LIUM-MIRACL Participation in the MADAR Arabic Dialect Identification Shared Task

Saméh Kchaou, Fethi Bougares, Lamia Hadrich-Belguith


Abstract
This paper describes the joint participation of the LIUM and MIRACL Laboratories at the Arabic dialect identification challenge of the MADAR Shared Task (Bouamor et al., 2019) conducted during the Fourth Arabic Natural Language Processing Workshop (WANLP 2019). We participated to the Travel Domain Dialect Identification subtask. We built several systems and explored different techniques including conventional machine learning methods and deep learning algorithms. Deep learning approaches did not perform well on this task. We experimented several classification systems and we were able to identify the dialect of an input sentence with an F1-score of 65.41% on the official test set using only the training data supplied by the shared task organizers.
Anthology ID:
W19-4625
Volume:
Proceedings of the Fourth Arabic Natural Language Processing Workshop
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | WANLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
219–223
Language:
URL:
https://www.aclweb.org/anthology/W19-4625
DOI:
10.18653/v1/W19-4625
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PDF:
http://aclanthology.lst.uni-saarland.de/W19-4625.pdf