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changeset 1:d8c7b69cb4c9

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author Yannick JACOB <y.jacob@se12.qmul.ac.uk>
date Tue, 03 Sep 2013 15:32:51 +0100
parents 2cd427e000b0
children 13ec2fa02a26
files Sirtassa/311CLNOF.WAV Sirtassa/311CLNOF.mid Sirtassa/Lussier_bassoon.mid Sirtassa/Lussier_bassoon.wav Sirtassa/Lussier_mix.wav Sirtassa/Lussier_trumpet.mid Sirtassa/Lussier_trumpet.wav Sirtassa/Sirtassa.m
diffstat 8 files changed, 0 insertions(+), 257 deletions(-) [+]
line wrap: on
line diff
Binary file Sirtassa/311CLNOF.WAV has changed
Binary file Sirtassa/311CLNOF.mid has changed
Binary file Sirtassa/Lussier_bassoon.mid has changed
Binary file Sirtassa/Lussier_bassoon.wav has changed
Binary file Sirtassa/Lussier_mix.wav has changed
Binary file Sirtassa/Lussier_trumpet.mid has changed
Binary file Sirtassa/Lussier_trumpet.wav has changed
--- a/Sirtassa/Sirtassa.m	Tue Sep 03 12:53:16 2013 +0100
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,257 +0,0 @@
-%% Default Values
-%Audio and score information
-if(~exist('midiCell','var'))
-    midiCell = cell(2,1);
-    midiCell{1} = 'Lussier_bassoon.mid';
-    midiCell{2} = 'Lussier_trumpet.mid';
-    mixName = 'Lussier_mix.wav';
-    %mixName = '311CLNOF.WAV';
-    %midiCell{1} = '311CLNOF.mid';
-end
-if(~exist('blockSize','var'))   blockSize = 2048;   end
-if(~exist('overlap','var'))     overlap = 2;        end
-%Maximum frequency of the filter
-if(~exist('bandPassFilterMaxFreq','var'))    bandPassFilterMaxFreq = 10000; end
-%Number of band pass filters in the filter
-if(~exist('nbBandPassFilters','var'))    nbBandPassFilters = 20;end
-%Maximum updates per frame
-if(~exist('maxUpdates','var'))    maxUpdates = 2;end
-%Number of partials in the model
-if(~exist('nbPartials','var'))    nbPartials = 8;end
-if(~exist('plotRefinedScore','var'))    plotRefinedScore = 0;end
-if(~exist('plotPartial','var'))    plotPartial = 0;end
-if(~exist('plotFilter','var'))    plotFilter = 0;end
-%Nummber of instrument in the mix.
-nbInstrument = length(midiCell);
-fftSize = blockSize;
-
-%Weights of the harmonic series
-partialsWeights = ones(nbPartials,nbInstrument);
-
-colors = 'rwm';
-%% Initialisation
-hopSize =blockSize/overlap;                   %Hopsize
-HFFTS = fftSize/2+1;                    %Size of the usefull part of the fft (half+1)
-[audio, fs] = wavread(mixName);
-
-% zeropadding the audio length
-audio(end:end+hopSize-mod(length(audio),hopSize)) = 0;
-audioLength = length(audio);
-
-scoreLength = audioLength/hopSize - overlap+1; %Number of frames
-wdw = hamming(blockSize);
-
-tic
-%% Create filters
-filterBasis = createBPFilters(bandPassFilterMaxFreq,nbBandPassFilters,fftSize,fftSize/fs);
-filterCoefficients = ones(nbBandPassFilters,nbInstrument);
-%% Creating the score
-originalScore = createScore(scoreLength,midiCell,fs/hopSize,fftSize/fs);
-originalScore(scoreLength+1:end,:) = [];
-gains = double(originalScore'>0);
-%% Creating spectrogram
-magnitude = zeros(fftSize, scoreLength);
-phase = zeros(fftSize, scoreLength);
