Speech endpoint detection and its implementation using matlab

计算声音信号的短时能量，过零率，然后检测语音的端点-Short-term calculation of the voice signal energy, zero-crossing rate, and then voice endpoint detection

ITU-T G.729A标准源代码解码端，已创建工程文件，方便初学者，已测试，运行良好-ITU-T G.729A standard decoder source code, project files have been created for beginners, have been tested, well-functioning

系统辨识与自适应控制MATLAB仿真CH6,好东西大家分享-System Identification and Adaptive Control of MATLAB simulation CH6, good things to share with you

在做和语音信号处理相关的项目时要用到的语音工具箱,比如语音识别,说话人识别等,里面有一些已经封装好的小函数,可供大家编程序的时候直接调用-In speech signal processing to do and projects related to voice use toolbox, such as speech recognition, speaker recognition, etc., there are some good small function package for everyone when programmed direct call

语音识别:语音矢量化及算法及与原文件的矢量对比功能源代码-Speech Recognition : Speech vector algorithm and the original document and the contrast vector function source code

英国爱丁堡大学的语音处理系统，可以找到大部分语音处理/识别/合成所需要的算法-University of Edinburgh voice processing system that can find most of voice processing/recognition/synthesis algorithms needed

G.723.1语音压缩编码的英文原文和中文译文。该协议是双速率语音压缩编码，提供5.3和6.3kbps的速率，占用很窄的带宽。-G.723.1 voice coding the original English and Chinese translations. The agreement is a two-bit-rate speech coding, and 5.3. Rate, which takes up a very narrow bandwidth.

本文将现实中采集到的一段语音加上了高斯白噪声，利用了LMS算法，将噪声滤除，仿真效果良好-This article will be collected in reality a section of voice coupled with a Gaussian white noise, using the LMS algorithm, the noise filtering, simulation results

用于语音识别，基于HMM模型，用C++语言编写。可用连续语音识别-It is based on HMM Model and developed with C++ which could be used to continuous speech recognition.

语音信号的频域处理,语音虽然是一个时变、非平稳的随机过程。但在短时间内可近似看作是平稳的。因此如果能从带噪语音的短时谱中估计出“纯净”语音的短时谱，即可达到语音增强的目的。由于噪声也是随机过程，因此这种估计只能建立在统计模型基础上。利用人耳感知对语音频谱分量的相位不敏感的特性，这类语音增强算法主要针对短时谱的幅度估计。 -voice signals in the frequency domain processing, voice is a time-varying, nonstationary random process. But in a short period of time can be approximated as smooth. So if Noisy Speech from the short-term spectrum estimate "pure" voice of the short-term spectrum, and reached speech enhancement purposes. As the noise is random process, which can only be estimated based on statistical models based on. Use ear perception of voice spectrum component of the phase sensitive to the characteristics of such speech enhancement algorithms targeted at the rate of short-term spectral estimation.