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        <title>Opportunities for Human-centered Evaluation of Machine Translation Systems</title>
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            <namePart type="family">Meza Ruiz</namePart>
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    <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.</abstract>
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%0 Conference Proceedings
%T Opportunities for Human-centered Evaluation of Machine Translation Systems
%A Liebling, Daniel
%A Heller, Katherine
%A Robertson, Samantha
%A Deng, Wesley
%Y Carpuat, Marine
%Y de Marneffe, Marie-Catherine
%Y Meza Ruiz, Ivan Vladimir
%S Findings of the Association for Computational Linguistics: NAACL 2022
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F liebling-etal-2022-opportunities
%X 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.
%R 10.18653/v1/2022.findings-naacl.17
%U https://aclanthology.org/2022.findings-naacl.17/
%U https://doi.org/10.18653/v1/2022.findings-naacl.17
%P 229-240

Markdown (Informal)

[Opportunities for Human-centered Evaluation of Machine Translation Systems](https://aclanthology.org/2022.findings-naacl.17/) (Liebling et al., Findings 2022)

• Opportunities for Human-centered Evaluation of Machine Translation Systems (Liebling et al., Findings 2022)

ACL

• Daniel Liebling, Katherine Heller, Samantha Robertson, and Wesley Deng. 2022. Opportunities for Human-centered Evaluation of Machine Translation Systems. In Findings of the Association for Computational Linguistics: NAACL 2022, pages 229–240, Seattle, United States. Association for Computational Linguistics.