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1 <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
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2 <html>
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3 <head>
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4 <link rel="stylesheet" media="screen" type="text/css" href="/screen.css"/>
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5 <link rel="icon" type="image/png" href="/images/waveform.png"/>
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6 <link rel="shortcut" type="image/png" href="/images/waveform.png"/>
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7 <title>Vamp Example Plugins: User Documentation</title>
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8 <meta name="robots" content="index"/>
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9 </head>
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10 <body>
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11 <h1 id="header"><span>Vamp Plugins</span></h1>
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12
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13 <h2>Vamp Example Plugins</h2>
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14
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15 <p>The “vamp-example-plugins” library contains a number of
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16 <a href="http://www.vamp-plugins.org/">Vamp audio analysis
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17 plugins</a> provided as part of the Vamp plugin SDK.
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18
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19 </p>
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20 <p>These are simple, but sometimes useful, plugins whose source code you
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21 are free to study and reuse in any proprietary or non-proprietary
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22 plugins of your own without any licensing obligation.
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23 </p>
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cannam@6
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24 <p>User documentation for the individual plugins in this library follows.
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25 </p>
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26 <div class="toc2">1. <a href="#amplitudefollower">Amplitude Follower</a></div>
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27 <div class="toc2">2. <a href="#fixedtempo">Simple Fixed Tempo Estimator</a></div>
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28 <div class="toc2">3. <a href="#percussiononsets">Simple Percussion Onset Detector</a></div>
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29 <div class="toc2">4. <a href="#powerspectrum">Simple Power Spectrum</a></div>
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30 <div class="toc2">5. <a href="#spectralcentroid">Spectral Centroid</a></div>
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31 <div class="toc2">6. <a href="#zerocrossing">Zero Crossings</a></div>
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32
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33 <div class="oddcontent"><a name="amplitudefollower"></a><h2>1. Amplitude Follower</h2>
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34
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35 <p><b>System identifier</b> – <code>vamp-example-plugins:amplitudefollower</code><br>
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36 <b>RDF URI</b> – <a href="http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#amplitudefollower">http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#amplitudefollower</a>
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37 </p>
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38 <p>Amplitude Follower tracks and returns the amplitude of the audio
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39 signal sample by sample, returning peak values block by block.
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40 </p>
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41 </div><div class="evencontent"><a name="toc2"></a><h3>1.1. Parameters</h3>
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42
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43 <p><b>Attack time</b> (seconds) – The 60dB convergence time for an increase in amplitude.<br>
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44 <b>Release time</b> (seconds) – The 60dB convergence time for a decrease in amplitude.
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45 </p>
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46 <p>For example, if you feed the plugin with a simple step function that
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47 jumps from level A to level B, then the output will start off as A,
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48 then at the moment of stepping it will start to converge exponentially
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49 to B, reaching with 60dB of the actual value within the time specified
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50 by the Attack time parameter.
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51 </p>
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52 <p>Similarly, if the plugin's input then steps down from B to A, the
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53 output will start converging at the moment of stepping, reaching
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54 within 60dB of the new value within the time specified by the Release
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55 time parameter.
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56 </p>
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57 </div><div class="oddcontent"><a name="toc3"></a><h3>1.2. Outputs</h3>
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58
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59 </div><div class="evencontent"><a name="toc4"></a><h4>1.2.1. Amplitude</h4>
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60
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61 <p>The peak tracked amplitude (in volts) for the current processing block.
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62 </p>
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63 </div><div class="oddcontent"><a name="toc5"></a><h3>1.3. References and Credits</h3>
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64
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65 <p>Amplitude Follower uses a method from the SuperCollider audio
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66 processing language. It was implemented as a Vamp plugin by Dan
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67 Stowell.
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68 </p>
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69 </div><div class="evencontent"><a name="fixedtempo"></a><h2>2. Simple Fixed Tempo Estimator</h2>
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70
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71 <p><b>System identifier</b> – <code>vamp-example-plugins:fixedtempo</code><br>
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72 <b>RDF URI</b> – <a href="http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#fixedtempo">http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#fixedtempo</a>
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73 </p>
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74 <p>Simple Fixed Tempo Estimator analyses a fragment of audio and
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75 estimates its tempo. It assumes that its input is of fixed tempo, and
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76 it analyses only the first (small but configurable number of) seconds
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77 before returning a result, discarding all subsequent input.
