Machine learning based english-to-Korean transliteration using grapheme and phoneme information

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dc.contributor.authorOh, JHko
dc.contributor.authorChoi, Key-Sunko
dc.date.accessioned2008-03-31T02:43:58Z-
dc.date.available2008-03-31T02:43:58Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2005-07-
dc.identifier.citationIEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E88D, no.7, pp.1737 - 1748-
dc.identifier.issn0916-8532-
dc.identifier.urihttp://hdl.handle.net/10203/3582-
dc.description.abstractMachine transliteration is an automatic method to generate characters or words in one alphabetical system for the corresponding characters in another alphabetical system. Machine transliteration can play an important role in natural language application such as information retrieval and machine translation, especially for handling proper nouns and technical terms. The previous works focus on either a grapheme-based or phoneme-based method. However, transliteration is an orthographical and phonetic converting process. Therefore, both grapheme and phoneme information should be considered in machine transliteration. In this paper, we propose a grapheme and phoneme-based transliteration model and compare it with previous grapheme-based and phoneme-based models using several machine learning techniques. Our method shows about 13 similar to 78% performance improvement.-
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherIEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG-
dc.subjectALGORITHM-
dc.titleMachine learning based english-to-Korean transliteration using grapheme and phoneme information-
dc.typeArticle-
dc.identifier.wosid000230702800055-
dc.identifier.scopusid2-s2.0-26044454624-
dc.type.rimsART-
dc.citation.volumeE88D-
dc.citation.issue7-
dc.citation.beginningpage1737-
dc.citation.endingpage1748-
dc.citation.publicationnameIEICE TRANSACTIONS ON INFORMATION AND SYSTEMS-
dc.identifier.doi10.1093/ietisy/e88-d.7.1737-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorChoi, Key-Sun-
dc.contributor.nonIdAuthorOh, JH-
dc.type.journalArticleArticle-
dc.subject.keywordAuthormachine transliteration-
dc.subject.keywordAuthormachine learning-
dc.subject.keywordAuthorinformation retrieval-
dc.subject.keywordAuthormachine translation-
dc.subject.keywordAuthornatural language processing-
dc.subject.keywordPlusALGORITHM-
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