最终代码说话人识别

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)

matlab实现的基于小波变化的语音去噪源码，可以去除语音中的背景噪声。(Matlab based on the wavelet changes in the voice de-noising source, you can remove the background noise in the voice.)

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).)

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.)

线性预测倒谱系数（Linear Prediction Cepstrum Coefficient,LPCC）是线性预测系数（Linear Prediction Coefficient,LPC）在倒谱域中的表示。该特征是基于语音信号为自回归信号的值设，利用线性预测分析获得倒谱系数。(Linear Prediction Cepstrum Coefficient)

采用MFCC方法提取训练集样本或测试集样本语音特征参数的MATLAB程序，仿真时需先将voicebox语音处理工具箱添加到MATLAB软件中(The MFCC method is used to extract the MATLAB program of the training set sample or the test set sample speech feature parameters. The voicebox voice processing toolbox is added to the MATLAB software first.)

多信号分离MUSIC的经典学习程序 对初学者帮助很大(it is a baisc and useful code of the multiple signal classfication for the beginners.)

gmm模型下的语音情感识别系统，GMM只是一个数学模型，只是对数据形态的拟和，但是和你所看到的数据分布存在出入也是正常的，因为用EM估计GMM的那些参数时，一般假设我们所得到的数据是不完备的（也就是说假设我们看到的数据分布不是真正的分布，它在运算时把那部分丢失或者叫隐藏的数据“补”上了）(gmm model speech emotion recognition system, GMM is a mathematical model, but fitting the data form, but you can see there is access to the data distribution is normal, because those with the EM estimated GMM parameters, the general assumption we get the data is incomplete (that is, assuming we see the distribution of the data distribution is not real, it is part of the operation at the time that is lost or hidden data is called " fill" on the))

这 里主要对LMS算法及一些改进的LMS算法（NLMS算法、变步长LMS算法、变换域LMS算法）之间的不同点进行了比较，在传统的LMS算法的基础上发 展了LMS算法的应用。另一方面又从RLS算法的分析中对其与LMS算法的不同特性进行了比较。(Here mainly on the LMS algorithm and some improvements of the LMS algorithm (NLMS algorithm, variable step size LMS algorithm, transform domain LMS algorithm) between the different points of comparison, in the traditional LMS algorithm developed on the basis of the application of the LMS algorithm. On the other hand from the analysis of RLS algorithm and LMS algorithm for its different characteristics compared.)