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78 </p>
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cannam@6
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79 <p>The plugin calculates an overall energy rise function across a series
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80 of short frequency-domain input frames, takes the autocorrelation of
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81 this function, filters it to stress possible metrical patterns,
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82 locates peaks, and converts from autocorrelation lag to the
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83 corresponding tempo.
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84 </p>
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85 <p>The filtering process involves searching for peaks at simple
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86 metrically related intervals (at a given autocorrelation lag as well
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87 as at 0.5, 2, and 4 times that lag), boosting each peak that shows
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88 strong related peaks. A simplistic perceptual curve is also applied
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89 in order to increase the probability of detecting a "likely" tempo.
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90 For improved tempo precision, each tempo with strong related peaks is
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91 averaged with the tempi calculated from those peaks.
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92 </p>
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93 <p>The method is best suited for 4/4 pop and dance rhythms.
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94 </p>
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95 <p>This plugin returns many of its intermediate calculations as
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96 additional outputs, as well as the most favoured tempo. Although as a
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97 tempo estimator it's still fairly primitive, it is intended to provide
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98 a useful example of a slightly more complex feature extraction plugin
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99 than the other examples, as well as one that returns several different
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100 types of output at a time.
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101 </p>
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102 </div><div class="oddcontent"><a name="toc7"></a><h3>2.1. Parameters</h3>
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103
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104 <p><b>Minimum estimated tempo</b>, <b>Maximum estimated tempo</b> (bpm) – These
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105 parameters control the range of values within which the tempo
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106 estimator will return its estimate.
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107 </p>
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108 <p><b>Input duration to study</b> (seconds) – The tempo estimator uses only the
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109 first part of its input, discarding any that follows. This parameter
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110 controls how much input it will use. There is no value in increasing
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111 this beyond 8x the duration of the slowest returned beat. The default
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112 of 10 seconds is likely to be appropriate for most purposes.
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113 </p>
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114 </div><div class="evencontent"><a name="toc8"></a><h3>2.2. Outputs</h3>
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115
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116 </div><div class="oddcontent"><a name="toc9"></a><h4>2.2.1. Tempo</h4>
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117
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118 <p>The tempo estimator's best guess at the tempo of its input, in beats
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119 per minute.
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120 </p>
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121 <p>This is returned as a feature whose timestamp and duration cover the
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122 range of the input which was used in estimating the tempo, with a
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123 single value containing the tempo.
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124 </p>
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125 </div><div class="evencontent"><a name="toc10"></a><h4>2.2.2. Tempo candidates</h4>
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126
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127 <p>Several guesses at the possible tempo. This output is returned as a
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128 single feature whose timestamp and duration cover the range of the
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129 input which was used in estimating the tempo, with up to 10 bins
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130 containing one tempo value in each bin, with the "best guess" tempo in
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131 bin 0.
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132 </p>
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133 </div><div class="oddcontent"><a name="toc11"></a><h4>2.2.3. Detection function</h4>
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134
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135 <p>The basic onset detection function used in tempo estimation.
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136 </p>
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137 </div><div class="evencontent"><a name="toc12"></a><h4>2.2.4. Autocorrelation function</h4>
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138
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139 <p>The autocorrelation of the onset detection function.
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140 </p>
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141 </div><div class="oddcontent"><a name="toc13"></a><h4>2.2.5. Filtered Autocorrelation</h4>
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142
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143 <p>The autocorrelation after filtering to boost values with possible
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144 metrically related peaks and to apply perceptual weighting. The peak
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145 value of this function is the one that will be used as the "best
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146 guess".
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147 </p>
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148 </div><div class="evencontent"><a name="toc14"></a><h3>2.3. References and Credits</h3>
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149
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150 <p>Simple Fixed Tempo Estimator uses a method derived from work by
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151 Matthew Davies: see for example M. E. P. Davies and M. D. Plumbley,
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152 <i>Beat Tracking With A Two State Model</i>, in Proceedings of the IEEE
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153 International Conference on Acoustics, Speech and Signal Processing
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154 2005. This plugin, made by Chris Cannam, is only an unsubtle
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155 simplification of a small part of the published method.