-audioVector = zeros(fftSize,1);
-for curFrame = 1:scoreLength
-    audioVector(1:blockSize) = audio(hopSize*(curFrame-1)+1:hopSize*(curFrame-1)+blockSize,1).*wdw;
-    spectrogramVector = fft(audioVector);
-    magnitude(:,curFrame) = abs(spectrogramVector);
-    phase(:,curFrame) = angle(spectrogramVector);
-end
-magnitude(HFFTS+1:end,:) = [];
-phase(HFFTS+1:end,:) = [];
-maxSizeWindows = 400;
-hammingWindows = cell(1,maxSizeWindows);
-for len = 1:maxSizeWindows
-    hammingWindows{len} = hamming(len);
-end
-
-%% Refine Score and create Excitation Spectrum
-refinedScore = originalScore;   %score to be refiened
-basicSpec = zeros(HFFTS, scoreLength);        %Basic theoretical spectrogram
-excitationSpectrums = cell(nbInstrument,scoreLength);   %cell for each frame
-largerES = cell(nbInstrument,scoreLength);   %cell for each frame
-
-for ins = 1:nbInstrument                %for each isntrument
-    for curFrame = 1: scoreLength        %for each frame
-        excitationSpectrums{ins,curFrame} = sparse(zeros(HFFTS,nbPartials));
-        largerES{ins,curFrame} = sparse(zeros(HFFTS,nbPartials));
-        if(originalScore(curFrame,ins))        %if there is a note
-            %Refine score and creates Excitation Spectrum
-            [refinedScore(curFrame,ins), width] = refineScore(magnitude(:,curFrame),originalScore(curFrame,ins));
-            excitationSpectrums{ins,curFrame} = sparse(createExcitationSpectrums(refinedScore(curFrame,ins),HFFTS,nbPartials,partialsWeights(:,ins),width,hammingWindows));
-            largerES{ins,curFrame} = sparse(createExcitationSpectrums(refinedScore(curFrame,ins),HFFTS,nbPartials,partialsWeights(:,ins),2*width,hammingWindows));
-        end
-        basicSpec(:,curFrame) = basicSpec(:,curFrame) + (excitationSpectrums{ins,curFrame}*partialsWeights(:,ins))*gains(ins,curFrame); %Spectrogram without update
-    end
-end
-%% Plot spectrogram and add original and refined score
-if (plotRefinedScore)
-    figure(1),imagesc(log(10*magnitude(1:fftSize/16,:)+1)), axis xy
-    plotableScore = originalScore+1;
-    plotableScore(plotableScore==1) = 0;
-    hold on ,plot(plotableScore,'.k'),
-    
-    for harm = 1 : nbPartials
-        for ins = nbInstrument:-1:1
-            plot(refinedScore(:,ins)*harm+1,['.' colors(ins)]), colorbar
-        end
-    end
-end
-%% Online Processing
-%Values that can be changed by the model.
-maskForChangeableValues = basicSpec > 10^-4;
-maskedSpectrogram = magnitude.*maskForChangeableValues;
-bufferSize = 100;
-nextProcess = 1;
-for curFrame = 1:scoreLength
-    if sum(refinedScore(curFrame,:),2)
-        UpdateGainCoefficientsOL2
-        if (curFrame==nextProcess)
-            first = max(curFrame-bufferSize+1,1);
-            currentMag = magnitude(:,first:curFrame);
-            tmpMaskForChangeableValues = basicSpec(:,first:curFrame) > 10^-4;
-            tmpMaskedSpectrogram = currentMag.*tmpMaskForChangeableValues;
-            len = curFrame-first+1;
-            for  nbUpdates = 1:maxUpdates           %update loop
-                UpdatePartialCoefficientsOL
