Presentation 2003/8/22
Direct Machine Translation Using Linguistic Similarities
Kyonghee PAIK, Hiromi NAKAIWA, Satoshi SHIRAI,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Conventional approaches to machine translation require many linguistic resources either as transfer rules or parallel corpora. However, we are attempting to measure how little knowledge can be used for machine translation between similar languages, starting off with only a transfer dictionary and a target language corpus. The proposed method of machine translation exploits the linguistic similarities to achieve acceptable translation with low cost. We introduce Japanese to Korean machine translation as a case study.
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Keyword(in English) Japanese / Korean / machine translation / monolingual corpus / transfer lexicon
Paper # NLC2003-21
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Conference Information
Committee NLC
Conference Date 2003/8/22(1days)
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Paper Information
Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Direct Machine Translation Using Linguistic Similarities
Sub Title (in English)
Keyword(1) Japanese
Keyword(2) Korean
Keyword(3) machine translation
Keyword(4) monolingual corpus
Keyword(5) transfer lexicon
1st Author's Name Kyonghee PAIK
1st Author's Affiliation ATR Spoken Language Translation Laboratories()
2nd Author's Name Hiromi NAKAIWA
2nd Author's Affiliation ATR Spoken Language Translation Laboratories /
3rd Author's Name Satoshi SHIRAI
3rd Author's Affiliation
Date 2003/8/22
Paper # NLC2003-21
Volume (vol) vol.103
Number (no) 280
Page pp.pp.-
#Pages 6
Date of Issue