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156 </p>
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157 <p>The Queen Mary plugin set
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158 (<a href="http://www.elec.qmul.ac.uk/digitalmusic/downloads/index.html#qm-vamp-plugins">http://www.elec.qmul.ac.uk/digitalmusic/downloads/index.html#qm-vamp-plugins</a>)
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159 contains a Tempo and Beat Tracker plugin by Matthew Davies providing a
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160 more realistic implementation.
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161 </p>
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162 </div><div class="oddcontent"><a name="percussiononsets"></a><h2>3. Simple Percussion Onset Detector</h2>
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163
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164 <p><b>System identifier</b> – <code>vamp-example-plugins:percussiononsets</code><br>
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165 <b>RDF URI</b> – <a href="http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#percussiononsets">http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#percussiononsets</a>
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166 </p>
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167 <p>Simple Percussion Onset Detector estimates the locations of percussive
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168 onsets in the audio signal.
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169 </p>
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170 <p>The principle is to exploit the broadband nature of noisy percussive
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171 onsets by identifying only those frames in which the energy rise shows
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172 a broadband profile.
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173 </p>
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174 <p>The plugin takes a series of frequency domain frames, and examines
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175 each frame to count the number of bins whose energy content has
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176 increased by more than a certain threshold since the prior frame.
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177 Frames in which this number is at a peak relative to prior and
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178 following frames and also exceeds another threshold value are
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179 classified as percussive onsets.
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180 </p>
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181 </div><div class="evencontent"><a name="toc16"></a><h3>3.1. Parameters</h3>
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182
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183 <p><b>Energy rise threshold</b> (dB) – The rise in energy within a bin from one
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184 frame to the next that is required for a bin to be counted toward the
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185 detection function's bin count. This roughly corresponds to how
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186 "loud" a percussive sound must be in order to be detected.
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187 </p>
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188 <p><b>Sensitivity</b> (%) – The proportion of bins that must exceed the energy
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189 rise threshold in order for an onset to be detected (at frames in
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190 which the detection function peaks). This roughly corresponds to how
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191 "noisy" a percussive sound must be in order to be detected.
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192 </p>
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193 </div><div class="oddcontent"><a name="toc17"></a><h3>3.2. Outputs</h3>
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194
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195 </div><div class="evencontent"><a name="toc18"></a><h4>3.2.1. Onsets</h4>
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196
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197 <p>The estimated onset locations.
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198 </p>
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199 </div><div class="oddcontent"><a name="toc19"></a><h4>3.2.2. Detection Function</h4>
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200
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201 <p>The energy rise detection function whose peaks were used to estimate
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202 onset locations.
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203 </p>
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204 </div><div class="evencontent"><a name="toc20"></a><h3>3.3. References and Credits</h3>
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205
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206 <p>The method used in Simple Percussion Onset Detector was described in
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207 Dan Barry, Derry Fitzgerald, Eugene Coyle and
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208 Bob Lawlor, <i>Drum Source Separation using Percussive Feature Detection and
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209 Spectral Modulation</i>, ISSC 2005. The plugin was made by Chris Cannam.
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210 </p>
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211 </div><div class="oddcontent"><a name="powerspectrum"></a><h2>4. Simple Power Spectrum</h2>
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212
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213 <p><b>System identifier</b> – <code>vamp-example-plugins:powerspectrum</code><br>
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214 <b>RDF URI</b> – <a href="http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#powerspectrum">http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#powerspectrum</a>
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215 </p>
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216 <p>Simple Power Spectrum returns a power spectrum calculated from
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217 windowed short-time Fourier transforms of the input audio. (The power
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218 spectrum for a frame consists of a sequence of the squares of the
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219 magnitudes of the complex values for each frequency bin in the result
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220 of the Fourier transform.)
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221 </p>
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222 <p>This very simple plugin is an illustration of the fact that if a
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223 plugin requests frequency-domain input, its input will already be in
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224 the form needed for a spectrum such as this. The plugin has no work
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225 left to do except to calculate the squared magnitude from the
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226 cartesian complex representation.
