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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 
% 
% 
%%%%%%%%%%%%%%%%%% 
% Mini-Project: An automatic speaker recognition system 
% 
% Responsible: Vladan Velisavljevic 
% Authors: Christian Cornaz 
% Urs Hunkeler 
[s,fs]=wavread('1.wav'); 
fs = 12500; 
m = 100; 
n = 256; 
l = length(s); 
nbFrame = floor((l - n) / m) + 1; 
 
s=double(s); 
s=filter([1 -0.9375],1,s); 
 
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; 
 
n2 = 1 + floor(n / 2); 
z = m * abs(frame(1:n2, :)).^2; 
r = dct(log(z)); 
plot(r); 
 
% 归一化倒谱提升窗口 
% w = 1+6*sin(pi*[1:12]./12); 
% w=w/max(w); 
% r=r.*w'; 
%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
%2005-12-25 modified by Robin 
%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
 
% 获得差分mfcc 
 
% dtm=zeros(size(r)); 
% for i=3:size(r,1)-2 
%     dtm(i,:)=-2*r(i-2,:)-r(i-1,:)+r(i+1,:)+2*r(i+2,:); 
% end 
% dtm=dtm/3; 
% % combine mfcc and △mfcc 
% % 连接mfcc和差分mfcc 
% ccc = [r dtm]; 
%  
% % 去除首尾两帧，因为这两帧的一阶差分参数为0 
% r=ccc(3:size(r,1)-2,:);