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speaker1PGMM

于 2012-04-24 发布 文件大小:55KB
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  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.)

文件列表:

speaker1 GMM
............\enframe.m,2068,2008-06-17
............\gausspdf.m,1084,2008-12-19
............\gmmparam.mat,64040,2009-06-04
............\gttestdt2.m,637,2009-06-04
............\main2.m,1684,2009-06-04
............\melbankm.m,2474,2008-12-19
............\mfcc0.m,3080,2009-05-19
............\readwav.m,8577,2006-11-18
............\speakerid2.m,1352,2009-06-04
............\speakertrain.m,767,2009-04-22

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    该文件为基于DTW的孤立词识别系统(特定人、小词汇量,未采用鲁棒语音识别技术)(The document DTW for isolated word recognition system based on (a specific person, small vocabulary, did not use robust speech recognition technology))
    2014-09-23 10:28:25下载
    积分:1
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    2020-10-26 20:29:59下载
    积分:1
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    最权威和最全面的语音识别的特征提取的 IEEE的期刊论文1980(The most authoritative and comprehensive speech recognition feature extraction of the IEEE Journal Papers 1980)
    2007-09-11 13:24:34下载
    积分:1
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    2014-02-18 19:26:21下载
    积分:1
  • 提取信号基频
    用自相关函数提取语音信号基频,提取音频文件的基频等高线(Use the autocorrelation function on segments of the signal (windowsize: 100ms) and compute the fundamental frequency. Use a max_time_lag of 100ms in the autocorrelation function and a window shift of 25ms. Create a fundamental frequency vector and plot the pitch contour.)
    2017-09-14 09:23:15下载
    积分:1
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    验证码识别简化源码程序,结合易语言位图操作支持库和应用接口支持库,实现验证码图像的识别简化。(Verification code identifying the source simplify procedures , combined with easy language bitmap operations support libraries and application interface support library that implements a simplified identification verification code image .)
    2016-04-09 17:48:20下载
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    2010-05-17 16:27:14下载
    积分:1
  • ABSE
    熵值越大则每个符号包含的平均信息量越大。有研究发现,在有噪声的语音信号中,语音信号的熵和噪声信号的熵存在着较大的差异,对噪声信号来说在整个频带内分布相对平坦,熵值小,语音信号集中在某些特定频段内,熵值大。因此利用这个差异可以区分噪音段和语音段。(The greater the entropy is, the greater the average information of each symbol is. It is found that, in noisy speech signals, the entropy of speech signals and the entropy of noise signals are quite different. For noisy signals, the distribution is relatively flat in the whole frequency band, and the entropy value is small. The speech signal is concentrated in some specific frequency bands, and the entropy value is large. So the difference can be used to distinguish the noise segment and the speech segment.)
    2020-11-02 21:29:54下载
    积分:1
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    2010-06-01 09:51:14下载
    积分:1
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