Clean Speech Is a Prior, Not a Finish Line
TL;DR for operators Kammoun, Leglaive, Alameda-Pineda, and Gerkmann propose a source-free way to adapt a pretrained speech-enhancement model to one noisy utterance at inference time.1 The system uses one second of unlabeled deployment audio and a separately trained model of clean speech as its adaptation signal. It resets the enhancement model to its pretrained parameters before each new utterance, so adaptation is local rather than cumulative. ...