source-localization

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.)

这是一个与语音识别与端点检测有关的文件,是用C++写的源程序,相信对大家有用(This is a speech recognition with the Endpoint Detection of the documents are written in C source files, it may be useful to think)

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.)

模式识别k聚类算法源代码，c语言内容描述。(Pattern Recognition Chapter )

ITU P.563 语音质量评价，能只送入失真信信号，而不需要参考信号，便能评价失真信号的MOS分 (ITU P.563 voice quality assessment can only be sent to the distortion of the letter signals without the need for a reference signal will be able to evaluate distortion signal MOS score)

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.)

c语言写的wav音频文件简单处理函数源码，包括wav_io处理，提取lpc系数、plar系数，可用于语音识别和合成中。可直接调用。(wav audio files simple c language handler source, including wav_io processing, extraction lpc coefficient plar coefficient, can be used for speech recognition and synthesis. Can be called directly. )

短时平均能量和平均幅度差函数进行基音检测的方法(Short-term average energy and average magnitude difference function pitch detection method)

应用LBG算法对语音信号进行矢量量化。本压缩包共有两个主文件，training.m对训练数据进行处理并得到四个初始码本，quantizing.m对待量化数据进行矢量量化。其余为自编功能函数。(application of voice signal VQ. The compressed into two main documents, training.m right training data to be processed and four of the initial code, quantizing.m treat quantitative data for vector quantization. The remainder self-function.)

提取语音信号的lpc参数并进行时间归整，需要将wav语音文件放在指定目录下‘e:yyzl’(voice signal from the lpc parameters and time consolidation, need to wav sound files on the specified directory 'e : yyzl')