More and more sign languages nowadays are now documented by large-scale digital corpora. But exploiting sign language (SL) corpus data remains subject to the time consuming and expensive manual task of annotating. In this paper, we present an ongoing research that aims at testing a new approach to better mine SL data. It relies on the methodology of corpus-based contrastive linguistics, exploiting SL corpora as bilingual corpora. We present and illustrate the main improvements we foresee in developing such an approach: downstream, for the benefit of the linguistic description and the bilingual (signed - spoken) competence of teachers, learners and the users; and upstream, in order to enable the automatisation of the annotation process of sign language data. We also describe the methodology we are using to develop a concordancer able to turn SL corpora into searchable translation corpora, and to derive from it a tool support to annotation.
@inproceedings{meurant:16032:sign-lang:lrec,
author = {Meurant, Laurence and Cleve, Anthony and Crasborn, Onno},
title = {Using sign language corpora as bilingual corpora for data mining: Contrastive linguistics and computer-assisted annotation},
pages = {159--166},
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/16032.pdf}
}
