Language Resources for European Sign Languages

Vincent Vandeghinste; Mirella De Sisto; Maria Kopf; Marc Schulder; Caro Brosens; Lien Soetemans; Rehana Omardeen; Frankie Picron; Davy Van Landuyt; Irene Murtagh; Elefterios Avramidis; Mathieu De Coster

doi:10.1007/978-3-031-47362-3_6

Language Resources for European Sign Languages

Vincent Vandeghinste, Mirella De Sisto, Maria Kopf, Marc Schulder, Caro Brosens, Lien Soetemans, Rehana Omardeen, Frankie Picron, Davy Van Landuyt, Irene Murtagh, Elefterios Avramidis, Mathieu De Coster

Cognitive Science and AI

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

41 Downloads (Pure)

Abstract

This chapter on Language resources for Europe’s Sign Languages is an adaptation of a deliverable that is part of a series of language deliverables developed within the framework of the European Language Equality (ELE) project. The series seeks to not only delineate the current state of affairs for each European language, but to additionally identify the gaps and factors that hinder further development in research and technology. The survey presented here focuses on the condition of Language Technology (LT) with regard to Europe’s sign languages, a set of languages often forgotten in the context of European language equality.

With the rise of the deep learning paradigm in artificial intelligence, sign language technologies become technologically feasible, provided that enough data is available to feed this data-hungry paradigm. It is exactly the quality and quantity of data that is the main bottleneck in development of well performing and useful technologies.

In the past, there have been several projects aimed at developing sign language technologies and methodologies that have been deemed of little value by the deaf communities. Co-creation and involvement of deaf communities throughout projects and development of technologies ensures that this does not happen again.

Original language	English
Title of host publication	Sign Language Machine Translation
Editors	Andy Way, Lorraine Leeson, Dimitar Shterionov
Publisher	Springer Cham
Chapter	6
Pages	141-170
Number of pages	30
Edition	1
ISBN (Electronic)	978-3-031-47362-3
ISBN (Print)	978-3-031-47364-7
DOIs	https://doi.org/10.1007/978-3-031-47362-3_6
Publication status	Published - 12 Nov 2024

Publication series

Name	Machine Translation: Technologies and Applications
Volume	5

Access to Document

10.1007/978-3-031-47362-3_6

language resources for european sign languagesFinal published version, 1.39 MB

Cite this

Vandeghinste, V., De Sisto, M., Kopf, M., Schulder, M., Brosens, C., Soetemans, L., Omardeen, R., Picron, F., Van Landuyt, D., Murtagh, I., Avramidis, E., & De Coster, M. (2024). Language Resources for European Sign Languages. In A. Way, L. Leeson, & D. Shterionov (Eds.), Sign Language Machine Translation (1 ed., pp. 141-170). (Machine Translation: Technologies and Applications; Vol. 5). Springer Cham. https://doi.org/10.1007/978-3-031-47362-3_6

@inbook{857f70f73d104c39bef88c07871aeca0,

title = "Language Resources for European Sign Languages",

abstract = "This chapter on Language resources for Europe{\textquoteright}s Sign Languages is an adaptation of a deliverable that is part of a series of language deliverables developed within the framework of the European Language Equality (ELE) project. The series seeks to not only delineate the current state of affairs for each European language, but to additionally identify the gaps and factors that hinder further development in research and technology. The survey presented here focuses on the condition of Language Technology (LT) with regard to Europe{\textquoteright}s sign languages, a set of languages often forgotten in the context of European language equality.With the rise of the deep learning paradigm in artificial intelligence, sign language technologies become technologically feasible, provided that enough data is available to feed this data-hungry paradigm. It is exactly the quality and quantity of data that is the main bottleneck in development of well performing and useful technologies.In the past, there have been several projects aimed at developing sign language technologies and methodologies that have been deemed of little value by the deaf communities. Co-creation and involvement of deaf communities throughout projects and development of technologies ensures that this does not happen again.",

author = "Vincent Vandeghinste and \{De Sisto\}, Mirella and Maria Kopf and Marc Schulder and Caro Brosens and Lien Soetemans and Rehana Omardeen and Frankie Picron and \{Van Landuyt\}, Davy and Irene Murtagh and Elefterios Avramidis and \{De Coster\}, Mathieu",

