Almieyar: A Culturally Grounded Benchmark for Multi-Dialect Arabic Speech Recognition
Arabic speech technology has largely focused on Modern Standard Arabic, leaving the living dialects spoken by hundreds of millions under-served. We introduce ALMIEYAR, a culturally grounded ASR benchmark covering 17 Arabic dialects across six families, built entirely from newly recorded speech unseen by existing models. Dialect-community coordinators selected culturally relevant images across 10 topics, and native speakers described them through five structured scenarios, yielding approximately 50 minutes per dialect (13.7 hours total). We benchmark 12 state-of-the-art ASR systems zero-shot, including GPT-4o-transcribe, Voxtral-Mini-4B, Fanar-STT-LF, Whisper, SeamlessM4T-v2, and wav2vec2-...
| Authors | Omid Ghahroodi, Anas Madkoor, Dima Faris Al Saudi et al. |
|---|---|
| Primary category | cs.CL |
| Published | 28 September 2026 |
| Last updated at source | 28 September 2026 |
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