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227 </p>
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228 <p>This plugin also illustrates how to return "grid-type" visualisation
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229 data from a Vamp plugin.
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230 </p>
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231 </div><div class="evencontent"><a name="toc22"></a><h3>4.1. Parameters</h3>
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232
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233 <p>None.
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234 </p>
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235 </div><div class="oddcontent"><a name="toc23"></a><h3>4.2. Outputs</h3>
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236
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237 </div><div class="evencontent"><a name="toc24"></a><h4>4.2.1. Power Spectrum</h4>
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238
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239 <p>The power spectrum calculated from the input frame. This output
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240 returns a single feature per processing block, containing
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241 blocksize/2+1 power values corresponding to the FFT bins from DC to
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242 Nyquist inclusive. The DC bin is always returned.
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243 </p>
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244 </div><div class="oddcontent"><a name="spectralcentroid"></a><h2>5. Spectral Centroid</h2>
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245
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246 <p><b>System identifier</b> – <code>vamp-example-plugins:spectralcentroid</code><br>
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247 <b>RDF URI</b> – <a href="http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#spectralcentroid">http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#spectralcentroid</a>
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248 </p>
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249 <p>Spectral Centroid calculates the "centre of gravity" of the frequency
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250 spectrum for each input frame.
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251 </p>
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252 </div><div class="evencontent"><a name="toc26"></a><h3>5.1. Parameters</h3>
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253
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254 <p>None.
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255 </p>
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256 </div><div class="oddcontent"><a name="toc27"></a><h3>5.2. Outputs</h3>
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257
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258 </div><div class="evencontent"><a name="toc28"></a><h4>5.2.1. Log Frequency Centroid</h4>
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259
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260 <p>The centroid of the log-weighted frequency spectrum. That is, the sum
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261 across Fourier transform output bins of the logarithm of the bin
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262 frequency multiplied by the bin magnitude, divided by the sum of the
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263 bin magnitudes, and the inverse logarithm taken so as to give the
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264 result as a frequency in Hz.
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265 </p>
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266 </div><div class="oddcontent"><a name="toc29"></a><h4>5.2.2. Linear Frequency Centroid</h4>
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267
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268 <p>The centroid of the linear-weighted frequency spectrum. That is, the
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269 sum across Fourier transform output bins of the bin frequency
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270 multiplied by the bin magnitude, divided by the sum of the bin
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271 magnitudes. The result is a frequency in Hz.
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272 </p>
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273 </div><div class="evencontent"><a name="zerocrossing"></a><h2>6. Zero Crossings</h2>
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274
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275 <p><b>System identifier</b> – <code>vamp-example-plugins:zerocrossing</code><br>
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276 <b>RDF URI</b> – <a href="http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#zerocrossing">http://vamp-plugins.org/rdf/plugins/vamp-example-plugins#zerocrossing</a>
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277 </p>
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278 <p>Zero Crossings calculates the positions and density of "zero-crossing"
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279 points in an audio waveform. For the purposes of this plugin, that
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280 means those positions at which the sampled value switches from
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281 zero-or-less to greater-than-zero, or vice versa.
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282 </p>
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283 </div><div class="oddcontent"><a name="toc31"></a><h3>6.1. Parameters</h3>
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284
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285 <p>None.
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286 </p>
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287 </div><div class="evencontent"><a name="toc32"></a><h3>6.2. Outputs</h3>
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288
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289 </div><div class="oddcontent"><a name="toc33"></a><h4>6.2.1. Zero Crossing Counts</h4>
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290
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291 <p>The number of zero-crossing points found in the current block of
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292 samples, as a single-valued feature returned per processing block.
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293 </p>
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294 </div><div class="evencontent"><a name="toc34"></a><h4>6.2.2. Zero Crossings</h4>
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295
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296 <p>The locations of zero-crossing points, returning one feature
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297 timestamped to the zero-crossing location, without values, for each
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298 crossing point.
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299 </p>
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300 <p></p>
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301
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302 </div>
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303 </body>
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304 </html>
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