2 citations · 2 across the 4 of their papers we have counts for
4 papers
DBHN-Net: Dual-Branch Hybrid Neural Network For Low-Complexity Monaural Speech Enhancement
Cunhang Fan, Enrui Liu, Jing Zhou +6
Although artificial neural network (ANN) based speech enhancement (SE) methods demonstrate excellent performance, the high computational complexity and high energy consumption hind…
MHANet: Multi-scale Hybrid Attention Network for Auditory Attention Detection
Lu Li, Cunhang Fan, Hongyu Zhang +4
Auditory attention detection (AAD) aims to detect the target speaker in a multi-talker environment from brain signals, such as electroencephalography (EEG), which has made great pr…
ListenNet: A Lightweight Spatio-Temporal Enhancement Nested Network for Auditory Attention Detection
Cunhang Fan, Xiaoke Yang, Hongyu Zhang +4
Auditory attention detection (AAD) aims to identify the direction of the attended speaker in multi-speaker environments from brain signals, such as Electroencephalography (EEG) sig…
BSDB-Net: Band-Split Dual-Branch Network with Selective State Spaces Mechanism for Monaural Speech Enhancement
Cunhang Fan, Enrui Liu, Andong Li +5
Although the complex spectrum-based speech enhancement(SE) methods have achieved significant performance, coupling amplitude and phase can lead to a compensation effect, where ampl…