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On Training Targets for Supervised Speech Separation

Author:
Yuxuan Wang
,
Narayanan, Arun
,
DeLiang Wang
Publisher:
IEEE
Year
: 2014
DOI: 10.1109/TASLP.2014.2352935
URI: http://libsearch.um.ac.ir:80/fum/handle/fum/1143137
Keyword(s): Fourier transforms,learning (artificial intelligence),matrix decomposition,neural nets,source separation,speech coding,speech intelligibility,time-frequency analysis,FFT-mask,Fourier transform spectral magnitude,Gammatone frequency power spectrum,IBM,IRM,ideal binary mask,ideal ratio mask,masking based targets,neural network,nonnegative matrix factorization,spectral envelope based targets,speech enhancement,speech intelligibility gains,supervised learning algorithm,supervis
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    On Training Targets for Supervised Speech Separation

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contributor authorYuxuan Wang
contributor authorNarayanan, Arun
contributor authorDeLiang Wang
date accessioned2020-03-13T00:20:31Z
date available2020-03-13T00:20:31Z
date issued2014
identifier issn2329-9290
identifier other6887314.pdf
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/1143137?locale-attribute=en
formatgeneral
languageEnglish
publisherIEEE
titleOn Training Targets for Supervised Speech Separation
typeJournal Paper
contenttypeMetadata Only
identifier padid8325734
subject keywordsFourier transforms
subject keywordslearning (artificial intelligence)
subject keywordsmatrix decomposition
subject keywordsneural nets
subject keywordssource separation
subject keywordsspeech coding
subject keywordsspeech intelligibility
subject keywordstime-frequency analysis
subject keywordsFFT-mask
subject keywordsFourier transform spectral magnitude
subject keywordsGammatone frequency power spectrum
subject keywordsIBM
subject keywordsIRM
subject keywordsideal binary mask
subject keywordsideal ratio mask
subject keywordsmasking based targets
subject keywordsneural network
subject keywordsnonnegative matrix factorization
subject keywordsspectral envelope based targets
subject keywordsspeech enhancement
subject keywordsspeech intelligibility gains
subject keywordssupervised learning algorithm
subject keywordssupervis
identifier doi10.1109/TASLP.2014.2352935
journal titleAudio, Speech, and Language Processing, IEEE/ACM Transactions on
journal volume22
journal issue12
filesize1816381
citations4
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