Munsit is the next-generation Arabic speech-to-text model built by CNTXT AI from the ground up in the UAE. Designed for high accuracy, real-world dialect diversity, and enterprise-grade performance, Munsit powers voice agents, meeting transcription.
Key Features:
State-of-the-Art Accuracy — Among the lowest Word Error Rate (WER) across standard benchmarks.
Massive Dataset — Trained on 30000 hours of raw Arabic audio.
Dialect-Agnostic Support — Works well across more than 25 dialects from across the Arabic-speaking world.
Clean & Noisy Conditions — Consistent performance across devices, background noise, and recording environments.
Real-World Use Cases —
• AI voice agents & virtual assistants that understand spoken Arabic across dialects
• Meeting transcription and note-taking
Key Features:
State-of-the-Art Accuracy — Among the lowest Word Error Rate (WER) across standard benchmarks.
Massive Dataset — Trained on 30000 hours of raw Arabic audio.
Dialect-Agnostic Support — Works well across more than 25 dialects from across the Arabic-speaking world.
Clean & Noisy Conditions — Consistent performance across devices, background noise, and recording environments.
Real-World Use Cases —
• AI voice agents & virtual assistants that understand spoken Arabic across dialects
• Meeting transcription and note-taking
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