Contribution
EEG-based spatial auditory attention decoding in a concurrent two talker scenario
* Presenting author
Abstract:
We present a study on EEG-based spatial auditory attention decoding, focusing on a classification task involving normal hearing- and hearing-impaired individuals listening to concurrent audio streams of two talkers while attending to one of them. Leveraging publicly available data, we trained a neural network to classify the direction of auditory attention. Our findings reveal the feasibility of using EEG signals to decode spatial auditory attention, shedding light on the potential for developing valuable technologies for individuals with and without hearing impairments. We explore the potential for personalized interventions and broader applications of EEG-based spatial auditory attention decoding in fields such as healthcare, communication technology, and cognitive neuroscience. Our study underscores the promise of EEG-based approaches in advancing our understanding of auditory attention and in developing innovative solutions to address challenges faced by individuals with and without hearing impairments.