1 citations · 1 across the 4 of their papers we have counts for
4 papers
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-…
uSee: Unified Speech Enhancement and Editing with Conditional Diffusion Models
Muqiao Yang, Chunlei Zhang, Yong Xu +4
Speech enhancement aims to improve the quality of speech signals in terms of quality and intelligibility, and speech editing refers to the process of editing the speech according t…
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…
SpatialCodec: Neural Spatial Speech Coding
Zhongweiyang Xu, Yong Xu, Vinay Kothapally +3
In this work, we address the challenge of encoding speech captured by a microphone array using deep learning techniques with the aim of preserving and accurately reconstructing cru…