@inproceedings{efthimiou:18043:sign-lang:lrec,
  author    = {Efthimiou, Eleni and Vasilaki, Kyriaki and Fotinea, Stavroula-Evita and Vacalopoulou, Anna and Goulas, Theodoros and Dimou, Athanasia-Lida},
  title     = {The {POLYTROPON} Parallel Corpus},
  pages     = {39--44},
  editor    = {Bono, Mayumi and Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna and Osugi, Yutaka},
  booktitle = {Proceedings of the {LREC2018} 8th Workshop on the Representation and Processing of Sign Languages: Involving the Language Community},
  maintitle = {11th International Conference on Language Resources and Evaluation ({LREC} 2018)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Miyazaki, Japan},
  day       = {12},
  month     = may,
  year      = {2018},
  isbn      = {979-10-95546-01-6},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/18043.html},
  abstract  = {Here we present the POLYTROPON parallel corpus for the language pair Greek Sign Language (GSL) -- Greek, which is created and annotated aiming to serve as a golden corpus available to the community of SL technologies for experimentation with various approaches to SL processing, focusing on machine learning for SL recognition, machine translation (MT) and information retrieval. The corpus volume incorporates 3653 clauses in three repetitions each, captured in front view by means of one HD and one kinect camera. Corpus annotation has allowed to extract initial features sets with the aim to reach a GSL level of abstraction close to the one currently available for Greek language representations, exploiting the inherent characteristics of the language in view of applying initial deep learning experiments on GSL data, where both words and signs may be represented as vectors of characteristics which allow dependency tree structure representations of input text and signed clauses as those created by the use of Tree Editor TrEd 2.0.}
}

@inproceedings{efthimiou:16003:sign-lang:lrec,
  author    = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Dimou, Athanasia-Lida and Goulas, Theodoros and Karioris, Panagiotis and Vasilaki, Kyriaki and Vacalopoulou, Anna and Pissaris, Michalis},
  title     = {From a Sign Lexical Database to an {SL} Golden Corpus -- the {POLYTROPON} {SL} Resource},
  pages     = {63--68},
  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/16003.html},
  abstract  = {The POLYTROPON lexicon resource is being created in an attempt i) to gather and recapture already available lexical resources of Greek Sign Language (GSL) in an up-to-date homogeneous manner, ii) to enrich these resources with new lemmas, and iii) to end up with a multipurpose-multiuse resource which can be equally exploited in end user oriented educational/communication services and in supporting various SL technologies. The database that hosts the newly acquired resource, incorporates various SL oriented fields of information, including information on compounding, GSL synonyms, classifier qualities, lemma related senses, semantic groupings etc, and also lemma coding for their manual and non-manual articulation activity. It also provides linking of GSL and Modern Greek equivalent(s) lemma pairs to serve bilingual use purposes. A by-product of considerable value is the parallel corpus which derived from the GSL examples of use accompanying each lemma entry in the dictionary and their translations into Modern Greek. The annotation of the corpus for the entailed signs and assignment of respective glosses in combination with data capturing by both HD and Kinect cameras in three repetitions, allowed for the creation of a golden parallel corpus available to the community of SL technologies for experimentation with various approaches to SL recognition, MT and information retrieval.}
}

@inproceedings{dimou:14022:sign-lang:lrec,
  author    = {Dimou, Athanasia-Lida and Goulas, Theodoros and Efthimiou, Eleni and Fotinea, Stavroula-Evita},
  title     = {Creation of a multipurpose sign language lexical resource: The {GSL} lexicon database},
  pages     = {37--42},
  editor    = {Crasborn, Onno and Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna},
  booktitle = {Proceedings of the {LREC2014} 6th Workshop on the Representation and Processing of Sign Languages: Beyond the Manual Channel},
  maintitle = {9th International Conference on Language Resources and Evaluation ({LREC} 2014)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Reykjavik, Iceland},
  day       = {31},
  month     = may,
  year      = {2014},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/14022.html},
  abstract  = {The GSL lexicon database is the first extensive database of Greek Sign Language (GSL) signs, created on the basis of knowledge derived from the linguistic analysis of natural signers{\'i} data. It incorporates a lemma list that currently includes approximately 6,000 entries and is intended to reach a total number of 10,000 entries within the next two years. The design of the database allows for classification of signs on the basis of their articulation features as regards both manual and non-manual elements. The adopted information management schema accompanying each entry provides for retrieval according to a variety of linguistic properties. In parallel, annotation of the full set of sign articulation features feeds more natural performance of synthetic signing engines and more effective treatment of sign language (SL) data in the framework of sign recognition and natural language processing.}
}