语音信号处理赵力（中文入门）

文中研究了6种常用数字调制信号识别的特征参数集，并采用决策树判别方法进行分类识别。仿真结果表明，在SNR≥5dB时，识别正确率在99 以上，且当SNR≥20dB时，识别正确率达到100 。其特点是，算法简单，识别正确率高，达到了自动分类识别的目的，并有利于实现识别的实时化。(In this paper, we study the set of characteristic parameters of the six kinds of commonly used digital modulation signal recognition, and decision tree method for classification. The simulation results show that SNR 鈮� 5dB, the correct rate more than 99 , and when SNR 鈮� 20dB, the correct rate of 100 . Which is characterized by simple algorithm to identify the correct rate, to achieve the purpose of automatic classification and recognition, and help to identify real-time.)

语音信号的录音、读入、放音等：利用函数wavread对语音信号进行采样,记住采样频率和采样点数，给出以下语音的波形图（2.wav），wavread的用法参见mablab帮助文件。利用wavplay或soundview放音。也可以利用wavrecord自己录制一段语音，并进行以上操作(需要话筒)。 (Speech signal recording, reading, playback, etc.: the voice signal using the function wavread sampling, sampling frequency and sampling points to remember, given the following speech waveform (2.wav), wavread usage see mablab help file. Using wavplay or soundview playback. Can also record a voice using wavrecord own, and the above operation (requires microphone).)

通过语音分帧、端点检测、pitch提取、DTW算法，实现歌曲识别(Through voice framing, endpoint detection, pit extraction, DTW algorithm, song recognition is realized)

一种改进的DTW语音识别算法,可以加快识别速度.(An improved DTW speech recognition algorithm, can accelerate the recognition speed.)

基于matlab的HMM语音识别仿真，通过matlab实现对0-9数字的语音识别(HMM speech recognition simulation based on MATLAB)

语音识别与合成入门2，word或压缩包中内有matlab源码(speech recognition and synthesis 2 entry, word or compressed packages within Matlab FOSS)

实现语音识别，使用HTK工具。README描述了具体的训练过程。(Voice recognition, using HTK tools. README describes the specific training process.)

对语音信号基频的提取对于语音信号的分析有一定作用(Basic frequency of speech Analysis )

4基于稀疏编码的语音增强方法.pdf (4 sparse coding speech enhancement based on 4 sparse coding speech enhancement method based on.Pdf.Pdf method)

基于矢量量化（VQ）的说话人识别算法源码(A Speaker Recognition Method Based on Modified VQ Algorithm)