-                UpdateFilterCoefficientsOL
-                if (plotFilter)
-                    %%%Filter
-                    figure(4),plot(outlook(1:blockSize/8,:)), title('Filter')
-                end
-                if (plotPartial)
-                    %%%Decay
-                    figure(5),stem(partialsWeights), title('Partial Weights')
-                end
-            end
-            nextProcess = min(ceil(curFrame*1.2),scoreLength)
-            %bufferSize = round(max(bufferSize,curFrame*0.5));
-            if (plotFilter)
-                %%%Filter
-                figure(4),plot(outlook(1:blockSize/8,:)), title('Filter')
-            end
-            if (plotPartial)
-                %%%Decay
-                figure(5),stem(partialsWeights), title('Partial Weights')
-                
-            end
-        end
-    end
-end
-timeV = toc;
-fprintf('Time: %6.3g s, %6.2g times real time \t \n ', timeV, timeV*fs/audioLength);
-
-
-% Remodel Spectrogram
-ECA = cell(nbInstrument,1);
-xHat = zeros(HFFTS,scoreLength);
-for ins = 1:nbInstrument
-    ECA{ins} = sparse(zeros(HFFTS,scoreLength));
-    for frame = 1:scoreLength
-        ECA{ins}(:,frame) = filterBasis * filterCoefficients(:,ins).*(largerES{ins,frame}*partialsWeights(:,ins));
-    end
-    xHat = xHat + ECA{ins}.*repmat(gains(ins,:),HFFTS,1);
-end
-%% Final plot
-%%%Spectrogram (comparison with basic and final)
-% % bMax = max(max(log(10*basicSpec+1)));
-% % xMax = max(max(log(10*xHat+1)));
-% % mMax = max(max(log(10*magnitude+1)));
-% % tMax = max([bMax mMax xMax]);
-% % figure(3), subplot(3,1,1), imagesc(log(10*basicSpec(1:hopSize/2,:)+1)), axis xy, linkaxes, caxis([0 tMax]), colorbar, title('Basic Model')
-% % subplot(3,1,2), imagesc(log(10*xHat(1:hopSize/2,:)+1)), axis xy, linkaxes, caxis([0 tMax]), colorbar, title('Optimised Spectrogram')
-% % subplot(3,1,3), imagesc(log(10*magnitude(1:hopSize/2,:)+1)), axis xy, linkaxes, caxis([0 tMax]), colorbar, title('Actual Spectrogram')
-% %
-% %
-% % %%%Filter
-% % figure(4),plot(outlook(1:blockSize/8,:)), title('Filter')
-% %
-% % %%%Decay
-% % figure(5),stem(partialsWeights), title('Partial Weights')
-
-%% Writing
-%extraInfo = [sprintf('_%d_%d_%d_%d_%d_%d',blockSize,overlap,maxUpdates,nbPartials,nbBandPassFilters,bandPassFilterMaxFreq) specExp];
-finalScale = zeros(audioLength,1);
-freq = zeros(fftSize,1);
-finalAudio = cell(nbInstrument+1,1);
-finalAudioMasked = cell(nbInstrument,1);
-
-wdw2 = hamming(fftSize);
-nbMaskingTechniques = 4;
-maskingCell = cell(1,nbMaskingTechniques);
-maskingCell{1} = 'raw';
-maskingCell{2} = 'per';
-maskingCell{3} = 'sha';
-maskingCell{4} = '10p';
-finalMask = cell(nbInstrument,nbMaskingTechniques); %4 is the number of different masking techniques
-for ins = 1:nbInstrument
-    finalMask{ins,1} = sparse(zeros(HFFTS,scoreLength));
-    finalMask{ins,4} = sparse(zeros(HFFTS,scoreLength));
-    for curFrame = 1:scoreLength
-        finalMask{ins,1}(:,curFrame) = filterBasis * filterCoefficients(:,ins).*(excitationSpectrums{ins,curFrame}*partialsWeights(:,ins));
