@inproceedings{xiao-etal-2025-toward,
title = "Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations",
author = "Xiao, Yimin and
Zhang, Yongle and
Ki, Dayeon and
Bao, Calvin and
Martindale, Marianna J. and
Vaughn, Charlotte and
Gao, Ge and
Carpuat, Marine",
editor = "Christodoulopoulos, Christos and
Chakraborty, Tanmoy and
Rose, Carolyn and
Peng, Violet",
booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2025",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.emnlp-main.1725/",
doi = "10.18653/v1/2025.emnlp-main.1725",
pages = "33997--34014",
ISBN = "979-8-89176-332-6",
abstract = "As Machine Translation (MT) becomes increasingly commonplace, understanding how the general public perceives and relies on imperfect MT is crucial for contextualizing MT research in real-world applications. We present a human study conducted in a public museum (n=452), investigating how fluency and adequacy errors impact bilingual and non-bilingual users' reliance on MT during casual use. Our findings reveal that non-bilingual users often over-rely on MT due to a lack of evaluation strategies and alternatives, while experiencing the impact of errors can prompt users to reassess future reliance. This highlights the need for MT evaluation and NLP explanation techniques to promote not only MT quality, but also MT literacy among its users."
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<abstract>As Machine Translation (MT) becomes increasingly commonplace, understanding how the general public perceives and relies on imperfect MT is crucial for contextualizing MT research in real-world applications. We present a human study conducted in a public museum (n=452), investigating how fluency and adequacy errors impact bilingual and non-bilingual users’ reliance on MT during casual use. Our findings reveal that non-bilingual users often over-rely on MT due to a lack of evaluation strategies and alternatives, while experiencing the impact of errors can prompt users to reassess future reliance. This highlights the need for MT evaluation and NLP explanation techniques to promote not only MT quality, but also MT literacy among its users.</abstract>
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%0 Conference Proceedings
%T Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations
%A Xiao, Yimin
%A Zhang, Yongle
%A Ki, Dayeon
%A Bao, Calvin
%A Martindale, Marianna J.
%A Vaughn, Charlotte
%A Gao, Ge
%A Carpuat, Marine
%Y Christodoulopoulos, Christos
%Y Chakraborty, Tanmoy
%Y Rose, Carolyn
%Y Peng, Violet
%S Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-332-6
%F xiao-etal-2025-toward
%X As Machine Translation (MT) becomes increasingly commonplace, understanding how the general public perceives and relies on imperfect MT is crucial for contextualizing MT research in real-world applications. We present a human study conducted in a public museum (n=452), investigating how fluency and adequacy errors impact bilingual and non-bilingual users’ reliance on MT during casual use. Our findings reveal that non-bilingual users often over-rely on MT due to a lack of evaluation strategies and alternatives, while experiencing the impact of errors can prompt users to reassess future reliance. This highlights the need for MT evaluation and NLP explanation techniques to promote not only MT quality, but also MT literacy among its users.
%R 10.18653/v1/2025.emnlp-main.1725
%U https://aclanthology.org/2025.emnlp-main.1725/
%U https://doi.org/10.18653/v1/2025.emnlp-main.1725
%P 33997-34014
Markdown (Informal)
[Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations](https://aclanthology.org/2025.emnlp-main.1725/) (Xiao et al., EMNLP 2025)
ACL
- Yimin Xiao, Yongle Zhang, Dayeon Ki, Calvin Bao, Marianna J. Martindale, Charlotte Vaughn, Ge Gao, and Marine Carpuat. 2025. Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, pages 33997–34014, Suzhou, China. Association for Computational Linguistics.