function [computedClass_Word, correctCount, allConf, sylConf, hitIndex, missIndex, missComputedPos] = classifyPostprocess(classifier, testID, testLabel, computedClass, score, data, allConf, sylConf)

computedClass_Word = ones(size(testID)) + ones(size(testID));
correctCount = 0;
hitIndex = [];
missIndex = [];
missComputedPos = [];

switch(classifier)             
    
    case 'svmc'
        count = computedClass;
        count(count==2) = 0;
        index = min(find(computedClass==1));    % Due to svm's probability estimation random side
        
        for n = min(testID):max(testID)
            startIndex = min(find(n==testID));      % Word index
            endIndex = max(find(n==testID));        % Word index
            temp = sum(count(startIndex:endIndex));
            if score(index)>0
                if temp>1
                    [prob, stressPos] = max(score(startIndex:endIndex));
                elseif temp==0
                    [prob, stressPos] = max(score(startIndex:endIndex));
                elseif temp==1
                    stressPos = find(computedClass(startIndex:endIndex)==1);
                end
            else
                if temp>1
                    [prob, stressPos] = min(score(startIndex:endIndex));
                elseif temp==0
                    [prob, stressPos] = min(score(startIndex:endIndex));
                elseif temp==1
                    stressPos = find(computedClass(startIndex:endIndex)==1);
                end                
            end
                
            computedClass_Word(startIndex+stressPos-1) = 1;
            
            switch(data.stressNum(n))
                case 2
                    sylConf.pos2 = [sylConf.pos2, stressPos];
                    sylConf.gt2 = [sylConf.gt2, data.stressPos(n)];
                    
                case 3
                    sylConf.pos3 = [sylConf.pos3, stressPos];
                    sylConf.gt3 = [sylConf.gt3, data.stressPos(n)];
                    
                case 4
                    sylConf.pos4 = [sylConf.pos4, stressPos];
                    sylConf.gt4 = [sylConf.gt4, data.stressPos(n)];
                    
                case 5
                    sylConf.pos5 = [sylConf.pos5, stressPos];
                    sylConf.gt5 = [sylConf.gt5, data.stressPos(n)];
                    
                case 6
                    sylConf.pos6 = [sylConf.pos6, stressPos];
                    sylConf.gt6 = [sylConf.gt6, data.stressPos(n)];
                    
                case 7
                    sylConf.pos7 = [sylConf.pos7, stressPos];
                    sylConf.gt7 = [sylConf.gt7, data.stressPos(n)];
                    
                case 8
                    sylConf.pos8 = [sylConf.pos8, stressPos];
                    sylConf.gt8 = [sylConf.gt8, data.stressPos(n)];                    
                    
            end
            
            allConf.predictPos = [allConf.predictPos, stressPos];
            allConf.gtPos = [allConf.gtPos, data.stressPos(n)];

            if sum(computedClass_Word(startIndex:endIndex)==testLabel(startIndex:endIndex)) == (endIndex-startIndex+1)
                correctCount = correctCount + 1;                        
                hitIndex = [hitIndex, n];
            else
                missIndex = [missIndex, n];
                missComputedPos = [missComputedPos, stressPos];
            end
        end
        
    case {'qc', 'nbc', 'gmmc', 'src'}
        count = computedClass;
        count(count==2) = 0;
        for n = min(testID):max(testID)
            startIndex = min(find(n==testID));      % Word index
            endIndex = max(find(n==testID));        % Word index
            temp = sum(count(startIndex:endIndex));
%             if temp>1
%                 [prob, stressPos] = max(score(1, startIndex:endIndex));
%             elseif temp==0
%                 [prob, stressPos] = min((score(2, startIndex:endIndex)));
%             elseif temp==1
%                 stressPos = find(computedClass(startIndex:endIndex)==1);
%             end
            [prob, stressPos] = max(score(1,startIndex:endIndex) - score(2,startIndex:endIndex));
            computedClass_Word(startIndex+stressPos-1) = 1;
            switch(data.stressNum(n))
                case 2
                    sylConf.pos2 = [sylConf.pos2, stressPos];
                    sylConf.gt2 = [sylConf.gt2, data.stressPos(n)];
                    
                case 3
                    sylConf.pos3 = [sylConf.pos3, stressPos];
                    sylConf.gt3 = [sylConf.gt3, data.stressPos(n)];
                    
                case 4
                    sylConf.pos4 = [sylConf.pos4, stressPos];
                    sylConf.gt4 = [sylConf.gt4, data.stressPos(n)];
                    
                case 5
                    sylConf.pos5 = [sylConf.pos5, stressPos];
                    sylConf.gt5 = [sylConf.gt5, data.stressPos(n)];
                    
                case 6
                    sylConf.pos6 = [sylConf.pos6, stressPos];
                    sylConf.gt6 = [sylConf.gt6, data.stressPos(n)];

                case 7
                    sylConf.pos7 = [sylConf.pos7, stressPos];
                    sylConf.gt7 = [sylConf.gt7, data.stressPos(n)];
                    
                case 8
                    sylConf.pos8 = [sylConf.pos8, stressPos];
                    sylConf.gt8 = [sylConf.gt8, data.stressPos(n)];                     
            end
            
            allConf.predictPos = [allConf.predictPos, stressPos];
            allConf.gtPos = [allConf.gtPos, data.stressPos(n)];

            if sum(computedClass_Word(startIndex:endIndex)==testLabel(startIndex:endIndex)) == (endIndex-startIndex+1)
                correctCount = correctCount + 1;              
                hitIndex = [hitIndex, n];
            else
                missIndex = [missIndex, n];
                missComputedPos = [missComputedPos, stressPos];
            end
        end
end