Mercurial > hg > qm-vamp-plugins
changeset 122:cfdb4e0dc34f
* rejig the README and INSTALLs a bit
| author | Chris Cannam <c.cannam@qmul.ac.uk> |
|---|---|
| date | Tue, 16 Jun 2009 10:21:12 +0000 |
| parents | 105509a173b7 |
| children | 25ef867820ba |
| files | INSTALL_linux.txt INSTALL_osx.txt INSTALL_win32.txt README.txt README.txt.linux README.txt.osx README.txt.win32 |
| diffstat | 7 files changed, 80 insertions(+), 1086 deletions(-) [+] |
line wrap: on
line diff
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/INSTALL_linux.txt Tue Jun 16 10:21:12 2009 +0000 @@ -0,0 +1,22 @@ + +QM Vamp Plugins +=============== + +To Install +========== + +This package contains plugins compiled for Linux on 32-bit x86 +(Intel/AMD) systems using GNU libc v6. + +To install them, copy the following files: + + qm-vamp-plugins.so + qm-vamp-plugins.cat + qm-vamp-plugins.n3 + +to one of the following directories: + + /usr/local/lib/vamp/ + /usr/lib/vamp/ + $HOME/vamp/ +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/INSTALL_osx.txt Tue Jun 16 10:21:12 2009 +0000 @@ -0,0 +1,21 @@ + +QM Vamp Plugins +=============== + +To Install +========== + +This package contains plugins for the Apple OS/X operating system, +compatible with both PPC and Intel hardware. + +To install them, copy the files + + qm-vamp-plugins.dylib + qm-vamp-plugins.cat + qm-vamp-plugins.n3 + +to either + + /Library/Audio/Plug-Ins/Vamp/ (for plugins to be available to all users) + $HOME/Library/Audio/Plug-Ins/Vamp/ (for plugins to be available to you only) +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/INSTALL_win32.txt Tue Jun 16 10:21:12 2009 +0000 @@ -0,0 +1,23 @@ + +QM Vamp Plugins +=============== + +To Install +========== + +This package contains plugins for Win32 systems (Windows XP, Vista). + +To install them, copy the files + + qm-vamp-plugins.dll + qm-vamp-plugins.cat + qm-vamp-plugins.n3 + +into the folder + + "C:\Program Files\Vamp Plugins\" + +You may also install them elsewhere, if you set the VAMP_PATH environment +variable to a semicolon-separated list of the folders in which plugins +may be found. e.g., "C:\My Plugins;C:\Program Files\Vamp Plugins". +
--- a/README.txt Fri Jun 12 16:06:04 2009 +0000 +++ b/README.txt Tue Jun 16 10:21:12 2009 +0000 @@ -413,3 +413,17 @@ The plugin works best at 44.1KHz input sample rate, and is tuned for piano and guitar music. + +Adaptive Spectrogram +-------------------- + + Identifier: qm-adaptivespectrogram + Authors: Wen Xue and Chris Cannam + Category: Visualisation + + References: X. Wen and M. Sandler. + Composite spectrogram using multiple Fourier transforms. + IET Signal Processing Journal, January 2009 + +The Adaptive Spectrogram plugin produces a composite spectrogram from +a set of series of short-time Fourier transforms at differing resolutions.
--- a/README.txt.linux Fri Jun 12 16:06:04 2009 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,362 +0,0 @@ - -QM Vamp Plugins -=============== - -Vamp audio feature extraction plugins from Queen Mary, University of London. -Version 1.5. - -For more information about Vamp plugins, see http://www.vamp-plugins.org/ -and http://www.sonicvisualiser.org/ . - - -To Install -========== - -This package contains plugins compiled for Linux on 32-bit x86 -(Intel/AMD) systems using GNU libc v6. - -To install them, copy the files - - qm-vamp-plugins.so and - qm-vamp-plugins.cat - -to one of the directories - - /usr/local/lib/vamp/ - /usr/lib/vamp/ or - $HOME/vamp/ - - -License -======= - -These plugins are provided in binary form only. You may install and -use the plugin binaries without fee for any purpose commercial or -non-commercial. You may redistribute the plugin binaries provided you -do so without fee and you retain this README file with your -distribution. You may not bundle these plugins with a commercial -product or distribute them on commercial terms. If you wish to -arrange commercial licensing terms, please contact the Centre for -Digital Music at Queen Mary, University of London. - -Copyright (c) 2006-2008 Queen Mary, University of London. All rights -reserved except as described above. - - -About This Release -================== - -This is a bugfix release only. The plugins provided are unchanged -from 1.4. - - -Plugins Included -================ - -This plugin set includes the following plugins: - - * Note onset detector - - * Beat tracker and tempo estimator - - * Key estimator and tonal change detector - - * Segmenter, to divide a track into a consistent sequence of segments - - * Timbral and rhythmic similarity between audio tracks - - * Chromagram, constant-Q spectrogram, and MFCC calculation plugins - -More details about the plugins follow. - - -Note Onset Detector -------------------- - - Identifier: qm-onsetdetector - Authors: Chris Duxbury, Juan Pablo Bello and Christian Landone - Category: Time > Onsets - - References: C. Duxbury, J. P. Bello, M. Davies and M. Sandler. - Complex domain Onset Detection for Musical Signals. - In Proceedings of the 6th Conference on Digital Audio - Effects (DAFx-03). London, UK. September 2003. - - D. Stowell and M. D. Plumbley. - Adaptive whitening for improved real-time audio onset - detection. - In Proceedings of the International Computer Music - Conference (ICMC'07), August 2007. - - D. Barry, D. Fitzgerald, E. Coyle and B. Lawlor. - Drum