ADIDA: Automatic Dialect Identification for Arabic

Ossama Obeid, Mohammad Salameh, Houda Bouamor, Nizar Habash


Abstract
This demo paper describes ADIDA, a web-based system for automatic dialect identification for Arabic text. The system distinguishes among the dialects of 25 Arab cities (from Rabat to Muscat) in addition to Modern Standard Arabic. The results are presented with either a point map or a heat map visualizing the automatic identification probabilities over a geographical map of the Arab World.
Anthology ID:
N19-4002
Volume:
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations)
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Editors:
Waleed Ammar, Annie Louis, Nasrin Mostafazadeh
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6–11
Language:
URL:
https://aclanthology.org/N19-4002
DOI:
10.18653/v1/N19-4002
Bibkey:
Cite (ACL):
Ossama Obeid, Mohammad Salameh, Houda Bouamor, and Nizar Habash. 2019. ADIDA: Automatic Dialect Identification for Arabic. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (Demonstrations), pages 6–11, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
ADIDA: Automatic Dialect Identification for Arabic (Obeid et al., NAACL 2019)
Copy Citation:
PDF:
https://aclanthology.org/N19-4002.pdf