GMM

语音识别程序，可以识别哪个声音是谁发出来的。(Voice recognition program, you can identify who sent the voice is coming.)

语音识别中的两种特征提取方法lpcc和mfcc，还有一个是文本无关的识别算法dtw，另外还有一个是预处理消噪部分的。共享一下，这些都是我调试过的，好用。(Speech Recognition two feature extraction methods and mfcc lpcc. There is a text-independent recognition algorithm dtw, in addition to a pretreatment is part of the noise source. Sharing that those are off the debugging and ease of use.)

语音信号的时域、频域分析,包括短时能量分析、短时平均过零率、自相关函数、短时平均幅度差函数等。(Time-domain speech signal, frequency domain analysis, including short-term energy analysis, the average short-term zero-crossing rate, autocorrelation function, such as short-time average magnitude difference function.)

本文主要研究普通计算环境下语音自动识别(ASR)技术的软件实时实现，基于语音识别的基本原理和过程。在VC环境下建立了一套语音识别系统及其演示软件。实验表明，该系统对特定人情况有较高的识别率和一定的实时性(In this paper, under the computing environment on general automatic speech recognition (ASR) technology to achieve real-time software, speech recognition based on the basic principles and processes. VC environment in the establishment of a voice recognition system and its presentation software. The experiments show that the systems are in particular have a high recognition rate and a certain degree of real-time)

语音处理的实用代码，完成耳语音的声韵分割功能(Practical speech processing code, complete the ear speech sound segmentation function)

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

LPC Speech Recoginze

核主成分分析法,用matlab实现,极为精彩.不可错过(Kernel Principal Component Analysis method, using matlab realize, is extremely exciting. Not to be missed)

这是一个语音的文件的一个FFT转换文件,是用C++写的源程序,相信对大家有用(This is a voice of a paper document conversion FFT is written in C source files, it may be useful to think)

SFS提供了计算语音本质的一系列工具。包括支持各种数据格式，信号处理和图形，频谱、共振峰分析，基频提取等等。在线文档说明请访问http://www.phon.ucl.ac.uk/resource/sfs/help/(SFS provides a voice calculated nature of a series of tools. Including support for various data formats, signal processing and graphics, spectrum, formant analysis, frequency, etc. extraction. Online document shows, please visit http :// www.phon.ucl.ac.uk/resource/sfs/help/)