@inproceedings{kaczmarek:20021:sign-lang:lrec,
  author    = {Kaczmarek, Marion and Filhol, Michael},
  title     = {Use cases for a Sign Language Concordancer},
  pages     = {113--116},
  editor    = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Hanke, Thomas and Hochgesang, Julie A. and Kristoffersen, Jette and Mesch, Johanna},
  booktitle = {Proceedings of the {LREC2020} 9th Workshop on the Representation and Processing of Sign Languages: Sign Language Resources in the Service of the Language Community, Technological Challenges and Application Perspectives},
  maintitle = {12th International Conference on Language Resources and Evaluation ({LREC} 2020)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Marseille, France},
  day       = {16},
  month     = may,
  year      = {2020},
  isbn      = {979-10-95546-54-2},
  language  = {english},
  url       = {https://www.sign-lang.uni-hamburg.de/lrec/pub/20021.html},
  abstract  = {This article treats about a Sign Language concordancer. In the past years, the need for content translated into Sign Language has been growing, and is still growing nowadays. Yet, unlike their text-to-text counterparts, Sign Language translators are not equipped with computer-assisted translation software. As we aim to provide them with such software, we explore the possibilities offered by a first tool: a Sign Language concordancer. It includes designing an alignments database as well as a search function to browse it. Testing sessions with professionals highlight relevant use cases for their professional practices. It can either comfort the translator when the results are identical, or show the importance of context when the results are different for a same expression. This concordancer is available online, and aim to be a collaborative tool. Though our current database is small, we hope for translators to invest themselves and help us to keep it expanding.}
}

@inproceedings{kaczmarek-filhol-2020-alignment:lrec,
  author    = {Kaczmarek, Marion and Filhol, Michael},
  title     = {Alignment Data base for a Sign Language Concordancer},
  pages     = {6069--6072},
  editor    = {Calzolari, Nicoletta and Fr{\'e}d{\'e}ric B{\'e}chet and Blache, Philippe and Choukri, Khalid and Cieri, Christopher and Declerck, Thierry and Goggi, Sara and Isahara, Hitoshi and Maegaard, Bente and Mariani, Joseph and Mazo, H{\'e}l{\`e}ne and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios},
  booktitle = {12th International Conference on Language Resources and Evaluation ({LREC} 2020)},
  publisher = {{European Language Resources Association (ELRA)}},
  address   = {Marseille, France},
  day       = {11--16},
  month     = may,
  year      = {2020},
  isbn      = {979-10-95546-34-4},
  language  = {english},
  url       = {https://aclanthology.org/2020.lrec-1.744},
  abstract  = {This article deals with elaborating a data base of alignments of parallel Franch-LSF segments. This data base is meant to be searched using a concordancer which we are also designing. We wish to equip Sign Language translators with tools similar to those used in text-to-text translation. To do so, we need language resources to feed them. Already existing Sign Language corpora can be found, but do not match our needs: working around a Sign Language concordancer, the corpus must be a parallel one and provide various examples of vocabulary and grammatical construction. We started with a parallel corpus of 40 short news and 120 SL videos , which we aligned manually by segments of various length. We described the methodology we used, how we define our segments and alignments. The last part concerns how we hope to allow the data base to keep growing in a near future.}
}