "Spectral binning",
+ "Windowing" ;
+ local:dimensions "9" ;
+ local:domain "temporal" ;
+ local:feature "AmplitudeDescriptor" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:AuditoryFilterBankTemporalEnvelopes a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Band-pass Filter (Bank)",
+ "Energy Spectral Density",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "62" ;
+ local:domain "modulation frequency" ;
+ local:feature "AuditoryFilterBankTemporalEnvelopes" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:AutocorrelationMFCCs a owl:Class ;
+ local:appdomain "speech recognition" ;
+ local:complexity "high" ;
+ local:computation "Autocorrelation",
+ "Discrete Cosine Transform",
+ "Discrete Fourier Transform",
+ "Logarithm",
+ "Low-pass Filter",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "cepstral" ;
+ local:feature "AutocorrelationMFCCs" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:BandPeriodicity a owl:Class ;
+ local:appdomain "audio segmentation" ;
+ local:complexity "medium" ;
+ local:computation "Autocorrelation",
+ "Band-pass Filter (Bank)",
+ "Root Mean Square",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:dimensions "4" ;
+ local:domain "modulation frequency" ;
+ local:feature "BandPeriodicity" ;
+ local:level "perceptual" ;
+ local:temporalscale "interframe" .
+
+local:Bandwidth a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Discrete Fourier Transform",
+ "Logarithm",
+ "Median",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "Bandwidth" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:BarkscaleFrequencyCepstralCoefficients a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "high" ;
+ local:computation "Discrete Cosine Transform",
+ "Discrete Fourier Transform",
+ "Logarithm",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "cepstral" ;
+ local:feature "BarkscaleFrequencyCepstralCoefficients" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:BeatHistogram a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Autocorrelation",
+ "Discrete Wavelet Transform",
+ "Low-pass Filter",
+ "Root Mean Square",
+ "Spectral binning",
+ "Windowing" ;
+ local:dimensions "6" ;
+ local:domain "modulation frequency" ;
+ local:feature "BeatHistogram" ;
+ local:level "perceptual" ;
+ local:temporalscale "interframe" .
+
+local:BeatSpectrum a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "high" ;
+ local:computation "Autocorrelation",
+ "Cross-Correlation",
+ "Discrete Fourier Transform",
+ "Logarithm",
+ "Low-pass Filter",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "modulation frequency" ;
+ local:feature "BeatSpectrum" ;
+ local:level "perceptual" ;
+ local:temporalscale "interframe" .
+
+local:BeatTracker a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "high" ;
+ local:computation "Band-pass Filter (Bank)",
+ "Comb Filter (Bank)",
+ "Derivation, Difference",
+ "Low-pass Filter",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "modulation frequency" ;
+ local:feature "BeatTracker" ;
+ local:level "perceptual" ;
+ local:temporalscale "interframe" .
+
+local:ChromaCENSFeatures a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Band-pass Filter Bank",
+ "Low-pass Filter",
+ "Normalization",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "12" ;
+ local:domain "frequency" ;
+ local:feature "ChromaCENSFeatures" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:Chromagram a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Fourier Transform",
+ "Logarithm",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "12" ;
+ local:domain "frequency" ;
+ local:feature "Chromagram" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:CyclicBeatSpectrum a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "high" ;
+ local:computation "Comb Filter (Bank)",
+ "Derivation, Difference",
+ "Discrete Fourier Transform",
+ "Low-pass Filter",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "modulation frequency" ;
+ local:feature "CyclicBeatSpectrum" ;
+ local:level "perceptual" ;
+ local:temporalscale "interframe" .
+
+local:DWPTbasedRhythmFeature a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Autocorrelation",
+ "Discrete Wavelet Transform",
+ "Root Mean Square",
+ "Spectral binning",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "modulation frequency" ;
+ local:feature "DWPTbasedRhythmFeature" ;
+ local:level "perceptual" ;
+ local:temporalscale "interframe" .
+
+local:DaubechiesWaveletCoefficientHistogram a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Wavelet Transform",
+ "Spectral binning",
+ "Windowing" ;
+ local:dimensions "28" ;
+ local:domain "frequency" ;
+ local:feature "DaubechiesWaveletCoefficientHistogram" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:DistortionDiscriminantAnalysis a owl:Class ;
+ local:appdomain "fingerprinting" ;
+ local:complexity "high" ;
+ local:computation "Logarithm",
+ "Modulated Complex Lapped Transform",
+ "Principal Component Analysis",
+ "Windowing" ;
+ local:dimensions "64" ;
+ local:domain "eigendomain" ;
+ local:feature "DistortionDiscriminantAnalysis" ;
+ local:level "physical" ;
+ local:temporalscale "interframe" .
+
+local:HarmonicCoefficient a owl:Class ;
+ local:appdomain "audio segmentation" ;
+ local:complexity "low" ;
+ local:computation "Autocorrelation",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "HarmonicCoefficient" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:HarmonicConcentration a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Fourier Transform",
+ "Energy Spectral Density",
+ "Root Mean Square",
+ "Windowing",
+ "Zero-/Level Crossing Detector" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "HarmonicConcentration" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:HarmonicDerivate a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Derivation, Difference",
+ "Discrete Fourier Transform",
+ "Logarithm",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "HarmonicDerivate" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:HarmonicEnergyEntropy a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Fourier Transform",
+ "Entropy",
+ "Windowing",
+ "Zero-/Level Crossing Detector" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "HarmonicEnergyEntropy" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:HarmonicProminence a owl:Class ;
+ local:appdomain "environmental sound recognition" ;
+ local:complexity "medium" ;
+ local:computation "Autocorrelation",
+ "Windowing",
+ "Zero-/Level Crossing Detector" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "HarmonicProminence" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:Inharmonicity a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Autocorrelation",
+ "Median",
+ "Windowing",
+ "Zero-/Level Crossing Detector" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "Inharmonicity" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:IntegralLoudness a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "high" ;
+ local:computation "(Non-) Linear Weighting Function",
+ "Discrete Fourier Transform",
+ "Exponential Function",
+ "Logarithm",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "IntegralLoudness" ;
+ local:level "perceptual" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:JointAcousticandModuluationFrequency a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "high" ;
+ local:computation "Discrete Fourier Transform",
+ "Discrete Wavelet Transform",
+ "Low-pass Filter",
+ "Regression",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "modulation frequency" ;
+ local:feature "JointAcousticandModuluationFrequency" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "interframe" .
