yycl

利用DTW模版匹配算法实现0~9十个数字的识别。(use DTW template matching algorithm 0-9 10-digit identification.)

实现语音的分割和识别，语音分割通过短时能量和过零率，语音识别通过dtw算法。(audio cut and reconige)

lpc提取共振峰和基频，适合初学语音的同学使用，增强认识(lpc formant extraction and baseband, suitable for beginners to use the voice of the students, and enhance understanding)

psola算法的设计与实现，经过调试已经可以运行(psola Algorithm Design and Implementation, after debugging has to run)

C# 对接 Java 3des md5WithRsa, 有需要的可以参考下(If you need C # to dock Java 3des md5WithRsa, you can refer to the following)

C#版语音识别系统，精准度超强，到得收藏(C# version of the speech recognition system, super accuracy to Favorites)

speech file to be analyzed Format : binary file 16 bit-samples 240 samples per frame (speech file to be analyzed Format : 16 bit binary file-samples of 240 samples per fram e)

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 )

对语音信号基频的提取对于语音信号的分析有一定作用(Basic frequency of speech Analysis )

绘制语音信号的 WVD 分布，对时频工具箱中的 tfrwv 及 tfrspwv 函数的使用进行了详细说明(The way of drawing speech signals WVD was shown in the m file, and corresponding functions tfrwv and tfrspwv were discussed thoroughly.)