Source Separation using Percussive Feature - Detection and Spectral Modulation. - ISSC 2005 - -The Note Onset Detector plugin analyses a single channel of audio and -estimates the locations of note onsets within the music. - -It calculates an onset likelihood function for each spectral frame, -and picks peaks in a smoothed version of this function. The plugin is -non-causal, returning all results at the end of processing. - -It has three outputs: the note onset positions, the onset detection -function used in estimating onset positions, and a smoothed version of -the detection function that is used in the peak-picking phase. - - -Tempo and Beat Tracker ----------------------- - - Identifier: qm-tempotracker - Authors: Matthew Davies and Christian Landone - Category: Time > Tempo - - References: M. E. P. Davies and M. D. Plumbley. - Context-dependent beat tracking of musical audio. - In IEEE Transactions on Audio, Speech and Language - Processing. Vol. 15, No. 3, pp1009-1020, 2007. - - M. E. P. Davies and M. D. Plumbley. - Beat Tracking With A Two State Model. - In Proceedings of the IEEE International Conference - on Acoustics, Speech and Signal Processing (ICASSP 2005), - Vol. 3, pp241-244 Philadelphia, USA, March 19-23, 2005. - -The Tempo and Beat Tracker plugin analyses a single channel of audio -and estimates the locations of metrical beats and the resulting tempo. - -It has three outputs: the beat positions, an ongoing estimate of tempo -where available, and the onset detection function used in estimating -beat positions. - - -Key Detector ------------- - - Identifier: qm-keydetector - Authors: Katy Noland and Christian Landone - Category: Key and Tonality - - References: K. Noland and M. Sandler. - Signal Processing Parameters for Tonality Estimation. - In Proceedings of Audio Engineering Society 122nd - Convention, Vienna, 2007. - -The Key Detector plugin analyses a single channel of audio and -continuously estimates the key of the music. - -It has four outputs: the tonic pitch of the key; a major or minor mode -flag; the key (combining the tonic and major/minor into a single -value); and a key strength plot which reports the degree to which the -chroma vector extracted from each input block correlates to the stored -key profiles for each major and minor key. The key profiles are drawn -from analysis of Book I of the Well Tempered Klavier by J S Bach, -recorded at A=440 equal temperament. - -The outputs have the values: - - Tonic pitch: C = 1, C#/Db = 2, ..., B = 12 - - Major/minor mode: major = 0, minor = 1 - - Key: C major = 1, C#/Db major = 2, ..., B major = 12 - C minor = 13, C#/Db minor = 14, ..., B minor = 24 - - Key Strength Plot: 25 separate bins per feature, separated into 1-12 - (major from C) and 14-25 (minor from C). Bin 13 is unused, not - for superstitious reasons but simply so as to delimit the major - and minor areas if they are displayed on a single plot by the - plugin host. Higher bin values show increased correlation with - the key profile for that key. - -The outputs are also labelled with pitch or key as text. - - -Tonal Change ------------- - - Identifier: qm-tonalchange - Authors: Chris Harte and Martin Gasser - Category: Key and Tonality - - References: C. A. Harte, M. Gasser, and M. Sandler. - Detecting harmonic change in musical audio. - In Proceedings of the 1st ACM workshop on Audio and Music - Computing Multimedia, Santa Barbara, 2006. - - C. A. Harte and M. Sandler. - Automatic chord identification using a quantised chromagram. - In Proceedings of the 118th Convention of the Audio - Engineering Society, Barcelona, Spain, May 28-31 2005. - -The Tonal Change plugin analyses a single channel of audio, detecting -harmonic changes such as chord boundaries. - -It has three outputs: a representation of the musical content in a -six-dimensional tonal space onto which the algorithm maps 12-bin -chroma vectors extracted from the audio; a function representing the -estimated likelihood of a tonal change occurring in each spectral -frame; and the resulting estimated positions of tonal changes. - - -Segmenter ---------- - - Identifier: qm-segmenter - Authors: Mark Levy - Category: Classification - - References: M. Levy and M. Sandler. - Structural segmentation of musical audio by constrained - clustering. - IEEE Transactions on Audio, Speech, and Language Processing, - February 2008. - -The Segmenter plugin divides a single channel of music up into -structurally consistent segments. Its single output contains a -numeric value (the segment type) for each moment at which a new -segment starts. - -For music with clearly tonally distinguishable sections such as verse, -chorus, etc., the segments with the same type may be expected to be -similar to one another in some structural sense (e.g. repetitions of -the chorus). - -The type of feature used in segmentation can be selected using the -Feature Type parameter. The default Hybrid (Constant-Q) is generally -effective for modern studio recordings, while the Chromatic option may -be preferable for live, acoustic, or older recordings, in which -repeated sections may be less consistent in sound. Also available is -a timbral (MFCC) feature, which is more likely to result in -classification by instrumentation rather than musical content. - -Note that this plugin does a substantial amount of