Sign inGet started
Paper · arXiv

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...

AuthorsShivam Singh, Aditya Yadavalli, Catherine Arnett et al.
Primary categorycs.CL
Published9 September 2026
Last updated at source4 October 2026
cs.CL
Embed this entry
<iframe src="https://silytics.si/embed/item/0c14ee96-d246-4a56-a287-adcb69fdd3e7" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 2 days

0 now. Counts as reported by the source, snapshotted daily by Silytics.

Connected in the knowledge graph

Explore this entry in the graph

Models and datasets referencing this paper

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.