对比三种机器翻译系统与两类校对员在专业翻译中的表现
Machine Translation and Post-Editing: Comparative Evaluation of Different MT Systems and Post-Editor Groups in Specialised Translation
- 用误差分类法评估DeepL、eTranslation、Systran三套系统
- 语言学家组在术语准确性和流畅性上优于NLP专家
- 凸显领域知识对专业翻译的关键作用
本文旨在评估英语到法语的专业化翻译中机器翻译（MT）与后编辑（PE）的质量。比较了三种MT系统（DeepL、eTranslation和Systran），并让两组后编辑人员——语言学家/译者与NLP专家——进行后编辑。翻译质量评估基于适配于MT与PE评估的误差分类法。结果显示，三套系统及两组后编辑人员在术语准确性与流畅性方面存在显著差异。本研究强调了专业化翻译中领域知识的重要性，以及机器翻译系统在特定用途语言（LSP）中的局限性与表现波动。
原文摘要 · Abstract (English)
This article aims to evaluate the quality of machine translation (MT) and post-editing (PE) in the context of specialised translation from English into French. Three MT systems (DeepL, eTranslation and Systran) were compared, and two groups of post-editors -linguists/translators and NLP experts -were asked to perform post-editing. Translation assessment is based on error annotation using an error typology adapted to MT and PE evaluation. The results reveal significant differences between the three MT systems and the two groups of post-editors, particularly in terms of terminological accuracy and fluency. This study highlights the importance of domain knowledge in specialised translation, as well as the limitations and variable performance of MT systems in language for specific purposes (LSP).
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