Automatic Classification of Handshapes in Russian Sign Language

Medet Mukushev, Alfarabi Imashev, Vadim Kimmelman, Anara Sandygulova


Abstract
Handshapes are one of the basic parameters of signs, and any phonological or phonetic analysis of a sign language must account for handshapes. Many sign languages have been carefully analysed by sign language linguists to create handshape inventories. This has theoretical implications, but also applied use, as it is important due to the need of generating corpora for sign languages that can be searched, filtered, sorted by different sign components (such as handshapes, orientation, location, movement, etc.). However, it is a very time-consuming process, thus only a handful of sign languages have such inventories. This work proposes a process of automatically generating such inventories for sign languages by applying automatic hand detection, cropping, and clustering techniques. We applied our proposed method to a commonly used resource: the Spreadthesign online dictionary (www.spreadthesign.com), in particular to Russian Sign Language (RSL). We then manually verified the data to be able to perform classification. Thus, the proposed pipeline can serve as an alternative approach to manual annotation, and can help linguists in answering numerous research questions in relation to handshape frequencies in sign languages.
Anthology ID:
2020.signlang-1.27
Volume:
Proceedings of the LREC2020 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
SignLang
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
165–170
Language:
English
URL:
https://aclanthology.org/2020.signlang-1.27
DOI:
Bibkey:
Cite (ACL):
Medet Mukushev, Alfarabi Imashev, Vadim Kimmelman, and Anara Sandygulova. 2020. Automatic Classification of Handshapes in Russian Sign Language. In Proceedings of the LREC2020 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives, pages 165–170, Marseille, France. European Language Resources Association (ELRA).
Cite (Informal):
Automatic Classification of Handshapes in Russian Sign Language (Mukushev et al., SignLang 2020)
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PDF:
https://aclanthology.org/2020.signlang-1.27.pdf