Open ASR Leaderboard adds Egyptian and Nigerian English accents
The Open ASR Leaderboard adds Egyptian and Nigerian English accents, and provides finer accent breakdowns on the Private tab according to the Kachru three circles model: US vs. non-US (UK, Australia, Canada, India, Nigeria, Egypt), as well as Inner Circle (US, UK, Australia, Canada) vs. Outer and Expanding Circles (India, Nigeria, Egypt). The data was collected by Liva AI through real consumer products, covering natural, high-context multimodal interaction behavior.
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Richer accent breakdown in the Private tab
With these new accents, we can now present a richer breakdown of accents, based on Kachru’s Three Circles (kudos to Hume AI for this idea in their leaderboard ). The Open ASR Leaderboard will now report:
US vs. non-US ( UK, Australia, Canada, India, Nigeria, Egypt )
Inner Circle ( US, UK, Australia, Canada ) vs. Outer & Expanding Circles ( India, Nigeria, Egypt )
As more accents join, we’ll split the Outer and Expanding Circles.
Liva AI collects multimodal interaction data through consumer products used by real people. Because Liva owns both the collection environment and distribution, it can design products around specific model gaps across domains, industries, languages, modalities, and interaction types. This gives it access to natural, high-context behavior that emerges through real product use, rather than artificially elicited or task-based interactions.
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Spaces mentioned in this article 2
RW-Voice EQ ASR
Explore and compare English speech‑recognition model performance
Open ASR Leaderboard
Explore speech model performance across datasets