Cohere Launches Open Source Arabic Speech Model That Beats Whisper In 96% Of Human Tests
Cohere launched Transcribe Arabic, a new open source speech recognition model licensed under Apache 2.0 that the company says tops the Open Universal Arabic ASR Leaderboard. The model claims superior transcription accuracy compared to existing open-weight systems, beating Whisper in 96% of human preference tests.
Designed to handle code-switching, multiple dialects, and Arabic-accented English, the architecture targets developers and businesses serving millions of Arabic speakers. The weights are available for download, allowing for direct integration into voice transcription and localization applications.
From the sources (7 posts)
@cohereWe’ve built Cohere Transcribe Arabic, the world’s most accurate open-source model for Arabic speech recognition. Available under Apache 2.0
@huggingfaceRT @cohere: We’ve built Cohere Transcribe Arabic, the world’s most accurate open-source model for Arabic speech recognition. Available und…
@clementdelangueRT @cohere: We’ve built Cohere Transcribe Arabic, the world’s most accurate open-source model for Arabic speech recognition. Available und…
@aidangomezRT @cohere: We’ve built Cohere Transcribe Arabic, the world’s most accurate open-source model for Arabic speech recognition. Available und…
@jayalammarنطلق اليوم نموذج @cohere Transcribe العربي، أفضل نموذج مفتوح المصدر لتحويل الكلام العربي من الصوت إلى نص، مع مراعاة اللهجات العربية المختلفة. يتصدر معيار Open Universal Arabic ASR Leaderboard. صُمم النموذج لدعم حالات تحويل الكلام بين العر
@cohereOur model tops the Open Universal Arabic ASR Leaderboard, outperforming Whisper and OmniASR in transcription accuracy. Human reviewers also preferred us to Whisper in 96% of tests.
@cohereTranscribe Arabic is built to bring frontier capabilities to the millions of Arabic speakers in business and developer communities. Built to handle code-switching, multiple dialects, and Arabic-accented English, we’re taking real-life trans