processing after -receiving all of the input audio data, before it produces any results. - - -Similarity ----------- - - Identifier: qm-similarity - Authors: Mark Levy, Kurt Jacobson and Chris Cannam - Category: Classification - - References: M. Levy and M. Sandler. - Lightweight measures for timbral similarity of musical audio. - In Proceedings of the 1st ACM workshop on Audio and Music - Computing Multimedia, Santa Barbara, 2006. - - K. Jacobson. - A Multifaceted Approach to Music Similarity. - In Proceedings of the Seventh International Conference on - Music Information Retrieval (ISMIR), 2006. - -The Similarity plugin treats each channel of its audio input as a -separate "track", and estimates how similar the tracks are to one -another using a selectable similarity measure. - -The plugin also returns the intermediate data used as a basis of the -similarity measure; it can therefore be used on a single channel of -input (with the resulting intermediate data then being applied in some -other similarity or clustering algorithm, for example) if desired, as -well as with multiple inputs. - -The underlying audio features used for the similarity measure can be -selected using the Feature Type parameter. The available features are -Timbre (in which the distance between tracks is a symmetrised -Kullback-Leibler divergence between Gaussian-modelled MFCC means and -variances across each track); Chroma (KL divergence of mean chroma -histogram); Rhythm (cosine distance between "beat spectrum" measures -derived from a short sampled section of the track); and combined -"Timbre and Rhythm" and "Chroma and Rhythm". - -The plugin has six outputs: a matrix of the distances between input -channels; a vector containing the distances between the first input -channel and each of the input channels; a pair of vectors containing -the indices of the input channels in the order of their similarity to -the first input channel, and the distances between the first input -channel and each of those channels; the means of the underlying -feature bins (MFCCs or chroma); the variances of the underlying -feature bins; and the beat spectra used for the rhythmic feature. - -Because Vamp does not have the capability to return features in matrix -form explicitly, the matrix output is returned as a series of vector -features timestamped at one-second intervals. Likewise, the -underlying feature outputs contain one vector feature per input -channel, timestamped at one-second intervals (so the feature for the -first channel is at time 0, and so on). Examining the features that -the plugin actually returns, when run on some test data, may make this -arrangement more clear. - -Note that the underlying feature values are only returned if the -relevant feature type is selected. That is, the means and variances -outputs are valid provided the pure rhythm feature is not selected; -the beat spectra output is valid provided rhythm is included in the -selected feature type. - - -Constant-Q Spectrogram ----------------------- - - Identifier: qm-constantq - Authors: Christian Landone - Category: Visualisation - - References: J. Brown. - Calculation of a constant Q spectral transform. - Journal of the Acoustical Society of America, 89(1): - 425-434, 1991. - -The Constant-Q Spectrogram plugin calculates a spectrogram based on a -short-time windowed constant Q spectral transform. This is a -spectrogram in which the ratio of centre frequency to resolution is -constant for each frequency bin. The frequency bins correspond to the -frequencies of "musical notes" rather than being linearly spaced in -frequency as they are for the conventional DFT spectrogram. - -The pitch range and the number of frequency bins per octave may be -adjusted using the plugin's parameters. Note that the plugin's -preferred step and block sizes depend on these parameters, and the -plugin will not accept any other block size. - - -Chromagram ----------- - - Identifier: qm-chromagram - Authors: Christian Landone - Category: Visualisation - -The Chromagram plugin calculates a constant Q spectral transform (as -above) and then wraps the frequency bin values into a single octave, -with each bin containing the sum of the magnitudes from the -corresponding bin in all octaves. The number of values in each -feature vector returned by the plugin is therefore the same as the -number of bins per octave configured for the underlying constant Q -transform. - -The pitch range and the number of frequency bins per octave for the -transform may be adjusted using the plugin's parameters. Note that -the plugin's preferred step and block sizes depend on these -parameters, and the plugin will not accept any other block size. - - -Mel-Frequency Cepstral Coefficients ------------------------------------ - - Identifier: qm-mfcc - Authors: Nicolas Chetry and Chris Cannam - Category: Low Level Features - - References: B. Logan. - Mel-Frequency Cepstral Coefficients for Music Modeling. - In Proceedings of the First International Symposium on Music - Information Retrieval (ISMIR), 2000. - -The Mel-Frequency Cepstral Coefficients plugin calculates MFCCs from a -single channel of audio, returning one MFCC vector from each process -call. It also returns the overall means of the coefficient values -across the length of the audio input, as a separate output at the end -of processing. -
