LPC-FORMANT-PITCH

采用广义旁瓣抵消（GSC）自适应波束形成方法实现时域和频域滤波，采用LMS自适应算法，最终实现语音增强。（文件中包含纯净语音及不同信噪比的带噪语音）(Generalized sidelobe canceller (GSC) adaptive beamforming method to achieve time-domain filtering using the LMS adaptive algorithm, and ultimately the speech enhancement)

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.)

用NLMS实现对语音的回声的消除,共4个文件,语音原声,语音回声,NLMS的实现,回声路径(Using NLMS realize voice echo on the elimination of a total of four documents, voice, soundtrack, voice echo, NLMS realization echo path)

高斯混合模型参数初始化程序，在对高斯混合模型的建立之前采用KMEANS算法进行初始化(Gaussian mixture model parameter initialization procedure, in the Gaussian mixture model is initialized before the algorithm used KMEANS)

语音信号处理--降噪方法之小波分解法 MATLAB例程(Speech Signal Processing--A MATLAB Routine of Wavelet Decomposition Method for Noise Reduction)

数字语音处理及MATLAB仿真_张雪英编著第二版 源码(Digital audio processing and MATLAB simulation _ Zhang Xueying edited version second source code)

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.)

进行语音合成和分析，最基本的数据来源和可靠合成基础(Speech synthesis and analysis, basic data sources and reliable synthetic base)

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.)

C语言实现的端点检测,具有良好的效果,对于做语音识别者来说，是很好的参考(C language implementation of endpoint detection, with good results)