+
+local:LineSpectralFrequencies a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "medium" ;
+ local:computation "Autoregression (Linear Prediction Analysis)",
+ "Percentile",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "LineSpectralFrequencies" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:LinearPredictionCepstralCoefficients a owl:Class ;
+ local:abbreviation "LPCC" ;
+ local:appdomain "speech recognition" ;
+ local:complexity "medium" ;
+ local:computation "Autoregression (Linear Prediction Analysis)",
+ "Band-pass Filter (Bank)",
+ "Cepstral Recursion Formula",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "cepstral" ;
+ local:feature "LinearPredictionCepstralCoefficients" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:LinearPredictionZCR a owl:Class ;
+ local:appdomain "speech recognition" ;
+ local:complexity "low" ;
+ local:computation "Autoregression (Linear Prediction Analysis)",
+ "Spectral binning",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "temporal" ;
+ local:feature "LinearPredictionZCR" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:LinearPredictiveCoding a owl:Class ;
+ local:abbreviation "LPC" ;
+ local:appdomain "speech recognition" ;
+ local:complexity "low" ;
+ local:computation "Autoregression (Linear Prediction Analysis)",
+ "Band-pass Filter (Bank)",
+ "Discrete Fourier Transform",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "LinearPredictiveCoding" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:MPEG7AudioFundamentalFrequency a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Autocorrelation",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "2" ;
+ local:domain "frequency" ;
+ local:feature "MPEG7AudioFundamentalFrequency" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:MPEG7AudioHarmonicity a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "medium" ;
+ local:computation "Autocorrelation",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "2" ;
+ local:domain "frequency" ;
+ local:feature "MPEG7AudioHarmonicity" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:MPEG7AudioSpectrumBasis a owl:Class ;
+ local:appdomain "environmental sound recognition" ;
+ local:complexity "high" ;
+ local:computation "Discrete Fourier Transform",
+ "Independent Component Analysis",
+ "Logarithm",
+ "Normalization",
+ "Regression",
+ "Singular Value Decomposition",
+ "Windowing" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "parameterized" ;
+ local:domain "eigendomain" ;
+ local:feature "MPEG7AudioSpectrumBasis" ;
+ local:level "physical" ;
+ local:temporalscale "interframe" .
+
+local:MPEG7AudioSpectrumCentroid a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Fourier Transform",
+ "Logarithm",
+ "Mean",
+ "Regression",
+ "Windowing" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "MPEG7AudioSpectrumCentroid" ;
+ local:level "perceptual" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:MPEG7AudioSpectrumSpread a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Fourier Transform",
+ "Logarithm",
+ "Median",
+ "Regression",
+ "Windowing" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "MPEG7AudioSpectrumSpread" ;
+ local:level "perceptual" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:MPEG7AudioWaveform a owl:Class ;
+ local:complexity "low" ;
+ local:computation "Histogram",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "2" ;
+ local:domain "temporal" ;
+ local:feature "MPEG7AudioWaveform" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:MPEG7HarmonicSpectralCentroid a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Fourier Transform",
+ "Mean",
+ "Windowing",
+ "Zero-/Level Crossing Detector" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "MPEG7HarmonicSpectralCentroid" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:MPEG7HarmonicSpectralDeviation a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Fourier Transform",
+ "Logarithm",
+ "Mean",
+ "Median",
+ "Windowing",
+ "Zero-/Level Crossing Detector" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "MPEG7HarmonicSpectralDeviation" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:MPEG7HarmonicSpectralSpread a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Fourier Transform",
+ "Median",
+ "Windowing",
+ "Zero-/Level Crossing Detector" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "MPEG7HarmonicSpectralSpread" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:MPEG7HarmonicSpectralVariation a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Cross-Correlation",
+ "Discrete Fourier Transform",
+ "Windowing",
+ "Zero-/Level Crossing Detector" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "MPEG7HarmonicSpectralVariation" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:MPEG7LogAttackTime a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "low" ;
+ local:computation "Logarithm",
+ "Power",
+ "Root Mean Square",
+ "Windowing" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "1" ;
+ local:domain "temporal" ;
+ local:feature "MPEG7LogAttackTime" ;
+ local:level "physical" ;
+ local:temporalscale "global" .
+
+local:MPEG7SpectralCentroid a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "low" ;
+ local:computation "Discrete Fourier Transform",
+ "Mean" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "MPEG7SpectralCentroid" ;
+ local:level "perceptual" ;
+ local:temporalscale "global" .
+
+local:MPEG7TemporalCentroid a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "low" ;
+ local:computation "Mean",
+ "Power",
+ "Windowing" ;
+ local:computedIn "MPEG-7" ;
+ local:dimensions "1" ;
+ local:domain "temporal" ;
+ local:feature "MPEG7TemporalCentroid" ;
+ local:level "physical" ;
+ local:temporalscale "interframe" .
+
+local:MelscaleFrequencyCepstralCoefficients a owl:Class ;
+ local:abbreviation "MFCC" ;
+ local:appdomain "several" ;
+ local:complexity "high" ;
+ local:computation "Discrete Cosine Transform",
+ "Discrete Fourier Transform",
+ "Logarithm",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "cepstral" ;
+ local:feature "MelscaleFrequencyCepstralCoefficients" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:ModifiedGroupDelay a owl:Class ;
+ local:appdomain "speech recognition" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Cosine Transform",
+ "Discrete Fourier Transform",
+ "Group Delay Function",
+ "Low-pass Filter",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "ModifiedGroupDelay" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:MultiresolutionEntropy a owl:Class ;
+ local:appdomain "speech recognition" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Fourier Transform",
+ "Entropy",
+ "Normalization",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "MultiresolutionEntropy" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:NoiseRobustAuditoryFeature a owl:Class ;
+ local:appdomain "environmental sound recognition" ;
+ local:complexity "high" ;
+ local:computation "(Non-) Linear Weighting Function",
+ "Band-pass Filter Bank",
+ "Derivation, Difference",
+ "Discrete Cosine Transform",
+ "Logarithm",
+ "Low-pass Filter",
+ "Windowing" ;
+ local:dimensions "256" ;
+ local:domain "cepstral" ;
+ local:feature "NoiseRobustAuditoryFeature" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:PerceptualLinearPrediction a owl:Class ;
+ local:appdomain "speech recognition" ;
+ local:complexity "high" ;
+ local:computation "(Non-) Linear Weighting Function",
+ "Autoregression (Linear Prediction Analysis)",
+ "Cepstral Recursion Formula",
+ "Discrete Cosine Transform",
+ "Discrete Fourier Transform",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "cepstral" ;
+ local:feature "PerceptualLinearPrediction" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:PhaseSpaceFeatures a owl:Class ;
+ local:appdomain "speech recognition" ;
+ local:complexity "high" ;
+ local:computation "Phase Space Embedding",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "phase space" ;
+ local:feature "PhaseSpaceFeatures" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:Pitch a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Autocorrelation",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "Pitch" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:PitchHistogram a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Autocorrelation",
+ "Root Mean Square",
+ "Spectral binning",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "PitchHistogram" ;
+ local:level "perceptual" ;
+ local:temporalscale "interframe" .
+
+local:PitchProfile a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "high" ;
+ local:computation "Constant Q Transform",
+ "Root Mean Square",
+ "Spectral binning",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:dimensions "12" ;
+ local:domain "frequency" ;
+ local:feature "PitchProfile" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:PitchSynchronousZCPA a owl:Class ;
+ local:appdomain "speech recognition" ;
+ local:complexity "medium" ;
+ local:computation "Autocorrelation",
+ "Band-pass Filter (Bank)",
+ "Logarithm",
+ "Root Mean Square",
+ "Spectral binning",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "temporal" ;
+ local:feature "PitchSynchronousZCPA" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:PsychoacousticalPitch a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "high" ;
+ local:computation "(Non-) Linear Weighting Function",
+ "Autocorrelation",
+ "Band-pass Filter (Bank)",
+ "Root Mean Square" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "PsychoacousticalPitch" ;
+ local:level "perceptual" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:PulseMetric a owl:Class ;
+ local:appdomain "audio segmentation" ;
+ local:complexity "medium" ;
+ local:computation "Autocorrelation",
+ "Band-pass Filter (Bank)",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "modulation frequency" ;
+ local:feature "PulseMetric" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:RatescalefrequencyFeatures a owl:Class ;
+ local:appdomain "environmental sound recognition" ;
+ local:complexity "high" ;
+ local:computation "(Non-) Linear Weighting Function",
+ "Band-pass Filter Bank",
+ "Derivation, Difference",
+ "Discrete Wavelet Transform",
+ "Low-pass Filter",
+ "Principal Component Analysis",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "256" ;
+ local:domain "eigendomain" ;
+ local:feature "RatescalefrequencyFeatures" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "interframe" .
