NADI 2022: The Third Nuanced Arabic Dialect Identification Shared Task

AbdelRahim Elmadany; Chiyu Zhang; Houda Bouamor; Muhammad Abdul-Mageed; Nizar Habash

NADI 2022: The Third Nuanced Arabic Dialect Identification Shared Task

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arxiv 2210.09582 v2 pith:LYMLGVRG submitted 2022-10-18 cs.CL

NADI 2022: The Third Nuanced Arabic Dialect Identification Shared Task

Muhammad Abdul-Mageed , Chiyu Zhang , AbdelRahim Elmadany , Houda Bouamor , Nizar Habash This is my paper

classification cs.CL

keywords subtasknadiarabicteamsdialectidentificationparticipatedshared

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We describe findings of the third Nuanced Arabic Dialect Identification Shared Task (NADI 2022). NADI aims at advancing state of the art Arabic NLP, including on Arabic dialects. It does so by affording diverse datasets and modeling opportunities in a standardized context where meaningful comparisons between models and approaches are possible. NADI 2022 targeted both dialect identification (Subtask 1) and dialectal sentiment analysis (Subtask 2) at the country level. A total of 41 unique teams registered for the shared task, of whom 21 teams have actually participated (with 105 valid submissions). Among these, 19 teams participated in Subtask 1 and 10 participated in Subtask 2. The winning team achieved 27.06 F1 on Subtask 1 and F1=75.16 on Subtask 2, reflecting that the two subtasks remain challenging and motivating future work in this area. We describe methods employed by participating teams and offer an outlook for NADI.

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NADI 2025: The First Multidialectal Arabic Speech Processing Shared Task
cs.CL 2025-09 conditional novelty 5.0

The NADI 2025 shared task introduces a standardized speech benchmark for eight Arabic dialects and reports best results of 79.8% dialect ID accuracy, 35.68 WER for ASR, and 55 WER for diacritic restoration.