This paper presents a 3D corpus of motion capture data on French Sign Language (LSF), which is the first one available for the scientific community for pluridisciplinary studies. The paper also exhibits the usefulness of performing kinematic analysis on the corpus. The goal of the analysis is to acquire informative and quantitative knowledge for the purpose of better understanding and modelling LSF movements. Several LSF native signers are involved in the project. They were asked to describe 25 pictures in a spontaneous way while the 3D position of various body parts was recorded. Data processing includes identifying the markers, interpolating the information of missing frames, and importing the data to an annotation software to segment and classify the signs. Finally, we present the results of an analysis performed to characterize information-bearing parameters and use them in a data mining and modelling perspective.
@inproceedings{benchiheub:16029:sign-lang:lrec,
author = {Benchiheub, Mohamed-El-Fatah and Berret, Bastien and Braffort, Annelies},
title = {Collecting and Analysing a Motion-Capture Corpus of {French} {Sign} {Language}},
pages = {7--12},
editor = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna},
booktitle = {Proceedings of the {LREC2016} 7th Workshop on the Representation and Processing of Sign Languages: Corpus Mining},
maintitle = {10th International Conference on Language Resources and Evaluation ({LREC} 2016)},
publisher = {{European Language Resources Association (ELRA)}},
address = {Portoro{\v z}, Slovenia},
day = {28},
month = may,
year = {2016},
language = {english},
url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/16029.pdf}
}