Time-domain single-channel speech enhancement (SE) still remains challenging to extract
the target speaker without any prior information on multi-talker conditions. It has been shown …

The monaural speech source separation problem is an important application in the signal
processing field. But recent interaction of deep learning algorithms with signal processing …

Humans possess the remarkable ability to selectively attend to a single speaker amidst
competing voices and background noise, known as selective auditory attention. Recent …

Humans show a remarkable ability in solving the cocktail party problem. Decoding auditory
attention from the brain signals is a major step toward the development of bionic ears …

Neuro-steered speaker extraction aims to extract the listener's brainattended speech signal
from a multi-talker speech signal, in which the attention is derived from the cortical activity …

In the field of neuro-steered speaker ectraction, a recently proposed end-to-end method
called U-shaped Brain Enhanced Speech Denoiser (U-BESD) has shown advantages in …

Humans possess the remarkable ability to selectively focus on one sound source in a
cocktail party scenario. Decoding auditory attention from brain signals is essential for the …

Speech enhancement is widely used as a front-end to improve the speech quality in many
audio systems, while it is still hard to extract the target speech in multi-talker conditions …

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 …

Brain-assisted speech enhancement (SE) has gained an increasing attention recently, as
electroencephalogram (EEG) measurements somehow reflect auditory attention clues. The …