96 lines
1.5 KiB
Text
96 lines
1.5 KiB
Text
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#lang scribble/manual
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@(require (for-label racket))
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@title{PV_JensenAndersen}
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FFT feature detector for onset detection.@section{related}
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Classes/PV_HainsworthFoote
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@section{categories}
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UGens>FFT
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@section{description}
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FFT feature detector for onset detection based on work described in
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emphasis::
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Jensen, K. & Andersen, T. H. (2003). Real-time Beat Estimation
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Using Feature Extraction. In Proceedings of the Computer Music Modeling
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and Retrieval Symposium, Lecture Notes in Computer Science. Springer
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Verlag.
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::
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First order derivatives of the features are taken.
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@racketblock[threshold:: may need to be set low to pick up on
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changes.
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]
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@section{classmethods}
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@section{private}
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categories
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@section{method}
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ar
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@section{argument}
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buffer
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FFT buffer.
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@section{argument}
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propsc
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Proportion of spectral centroid feature.
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@section{argument}
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prophfe
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Proportion of high frequency energy feature.
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@section{argument}
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prophfc
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Proportion of high frequency content feature.
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@section{argument}
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propsf
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Proportion of spectral flux feature.
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@section{argument}
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threshold
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Threshold level for allowing a detection.
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@section{argument}
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waittime
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If triggered, minimum wait until a further frame can cause
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another spot (useful to stop multiple detects on heavy signals).
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@section{Examples}
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@racketblock[
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(
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SynthDef(\fftod, { var source1, detect;
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source1 = AudioIn.ar(1);
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detect = PV_JensenAndersen.ar(FFT(LocalBuf(2048), source1),
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threshold:MouseX.kr(0.1,1.0));
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Out.ar(0, SinOsc.ar([440,445], 0, Decay.ar(0.1*detect, 0.1)));
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}).play(s);
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)
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::
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]
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