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语音识别，有详细的程序注释，正确率达到95 (Speech recognition, detailed program notes, the correct rate of 95 )

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)

有关语音的matlab源程序,其中包含语音的频谱分析等.(Matlab source code on the voice, including voice spectrum analysis.)

C# 对接 Java 3des md5WithRsa, 有需要的可以参考下(If you need C # to dock Java 3des md5WithRsa, you can refer to the following)

语音识别开源代码 sphinx 0.8 windows版本(sphinx 0.8，ASR)

uds 诊断主机模式，采用C语言作为开发语音。( This is a platform agnostic C library that implements the Unified Diagnostics Services protocol for automotive electronics. UDS is documented in ISO 14229 and is the underpinning for the more well-known On-board Diagnostics (OBD) standard. The library currently supports UDS running over CAN (ISO 15765-4), which uses the ISO-TP (ISO 15765-2) protocol for message framing. This library doesn t assume anything about the source of your diagnostic message requests or underlying interface to the CAN bus)

语音AEC的demo程序和库源代码，在win7下验证可行。(audio aec demo in windows7.)

在matlab平台利用GUI界面实现录音，播放。并对语音信号进行频谱分析，特定人语音识别，混响，混频等基础功能。(On the MATLAB platform, the GUI interface is used to record and play. And the speech signal spectrum analysis, specific speech recognition, reverberation, mixing and other basic functions.)

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.)

基于Matlab的织物疵点检测和识别系统(Fabric defect detection and identification systems based on Matlab)