ASL-Skeleton3D and ASL-Phono: Two Novel Datasets for the American Sign Language
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Abstract (arXiv)
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.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 4 of its 24 references that are in the map. First posted on arXiv 6 Jan 2022.
Builds on
4 of 24 references.
References · 4
- 2018OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fieldscited by 1,161
- 2017Hand Keypoint Detection in Single Images using Multiview Bootstrappingcited by 231
- 2018MS-ASL: A Large-Scale Data Set and Benchmark for Understanding American Sign Languagecited by 118
- 2019Spatial-Temporal Graph Convolutional Networks for Sign Language Recognitioncited by 23
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Citing papers per year: 2022: 1.
1 paper.