BuzzASR: A Swarm of 100+ Monolingual Speech Recognition Models
We introduce BuzzASR, a collection of language-specialized fine-tuned Whisper models adapted for automatic speech recognition (ASR) in 102 languages. Large end-to-end Transformer-based ASR models such as Whisper have revolutionized ASR, but most prominent models are highly multilingual. As a result, these models often perform poorly on languages less well-represented in their training set. While it has long been known that effective language adaptation can be achieved through simple fine-tuning on monolingual data, this strategy has only been applied to a small number of languages. We massively scale up this simple approach to 102 languages covered in the FLEURS dataset, while also implem...
| Authors | Shivam Singh, Aditya Yadavalli, Catherine Arnett et al. |
|---|---|
| Primary category | cs.CL |
| Published | 9 September 2026 |
| Last updated at source | 4 October 2026 |
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- BuzzASR/burmeseModel · cited by
- BuzzASR/uzbekModel · cited by
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- BuzzASR/sorani-kurdishModel · cited by
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- BuzzASR/bulgarianModel · cited by
- BuzzASR/mongolianModel · cited by
- BuzzASR/turkishModel · cited by
- BuzzASR/lithuanianModel · cited by
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Models and datasets referencing this paper
- BuzzASR/bulgarianModel
- BuzzASR/persianModel
- BuzzASR/koreanModel
- BuzzASR/mongolianModel
- BuzzASR/georgianModel
- BuzzASR/turkishModel
- BuzzASR/sorani-kurdishModel
- BuzzASR/uzbekModel
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