+
+local:RelativeSpectralPLP a owl:Class ;
+ local:appdomain "speech recognition" ;
+ local:complexity "high" ;
+ local:computation "(Non-) Linear Weighting Function",
+ "Autoregression (Linear Prediction Analysis)",
+ "Band-pass Filter (Bank)",
+ "Cepstral Recursion Formula",
+ "Discrete Cosine Transform",
+ "Discrete Fourier Transform",
+ "Exponential Function",
+ "Logarithm",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "cepstral" ;
+ local:feature "RelativeSpectralPLP" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:RhythmPatterns a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "high" ;
+ local:computation "(Non-) Linear Weighting Function",
+ "Discrete Fourier Transform",
+ "Harmonic Peak Detection",
+ "Logarithm",
+ "Low-pass Filter",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "80" ;
+ local:domain "modulation frequency" ;
+ local:feature "RhythmPatterns" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "interframe" .
+
+local:Sharpness a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "medium" ;
+ local:computation "(Non-) Linear Weighting Function",
+ "Discrete Fourier Transform",
+ "Mean",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "Sharpness" ;
+ local:level "perceptual" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:ShortTimeEnergy a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Deviation, Sum of Differences",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "temporal" ;
+ local:feature "ShortTimeEnergy" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:Sone a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "high" ;
+ local:computation "(Non-) Linear Weighting Function",
+ "Discrete Fourier Transform",
+ "Logarithm",
+ "Low-pass Filter",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "Sone" ;
+ local:level "perceptual" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:SpectralCenter a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "low" ;
+ local:computation "Discrete Fourier Transform",
+ "Energy Spectral Density",
+ "Harmonic Peak Detection",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "SpectralCenter" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:SpectralCentroid a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Discrete Fourier Transform",
+ "Logarithm",
+ "Mean",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "SpectralCentroid" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:SpectralCrest a owl:Class ;
+ local:appdomain "fingerprinting" ;
+ local:complexity "low" ;
+ local:computation "Discrete Fourier Transform",
+ "Logarithm",
+ "Mean",
+ "Regression",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "SpectralCrest" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:SpectralDispersion a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "low" ;
+ local:computation "Discrete Fourier Transform",
+ "Energy Spectral Density",
+ "Harmonic Peak Detection",
+ "Median",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "SpectralDispersion" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:SpectralFlatness a owl:Class ;
+ local:appdomain "fingerprinting" ;
+ local:complexity "medium" ;
+ local:computation "Discrete Fourier Transform",
+ "Logarithm",
+ "Mean",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "SpectralFlatness" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:SpectralFlux a owl:Class ;
+ local:abbreviation "SF" ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Derivation, Difference",
+ "Discrete Fourier Transform",
+ "Root Mean Square",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "SpectralFlux" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:SpectralPeakStructure a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "medium" ;
+ local:computation "Derivation, Difference",
+ "Discrete Fourier Transform",
+ "Entropy",
+ "Spectral binning",
+ "Windowing",
+ "Zero-/Level Crossing Detector" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "SpectralPeakStructure" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:SpectralPeaks a owl:Class ;
+ local:appdomain "music information retrieval" ;
+ local:complexity "low" ;
+ local:computation "Derivation, Difference",
+ "Discrete Fourier Transform",
+ "Sum, Weighted Sum",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "SpectralPeaks" ;
+ local:level "physical" ;
+ local:temporalscale "interframe" .
+
+local:SpectralRolloff a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Discrete Fourier Transform",
+ "Polynomial Root Finding",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "frequency" ;
+ local:feature "SpectralRolloff" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:SpectralSlope a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Discrete Fourier Transform",
+ "Peak Detection",
+ "Windowing" ;
+ local:dimensions "4" ;
+ local:domain "frequency" ;
+ local:feature "SpectralSlope" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:SubbandEnergyRatio a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Discrete Fourier Transform",
+ "Energy Spectral Density",
+ "Normalization",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "frequency" ;
+ local:feature "SubbandEnergyRatio" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:SubbandSpectralFlux a owl:Class ;
+ local:appdomain "environmental sound recognition" ;
+ local:complexity "medium" ;
+ local:computation "Derivation, Difference",
+ "Discrete Fourier Transform",
+ "Logarithm",
+ "Mean",
+ "Normalization",
+ "Regression",
+ "Windowing" ;
+ local:dimensions "8" ;
+ local:domain "frequency" ;
+ local:feature "SubbandSpectralFlux" ;
+ local:level "perceptual" ;
+ local:temporalscale "intraframe" .
+
+local:Volume a owl:Class ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Power",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "temporal" ;
+ local:feature "Volume" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
+local:ZeroCrossingPeakAmplitudes a owl:Class ;
+ local:appdomain "speech recognition" ;
+ local:complexity "medium" ;
+ local:computation "Band-pass Filter (Bank)",
+ "Logarithm",
+ "Root Mean Square",
+ "Spectral binning",
+ "Windowing" ;
+ local:dimensions "parameterized" ;
+ local:domain "temporal" ;
+ local:feature "ZeroCrossingPeakAmplitudes" ;
+ local:level "physical" ;
+ local:model "psychoacoustic" ;
+ local:temporalscale "intraframe" .
+
+local:ZeroCrossingRate a owl:Class ;
+ local:abbreviation "ZCR" ;
+ local:appdomain "several" ;
+ local:complexity "low" ;
+ local:computation "Spectral binning",
+ "Windowing" ;
+ local:dimensions "1" ;
+ local:domain "temporal" ;
+ local:feature "ZeroCrossingRate" ;
+ local:level "physical" ;
+ local:temporalscale "intraframe" .