year = "2024",

month = nov,

day = "12",

doi = "10.1007/978-3-031-47362-3\_6",

language = "English",

isbn = "978-3-031-47364-7",

series = "Machine Translation: Technologies and Applications",

publisher = "Springer Cham",

pages = "141--170",

editor = "Andy Way and Leeson, \{Lorraine \} and Dimitar Shterionov",

booktitle = "Sign Language Machine Translation",

edition = "1",

}

Vandeghinste, V, De Sisto, M, Kopf, M, Schulder, M, Brosens, C, Soetemans, L, Omardeen, R, Picron, F, Van Landuyt, D, Murtagh, I, Avramidis, E & De Coster, M 2024, Language Resources for European Sign Languages. in A Way, L Leeson & D Shterionov (eds), Sign Language Machine Translation. 1 edn, Machine Translation: Technologies and Applications, vol. 5, Springer Cham, pp. 141-170. https://doi.org/10.1007/978-3-031-47362-3_6

Language Resources for European Sign Languages. / Vandeghinste, Vincent; De Sisto, Mirella; Kopf, Maria et al.
Sign Language Machine Translation. ed. / Andy Way; Lorraine Leeson; Dimitar Shterionov. 1. ed. Springer Cham, 2024. p. 141-170 (Machine Translation: Technologies and Applications; Vol. 5).

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

TY - CHAP

T1 - Language Resources for European Sign Languages

AU - Vandeghinste, Vincent

AU - De Sisto, Mirella

AU - Kopf, Maria

AU - Schulder, Marc

AU - Brosens, Caro

AU - Soetemans, Lien

AU - Omardeen, Rehana

AU - Picron, Frankie

AU - Van Landuyt, Davy

AU - Murtagh, Irene

AU - Avramidis, Elefterios

AU - De Coster, Mathieu

PY - 2024/11/12

Y1 - 2024/11/12

N2 - This chapter on Language resources for Europe’s Sign Languages is an adaptation of a deliverable that is part of a series of language deliverables developed within the framework of the European Language Equality (ELE) project. The series seeks to not only delineate the current state of affairs for each European language, but to additionally identify the gaps and factors that hinder further development in research and technology. The survey presented here focuses on the condition of Language Technology (LT) with regard to Europe’s sign languages, a set of languages often forgotten in the context of European language equality.With the rise of the deep learning paradigm in artificial intelligence, sign language technologies become technologically feasible, provided that enough data is available to feed this data-hungry paradigm. It is exactly the quality and quantity of data that is the main bottleneck in development of well performing and useful technologies.In the past, there have been several projects aimed at developing sign language technologies and methodologies that have been deemed of little value by the deaf communities. Co-creation and involvement of deaf communities throughout projects and development of technologies ensures that this does not happen again.

AB - This chapter on Language resources for Europe’s Sign Languages is an adaptation of a deliverable that is part of a series of language deliverables developed within the framework of the European Language Equality (ELE) project. The series seeks to not only delineate the current state of affairs for each European language, but to additionally identify the gaps and factors that hinder further development in research and technology. The survey presented here focuses on the condition of Language Technology (LT) with regard to Europe’s sign languages, a set of languages often forgotten in the context of European language equality.With the rise of the deep learning paradigm in artificial intelligence, sign language technologies become technologically feasible, provided that enough data is available to feed this data-hungry paradigm. It is exactly the quality and quantity of data that is the main bottleneck in development of well performing and useful technologies.In the past, there have been several projects aimed at developing sign language technologies and methodologies that have been deemed of little value by the deaf communities. Co-creation and involvement of deaf communities throughout projects and development of technologies ensures that this does not happen again.

U2 - 10.1007/978-3-031-47362-3_6

DO - 10.1007/978-3-031-47362-3_6

M3 - Chapter

SN - 978-3-031-47364-7

T3 - Machine Translation: Technologies and Applications

SP - 141

EP - 170

BT - Sign Language Machine Translation

A2 - Way, Andy

A2 - Leeson, Lorraine

A2 - Shterionov, Dimitar

PB - Springer Cham

ER -

Language Resources for European Sign Languages

Abstract

Publication series

Access to Document

Fingerprint

Cite this