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EndPointDetectionDlg.rar
- 语音端点检测，VC+matlab混合编程，这个文件是包含语音端点检测的代码,用的是时频参数算法,Speech Endpoint Detection, VC+ Matlab mixed programming, this document is contained in voice activity detection of code, using a time-frequency parameters algorithm
detectendpoint1.rar
- 计算过零率，短时能量，调整能量门限，端点检测都是语音信号当中不可缺少的部分,Calculation of zero-crossing rate, short-term energy and adjust the energy threshold, endpoint detection of speech signals which are an integral part of
Endpoint-detection-of-speech-signal
- 语音信号的端点检测分析，有短时能量分析,短时过零率分析,和终点检测-Endpoint detection of speech signal, a short-term energy analysis, short-term rate of zero, and the end point detection
detection
- 基于倒谱，分形，和谱熵的语音端点检测程序，三个文件夹内对应三种程序-Cepstrum-based, fractal, and spectral entropy of speech endpoint detection procedures, the three folders corresponding to the three procedures
speech
- 语音参数短时能量，短时过零率，短时平均幅度，语音端点检测，fft变换与反变换-Voice parameters of short-time energy, short-time zero-crossing rate, short-term average rate, voice activity detection, fft transform and inverse transform
noisex
- 递归度信号处理.可用语语音信号处理,如端点检测,清浊音分割.-Recursive-degree signal processing. Can be language speech signal processing, such as endpoint detection, segmentation Voicing.
vad
- 几篇带噪声语音信号端点检测算法的论文，希望对大家有用-Speech signal with noise several endpoint detection algorithm for papers, in the hope that useful
spectral_speech_enhancement
- 在强噪声环境下，说话人话音受到很强烈的干扰，语音增强是很有必要的。在TDS5410-TDK实验板，实现了谱衰减算法。主要包括有声/无声检测算法、发送/接收缓冲区的调度、语音降噪算法。试验结果表明，其降噪效果明显，试听效果较好。 -In strong noise environment, the speaker voice by the very strong interference, speech enhancement is necessary. TDS5410-TDK experim
spsub
- provides basic spectral subtraction [SS] function for speech enhancement. basic envelope detection is also achieved for SS.
endpointdetection
- 语音检测的目的是在一串连续的记录信号中将重要的信息分离出来。在电信应用领域，语音检测是必需的。对于自动语音识别，端点检测在分离重要语音信息时是必需的，这样可以产生语音模式或语音模板。-Voice detection is aimed at a string of consecutive records of information important signal will be separated. At the field of telecommunications applications
mfccvaddtw
- 语音信号处理的最基本的Maylab处理程序，包括读入语音波形，清音浊音的检测，加窗，过零率，短时能量，基音最大值。最后有test给出演示-Speech Signal Processing Maylab the most basic treatment procedures, including read into the voice waveform, voiceless voiced detection, add windows, zero-crossing rate, short-term
DTWspeech
- 本 文 首先 介绍了语音识别的研究和发展状况，然后循着语音识别系统的 处理过程，介绍了语音识别的各个步骤，并对每个步骤可用的几种方法在实 验基础上进行了分析对比。研究了语音信号的预处理和特征参数提取，包括 语音信号的数字化、分帧加窗、预加重滤波、端点检测及时域特征向量和变 换域特征向量.其中端点检测采用双门限法.通过实验比对特征参数的选取， 采用12阶线性预测倒谱系数作为识别参数。详细分析了特定人孤立词识别算 法，选定动态时间弯折为识别算法，并重点介绍其设计实现。 在
newvq
- this a speech recognition code based on vector qunatisation wid end point detection.-this is a speech recognition code based on vector qunatisation wid end point detection.
gerven1997algo3
- Gerven, S. V. & Xie, F. "A Comparative Study of Speech Detection Methods" EUROSPEECH 97, 1997 , 1095-1098. -Gerven, S. V. & Xie, F. "A Comparative Study of Speech Detection Methods" EUROSPEECH 97, 1997 , 1095-1098.
audio processing
- 语音信号处理-对输入语音信号进行端点检测和基音轨迹的检测（利用acf、amdf和acf/amdf三种方法）。-Speech Signal Processing- the input voice signal trajectory endpoint detection and pitch detection (using acf, amdf and acf/amdf three methods).
F2_6764
- 端点检测是指用数字处理技术来找出语音信号中的各种段落（如音素、音节、词素、词等）的始点和终点的位置。语音段起止端点检测是语音分析、语音合成和语音识别中的一个必要环节。传统的端点检测方法是从wav文件中获取语音采样，将其分帧并计算短时能量和过零率参数，然后进行端点检测。这种工作方式被称为离线处理方法 ，无法实现语音信号的实时处理，对于语音信号分析具有一定的局限性。本文通过开发ActiveX控件，在MATLAB环境下将其嵌入到figure窗口中，以GUI程序的方式使用，实现语音信号端点检测的实时处
vad
- 语音端点检测，采用短时能量和过零率的双门限检测方法。-Endpoint of speech detection, using short-term energy and zero-crossing rate of two-threshold detection method
voiceenergy
- 语音识别，能量计算，过零率检测，发生点检测，用于音符切分-Speech recognition, energy calculation, zero-crossing rate detection, point detection occurs for note segmentation
beat
- 语音分析软件。主要是进行onset发现，以及beat计算。常用的语音切分工具-Voice analysis software. Mainly for onset detection, beat calculation. Commonly used in speech segmentation tool
dtw
- dtw文件是运用DTW算法实现安静环境下语音识别的。其中vad.m是端点检测程序；lpc.m是计算LPC参数的程序；lpc21lpcc.m是计算LPCC参数的程序；mfcc.m是计算MFCC参数的程序；dtw.m是实现经典DTW算法的程序；dtw2.m是实现高效DTW算法的程序，testdtw.m是最终测试程序，其中可以通过改变其中的特征参数名选择不同的特征参数。-dtw file DTW algorithm is to use speech recognition in quiet envir