--- a/README.txt.osx Fri Jun 12 16:06:04 2009 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,361 +0,0 @@ - -QM Vamp Plugins -=============== - -Vamp audio feature extraction plugins from Queen Mary, University of London. -Version 1.5. - -For more information about Vamp plugins, see http://www.vamp-plugins.org/ -and http://www.sonicvisualiser.org/ . - - -To Install -========== - -This package contains plugins for the Apple OS/X operating system, -compatible with both PPC and Intel hardware. - -To install them, copy the files - - qm-vamp-plugins.dylib and - qm-vamp-plugins.cat - -to either - - /Library/Audio/Plug-Ins/Vamp/ (for plugins available to all users) or - $HOME/Library/Audio/Plug-Ins/Vamp/ (for plugins available to you only). - - -License -======= - -These plugins are provided in binary form only. You may install and -use the plugin binaries without fee for any purpose commercial or -non-commercial. You may redistribute the plugin binaries provided you -do so without fee and you retain this README file with your -distribution. You may not bundle these plugins with a commercial -product or distribute them on commercial terms. If you wish to -arrange commercial licensing terms, please contact the Centre for -Digital Music at Queen Mary, University of London. - -Copyright (c) 2006-2008 Queen Mary, University of London. All rights -reserved except as described above. - - -About This Release -================== - -This is a bugfix release only. The plugins provided are unchanged -from 1.4. - - -Plugins Included -================ - -This plugin set includes the following plugins: - - * Note onset detector - - * Beat tracker and tempo estimator - - * Key estimator and tonal change detector - - * Segmenter, to divide a track into a consistent sequence of segments - - * Timbral and rhythmic similarity between audio tracks - - * Chromagram, constant-Q spectrogram, and MFCC calculation plugins - -More details about the plugins follow. - - -Note Onset Detector -------------------- - - Identifier: qm-onsetdetector - Authors: Chris Duxbury, Juan Pablo Bello and Christian Landone - Category: Time > Onsets - - References: C. Duxbury, J. P. Bello, M. Davies and M. Sandler. - Complex domain Onset Detection for Musical Signals. - In Proceedings of the 6th Conference on Digital Audio - Effects (DAFx-03). London, UK. September 2003. - - D. Stowell and M. D. Plumbley. - Adaptive whitening for improved real-time audio onset - detection. - In Proceedings of the International Computer Music - Conference (ICMC'07), August 2007. - - D. Barry, D. Fitzgerald, E. Coyle and B. Lawlor. - Drum Source Separation using Percussive Feature - Detection and Spectral Modulation. - ISSC 2005 - -The Note Onset Detector plugin analyses a single channel of audio and -estimates the locations of note onsets within the music. - -It calculates an onset likelihood function for each spectral frame, -and picks peaks in a smoothed version of this function. The plugin is -non-causal, returning all results at the end of processing. - -It has three outputs: the note onset positions, the onset detection -function used in estimating onset positions, and a smoothed version of -the detection function that is used in the peak-picking phase. - - -Tempo and Beat Tracker ----------------------- - - Identifier: qm-tempotracker - Authors: Matthew Davies and Christian Landone - Category: Time > Tempo - - References: M. E. P. Davies and M. D. Plumbley. - Context-dependent beat tracking of musical audio. - In IEEE Transactions on Audio, Speech and Language - Processing. Vol. 15, No. 3, pp1009-1020, 2007. - - M. E. P. Davies and M. D. Plumbley. - Beat Tracking With A Two State Model. - In Proceedings of the IEEE International Conference - on Acoustics, Speech and Signal Processing (ICASSP 2005), - Vol. 3, pp241-244 Philadelphia, USA, March 19-23, 2005. - -The Tempo and Beat Tracker plugin analyses a single channel of audio -and estimates the locations of metrical beats and the resulting tempo. - -It has three outputs: the beat positions, an ongoing estimate of tempo -where available, and the onset detection function used in estimating -beat positions. - - -Key Detector ------------- - - Identifier: qm-keydetector - Authors: Katy Noland and Christian Landone - Category: Key and Tonality - - References: K. Noland and M. Sandler. - Signal Processing Parameters for Tonality Estimation. - In Proceedings of Audio Engineering Society 122nd - Convention, Vienna, 2007. - -The Key Detector plugin analyses a single channel of audio and -continuously estimates the key of the music. - -It has four outputs: the tonic pitch of the key; a major or minor mode -flag; the key (combining the tonic and major/minor into a single -value); and a key strength plot which reports the degree to which the -chroma vector extracted from each input block correlates to the stored -key profiles for each major and minor key. The key profiles are drawn -from analysis of Book I of the Well Tempered Klavier by J S Bach, -recorded at A=440 equal temperament. - -The outputs have the values: - - Tonic pitch: C = 1, C#/Db = 2, ..., B = 12 - - Major/minor mode: major = 0, minor = 1 - - Key: C major = 1, C#/Db major = 2, ..., B major = 12 - C minor = 13, C#/Db minor = 14, ..., B minor = 24 - - Key Strength Plot: 25 separate bins per