pujian

这是一个语音处理工具箱，提供了语音处理的基本函数，包括有分帧、能量计算、零交叉计算、多种方法的音调提取、共振峰提取。。。等等。(This is a speech processing toolbox provides the basic function of voice processing, including one of those who frame, energy calculation, zero cross-terms, various methods of pitch extraction, formant extraction. . . And so on.)

基于谱减法的语音降噪处理，里面有声音文件，可以直接运行观察效果(Based on the spectral subtraction speech denoising processing, there are sound files, can be run directly observed effect)

基于语音信号工具箱的隐马尔科夫HMM模型的说话人识别，请联系lishicheng64@126.com(Speech signal based on HMM toolbox Hidden Markov Model speaker recognition, please contact lishicheng64@126.com)

语音信号处理课件：语音基础知识、短时时域分析、频域分析、倒谱域分析、线性预测技术、语音增强、语音识别(Speech signal processing courseware: basic knowledge of speech, short-term time domain analysis, frequency domain analysis, cepstrum domain analysis, linear prediction technology, speech enhancement, speech recognition)

function [Coefficients,residual,pitch,Gain,parcorCoefficients,stream,B,crossmat,error_stream] = lpcanalysis(speechtodecode,samplerate,L,windowtime,preemp)

P.863标准（POLQA）,语音质量的客观评测标准，是对P.862标准（PESQ）的升级，适应范围更广，评价结果更接近主观的MOS。(P.863 Standards (POLQA), objective voice quality uation standard is the standard P.862 (PESQ) upgrade, adapt a wider range of uation results closer to the subjective MOS.)

说话人识别系统,界面友好，可以对实时录音的说话人进行识别(Speaker recognition system, user-friendly, real-time recording can be carried out to identify the speaker)

extract features by MFCC method using Matlab language

熵值越大则每个符号包含的平均信息量越大。有研究发现，在有噪声的语音信号中，语音信号的熵和噪声信号的熵存在着较大的差异，对噪声信号来说在整个频带内分布相对平坦，熵值小，语音信号集中在某些特定频段内，熵值大。因此利用这个差异可以区分噪音段和语音段。(The greater the entropy is, the greater the average information of each symbol is. It is found that, in noisy speech signals, the entropy of speech signals and the entropy of noise signals are quite different. For noisy signals, the distribution is relatively flat in the whole frequency band, and the entropy value is small. The speech signal is concentrated in some specific frequency bands, and the entropy value is large. So the difference can be used to distinguish the noise segment and the speech segment.)

c++语言开发，用于LPCC特征参数提取的，在语言识别系统中应用广泛。(c language, LPCC Features for feature extraction, in language recognition system widely used.)