Considerations for meaningful sign language machine translation based on glosses

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 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 languageEnglish
Title of host publicationShort Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages682-693
Number of pages12
ISBN (Electronic)9781959429715
StatePublished - 2023
Event61st Annual Meeting of the Association for Computational Linguistics, ACL 2023 - Toronto, Canada
Duration: 9 Jul 202314 Jul 2023

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
Volume2
ISSN (Print)0736-587X

Conference

Conference61st Annual Meeting of the Association for Computational Linguistics, ACL 2023
Country/TerritoryCanada
CityToronto
Period9/07/2314/07/23

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).

FundersFunder number
Horizon 2020101016982
Innosuisse - Schweizerische Agentur für Innovationsförderung802774, PFFS-21-47

    Fingerprint

    Dive into the research topics of 'Considerations for meaningful sign language machine translation based on glosses'. Together they form a unique fingerprint.

    Cite this