Considerations for meaningful sign language machine translation based on glosses

Mathias Müller; Zifan Jiang; Amit Moryossef; Annette Rios; Sarah Ebling

doi:10.18653/v1/2023.acl-short.60

Considerations for meaningful sign language machine translation based on glosses

Mathias Müller, Zifan Jiang, Amit Moryossef, Annette Rios, Sarah Ebling

Department of Computer Science

University of Zurich

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

19 Scopus citations

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.

Original language	English
Title of host publication	Short Papers
Publisher	Association for Computational Linguistics (ACL)
Pages	682-693
Number of pages	12
ISBN (Electronic)	9781959429715
DOIs	https://doi.org/10.18653/v1/2023.acl-short.60
State	Published - 2023
Event	61st Annual Meeting of the Association for Computational Linguistics, ACL 2023 - Toronto, Canada Duration: 9 Jul 2023 → 14 Jul 2023

Publication series

Name	Proceedings of the Annual Meeting of the Association for Computational Linguistics
Volume	2
ISSN (Print)	0736-587X

Conference

Conference	61st Annual Meeting of the Association for Computational Linguistics, ACL 2023
Country/Territory	Canada
City	Toronto
Period	9/07/23 → 14/07/23

Bibliographical note

Publisher Copyright:
© 2023 Association for Computational Linguistics.

Funding

This work was funded by the EU Horizon 2020 project EASIER (grant agreement no. 101016982), the Swiss Innovation Agency (Innosuisse) flag-ship IICT (PFFS-21-47) and the EU Horizon 2020 project iEXTRACT (grant agreement no. 802774).

Funders	Funder number
Horizon 2020	101016982
Innosuisse - Schweizerische Agentur für Innovationsförderung	802774, PFFS-21-47

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10.18653/v1/2023.acl-short.60

Cite this

Müller, M., Jiang, Z., Moryossef, A., Rios, A., & Ebling, S. (2023). Considerations for meaningful sign language machine translation based on glosses. In Short Papers (pp. 682-693). (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Vol. 2). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.acl-short.60

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title = "Considerations for meaningful sign language machine translation based on glosses",

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.",

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Müller, M, Jiang, Z, Moryossef, A, Rios, A & Ebling, S 2023, Considerations for meaningful sign language machine translation based on glosses. in Short Papers. Proceedings of the Annual Meeting of the Association for Computational Linguistics, vol. 2, Association for Computational Linguistics (ACL), pp. 682-693, 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023, Toronto, Canada, 9/07/23. https://doi.org/10.18653/v1/2023.acl-short.60

Considerations for meaningful sign language machine translation based on glosses. / Müller, Mathias; Jiang, Zifan; Moryossef, Amit et al.
Short Papers. Association for Computational Linguistics (ACL), 2023. p. 682-693 (Proceedings of the Annual Meeting of the Association for Computational Linguistics; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Considerations for meaningful sign language machine translation based on glosses

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