Domain training
Specialized terminology and task-specific examples teach each model the distinctions its users depend on.
domainSpecialized speech models engineered for tight power and memory budgets. Recognition runs entirely on your hardware.
Named for the kea, New Zealand's alpine parrot: clever, hardy and at home where few birds survive. Our models share that ethos, built small to work in hard places.
Derived from NVIDIA's Parakeet-TDT 0.6B v2, with 98% of its weights constrained to ternary values {−1, 0, +1}. Your audio never leaves this tab.
Downloaded once from Hugging Face, verified, then cached in your browser.
Kea-T downloads 181 MB. Best on Wi-Fi and a laptop or desktop.
This browser doesn't expose WebGPU, so Kea-T can't run here. Try a recent Chrome, Edge or Safari on a laptop or desktop.
Specialized terminology and task-specific examples teach each model the distinctions its users depend on.
domainWind, rotor wash, radio traffic. We train around the sounds that compete with a user's voice.
fieldCompute, memory and battery limits guide model size and architecture from the start.
hardwareA 24-layer FastConformer encoder with token-and-duration decoding, which skips ahead over frames instead of stepping through every one.
archCustom compute kernels read the packed 2-bit weights directly: on datacenter GPUs, on laptops, and in this page through WebGPU.
kernelsEvery large encoder matrix holds only −1, 0 or +1, with one scale per row: 181 MB on disk against 2,472 MB for the original, at 6.84% mean WER versus 6.45%.
quantModel files are checked against a published SHA-256 before they run. Audio stays on your device, with no telemetry or cloud dependency.
integrityA voice-operated, local-only guide to the Tactical Combat Casualty Care manual, with source-cited responses for trained responders.
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