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pyAudioAnalysis-master

于 2016-09-22 发布 文件大小:46465KB
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  实现语音的分割和识别，语音分割通过短时能量和过零率，语音识别通过dtw算法。(audio cut and reconige)

文件列表：

pyAudioAnalysis-master
......................\.gitignore,21,2016-04-13
......................\analyzeMovieSound.py,6014,2016-04-13
......................\audioAnalysis.py,25270,2016-04-13
......................\audioAnalysisRecordAlsa.py,5114,2016-04-13
......................\audioBasicIO.py,3137,2016-04-13
......................\audioFeatureExtraction.py,31667,2016-04-13
......................\audioFeatureExtraction.pyc,25463,2016-05-11
......................\audioSegmentation.py,44252,2016-04-13
......................\audioTrainTest.py,33481,2016-04-13
......................\audioTrainTest.pyc,28703,2016-05-11
......................\audioVisualization.py,8136,2016-04-13
......................\data
......................\....\3WORDS.wav,841772,2016-04-13
......................\....\beat
......................\....\....\100 BPM - Rhythm patterns - Salsa.mp3,3894701,2016-04-13
......................\....\....\120 BPM Techno Drum Loop.mp3,6000798,2016-04-13
......................\....\....\170 BPM - Simple Straight Beat - Drum Track.mp3,5071674,2016-04-13
......................\....\....\200 BPM (goa psy trance).mp3,5278146,2016-04-13
......................\....\....\small.wav,319566,2016-04-13
......................\....\computational.sh,344,2016-04-13
......................\....\count.segments,326,2016-04-13
......................\....\count.wav,187854,2016-04-13
......................\....\count2.segments,320,2016-04-13
......................\....\count2.wav,337622,2016-04-13
......................\....\diarizationExample.pkf,83992,2016-05-12
......................\....\diarizationExample.segments,126,2016-04-13
......................\....\diarizationExample.wav,1343534,2016-04-13
......................\....\diarizationExample2.segments,108,2016-04-13
......................\....\diarizationExample2.wav,713670,2016-04-13
......................\....\diarizationResults.xls,138752,2016-04-13
......................\....\doremi.wav,256406,2016-04-13
......................\....\hmmRadioSM,2927,2016-04-13
......................\....\knn5Classes,59809,2016-04-13
......................\....\knnMovies8classes,1912893,2016-04-13
......................\....\knnMusicGenre3,185105,2016-04-13
......................\....\knnSM,944162,2016-04-13
......................\....\knnSM.arff,940345,2016-04-13
......................\....\knnSpeakerAll,194073,2016-04-13
......................\....\knnSpeakerFemaleMale,151673,2016-04-13
......................\....\matSegToCSV.m,364,2016-04-13
......................\....\matSegToCSV_dir.m,203,2016-04-13
......................\....\recording1.wav,1600044,2016-04-13
......................\....\recording2.wav,960044,2016-04-13
......................\....\recording3.wav,1600044,2016-04-13
......................\....\recordRadio.py,4693,2016-04-13
......................\....\scottish.segments,94,2016-04-13
......................\....\scottish.wav,7914284,2016-04-13
......................\....\similarities.html,4082,2016-04-13
......................\....\speechEmotion
......................\....\.............\00.wav,66846,2016-04-13
......................\....\.............\01.wav,46950,2016-04-13
......................\....\.............\02.wav,89124,2016-04-13
......................\....\.............\03.wav,76832,2016-04-13
......................\....\.............\04.wav,58646,2016-04-13
......................\....\.............\05.wav,122834,2016-04-13
......................\....\.............\06.wav,119644,2016-04-13
......................\....\.............\07.wav,72578,2016-04-13
......................\....\.............\08.wav,101346,2016-04-13
......................\....\.............\09.wav,125938,2016-04-13
......................\....\.............\10.wav,57344,2016-04-13
......................\....\.............\11.wav,48544,2016-04-13
......................\....\.............\12.wav,60242,2016-04-13
......................\....\.............\13.wav,78520,2016-04-13
......................\....\.............\14.wav,58474,2016-04-13
......................\....\.............\15.wav,54342,2016-04-13
......................\....\.............\16.wav,47448,2016-04-13
......................\....\.............\17.wav,48812,2016-04-13
......................\....\.............\18.wav,70820,2016-04-13
......................\....\.............\19.wav,60396,2016-04-13
......................\....\.............\20.wav,51352,2016-04-13
......................\....\.............\21.wav,49182,2016-04-13
......................\....\.............\22.wav,71190,2016-04-13
......................\....\.............\23.wav,49996,2016-04-13
......................\....\.............\24.wav,66646,2016-04-13
......................\....\.............\25.wav,189004,2016-04-13
......................\....\.............\26.wav,198938,2016-04-13
......................\....\.............\27.wav,175958,2016-04-13
......................\....\.............\28.wav,217260,2016-04-13
......................\....\.............\29.wav,171572,2016-04-13
......................\....\.............\30.wav,97654,2016-04-13
......................\....\.............\31.wav,94250,2016-04-13
......................\....\.............\32.wav,64970,2016-04-13
......................\....\.............\33.wav,50048,2016-04-13
......................\....\.............\34.wav,95876,2016-04-13
......................\....\.............\35.wav,130148,2016-04-13
......................\....\.............\36.wav,66674,2016-04-13
......................\....\.............\37.wav,65866,2016-04-13
......................\....\.............\38.wav,63730,2016-04-13
......................\....\.............\39.wav,48938,2016-04-13
......................\....\.............\40.wav,112102,2016-04-13
......................\....\.............\41.wav,113118,2016-04-13
......................\....\.............\42.wav,113436,2016-04-13
......................\....\.............\43.wav,115640,2016-04-13
......................\....\.............\44.wav,115758,2016-04-13
......................\....\.............\45.wav,117082,2016-04-13
......................\....\.............\46.wav,122598,2016-04-13
......................\....\.............\47.wav,123740,2016-04-13
......................\....\.............\48.wav,125690,2016-04-13
......................\....\.............\49.wav,125834,2016-04-13

