1 citations · 1 across the 7 of their papers we have counts for
7 papers
IEFS-GMB: Gradient Memory Bank-Guided Feature Selection Based on Information Entropy for EEG Classification of Neurological Disorders
Liang Zhang, Hanyang Dong, Jia-Hong Gao +5
Deep learning-based EEG classification is crucial for the automated detection of neurological disorders, improving diagnostic accuracy and enabling early intervention. However, the…
M3ANet: Multi-scale and Multi-Modal Alignment Network for Brain-Assisted Target Speaker Extraction
Cunhang Fan, Ying Chen, Jian Zhou +6
The brain-assisted target speaker extraction (TSE) aims to extract the attended speech from mixed speech by utilizing the brain neural activities, for example Electroencephalograph…
Region-Based Optimization in Continual Learning for Audio Deepfake Detection
Yujie Chen, Jiangyan Yi, Cunhang Fan +10
Rapid advancements in speech synthesis and voice conversion bring convenience but also new security risks, creating an urgent need for effective audio deepfake detection. Although…
UNO Arena for Evaluating Sequential Decision-Making Capability of Large Language Models
Zhanyue Qin, Haochuan Wang, Deyuan Liu +9
Sequential decision-making refers to algorithms that take into account the dynamics of the environment, where early decisions affect subsequent decisions. With large language model…
Frequency-mix Knowledge Distillation for Fake Speech Detection
Cunhang Fan, Shunbo Dong, Jun Xue +3
In the telephony scenarios, the fake speech detection (FSD) task to combat speech spoofing attacks is challenging. Data augmentation (DA) methods are considered effective means to…
DGSD: Dynamical Graph Self-Distillation for EEG-Based Auditory Spatial Attention Detection
Cunhang Fan, Hongyu Zhang, Wei Huang +5
Auditory Attention Detection (AAD) aims to detect target speaker from brain signals in a multi-speaker environment. Although EEG-based AAD methods have shown promising results in r…