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root / _beattracker / bcfm.m @ 8:b5b38998ef3b
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function [measures,db] = bcfm(bcf,beats,timesig) |
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if timesig == 0 |
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timesig =4; |
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end |
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% extract measures from bcf and timesig. |
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for k=1:timesig, |
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db(k) = mean(bcf(k:timesig:end)); |
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end |
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[val,downbeat] = max(db); |
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if(downbeat ==timesig), |
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downbeat = 0; |
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end |
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downbeat = downbeat+1; |
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measures = beats(downbeat:timesig:end); |
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if 0 |
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% for extracting batchwise measures... |
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for i=1:222, |
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meas{1,i} = bcfm(bcfs{i}.spec,anns.beats{i},anns.timesig{i});
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% meas{2,i} = bcfm(bcf{i}.specs,anns.beats{i},anns.timesig{i});
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meas{2,i} = bcfm(bcfs{i}.cq,anns.beats{i},anns.timesig{i});
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% meas{4,i} = bcfm(bcf{i}.cqs,anns.beats{i},anns.timesig{i});
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meas{3,i} = bcfm(bcfs{i}.hpcp,anns.beats{i},anns.timesig{i});
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% meas{6,i} = bcfm(bcf{i}.hpcps,anns.beats{i},anns.timesig{i});
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meas{4,i} = bcfm(bcfs{i}.chroma,anns.beats{i},anns.timesig{i});
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% meas{8,i} = bcfm(bcf{i}.chromas,anns.beats{i},anns.timesig{i});
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meas{5,i} = bcfm(bcfs{i}.mfcc,anns.beats{i},anns.timesig{i});
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% y = bcfs{i}.spec+bcfs{i}.cq+bcfs{i}.hpcp+bcfs{i}.chroma+bcfs{i}.mfcc;
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% meas{6,i} = bcfm(y,anns.beats{i},anns.timesig{i});
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% % voting mechanism.. find which measures are the same... |
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% zz = zeros(5); |
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% for k=1:5, |
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% for j=1:5, |
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% zz(k,j) = double(~~sum(meas{k,i}==meas{j,i}));
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% end |
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% end |
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% |
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% for p=1:5, zz(p,p) = 0; end |
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% % find which is similar to another |
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% [val,ind] = max(sum(zz)); |
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% % and put these in place... |
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% meas{6,i} = meas{ind,i};
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% |
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end |
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% and their evaluation |
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for j=1:5 |
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for i=1:222, |
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% only need rcl |
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[m.rcl(j,i), m.rtot(j,i), m.acl(j,i), m.atot(j,i)] = cont_eval(anns.actmeasures{i},meas{j,i},0.1);
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end |
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end |
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end |
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if 0 |
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% for extracting batchwise measures... |
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for i=1:222, |
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meas{1,i} = bcfm(bcf{i}.spec,beats{i},timesig{i});
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% meas{2,i} = bcfm(bcf{i}.specs,anns.beats{i},anns.timesig{i});
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meas{2,i} = bcfm(bcf{i}.cq,beats{i},timesig{i});
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% meas{4,i} = bcfm(bcf{i}.cqs,anns.beats{i},anns.timesig{i});
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meas{3,i} = bcfm(bcf{i}.hpcp,beats{i},timesig{i});
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% meas{6,i} = bcfm(bcf{i}.hpcps,anns.beats{i},anns.timesig{i});
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meas{4,i} = bcfm(bcf{i}.chroma,beats{i},timesig{i});
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% meas{8,i} = bcfm(bcf{i}.chromas,anns.beats{i},anns.timesig{i});
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end |
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% and their evaluation |
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for j=1:4 |
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for i=1:222, |
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% only need rcl |
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[m.rcl(j,i), m.rtot(j,i), m.acl(j,i), m.atot(j,i)] = cont_eval(anns.actmeasures{i},meas{j,i},0.1);
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end |
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end |
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end |
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%new classification approach |
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if 0 |
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fname = '95_HipHopFatty'; |
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[bcf,frame,beats] = getbcfs2(fname); y = kmeans(frame.spec,4); |
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measures = bcfm(~~abs(diff(y)),beats,4); |
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figure(1);subplot(311); imagesc(10*log(1+abs(frame.spec'))); axis xy; colormap('hot'); subplot(312); stem(y); axis tight; subplot(313); stem(~~abs(diff(y))); axis tight;
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out = playbeats(measures,wavread(fname),44100); wavwrite(out,44100,'~/Desktop/z2.wav'); |
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end |