WienerScalart

基于MFCC的GMM的说话人识别，是很好的语音处理程序(MFCC of the GMM based speaker recognition, speech processing is a very good program)

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)

ARMA模型建立程序，给出自相关序列，指定ARMA模型的P阶，Q阶参数，得出相应的参数值 function [bq ,ap]=armahat(rx,p,q)(ARMA model for the establishment of procedures, to come from related sequences, designated the P-order ARMA model, Q-order parameters, the corresponding parameter values derived function [bq, ap] = armahat (rx, p, q))

这是开源语音合成espeak的源代码，对研究TTS的同学很有帮助。(This source code is open source speech synthesizer espeak, helpful studies TTS classmates.)

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)

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 )

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.)

完整的基音识别程序,经过修改,测试正确。包含基音检测，DTW，LPCC，MFCC提取等(integrity of the pitch identification procedures, the result of the revision, the test correctly. Pitch Detection included, DTW, LPCC Features, MFCC extraction)

adaptive modulation cm in speech coding

语音信号的录音、读入、放音等：利用函数wavread对语音信号进行采样,记住采样频率和采样点数，给出以下语音的波形图（2.wav），wavread的用法参见mablab帮助文件。利用wavplay或soundview放音。也可以利用wavrecord自己录制一段语音，并进行以上操作(需要话筒)。 (Speech signal recording, reading, playback, etc.: the voice signal using the function wavread sampling, sampling frequency and sampling points to remember, given the following speech waveform (2.wav), wavread usage see mablab help file. Using wavplay or soundview playback. Can also record a voice using wavrecord own, and the above operation (requires microphone).)