Enhancing Syllabic Component Classification in Japanese Sign Language by Pre-training on Non-Japanese Sign Language Data

Jundai Inoue, Makoto Miwa, Yutaka Sasaki, Daisuke Hara


Anthology ID:
2024.signlang-1.13
Volume:
Proceedings of the LREC-COLING 2024 11th Workshop on the Representation and Processing of Sign Languages: Evaluation of Sign Language Resources
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Eleni Efthimiou, Stavroula-Evita Fotinea, Thomas Hanke, Julie A. Hochgesang, Johanna Mesch, Marc Schulder
Venue:
SignLang
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
123–130
Language:
URL:
https://aclanthology.org/2024.signlang-1.13
DOI:
Bibkey:
Cite (ACL):
Jundai Inoue, Makoto Miwa, Yutaka Sasaki, and Daisuke Hara. 2024. Enhancing Syllabic Component Classification in Japanese Sign Language by Pre-training on Non-Japanese Sign Language Data. In Proceedings of the LREC-COLING 2024 11th Workshop on the Representation and Processing of Sign Languages: Evaluation of Sign Language Resources, pages 123–130, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Enhancing Syllabic Component Classification in Japanese Sign Language by Pre-training on Non-Japanese Sign Language Data (Inoue et al., SignLang 2024)
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PDF:
https://aclanthology.org/2024.signlang-1.13.pdf