PAST_disp_signal

语音增强电子书，国外经典教材，自适应滤波，卡尔曼滤波，最小均方算法等等(speech enhancement ebook)

声音特征提取程序，分帧后，对于每一帧提取MFCC等特征(voice feature extraction)

语音压缩感知，观测矩阵采用混沌序列，稀疏字典采用KSVD训练得到。(compressed sensing with chaotic sequence and K-SVD )

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.)

H-H微分方程的matlab原代码,内包含说明文档,对模拟神经元有帮助.(H-H Differential Equations Matlab original code, which includes documentation, simulated neurons to help.)

自己用matlab编的语音合成识别程序，验证好使。(Yourself using matlab speech synthesis recognition program, verify so.)

非常实用的java小实例，个人录音，实现了很简单的小功能，对于我们初学者很有帮助哦，拿来分享给大家。(Very practical examples of java small, personal recording, to achieve a very simple little feature, very helpful for us beginners Oh, bring to others.)

实现语音识别，使用HTK工具。README描述了具体的训练过程。(Voice recognition, using HTK tools. README describes the specific training process.)

说话人识别GMM模型训练MATLAB程序，需要和voicebox配合使用，使用voicebox提取MFCC和k均值分类，这是GMM说话人识别模型的训练程序。(Speaker Recognition GMM model training MATLAB program used in conjunction with and voicebox, voicebox extract MFCC and k-means classification, which is a GMM speaker recognition model training program.)

语音信号的时域频域分析，从短时能量到语谱图，以及线性预测参数和梅尔倒谱系数等等(Speech signal in time domain frequency domain analysis, from the short-term energy to the spectrogram, and the linear prediction parameters and the Mel cepstral coefficients, etc.)