@inproceedings{vazquezenriquez:24033:sign-lang:lrec,
  author    = {V{\'a}zquez-Enr{\'i}quez, Manuel and Alba-Castro, Jos{\'e} Luis and P{\'e}rez-P{\'e}rez, Ania and Cabeza-Pereiro, Mar{\'i}a del Carmen and Doc{\'i}o-Fern{\'a}ndez, Laura},
  title     = {{SignaMed}: a Cooperative Bilingual {LSE-Spanish} Dictionary in the Healthcare Domain},
  pages     = {386--394},
  editor    = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Mesch, Johanna and Schulder, Marc},
  booktitle = {Proceedings of the {LREC-COLING} 2024 11th Workshop on the Representation and Processing of Sign Languages: Evaluation of Sign Language Resources},
  maintitle = {2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation ({LREC-COLING} 2024)},
  publisher = {{ELRA Language Resources Association (ELRA) and the International Committee on Computational Linguistics (ICCL)}},
  address   = {Torino, Italy},
  day       = {25},
  month     = may,
  year      = {2024},
  isbn      = {978-2-493814-30-2},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/24033.html},
  abstract  = {In this paper we present SignaMed, a bilingual dictionary accessible in Spanish and LSE (Spanish Sign Language) specific to the medical domain. Building a sign language dataset to develop machine learning algorithms and linguistic studies is a complex task that requires the cooperation of Deaf people. The dictionary platform, built with their contributions, offers diverse access modes for users, including basic search functionalities, games, and activities for sign donation. It allows sign searching using webcam or mobile phone capturing, facilitating intuitive interaction and feedback. The article presents the technical, linguistic and cooperation details behind the construction of the dictionary and will hopefully serve as inspiration for similar initiatives in other sign languages. The dictionary is accessible through https://signamed.web.app.}
}

@inproceedings{cabeza-pereiro-etal-2016-corilse:lrec,
  author    = {Cabeza-Pereiro, Mar{\'i}a del Carmen and Garcia-Miguel, Jos{\'e} Ma and Mateo, Carmen Garc{\'i}a and Castro, Jos{\'e} Luis Alba},
  title     = {{CORILSE}: a {S}panish {S}ign {L}anguage Repository for Linguistic Analysis},
  pages     = {1402--1407},
  editor    = {Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Goggi, Sara and Grobelnik, Marko and Maegaard, Bente and Mariani, Joseph and Mazo, H{\'e}l{\`e}ne and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios},
  booktitle = {10th International Conference on Language Resources and Evaluation ({LREC} 2016)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Portoro{\v z}, Slovenia},
  day       = {23--28},
  month     = may,
  year      = {2016},
  isbn      = {978-2-9517408-9-1},
  language  = {english},
  url       = {https://aclanthology.org/L16-1223},
  abstract  = {CORILSE is a computerized corpus of Spanish Sign Language (Lengua de Signos Espa{\~n}ola, LSE). It consists of a set of recordings from different discourse genres by Galician signers living in the city of Vigo. In this paper we describe its annotation system, developed on the basis of pre-existing ones (mostly the model of Auslan corpus). This includes primary annotation of id-glosses for manual signs, annotation of non-manual component, and secondary annotation of grammatical categories and relations, because this corpus is been built for grammatical analysis, in particular argument structures in LSE. Up until this moment the annotation has been basically made by hand, which is a slow and time-consuming task. The need to facilitate this process leads us to engage in the development of automatic or semi-automatic tools for manual and facial recognition. Finally, we also present the web repository that will make the corpus available to different types of users, and will allow its exploitation for research purposes and other applications (e.g. teaching of LSE or design of tasks for signed language assessment).}
}