function [ ccc ] = mfcc( x )
%MFCC 此处显示有关此函数的摘要
% mfcc完整参数形成
% 此处显示详细说明
%读取语音信号
audio = audioread(x);
%归一化mel滤波器 三角滤波器 掩蔽效应
bank = melbankm(24,256,8000,0,0.5,'m');
%MELBANKM determine matrix for a mel-spaced filterbank [X,MN,MX]=(P,N,FS,FL,FH,W)
%
% Inputs: p number of filters in filterbank
% n length of fft
% fs sample rate in Hz
% fl low end of the lowest filter as a fraction of fs (default = 0)
% fh high end of highest filter as a fraction of fs (default = 0.5)
% w any sensible combination of the following:
% 't' triangular shaped filters in mel domain (default)
% 'n' hanning shaped filters in mel domain
% 'm' hamming shaped filters in mel domain
%
% 'z' highest and lowest filters taper down to zero (default)
% 'y' lowest filter remains at 1 down to 0 frequency and
% highest filter remains at 1 up to nyquist freqency
%
% If 'ty' or 'ny' is specified, the total power in the fft is preserved.
%
bank = full(bank);%转换为满矩阵
bank = bank/max(bank(:));
%DCT系数，一般为12&24
%12行数，24列数，从n开始内循环到外循环
for k=1:12
n=0:23;
dctcoef(k,:) = cos((2*n+1)*k*pi/(2*24));
end
%归一化倒谱提升窗口
w = 1 + 6*sin(pi*[1:12]./12);%有公式代入
w = w/max(w);
%预加重滤波器
xx = filter([1 -0.9375],1,audio);
%语音信号分帧
frame = enframe(xx,256,80);
%计算每帧MFCC参数
for i = 1:size(frame,1)
y = frame(i,:);
s = y'.*hamming(256);%汉明窗
t = abs(fft(s));%快速傅里叶转换
t = t.^2;
c1 = dctcoef*log(bank*t(1:129));%129是bank的列数
c2 = c1.*w';
m(i,:)=c2';
end
%差分参数
dtm = zeros(size(m));
for i = 3:size(m,1)-2
dtm(i,:) = -2*m(i-2,:) - m(i-1,:) + m(i+1,:) + 2*m(i+2,:);
end
dtm = dtm/3;
%合并MFCC参数
ccc = [m dtm];
%去除首尾帧
ccc = ccc(3:size(m,1)-2,:);%出现24维数是因为12阶MFCC进行一阶差分，形成24维
end
评论0