An Interdisciplinary Approach to Human-Centered Machine Translation
Document Type
Conference Proceeding
Role
Contributor
Publication
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Publisher
Association for Computational Linguistics
Standard Number
9798891763326
First Page
22859
Last Page
22879
Publication Date
11-2025
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.
Repository Citation
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, Elaine C. Khoong, William D. Lewis, André F. T. Martins, Mary Nurminen, Douglas W. Oard, Maja Popovic, Michel Simard, and François Yvon. 2025. An Interdisciplinary Approach to Human-Centered Machine Translation. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 22859–22879, Suzhou, China. Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.emnlp-main.1164