GMM-apply-for-text-to-speech

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 )

用matlab实现LPCC特征的提取的程序！(Using matlab realize LPCC feature extraction procedure!)

语音自动识别技术，采用C++编程，可以给做语音识别的提供参考(Automatic speech recognition technology, using C++ programming, you can do to provide a reference for Speech Recognition)

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.)

I:CSDN技术中心 进程管理器---一个SDK的例子(I : CSDN Technology Center process management-- for example an SDK)

语音信号处理中的所有基本的算法的代码 联合开发网 - pudn.com

mp3算法并讲解mp3编码(mp3 algorithm on the MP3 encoder and)

在平台上找到的滑动/移动DCTII算法，都是用不了的，尤其是用于LMS，根本不适用，查了国内外论文，遍了程序，供大家参考(In PUDN,most DCT programm are not fit to LMS adaptive filter. with several literatures, this programm is finished for LMS filter.)

用自相关函数提取语音信号基频，提取音频文件的基频等高线(Use the autocorrelation function on segments of the signal (windowsize: 100ms) and compute the fundamental frequency. Use a max_time_lag of 100ms in the autocorrelation function and a window shift of 25ms. Create a fundamental frequency vector and plot the pitch contour.)

语音信号分帧后，计算每帧信号的短时平均能量(After the speech signal is framed, the short-term average energy of each frame signal is calculated)