Trends and challenges for sign language recognition with machine learning

Jerome Fink; Mathieu De Coster; Joni Dambre; Benoît Frénay

Trends and challenges for sign language recognition with machine learning

Titre traduit de la contribution: Tendances et défis de la reconnaissance de la langue des signes avec du machine learning

Jerome Fink, Mathieu De Coster, Joni Dambre, Benoît Frénay

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférence › Article dans les actes d'une conférence/un colloque

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Résumé

Les recherches en traitement du langage ont aboutis à la création de puissants outils pour les individus et les entreprises. Néanmoins, ces succès obtenus sur les langages écrits n'ont pas encore affecté le domaine des langues des signes. Pourtant, la création d'outils similaires pour les langues des signes bénéficierait aux sourds et aux entendants en permettant de rendre l'apprentissage et la communication plus accessible pour tous.
La reconnaissance des langues des signes et sa traduction passera par l'intelligence artificielle mais requière aussi une collaboration avec les linguistes et la communauté sourde. Ce papier décrit les défis qui attendent les chercheurs en IA et résumes les avancées du domaine.

Titre traduit de la contribution	Tendances et défis de la reconnaissance de la langue des signes avec du machine learning
langue originale	Anglais
titre	ESANN 2023
Sous-titre	31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Bruges & online event October 4-5-6 2023
Editeur	i6doc.com
Pages	561-570
Nombre de pages	10
ISBN (Electronique)	9782875870889
ISBN (imprimé)	9782875870872
Etat de la publication	Publié - 4 oct. 2023

Série de publications

Nom	31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

Accès au document

ES2023-7 (1)License: Non spécifié

European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
Fink, J. (Orateur)
31 oct. 0006
Activité: Participation ou organisation d'un événement › Participation à une conférence, un congrès

Contient cette citation

Fink, J., De Coster, M., Dambre, J., & Frénay, B. (2023). Trends and challenges for sign language recognition with machine learning. Dans ESANN 2023 : 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Bruges & online event October 4-5-6 2023 (p. 561-570). (31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning). i6doc.com.

Fink, Jerome ; De Coster, Mathieu ; Dambre, Joni et al. / Trends and challenges for sign language recognition with machine learning. ESANN 2023 : 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Bruges & online event October 4-5-6 2023. i6doc.com, 2023. p. 561-570 (31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

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title = "Trends and challenges for sign language recognition with machine learning",

abstract = "Research in natural language processing has led to the creation of powerful tools for individuals, companies... However, these successes for written languages have not yet affected signed languages (SLs) to the same extent. The creation of similar tools for signed languages would benefit deaf, hard of hearing, and hearing people by making SL content, learning, and communication more accessible for everyone. SL recognition and translation are related to AI, but require collaboration with linguists and stakeholders. This paper describes related challenges from an AI researcher{\textquoteright}s point of view and summarizes the state of the art in these domains.",

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Fink, J, De Coster, M, Dambre, J & Frénay, B 2023, Trends and challenges for sign language recognition with machine learning. Dans ESANN 2023 : 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Bruges & online event October 4-5-6 2023. 31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, i6doc.com, p. 561-570.

Trends and challenges for sign language recognition with machine learning. / Fink, Jerome; De Coster, Mathieu; Dambre, Joni et al.
ESANN 2023 : 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Bruges & online event October 4-5-6 2023. i6doc.com, 2023. p. 561-570 (31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférence › Article dans les actes d'une conférence/un colloque

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AB - Research in natural language processing has led to the creation of powerful tools for individuals, companies... However, these successes for written languages have not yet affected signed languages (SLs) to the same extent. The creation of similar tools for signed languages would benefit deaf, hard of hearing, and hearing people by making SL content, learning, and communication more accessible for everyone. SL recognition and translation are related to AI, but require collaboration with linguists and stakeholders. This paper describes related challenges from an AI researcher’s point of view and summarizes the state of the art in these domains.

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Fink J, De Coster M, Dambre J, Frénay B. Trends and challenges for sign language recognition with machine learning. Dans ESANN 2023 : 31st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning - Bruges & online event October 4-5-6 2023. i6doc.com. 2023. p. 561-570. (31th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).

Trends and challenges for sign language recognition with machine learning

Résumé

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European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

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