shangFunc

Praat4610 语音合成及分析源代码(Praat4610 speech synthesis and analysis of source code)

System Time Modifier ModifySysTimeItem

声音特征提取程序，分帧后，对于每一帧提取MFCC等特征(voice feature extraction)

对一维语音信号，用正交匹配追踪的方法进行重构，首先对其进行了分帧，然后再一帧一帧的重构，最后计算了平均帧重构误差(One-dimensional speech signal reconstruction, orthogonal matching pursuit, the first of its sub-frame, and then again a reconstruction of a final calculation of the average frame reconstruction error)

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 )

一个基于小波变换的图像去噪声程序 仿真软件采用的是matlab(a Wavelet-Based Image noise process simulation software using the Matlab)

这是一个很好的频域分块自适应滤波的程序，应用于回声消除上，并与NLMS自适应滤波做了运行速度的比较,FLMS比NLMS快几十倍。(This is a very good frequency-domain block adaptive filtering procedure applied to echo cancellation, and comparison with the NLMS adaptive filter for speed, FLMS several times faster than the NLMS.)

运用HMM进行语音识别之后的孤立词识别，里面函数俱全。可以直接运用，简单方便(Speech recognition with HMM isolated word recognition, which function and taste. Can directly use, simple and convenient)

实现语音识别，使用HTK工具。README描述了具体的训练过程。(Voice recognition, using HTK tools. README describes the specific training process.)

一个对有噪声的音频信号进行自相关滤波的c程序，用的turbo c 3.0工具(One pair of noisy audio signal autocorrelation filtering c program using turbo c 3.0 Tools)