+
diff -r 000000000000 -r 62d2c72e4223 rdfpy/convertXMLtoN3.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfpy/convertXMLtoN3.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,16 @@
+import rdflib, os, fnmatch
+from rdflib import Graph, RDF, RDFS, plugin, URIRef, Literal, OWL
+
+basedir = '/Users/alo/MusicOntology/features/'
+
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+
+for name in os.listdir(basedir+'rdf/'):
+ if fnmatch.fnmatch(name, '*.rdf'):
+ graph = Graph()
+ graph.parse(basedir+'rdf/'+name)
+ graph.bind(name[3:-4], URIRef('file://'+basedir+"rdf/"))
+ graph.bind('owl', 'http://www.w3.org/2002/07/owl#')
+
+ graph.serialize(basedir+'rdfn3/'+name.split('.')[0]+'.n3', format='n3')
+ print "Serialized graph to " + basedir+'rdfn3/'+name.split('.')[0]+'.n3'
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdfpy/writeAubioOnto.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfpy/writeAubioOnto.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,52 @@
+import rdflib
+from rdflib import Graph, RDF, RDFS, plugin, URIRef, Literal, OWL
+
+basedir = '/Users/alo/MusicOntology/features/'
+
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+
+graph = Graph()
+graph.bind('af', URIRef(local))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+graph.bind('owl', URIRef('http://www.w3.org/2002/07/owl#'))
+
+source = Graph()
+source.parse(basedir+'rdfonto/af-aubio.n3', format='n3')
+
+categories = []
+
+for su, ob in source.subject_objects(URIRef('file:///Users/alo/MusicOntology/features/rdf/type')):
+ if not ob in categories:
+ categories.append(ob)
+
+for category in categories:
+ graph.add((
+ URIRef(local+category),
+ RDF.type,
+ OWL.Class
+ ))
+
+for su in source.subjects(RDF.type, RDFS.Resource):
+ idref = URIRef(local+su.split('/')[-1])
+ graph.add((
+ idref,
+ RDF.type,
+ OWL.Class
+ ))
+
+ for ob in source.objects(su,URIRef('file:///Users/alo/MusicOntology/features/rdf/type')):
+ graph.add((
+ idref,
+ RDFS.subClassOf,
+ URIRef(local+ob)
+ ))
+
+ for ob in source.objects(su,URIRef('http://purl.org/dc/elements/1.1/description')):
+ graph.add((
+ idref,
+ URIRef('http://purl.org/dc/elements/1.1/description'),
+ ob
+ ))
+
+graph.serialize(basedir + 'rdfonto/aubio-onto.rdf')
+graph.serialize(basedir + 'rdfonto/aubio-onto.n3', format='n3')
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdfpy/writeBaseOnto.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfpy/writeBaseOnto.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,609 @@
+import rdflib, os, fnmatch, urllib2
+from rdflib import Graph, RDF, RDFS, plugin, URIRef, Literal, OWL, XSD, Namespace
+from xml.dom.minidom import parseString
+
+names = [line.strip() for line in open('pdfextract/names.txt')]
+cat = [line.strip() for line in open('pdfextract/categories.txt')]
+sig = [line.strip() for line in open('pdfextract/sig.txt')]
+
+basedir = '/Users/alo/MusicOntology/features/'
+
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+
+DC = Namespace(u"http://purl.org/dc/elements/1.1/")
+VS = Namespace(u"http://www.w3.org/2003/06/sw-vocab-status/ns#")
+
+graph = Graph()
+graph.bind('af', URIRef(local))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+graph.bind('owl', URIRef('http://www.w3.org/2002/07/owl#'))
+graph.bind('xsd', URIRef('http://www.w3.org/2001/XMLSchema#'))
+graph.bind('vs', URIRef('http://www.w3.org/2003/06/sw-vocab-status/ns#'))
+
+graph.add((
+ URIRef(''),
+ RDF.type,
+ OWL.Ontology
+))
+
+graph.add((
+ URIRef(''),
+ DC['title'],
+ Literal("Audio Features Base Ontology")
+))
+
+graph.add((
+ URIRef(''),
+ OWL.versionInfo,
+ Literal("Version 0.1")
+))
+
+graph.add((
+ URIRef(''),
+ DC['description'],
+ Literal("This is a base ontology for the Audio Features engineering process collected from literature")
+))
+
+graph.add((
+ VS['term_status'],
+ RDF.type,
+ OWL.AnnotationProperty
+))
+
+i = 0
+
+order = [
+ "Zero Crossing Rate",
+ "Linear Predictive Coding",
+ "Mel-scale Frequency Cepstral Coefficients",
+ "Auditory Filter Bank Temporal Envelopes",
+ "Rate-scale-frequency Features",
+ "Phase Space Features"
+]
+
+domains = {
+ "Zero Crossing Rate": 'temporal',
+ "Linear Predictive Coding": 'frequency',
+ "Mel-scale Frequency Cepstral Coefficients": 'cepstral',
+ "Auditory Filter Bank Temporal Envelopes": 'modulation frequency',
+ "Rate-scale-frequency Features": 'eigendomain',
+ "Phase Space Features": 'phase space'
+}
+
+abbr = {
+ "Zero Crossing Rate": "ZCR",
+ "Mel-scale Frequency Cepstral Coefficients": "MFCC",
+ "Linear Predictive Coding": "LPC",
+ "Linear Prediction Cepstral Coefficients": "LPCC",
+ "Zero crossing peak amplitudes": "ZCPA",
+ "Line spectral frequencies": "LSF",
+ "Short-time energy": "STE",
+ "Amplitude descriptor": "AD",
+ "Adaptive time frequency transform": "ATFT",
+ "Daubechies Wavelet coefficient histogram": "DWCH",
+ "Spectral Flux": "SF",
+ "Group delay function": "GDF",
+ "Modified group delay function": "MGDF",
+ "Spectral centroid": "SC",
+ "Subband spectral flux": "SSF",
+ "Perceptual linear prediction": "PLP"
+}
+
+appdom = {
+ 'ASR': "Speech Recognition",
+ 'ESR': "Environmental Sound Recognition",
+ 'MIR': "Music Information Retrieval",
+ 'AS': "Audio Segmentation",
+ 'FP': "Fingerprinting",
+ 'VAR': "Several",
+ 'EXC': ""
+}
+
+domain = ""
+domainIndex = 0
+compdict = {}
+
+graph.add((
+ URIRef(local + 'MathematicalOperation'),
+ RDF.type,
+ OWL.Class
+))
+
+graph.add((
+ URIRef(local + 'Filter'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'Filter'),
+ RDFS.subClassOf,
+ URIRef(local + 'MathematicalOperation')
+))
+
+graph.add((
+ URIRef(local + 'Transformation'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'Transformation'),
+ RDFS.subClassOf,
+ URIRef(local + 'MathematicalOperation')
+))
+graph.add((
+ URIRef(local + 'Aggregation'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'Aggregation'),
+ RDFS.subClassOf,
+ URIRef(local + 'MathematicalOperation')
+))
+
