Abstract
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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CITATION STYLE
Carpuat, M., Asscher, O., Bali, K., Bentivogli, L., Blain, F., Bowker, L., … Yvon, F. (2025). An Interdisciplinary Approach to Human-Centered Machine Translation. In EMNLP 2025 - 2025 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (pp. 22859–22879). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2025.emnlp-main.1164
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