HHT

对基于残留噪声去除的谱减法的编程，实现了高去噪水平(The program of spectral subtraction based on residual noise removal has achieved high denoising level.)

语音识别,有GUI界面，实现0~9数字语音识别(speaker identification)

VAD去噪算法，可以有效的过滤静音和无效的语音，同时消除了一些背景噪声。(VAD denoising algorithm, can effectively filter invalid mute and voice, while eliminating some background noise.)

这是基于隐马尔可夫模型的连续语音识别代码，不同于dtw,这是个完整的工程，我把需要的voicebox也放进去了，一共用到9个子函数，包括模板的训练算法何识别算法，是完全可以使用的。(This is based on the hidden Markov model of continuous voice recognition code, different the dtw, which is a complete project, I need to put the voicebox into a total of nine sub-functions, including the template training algorithm to identify the algorithm, Is fully available.)

ARMA模型建立程序，给出自相关序列，指定ARMA模型的P阶，Q阶参数，得出相应的参数值 function [bq ,ap]=armahat(rx,p,q)(ARMA model for the establishment of procedures, to come from related sequences, designated the P-order ARMA model, Q-order parameters, the corresponding parameter values derived function [bq, ap] = armahat (rx, p, q))

文字转语音C#源码，利用windows speech.lib 实现文本转语音 可设置rate 保存为wav文件格式。(Text to voice C# source code, using windows speech. lib to achieve text to voice can be set rate saved as WAV file format.)

语音识别中的两种特征提取方法lpcc和mfcc，还有一个是文本无关的识别算法dtw，另外还有一个是预处理消噪部分的。共享一下，这些都是我调试过的，好用。(Speech Recognition two feature extraction methods and mfcc lpcc. There is a text-independent recognition algorithm dtw, in addition to a pretreatment is part of the noise source. Sharing that those are off the debugging and ease of use.)

很好的一本关于语音信号处理的书，而且是中文版的，比较好用(A good book on speech signal processing, and is the Chinese version, more useful)

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.)

语音唤醒就是在设备待机状态下，用户说出特定的语音指令（唤醒词）使设备进入工作状态或完成某一操作。设备为了实现语音唤醒功能，就需要设备实时监听，也就是实时的录音并分析有没有唤醒词来唤醒设备。评价一个语音唤醒系统的标准有三个：唤醒正确率、误报率、功耗。一般情况下，唤醒正确率越高 ，误报率也越高。好的系统就需要唤醒率高，误报率低，功耗低。(Speech wakeup is when the device is in standby mode, the user speaks a particular voice command (wake up word), so that the device enters the work state or completes an operation. In order to realize the function of speech wakeup, the device needs real-time monitoring, that is, real-time recording and analyzing whether or not wake words are used to wake up the equipment. There are three criteria for evaluating a voice wakeup system: wakeup accuracy, false positive rate, and power consumption. Generally, the higher the correct rate of arousal, the higher the false positive rate. A good system requires high wake-up rate, low false positive rate and low power consumption.)