most citedUnifying Robustness and Fidelity: A Comprehensive Study of Pretrained Generative Methods for Speech Enhancement in Adverse Conditions

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eess.AS2026

ArrayDPS-Refine: Generative Refinement of Discriminative Multi-Channel Speech Enhancement

Zhongweiyang Xu, Ashutosh Pandey, Juan Azcarreta +3

Multi-channel speech enhancement aims to recover clean speech from noisy multi-channel recordings. Most deep learning methods employ discriminative training, which can lead to non-…

eess.AS2023★ 1 cited

Unifying Robustness and Fidelity: A Comprehensive Study of Pretrained Generative Methods for Speech Enhancement in Adverse Conditions

Heming Wang, Meng Yu, Hao Zhang +5

Enhancing speech signal quality in adverse acoustic environments is a persistent challenge in speech processing. Existing deep learning based enhancement methods often struggle to…