rbfrengong.m

用matlab编程,采用神经网络是别的方法,

clc;
clear;
num=15;

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(1:300);
	ref(i).p = b;
    
end 
p=ref(1).p;
for i=1:num-1
    p=[p;ref(i+1).p];
end
T=[1 0 0 0 0 0 0 0 0 0 0 0 0 0 0;
   0 1 0 0 0 0 0 0 0 0 0 0 0 0 0;
   0 0 1 0 0 0 0 0 0 0 0 0 0 0 0;
   0 0 0 1 0 0 0 0 0 0 0 0 0 0 0;
   0 0 0 0 1 0 0 0 0 0 0 0 0 0 0;
   0 0 0 0 0 1 0 0 0 0 0 0 0 0 0;
   0 0 0 0 0 0 1 0 0 0 0 0 0 0 0;
   0 0 0 0 0 0 0 1 0 0 0 0 0 0 0;
   0 0 0 0 0 0 0 0 1 0 0 0 0 0 0;
   0 0 0 0 0 0 0 0 0 1 0 0 0 0 0;
   0 0 0 0 0 0 0 0 0 0 1 0 0 0 0;
   0 0 0 0 0 0 0 0 0 0 0 1 0 0 0;
   0 0 0 0 0 0 0 0 0 0 0 0 1 0 0;
   0 0 0 0 0 0 0 0 0 0 0 0 0 1 0;
   0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
];

p=p';
T=T';
spread=1.2;
net=newrbe(p,T,spread);
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(1:300);
    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);
%maxvalue=0;k=0;
%for m=1;num
    %for n=1:num
        %if (Y_test(n,m)>maxvalue)
           % maxvalue=Y_test(n,m);
           % k=n;
           %end
           %end
    %msg = sprintf('测试说话人 %d 和模板中的说话人 %d 匹配', m, k);
    %disp(msg);
   %maxvalue=0;
   % k=0;
   %end