10 citations · 12 across the 8 of their papers we have counts for
4 papers · 1 filter
Using Ear-EEG to Decode Auditory Attention in Multiple-speaker Environment
Haolin Zhu, Yujie Yan, Xiran Xu +4
Auditory Attention Decoding (AAD) can help to determine the identity of the attended speaker during an auditory selective attention task, by analyzing and processing measurements o…
Self-supervised speech representation and contextual text embedding for match-mismatch classification with EEG recording
Bo Wang, Xiran Xu, Zechen Zhang +4
Relating speech to EEG holds considerable importance but is challenging. In this study, a deep convolutional network was employed to extract spatiotemporal features from EEG data.…
ConvConcatNet: a deep convolutional neural network to reconstruct mel spectrogram from the EEG
Xiran Xu, Bo Wang, Yujie Yan +4
To investigate the processing of speech in the brain, simple linear models are commonly used to establish a relationship between brain signals and speech features. However, these l…
A DenseNet-based method for decoding auditory spatial attention with EEG
Xiran Xu, Bo Wang, Yujie Yan +2
Auditory spatial attention detection (ASAD) aims to decode the attended spatial location with EEG in a multiple-speaker setting. ASAD methods are inspired by the brain lateralizati…