voice

matlab编写的muCVSD语音编码解码器，参数可调，十分方便(matlab prepared muCVSD speech codec parameter adjustable, very convenient)

一个盲信号分离的卷积方法，适合分离实际卷积混合的模型，希望对初学者有帮助。(Convolution of a blind signal separation method, suitable for separation of the real convolution mixture model, want to help beginners.)

用于语音信号，心音信号基于SVM的MATLAB识别(Recognition of Speech Signal and Heart Sound Signal Based on SVM)

文中研究了6种常用数字调制信号识别的特征参数集，并采用决策树判别方法进行分类识别。仿真结果表明，在SNR≥5dB时，识别正确率在99 以上，且当SNR≥20dB时，识别正确率达到100 。其特点是，算法简单，识别正确率高，达到了自动分类识别的目的，并有利于实现识别的实时化。(In this paper, we study the set of characteristic parameters of the six kinds of commonly used digital modulation signal recognition, and decision tree method for classification. The simulation results show that SNR 鈮� 5dB, the correct rate more than 99 , and when SNR 鈮� 20dB, the correct rate of 100 . Which is characterized by simple algorithm to identify the correct rate, to achieve the purpose of automatic classification and recognition, and help to identify real-time.)

使用TD-PSOLA（td-psola、psola）算法，做了一个语音合成，实现语音声调的变调，时长的变化等功能。参考praat源码，提取出其合成方法，效果不错。需要提供pitchtier、durationtier、pointprocess等准换信息文本（可由praat产生）供readfile函数读入(Use TD-PSOLA (TD-PSOLA, PSOLA algorithm, made a speech synthesis, speech tone tone sandhi, long-term changes in the function. Reference Praat source code, extract its synthetic method, the effect of the same.)

一款语音和成软件,主要是文本转语音，包括英文、普通话等(text change to speak)

采用矢量量化对语音信号量化，并与标量量化对比分析，绘制了语音信号的概率密度曲线(The use of vector quantization for speech signal quantization and scalar quantization and comparative analysis, rendering the speech signal probability density curve)

C语音实现Matlab corrcoef（求两个信号的互相关系数），包括了Matlab的对比验证源代码(Calculate the correlation coefficient refer the Matlab function:corrcoef)

图像识别，可以识别出图片中的需要的水果。mtalab实现的。(Image recognition, the image can be identified in fruit required. mtalab achieved.)

声纹识别和语音识别，语音识别的模块使用的讯飞云。声纹识别的代码则是参考了Dake前辈的代码。在此提出感谢。(Voiceprint recognition and speech recognition, voice recognition module for use hearing Fei. Voiceprint identification code is a reference to the Dake predecessors code. Presented in this thanks.)