2025
EMNLP
EMNLP 2025
An Interdisciplinary Approach to Human-Centered Machine Translation
Abstract
AbstractMachine 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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Mega-Team
- 20 authors
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Interdisciplinary Bridge
- Artificial Intelligence and Interdisciplinary and Natural Language Processing
Authors
Marine Carpuat,
Omri Asscher,
Kalika Bali,
Luisa Bentivogli,
Frédéric Blain,
Lynne Bowker,
Monojit Choudhury,
Hal Daume 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 Popović,
Michel Simard,
François Yvon