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ASL-Skeleton3D and ASL-Phono: Two Novel Datasets for the American Sign Language

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arxiv 2201.02065 v1 pith:V7PYPZYU submitted 2022-01-06 cs.CV cs.CL

ASL-Skeleton3D and ASL-Phono: Two Novel Datasets for the American Sign Language

classification cs.CV cs.CL
keywords languagesigndatasetsamericanessentialindividualsnovelrepresentation
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Sign language is an essential resource enabling access to communication and proper socioemotional development for individuals suffering from disabling hearing loss. As this population is expected to reach 700 million by 2050, the importance of the language becomes even more essential as it plays a critical role to ensure the inclusion of such individuals in society. The Sign Language Recognition field aims to bridge the gap between users and non-users of sign languages. However, the scarcity in quantity and quality of datasets is one of the main challenges limiting the exploration of novel approaches that could lead to significant advancements in this research area. Thus, this paper contributes by introducing two new datasets for the American Sign Language: the first is composed of the three-dimensional representation of the signers and, the second, by an unprecedented linguistics-based representation containing a set of phonological attributes of the signs.

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Cited by 2 Pith papers

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    DigitCode tokenizes hand motion by anatomical units, showing the token span (bone/finger/hand) matters more than the quantizer family, and reduces symbolic reconstruction error by about three quarters.

  2. Sign-Language Datasets at Scale: A Comprehensive Survey on Resources, Benchmarks, and Annotation Standards

    cs.CL 2026-04 unverdicted novelty 5.0

    A survey indexes 120 sign-language datasets from 35 languages, identifies modality, annotation, and bias issues, and proposes a standardized 24-field datasheet with an open repository.