+for filename in ['filters', 'trans', 'aggr']:
+ compsuper = filename.replace('filters', 'Filter').replace('trans', 'Transformation').replace('aggr', 'Aggregation')
+ for line in [line.strip() for line in open(basedir + 'pdfextract/' + filename + '.txt')]:
+ compname = line[2:]
+ compidref = URIRef(local + compname.replace(' ', '').replace('(', '').replace(')', '').replace('-', '').replace(',', ''))
+ graph.add((
+ compidref,
+ RDF.type,
+ OWL.Class
+ ))
+ graph.add((
+ compidref,
+ RDFS.subClassOf,
+ URIRef(local + compsuper)
+ ))
+ graph.add((
+ compidref,
+ RDFS.label,
+ Literal(compname)
+ ))
+ compdict[line[0]] = compidref
+
+graph.add((
+ URIRef(local + 'Signal'),
+ RDF.type,
+ OWL.Class
+))
+
+graph.add((
+ URIRef(local + 'Feature'),
+ RDF.type,
+ OWL.Class
+))
+
+graph.add((
+ URIRef(local + 'Feature'),
+ OWL.subClassOf,
+ URIRef(local + 'Signal'),
+))
+
+for dom in domains.values():
+ idref = URIRef(local + dom.capitalize().replace(' ', '') + 'Feature')
+ graph.add((
+ idref,
+ RDF.type,
+ OWL.Class
+ ))
+ graph.add((
+ idref,
+ RDFS.subClassOf,
+ URIRef(local + 'Feature')
+ ))
+
+graph.add((
+ URIRef(local + 'PerceptualFeature'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'PerceptualFeature'),
+ RDFS.subClassOf,
+ URIRef(local + 'Feature')
+))
+
+graph.add((
+ URIRef(local + 'FrequencyDomainPerceptualFeature'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'FrequencyDomainPerceptualFeature'),
+ RDFS.subClassOf,
+ URIRef(local + 'FrequencyFeature')
+))
+graph.add((
+ URIRef(local + 'FrequencyDomainPerceptualFeature'),
+ OWL.equivalentClass,
+ URIRef(local + 'PerceptualFeature')
+))
+
+graph.add((
+ URIRef(local + 'FrequencyDomainPhysicalFeature'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'FrequencyDomainPhysicalFeature'),
+ RDFS.subClassOf,
+ URIRef(local + 'FrequencyFeature')
+))
+graph.add((
+ URIRef(local + 'FrequencyDomainPhysicalFeature'),
+ OWL.equivalentClass,
+ URIRef(local + 'PhysicalFeature')
+))
+
+
+
+graph.add((
+ URIRef(local + 'PhysicalFeature'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'PhysicalFeature'),
+ RDFS.subClassOf,
+ URIRef(local + 'Feature')
+))
+
+graph.add((
+ URIRef(local + 'ParametrizedDimensions'),
+ RDF.type,
+ OWL.Class
+))
+
+graph.add((
+ URIRef(local + 'ComputationalComplexity'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'LowComplexity'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'LowComplexity'),
+ RDFS.subClassOf,
+ URIRef(local + 'ComputationalComplexity')
+))
+graph.add((
+ URIRef(local + 'MediumComplexity'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'MediumComplexity'),
+ RDFS.subClassOf,
+ URIRef(local + 'ComputationalComplexity')
+))
+graph.add((
+ URIRef(local + 'HighComplexity'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'HighComplexity'),
+ RDFS.subClassOf,
+ URIRef(local + 'ComputationalComplexity')
+))
+
+graph.add((
+ URIRef(local + 'TemporalScale'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'IntraFrame'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'IntraFrame'),
+ RDFS.subClassOf,
+ URIRef(local + 'TemporalScale')
+))
+graph.add((
+ URIRef(local + 'InterFrame'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'InterFrame'),
+ RDFS.subClassOf,
+ URIRef(local + 'TemporalScale')
+))
+graph.add((
+ URIRef(local + 'Global'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local + 'Global'),
+ RDFS.subClassOf,
+ URIRef(local + 'TemporalScale')
+))
+
+
+graph.add((
+ URIRef(local + 'ApplicationDomain'),
+ RDF.type,
+ OWL.Class
+))
+
+for key in appdom.keys():
+ if appdom[key] != "":
+ idref = URIRef(local + appdom[key].replace(" ", ""))
+ graph.add((
+ idref,
+ URIRef(RDF.type),
+ OWL.Class
+ ))
+ graph.add((
+ idref,
+ RDFS.subClassOf,
+ URIRef(local + 'ApplicationDomain')
+ ))
+
+#properties
+graph.add((
+ URIRef(local + "application_domain"),
+ RDF.type,
+ RDF.Property
+))
+graph.add((
+ URIRef(local + "application_domain"),
+ RDFS.range,
+ URIRef(local + 'ApplicationDomain')
+))
+graph.add((
+ URIRef(local + "application_domain"),
+ VS['term_status'],
+ Literal("testing")
+))
+graph.add((
+ URIRef(local + "application_domain"),
+ RDFS.comment,
+ Literal("application domain property")
+))
+
+
+
+graph.add((
+ URIRef(local + "semantic_interpretation"),
+ RDF.type,
+ RDF.Property
+))
+graph.add((
+ URIRef(local + "semantic_interpretation"),
+ VS['term_status'],
+ Literal("testing")
+))
+
+graph.add((
+ URIRef(local + "computational_complexity"),
+ RDF.type,
+ RDF.Property
+))
+graph.add((
+ URIRef(local + "computational_complexity"),
+ VS['term_status'],
+ Literal("testing")
+))
+
+graph.add((
+ URIRef(local + "computational_complexity"),
+ RDFS.range,
+ URIRef(local + 'ComputationalComplexity')
+))
+
+graph.add((
+ URIRef(local + "psychoacoustic_model"),
+ RDF.type,
+ RDF.Property
+))
+graph.add((
+ URIRef(local + "psychoacoustic_model"),
+ RDFS.range,
+ XSD.Boolean
+))
+graph.add((
+ URIRef(local + "psychoacoustic_model"),
+ VS['term_status'],
+ Literal("testing")
+))
+
+
+graph.add((
+ URIRef(local + "dimensions"),
+ RDF.type,
+ RDF.Property
+))
+graph.add((
+ URIRef(local + "dimensions"),
+ RDFS.range,
+ XSD.Integer
+))
+graph.add((
+ URIRef(local + "dimensions"),
+ RDFS.range,
+ URIRef(local + 'ParametrizedDimensions')
+))
+
+graph.add((
+ URIRef(local + "temporal_scale"),
+ RDF.type,
+ RDF.Property
+))
+graph.add((
+ URIRef(local + "temporal_scale"),
+ RDFS.range,
+ URIRef(local + 'TemporalScale')
+))
+
+for name in names:
+ id = local + (name.replace(' ','').replace('-',''))
+
+ if name == order[domainIndex]:
+ domain = domains[order[domainIndex]]
+ domainIndex += 1
+
+ graph.add(( URIRef(id),
+ URIRef('http://www.w3.org/1999/02/22-rdf-syntax-ns#type'),
+ OWL.Class
+ ))
+
+ graph.add((
+ URIRef(id),
+ VS['term_status'],
+ Literal("testing")
+ ))
+
+ if domain == "frequency":
+ if word[1] == 'Y':
+ temp = URIRef(local + 'FrequencyDomainPerceptualFeature')
+ else:
