Earticle

초록

영어

As the artificial intelligence (AI) plays a crucial role in machine translation (MT) which has loomed large as a new translation paradigm, concerns have also arisen if MT can produce a quality product as human translation (HT) can. In fact, several MT experimental studies report cases in which the MT product called post-editing (PE) as equally as HT or often superior ([1],[2],[6]). As motivated from those studies on translation quality between HT and PE, this study set up an experimental situation in which Korean literature was translated into English, comparatively, by 3 translators and 3 post-editors. Afterwards, a group of 3 other Koreans checked for accuracy of HT and PE; a group of 3 English native speakers scored for fluency of HT and PE. The findings are (1) HT took the translation time, at least, twice longer than PE. (2) Both HT and PE produced similar error types, and Mistranslation and Omission were the major errors for accuracy and Grammar for fluency. (3) HT turned to be inferior to PE for both accuracy and fluency.

목차

Abstract
1. Introduction
2. Related works
3. Present research
3.1 Research questions
3.2 Content profiles and adjustments
3.3 Translator (HT) and post-editor (PE) profiles
3.4 MT platform: VisualTran of EverTran Co., Ltd.
3.5 Translation processes
3.6 Evaluation criteria
3.7 Evaluator profiles for accuracy and fluency
4. Results
4.1 Accuracy comparison
4.2 Fluency comparison
5. Summary
Acknowledgement
References

키워드

저자

• IL-JAE LEE [ Department of English Language and Literature, Kwangwoon University, Translation Industry Research Center of Korea, Kwangwoon University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Advanced Culture Technology(IJACT)

• 간기

  계간

• pISSN

  2288-7202

• eISSN

  2288-7318

• 수록기간

  2013~2025

• 등재여부

  KCI 등재

• 십진분류

  KDC 600 DDC 700