Opportunities for Human-centered Evaluation of Machine Translation Systems
Daniel Liebling, Katherine Heller, Samantha Robertson, Wesley Deng
Abstract
Machine translation models are embedded in larger user-facing systems. Although model evaluation has matured, evaluation at the systems level is still lacking. We review literature from both the translation studies and HCI communities about who uses machine translation and for what purposes. We emphasize an important difference in evaluating machine translation models versus the physical and cultural systems in which they are embedded. We then propose opportunities for improved measurement of user-facing translation systems. We pay particular attention to the need for design and evaluation to aid engendering trust and enhancing user agency in future machine translation systems.
BibTeX
@inproceedings{liebling-etal-2022-opportunities,
title = "Opportunities for Human-centered Evaluation of Machine Translation Systems",
author = "Liebling, Daniel and
Heller, Katherine and
Robertson, Samantha and
Deng, Wesley",
editor = "Carpuat, Marine and
de Marneffe, Marie-Catherine and
Meza Ruiz, Ivan Vladimir",
booktitle = "Findings of the Association for Computational Linguistics: NAACL 2022",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.findings-naacl.17/",
doi = "10.18653/v1/2022.findings-naacl.17",
pages = "229--240"
}