@inproceedings{kamal:20029:sign-lang:lrec,
  author    = {Kamal, Zina and Hassani, Hossein},
  title     = {Towards {Kurdish} Text to Sign Translation},
  pages     = {117--122},
  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/20029.html},
  doi       = {10.63317/39izdec47vq4},
  abstract  = {The resources and technologies for Sign language processing of resourceful languages are emerging, while the low-resource languages are falling behind. Kurdish is a multi-dialect language, and it is considered a low-resource language. It is spoken by approximately 30 million people in several countries, which denotes that it has a large community with hearing-impairments as well. This paper reports on a project which aims to develop the necessary data and tools to process the Sign language for Sorani as one of the spoken Kurdish dialects. We present the results of developing a dataset in HamNoSys and its corresponding SiGML form for the Kurdish Sign lexicon. We use this dataset to implement a sign-supported Kurdish tool to check the accuracy of the Sign lexicon. We tested the tool by presenting it to hearing-impaired individuals. The experiment showed that 100{\%} of the translated letters were understandable by a hearing-impaired person. The percentages were 65{\%} for isolated words, and approximately 30{\%} for the words in sentences. The data is publicly available at https://github.com/KurdishBLARK/KurdishSignLanguage for non-commercial use under the CC BY-NC-SA 4.0 licence}
}