feature, separated into 1-12 - (major from C) and 14-25 (minor from C). Bin 13 is unused, not - for superstitious reasons but simply so as to delimit the major - and minor areas if they are displayed on a single plot by the - plugin host. Higher bin values show increased correlation with - the key profile for that key. - -The outputs are also labelled with pitch or key as text. - - -Tonal Change ------------- - - Identifier: qm-tonalchange - Authors: Chris Harte and Martin Gasser - Category: Key and Tonality - - References: C. A. Harte, M. Gasser, and M. Sandler. - Detecting harmonic change in musical audio. - In Proceedings of the 1st ACM workshop on Audio and Music - Computing Multimedia, Santa Barbara, 2006. - - C. A. Harte and M. Sandler. - Automatic chord identification using a quantised chromagram. - In Proceedings of the 118th Convention of the Audio - Engineering Society, Barcelona, Spain, May 28-31 2005. - -The Tonal Change plugin analyses a single channel of audio, detecting -harmonic changes such as chord boundaries. - -It has three outputs: a representation of the musical content in a -six-dimensional tonal space onto which the algorithm maps 12-bin -chroma vectors extracted from the audio; a function representing the -estimated likelihood of a tonal change occurring in each spectral -frame; and the resulting estimated positions of tonal changes. - - -Segmenter ---------- - - Identifier: qm-segmenter - Authors: Mark Levy - Category: Classification - - References: M. Levy and M. Sandler. - Structural segmentation of musical audio by constrained - clustering. - IEEE Transactions on Audio, Speech, and Language Processing, - February 2008. - -The Segmenter plugin divides a single channel of music up into -structurally consistent segments. Its single output contains a -numeric value (the segment type) for each moment at which a new -segment starts. - -For music with clearly tonally distinguishable sections such as verse, -chorus, etc., the segments with the same type may be expected to be -similar to one another in some structural sense (e.g. repetitions of -the chorus). - -The type of feature used in segmentation can be selected using the -Feature Type parameter. The default Hybrid (Constant-Q) is generally -effective for modern studio recordings, while the Chromatic option may -be preferable for live, acoustic, or older recordings, in which -repeated sections may be less consistent in sound. Also available is -a timbral (MFCC) feature, which is more likely to result in -classification by instrumentation rather than musical content. - -Note that this plugin does a substantial amount of processing after -receiving all of the input audio data, before it produces any results. - - -Similarity ----------- - - Identifier: qm-similarity - Authors: Mark Levy, Kurt Jacobson and Chris Cannam - Category: Classification - - References: M. Levy and M. Sandler. - Lightweight measures for timbral similarity of musical audio. - In Proceedings of the 1st ACM workshop on Audio and Music - Computing Multimedia, Santa Barbara, 2006. - - K. Jacobson. - A Multifaceted Approach to Music Similarity. - In Proceedings of the Seventh International Conference on - Music Information Retrieval (ISMIR), 2006. - -The Similarity plugin treats each channel of its audio input as a -separate "track", and estimates how similar the tracks are to one -another using a selectable similarity measure. - -The plugin also returns the intermediate data used as a basis of the -similarity measure; it can therefore be used on a single channel of -input (with the resulting intermediate data then being applied in some -other similarity or clustering algorithm, for example) if desired, as -well as with multiple inputs. - -The underlying audio features used for the similarity measure can be -selected using the Feature Type parameter. The available features are -Timbre (in which the distance between tracks is a symmetrised -Kullback-Leibler divergence between Gaussian-modelled MFCC means and -variances across each track); Chroma (KL divergence of mean chroma -histogram); Rhythm (cosine distance between "beat spectrum" measures -derived from a short sampled section of the track); and combined -"Timbre and Rhythm" and "Chroma and Rhythm". - -The plugin has six outputs: a matrix of the distances between input -channels; a vector containing the distances between the first input -channel and each of the input channels; a pair of vectors containing -the indices of the input channels in the order of their similarity to -the first input channel, and the distances between the first input -channel and each of those channels; the means of the underlying -feature bins (MFCCs or chroma); the variances of the underlying -feature bins; and the beat spectra used for the rhythmic feature. - -Because Vamp does not have the capability to return features in matrix -form explicitly, the matrix output is returned as a series of vector -features timestamped at one-second intervals. Likewise, the -underlying feature outputs contain one vector feature per input -channel, timestamped at one-second intervals (so the feature for the -first channel is at time 0, and so on). Examining the features that -the plugin actually returns, when run on some test data, may make this -arrangement more clear. - -Note that the underlying feature values