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语音自动识别技术，采用C++编程，可以给做语音识别的提供参考(Automatic speech recognition technology, using C++ programming, you can do to provide a reference for Speech Recognition)

MFCC：Mel频率倒谱系数的缩写。Mel频率是基于人耳听觉特性提出来的，它与Hz频率成非线性对应关系。Mel频率倒谱系数(MFCC)则是利用它们之间的这种关系，计算得到的Hz频谱特征。(Speech signal feature extraction)

关于蚁群聚类算法的matlab实现，对于初学者是很有帮助的呀～～ (On the ant colony clustering algorithm matlab realize, for beginners it is helpful ~ ~)

本实例程序是基于matlab的语音识别程序，通过提取传统的MFCC特征集，采用当前流行的SVM分类器，作为对比实验是一个不错的选择。(This example program is popular SVM classifier matlab speech recognition program to extract MFCC feature set, as a comparative experiment is a good choice. )

System Time Modifier ModifySysTimeItem

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.)

语音处理的实用代码，完成耳语音的声韵分割功能(Practical speech processing code, complete the ear speech sound segmentation function)

不错的盲源分离工具箱，实现对声源的分离,包含多个子程序(a nice toolbox of blind source separation used to separate multiple sources)

提供了segmantal SNR及IS的计算代码，用于语音增强后评价用。(Provided segmantal SNR and IS calculation code for speech enhancement with post-evaluation.)

基于DTW算法实现孤立数字及连续数字语句的识别，识别率还可以（内含语音数据集）(Based on DTW algorithm, isolated number and continuous number statements can be recognized, and the recognition rate can also be (including voice data set))