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129 lines
6.9 KiB
Plaintext
129 lines
6.9 KiB
Plaintext
TITLE:: FluidBufSpectralShape
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SUMMARY:: Seven Spectral Shape Descriptors on a Buffer
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CATEGORIES:: Libraries>FluidDecomposition
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RELATED:: Guides/FluCoMa, Guides/FluidDecomposition, Guides/FluidBufMultiThreading, Classes/SpecCentroid, Classes/SpecFlatness, Classes/SpecCentroid, Classes/SpecPcile
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DESCRIPTION::
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This class implements seven of the most popular spectral shape descriptors, computed on a linear scale for both amplitude and frequency. It is part of the LINK:: Guides/FluidDecomposition:: of LINK:: Guides/FluCoMa::. For more explanations, learning material, and discussions on its musicianly uses, visit http://www.flucoma.org/
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The descriptors are:
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LIST::
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##the four first statistical moments (https://en.wikipedia.org/wiki/Moment_(mathematics) ), more commonly known as:
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LIST::
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## the spectral centroid (1) in Hz. This is the point that splits the spectrum in 2 halves of equal energy. It is the weighted average of the magnitude spectrum.
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## the spectral spread (2) in Hz. This is the standard deviation of the spectrum envelop, or the average of the distance to the centroid.
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## the normalised skewness (3) as ratio. This indicates how tilted is the spectral curve in relation to the middle of the spectral frame, i.e. half of the Nyquist frequency. If it is below that frequency, i.e. the central bin of the magnitude spectrum, it is positive.
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## the normalised kurtosis (4) as ratio. This indicates how focused is the spectral curve. If it is peaky, it is high.
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::
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## the rolloff (5) in Hz. This indicates the frequency under which 95% of the energy is included.
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## the flatness (6) in dB. This is the ratio of geometric mean of the magnitude, over the arithmetic mean of the magnitudes. It yields a very approximate measure on how noisy a signal is.
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## the crest (7) in dB. This is the ratio of the loudest magnitude over the RMS of the whole frame. A high number is an indication of a loud peak poking out from the overal spectral curve.
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The drawings in Peeters 2003 (http://recherche.ircam.fr/anasyn/peeters/ARTICLES/Peeters_2003_cuidadoaudiofeatures.pdf) are useful, as are the commented examples below. For the mathematically-inclined reader, the tutorials and code offered here (https://www.audiocontentanalysis.org/) are interesting to further the understanding.
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::
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The process will return a multichannel buffer with the seven channels per input channel, each containing the 7 shapes. Each sample represents a value, which is every hopSize.
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STRONG::Threading::
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By default, this UGen spawns a new thread to avoid blocking the server command queue, so it is free to go about with its business. For a more detailed discussion of the available threading and monitoring options, including the two undocumented Class Methods below (.processBlocking and .kr) please read the guide LINK::Guides/FluidBufMultiThreading::.
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CLASSMETHODS::
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METHOD:: process, processBlocking
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This is the method that calls for the spectral shape descriptors to be calculated on a given source buffer.
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ARGUMENT:: server
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The server on which the buffers to be processed are allocated.
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ARGUMENT:: source
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The index of the buffer to use as the source material to be described through the various descriptors. The different channels of multichannel buffers will be processing sequentially.
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ARGUMENT:: startFrame
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Where in the srcBuf should the process start, in sample.
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ARGUMENT:: numFrames
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How many frames should be processed.
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ARGUMENT:: startChan
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For multichannel srcBuf, which channel should be processed first.
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ARGUMENT:: numChans
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For multichannel srcBuf, how many channel should be processed.
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ARGUMENT:: features
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The destination buffer for the 7 spectral features describing the spectral shape.
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ARGUMENT:: windowSize
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The window size. As spectral shape estimation relies on spectral frames, we need to decide what precision we give it spectrally and temporally, in line with Gabor Uncertainty principles. http://www.subsurfwiki.org/wiki/Gabor_uncertainty
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ARGUMENT:: hopSize
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The window hop size. As spectral shape estimation relies on spectral frames, we need to move the window forward. It can be any size but low overlap will create audible artefacts. The -1 default value will default to half of windowSize (overlap of 2).
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ARGUMENT:: fftSize
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The inner FFT/IFFT size. It should be at least 4 samples long, at least the size of the window, and a power of 2. Making it larger allows an oversampling of the spectral precision. The -1 default value will use the next power of 2 equal or above the windowSize.
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ARGUMENT:: padding
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Controls the zero-padding added to either end of the source buffer or segment. Possible values are 0 (no padding), 1 (default, half the window size), or 2 (window size - hop size). Padding ensures that all input samples are completely analysed: with no padding, the first analysis window starts at time 0, and the samples at either end will be tapered by the STFT windowing function. Mode 1 has the effect of centering the first sample in the analysis window and ensuring that the very start and end of the segment are accounted for in the analysis. Mode 2 can be useful when the overlap factor (window size / hop size) is greater than 2, to ensure that the input samples at either end of the segment are covered by the same number of analysis frames as the rest of the analysed material.
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ARGUMENT:: freeWhenDone
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Free the server instance when processing complete. Default true
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ARGUMENT:: action
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A Function to be evaluated once the offline process has finished and all Buffer's instance variables have been updated on the client side. The function will be passed [features] as an argument.
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returns:: an instance of the processor
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EXAMPLES::
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code::
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// create some buffers
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(
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b = Buffer.read(s,File.realpath(FluidBufSpectralShape.class.filenameSymbol).dirname.withTrailingSlash ++ "../AudioFiles/Nicol-LoopE-M.wav");
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c = Buffer.new(s);
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)
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// run the process with basic parameters
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(
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Routine{
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t = Main.elapsedTime;
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FluidBufSpectralShape.process(s, b, features: c).wait;
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(Main.elapsedTime - t).postln;
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}.play
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)
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// listen to the source and look at the buffer
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b.play;
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c.plot(separately:true)
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::
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STRONG::A stereo buffer example.::
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CODE::
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// load two very different files
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(
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b = Buffer.read(s,File.realpath(FluidBufSpectralShape.class.filenameSymbol).dirname.withTrailingSlash ++ "../AudioFiles/Tremblay-SA-UprightPianoPedalWide.wav");
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c = Buffer.read(s,File.realpath(FluidBufSpectralShape.class.filenameSymbol).dirname.withTrailingSlash ++ "../AudioFiles/Tremblay-AaS-AcousticStrums-M.wav");
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)
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// composite one on left one on right as test signals
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FluidBufCompose.process(s, c, numFrames:b.numFrames, startFrame:555000,destStartChan:1, destination:b)
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b.play
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// create a buffer as destinations
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c = Buffer.new(s);
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//run the process on them
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(
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Routine{
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t = Main.elapsedTime;
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FluidBufSpectralShape.process(s, b, features: c).wait;
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(Main.elapsedTime - t).postln;
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}.play
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)
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// look at the buffer: 7shapes for left, then 7 shapes for right
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c.plot(separately:true)
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::
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