are only returned if the -relevant feature type is selected. That is, the means and variances -outputs are valid provided the pure rhythm feature is not selected; -the beat spectra output is valid provided rhythm is included in the -selected feature type. - - -Constant-Q Spectrogram ----------------------- - - Identifier: qm-constantq - Authors: Christian Landone - Category: Visualisation - - References: J. Brown. - Calculation of a constant Q spectral transform. - Journal of the Acoustical Society of America, 89(1): - 425-434, 1991. - -The Constant-Q Spectrogram plugin calculates a spectrogram based on a -short-time windowed constant Q spectral transform. This is a -spectrogram in which the ratio of centre frequency to resolution is -constant for each frequency bin. The frequency bins correspond to the -frequencies of "musical notes" rather than being linearly spaced in -frequency as they are for the conventional DFT spectrogram. - -The pitch range and the number of frequency bins per octave may be -adjusted using the plugin's parameters. Note that the plugin's -preferred step and block sizes depend on these parameters, and the -plugin will not accept any other block size. - - -Chromagram ----------- - - Identifier: qm-chromagram - Authors: Christian Landone - Category: Visualisation - -The Chromagram plugin calculates a constant Q spectral transform (as -above) and then wraps the frequency bin values into a single octave, -with each bin containing the sum of the magnitudes from the -corresponding bin in all octaves. The number of values in each -feature vector returned by the plugin is therefore the same as the -number of bins per octave configured for the underlying constant Q -transform. - -The pitch range and the number of frequency bins per octave for the -transform may be adjusted using the plugin's parameters. Note that -the plugin's preferred step and block sizes depend on these -parameters, and the plugin will not accept any other block size. - - -Mel-Frequency Cepstral Coefficients ------------------------------------ - - Identifier: qm-mfcc - Authors: Nicolas Chetry and Chris Cannam - Category: Low Level Features - - References: B. Logan. - Mel-Frequency Cepstral Coefficients for Music Modeling. - In Proceedings of the First International Symposium on Music - Information Retrieval (ISMIR), 2000. - -The Mel-Frequency Cepstral Coefficients plugin calculates MFCCs from a -single channel of audio, returning one MFCC vector from each process -call. It also returns the overall means of the coefficient values -across the length of the audio input, as a separate output at the end -of processing. -
--- a/README.txt.win32 Fri Jun 12 16:06:04 2009 +0000 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,363 +0,0 @@ - -QM Vamp Plugins -=============== - -Vamp audio feature extraction plugins from Queen Mary, University of London. -Version 1.5. - -For more information about Vamp plugins, see http://www.vamp-plugins.org/ -and http://www.sonicvisualiser.org/ . - - -To Install -========== - -This package contains plugins for Win32 systems (Windows XP, Vista). - -To install them, copy the files - - qm-vamp-plugins.dll and - qm-vamp-plugins.cat - -into the folder - - "C:\Program Files\Vamp Plugins\". - -You may also install them elsewhere and set the VAMP_PATH environment -variable to a semicolon-separated list of the folders in which plugins -may be found. e.g., "C:\My Plugins;C:\Program Files\Vamp Plugins". - - -License -======= - -These plugins are provided in binary form only. You may install and -use the plugin binaries without fee for any purpose commercial or -non-commercial. You may redistribute the plugin binaries provided you -do so without fee and you retain this README file with your -distribution. You may not bundle these plugins with a commercial -product or distribute them on commercial terms. If you wish to -arrange commercial licensing terms, please contact the Centre for -Digital Music at Queen Mary, University of London. - -Copyright (c) 2006-2008 Queen Mary, University of London. All rights -reserved except as described above. - - -About This Release -================== - -This is a bugfix release only. The plugins provided are unchanged -from 1.4. - - -Plugins Included -================ - -This plugin set includes the following plugins: - - * Note onset detector - - * Beat tracker and tempo estimator - - * Key estimator and tonal change detector - - * Segmenter, to divide a track into a consistent sequence of segments - - * Timbral and rhythmic similarity between audio tracks - - * Chromagram, constant-Q spectrogram, and MFCC calculation plugins - -More details about the plugins follow. - - -Note Onset Detector -------------------- - - Identifier: qm-onsetdetector - Authors: Chris Duxbury, Juan Pablo Bello and Christian Landone - Category: Time > Onsets - - References: C. Duxbury, J. P. Bello, M. Davies and M. Sandler. - Complex domain Onset Detection for Musical Signals. - In Proceedings of the 6th Conference on Digital Audio - Effects (DAFx-03). London, UK. September 2003. - - D. Stowell and M. D. Plumbley. - Adaptive whitening for improved real-time audio onset - detection. - In Proceedings of the International Computer Music - Conference (ICMC'07), August 2007. - - D. Barry, D. Fitzgerald, E. Coyle and B. Lawlor. - Drum Source Separation