ACF

mfcc参数提取过程，具体内容可以参看参考(MFCC parameter extraction process)

凌阳SPCE06的语音通信代码,利用了双缓冲队列,是学习的好例子,希望很大家一起分享(Sunplus SPCE06 voice communications code, the use of the double-buffer queue, is a good example of learning, hope to share with everyone)

基于人脸和语音双通道的生物认证算法，已经通过编译，效果较好。(based on human face and voice of biological dual-channel authentication algorithms, compiler has been passed, the result is better.)

extract features by MFCC method using Matlab language

EVRC的语音编码算法研究及仿真,及二阶固定码本搜索算法(Speech Coding Algorithm and Simulation of EVRC)

一个可执行的HMM语音识别程序例程，实现了对10个数字音的识别程序，包含了HMM语音识别中的分段，MFCC特征提取，Baum-Welch训练，及Viterbi等算法，通过此例程可以很好的理解HMM的算法原理(An executable HMM-based 10 digits speech recogntion program example. this code zip file includes segmentation, MFCC feature extraction, Baum-Welch based re-estimation and Viterbi algorithm involved in HMM. it helps much better understand the HMM algorithm and its application for speech recogntion. )

一种加权K近邻语音情感识别程序，包括部分柏林语音情感库(A Weighting K-nearest neighbor speech emotion recognition program, including some libraries Berlin Speech Emotion)

台湾国立中央大学开发的EMD-HHT算法,其中,EMD-HHT的创始人为该中心的主任.(EMD-HHT IS SPECIALLY DESIGNED FOR PROCESSING NONSTATIONARY AND NONLINEAR SIGNALS. IT CAN DECOMPSE SIGNALS AND THEN RECONSTRUCT SIGNALS ACCORDING TO SOME CRITERIA. AFTER THE PROCESS, SIGNALS WOULD HAVE HIGH SIGNALTO NOISE RATIO. IT HAS BEEN APPLIED TO VARIOUS TYPES OF SINALS FROM INDUSTRY AND ACHIEVED GREAT SUCCESS. IT EVOLVES FROM THREE SOURCES: FRANCE SCIENTIST G RILLING, MATLAB FILE EXCHANGE CENTRE BY MR TAN AND TAIWAN NATIONAL CENTRAL UNIVERSITY CENTRE.)

memcached资源demo(已调试通过)(Memcached Resource demo (Debug passed))

语音合成程序源码！psalo频域基音同步叠加方法。它首先对原始语音信号进行短时频域变换，的到短时谱与短时谱包络。短时谱除以短时谱包络的到声源短时谱，对声源短时谱的实部与与虚部分别进行线性插值，就能达到改变变语音信号基频的目的，然后再进行频域反变换，可的到变换后的短时语音信号。短时谱包络部分也能独立改变，以达到改变音色的目的。 (Voice synthesis program source! psalo frequency domain pitch synchronous superposition method. It was first carried out on the original speech signal a short-time frequency-domain transform, to the short-time spectrum and short-time spectrum envelope. The short-time spectrum divided by the short-time spectrum envelope of the short time spectrum of the sound source, the short time spectrum of the real part of the sound source, and the imaginary parts of the linear interpolation, can achieve the purpose of changing the fundamental frequency of the alternating speech signal, and then then the inverse transform of the frequency domain, can be to the short-time speech signal after conversion. The short-time spectral envelope section can be varied independently, in order to achieve the purpose of changing the tone.)