3 citations · 5 across the 3 of their papers we have counts for
3 papers
eess.AS2022★ 1 cited
FB-MSTCN: A Full-Band Single-Channel Speech Enhancement Method Based on Multi-Scale Temporal Convolutional Network
Zehua Zhang, Lu Zhang, Xuyi Zhuang +3
In recent years, deep learning-based approaches have significantly improved the performance of single-channel speech enhancement. However, due to the limitation of training data an…
eess.AS2021★ 3 cited
Incorporating Multi-Target in Multi-Stage Speech Enhancement Model for Better Generalization
Lu Zhang, Mingjiang Wang, Andong Li +2
Recent single-channel speech enhancement methods based on deep neural networks (DNNs) have achieved remarkable results, but there are still generalization problems in real scenes.…
eess.AS2021★ 1 cited
Deep Interaction between Masking and Mapping Targets for Single-Channel Speech Enhancement
Lu Zhang, Mingjiang Wang, Zehua Zhang +1
The most recent deep neural network (DNN) models exhibit impressive denoising performance in the time-frequency (T-F) magnitude domain. However, the phase is also a critical compon…