LMS_PI

基于熵的端点检测算法，比传统的端点检测能更精确的检测出端点(endpoint detection algorithm than the traditional endpoint detection more accurate detection of Endpoint)

语音信号去噪，在MATLAB开发环境下，对含噪声的语音信号进行卡尔曼滤波，实现语音增强的功能。(The voice signal denoising, the Kalman filter, the noisy speech signal in the MATLAB development environment Wave, speech enhancement.)

C语言实现的端点检测,具有良好的效果,对于做语音识别者来说，是很好的参考(C language implementation of endpoint detection, with good results)

HMM连续语音识别(Continuous Speech Recognition)

labview做的分析语音信号的程序，做简单的频谱分析，识别(failed to translate)

一个对有噪声的音频信号进行自相关滤波的c程序，用的turbo c 3.0工具(One pair of noisy audio signal autocorrelation filtering c program using turbo c 3.0 Tools)

用c编写的文字转化成声音的程序,可以把该程序移植到单片机和其他嵌入式处理器中.实现应有的功能.(With c prepared text into sound procedures, the program can be transplanted into single-chip and other embedded processors. Realize the function.)

最权威和最全面的语音识别的特征提取的 IEEE的期刊论文1980(The most authoritative and comprehensive speech recognition feature extraction of the IEEE Journal Papers 1980)

H-H微分方程的matlab原代码,内包含说明文档,对模拟神经元有帮助.(H-H Differential Equations Matlab original code, which includes documentation, simulated neurons to help.)

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.)