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SURE-Voice: A Front-End Baseline for Speech-Evidence Filtering in Speech LLMs

arXiv · AI, language, vision and robotics · article · Aug 27, 2026 · UTC

Speech language models (speech LLMs) can generate plausible outputs from audio that contains no usable speech evidence. We study this failure as a pre-generation support-estimation problem and present SURE-Voice, a training-free front end that decides whether an audio prompt contains intelligible speech evidence before calling a speech LLM. We build SURE-Challenge with a 640-example SURE-Core split and a 1,920-example SURE-Extended split derived from 120 LibriSpeech source utterances. Using one fixed operating point, an energy screen plus Whisper token confidence raises unsupported accuracy on

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Evidence & attribution

First collected: 2026-09-21T08:21:55.975Z. This is not the publication date.