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本文介绍了基于麦克风阵列的声源定位算法，给初学者有很大的帮助(This article describes the microphone array based sound source localization algorithm, a great help for beginners)

科大讯飞关于语音识别开发SDK库，支持语音转汉字功能及根据读汉字功能。有兴趣的可以好好研究研究(IFLYTEK speech recognition development SDK library are interested in a good studies)

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/)

本书系统地阐述了语音信号处理的原理、方法、技术和应用，同时给出了部分内容对应的MATLAB仿真源程序。全书共12章，第1章至第7章是基本理论部分，包括语音信号的数字模型、语音信号的短时时域分析和频域分析、语音信号的同态处理、语音信号线性预测分析和矢量量化；第8章至第12章是应用部分，包括语音编码、语音合成、语音识别、语音增强和语音处理的实时实现。本书内容全面，重点突出，原理阐述深入浅出，注重理论与实际应用的结合，可读性强。(This book describes the speech signal processing principles, methods, techniques and applications, and gives the corresponding part of the contents of the MATLAB simulation source. The book is 12 chapters, Chapter 1 to Chapter 7 is the basic theoretical part, including voice signal digital model, speech signal analysis in time domain and frequency domain analysis, speech signal homomorphic processing, speech signal analysis and linear prediction vector quantified Chapter 8 to Chapter 12 is the application of parts, including speech coding, speech synthesis, speech recognition, speech enhancement and voice processing, real-time implementation. The book is comprehensive, focused and Rationale layman, focusing on the combination of theory and practical application, readable.)

针对信号自适应chirplet分解未知参数多、实现起来比较困难的特点，文献[1]提出了一种新的chirplet分解快速算法。该算法利用计算信号的二次相位函数，得到其能量分布集中于信号的调频率曲线上的结论，此时通过谱峰检测可同时获得chirplet调频率、时间中心和幅度的估计；然后通过解线性调频技术获得其初始频率和宽度的估计，仿真结果验证了本文算法的有效性。(this code includs one method for chirplet analasis,that is used in voice and ultra-wave analasys,etc.)

Speaker Identification using MFCC feature and VQ training, very clear MATLAB code

实现语音的分割和识别，语音分割通过短时能量和过零率，语音识别通过dtw算法。(audio cut and reconige)

回音消除算法matlab,采用的VIRE的双方通话检测(Matlab algorithms eliminate echoes, the two sides call the VIRE Detection)

基于LMS算法的变换域的源程序，里面给出了学习曲线，迭代后的输出曲线(LMS algorithm based on the Domain source, which is a learning curve, the output iterative curve)

cubica算法performes ICA by diagonalization of third- and fourth-order cumulants simultaneously(cubica algorithm performes ICA by diagonalization of third- and fourth-order cumulants simultaneously)