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Comparison of Korean-Russian punctuation of Machine Translation and Human Translation and its practical implications
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- 발행기관
- 한국외국어대학교 통번역연구소 바로가기
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- 간행물
- 한국외국어대학교 통번역연구소 학술대회 바로가기
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- 통권
- 제18회 ITRI-GSIT 국제 학술대회 (2018.01)바로가기
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- 페이지
- pp.291-291
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A333521
원문정보
초록
- 영어
- Recently Neural Machine Translation(NMT) has greatly improved machine translation and raised the debate about expectations and limitations on the machine translation quality. Google Neural Machine Translation (GNMT) was first enabled for 8 languages: to and from English and French, German, Spanish, Portuguese, Chinese, Japanese, Korean and Turkish in 2016. In March 2017, three additional languages were enabled: Russian, Hindi and Vietnamese along with Thai for which support was added later(Wikipedia). This paper focuses on inadequate punctuation in the sentence unit of machine translation. This paper compares the punctuation translation in the Google Neural Network Translation Service from Korean to Russian with the punctuation translation strategy of human translation to identify the problems and causes of MT and to suggest a practical implication. Subject of analysis is the Internet Newspaper, translated from Korea to Russian. Parallel corpus of Korean-Russian Human Translation(HT) and Machine Translation(MT) was analyzed by UAM Corpus tool for quantitative and qualitative analysis of punctuation translation.
키워드
Machine Translation(MT) Human Translation(HT) punctuation translation comparison저자
간행물 정보
발행기관
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- 발행기관명
- 한국외국어대학교 통번역연구소 [Interpreting and Translation Research Institute, Hankuk University of Foreign Studies]
- 설립연도
- 1997
- 분야
- 인문학>통역번역학
간행물
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- 간행물명
- 한국외국어대학교 통번역연구소 학술대회
- 간기
- 반년간
- 수록기간
- 2016~2026
- 십진분류
- KDC 717 DDC 400
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