spectrelentropy

标准的10个数字和26个字母的男语音数据库，用于语音信号处理(10 numbers and 26 letters of the standard male voice database for speech signal processing)

男女变声器，语言信号处理，录音，matlab，各种滤波器，有预处理，自定义时长录音并保存，自主选择文件，自主制作界面(Male and female voice changer, speech signal processing, audio, MATLAB, various filters, pretreatment, long recording and save custom, choose file, independent production interface)

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.)

语音信号处理中的所有基本的算法的代码（C语言版）(Speech signal processing algorithms in all the basic code (C language version))

本文介绍MVDR算法实现及其改进 用于多麦克风语音增强(The minimum variance distortionless response (MVDR), originally developed by Capon for frequency-wavenumber analysis, is a very well established method in array process-ing. It is also used in spectral estimation. The aim of this paper is to show how the MVDR method can be used to es-timate the magnitude squared coherence (MSC) function, which is very useful in so many applications but so few methods exist to estimate it)

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)

c++语言开发，用于LPCC特征参数提取的，在语言识别系统中应用广泛。(c language, LPCC Features for feature extraction, in language recognition system widely used.)

这是基于HMM的数字语音识别，实现了0到9 的识别，并带有GUI界面，可以进行录音和播放，预处理，识别结果准确，并附有音频(This is a digital speech recognition based on HMM identification of 0-9, with a GUI interface and recording box player, there are pretreatment, accurate identification, together with audio)

基于非线性主分量分析(PAST)的 自适应盲信号分离 (Based on nonlinear principal component analysis (PAST) Adaptive Blind Signal Separation)

量子粒子群算法应用。对三个水听器的位置定位，在假设水听器位置已知情况下，以及其他方法估计得到的时延，通过量子粒子群算法计算，验证量子粒子群算法的计算精度。(Quantum particle swarm optimization application. Position location of the three hydrophones in the hydrophone position assumed known case, and other methods for estimating time delay obtained by calculating the quantum PSO QPSO verify the accuracy of the algorithm.)