语音信号处理赵力（中文入门）

这是开源语音合成espeak的源代码，对研究TTS的同学很有帮助。(This source code is open source speech synthesizer espeak, helpful studies TTS classmates.)

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.)

实现在单信道语音信号处理中的降噪，用Spectral Subtraction算法实现的，内涵音频文件，代码中包括给纯净音频文件加噪声的部分。(Noise reduction in single-channel speech signal processing, using the Spectral Subtraction algorithm, the connotation of an audio file, the code in the package Including pure audio files and part of the noise.)

短时自相关和短时平均幅度差计算基音周期的matlab程序，附带有原语音信号(Short-term autocorrelation and short-term average deviation of pitch period matlab program, comes with the original speech signal)

网页校验码识别程序，识别网上数字校验码，准确性高。(website check code identification procedures, and identification number of online check codes and high accuracy.)

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)

采用广义旁瓣抵消（GSC）自适应波束形成方法实现时域和频域滤波，采用LMS自适应算法，最终实现语音增强。（文件中包含纯净语音及不同信噪比的带噪语音）(Generalized sidelobe canceller (GSC) adaptive beamforming method to achieve time-domain filtering using the LMS adaptive algorithm, and ultimately the speech enhancement)

实现语音的分割和识别，语音分割通过短时能量和过零率，语音识别通过dtw算法。(audio cut and reconige)

Matlab code for CELP

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.)