CLEAN_MFCC_STD

语音AEC的demo程序和库源代码，在win7下验证可行。(audio aec demo in windows7.)

HMM语音识别,包含主要算法,进行语音识别(HMM speech recognition, contains the main algorithm for speech recognition)

这是语音信号处理中求倒谱的程序,我自己编的,很简单,实现了一段序列求倒谱的功能(This is the voice signal processing for cepstrum procedures, I developed, is very simple. achieve a sequence for the functional cepstrum)

模式识别k聚类算法源代码，c语言内容描述。(Pattern Recognition Chapter )

将wav格式文件转化为txt格式的程序,用于读入语音文件转换TXT格式，便于程序分析(Wav format files into txt format program)

语音识别，实现语音的识别功能，，特定人的语音识别。识别0~9的发音(Speech recognition, voice recognition function, a particular person' s speech recognition. Identify the pronunciation of 0 to 9)

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.)

实现声源定位功能，利用两个麦克风的语音数据获得原始声源的位置!(Achieve sound localization function, using two microphones for voice access to the original source data location!)

自制DMX512控制台,很不错的一个软件,他对灯光的控制,非常出色.(Homemade DMX512 console, a very good one software, he lighting control, very good.)

这是自己毕业设计做的PCA和LDA的结合，训练和识别别过程都有，用的是ORL库里的图像，具有较高的识别率！ (This is a combination of PCA and LDA graduation design, training and do the process of the identification with ORL library of images, has a high recognition rate!)