BSS_decomp

从wave中读取数据，通过mfcc提取特征系数。从txt文件中读取基于GMM的分类器，最终识别为那种类型(Read data from the wave through the MFCC feature extraction coefficient. Txt file to read from the GMM-based classifier, and ultimately identified as the type)

微软研究院的说话人识别工具包，包括GMM-UBM、I-Vector。其中demo_gmm_ubm_artificial.m和demo_ivector_plda_artificial.m为生成模拟特征参数进行训练与识别的教学示例，十分适合初学者学习说话人识别基础算法。具体使用方法请看内部文档。(Microsoft Research s speaker recognition toolkit, including GMM-UBM, I-Vector. Demo_gmm_ubm_artificial.m and demo_ivector_plda_artificial.m which generates an analog characteristic parameters for example teaching training and recognition, very suitable for beginners to learn the basic algorithm for speaker recognition. See the specific use of internal documents.)

实现多个人的说话人识别，基于gmm模型，用mfcc参数训练(voice conversion based on gmm)

一个谱相减程序（IN MATLAB）， 一个谱相减程序（IN MATLAB），(a spectral subtraction procedure (IN MATLAB), a spectral subtraction procedure (IN MATLAB).)

语音识别中信号特征的提取，基因周期估计，共振峰估计等。(Signal feature extraction in speech recognition, cycle genes estimation, formant estimation,etc)

用于汉语语调识别的程序，可以识别我们说话中的四个声调。已通过测试(Chinese tone recognition for the program, has been tested)

语音自动识别技术，采用C++编程，可以给做语音识别的提供参考(Automatic speech recognition technology, using C++ programming, you can do to provide a reference for Speech Recognition)

语音信号处理中的所有基本的算法的代码（C语言版）(Speech signal processing algorithms in all the basic code (C language version))

利用自相关或平均幅度差提取基音原理，帧长160，帧移80。求能量E、过零率Z和基音周期pitch；采用自相关法或平均幅度差法求取基音周期，基音周期范围（80~400hz）；画出能量、过零率和基音曲线。(Pitch principle is extracted by means of autocorrelation or mean amplitude difference)

语音信号时频分析，包括语谱图，过零率，自编的自相关，以及最后用了三种方法（短时能量和过零率、谱熵法、Teager算子）进行端点检测，代码完整且测试通过(time and frequency domain analysis of speech signals,including spectrogram,rate of zerocrossing,autocorrelation.and three method of endpoint detection,especially the Teager )