법률 특화 번역엔진 성능 평가 - 한영 계약서 번역을 중심으로 -

초록

This study aims to examine the possibility to enhance the performance of a machine translation engine in Korean-to-English legal translation. With the rise of neural machine translation, translation scholars quickly responded to investigate the output and limitations of machine translation. However, there has been little research to date on enhancing the quality of raw machine translation itself. As the legal field generates vast demand for machine translation post-editing, any improvement in machine translation engine performance can be of significant contribution. Hence, this paper will introduce an experimental machine translation engine trained with a bilingual legal corpus and verify whether it is possible to create a domain-specific engine that can outperform a freely available general purpose translation service. To that end, the output from the experimental engine and Google Translate will be compared and analyzed in terms of accuracy, fluency, usability, and essential changes. Last but not least, this paper will examine the potential contribution that translators can make and areas of collaboration between translation scholars and translation engine developers. (Hankuk University of Foreign Studies, Korea)

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