NADI 2026 TASK 5.2 SLU – SLOT FILLING
Organizer: harounelleuch; 2 submissions; The Slot Filling subtask evaluates systems on their ability to extract semantic information directly from spoken utterances in Tunisian Ara...
Organizer harounelleuchAbout this hackathon
The Slot Filling subtask evaluates systems on their ability to extract semantic information directly from spoken utterances in Tunisian Arabic. Given an input audio recording, participants must produce the corresponding transcription with inline slot annotations following the SLURP-TN format. Submissions are evaluated using Concept Error Rate (CoER) and Concept-Value Error Rate (CVER). For more details, visit the **official NADI 2026 page**: https://nadi.dlnlp.ai/2026/ The **dataset** is available here: https://huggingface.co/datasets/Elyadata/SLURP-TN and **baselines** are available here: https://github.com/elyadata/SLURP-TN-baselines
Tracks
General Track
Organizer: harounelleuch; 2 submissions; The Slot Filling subtask evaluates systems on their ability to extract semantic information directly from spoken utterances in Tunisian Arabic. Given an input audio recording, participants must produce the corresponding transcription with inline slot annotations following the SLURP-TN format. Submissions are evaluated using Concept Error Rate (CoER) and Concept-Value Error Rate (CVER). For more details, visit the **official NADI 2026 page**: https://nadi.dlnlp.ai/2026/ The **dataset** is available here: https://huggingface.co/datasets/Elyadata/SLURP-TN and **baselines** are available here: https://github.com/elyadata/SLURP-TN-baselines
Prizes
Project Prize
Organizer: harounelleuch; 2 submissions; The Slot Filling subtask evaluates systems on their ability to extract semantic information directly from spoken utterances in Tunisian Arabic. Given an input audio recording, participants must produce the corresponding transcription with inline slot annotations following the SLURP-TN format. Submissions are evaluated using Concept Error Rate (CoER) and Concept-Value Error Rate (CVER). For more details, visit the **official NADI 2026 page**: https://nadi.dlnlp.ai/2026/ The **dataset** is available here: https://huggingface.co/datasets/Elyadata/SLURP-TN and **baselines** are available here: https://github.com/elyadata/SLURP-TN-baselines
Schedule
Jun 15, 04:00 PM
Tags
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