【语音识别】基于matlab说话人识别系统【含Matlab源码 1704期】

一、获取代码方式

获取代码方式1：
完整代码已上传我的资源：【语音识别】基于matlab说话人识别系统【含Matlab源码 1704期】

获取代码方式2：
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备注：
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二、部分源代码

function test(testdir, n, code)
% Speaker Recognition: Testing Stage
%
% Input:
%       testdir : string name of directory contains all test sound files
%       n       : number of test files in testdir
%       code    : codebooks of all trained speakers
%
% Note:
%       Sound files in testdir is supposed to be: 
%               s1.wav, s2.wav, ..., sn.wav
%
% Example:
%       >> test('C:\data\amintest\', 8, code);

for k = 1:n                     % read test sound file of each speaker
    file = sprintf('%ss%d.wav', testdir, k);
    [s, fs] = wavread(file);      
        
    v = mfcc(s, fs);            % Compute MFCC's
   
    distmin = inf;
    k1 = 0;
   
    for l = 1:length(code)      % each trained codebook, compute distortion
        d = disteu(v, code{l}); 
        dist = sum(min(d,[],2)) / size(d,1);
      
        if dist < distmin
            distmin = dist;
            k1 = l;
        end      
    end
   
    msg = sprintf('Speaker %d matches with speaker %d', k, k1);
    disp(msg);
end
function r = mfcc(s, fs)
% MFCC
%
% Inputs: s  contains the signal to analize
%         fs is the sampling rate of the signal
%
% Output: r contains the transformed signal
%
%
%%%%%%%%%%%%%%%%%%
%
m = 100;
n = 256;
l = length(s);

nbFrame = floor((l - n) / m) + 1;

for i = 1:n
    for j = 1:nbFrame
        M(i, j) = s(((j - 1) * m) + i);
    end
end

h = hamming(n);

M2 = diag(h) * M;

for i = 1:nbFrame
    frame(:,i) = fft(M2(:, i));
end

t = n / 2;
tmax = l / fs;

m = melfb(20, n, fs);
n2 = 1 + floor(n / 2);
z = m * abs(frame(1:n2, :)).^2;

r = dct(log(z));



  

 

  
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三、运行结果

四、matlab版本及参考文献

1 matlab版本
2014a

2 参考文献
[1]韩纪庆,张磊,郑铁然.语音信号处理（第3版）[M].清华大学出版社，2019.
[2]柳若边.深度学习:语音识别技术实践[M].清华大学出版社，2019.

文章来源: qq912100926.blog.csdn.net，作者：海神之光，版权归原作者所有，如需转载，请联系作者。

原文链接：qq912100926.blog.csdn.net/article/details/122892015