sign-lang@LREC Anthology

MC-TRISLAN: A Large 3D Motion Capture Sign Language Data-set

Jedlička, Pavel | Krňoul, Zdeněk | Železný, Miloš | Müller, Luděk

Volume:
Proceedings of the LREC2022 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources
Venue:
Marseille, France
Date:
25 June 2022
Pages:
88–93
Publisher:
European Language Resources Association (ELRA)
License:
CC BY-NC 4.0
sign-lang ID:
22039
ACL ID:
2022.signlang-1.14
ISBN:
979-10-95546-86-3

Content Categories

Projects:
ELG
Languages:
Czech Sign Language
Corpora:
MC-TRISLAN

Abstract

The new 3D motion capture data corpus expands the portfolio of existing language resources by a corpus of 18~hours of Czech sign language. This helps to alleviate the current problem, which is a critical lack of high quality data necessary for research and subsequent deployment of machine learning techniques in this area. We currently provide the largest collection of annotated sign language recordings acquired by state-of-the-art 3D human body recording technology for the successful future deployment in communication technologies, especially machine translation and sign language synthesis.

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@inproceedings{jedlicka:22039:sign-lang:lrec,
  author    = {Jedli{\v c}ka, Pavel and Kr{\v n}oul, Zden{\v e}k and {\v Z}elezn{\'y}, Milo{\v s} and M{\"u}ller, Lud{\v e}k},
  title     = {{MC-TRISLAN}: A Large {3D} Motion Capture Sign Language Data-set},
  pages     = {88--93},
  editor    = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Schulder, Marc},
  booktitle = {Proceedings of the {LREC2022} 10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources},
  maintitle = {13th International Conference on Language Resources and Evaluation ({LREC} 2022)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Marseille, France},
  day       = {25},
  month     = jun,
  year      = {2022},
  isbn      = {979-10-95546-86-3},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/22039.pdf}
}
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