annotate Code/Classifiers/SVM_HNR_Singing.m @ 4:92ca03a8fa99 tip

Update to ICASSP 2013 benchmark

function [] = SVM_HNR_Singing(  inputFileName )

cd 'C:\Users\dawn\Dropbox\TestResults'

DEBUG = 1;
% output results file name
% masterFileOutputID = fopen( 'SVM_Singing_HNR.txt', 'a' );
outputFileName = ['SVM_' inputFileName];
masterFileOutputID = fopen( outputFileName, 'a' );

% input results file name
% inputFileName = 'singingBasicHNRStats.txt';

% fprintf( masterFileOutputID, '\n RESULTS FILE NAME: %s\n', inputFileName);
inputFileID = fopen( inputFileName );

% noOfArguments = length(varargin);

% outputFileName = 'individualResults/SVM_Results_';
% resultsFileName = 'SVM_Results_';
% titleName = '';
% for i=1 : noOfArguments
%     titleName = [ titleName varargin{i} '_'];
%     fprintf( masterFileOutputID, '%s_', varargin{i} );
% end

% outputFileName = [ outputFileName titleName ];
% resultsFileName = [ resultsFileName titleName ];

fprintf( masterFileOutputID, '\t' );

% outputFileName = [ outputFileName '.txt'];
% resultsFileName = [ resultsFileName '.txt'];
% 
% fileOutputID = fopen( outputFileName, 'w' );
% fileSVMOutputID = fopen( resultsFileName, 'w' );

% -------------------- get the data from the results file ---------------
lineCount = 0;
fileCount = 0;
data = [];
groups = [];

while( ~(feof(inputFileID)) )
    
    outputValues = [];
    thestr = fgetl(inputFileID);
    fileCount = fileCount + 1;

    % determine whether we have a positive or negative sample
    sampleEmotion( fileCount ) = 'U';
    if( ~(isempty(strfind(thestr,'pos'))))
        % sample is positive
        sampleEmotion( fileCount ) = 'P';
        groups( fileCount ) = 1;
    elseif( ~(isempty(strfind(thestr,'neg'))))
        % sample is negative
        sampleEmotion( fileCount ) = 'N';
        groups( fileCount ) = 0;
    else
        disp('EEEK!');
        pause;
    end

    % determine whether we have a male, female or trans sample
    gender( fileCount ) = '?';
    if( ~(isempty(strfind(thestr,'fem'))))
        % gender is female
        gender( fileCount ) = 'F';
    elseif( ~(isempty(strfind(thestr,'male'))))
        % gender is male
        gender( fileCount ) = 'M';
    elseif( ~(isempty(strfind(thestr,'trans'))))
        % gender is trans
        gender( fileCount ) = 'T';
    else
        disp('EEEK!');
        pause;
    end

    %how many values are in the string?
    spaces = strfind( thestr, ' ' );
    numberstr = thestr( spaces(1) : end ); % chop off the file name  
    vars = sscanf( numberstr, '%f', inf );
    data( fileCount, : ) = vars;
        
    lineCount = lineCount + 1;
    
end
fclose(inputFileID);

% ------------  apply the SVM classifier  ------------------------

G1E1 = []; G1E2 = []; G2E1 = []; G2E2 = []; UE1 = []; UE2 = [];

noOfIterations = 10;

for n = 1:noOfIterations
    % Randomly select training and test sets
    [train, test] = crossvalind('holdOut',groups);
    cp = classperf(groups);
    
    % Use a linear support vector machine classifier
    svmStruct = svmtrain(data(train,:),groups(train),'showplot',true);
    classes = svmclassify(svmStruct,data(test,:),'showplot',true);
    % See how well the classifier performed
    classperf(cp,classes,test);
    numbers = cp.CountingMatrix;

    G1E1(n) = numbers(1,1);
    G1E2(n) = numbers(1,2);
    G2E1(n) = numbers(2,1);
    G2E2(n) = numbers(2,2);
    UE1(n) = numbers(3,1);
    UE2(n) = numbers(3,2);
    
end

G1E1 = sum(G1E1) / noOfIterations;
G1E2 = sum(G1E2) / noOfIterations;
G2E1 = sum(G2E1) / noOfIterations;
G2E2 = sum(G2E2) / noOfIterations;
% 
% fprintf( fileOutputID, '\n' );
% fclose( fileOutputID );
% fprintf( fileSVMOutputID, '\n' );
% fclose( fileKMeansOutputID );
fprintf( masterFileOutputID, '\n' );
fclose( masterFileOutputID );

end