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Vocabulary gaussian clustering model using AELMS filter

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dc.contributor.authorLee, J.-S.-
dc.contributor.authorOh, S.-Y.-
dc.date.available2020-02-29T01:41:45Z-
dc.date.created2020-02-12-
dc.date.issued2013-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/14946-
dc.description.abstractWith the AELMS filter, which can preserve sources features of speech and decrease the damage on speech information, noise of a contaminated speech signal got canceled, and a gaussian model was clustered as a method to make noise more robust. By composing a gaussian clustering model, which is a robust speech recognition clustering model, in a noise environment, a recognition performance was evaluated. The study shows that SNR of speech, which was gained by canceling the environment noise which was kept changing, was enhanced by 2.7dB in an average and a recognition rate was improved by 3.1%. © 2013 IEEE.-
dc.language영어-
dc.language.isoen-
dc.relation.isPartOf2013 International Conference on Information Science and Applications, ICISA 2013-
dc.subjectAELMS Filter-
dc.subjectClustering model-
dc.subjectGaussian model-
dc.subjectGaussians-
dc.subjectNoise environments-
dc.subjectRobust speech recognition-
dc.subjectSpeech information-
dc.subjectSpeech signals-
dc.subjectCluster analysis-
dc.subjectGaussian distribution-
dc.subjectInformation science-
dc.subjectSpeech recognition-
dc.subjectSignal to noise ratio-
dc.titleVocabulary gaussian clustering model using AELMS filter-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.doi10.1109/ICISA.2013.6579392-
dc.identifier.bibliographicCitation2013 International Conference on Information Science and Applications, ICISA 2013-
dc.identifier.scopusid2-s2.0-84883768467-
dc.citation.title2013 International Conference on Information Science and Applications, ICISA 2013-
dc.contributor.affiliatedAuthorOh, S.-Y.-
dc.type.docTypeConference Paper-
dc.subject.keywordAuthorAELMS Filter-
dc.subject.keywordAuthorGaussian model-
dc.subject.keywordPlusAELMS Filter-
dc.subject.keywordPlusClustering model-
dc.subject.keywordPlusGaussian model-
dc.subject.keywordPlusGaussians-
dc.subject.keywordPlusNoise environments-
dc.subject.keywordPlusRobust speech recognition-
dc.subject.keywordPlusSpeech information-
dc.subject.keywordPlusSpeech signals-
dc.subject.keywordPlusCluster analysis-
dc.subject.keywordPlusGaussian distribution-
dc.subject.keywordPlusInformation science-
dc.subject.keywordPlusSpeech recognition-
dc.subject.keywordPlusSignal to noise ratio-
dc.description.journalRegisteredClassscopus-
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