comparison adaptInstrSpecExample.m @ 0:b4e26b53072f tip

Initial commit.

+% This is an example script to illustrate the use of the CAdaptInstrSpec
+% class. The script loads the spectra extracted two recordings of two
+% different violins. It then applied the CAdaptInstrSpec class to adapt the
+% spectra of the first violin to those of the second.
+
+clearvars;
+close all;
+
+addpath('./functions/');
+
+
+%% constants
+
+% file paths of instrument spectra
+noteSpectraFilePaths = {'./instrSpectra/Violin.CQT.mat'; ...
+                        './instrSpectra/Violin2.CQT.mat'};
+numInstr = length(noteSpectraFilePaths);
+
+% analysis
+tuningFreqInHz = 440;
+costFctName = 'LS';
+beta = 2; % only needed for plotting. should match the cost function above
+numIter = 5;
+
+
+
+
+%% load instrument spectra
+instrSpec = cell(numInstr,1);
+f0Idcs    = cell(numInstr,1);
+
+for instrIdx = 1:numInstr
+    load(noteSpectraFilePaths{instrIdx}); % loads variables: noteSpectra, midiPitches, freqsInHz
+    instrSpec{instrIdx} = noteSpectra;
+    f0Idcs{instrIdx} = midiPitch2Shift(midiPitches, tuningFreqInHz, freqsInHz)+1;
+end
+numBinsPerSemitone = getNumBinsPerSemitoneFromFreqVec(freqsInHz);
+
+
+%% estimate filter curve
+
+% create instrSpecFilter object
+instrFiltObj = CAdaptInstrSpec(instrSpec{1}, instrSpec{2}, f0Idcs{1}, f0Idcs{2}, numBinsPerSemitone, costFctName);
+
+% apply update function for h
+for iterIdx = 1:numIter;
+    instrFiltObj = instrFiltObj.updateH;
+end
+
+h = instrFiltObj.getH;
+h_smooth = instrFiltObj.getSmoothedH;
+
+
+%% estimate spectra with given filter curve
+estSpectra = instrFiltObj.estimateSpectra(f0Idcs{1});
+
+
+
+
+%% plot results
+
+% plot original spectra and estimated spectra
+yticks = [250 500 1000 2000 4000];
+yticklabel = {'250'; '500'; '1k'; '2k'; '4k'};
+
+figure;
+subplot(311);
+imagesc(f0Idcs{1}, freqsInHz, instrSpec{1});
+axis xy;
+set(gca, 'YScale', 'log', 'YTick', yticks, 'YTickLabel', yticklabel);
+xlabel('pitch index');
+ylabel('frequency [Hz]');
+title('spectra of instrument 1');
+
+
+subplot(312);
+imagesc(f0Idcs{1}, freqsInHz, instrSpec{2});
+axis xy;
+set(gca, 'YScale', 'log', 'YTick', yticks, 'YTickLabel', yticklabel);
+xlabel('pitch index');
+ylabel('frequency [Hz]');
+title('spectra of instrument 2');
+
+subplot(313);
+imagesc(f0Idcs{1}, freqsInHz, estSpectra);
+axis xy;
+set(gca, 'YScale', 'log', 'YTick', yticks, 'YTickLabel', yticklabel);
+xlabel('pitch index');
+ylabel('frequency [Hz]');
+title('spectra of instrument 2 adapted to instrument 1')
+
+
+% plot filter curve and errors
+xticks = [125 250 500 1000 2000 4000];
+xticklabel = {'125'; '250'; '500'; '1k'; '2k'; '4k'};
+
+% compute beta divergence for each element
+betaDivsOriginal = betaDivergencePerElement(instrSpec{1}, instrSpec{2}, beta);
+betaDivsEstimate = betaDivergencePerElement(instrSpec{1}, estSpectra,   beta);
+
+% scale per-element beta divergence for image plot
+numColors = size(colormap,1);
+maxDist     = max([betaDivsOriginal(:); betaDivsEstimate(:)]);
+betaDivsOriginal = betaDivsOriginal / maxDist * numColors;
+betaDivsEstimate = betaDivsEstimate / maxDist * numColors;
+
+
+
+figure;
+subplot(311)
+%stem(freqsInHz(h ~= 0), h(h ~= 0), 'k', 'filled');
+plot(freqsInHz(h ~= 0), h(h ~= 0), 'k.');
+hold on;
+plot(freqsInHz, h_smooth, 'k');
+hold off;
+axis tight;
+set(gca, 'XScale', 'log', 'XTick', xticks, 'XTickLabel', xticklabel);
+title('estimated filter curve ''h''');
+legend('original', 'smoothed', 'Location', 'NorthWest');
+
+subplot(312);
+image(f0Idcs{1}, freqsInHz, betaDivsOriginal);
+axis xy;
+set(gca, 'YScale', 'log', 'YTick', yticks, 'YTickLabel', yticklabel);
+xlabel('pitch index');
+ylabel('frequency [Hz]');
+title('elementwise differences between original sets of spectra');
+
+subplot(313);
+image(f0Idcs{1}, freqsInHz, betaDivsEstimate);
+axis xy;
+set(gca, 'YScale', 'log', 'YTick', yticks, 'YTickLabel', yticklabel);
+xlabel('pitch index');
+ylabel('frequency [Hz]');
+title('differences between original and adapted set of spectra');