yuyinxinhaolianghua

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.)

matlab代码，语音的压缩和编码，主要利用了心理声学模型，得到低比特编码 和高质量语音(matlab code, voice compression and coding, psychoacoustic model used by low-bit encoding and high-quality voice)

是信号处理的基础，完整的基于HMM的语音识别系统，外文资料里面的源代码。( Is the basis of the signal processing, Complete HMM-based speech recognition system, Foreign materials inside the source code.)

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)

Edinburgh Speech Tools for speech synthesis

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.)

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)

实现对一个余弦信号的均匀量化和μ律非均匀量化，并将结果输出在图形界面上。(The uniform quantization and non uniform quantization of a cosine signal are realized and the results are output on the graphical interface.)

自己提取的讯飞输入法语音识别组件，可绿色运行，解压双击iFlyVoice.exe即可运行，语音识别能力比较强！(The voice recognition component extracted by Xunfei can be operated in green, decompressed and double-clicked iFlyVoice.exe can be operated, and the voice recognition ability is relatively strong!)

语音信号的特征提取，语音信号的Mel倒谱特征（MFCC）的求解方法，语音信号的线性预测原理以及LPC特征的求解方法 (Speech signal feature extraction, speech signal characteristics of Mel cepstrum (MFCC) the solution, voice signals, as well as the principle of linear prediction characteristics of the LPC method)