3D-LEX v10: 3D Lexicons for American Sign Language and Sign Language of the Netherlands
<|reference_start|>3D-LEX v10: 3D Lexicons for American Sign Language and Sign Language of the Netherlands: In this work, we present an efficient approach for capturing sign language in 3D, introduce the 3D-LEX v1.0 dataset, and detail a method for semi-automatic annotation of phonetic properties. Our procedure integrates three motion capture techniques encompassing high-resolution 3D poses, 3D handshapes, and depth-aware facial features, and attains an average sampling rate of one sign every 10 seconds. This includes the time for presenting a sign example, performing and recording the sign, and archiving the capture. The 3D-LEX dataset includes 1,000 signs from American Sign Language and an additional 1,000 signs from the Sign Language of the Netherlands. We showcase the dataset utility by presenting a simple method for generating handshape annotations directly from 3D-LEX. We produce handshape labels for 1,000 signs from American Sign Language and evaluate the labels in a sign recognition task. The labels enhance gloss recognition accuracy by 5% over using no handshape annotations, and by 1% over expert annotations. Our motion capture data supports in-depth analysis of sign features and facilitates the generation of 2D projections from any viewpoint. The 3D-LEX collection has been aligned with existing sign language benchmarks and linguistic resources, to support studies in 3D-aware sign language processing.<|reference_end|>
@article{ranum20243d-lex,
    title={3D-LEX v1.0: 3D Lexicons for American Sign Language and Sign Language of
  the Netherlands},
    author={Oline Ranum and Gomer Otterspeer and Jari I. Andersen and Robert G.
  Belleman and Floris Roelofsen},
    journal={Proceedings of the LREC-COLING 2024 11th Workshop on the
  Representation and Processing of Sign Languages: Evaluation of Sign Language
  Resources, pages 290 to 301},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.01901},
    primaryClass={cs.CV cs.AI cs.CL}
}