Crowdsourcing Kazakh-Russian Sign Language: FluentSigners-50

Medet Mukushev, Aigerim Kydyrbekova, Alfarabi Imashev, Vadim Kimmelman, Anara Sandygulova


Abstract
This paper presents the methodology we used to crowdsource a data collection of a new large-scale signer independent dataset for Kazakh-Russian Sign Language (KRSL) created for Sign Language Processing. By involving the Deaf community throughout the research process, we firstly designed a research protocol and then performed an efficient crowdsourcing campaign that resulted in a new FluentSigners-50 dataset. The FluentSigners-50 dataset consists of 173 sentences performed by 50 KRSL signers for 43,250 video samples. Dataset contributors recorded videos in real-life settings on various backgrounds using various devices such as smartphones and web cameras. Therefore, each dataset contribution has a varying distance to the camera, camera angles and aspect ratio, video quality, and frame rates. Additionally, the proposed dataset contains a high degree of linguistic and inter-signer variability and thus is a better training set for recognizing a real-life signed speech. FluentSigners-50 is publicly available at https://krslproject.github.io/fluentsigners-50/
Anthology ID:
2022.lrec-1.271
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2541–2547
Language:
URL:
https://aclanthology.org/2022.lrec-1.271
DOI:
Bibkey:
Cite (ACL):
Medet Mukushev, Aigerim Kydyrbekova, Alfarabi Imashev, Vadim Kimmelman, and Anara Sandygulova. 2022. Crowdsourcing Kazakh-Russian Sign Language: FluentSigners-50. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 2541–2547, Marseille, France. European Language Resources Association.
Cite (Informal):
Crowdsourcing Kazakh-Russian Sign Language: FluentSigners-50 (Mukushev et al., LREC 2022)
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PDF:
https://preview.aclanthology.org/author-url/2022.lrec-1.271.pdf
Data
How2Sign