An Interdisciplinary Approach to Human-Centered Machine Translation
Computation and Language
2025-06-17 v1 Artificial Intelligence
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.
Cite
@article{arxiv.2506.13468,
title = {An Interdisciplinary Approach to Human-Centered Machine Translation},
author = {Marine Carpuat and Omri Asscher and Kalika Bali and Luisa Bentivogli and Frédéric Blain and Lynne Bowker and Monojit Choudhury and Hal Daumé and Kevin Duh and Ge Gao and Alvin Grissom and Marzena Karpinska and Elaine C. Khoong and William D. Lewis and André F. T. Martins and Mary Nurminen and Douglas W. Oard and Maja Popovic and Michel Simard and François Yvon},
journal= {arXiv preprint arXiv:2506.13468},
year = {2025}
}
Comments
20 pages