yuyinxinhaolianghua

基于倒谱短时部分反映了语音的声道特性，先用汉明窗取一帧语音，然后经变换得到语音倒谱，将倒谱短时部分取出，进行正交反变换后将得到声道的对数谱，即得到语音频谱的包络。将频谱包络和频谱画在一张图上，有很好的对比效果。获取的包络效果十分好。(Based Cepstral partly reflects the short channel characteristics of the speech, first take a Hamming window with a frame of speech, and speech cepstrum obtained by converting the cepstrum short segment out inverse orthogonal transform to obtain channel will of the spectrum, i.e. to obtain the envelope of the speech spectrum. The spectral envelope and spectral painted on a chart, there is a good contrast. Get the envelope effect is very good.)

从一段音频中识别说话人的性别。开发环境vs2005(To identify the audio from a speaker' s gender. Development Environment vs2005)

基于FastICA相结合实现的语音信号的采集、随机混合，再通过盲分离将混合后的语音信号分离(Speech signal acquisition and random mixing based on FastICA, and then the mixed speech signal is separated by blind separation.)

PESQ-主观语音质量评估。 ITU-T P.862建议书提供的客观MOS值评价方法。PESQ可以广泛的用于现场和模拟网络中端到端测量。背景(环境)噪声和噪声处理,可以通过用PESQ比较干净的、未处理的信号和编码的、经噪声干扰失真的信号评估得到。(PESQ- subjective speech quality assessment. ITU-T P.862 recommendations for objective MOS value uation method book provides. PESQ can be widely used in the field and in the end measurement analog networks. Background (ambient) noise and noise processing, you can use PESQ relatively clean, unprocessed signal uation and signal encoded by the noise distortion obtained.)

（1）理解矢量量化的基本原理。 （2）掌握矢量量化器设计的LBG方法。 （3）运用LBG方法获取语音短时平均能量码书((1) to understand the basic principles of vector quantization. (2) master the vector quantizer design LBG method. (3) Using the LBG method to obtain the speech short time average energy code book)

说话人识别GMM模型训练MATLAB程序，需要和voicebox配合使用，使用voicebox提取MFCC和k均值分类，这是GMM说话人识别模型的训练程序。(Speaker Recognition GMM model training MATLAB program used in conjunction with and voicebox, voicebox extract MFCC and k-means classification, which is a GMM speaker recognition model training program.)

自动语音应答系统 硬件需要一个语音卡或一个语音modem 其中有6个类，下载包里头有详细类说明(Automatic Voice Response System hardware needs a sound card or a voice modem which six categories, Download Packet Erlitou detailed presentation on)

Praat4610 语音合成及分析源代码(Praat4610 speech synthesis and analysis of source code)

本篇文章是要使针对HMM初学者，该文主要介绍了HMM原理(This article is to make for beginners HMM, the article mainly introduces the principle of HMM)

熵值越大则每个符号包含的平均信息量越大。有研究发现，在有噪声的语音信号中，语音信号的熵和噪声信号的熵存在着较大的差异，对噪声信号来说在整个频带内分布相对平坦，熵值小，语音信号集中在某些特定频段内，熵值大。因此利用这个差异可以区分噪音段和语音段。(The greater the entropy is, the greater the average information of each symbol is. It is found that, in noisy speech signals, the entropy of speech signals and the entropy of noise signals are quite different. For noisy signals, the distribution is relatively flat in the whole frequency band, and the entropy value is small. The speech signal is concentrated in some specific frequency bands, and the entropy value is large. So the difference can be used to distinguish the noise segment and the speech segment.)