peakerDataunction [recogRate, confusionMatrix, speakerSet]=speakerIdentify(speakerSet, gmm)
% speakerIdentify: speaker identification using GMM parameters
%	Usage: [recogRate, confusionMatrix, speakerSet]=speakerIdentify(speakerSet, gmm)
%		speakerSet: structure array generated by speakerSetRead.m
%		gmm: GMM parameters

%	Roger Jang, 20070517

currDir=pwd;
cd('c/int')
% ====== Speaker identification using GMM parameters
speakerNum=length(speakerSet);
for i=1:speakerNum
	fprintf('%d/%d: Recognizing wave files by %s\n', i, speakerNum, speakerSet(i).name);
	for j=1:length(speakerSet(i).sentence)
	%	fprintf('\t%d/%d: %s\n', j, length(speakerSet(i).sentence), speakerSet(i).sentence(j).path);
		waveFile=speakerSet(i).sentence(j).path;
		if exist('output.txt'), delete('output.txt'); end
		cmd=['speakerIdentifyIntC.exe ', waveFile, ' MFCC gmmList.txt output.txt'];
		[status, result]=dos(cmd);
		pause(0.1);	% wait for the previous program to write files
		if ~exist('output.txt')
			fprintf('cmd=%s\n', cmd);
			fprintf('result=%s\n', result);
			keyboard
		end
		contents = textread('output.txt','%s','delimiter','\n','whitespace','');
		contents(1)=[];
		for k=1:length(contents)
			items=split(contents{k}, 9);
			cumLogProb(k)=eval(items{2});
		end
		[maxProb, index]=max(cumLogProb);
		speakerSet(i).sentence(j).predictedSpeaker=index;
		speakerSet(i).sentence(j).cumLogProb=cumLogProb;
	end
end
cd(currDir);

% ====== Compute confusion matrix and recognition rate
confusionMatrix=zeros(speakerNum);
for i=1:speakerNum,
	predictedSpeaker=[speakerSet(i).sentence.predictedSpeaker];
	[index, count]=elementCount(predictedSpeaker);
	confusionMatrix(i, index)=count;
end
recogRate=sum(diag(confusionMatrix))/sum(sum(confusionMatrix));