EVRC

hmm文件时运用HMM算法实现噪声环境下语音识别的。其中vad.m是端点检测程序；mfcc.m是计算MFCC参数的程序；pdf.m函数是计算给定观察向量对该高斯概率密度函数的输出概率；mixture.m是计算观察向量对于某个HMM状态的输出概率，也就是观察向量对该状态的若干高斯混合元的输出概率的线性组合；getparam.m函数是计算前向概率、后向概率、标定系数等参数；viterbi.m是实现Viterbi算法；baum.m是实现Baum-Welch算法；inithmm.m是初始化参数；train.m是训练程序；main.m是训练程序的脚本文件；recog.m是识别程序。(hmm HMM algorithm file using speech recognition in noisy environments. Which is the endpoint detection process vad.m mfcc.m procedure is to calculate the MFCC parameters pdf.m function is calculated for a given observation vector of the Gaussian probability density function of output probability mixture.m is to calculate the observation vector for a HMM state output probability of observation vector is the number of Gaussian mixture per state output probability of the linear combination getparam.m before the calculation of the probability function, backward probability, calibration coefficients and other parameters viterbi.m is Viterbi algorithm implementation baum.m Baum-Welch algorithm to achieve inithmm.m is the initialization parameters train.m is the training program main.m training program is a script file recog.m is to identify procedures.)

将wav格式文件转化为txt格式的程序,用于读入语音文件转换TXT格式，便于程序分析(Wav format files into txt format program)

语音信号去噪，在MATLAB开发环境下，对含噪声的语音信号进行卡尔曼滤波，实现语音增强的功能。(The voice signal denoising, the Kalman filter, the noisy speech signal in the MATLAB development environment Wave, speech enhancement.)

语音增强算法综述，还可以，基本的谱减法，维纳滤波法都有(Overview of speech enhancement algorithm, can also basic spectral subtraction, Wiener filtering method has)

西奥多里蒂斯著，李晶皎译 本书系统阐述了模式识别的原理与方法，并在此基础上介绍了模式识别的应用。全书分为：基础部分和应用部分：基础部分主要包括统计模式识别、模糊模式识别、神经网络模式识别等内容；应用部分有车牌识别和语音识别。 (This paper discussed the principles and methods of pattern recognition, and based on this, the application of pattern recognition. Encyclopedia is divided into: basic part and application part: basic parts mainly include statistical pattern recognition, the fuzzy pattern recognition, neural network pattern recognition content Application part have license plate identification and voice recognition.)

利用自适应滤波器对心音信号进行预测，包括了LMS算法，归一化LMS，变步长LMS和RLS算法，其中RLS的预测效果最好.(Heart sound signals using adaptive filter to predict, including the LMS algorithm, the normalized LMS, variable step size LMS and RLS algorithm, in which the best forecast of RLS.)

3、语音特征提取与分类 首先, 待识别语音转化为电信号后输入识别系统, 经过预处理后用数学方法提取语音特征信号, 提取出的语音特征信号可以看成该段语音的模式。(3, the voice feature extraction and classification First, to be recognized voice into electrical signals input recognition system, after pretreatment with a mathematical method to extract speech characteristic signal extracted speech characteristic signal can be seen as the voice segment model.)

程序实现的功能是：一种改进型的LMS算法！具有收敛速度快的特点(Procedures for the realization of the functions are: an improved algorithm of LMS! With the characteristics of fast convergence)

语音识别中的两种特征提取方法lpcc和mfcc，还有一个是文本无关的识别算法dtw，另外还有一个是预处理消噪部分的。共享一下，这些都是我调试过的，好用。(Speech Recognition two feature extraction methods and mfcc lpcc. There is a text-independent recognition algorithm dtw, in addition to a pretreatment is part of the noise source. Sharing that those are off the debugging and ease of use.)

LBG-vector quantization algorithm