Sign languages as source language for machine translation : historical overview and challenges
- Author
- Joni Dambre (UGent) and Mathieu De Coster (UGent)
- Organization
- Project
- Abstract
- Sign language machine translation (SLMT) is machine translation (MT) in which at least the source or the target language is a sign language, but the combination of both is also possible. In general, today’s approaches to SLMT heavily build on traditional (i.e., text-to-text) MT systems and focus on solutions to adapt those to having a sign language at the input side or at the output side. Both cases lead to very different challenges and technological solutions, and this chapter focuses only on having a sign language as the source language. It covers the differences between written and sign languages that must be taken into account, the historical evolutions we have seen in the field and the way they have been impacted by the amount and quality of the available data.
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01JCN7EY0HQ2T7MPAXVFA1A3WH
- MLA
- Dambre, Joni, and Mathieu De Coster. “Sign Languages as Source Language for Machine Translation : Historical Overview and Challenges.” Sign Language Machine Translation, edited by Andy Way et al., vol. 5, Springer, 2024, pp. 171–98, doi:10.1007/978-3-031-47362-3_7.
- APA
- Dambre, J., & De Coster, M. (2024). Sign languages as source language for machine translation : historical overview and challenges. In A. Way, L. Leeson, & D. Shterionov (Eds.), Sign language machine translation (Vol. 5, pp. 171–198). https://doi.org/10.1007/978-3-031-47362-3_7
- Chicago author-date
- Dambre, Joni, and Mathieu De Coster. 2024. “Sign Languages as Source Language for Machine Translation : Historical Overview and Challenges.” In Sign Language Machine Translation, edited by Andy Way, Lorraine Leeson, and Dimitar Shterionov, 5:171–98. Cham: Springer. https://doi.org/10.1007/978-3-031-47362-3_7.
- Chicago author-date (all authors)
- Dambre, Joni, and Mathieu De Coster. 2024. “Sign Languages as Source Language for Machine Translation : Historical Overview and Challenges.” In Sign Language Machine Translation, ed by. Andy Way, Lorraine Leeson, and Dimitar Shterionov, 5:171–198. Cham: Springer. doi:10.1007/978-3-031-47362-3_7.
- Vancouver
- 1.Dambre J, De Coster M. Sign languages as source language for machine translation : historical overview and challenges. In: Way A, Leeson L, Shterionov D, editors. Sign language machine translation. Cham: Springer; 2024. p. 171–98.
- IEEE
- [1]J. Dambre and M. De Coster, “Sign languages as source language for machine translation : historical overview and challenges,” in Sign language machine translation, vol. 5, A. Way, L. Leeson, and D. Shterionov, Eds. Cham: Springer, 2024, pp. 171–198.
@incollection{01JCN7EY0HQ2T7MPAXVFA1A3WH,
abstract = {{Sign language machine translation (SLMT) is machine translation (MT) in which at least the source or the target language is a sign language, but the combination of both is also possible. In general, today’s approaches to SLMT heavily build on traditional (i.e., text-to-text) MT systems and focus on solutions to adapt those to having a sign language at the input side or at the output side. Both cases lead to very different challenges and technological solutions, and this chapter focuses only on having a sign language as the source language. It covers the differences between written and sign languages that must be taken into account, the historical evolutions we have seen in the field and the way they have been impacted by the amount and quality of the available data.}},
author = {{Dambre, Joni and De Coster, Mathieu}},
booktitle = {{Sign language machine translation}},
editor = {{Way, Andy and Leeson, Lorraine and Shterionov, Dimitar}},
isbn = {{9783031473616}},
issn = {{2522-8021}},
language = {{eng}},
pages = {{171--198}},
publisher = {{Springer}},
series = {{Machine translation : technologies and applications}},
title = {{Sign languages as source language for machine translation : historical overview and challenges}},
url = {{http://doi.org/10.1007/978-3-031-47362-3_7}},
volume = {{5}},
year = {{2024}},
}
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