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用vq算法进行说话人识别，能达到良好的效果(Using VQ speaker recognition algorithm can achieve good results)

语音信号处理c语言程序-音高、加窗、MFCC、PLP、等(C programming language speech signal processing- pitch, add window, MFCC, PLP, etc)

通过广义互相关法求时延 三种加权系数 ROTH SCOT PHAT(Delay by the generalized cross correlation method)

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.)

GMM的说话人识别系统，识别效果90 多(GMM speaker recognition system, the recognition effect more than 90 )

基于espeak的一个文本转语音的代码,可以把文本转成WAV文件(basic espaeck to translate txt to wav file)

基于语音信号工具箱的隐马尔科夫HMM模型的说话人识别，请联系lishicheng64@126.com(Speech signal based on HMM toolbox Hidden Markov Model speaker recognition, please contact lishicheng64@126.com)

C语言fft和ifdct的函数，可以直接使用(C language functions fft and ifdct can be directly used)

分段信噪比测试，主要是用于语音增强，语音编码后的测试使用(segment SNR test, primarily for speech enhancement, speech coding after testing)

是一个语音识别的程序，有LPCC，MFCC等的代码，最后用SVM进行分类(Is a voice recognition program, there LPCC, MFCC and other code, the final classification with SVM)