using Percussive Feature - Detection and Spectral Modulation. - ISSC 2005 - -The Note Onset Detector plugin analyses a single channel of audio and -estimates the locations of note onsets within the music. - -It calculates an onset likelihood function for each spectral frame, -and picks peaks in a smoothed version of this function. The plugin is -non-causal, returning all results at the end of processing. - -It has three outputs: the note onset positions, the onset detection -function used in estimating onset positions, and a smoothed version of -the detection function that is used in the peak-picking phase. - - -Tempo and Beat Tracker ----------------------- - - Identifier: qm-tempotracker - Authors: Matthew Davies and Christian Landone - Category: Time > Tempo - - References: M. E. P. Davies and M. D. Plumbley. - Context-dependent beat tracking of musical audio. - In IEEE Transactions on Audio, Speech and Language - Processing. Vol. 15, No. 3, pp1009-1020, 2007. - - M. E. P. Davies and M. D. Plumbley. - Beat Tracking With A Two State Model. - In Proceedings of the IEEE International Conference - on Acoustics, Speech and Signal Processing (ICASSP 2005), - Vol. 3, pp241-244 Philadelphia, USA, March 19-23, 2005. - -The Tempo and Beat Tracker plugin analyses a single channel of audio -and estimates the locations of metrical beats and the resulting tempo. - -It has three outputs: the beat positions, an ongoing estimate of tempo -where available, and the onset detection function used in estimating -beat positions. - - -Key Detector ------------- - - Identifier: qm-keydetector - Authors: Katy Noland and Christian Landone - Category: Key and Tonality - - References: K. Noland and M. Sandler. - Signal Processing Parameters for Tonality Estimation. - In Proceedings of Audio Engineering Society 122nd - Convention, Vienna, 2007. - -The Key Detector plugin analyses a single channel of audio and -continuously estimates the key of the music. - -It has four outputs: the tonic pitch of the key; a major or minor mode -flag; the key (combining the tonic and major/minor into a single -value); and a key strength plot which reports the degree to which the -chroma vector extracted from each input block correlates to the stored -key profiles for each major and minor key. The key profiles are drawn -from analysis of Book I of the Well Tempered Klavier by J S Bach, -recorded at A=440 equal temperament. - -The outputs have the values: - - Tonic pitch: C = 1, C#/Db = 2, ..., B = 12 - - Major/minor mode: major = 0, minor = 1 - - Key: C major = 1, C#/Db major = 2, ..., B major = 12 - C minor = 13, C#/Db minor = 14, ..., B minor = 24 - - Key Strength Plot: 25 separate bins per feature, separated into 1-12 - (major from C) and 14-25 (minor from C). Bin 13 is unused, not - for superstitious reasons but simply so as to delimit the major - and minor areas if they are displayed on a single plot by the - plugin host. Higher bin values show increased correlation with - the key profile for that key. - -The outputs are also labelled with pitch or key as text. - - -Tonal Change ------------- - - Identifier: qm-tonalchange - Authors: Chris Harte and Martin Gasser - Category: Key and Tonality - - References: C. A. Harte, M. Gasser, and M. Sandler. - Detecting harmonic change in musical audio. - In Proceedings of the 1st ACM workshop on Audio and Music - Computing Multimedia, Santa Barbara, 2006. - - C. A. Harte and M. Sandler. - Automatic chord identification using a quantised chromagram. - In Proceedings of the 118th Convention of the Audio - Engineering Society, Barcelona, Spain, May 28-31 2005. - -The Tonal Change plugin analyses a single channel of audio, detecting -harmonic changes such as chord boundaries. - -It has three outputs: a representation of the musical content in a -six-dimensional tonal space onto which the algorithm maps 12-bin -chroma vectors extracted from the audio; a function representing the -estimated likelihood of a tonal change occurring in each spectral -frame; and the resulting estimated positions of tonal changes. - - -Segmenter ---------- - - Identifier: qm-segmenter - Authors: Mark Levy - Category: Classification - - References: M. Levy and M. Sandler. - Structural segmentation of musical audio by constrained - clustering. - IEEE Transactions on Audio, Speech, and Language Processing, - February 2008. - -The Segmenter plugin divides a single channel of music up into -structurally consistent segments. Its single output contains a -numeric value (the segment type) for each moment at which a new -segment starts. - -For music with clearly tonally distinguishable sections such as verse, -chorus, etc., the segments with the same type may be expected to be -similar to one another in some structural sense (e.g. repetitions of -the chorus). - -The type of feature used in segmentation can be selected using the -Feature Type parameter. The default Hybrid (Constant-Q) is generally -effective for modern studio recordings, while the Chromatic option may -be preferable for live, acoustic, or older recordings, in which -repeated sections may be less consistent in sound. Also available is -a timbral (MFCC) feature, which is more likely to result in -classification by instrumentation rather than musical content. - -Note that this plugin does a substantial amount of processing after -receiving all of the input audio data, before it produces any results. - - -Similarity ----------- - - Identifier: qm-similarity - Authors: Mark Levy, Kurt Jacobson and Chris Cannam - Category: Classification - - References: M. Levy and M. Sandler. - Lightweight measures for timbral similarity of musical audio. - In Proceedings of the 1st ACM workshop on Audio and Music - Computing Multimedia, Santa Barbara, 2006. - - K. Jacobson. - A Multifaceted Approach to Music Similarity. - In Proceedings of the Seventh International Conference on - Music Information Retrieval (ISMIR), 2006. - -The Similarity plugin treats each channel of its audio input as a -separate "track", and estimates how similar the tracks are to one -another using a selectable similarity measure. - -The plugin also returns the intermediate data used as a basis of the -similarity measure; it can therefore be used on a single channel of -input (with the resulting intermediate data then being applied in some -other similarity or clustering algorithm, for example) if desired, as -well as with multiple inputs. - -The underlying audio features used for the similarity measure can be -selected using the Feature Type parameter. The available features are -Timbre (in which the distance between tracks is a symmetrised -Kullback-Leibler divergence between Gaussian-modelled MFCC means and -variances across each track); Chroma (KL divergence of mean chroma -histogram); Rhythm (cosine distance between "beat spectrum" measures -derived from a short sampled section of the track); and combined -"Timbre and Rhythm" and "Chroma and Rhythm". - -The plugin has six outputs: a matrix of the distances between input -channels; a vector containing the distances between the first input -channel and each of the input channels; a pair of vectors containing -the indices of the input channels in the order of their similarity to -the first input channel, and the distances between the first input -channel and each of those channels; the means of the underlying -feature bins (MFCCs or chroma); the variances of the underlying -feature bins; and the beat spectra used for the rhythmic feature. - -Because Vamp does not have the capability to return features in matrix -form explicitly, the matrix output is returned as a series of vector -features timestamped at one-second intervals. Likewise, the -underlying feature outputs contain one vector feature per input -channel, timestamped at one-second intervals (so the feature for the -first channel is at time 0, and so on). Examining the features that -the plugin actually returns, when run on some test data, may make this -arrangement more clear. - -Note that the underlying feature values are only returned if the -relevant feature type is selected. That is, the means and variances -outputs are valid provided the pure rhythm feature is not selected; -the beat spectra output is valid provided rhythm is included in the -selected feature type. - - -Constant-Q Spectrogram ----------------------- - - Identifier: qm-constantq - Authors: Christian Landone - Category: Visualisation - - References: J. Brown. - Calculation of a constant Q spectral transform. - Journal of the Acoustical Society of America, 89(1): - 425-434, 1991. - -The Constant-Q Spectrogram plugin calculates a spectrogram based on a -short-time windowed constant Q spectral transform. This is a -spectrogram in which the ratio of centre frequency to resolution is -constant for each frequency bin. The frequency bins correspond to the -frequencies of "musical notes" rather than being linearly spaced in -frequency as they are for the conventional DFT spectrogram. - -The pitch range and the number of frequency bins per octave may be -adjusted using the plugin's parameters. Note that the plugin's -preferred step and block sizes depend on these parameters, and the -plugin will not accept any other block size. - - -Chromagram ----------- - - Identifier: qm-chromagram - Authors: Christian Landone - Category: Visualisation - -The Chromagram plugin calculates a constant Q spectral transform (as -above) and then wraps the frequency bin values into a single octave, -with each bin containing the sum of the magnitudes from the -corresponding bin in all octaves. The number of values in each -feature vector returned by the plugin is therefore the same as the -number of bins per octave configured for the underlying constant Q -transform. - -The pitch range and the number of frequency bins per octave for the -transform may be adjusted using the plugin's parameters. Note that -the plugin's preferred step and block sizes depend on these -parameters, and the plugin will not accept any other block size. - - -Mel-Frequency Cepstral Coefficients ------------------------------------ - - Identifier: qm-mfcc - Authors: Nicolas Chetry and Chris Cannam - Category: Low Level Features - - References: B. Logan. - Mel-Frequency Cepstral Coefficients for Music Modeling. - In Proceedings of the First International Symposium on Music - Information Retrieval (ISMIR), 2000. - -The Mel-Frequency Cepstral Coefficients plugin calculates MFCCs from a -single channel of audio, returning one MFCC vector from each process -call. It also returns the overall means of the coefficient values -across the length of the audio input, as a separate output at the end -of processing. -