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Considerations for meaningful sign language machine translation based on glosses

Müller, Mathias; Jiang, Zifan; Moryossef, Amit; Rios, Annette; Ebling, Sarah (2023). Considerations for meaningful sign language machine translation based on glosses. In: The 61st Conference of the the Association for Computational Linguistics, Toronto, Canada, 9 July 2023 - 14 July 2023. ACL Anthology, 682-693.

Abstract

Automatic sign language processing is gaining popularity in Natural Language Processing (NLP) research (Yin et al., 2021). In machine translation (MT) in particular, sign language translation based on glosses is a prominent approach. In this paper, we review recent works on neural gloss translation. We find that limitations of glosses in general and limitations of specific datasets are not discussed in a transparent manner and that there is no common standard for evaluation. To address these issues, we put forward concrete recommendations for future research on gloss translation. Our suggestions advocate awareness of the inherent limitations of gloss-based approaches, realistic datasets, stronger baselines and convincing evaluation.

Additional indexing

Item Type:Conference or Workshop Item (Paper), not_refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
06 Faculty of Arts > Zurich Center for Linguistics
08 Research Priority Programs > Digital Society Initiative
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Scopus Subject Areas:Physical Sciences > Computer Science Applications
Social Sciences & Humanities > Linguistics and Language
Social Sciences & Humanities > Language and Linguistics
Language:English
Event End Date:14 July 2023
Deposited On:30 Oct 2023 13:22
Last Modified:30 Mar 2024 04:46
Publisher:ACL Anthology
ISBN:978-1-959429-71-5
Additional Information:Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.18653/v1/2023.acl-short.60
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  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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