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  • ACFandAMDFpitch
    短时自相关和短时平均幅度差计算基音周期的matlab程序，附带有原语音信号(Short-term autocorrelation and short-term average deviation of pitch period matlab program, comes with the original speech signal)
    2013-08-13 09:02:28下载
    积分：1
  • pyAudioAnalysis-master
    实现语音的分割和识别，语音分割通过短时能量和过零率，语音识别通过dtw算法。(audio cut and reconige)
    2016-09-22 17:40:26下载
    积分：1
  • 功能是在语音中提取基音频率的程序pitch
    matlab程序，功能是在语音中提取基音频率的程序。输入为.wav格式的语音文件，输出各帧基音频率。(matlab procedures, functions in the voice pitch frequency extraction procedure. Input. Wav format audio files, the output of the frame pitch.)
    2020-11-29 22:49:28下载
    积分：1
  • AudioPlayer
    这是语音播放接口组件，将语音数据输入，会播放声音。经过测试确保可用。(This is the voice player interface module, the voice data input, will play the sound. After testing to ensure that the.)
    2016-11-11 16:57:53下载
    积分：1
  • tibaoluo
    基于倒谱短时部分反映了语音的声道特性，先用汉明窗取一帧语音，然后经变换得到语音倒谱，将倒谱短时部分取出，进行正交反变换后将得到声道的对数谱，即得到语音频谱的包络。将频谱包络和频谱画在一张图上，有很好的对比效果。获取的包络效果十分好。(Based Cepstral partly reflects the short channel characteristics of the speech, first take a Hamming window with a frame of speech, and speech cepstrum obtained by converting the cepstrum short segment out inverse orthogonal transform to obtain channel will of the spectrum, i.e. to obtain the envelope of the speech spectrum. The spectral envelope and spectral painted on a chart, there is a good contrast. Get the envelope effect is very good.)
    2013-11-01 14:13:17下载
    积分：1
  • VQ ASR
    基于VQ的说话人识别系统，在MATLAB环境下实现基于矢量量化的说话人识别系统。在实时录音的情况下，利用该说话人识别系统，对不同的人的1s～7s的语音进行辨识。实现与文本无关的自动说话人确认的实时识别。(speaker recognition system based on vector quantization)
    2019-06-07 12:44:37下载
    积分：1
  • Abdul_Syafiq_Abdull_Sukor
    the document explains speech recognition using mel frequency cpstrum coeefficient and noise reduction method
    2012-11-21 04:35:09下载
    积分：1
  • speech-emotion-recognition-system
    gmm模型下的语音情感识别系统，GMM只是一个数学模型，只是对数据形态的拟和，但是和你所看到的数据分布存在出入也是正常的，因为用EM估计GMM的那些参数时，一般假设我们所得到的数据是不完备的（也就是说假设我们看到的数据分布不是真正的分布，它在运算时把那部分丢失或者叫隐藏的数据“补”上了）(gmm model speech emotion recognition system, GMM is a mathematical model, but fitting the data form, but you can see there is access to the data distribution is normal, because those with the EM estimated GMM parameters, the general assumption we get the data is incomplete (that is, assuming we see the distribution of the data distribution is not real, it is part of the operation at the time that is lost or hidden data is called " fill" on the))
    2011-04-27 09:02:20下载
    积分：1
  • main
    用于语音信号，心音信号基于SVM的MATLAB识别(Recognition of Speech Signal and Heart Sound Signal Based on SVM)
    2017-05-16 11:06:33下载
    积分：1
  • 传统谱减与MCRA语音增强算法
    传统语音增强算法，谱减法和MCRC算法，matlab源代码。(Traditional speech enhancement algorithm, spectral subtraction and MCRC algorithm, matlab source code.)
    2018-11-22 18:14:55下载
    积分：1
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