+ temp = URIRef(local + 'FrequencyDomainPhysicalFeature')
+
+ graph.add((
+ URIRef(id),
+ RDFS.subClassOf,
+ URIRef(temp)
+ ))
+
+ else:
+ graph.add((
+ URIRef(id),
+ RDFS.subClassOf,
+ URIRef(local + domain.capitalize().replace(' ', '') + 'Feature')
+ ))
+
+ graph.add((
+ URIRef(id),
+ #URIRef(local + 'feature'),
+ RDFS.label,
+ Literal(name.replace(' ','').replace('-',''))
+ ))
+
+ graph.add((
+ URIRef(id),
+ RDFS.comment,
+ Literal(name + " feature")
+ ))
+
+ graph.add((
+ URIRef(id),
+ RDFS.label,
+ Literal(name)
+ ))
+
+ word = cat[i].split(' ')
+
+ temp = {
+ 'I': URIRef(local+'IntraFrame'),
+ 'X': URIRef(local+'InterFrame'),
+ 'G': URIRef(local+'Global')
+ }[word[0]]
+
+ graph.add((
+ URIRef(id),
+ URIRef(local + 'temporal_scale'),
+ temp
+ ))
+
+
+ if word[1] == 'Y':
+ temp = URIRef(local + 'PerceptualFeature')
+ else:
+ temp = URIRef(local + 'PhysicalFeature')
+
+ graph.add((
+ URIRef(id),
+ URIRef(local + "semantic_interpretation"),
+ temp
+ ))
+
+ if word[2] == 'Y':
+ graph.add((
+ URIRef(id),
+ URIRef(local + "psychoacoustic_model"),
+ Literal(True)
+ ))
+ else:
+ graph.add((
+ URIRef(id),
+ URIRef(local + "psychoacoustic_model"),
+ Literal(False)
+ ))
+
+ temp = {
+ 'L': URIRef(local + 'LowComplexity'),
+ 'M': URIRef(local + 'MediumComplexity'),
+ 'H': URIRef(local + 'HighComplexity')
+ }[word[3]]
+
+ graph.add((
+ URIRef(id),
+ URIRef(local + "computational_complexity"),
+ temp
+ ))
+
+ if word[4] == 'V':
+ temp = URIRef(local + 'ParametrizedDimensions')
+ else:
+ temp = Literal(int(word[4]))
+
+ graph.add((
+ URIRef(id),
+ URIRef(local + 'dimensions'),
+ temp
+ ))
+
+ temp = appdom[word[5]]
+
+ if temp != '':
+ graph.add((
+ URIRef(id),
+ URIRef(local + "application_domain"),
+ URIRef(local + temp.replace(" ", ""))
+ ))
+
+ steps = sig[i].split(' ')
+
+ for key in steps:
+ graph.add((
+ URIRef(id),
+ URIRef(local + 'computation'),
+ compdict[key]
+ ))
+
+ if name.find('MPEG-7') >= 0:
+ graph.add((
+ URIRef(id),
+ URIRef(local + 'computedIn'),
+ Literal('MPEG-7')
+ ))
+ #graph.add((
+ # URIRef(local+name.replace('MPEG-7', '').lower().lstrip().replace(' ', '_')+'_feature'),
+ # RDF.type,
+ # URIRef(id)
+ #))
+
+ if name in abbr.keys():
+ graph.add((
+ URIRef(id),
+ URIRef(local + 'abbreviation'),
+ Literal(abbr[name])
+ ))
+
+
+ i += 1
+
+
+
+graph.serialize('/Users/alo/MusicOntology/features/baseOnto.n3', format='n3')
+graph.serialize('/Users/alo/MusicOntology/features/baseOnto.rdf')
diff -r 000000000000 -r 62d2c72e4223 rdfpy/writeCatalogue.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfpy/writeCatalogue.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,27 @@
+import rdflib, os, fnmatch, urllib2
+from rdflib import Graph, RDF, RDFS, plugin, URIRef, Literal, OWL
+from xml.dom.minidom import parseString
+
+ns = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+
+basedir = '/Users/alo/MusicOntology/features/'
+
+execfile(basedir + 'pdfextract/graphDefs.py')
+
+graph = Graph()
+graph.bind('af', URIRef(ns))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+graph.bind('owl', OWL)
+
+addBaseTriples(graph, ns)
+
+loadBase( graph, basedir + 'rdf/base.rdf' )
+
+for name in os.listdir(basedir+'rdf/'):
+ if fnmatch.fnmatch(name, 'af-*.rdf'):
+ addTriplesFromFile(graph, basedir+'rdf/'+name, ns)
+
+compareForSimilarities(graph, ns)
+
+graph.serialize(basedir + 'af-catalogue.rdf')
+graph.serialize(basedir + 'af-catalogue.n3', format='n3')
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdfpy/writeMIRToolboxOnto.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfpy/writeMIRToolboxOnto.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,125 @@
+import rdflib, os
+from rdflib import Graph, RDF, RDFS, plugin, URIRef, Literal, OWL, Namespace
+
+basedir = '/Users/alo/MusicOntology/features/'
+
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+
+DC = Namespace(u"http://purl.org/dc/elements/1.1/")
+
+graph = Graph()
+graph.bind('af', URIRef(local))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+graph.bind('owl', URIRef('http://www.w3.org/2002/07/owl#'))
+
+graph.add((
+ URIRef(''),
+ RDF.type,
+ OWL.Ontology
+))
+
+graph.add((
+ URIRef(''),
+ DC['title'],
+ Literal("MIR Toolbox Ontology")
+))
+
+graph.add((
+ URIRef(''),
+ OWL.versionInfo,
+ Literal("Version 0.1")
+))
+
+graph.add((
+ URIRef(''),
+ DC['description'],
+ Literal("This is an ontology derived from MIR Toolbox for the Audio Features engineering process")
+))
+
+source = Graph()
+source.parse(basedir+'rdfonto/af-MIRToolbox.rdf')
+
+graph.add((
+ URIRef(local+'Operator'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local+'FeatureExtractor'),
+ RDF.type,
+ OWL.Class
+))
+graph.add((
+ URIRef(local+'HighLevelFeature'),
+ RDF.type,
+ OWL.Class
+))
+
+for name in ['Structure', 'Statistics', 'Predictions', 'Similarity']:
+ idref = URIRef(local+name)
+ graph.add((
+ idref,
+ RDF.type,
+ OWL.Class
+ ))
+ graph.add((
+ idref,
+ RDFS.subClassOf,
+ URIRef(local+'HighLevelFeature')
+ ))
+
+
+for name in ['Dynamics', 'Rhythm', 'Timbre', 'Pitch', 'Tonality']:
+ idref = URIRef(local+name+'FeatureExtractor')
+ graph.add((
+ idref,
+ RDF.type,
+ OWL.Class
+ ))
+ graph.add((
+ idref,
+ RDFS.subClassOf,
+ URIRef(local+'FeatureExtractor')
+ ))
+
+for su in source.subjects(RDF.type, RDFS.Resource):
+ idref = URIRef(local + su.split('/')[-1])
+ graph.add((
+ idref,
+ RDF.type,
+ OWL.Class
+ ))
+
+ count=sum(1 for _ in source.objects(su, URIRef(local+'tag')))
+
+ if count == 1:
+ for it in source.objects(su, URIRef(local+'tag')):
+ graph.add((
+ idref,
+ RDFS.subClassOf,
+ URIRef(local+it+'FeatureExtractor')
+ ))
+
+ count = sum(1 for _ in source.objects(su, URIRef(local+'group')))
+
+ if count == 1:
+ for it in source.objects(su, URIRef(local+'group')):
+ graph.add((
+ idref,
+ RDFS.subClassOf,
+ URIRef(local+it)
+ ))
+
+ count=sum(1 for _ in source.objects(su, URIRef(local+'type')))
+
+ if count == 1:
+ for it in source.objects(su, URIRef(local+'type')):
