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

Update to ICASSP 2013 benchmark

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/Code/Classifiers/SVM_HNR_Singing.m	Wed Feb 13 11:02:39 2013 +0000
@@ -0,0 +1,133 @@
+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
+
+