lvqrengong.m

用matlab编程,采用神经网络是别的方法,

clear;
num=10;

disp('正在计算识别模型...')
for i=1:num
   fname = sprintf('%ss%d.wav', 'data\train\', i); 
   [s, fs] = wavread(fname);
    v =mfcc(s, fs); 
    [n,m]=size(v);
    a=reshape(v,1,n*m);
    b=a(1:3000);
	ref(i).p = b;
    
end 
p=ref(1).p;
for i=1:num-1
    p=[p;ref(i+1).p];
end
p=p';
T=[1 0 0 0 0 0 0 0 0 0 ;
   0 1 0 0 0 0 0 0 0 0;
   0 0 1 0 0 0 0 0 0 0 ;
   0 0 0 1 0 0 0 0 0 0 ;
   0 0 0 0 1 0 0 0 0 0 ;
   0 0 0 0 0 1 0 0 0 0 ;
   0 0 0 0 0 0 1 0 0 0 ;
   0 0 0 0 0 0 0 1 0 0 ;
   0 0 0 0 0 0 0 0 1 0 ;
   0 0 0 0 0 0 0 0 0 1 ;  
];

%c=[ 1 2 3 4 5 6 7 8 9 10];
%T=ind2vec(c);



T=T';

net=newlvq(minmax(p),10,[0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 ] );

w1=net.IW{1};
w1
net.trainParam.epochs = 1000;

net=train(net,p,T);
Y=sim(net,p);

yc=vec2ind(Y);

disp('正在计算测试识别的结果...')
for i=1:num
   fname = sprintf('%ss%d.wav', 'data\test\', i); 
   [s, fs] = wavread(fname);
    v =mfcc(s, fs); 
    [n,m]=size(v);
    a_test=reshape(v,1,n*m);
    b_test=a_test(1:3000);
    test(i).p_test = b_test;
    
end 
p_test=test(1).p_test;
for i=1:num-1
    p_test=[p_test;test(i+1).p_test];
end
p_test=p_test';


y_test= sim(net,p_test);

yc_test=vec2ind(y_test);
yc
yc_test