+ if it == "Operator":
+ graph.add((
+ idref,
+ RDFS.subClassOf,
+ URIRef(local+it)
+ ))
+
+graph.serialize(basedir + 'rdfonto/MIR-onto.rdf')
+graph.serialize(basedir + 'rdfonto/MIR-onto.n3', format='n3')
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdfpy/writeMarsyas.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfpy/writeMarsyas.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,42 @@
+import rdflib, os, fnmatch, urllib2
+from rdflib import Graph, RDF, RDFS, plugin, URIRef, Literal, OWL
+
+############# Marsyas ###############
+def removeNonAscii(s): return "".join(i for i in s if ord(i)<128)
+
+mdir = '/Users/alo/Development/MIR/marsyas-0.4.7/src/marsyas/'
+
+graph = Graph()
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+graph.bind('local', URIRef(local))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+
+for name in os.listdir(mdir):
+ if fnmatch.fnmatch(name, '*.h'):
+ file = open(mdir + name)
+ code = file.read()
+ file.close()
+ if ('\ingroup' in code) and ('Analysis' in code):
+ if code.find('\class') == -1:
+ cl = name[:-2]
+ else:
+ cl = code[code.find('\class')+7:code.find('\n', code.find('\class')+7)]
+
+ br = code[code.find('brief')+5:code.find('*/', code.find('brief')+5)]
+ br = br.replace('\n', ' ')
+ br = " ".join(br.split())
+
+ br = removeNonAscii(br)
+
+ graph.add((
+ URIRef(cl),
+ URIRef('http://www.w3.org/1999/02/22-rdf-syntax-ns#type'),
+ URIRef('http://www.w3.org/2000/01/rdf-schema#Resource')
+ ))
+ graph.add((
+ URIRef(cl),
+ URIRef('http://purl.org/dc/elements/1.1/description'),
+ Literal(br)
+ ))
+
+graph.serialize('/Users/alo/MusicOntology/features/rdfn3/af-Marsyas.n3', format='n3')
diff -r 000000000000 -r 62d2c72e4223 rdfpy/writeMarsyasOnto.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfpy/writeMarsyasOnto.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,99 @@
+import rdflib
+from rdflib import Graph, RDF, RDFS, plugin, URIRef, Literal, OWL, Namespace
+
+basedir = '/Users/alo/MusicOntology/features/'
+
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+
+DC = Namespace(u"http://purl.org/dc/elements/1.1/")
+
+graph = Graph()
+graph.bind('af', URIRef(local))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+graph.bind('owl', URIRef('http://www.w3.org/2002/07/owl#'))
+
+graph.add((
+ URIRef(''),
+ RDF.type,
+ OWL.Ontology
+))
+
+graph.add((
+ URIRef(''),
+ DC['title'],
+ Literal("Marsyas Ontology")
+))
+
+graph.add((
+ URIRef(''),
+ OWL.versionInfo,
+ Literal("Version 0.1")
+))
+
+graph.add((
+ URIRef(''),
+ DC['description'],
+ Literal("This is an ontology derived from Marsyas feature extraction tools for the Audio Features engineering process")
+))
+
+
+source = Graph()
+source.parse(basedir+'rdfonto/af-Marsyas.n3', format='n3')
+
+categories = []
+
+for su, ob in source.subject_objects(URIRef('file:///Users/alo/MusicOntology/features/rdf/type')):
+ if not ob in categories:
+ categories.append(ob)
+
+graph.add((
+ URIRef(local+'Analysis'),
+ RDF.type,
+ OWL.Class
+))
+
+for category in categories:
+ graph.add((
+ URIRef(local+category),
+ RDF.type,
+ OWL.Class
+ ))
+ graph.add((
+ URIRef(local+category),
+ RDFS.subClassOf,
+ URIRef(local+'Analysis'),
+ ))
+
+for su in source.subjects(RDF.type, RDFS.Resource):
+ idref = URIRef(local+su.split('/')[-1])
+ graph.add((
+ idref,
+ RDF.type,
+ OWL.Class
+ ))
+
+ count = sum(1 for _ in source.objects(su,URIRef('file:///Users/alo/MusicOntology/features/rdf/type')))
+
+ if count > 0:
+ for ob in source.objects(su,URIRef('file:///Users/alo/MusicOntology/features/rdf/type')):
+ graph.add((
+ idref,
+ RDFS.subClassOf,
+ URIRef(local+ob)
+ ))
+ else:
+ graph.add((
+ idref,
+ RDFS.subClassOf,
+ URIRef(local+'Analysis'),
+ ))
+
+ for ob in source.objects(su,URIRef('http://purl.org/dc/elements/1.1/description')):
+ graph.add((
+ idref,
+ URIRef('http://purl.org/dc/elements/1.1/description'),
+ ob
+ ))
+
+graph.serialize(basedir + 'rdfonto/Marsyas-onto.rdf')
+graph.serialize(basedir + 'rdfonto/Marsyas-onto.n3', format='n3')
\ No newline at end of file
diff -r 000000000000 -r 62d2c72e4223 rdfpy/writeRDFs.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/rdfpy/writeRDFs.py Mon Feb 25 14:40:54 2013 +0000
@@ -0,0 +1,272 @@
+import rdflib, os, fnmatch, urllib2
+from rdflib import Graph, RDF, RDFS, plugin, URIRef, Literal, OWL
+from xml.dom.minidom import parseString
+
+############# Vamp ###############
+
+vampdir = '/Users/alo/Library/Audio/Plug-Ins/Vamp/'
+
+source = Graph()
+
+graph = Graph()
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+graph.bind('local', URIRef(local))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+
+for name in os.listdir(vampdir):
+ if fnmatch.fnmatch(name, '*.n3'):
+
+ print (vampdir + name)
+
+ source.parse(vampdir + name, format='n3')
+
+ for su, pr in source.subject_predicates(URIRef('http://purl.org/ontology/vamp/Plugin')):
+
+ for name in source.objects(su, URIRef('http://purl.org/ontology/vamp/name')):
+ id = name.replace(' ', '').replace('Marsyas-BatchFeatureExtract-', '')
+ feature = name
+ graph.add((
+ URIRef(id),
+ URIRef('http://www.w3.org/1999/02/22-rdf-syntax-ns#type'),
+ URIRef('http://www.w3.org/2000/01/rdf-schema#Resource')
+ ))
+ graph.add((
+ URIRef(id),
+ URIRef(local+'feature'),
+ Literal(feature)
+ ))
+ for domain in source.objects(su, URIRef('http://purl.org/ontology/vamp/input_domain')):
+ dom = domain.split('/')[-1].replace('Domain', '')
+ dom = dom.lower().replace('Time', 'temporal')
+ graph.add((
+ URIRef(id),
+ URIRef(local+'domain'),
+ Literal(dom)
+ ))
+ for desc in source.objects(su, URIRef('http://purl.org/dc/elements/1.1/description')):
+ description = " ".join(desc.split())
+ graph.add((
+ URIRef(id),
+ URIRef('http://purl.org/dc/elements/1.1/description'),
+ Literal(description)
+ ))
+ for maker in source.objects(su, URIRef('http://xmlns.com/foaf/0.1/maker')):
+ for mname in source.objects(maker, URIRef('http://xmlns.com/foaf/0.1/name')):
