On-device speech-to-text
Provides speech-to-text with a 29-million-parameter model described as 17 MB in size.
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Audio and video / product dossier
Open-weight, on-device speech recognition that predicts words before speakers finish them.
Product brief
Earlybird is a 29M-parameter, 17 MB on-device speech-to-text model that predicts each word correctly about 90 ms before the speaker finishes it, with a confidence on every word. Built for voice agents that need to act sooner. Open weights and code.
Why we selected it
A technically distinctive release for voice-agent builders and researchers: a 29M-parameter on-device model with open weights and code. Its claimed ability to predict words before completion offers a specific latency-re
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Only capabilities supported by the product information we collected are listed here.
Provides speech-to-text with a 29-million-parameter model described as 17 MB in size.
The product description claims it predicts each word correctly about 90 milliseconds before the speaker finishes it.
Outputs a confidence value for every word.
Makes model weights and code available for developers and researchers.
Best-fit use cases
FAQ
Earlybird is an on-device speech-to-text model built for voice agents that need to act sooner.
The description lists 29 million parameters and a model size of 17 MB.
It claims to predict each word correctly about 90 milliseconds before the speaker finishes it.
Yes. It provides a confidence value for every word.
Yes. Earlybird is described as having open weights and code.