NADI 2024: The Fifth Nuanced Arabic Dialect Identification Shared Task

• URL: http://arxiv.org/abs/2407.04910v1
• Date: Sat, 6 Jul 2024 01:18:58 GMT
• Title: NADI 2024: The Fifth Nuanced Arabic Dialect Identification Shared Task
• Authors: Muhammad Abdul-Mageed, Amr Keleg, AbdelRahim Elmadany, Chiyu Zhang, Injy Hamed, Walid Magdy, Houda Bouamor, Nizar Habash,
• Abstract summary: We describe the findings of the fifth Nuanced Arabic Dialect Identification Shared Task (NADI 2024) NADI 2024 targeted both dialect identification cast as a multi-label task and identification of the Arabic level of dialectness. Winning teams achieved 50.57 Ftextsubscript1 on Subtask1, 0.1403 RMSE for Subtask2, and 20.44 BLEU in Subtask3, respectively.
• Score: 28.40134178913119
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We describe the findings of the fifth Nuanced Arabic Dialect Identification Shared Task (NADI 2024). NADI's objective is to help advance SoTA Arabic NLP by providing guidance, datasets, modeling opportunities, and standardized evaluation conditions that allow researchers to collaboratively compete on pre-specified tasks. NADI 2024 targeted both dialect identification cast as a multi-label task (Subtask~1), identification of the Arabic level of dialectness (Subtask~2), and dialect-to-MSA machine translation (Subtask~3). A total of 51 unique teams registered for the shared task, of whom 12 teams have participated (with 76 valid submissions during the test phase). Among these, three teams participated in Subtask~1, three in Subtask~2, and eight in Subtask~3. The winning teams achieved 50.57 F\textsubscript{1} on Subtask~1, 0.1403 RMSE for Subtask~2, and 20.44 BLEU in Subtask~3, respectively. Results show that Arabic dialect processing tasks such as dialect identification and machine translation remain challenging. We describe the methods employed by the participating teams and briefly offer an outlook for NADI.

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