+ makername = mname
+ graph.add((
+ URIRef(id),
+ URIRef(local+'source'),
+ Literal(makername)
+ ))
+
+ count=sum(1 for _ in source.objects(su, URIRef('http://purl.org/ontology/vamp/output')))
+
+ if count == 1:
+ for it in source.objects(su, URIRef('http://purl.org/ontology/vamp/output')):
+ for output in source.objects(it, URIRef('http://www.w3.org/1999/02/22-rdf-syntax-ns#type')):
+ out = output.split('/')[-1].replace('Output', '')
+ if out.find('Sparse') >= 0 or out.find('Dense') >= 0:
+ graph.add((
+ URIRef(id),
+ URIRef(local+'output'),
+ Literal(out)
+ ))
+
+ else:
+ for it in source.objects(su, URIRef('http://purl.org/ontology/vamp/output')):
+ for name in source.objects(it, URIRef('http://purl.org/dc/elements/1.1/title')):
+ if name != feature:
+ subid = name.replace(' ', '')
+ graph.add((
+ URIRef(subid),
+ URIRef('http://www.w3.org/1999/02/22-rdf-syntax-ns#type'),
+ URIRef('http://www.w3.org/2000/01/rdf-schema#Resource')
+ ))
+ graph.add((
+ URIRef(subid),
+ URIRef(local+'feature'),
+ Literal(name + " (" + feature + ")")
+ ))
+ graph.add((
+ URIRef(subid),
+ URIRef(local+'domain'),
+ Literal(dom)
+ ))
+ graph.add((
+ URIRef(subid),
+ URIRef(local+'source'),
+ Literal(makername)
+ ))
+ for output in source.objects(it, URIRef('http://www.w3.org/1999/02/22-rdf-syntax-ns#type')):
+ out = output.split('/')[-1].replace('Output', '')
+ if out.find('Sparse') >= 0 or out.find('Dense') >= 0:
+ graph.add((
+ URIRef(subid),
+ URIRef(local+'output'),
+ Literal(out)
+ ))
+
+graph.serialize('/Users/alo/MusicOntology/features/rdf/af-Vamp.rdf')
+
+############# Marsyas ###############
+mdir = '/Users/alo/Development/MIR/marsyas-0.4.7/src/marsyas/'
+
+madict = {}
+
+graph = Graph()
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+graph.bind('local', URIRef(local))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+
+for name in os.listdir(mdir):
+ if fnmatch.fnmatch(name, '*.h'):
+ code = [line.strip() for line in open(mdir + name)]
+ found = False
+ for line in code:
+ if line.find('\ingroup Analysis') >= 0:
+ found = True
+ break
+
+ if found:
+ i = 0
+ cl = ''
+ for line in code:
+ if line.find('\class') >= 0:
+ cl = line.split(' ')[-1]
+ madict[cl] = {'brief': code[i+2][7:]}
+ if code[i+3] != '':
+ madict[cl]['brief'] += code[i+3]
+
+ break
+
+ i += 1
+
+ graph.add((
+ URIRef(cl),
+ URIRef('http://www.w3.org/1999/02/22-rdf-syntax-ns#type'),
+ URIRef('http://www.w3.org/2000/01/rdf-schema#Resource')
+ ))
+
+ graph.add((
+ URIRef(cl),
+ URIRef('http://purl.org/dc/elements/1.1/description'),
+ Literal(madict[cl]['brief'])
+ ))
+
+graph.serialize('/Users/alo/MusicOntology/features/rdf/af-Marsyas.rdf')
+
+############# jMIR ###############
+jdir = '/Users/alo/Development/MIR/jAudio/jAudio/'
+jsrc = '/Users/alo/Development/MIR/jAudio/jAudio/src/jAudioFeatureExtractor/AudioFeatures/'
+
+file = urllib2.urlopen('file://' + jdir + 'features.xml')
+data = file.read()
+file.close()
+
+dom = parseString(data)
+jmir = dom.getElementsByTagName('feature')
+
+graph = Graph()
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+graph.bind('local', URIRef(local))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+
+for nodes in jmir:
+ jname = nodes.childNodes[1].firstChild.nodeValue.split('.')[-1]
+ graph.add((
+ URIRef(jname),
+ URIRef('http://www.w3.org/1999/02/22-rdf-syntax-ns#type'),
+ URIRef('http://www.w3.org/2000/01/rdf-schema#Resource')
+ ))
+ file = open(jsrc + jname + '.java')
+ code = file.read()
+ searchstr = 'String name ='
+ start = code.find(searchstr) + len(searchstr)
+ start = code.find('"', start) + 1
+ end = code.find('"', start)
+ name = code[start:end]
+
+ if name > "":
+ graph.add((
+ URIRef(jname),
+ URIRef(local+'name'),
+ Literal(name)
+ ))
+
+ searchstr = 'String description'
+ start = code.find(searchstr) + len(searchstr)
+ start = code.find('"', start) + 1
+ end = code.find('";', start)
+ desc = code[start:end]
+ desc = desc.replace("
", "").replace("\t", "").replace('\n', '').replace('+', '').replace('"', '').replace(';', '').replace('//\n', '')
+ desc = " ".join(desc.split())
+
+ if desc > "":
+ graph.add((
+ URIRef(jname),
+ URIRef('http://purl.org/dc/elements/1.1/description'),
+ Literal(desc)
+ ))
+
+
+graph.serialize('/Users/alo/MusicOntology/features/rdf/af-jMIR.rdf')
+
+
+############# yaafe ###############
+
+graph = Graph()
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+graph.bind('local', URIRef(local))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+
+path = "/Users/alo/Development/MIR/yaafe-v0.64/src_python/yaafefeatures.py"
+
+lines = [line.strip() for line in open(path)]
+
+count = 0
+
+for ln in lines:
+ if ln.find('class ') >= 0:
+ yname = ln[6:ln.find('(AudioFeature)')]
+ desc = lines[count+2]
+ desc = desc.replace("`", "").replace("<", "").replace(">", "")
+ desc = " ".join(desc.split())
+
+ graph.add((
+ URIRef(yname),
+ URIRef('http://www.w3.org/1999/02/22-rdf-syntax-ns#type'),
+ URIRef('http://www.w3.org/2000/01/rdf-schema#Resource')
+ ))
+
+ graph.add((
+ URIRef(yname),
+ URIRef('http://purl.org/dc/elements/1.1/description'),
+ Literal(desc)
+ ))
+
+ count += 1
+
+graph.serialize('/Users/alo/MusicOntology/features/rdf/af-Yaafe.rdf')
+
+############# libXtract ###############
+graph = Graph()
+local = 'http://sovarr.c4dm.eecs.qmul.ac.uk/features/'
+graph.bind('local', URIRef(local))
+graph.bind('dc', URIRef('http://purl.org/dc/elements/1.1/'))
+
+path = '/Users/alo/Development/MIR/LibXtract/xtract/libxtract.h'
+
+lines = [line.strip() for line in open(path)]
+
+xtract = lines[(lines.index('enum xtract_features_ {')+1):(lines.index('XTRACT_WINDOWED')-1)]
+
+for ln in xtract:
+ xname = ln[(ln.index('_')+1):-1].replace("_", " ").lower().capitalize()
+
+ graph.add((
+ URIRef(xname),
+ URIRef('http://www.w3.org/1999/02/22-rdf-syntax-ns#type'),
+ URIRef('http://www.w3.org/2000/01/rdf-schema#Resource')
+ ))
+
+graph.serialize('/Users/alo/MusicOntology/features/rdf/af-libXtract.rdf')