An Interdisciplinary Approach to Human-Centered Machine Translation
Marine Carpuat, Omri Asscher, Kalika Bali, Luisa Bentivogli, Frédéric Blain, Lynne Bowker, Monojit Choudhury, Hal Daumé III, Kevin Duh, Ge Gao, Alvin Grissom II, Marzena Karpinska
摘要
Machine Translation (MT) tools are widely used today, often in contexts where professional translators are not present. Despite progress in MT technology, a gap persists between system development and real-world usage, particularly for non-expert users who may struggle to assess translation reliability. This paper advocates for a human-centered approach to MT, emphasizing the alignment of system design with diverse communicative goals and contexts of use. We survey the literature in Translation Studies and Human-Computer Interaction to recontextualize MT evaluation and design to address the diverse real-world scenarios in which MT is used today.
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引用它的顶会 Paper2
- Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine TranslationDayeon Ki, Kevin Duh, Marine CarpuatEMNLP 2025
- Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect TranslationsYimin Xiao, Yongle Zhang, Dayeon Ki, Calvin Bao 等EMNLP 2025
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