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122 lines
4.1 KiB
Markdown
122 lines
4.1 KiB
Markdown
// load a source
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b = Buffer.read(s,"/Volumes/machins/projets/newsfeed/sons/textes/Audio/synth/fromtexttospeech-AmE-George.wav")
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b.play
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//slightly oversegment with novelty
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//segments should still make sense but might cut a few elements in 2 or 3
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~originalslices = Buffer(s);
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FluidBufNoveltySlice.process(s, b, indices: ~originalslices, feature: 1, kernelSize: 29, threshold: 0.05, filterSize: 5, hopSize: 128, action: {~originalslices.numFrames.postln;})
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//test the segmentation by looping them
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(
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{
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BufRd.ar(1, b,
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Phasor.ar(0,1,
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BufRd.kr(1, ~originalslices,
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MouseX.kr(0, BufFrames.kr(~originalslices) - 1), 0, 1),
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BufRd.kr(1, ~originalslices,
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MouseX.kr(1, BufFrames.kr(~originalslices)), 0, 1),
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BufRd.kr(1,~originalslices,
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MouseX.kr(0, BufFrames.kr(~originalslices) - 1), 0, 1)), 0, 1);
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}.play;
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)
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//analyse each segment with MFCCs in a dataset
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~originalslices.getn(0,~originalslices.numFrames, {|x|~originalslicesarray = x; if ((x.last != b.numFrames), {~originalslicesarray = ~originalslicesarray ++ (b.numFrames)}); });//retrieve the indices and add the file boundary at the end if not there already
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//iterates through the
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//a few buffers and our dataset - with back and forth from the language
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(
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~mfccs = Buffer(s);
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~stats = Buffer(s);
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~flat = Buffer(s);
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~slices = FluidDataSet(s,\slices);
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Routine{
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s.sync;
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(~originalslicesarray.size - 1).do{|i|
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FluidBufMFCC.process(s, b, startFrame: ~originalslicesarray[i], numFrames: (~originalslicesarray[i+1] - ~originalslicesarray[i]), numChans: 1,features: ~mfccs, numCoeffs: 20, action: {
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FluidBufStats.process(s, ~mfccs, startChan: 1, stats: ~stats, action: {
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FluidBufFlatten.process(s, ~stats, ~flat, action: {
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~slices.addPoint(i.asSymbol, ~flat);
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});
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});
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});
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};
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}.play;
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)
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~slices.print
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//run a window over consecutive segments, forcing them in 2 classes, and merging the consecutive segments of similar class
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//we overlap the analysis with the last (original) slice to check for continuity
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(
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~winSize = 4;//the number of consecutive items to split in 2 classes;
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~query = FluidDataSetQuery(s);
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~kmeans = FluidKMeans(s,2,100);
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~windowDS = FluidDataSet(s,\windowDS);
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~windowLS = FluidLabelSet(s,\windowLS);
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~slices.dump{|x|~sliceDict = x;};
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)
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(
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Routine{
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~indices = [0];
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~head = 0;
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~tempDict = ();
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while ( {~head <= (~originalslicesarray.size - ~winSize)},
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{
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var step = ~winSize - 1;
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var nbass = [];
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~assignments = [];
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//run a process on ~winSize items from ~head (with an overlap of 1)
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//copy the items to a subdataset
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~winSize.do{|i|
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~tempDict.put((i.asString), ~sliceDict["data"][(i+~head).asString]);//here one could curate which stats to take
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"whichslices:%\n".postf(i+~head);
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};
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~windowDS.load(Dictionary.newFrom([\cols, 133, \data, ~tempDict]), action: {
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"% - loaded\n".postf(~head);
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//kmeans 2 and retrieve ordered array of class assignations
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~kmeans.fitPredict(~windowDS, ~windowLS, action: {|x|
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nbass = x;
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"% - fitted1: ".postf(~head); nbass.postln;
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// if (nbass.includes(0.0), { Routine{~kmeans.fitPredict(~windowDS, ~windowLS, {|x| nbass = x; "% - fitted2: ".postf(~head); nbass.postln; s.sync;});}.play; });
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~windowLS.dump{|x|
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~assignments = x.at("data").asSortedArray.flop[1].flatten;
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"% - assigned ".postf(~head);
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~assignments.postln;
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step.do{|i|
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if (~assignments[i+1] != ~assignments[i], {~indices= ~indices ++ (~originalslicesarray[~head+i+1])});
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};
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};
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});
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});
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s.sync;
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~head = ~head + step;
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"-----------------".postln;
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});
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//leftovers
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if ( (~originalslicesarray.size - ~head) > 1, {
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//run a process on (a.size - ~head) items from ~head
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(~originalslicesarray.size - ~head - 1).do{|i|
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if (~assignments[i+1] != ~assignments[i], {~indices= ~indices ++ (~originalslicesarray[~head+i+1])});
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// (~head+i).postln;
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};
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});
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~indices.postln;
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}.play;
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)
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{var i = 8;BufRd.ar(1,b,Line.ar(~originalslicesarray[i],~originalslicesarray[i+1],(~originalslicesarray[i+1] - ~originalslicesarray[i])/b.sampleRate, doneAction: 2))}.play;
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{var i = 4;BufRd.ar(1,b,Line.ar(~indices[i],~indices[i+1],(~indices[i+1] - ~indices[i])/b.sampleRate, doneAction: 2))}.play;
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//export to reaper
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