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
- Editors:
- Wassim El-Hajj, Lamia Hadrich Belguith, Fethi Bougares, Walid Magdy, Imed Zitouni, Nadi Tomeh, Mahmoud El-Haj, Wajdi Zaghouani
- Venue:
- WANLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 219–223
- Language:
- URL:
- https://aclanthology.org/W19-4625
- DOI:
- 10.18653/v1/W19-4625
- Cite (ACL):
- Saméh Kchaou, Fethi Bougares, and Lamia Hadrich-Belguith. 2019. LIUM-MIRACL Participation in the MADAR Arabic Dialect Identification Shared Task. In Proceedings of the Fourth Arabic Natural Language Processing Workshop, pages 219–223, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- LIUM-MIRACL Participation in the MADAR Arabic Dialect Identification Shared Task (Kchaou et al., WANLP 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-1/W19-4625.pdf