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Look Less, Hear Better: Jointly Rewarded GRPO for Streaming ASR

arXiv · AI, language, vision and robotics · article · Sep 16, 2026 · UTC

Streaming automatic speech recognition (ASR) must be judged jointly on what it transcribes and on how quickly it commits each word. Delayed streams modeling (DSM) has become the dominant paradigm for streaming large audio-language models, exposing a structural delay $τ$ that bounds the decoder's lookahead. We show that $τ$ is a poor proxy for user-perceived latency, and that the alignment-based supervision of DSM leaves latency on the table: the same forced-aligned transcript is used at every $τ$, forcing the model to withhold words it could already commit. We introduce AWED, a word-level emis

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First collected: 2026-09-20T08:01:03.945Z. This is not the publication date.