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        <title>FLEURS-ASL: Including American Sign Language in Massively Multilingual Multitask Evaluation</title>
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            <namePart type="given">Luis</namePart>
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    <abstract>Sign language translation has historically been peripheral to mainstream machine translation research. In order to help converge the fields, we introduce FLEURS-ASL, an extension of the multiway parallel benchmarks FLORES (for text) and FLEURS (for speech) to support their first sign language (as video), American Sign Language, translated by 5 Certified Deaf Interpreters. FLEURS-ASL can be used to evaluate a variety of tasks—primarily sentence- and discourse-level translation—between ASL and 200 other languages as text, or 102 languages as speech. We provide baselines for tasks from ASL to English text using a unified modeling approach that incorporates timestamp tokens and previous text tokens in a 34-second context window, trained on random video clips from YouTube-ASL. This model meets or exceeds the performance of phrase-level baselines while supporting a multitude of new tasks. We also use FLEURS-ASL to show that multimodal frontier models have virtually no understanding of ASL, underscoring the importance of including sign languages in standard evaluation suites.</abstract>
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%0 Conference Proceedings
%T FLEURS-ASL: Including American Sign Language in Massively Multilingual Multitask Evaluation
%A Tanzer, Garrett
%Y Chiruzzo, Luis
%Y Ritter, Alan
%Y Wang, Lu
%S Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
%D 2025
%8 April
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-189-6
%F tanzer-2025-fleurs
%X Sign language translation has historically been peripheral to mainstream machine translation research. In order to help converge the fields, we introduce FLEURS-ASL, an extension of the multiway parallel benchmarks FLORES (for text) and FLEURS (for speech) to support their first sign language (as video), American Sign Language, translated by 5 Certified Deaf Interpreters. FLEURS-ASL can be used to evaluate a variety of tasks—primarily sentence- and discourse-level translation—between ASL and 200 other languages as text, or 102 languages as speech. We provide baselines for tasks from ASL to English text using a unified modeling approach that incorporates timestamp tokens and previous text tokens in a 34-second context window, trained on random video clips from YouTube-ASL. This model meets or exceeds the performance of phrase-level baselines while supporting a multitude of new tasks. We also use FLEURS-ASL to show that multimodal frontier models have virtually no understanding of ASL, underscoring the importance of including sign languages in standard evaluation suites.
%R 10.18653/v1/2025.naacl-long.314
%U https://aclanthology.org/2025.naacl-long.314/
%U https://doi.org/10.18653/v1/2025.naacl-long.314
%P 6167-6191

Markdown (Informal)

[FLEURS-ASL: Including American Sign Language in Massively Multilingual Multitask Evaluation](https://aclanthology.org/2025.naacl-long.314/) (Tanzer, NAACL 2025)

• FLEURS-ASL: Including American Sign Language in Massively Multilingual Multitask Evaluation (Tanzer, NAACL 2025)

ACL

• Garrett Tanzer. 2025. FLEURS-ASL: Including American Sign Language in Massively Multilingual Multitask Evaluation. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), pages 6167–6191, Albuquerque, New Mexico. Association for Computational Linguistics.