-        finalMask{ins,4}(:,curFrame) = filterBasis * filterCoefficients(:,ins).*(largerES{ins,curFrame}*partialsWeights(:,ins));
-    end
-    
-    finalMask{ins,1} = finalMask{ins,1}.*repmat(gains(ins,:),HFFTS,1);
-    finalMask{ins,4} = finalMask{ins,4}.*repmat(gains(ins,:),HFFTS,1);
-    
-    % masking strategy 1
-    finalMask{ins,2} = magnitude .* (finalMask{ins,4} ./ (xHat+eps));
-    
-    % masking strategy 2
-    finalMask{ins,3} = magnitude .* ( (finalMask{ins,4}+eps) ./ (xHat+eps));
-    
-    % masking strategy 3
-    finalMask{ins,4} = magnitude .* ( (finalMask{ins,4}+0.1 * eps) ./ (xHat+eps));
-    
-    finalAudio{ins} = zeros(audioLength,1);
-    finalAudioMasked{ins} = zeros(audioLength,1);
-end
-
-% sonifying the model
-finalAudio{nbInstrument+1} = zeros(audioLength,1);
-%Overlap and add
-for curFrame = 1:scoreLength
-    freq(1:HFFTS) = xHat(:,curFrame).*exp(1i*phase(:,curFrame));
-    freq(HFFTS+1:fftSize) = freq(HFFTS-1:-1:2);
-    faudio = real(ifft(freq)).*wdw2;
-    finalAudio{nbInstrument+1}((curFrame-1)*hopSize+1:(curFrame-1)*hopSize+fftSize,1) = finalAudio{nbInstrument+1}((curFrame-1)*hopSize+1:(curFrame-1)*hopSize+fftSize,1) + faudio;
-    for ins = 1:nbInstrument
-        freq(1:HFFTS) = finalMask{ins,1}(:,curFrame).*exp(1i*phase(:,curFrame));
-        freq(HFFTS+1:fftSize) = freq(HFFTS-1:-1:2);
-        faudio = real(ifft(freq)).*wdw2;
-        finalAudio{ins}((curFrame-1)*hopSize+1:(curFrame-1)*hopSize+fftSize,1) = finalAudio{ins}((curFrame-1)*hopSize+1:(curFrame-1)*hopSize+fftSize,1) + faudio;
-    end
-    finalScale((curFrame-1)*hopSize+1:(curFrame-1)*hopSize+fftSize,1) = finalScale((curFrame-1)*hopSize+1:(curFrame-1)*hopSize+fftSize,1) + wdw2;
-end
-
-for ins = 1:nbInstrument
-    finalAudio{ins} = finalAudio{ins}./finalScale;
-    %    wavwrite(finalAudio{ins},fs,16,[midiCell{ins}(1:4) '_' num2str(ins) '_' maskingCell{1} extraInfo '.wav']);
-end
-finalAudio{nbInstrument+1} = finalAudio{nbInstrument+1}./finalScale;
-%wavwrite(finalAudio{nbInstrument+1},fs,16,[mixName(1:4) '_0_' maskingCell{1} extraInfo '.wav']);
-
-% sonifying the masked version
-%Overlap and add
-for tech = 2:nbMaskingTechniques
-    finalScale = zeros(audioLength,1);
-    for curFrame = 1:scoreLength
-        for ins = 1:nbInstrument
-            freq(1:HFFTS) = finalMask{ins,tech}(:,curFrame).*exp(i*phase(:,curFrame));
-            freq(HFFTS+1:fftSize) = freq(HFFTS-1:-1:2);
-            faudio = real(ifft(freq)).*wdw2;
-            finalAudioMasked{ins}((curFrame-1)*hopSize+1:(curFrame-1)*hopSize+fftSize,1) = finalAudioMasked{ins}((curFrame-1)*hopSize+1:(curFrame-1)*hopSize+fftSize,1) + faudio;
-        end
-        finalScale((curFrame-1)*hopSize+1:(curFrame-1)*hopSize+fftSize,1) = finalScale((curFrame-1)*hopSize+1:(curFrame-1)*hopSize+fftSize,1) + wdw2;
-    end
-    for ins = 1:nbInstrument
-        finalAudioMasked{ins} = finalAudioMasked{ins}./finalScale;
-        %    wavwrite(finalAudioMasked{ins},fs,16,[midiCell{ins}(1:4) '_' num2str(ins) '_' maskingCell{tech} extraInfo '.wav']);
-    end
-end
-
-
-