5 accepted papers
This paper describes the auditory EEG challenge which was organized as one of the Signal Processing Grand Challenges of ICASSP 2023. This challenge consists of two tasks in which the goal is to relate electroencephalogram (EEG) signals to the presented speech stimulus. In the first task, named match…
It is possible to decode auditory attention to speech from electrophysiological brain recordings such as electroencephalography (EEG). Such an auditory attention decoding (AAD) allows, e.g., to determine to which person a listener is attending in a multi-talker scenario. The vast majority of researc…
The electroencephalogram (EEG) is a powerful method to understand how the brain processes speech. Linear models have recently been replaced for this purpose with deep neural networks and yield promising results. In related EEG classification fields, it is shown that explicitly modeling subject-invar…
Auditory attention decoding (AAD) algorithms decode the auditory attention from electroencephalography (EEG) signals that capture the listener’s neural activity. Such AAD methods are believed to be an important ingredient towards so-called neuro-steered assistive hearing devices. For example, tradit…
Modeling the relationship between natural speech and a recorded electroencephalogram (EEG) helps us understand how the brain processes speech and has various applications in neuroscience and brain-computer interfaces. In this context, so far mainly linear models have been used. However, the decoding…