한-영 신문사설 번역에서 나타나는 인간번역과 기계번역 간의 어휘 사용 차이 연구

Abstract

This study aims to identify stylistic differences between human and machine translation in terms of word usage. For this purpose, a comparable corpus was constructed, which consisted of English translations of 110 Korean newspaper editorials done by a group of human translators and three online machine translation services (Google, Bing and Papago) respectively. Principal component analysis was performed on the corpus to investigate differences in the way 200 most frequent terms are related to the human and machine translators. Additionally, part-of-speech analyses were carried out to further elucidate the differences found in the PCA analysis. The major findings are that machine translators tend to overuse ‘be’ verbs and ‘as’ and ‘if’ subjunctive connectives, while underusing third-person personal pronouns, particularly the female form, ‘she’. Additionally, they were found to rely heavily on high-frequency content words. These characteristics of machine translators are construed as stemming from their scope of lexical options being limited by structural correspondence to original Korean texts.