QC-GO Submission for MADAR Shared Task: Arabic Fine-Grained Dialect Identification

Younes Samih, Hamdy Mubarak, Ahmed Abdelali, Mohammed Attia, Mohamed Eldesouki, Kareem Darwish


Abstract
This paper describes the QC-GO team submission to the MADAR Shared Task Subtask 1 (travel domain dialect identification) and Subtask 2 (Twitter user location identification). In our participation in both subtasks, we explored a number of approaches and system combinations to obtain the best performance for both tasks. These include deep neural nets and heuristics. Since individual approaches suffer from various shortcomings, the combination of different approaches was able to fill some of these gaps. Our system achieves F1-Scores of 66.1% and 67.0% on the development sets for Subtasks 1 and 2 respectively.
Anthology ID:
W19-4639
Volume:
Proceedings of the Fourth Arabic Natural Language Processing Workshop
Month:
August
Year:
2019
Address:
Florence, Italy
Venue:
WANLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
290–294
Language:
URL:
https://aclanthology.org/W19-4639
DOI:
10.18653/v1/W19-4639
Bibkey:
Cite (ACL):
Younes Samih, Hamdy Mubarak, Ahmed Abdelali, Mohammed Attia, Mohamed Eldesouki, and Kareem Darwish. 2019. QC-GO Submission for MADAR Shared Task: Arabic Fine-Grained Dialect Identification. In Proceedings of the Fourth Arabic Natural Language Processing Workshop, pages 290–294, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
QC-GO Submission for MADAR Shared Task: Arabic Fine-Grained Dialect Identification (Samih et al., WANLP 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/author-url/W19-4639.pdf