hmm

代码说明：

  hmm文件时运用HMM算法实现噪声环境下语音识别的。其中vad.m是端点检测程序；mfcc.m是计算MFCC参数的程序；pdf.m函数是计算给定观察向量对该高斯概率密度函数的输出概率；mixture.m是计算观察向量对于某个HMM状态的输出概率，也就是观察向量对该状态的若干高斯混合元的输出概率的线性组合；getparam.m函数是计算前向概率、后向概率、标定系数等参数；viterbi.m是实现Viterbi算法；baum.m是实现Baum-Welch算法；inithmm.m是初始化参数；train.m是训练程序；main.m是训练程序的脚本文件；recog.m是识别程序。(hmm HMM algorithm file using speech recognition in noisy environments. Which is the endpoint detection process vad.m mfcc.m procedure is to calculate the MFCC parameters pdf.m function is calculated for a given observation vector of the Gaussian probability density function of output probability mixture.m is to calculate the observation vector for a HMM state output probability of observation vector is the number of Gaussian mixture per state output probability of the linear combination getparam.m before the calculation of the probability function, backward probability, calibration coefficients and other parameters viterbi.m is Viterbi algorithm implementation baum.m Baum-Welch algorithm to achieve inithmm.m is the initialization parameters train.m is the training program main.m training program is a script file recog.m is to identify procedures.)

文件列表：

hmm
...\baum.m,1511,2001-11-12
...\getparam.m,1990,2002-02-28
...\hmm.mat,63856,2001-11-12
...\inithmm.asv,1266,2009-10-19
...\inithmm.m,1266,2009-10-19
...\main.m,165,2001-11-13
...\mfcc.m,859,2001-11-09
...\mixture.m,357,2001-11-11
...\pdf.m,230,2001-11-10
...\recog.asv,264,2009-10-19
...\recog.m,252,2009-10-18
...\samples.mat,630000,2001-11-12
...\train.m,839,2001-11-13
...\vad.m,1860,2009-10-18
...\viterbi.m,1026,2001-11-11