Developing a Fine-grained Corpus for a Less-resourced Language: the case of Kurdish

Roshna Abdulrahman, Hossein Hassani, Sina Ahmadi


Abstract
Kurdish is a less-resourced language consisting of different dialects written in various scripts. Approximately 30 million people in different countries speak the language. The lack of corpora is one of the main obstacles in Kurdish language processing. In this paper, we present KTC-the Kurdish Textbooks Corpus, which is composed of 31 K-12 textbooks in Sorani dialect. The corpus is normalized and categorized into 12 educational subjects containing 693,800 tokens (110,297 types). Our resource is publicly available for non-commercial use under the CC BY-NC-SA 4.0 license.
Anthology ID:
W19-3634
Volume:
Proceedings of the 2019 Workshop on Widening NLP
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Amittai Axelrod, Diyi Yang, Rossana Cunha, Samira Shaikh, Zeerak Waseem
Venue:
WiNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
106–109
Language:
URL:
https://aclanthology.org/W19-3634
DOI:
Bibkey:
Cite (ACL):
Roshna Abdulrahman, Hossein Hassani, and Sina Ahmadi. 2019. Developing a Fine-grained Corpus for a Less-resourced Language: the case of Kurdish. In Proceedings of the 2019 Workshop on Widening NLP, pages 106–109, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Developing a Fine-grained Corpus for a Less-resourced Language: the case of Kurdish (Abdulrahman et al., WiNLP 2019)
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