Linguistics and Languages

Performance and perception: machine translation post-editing in Chinese-English news translation by novice translators

Y. Yang, R. Liu, et al.

Discover how machine translation can support novice translators in news translation, as explored by Yanxia Yang, Runze Liu, Xingmin Qian, and Jiayue Ni. This study reveals the strengths and weaknesses of MT, particularly in handling cultural nuances and structural coherence, while highlighting its appeal and potential in translator training programs.

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Playback language: English

Index

Abstract

This study investigates the effectiveness of machine translation (MT) in assisting novice translators in news translation. A Chinese-English news translation test compared the performance and perceptions of learners using MT post-editing versus manual translation. Findings showed MT struggled with cultural and semantic nuances, and coherent structural translation. While no significant quality difference existed between post-editing and manual translation (post-editing showed slightly better quality), MT reduced processing time and mental workload. Learners preferred MT post-editing for news translation, suggesting its potential integration into translator training programs.

Publisher

Humanities and Social Sciences Communications

Published On

Nov 09, 2023

Authors

Yanxia Yang, Runze Liu, Xingmin Qian, Jiayue Ni

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