clear all;
vsdOpt=vsdOptSet;
if vsdOpt.useInputNormalize==1
	error('This is not implemneted yet!\n');
end
plotOpt=1;

% ====== Load parameters
load gmmData.mat
load transProb.mat
transLogProb=log(transProb);
gmmcPrm=gmmData(index);

pvData=recursiveFileList(vsdOpt.waveDir, 'pv');

for i=1:length(pvData)
	fprintf('%d/%d: ', i, length(pvData));
	pvFile=pvData(i).path;
	waveFile=strrep(pvFile, '.pv', '.wav');
	[y, fs, nbits]=wavReadInt(waveFile);
	%load bestInputIndex.mat
	[inData, outData, inputName, annotation]=wave2feature(waveFile, vsdOpt);
	%inData=inData(bestInputIndex, :);
	%inputName=inputName(bestInputIndex);
	vsdResult=waveDecode(waveFile, vsdOpt, gmmcPrm, transProb, plotOpt, inputName);
	% ====== HMM recog. rate
	computedClassIndex = vsdResult';
	pvData(i).hmmRr=sum(outData==computedClassIndex)/length(outData);
	fprintf('hmmRr=%.2f%%, ', pvData(i).hmmRr*100);
	% ====== GMMC recog. rate
	computedClassIndex = gmmcEval(inData, gmmcPrm);
	pvData(i).gmmcRr=sum(outData==computedClassIndex)/length(outData);
	fprintf('gmmcRr=%.2f%%, ', pvData(i).gmmcRr*100);
	fprintf('waveFile=%s\n', pvData(i).path);
end

fprintf('Overall HMM RR = %.2f%%\n', mean([pvData.hmmRr])*100);
fprintf('Overall GMMC RR = %.2f%%\n', mean([pvData.gmmcRr])*100);

return

allSingers={pvData.parentDir};
uniqueSingers=unique(allSingers);
for i=1:length(uniqueSingers)
	singer=uniqueSingers{i};
	singerData(i).singer=singer;
	index=find(strcmp(allSingers, singer));
	singerData(i).hmmRr=mean([pvData(index).hmmRr]);
	singerData(i).gmmcRr=mean([pvData(index).gmmcRr]);
end
[junk, index]=sort([singerData.hmmRr]);
singerData=singerData(index);
structDispInHtml(singerData, 'singerData');

[junk, index]=sort([pvData.hmmRr]);
pvData=pvData(index);
structDispInHtml(pvData, 'pvData');

% ====== Examine the result based on HMM RR
[junk, index]=sort([pvData.hmmRr]);
pvData=pvData(index);
for i=1:length(pvData)
	fprintf('%d/%d: ', i, length(pvData));
	pvFile=pvData(i).path;
	waveFile=strrep(pvFile, '.pv', '.wav');
	[y, fs, nbits]=wavReadInt(waveFile);
	%load bestInputIndex.mat
	[inData, outData, inputName, annotation]=wave2feature(waveFile, vsdOpt);
	%inData=inData(bestInputIndex, :);
	%inputName=inputName(bestInputIndex);
	vsdResult=waveDecode(waveFile, vsdOpt, gmmcPrm, transProb, plotOpt, inputName);
	% ====== HMM recog. rate
	computedClassIndex = vsdResult';
	pvData(i).hmmRr=sum(outData==computedClassIndex)/length(outData);
	fprintf('hmmRr=%.2f%%, ', pvData(i).hmmRr*100);
	% ====== GMMC recog. rate
	computedClassIndex = gmmcEval(inData, gmmcPrm);
	pvData(i).gmmcRr=sum(outData==computedClassIndex)/length(outData);
	fprintf('gmmcRr=%.2f%%, ', pvData(i).gmmcRr*100);
	fprintf('waveFile=%s\n', pvData(i).path);
	fprintf('Press any key to continue...'); pause; fprintf('\n');
end