Benchmark Databases for Video-Based Automatic Sign Language Recognition

Philippe Dreuw, Carol Neidle, Vassilis Athitsos, Stan Sclaroff, Hermann Ney

Abstract
A new, linguistically annotated, video database for automatic sign language recognition is presented. The new RWTH-BOSTON-400 corpus, which consists of 843 sentences, several speakers and separate subsets for training, development, and testing is described in detail. For evaluation and benchmarking of automatic sign language recognition, large corpora are needed. Recent research has focused mainly on isolated sign language recognition methods using video sequences that have been recorded under lab conditions using special hardware like data gloves. Such databases have often consisted generally of only one speaker and thus have been speaker-dependent, and have had only small vocabularies. A new database access interface, which was designed and created to provide fast access to the database statistics and content, makes it possible to easily browse and retrieve particular subsets of the video database. Preliminary baseline results on the new corpora are presented. In contradistinction to other research in this area, all databases presented in this paper will be publicly available.
Anthology ID:
L08-1469
Volume:
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Month:
May
Year:
2008
Address:
Marrakech, Morocco
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
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URL:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/287_paper.pdf
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Cite (ACL):
Philippe Dreuw, Carol Neidle, Vassilis Athitsos, Stan Sclaroff, and Hermann Ney. 2008. Benchmark Databases for Video-Based Automatic Sign Language Recognition. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).
Cite (Informal):
Benchmark Databases for Video-Based Automatic Sign Language Recognition (Dreuw et al., LREC 2008)
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http://www.lrec-conf.org/proceedings/lrec2008/pdf/287_paper.pdf
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