The Sign Language Dataset Compendium


Corpus

POLYTROPON Parallel Corpus

The POLYTROPON Parallel Corpus is a corpus of Greek Sign Language and Greek. The corpus consists of 3600 sentences performed by a single signer in three repetitions each. The POLYTROPON corpus was constructed at the Athena Research Center at the Institute for Language and Speech Processing (ILSP) under the lead of Eleni Efthimiou.

Basis for the POLYTROPON Parallel Corpus is the POLYTROPON Lexicon. For each sign entry in the lexicon a GSL example of use was recorded and translated to Modern Greek. The annotation provides information for the grammar levels of lexicon, morphology, syntax and semantics.

Recordings were made with one HD and one kinect camera capturing the front view of the signer. The recording took place in a studio with uni-coloured background.

Language Greek Sign Language
Size 3600 utterances with 3 repetitions each, 10000 lexicon entries, 1600 lemmas annotated
Participants 1 participant
Metadata Format not available
Translation Modern Greek, 3500 sentences translated
Annotation GR glosses, clause boundaries, HamNoSys, SiS-Builder non-manuals annotation tool, classifiers, sentence type and clause type
fully annotated (100%)
Data Format iLex, ELAN
Licence CC BY-NC-SA 4.0
Access Access to video and ELAN files requires registration
Webpages Dataset: http://sign.ilsp.gr/signilsp-site/index.php/en/ppc/
Entry at clarin:el: http://hdl.handle.net/11500/ATHENA-0000-0000-4C77-6
Institution Institute for Language and Speech Processing, Athena Research Center

Cite as

Eleni Efthimiou, Kiki Vasilaki, Stavroula-Evita Fotinea, Anna Vacalopoulou, Theodore Goulas and Athanasia-Lida Dimou. (2018): The POLYTROPON Parallel Corpus. In Proc. of the LREC 2018 Workshop “8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community”. Mayumi Bono, Eleni Efthimiou, Stavroula-Evita Fotinea, Thomas Hanke, Julie Hochgesang, Jette Kristoffersen, Johanna Mesch, Yutaka Osugi (eds). 12 May 2018, Miyazaki (Japan). ISBN: 979-10-95546-01-6, EAN: 9791095546016, pp:39-44

This entry was last modified on 6 January 2023.