Per Channel Automatic Annotation of Sign Language Motion Capture Data

Naert, Lucie | Reverdy, Clément | Larboulette, Caroline | Gibet, Sylvie

Volume:: Proceedings of the LREC2018 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community
Venue:: Miyazaki, Japan
Date:: 12 May 2018
Pages:: 139–146
Publisher:: European Language Resources Association (ELRA)
License:: CC BY-NC 4.0
sign-lang ID:: 18014
ISBN:: 979-10-95546-01-6

Content Categories

Projects:: Sign3D
Languages:: French Sign Language
Corpora:: FEel, Sign3D

Abstract

Manual annotation is an expensive and time consuming task partly due to the high number of linguistic channels that usually compose sign language data. In this paper, we propose to automatize the annotation of sign language motion capture data by processing each channel separately. Motion features (such as distances between joints or facial descriptors) that take advantage of the 3D nature of motion capture data and the specificity of the channel are computed in order to (i) segment and (ii) label the sign language data. Two methods of automatic annotation of French Sign Language utterances using similar processes are developed. The first one describes the automatic annotation of thirty-two hand configurations while the second method describes the annotation of facial expressions using a closed vocabulary of seven expressions. Results for the two methods are then presented and discussed.

Keywords

Computer recognition of sign language and steps towards automatic annotation

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Citation in ACL Citation Format

Lucie Naert, Clément Reverdy, Caroline Larboulette, Sylvie Gibet. 2018. Per Channel Automatic Annotation of Sign Language Motion Capture Data. In Proceedings of the LREC2018 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community, pages 139–146, Miyazaki, Japan. European Language Resources Association (ELRA).

BibTeX Export

@inproceedings{naert:18014:sign-lang:lrec,
  author    = {Naert, Lucie and Reverdy, Cl{\'e}ment and Larboulette, Caroline and Gibet, Sylvie},
  title     = {Per Channel Automatic Annotation of Sign Language Motion Capture Data},
  pages     = {139--146},
  editor    = {Bono, Mayumi and Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Osugi, Yutaka},
  booktitle = {Proceedings of the {LREC2018} 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community},
  maintitle = {11th International Conference on Language Resources and Evaluation ({LREC} 2018)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Miyazaki, Japan},
  day       = {12},
  month     = may,
  year      = {2018},
  isbn      = {979-10-95546-01-6},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/18014.pdf}
}