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Analyzing Quality Improvements in Legal Domain–Adaptive Machine Translation: A Case Study of Chinese–Korean Contract Translation.

  • T&I REVIEW
  • Abbr : tnirvw
  • 2025, 15(1), pp.89~108
  • DOI : 10.22962/tnirvw.2025.15.1.004
  • Publisher : Ewha Research Institute for Translation Studies
  • Research Area : Humanities > Interpretation and Translation Studies
  • Received : May 9, 2025
  • Accepted : June 16, 2025
  • Published : June 30, 2025

Seunghyuk Choi 1 Byeong Kwu Kang 2

1중앙대학교
2서강대학교

Accredited

ABSTRACT

Seunghyuk Choi and Byeongkwu Kang (2025). Analyzing Quality Improvements in Legal Domain–Adaptive Machine Translation: A Case Study of Chinese–Korean Contract Translation. This study evaluates domain-adaptive machine translation for legal texts by developing a “contract-adaptive machine translation model”(contract-adaptive model). Using a 53,334-character corpus of Chinese contracts, we fine-tuned a neural translation system and assessed outputs using two semantic-oriented automatic metrics: BERTScore and BLEURT. The evaluation results demonstrate that the contract-adaptive model consistently achieved higher scores across both metrics. In histograms visualizing BERTScore and BLEURT, the contract-adaptive model was concentrated in the high-score regions, and its median values were higher in the corresponding box plots. Analysis of actual translation examples showed that the contract-adaptive model delivered improved translation quality tailored to contractual usage - in terms of syntactic and semantic features. (Chung-Ang University, Sogang University, Korea)

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