GigaSpeech 3 for Arabic speech recognition
39,000-hour GigaSpeech 3 corpus covers five Arabic dialects and reduces WER by 16.6% relative to prior systems.
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39,000-hour GigaSpeech 3 corpus covers five Arabic dialects and reduces WER by 16.6% relative to prior systems.
Eleven models generally scored worse on culturally localized problems than on translated-only versions.
TII released Falcon-ASR, a 1.6B Arabic speech model reporting 20.92% average WER; weights are not public.
LoRA-adapted Whisper systems for NADI 2026 Arabic ASR reach 57.1%, 46.7%, and 14.49% WER on three subtasks.
TII’s Falcon-Emirati is an LLM built for Emirati dialect, culture, and linguistic nuance.
Muslim is a production Arabic voice AI for sourced Islamic knowledge, releasing a 6B router and TTS model.
QuranicMMLU offers 980 questions testing generative models on Quranic Arabic across five linguistic pillars.
Nuha-Speech initiative builds general-purpose Arabic speech-LLMs using a 1.5M-sample speech QA corpus and fine-tuned Qwen-Omni variants.
Rosetta ranks 4th and 5th in AlexandriaX-2026 dialectal Arabic dialogue translation using a LoRA adapter on NileChat-3B, finding limited pretraining benefit.
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