基于神经网络的语音情感识别附matlab代码.zip

%基于神经网络的语音情感识别 clc close all clear all load A_fear fearVec; load F_happiness hapVec; load N_neutral neutralVec; load T_sadness sadnessVec; load W_anger angerVec; trainsample(1:30,1:140)=angerVec(:,1:30)'; trainsample(31:60,1:140)=hapVec(:,1:30)'; trainsample(61:90,1:140)=neutralVec(:,1:30)'; trainsample(91:120,1:140)=sadnessVec(:,1:30)'; trainsample(121:150,1:140)=fearVec(:,1:30)'; trainsample(1:30,141)=1; trainsample(31:60,141)=2; trainsample(61:90,141)=3; trainsample(91:120,141)=4; trainsample(121:150,141)=5; testsample(1:20,1:140)=angerVec(:,31:50)'; testsample(21:40,1:140)=hapVec(:,31:50)'; testsample(41:60,1:140)=neutralVec(:,31:50)'; testsample(61:80,1:140)=sadnessVec(:,31:50)'; testsample(81:100,1:140)=fearVec(:,31:50)'; testsample(1:20,141)=1; testsample(21:40,141)=2; testsample(41:60,141)=3; testsample(61:80,141)=4; testsample(81:100,141)=5; class=trainsample(:,141); sum=bpnn(trainsample,testsample,class); figure(1) bar(sum,0.5); set(gca,'XTickLabel',{'生气','高兴','中性','悲伤','害怕'}); ylabel('识别率'); xlabel('五种基本情感'); p_train=trainsample(:,1:140)'; t_train=trainsample(:,141)'; p_test=testsample(:,1:140)'; t_test=testsample(:,141)'; sumpnn=pnn(p_train,t_train,p_test,t_test); figure(2) bar(sumpnn,0.5); set(gca,'XTickLabel',{'生气','高兴','中性','悲伤','害怕'}); ylabel('识别率'); xlabel('五种基本情感'); sumlvq=lvq(trainsample,testsample,class); figure(3) bar(sumlvq,0.5); set(gca,'XTickLabel',{'生气','高兴','中性','悲伤','害怕'}); ylabel('识别率'); xlabel('五种基本情感');