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An Interdisciplinary Approach to Human-Centered Machine Translation

Carpuat, Marine
; 
Asscher, Omri
; 
Bali, Kalika
; 
Bentivogli, Luisa
; 
Blain, Fred
; 
Bowker, Lynne
; 
Choudhury, Monojit
; 
Iii, Hal Daumé
; 
Duh, Kevin
; 
Gao, Ge
... show 10 more
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Author
Carpuat, Marine
Asscher, Omri
Bali, Kalika
Bentivogli, Luisa
Blain, Fred
Bowker, Lynne
Choudhury, Monojit
Iii, Hal Daumé
Duh, Kevin
Gao, Ge
Grissom II, Alvin C
Karpinska, Marzena
Khoong, Elaine C
Lewis, William D
Martins, Andre
Nurminen, Mary
Oard, Douglas W
Popovic, Maja
Simard, Michel
Yvon, François
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Natural Language Processing
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Conference proceeding
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http://creativecommons.org/licenses/by/4.0/
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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.
Citation
M. Carpuat, O. Asscher, K. Bali, L. Bentivogli, F. Blain, L. Bowker , et al., "An Interdisciplinary Approach to Human-Centered Machine Translation," 2025, pp. 22870-22890.
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Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
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Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Publisher
Association for Computational Linguistics
DOI
10.18653/v1/2025.emnlp-main.1164
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https://aclanthology.org/2025.emnlp-main.1164/
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