An Interdisciplinary Approach to Human-Centered Machine Translation
University of Maryland, College Park · Bar-Ilan University · Microsoft Research Labs · Fondazione Bruno Kessler · Tilburg University · Université Laval · Mohamed bin Zayed University of Artificial Intelligence · Johns Hopkins University · Haverford College · Microsoft · University of California, San Francisco · University of Washington · Instituto Superior Técnico and Unbabel · Tampere University · IU International University of Applied Sciences and Dublin City University · National Research Council Canada · ISIR, Sorbonne Université & CNRS
PDF 由论文原始站点提供，PaperCompass 不保存论文文件。DOI 10.18653/v1/2025.emnlp-main.1164 ↗
摘要
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.