# Falcon-ASR

Abu Dhabi's Technology Innovation Institute released Falcon-ASR, a 1.6-billion-parameter speech recognition model built for Arabic with particular attention to the Emirati dialect, and also covering English, French, Spanish and Portuguese. Across six Arabic test sets it reached an average word error rate of 20.92%, below the best published 23.17% in the leaderboard snapshot used for comparison; on an internal Emirati evaluation it recorded 22.73% word error and 10.19% character error, the lowest among the systems compared. The model also emits word-level timestamps that link each transcribed word to its position in the audio.

Abu Dhabi's Technology Innovation Institute released Falcon-ASR, a 1.6-billion-parameter speech recognition model built for Arabic with particular attention to the Emirati dialect, and also covering English, French, Spanish and Portuguese. Across six Arabic test sets it reached an average word error rate of 20.92%, below the best published 23.17% in the leaderboard snapshot used for comparison; on an internal Emirati evaluation it recorded 22.73% word error and 10.19% character error, the lowest among the systems compared. The model also emits word-level timestamps that link each transcribed word to its position in the audio.

The Technology Innovation Institute (TII) in Abu Dhabi released Falcon-ASR, a 1.6B-parameter speech recognition model focused on Arabic with particular attention to the Emirati dialect and also supporting English, French, Spanish and Portuguese; it reached 20.92% average word error rate across six Arabic test sets, better than the 23.17% best published result it cites, and 22.73% WER with 10.19% CER on an internal Emirati evaluation, the lowest among the systems compared, while also providing word-level timestamps.

The Technology Innovation Institute (TII) in Abu Dhabi released Falcon-ASR, a 1.6B-parameter speech recognition model focused on Arabic with particular attention to the Emirati dialect and also supporting English, French, Spanish and Portuguese; it reached 20.92% average word error rate across six Arabic test sets, better than the 23.17% best published result it cites, and 22.73% WER with 10.19% CER on an internal Emirati evaluation, the lowest among the systems compared, while also providing word-level timestamps.