test

功率倒置算法的LMS实现，因为自己遇到了点问题，本人一直在找这个程序，没找到，故自己重新检查把问题发现了，相信如果你要实现的话可能会遇到这个问题祝你好运！(Power inversion algorithm LMS implementation, because they encountered a point problem, I ve been looking for this program, did not find it to re-examine the problem yourself discovered, I believe if you want to achieve, then you may encounter this problem Good luck!)

function [Coefficients,residual,pitch,Gain,parcorCoefficients,stream,B,crossmat,error_stream] = lpcanalysis(speechtodecode,samplerate,L,windowtime,preemp)

基于最小均方误差的助听器语音去噪算法, 用于以最大程度消除助听器接受的语音杂音.(Speech denoising algorithm based on the minimum mean square error of a hearing aid for the hearing aid acceptable voice murmur eliminated to the greatest extent.)

基于MFCC的利用LPCC做的说话人识别论文(Based on the MFCC the use of LPCC do the speaker identification papers)

绘制语音信号的 WVD 分布，对时频工具箱中的 tfrwv 及 tfrspwv 函数的使用进行了详细说明(The way of drawing speech signals WVD was shown in the m file, and corresponding functions tfrwv and tfrspwv were discussed thoroughly.)

GMM说话人识别平台全套，从特征提取到模式识别，到识别率，一整套都有(GMM speaker recognition platform full, from feature extraction to pattern recognition, the recognition rate, set both)

一个能实现对语音信号分帧的STFT和ISTFT的函数(Realize a sub-frame of the speech signal and the STFT of the function ISTFT)

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.)

GMM的说话人识别系统，识别效果90 多(GMM speaker recognition system, the recognition effect more than 90 )

本次课程设计主要介绍了语音信号的录制、语音信号的采集与分析、语音信号的采样、语音信号的频谱分析、加噪后的频谱分析、滤波器的设计以及对于语音信号的回放等知识。通过 Cool Edit录制一段语音信号，运用MATLAB对其进行时域与频域分析，然后设计滤波器加入噪声进行滤波处理，比较滤波前后始于波形或频谱的变化，最后实现对于语音的回放设计。(Digital voice processing filter design)