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rebuilt.HumanTimbre_recognition-master

于 2018-03-31 发布 文件大小:18577KB
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  利用mfcc特性进行语音识别，分类算法为svm。(Speech recognition using MFCC characteristics)

文件列表：

HumanTimbre_recognition-master, 0 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法, 0 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\mfcc.m, 1341 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\sa1.wav, 127020 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\sa1_segmentation.wav, 70046 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\vad.m, 2274 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox.zip, 536479 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox, 0 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\Contents.m, 11244 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\activlev.m, 11650 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\atan2sc.m, 1739 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\bark2frq.m, 4341 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\bitsprec.m, 3218 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\cblabel.m, 2409 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\ccwarpf.m, 1954 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\cep2pow.m, 2080 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\choosenk.m, 2176 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\choosrnk.m, 1577 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\correlogram.m, 3852 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\distchar.m, 3747 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\distchpf.m, 3361 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\disteusq.m, 3599 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\distisar.m, 4565 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\distispf.m, 3671 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\distitar.m, 4100 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\distitpf.m, 3538 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\ditherq.m, 1930 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\dlyapsq.m, 2668 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\dualdiag.m, 2433 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\dypsa.m, 25603 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\enframe.m, 2821 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\entropy.m, 3812 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\erb2frq.m, 2667 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\estnoisem.m, 15221 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\ewgrpdel.m, 2401 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\figbolden.m, 3652 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\filtbankm.m, 14347 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\filterbank.m, 3417 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\findpeaks.m, 4121 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\finishat.m, 2763 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\flac.exe, 262144 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\fopenmkd.m, 2200 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\frac2bin.m, 2424 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\fram2wav.m, 5135 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\frq2bark.m, 5718 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\frq2erb.m, 2615 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\frq2mel.m, 2470 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\frq2midi.m, 2035 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\fxpefac.m, 15898 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\fxrapt.m, 16559 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\gammabank.m, 9251 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\gausprod.m, 6512 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\gaussmix.m, 22370 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\gaussmixd.m, 6530 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\gaussmixp.m, 8062 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\glotlf.m, 3255 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\glotros.m, 1841 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\gmmlpdf.m, 4569 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\histndim.m, 4537 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\huffman.m, 2406 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\imagehomog.m, 5279 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\importsii.m, 3788 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\irdct.m, 2403 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\irfft.m, 3241 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\kmeanhar.m, 7825 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\kmeanlbg.m, 1834 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\kmeans.m, 5356 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\ldatrace.m, 3224 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lin2pcma.m, 2138 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lin2pcmu.m, 2028 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lognmpdf.m, 2034 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\logsum.m, 1848 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcaa2ao.m, 1245 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcaa2dl.m, 1416 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcaa2rf.m, 1292 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcao2rf.m, 1233 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2am.m, 2724 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2cc.m, 1710 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2db.m, 1379 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2ff.m, 1284 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2fm.m, 2707 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2im.m, 1329 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2ls.m, 1958 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2pf.m, 1410 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2pp.m, 1728 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2ra.m, 1315 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2rf.m, 1640 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2rr.m, 1787 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcar2zz.m, 1275 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcauto.m, 4223 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcbwexp.m, 1461 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpccc2ar.m, 1485 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpccc2cc.m, 1293 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpccc2db.m, 1704 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpccc2pf.m, 1623 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcconv.m, 4265 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpccovar.m, 4952 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpccw2zz.m, 1314 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcdb2pf.m, 1232 , 2016-06-27
HumanTimbre_recognition-master\MFCC算法\voicebox\lpcdl2aa.m, 1299 , 2016-06-27

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  • 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
  • 60368809
    memcached资源demo(已调试通过)(Memcached Resource demo (Debug passed))
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  • PSDownload
    评书,语音小说下载程序,修改一下可批量下载(Storytelling, voice novels download, modify available for bulk download)
    2013-08-23 11:51:27下载
    积分：1
  • sfs310s1
    SFS提供了计算语音本质的一系列工具。包括支持各种数据格式，信号处理和图形，频谱、共振峰分析，基频提取等等。在线文档说明请访问http://www.phon.ucl.ac.uk/resource/sfs/help/(SFS provides a voice calculated nature of a series of tools. Including support for various data formats, signal processing and graphics, spectrum, formant analysis, frequency, etc. extraction. Online document shows, please visit http :// www.phon.ucl.ac.uk/resource/sfs/help/)
    2007-04-03 14:54:52下载
    积分：1
  • hmm
    hmm文件时运用HMM算法实现噪声环境下语音识别的。其中vad.m是端点检测程序；mfcc.m是计算MFCC参数的程序；pdf.m函数是计算给定观察向量对该高斯概率密度函数的输出概率；mixture.m是计算观察向量对于某个HMM状态的输出概率，也就是观察向量对该状态的若干高斯混合元的输出概率的线性组合；getparam.m函数是计算前向概率、后向概率、标定系数等参数；viterbi.m是实现Viterbi算法；baum.m是实现Baum-Welch算法；inithmm.m是初始化参数；train.m是训练程序；main.m是训练程序的脚本文件；recog.m是识别程序。(hmm HMM algorithm file using speech recognition in noisy environments. Which is the endpoint detection process vad.m mfcc.m procedure is to calculate the MFCC parameters pdf.m function is calculated for a given observation vector of the Gaussian probability density function of output probability mixture.m is to calculate the observation vector for a HMM state output probability of observation vector is the number of Gaussian mixture per state output probability of the linear combination getparam.m before the calculation of the probability function, backward probability, calibration coefficients and other parameters viterbi.m is Viterbi algorithm implementation baum.m Baum-Welch algorithm to achieve inithmm.m is the initialization parameters train.m is the training program main.m training program is a script file recog.m is to identify procedures.)
    2010-09-16 20:51:49下载
    积分：1
  • fixedbeam
    经典麦克风语音增强算法，当阵元数目越多，语音增强效果越好(Classical microphone speech enhancement algorithm, the more the number of elements, the better the speech enhancement effect)
    2018-07-22 19:31:17下载
    积分：1
  • rever
    1.进行含噪语音信号的时频分析 2.设计合适滤波器进行去噪 3.进行去噪后信号的时频分析4.设计一个混响器（用四个梳状滤波器和两个全通滤波器（下图所示））来产生回声（通过一个均衡器(Reverberation)
    2009-06-25 15:51:32下载
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  • ZXG
    一个对有噪声的音频信号进行自相关滤波的c程序，用的turbo c 3.0工具(One pair of noisy audio signal autocorrelation filtering c program using turbo c 3.0 Tools)
    2021-03-01 22:29:34下载
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  • process_params
    parameter参数提取程序，matlab实现(parameter process in matlab)
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    code for voice analysis final code for sapeech recognition
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