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Jieun Lee and Hyoeun Choi (2022), A case study of Korean-English machine translation of dual subject sentences: A comparison of statutory translations by Google Translate and Naver Papago.

  • T&I REVIEW
  • Abbr : tnirvw
  • 2022, 12(1), pp.211-242
  • DOI : 10.22962/tnirvw.2022.12.1.010
  • Publisher : Ewha Research Institute for Translation Studies
  • Research Area : Humanities > Interpretation and Translation Studies
  • Received : April 20, 2022
  • Accepted : June 20, 2022
  • Published : June 30, 2022

Jieun Lee 1 Choi, Hyo-eun 1

1이화여자대학교

Accredited

ABSTRACT

This paper addresses the features of Korean-English machine translations by the Google Translate and Papago translation engines, focusing on the English translation of Korean dual subject sentences. The analysis of the English translations of Korean statutes consisting of 41 dual subject clauses reveals some similarities between human translation and machine translation. In human translations, either N1 or N2 of the source text served as the subject and N1 was often omitted in the English translation, whereas in machine translations, either N1 or N2 of the source text was translated into the subject and N1 was often omitted when N2 served as the subject in the English translation. However, machine translations differed from human translations in that machine translations unduly omitted N1 or N2 and the syntactic structure of machine translations was not as diverse as that of human translations. This study also suggests that machine translations produced by the two distinct engines were similar in terms of the usage of N1 and N2 in the English translation. Given that this paper is based on a small-scale pilot study, further research is needed to corroborate the findings drawing on diverse texts containing dual subject clauses. (Ewha Womans University, Korea)

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.