sign-lang@LREC Anthology

Retrospective of Kazakh-Russian Sign Language Corpus Formation

Imashev, Alfarabi ORCID button Imashev, Alfarabi | Kydyrbekova, Aigerim | Mukushev, Medet ORCID button Mukushev, Medet | Sandygulova, Anara ORCID button Sandygulova, Anara | Islam, Shynggys | Israilov, Khassan | Makazhanov, Aibek | Yessenbayev, Zhandos


Volume:
Proceedings of the LREC-COLING 2024 11th Workshop on the Representation and Processing of Sign Languages: Evaluation of Sign Language Resources
Venue:
Torino, Italy
Date:
25 May 2024
Pages:
189–201
Publisher:
ELRA Language Resources Association (ELRA) and the International Committee on Computational Linguistics (ICCL)
License:
CC BY-NC 4.0
sign-lang ID:
24023
ACL ID:
2024.signlang-1.12
ISBN:
978-2-493814-30-2

Abstract

Sign language (SL) is a mode of communication that, in most cases, relies on visual perception exclusively and utilizes visual-gestural modality. Sign languages are already universally acknowledged as complete and natural languages. The advent of machine learning techniques has expanded the range of potential applications, not only in industry but also in addressing societal needs. Previous research conducted before 2015 has already demonstrated encouraging outcomes in developing sign language recognition systems that are both quite accurate and resilient. Nevertheless, the effectiveness and utilization of algorithms are impacted not only by their accessibility but also, at times to a greater extent, by the presence of substantial quantities of pertinent data. At the commencement of the local sign language corpus collection in 2015, there was a notable deficit of local Kazakh-Russian sign language (K-RSL) data available for computer vision and machine-learning tasks. There were already corpora of another lexically close Russian Sign Langauge (RSL), but they were aimed at and tailored for research in linguistics. Therefore, we initiated the procedure by collecting pertinent data appropriate for machine-learning purposes. The subsets have been incorporated into the principal corpus and will be subject to future enhancements and refinements. This paper provides a concise overview of the collected components of the Kazakh-Russian Sign Language Corpus and the resulting outcomes derived from them within the last decade.

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@inproceedings{imashev:24023:sign-lang:lrec,
  author    = {Imashev, Alfarabi and Kydyrbekova, Aigerim and Mukushev, Medet and Sandygulova, Anara and Islam, Shynggys and Israilov, Khassan and Makazhanov, Aibek and Yessenbayev, Zhandos},
  title     = {Retrospective of {Kazakh-Russian} {Sign} {Language} Corpus Formation},
  pages     = {189--201},
  editor    = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Mesch, Johanna and Schulder, Marc},
  booktitle = {Proceedings of the {LREC-COLING} 2024 11th Workshop on the Representation and Processing of Sign Languages: Evaluation of Sign Language Resources},
  maintitle = {2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation ({LREC-COLING} 2024)},
  publisher = {{ELRA Language Resources Association (ELRA) and the International Committee on Computational Linguistics (ICCL)}},
  address   = {Torino, Italy},
  day       = {25},
  month     = may,
  year      = {2024},
  isbn      = {978-2-493814-30-2},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/24023.pdf}
}
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