speech_vad

本实例程序是基于matlab的语音识别程序，通过提取传统的MFCC特征集，采用当前流行的SVM分类器，作为对比实验是一个不错的选择。(This example program is popular SVM classifier matlab speech recognition program to extract MFCC feature set, as a comparative experiment is a good choice. )

单点定位的滤波程序，可以获得速度信息和位置信息,这是一个滤波程序，对语音信号滤波。(A single point positioning of the filtering process, get the speed of information and location information,this is a wiener filtering process to filter the speech signal.)

LMS算法多麦克风语音降噪，语音降噪处理，基于matlab(LMS algorithm for multi-microphone speech noise reduction, voice, noise reduction, based on matlab)

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)

通常语音信号在增强时会出现混响现象，演讲者为了消除背景混响，不得不频繁地偏转头部的方向，这样会造成脉冲响应的不断改变。我们结合盲解卷法和频谱消去法来提高逆滤波器的滤波效果。我们利用输入语音信号间的相关系数矩阵计算出稳定、精确的室内脉冲响应的逆滤波器，而这些输入信号无需测量室内的脉冲响应就能被观测到。逆滤波能够消除早期的反射，这些反射包含混响中的绝大部分能量。之后，用频谱消去法来抑制逆滤波后的信号的尾部混响。本方法在实际适应性方面的表现通过具体的实验进行了验证，结果表明盲解卷法和频谱消去法的结合相较于单独使用一种方法，能够提供一个更优越的演说环境。(Usually voice signal will be enhanced when the reverberation phenomenon, the speaker in order to eliminate the background reverberation, and had to frequently deflect the direction of the head, this will cause the impulse response of changing. We combine the blind deconvolution and spectral elimination method to improve the filtering effect of the inverse filter. We use the correlation coefficient matrix between the input speech signal to calculate the stable, accurate inverse filter of the indoor impulse response, and these input signals do not need to measure the room impulse response can be observed. Inverse filtering to eliminate early reflections, these reflections contains most of the energy in the reverberation. After the spectrum elimination method to suppress the tail reverberation of the signal after the inverse filtering. Performance in the actual adaptation of the method by specific experimental validation results show that the blind deconvolution and spectrum to eliminate )

adaptive modulation cm in speech coding

分段信噪比测试，主要是用于语音增强，语音编码后的测试使用(segment SNR test, primarily for speech enhancement, speech coding after testing)

基于峭度的盲分离开关算法的matlab源代码程序(Blind Source Separation Based on Kurtosis switch algorithm )

短时平均能量和平均幅度差函数进行基音检测的方法(Short-term average energy and average magnitude difference function pitch detection method)

提供了segmantal SNR及IS的计算代码，用于语音增强后评价用。(Provided segmantal SNR and IS calculation code for speech enhancement with post-evaluation.)