Coding and analyzing large amounts of video data is a challenge for sign language researchers, who traditionally code 2D video data manually. In recent years, the implementation of 3D motion capture technology as a means of automatically tracking movement in sign language data has been an important step forward. Several studies show that motion capture technologies can measure sign language movement parameters - such as volume, speed, variance - with high accuracy and objectivity. In this paper, using motion capture technology and machine learning, we attempt to automatically measure a more complex feature in sign language known as distalization. In general, distalized signs use the joints further from the torso (such as the wrist), however, the measure is relative and therefore distalization is not straightforward to measure. The development of a reliable and automatic measure of distalization using motion tracking technology is of special interest in many fields of sign language research.
|Title of host publication||10th Workshop on the Representation and Processing of Sign Languages|
|Subtitle of host publication||Multilingual Sign Language Resources, sign-lang 2022 - held in conjunction with the International Conference on Language Resources and Evaluation, LREC 2022 - Proceedings|
|Editors||Eleni Efthimiou, Stavroula-Evita Fotinea, Thomas Hanke, Julie A. Hochgesang, Jette Kristoffersen, Johanna Mesch, Marc Schulder|
|Publisher||European Language Resources Association (ELRA)|
|Number of pages||5|
|State||Published - 2022|
|Event||10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources, sign-lang 2022 - Marseille, France|
Duration: 20 Jun 2022 → 25 Jun 2022
|Name||10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources, sign-lang 2022 - held in conjunction with the International Conference on Language Resources and Evaluation, LREC 2022 - Proceedings|
|Conference||10th Workshop on the Representation and Processing of Sign Languages: Multilingual Sign Language Resources, sign-lang 2022|
|Period||20/06/22 → 25/06/22|
Bibliographical noteFunding Information:
Thanks to Klil Eden and Nadav Eichler for their help in this project. Funding for this project was supported by an Israeli Science Foundation grant to Dr. Rose Stamp (2757/20; ISL Corpus project).
© European Language Resources Association (ELRA), licensed under CC-BY-NC 4.0.
- Israeli Sign Language
- Kinect Azure
- motion capture
ASJC Scopus subject areas
- Language and Linguistics
- Library and Information Sciences
- Linguistics and Language