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Plausibility and Well-formedness Acceptability Test on Deep Neural Nativeness Classification

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dc.contributor.authorSanghoun Song-
dc.date.accessioned2021-08-27T10:36:46Z-
dc.date.available2021-08-27T10:36:46Z-
dc.date.created2021-04-22-
dc.date.issued2020-10-24-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/5062-
dc.publisherVNU University of Science-
dc.titlePlausibility and Well-formedness Acceptability Test on Deep Neural Nativeness Classification-
dc.title.alternativePlausibility and Well-formedness Acceptability Test on Deep Neural Nativeness Classification-
dc.typeConference-
dc.contributor.affiliatedAuthorSanghoun Song-
dc.identifier.bibliographicCitationThe 34th Pacific Asia Conference on Language, Information and Computation (PACLIC 34)-
dc.relation.isPartOfThe 34th Pacific Asia Conference on Language, Information and Computation (PACLIC 34)-
dc.relation.isPartOfProceedings of PACLIC 34-
dc.citation.titleThe 34th Pacific Asia Conference on Language, Information and Computation (PACLIC 34)-
dc.citation.conferencePlaceVN-
dc.citation.conferencePlace코로나 사태로 인해 온라인 전환-
dc.citation.conferenceDate2020-10-24-
dc.type.rimsCONF-
dc.description.journalClass1-
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