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JLDATA
- 摘 要：本论文主要研究了语音识别的基本原理,对语音识别系统的构成进行分析处理,其中包括预处理、特征参数提取、建立模块库、识别匹配几大部分。预处理又包括语音采样、预加重、加窗（汉明窗）、端点检测；特征提取的参数是梅尔频率倒谱系数MFCC。 该语音系统采用的是动态时间伸缩算法(DTW)，研究对象是特定人的语音识别，并在MATLAB平台上实现。为了进行后续研究，首先使用电脑中的录音系统录制了阿拉伯数字0—9的语音文件，并转化成 “.wav”格式的文件。-Abstract: This thesis
vad
- 在语音识别中来完成对语音信号的端点检测以便于减少冗余-In speech recognition to complete the speech signal endpoint detection in order to facilitate the reduction of redundancy
wavlet-pitch-dection
- 算法是在MATLAB环境下编译的，其实现的功能主要是采用小波包BARK域中子带方差法来实现端点检测，实验结果表明在高信噪比情况下效果显著-Algorithm is compiled in MATLAB environment, and its main function is implemented using wavelet packet BARK sub-band variance jurisdictions to implement endpoint detection, experime
duandian2
- matalab 编写，端点检测代码，用于语音识别方向，断电检测是一个经久不衰的课题，这个应该有用-Endpoint detection code
EndDetection
- 声纹识别,语音帧的端点检测 matlab代码-End Detection
offline-sEMG-recognition
- 提取人体手臂肌电信号，手势识别，包括肌电信号的预处理，端点检测，特征提取，特征降维，SVM分类识别-sEMG based hand movements recognition using SVM
vad
- 改程序的功能：在进行语音识别时，完成对采集到的语音信号进行端点检测-The app features: when making the speech recognition, complete the acquisition to the endpoint detection of speech signal
a3
- 语音信号的分析及前期的预处理，包括语音信号的一些特征；预处理包括前期的预滤波、小波降噪、预加重、加窗分帧、语音端点检测。-Speech signal analysis and pre processing, including some of the features of the speech signal preprocessing including pre filtering, wavelet noise reduction, pre emphasis, plus window fram
nnmfcc1
- 不消除静音段,即不通过端点检测,方便说话人识别之后调整语音流的特征显著图.- 37/5000 Bù xiāochú jìngyīn duàn, jí bù tōngguò duāndiǎn jiǎncè, fāngbiàn shuōhuà rén shìbié zhīhòu tiáozhěng yǔyīn liú de tèzhēng xiǎnzhù tú. Does not eliminate the silent section, that is, through the end
speech_usod
- 语音信号处理中的端点检测,用于清浊音的鉴别,必要过程-Endpoint detection of speech signal processing is used to clear in the identification of dullness, necessary process
pointfind
- matlab实现语音信号基于mel滤波器的端点检测，并应用于一个语音文件上。-Matlab to achieve voice signal based on mel filter endpoint detection, and applied to a voice file.
function
- 基于双门限语音端点检测程序,检测出每个字的端点，-double deadline
mfcc
- 本文根据孤立词语音识别系统的处理步骤，从语音信号的预处理开始，分别详细说明了每个过程，比如预加重、分帧加窗和端点检测。接着介绍了特征参数MFCC的原理与选取，最后介绍了DTW算法的特点-In this paper, based on the process steps of isolated words speech recognition technology, starting with the speech signal pre-processing, each process is
calculmthondetectionand
- 语音信号端点检测仿真,内容涉及短时能量及过零率的计算-Speech signal endpoint detection simulation, the content involves the short-time energy and zero crossing rate calculation
speech_matlab
- 这是一个语音识别的代码包，资料很全，是基于动态时间规划技术的，有0到9十个数字建立的模板库，也有这是个数字的测试模板库，可以实现这十个数字的孤立词识别，再matlab实现的功能，包括几个子函数，比如端点检测，模板距离计算，完全可以运行，可以用于语音领域的初学者学习-This is a voice recognition code package, the information is very full, is based on dynamic time planning technology,
1236925
- 基于DTW算法的孤立字识别系统,用Matlab编程实现语音信号的端点检测-Isolated word recognition system based on DTW algorithm and Matlab programming to realize voice signal endpoint detection
record
- 语音mfcc,用来录取人声，进行端点检测，分析人声的音量(Voice MFCC, used for voice retrieval, endpoint detection, analysis of voice volume)
train
- 基于BP网络和多特征的语音端点检测，提取自相关函数最大值和频带方差作为BP网络输入，输出判断是否为语音信号。(A Speech Endpoint Detection Algorithm Based on BP Neural Network and Multiple Features)
detectioh
- 基于DTW算法的孤立字识别系统,用Matlab编程实现语音信号的端点检测(Isolated word recognition system based on DTW algorithm and Matlab programming to realize voice signal endpoint detection)
heapenqueue
- 语音信号端点检测仿真,内容涉及短时能量及过零率的计算(Speech signal endpoint detection simulation, the content involves the short-time energy and zero crossing rate calculation)