A multi-metric learned quality model (Uni-VERSA-Ext) is used as a differentiable training loss for speech enhancement, with a regularization term to prevent adversarial exploitation.
Fat-hubert: Front-end adaptive training of hidden-unit bert for distortion-invariant robust speech recognition,
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Improving Speech Enhancement with Multi-Metric Supervision from Learned Quality Assessment
A multi-metric learned quality model (Uni-VERSA-Ext) is used as a differentiable training loss for speech enhancement, with a regularization term to prevent adversarial exploitation.