Training-Free Intelligibility-Guided Observation Addition for Noisy ASR

arXiv:2602.20967v2 Announce Type: replace-cross Abstract: Automatic speech recognition (ASR) degrades severely in noisy environments. Although speech enhancement (SE) front-ends effectively suppress background noise, they often introduce artifacts that harm recognition. Observation addition (OA) addressed this issue by fusing noisy and SE enhanced speech, improving recognition without modifying the parameters of the SE or ASR models. This paper proposes an intelligibility-guided OA method, where fusion weights are derived from intelligibility estimates obtained directly from the backend ASR. U

Source: arXiv cs.AI — read the full report at the original publisher.

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