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논문 기본 정보

자료유형
학술저널
저자정보
Zhuqing Wang (이화여자대학교) 이승아 (이화여자대학교)
저널정보
한국언어정보학회 언어와 정보 언어와 정보 제22권 제1호
발행연도
2018.2
수록면
175 - 201 (27page)
DOI
http://dx.doi.org/10.29403/LI.22.1.8

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Zhuqing Wang and Seung-Ah Lee. 2018. Machine Translation versus Human Translation: The Case of English-to-Chinese Translation of Relative Clauses. Language and Information 22.1, 175-201. This paper compares translations done by professional human translators (as manifested in the Babel English-Chinese Parallel Corpus) and machine translation sproduced by Google Translate (with English as the source language and Simplified Chinese as the target language). Capitalizing on the branching direction of these two languages, we investigated translation strategies of restrictive relative clauses by focusing on which-relatives. The specific objectives of the study were to (a) extract relevant data from a parallel corpus; (b) assess machine translation quality; and (c) highlight the similarities and dissimilarities between corpus outputs and machine translation outputs. Of the 147 test materials, 115 Google Translate outputs (78.2%) were rated as ‘successful’ or ‘acceptable’. No significant differences were found between the degree of success in machine translations and linguistic factors (e.g., the active or passive voice in relativeclauses). This finding confirms that linguistic knowledge is not required when using statistical machine translation (SMT) such as Google Translate. Another noteworthy finding was that Google Translate did not use the least frequently occurring translation strategy in the parallel corpus. This is not surprising given that SMT systems greatly rely on parallel corpora for training statistical translation models.

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