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Korean speech recognition based on grapheme

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dc.contributor.authorLee, Mun-hak-
dc.contributor.authorChang, Joon Hyuk-
dc.date.accessioned2021-08-02T10:54:02Z-
dc.date.available2021-08-02T10:54:02Z-
dc.date.created2021-05-12-
dc.date.issued2019-09-
dc.identifier.issn1225-4428-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/12577-
dc.description.abstractThis paper is a study on speech recognition in the Korean using grapheme unit (Cho-sumg [onset], Jung-sung [nucleus], Jong-sung [coda]). Here we make ASR (Automatic speech recognition) system without G2P (Grapheme to Phoneme) process and show that Deep learning based ASR systems can learn Korean pronunciation rules without G2P process. The proposed model is shown to reduce the word error rate in the presence of sufficient training data.-
dc.language한국어-
dc.language.isoko-
dc.publisherACOUSTICAL SOC KOREA-
dc.titleKorean speech recognition based on grapheme-
dc.title.alternative문자소 기반의 한국어 음성인식-
dc.typeArticle-
dc.contributor.affiliatedAuthorChang, Joon Hyuk-
dc.identifier.doi10.7776/ASK.2019.38.5.601-
dc.identifier.scopusid2-s2.0-85079173367-
dc.identifier.wosid000489148400014-
dc.identifier.bibliographicCitationJOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA, v.38, no.5, pp.601 - 606-
dc.relation.isPartOfJOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA-
dc.citation.titleJOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA-
dc.citation.volume38-
dc.citation.number5-
dc.citation.startPage601-
dc.citation.endPage606-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.identifier.kciidART002509824-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscopus-
dc.description.journalRegisteredClasskci-
dc.relation.journalResearchAreaAcoustics-
dc.relation.journalWebOfScienceCategoryAcoustics-
dc.subject.keywordAuthorAutomatic speech recognition-
dc.subject.keywordAuthorDeep learning-
dc.subject.keywordAuthorLexicon-
dc.subject.keywordAuthorKaldi-
dc.identifier.urlhttp://koreascience.or.kr/article/JAKO201929565689470.page-
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