1 citations · 1 across the 1 of their papers we have counts for
3 papers
Extracting Different Levels of Speech Information from EEG Using an LSTM-Based Model
Mohammad Jalilpour Monesi, Bernd Accou, Tom Francart +1
Decoding the speech signal that a person is listening to from the human brain via electroencephalography (EEG) can help us understand how our auditory system works. Linear models h…
Riemannian geometry-based decoding of the directional focus of auditory attention using EEG
Simon Geirnaert, Tom Francart, Alexander Bertrand
Auditory attention decoding (AAD) algorithms decode the auditory attention from electroencephalography (EEG) signals that capture the listener's neural activity. Such AAD methods a…
An LSTM Based Architecture to Relate Speech Stimulus to EEG
Mohammad Jalilpour Monesi, Bernd Accou, Jair Montoya-Martinez +2
Modeling the relationship between natural speech and a recorded electroencephalogram (EEG) helps us understand how the brain processes speech and has various applications in neuros…