2023, Vol.24, No.1

The Journal of Translation Studies 2023 KCI Impact Factor : 1.49

pISSN : 1229-795X
https://journal.kci.go.kr/kats

This paper addresses the quality of Korean-English legal and patent translation outputs by a commercial neural machine translation engine customized for legal and patent translations. The current research is based on both automatic and human evaluations of Otran’s English translations of Korean statutes and Korean titles of invention and abstracts extracted from patent gazettes. In automatic evaluation, both BLEU and METEOR scores revealed that legal translation outperformed patent translation. Human evaluation results confirmed the automatic evaluation results, showing Otran’s legal translation receiving better evaluation than its patent translation. According to the error comments provided by evaluators, terminology and other errors, mostly stylistic issues, were the most prevalent error types in the legal translation, while terminology and syntax errors were the most frequent in the patent translation. In the legal translation, accuracy and fluency errors were far scarcer than in the patent translation. The results suggest that the domain-specific NMT engine needs improvement in handling terminology in both legal and patent translation, and its legal translation output proved to be good enough for gisting. The findings from this case study cannot be generalized and thus call for further research.

In the era of multilingual law making and law enforcement, legal translation conducted in institutions at national, international and supranational levels has been at the core of legal translation studies over the past decade. This study investigates the concept, scope and quality indicators of institutional legal translation with special attention on improving its quality in Korean settings. Based on the academic literature and the European Commission’s Translation Quality Guidelines, this study identifies three key quality indicators or parameters, i.e. accuracy, consistency and clarity, with prioritized, fit-for-purpose rules depending on the legal status, communicative purpose, recipient, and text type of the translation. In order to apply such indicators with necessary modifications to Korean institutions, this study presents the genre taxonomies of institutional legal translation in Korea and suggests key indicators and the priority of their application in the case of authentic and non-authentic translation produced by Korean institutions.

In recent years, machine translation post-editing has gained much popularity not only in translator training programs and courses but also in EFL classes. The majority of previous studies, however, largely focused on the impact of machine translation (MT) on L2 writing. Building upon the theories and practices of pedagogical application of MT, and by adopting the concept of translanguaging that legitimises learners’ deployment of full linguistic repertoire including L1, this study explores Korean EFL learners’ perceptions of MT and frequent errors in English-into-Korean post-editing. According to the results of a survey and students’ self-reports of their experience with MT, the use of MT in EFL learning was perceived by the learners as an innovative and positive learning experience. The learners highly appreciated the use of MT in their reading practice and post-editing by pointing out that the use of MT reduces stress and increases motivation to learn English. This study also reveals that post-editing practice can help learners understand deficiencies in free online MT output and raise their awareness of the linguistic structure and subtleties of language.