无源文本时，利用上下文进行单语人工评估也能达到双语评估效果。
Context-Aware Monolingual Human Evaluation of Machine Translation
- 在无源文本情况下，基于上下文的单语评估可替代双语评估
- 四位专业译者验证了单语评估与双语评估结果相当
- 适合资源有限但需高效评估机器翻译质量的场景
本文探索在无源文本条件下，利用上下文信息的单语人工评估在机器翻译（MT）质量评估中的可行性。通过对比单语评估与带源文本的双语评估，在单一系统评估和成对系统比较两种场景下展开研究。四位专业译者分别完成单语与双语评估，包括打分、错误标注及体验反馈。结果显示，上下文感知的单语评估在效果上可与双语评估相媲美，表明该方法在效率与可靠性之间具有平衡潜力，为无源条件下的机器翻译评估提供了可行方案。
原文摘要 · Abstract (English)
This paper explores the potential of context-aware monolingual human evaluation for assessing machine translation (MT) when no source is given for reference. To this end, we compare monolingual with bilingual evaluations (with source text), under two scenarios: the evaluation of a single MT system, and the comparative evaluation of pairwise MT systems. Four professional translators performed both monolingual and bilingual evaluations by assigning ratings and annotating errors, and providing feedback on their experience. Our findings suggest that context-aware monolingual human evaluation achieves comparable outcomes to human bilingual evaluations, and suggest the feasibility and potential of monolingual evaluation as an efficient approach to assessing MT.
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