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.
NADI 2024: The Fifth Nuanced Arabic Dialect Identification Shared Task
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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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NADI 2025: The First Multidialectal Arabic Speech Processing Shared Task
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.