Zobrazeno 1 - 10
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pro vyhledávání: '"Accou, Bernd"'
Autor:
Puffay, Corentin, Accou, Bernd, Bollens, Lies, Monesi, Mohammad Jalilpour, Vanthornhout, Jonas, Van hamme, Hugo, Francart, Tom
Objective. When a person listens to continuous speech, a corresponding response is elicited in the brain and can be recorded using electroencephalography (EEG). Linear models are presently used to relate the EEG recording to the corresponding speech
Externí odkaz:
http://arxiv.org/abs/2302.01736
Stimulus-evoked EEG data has a notoriously low signal-to-noise ratio and high inter-subject variability. We propose a novel paradigm for the self-supervised extraction of stimulus-related brain response data: a model is trained to extract similar inf
Externí odkaz:
http://arxiv.org/abs/2302.01924
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 have been used to reconstruct the EEG from speech or vice versa. Recent
Externí odkaz:
http://arxiv.org/abs/2106.09622
Objective: Currently, only behavioral speech understanding tests are available, which require active participation of the person being tested. As this is infeasible for certain populations, an objective measure of speech intelligibility is required.
Externí odkaz:
http://arxiv.org/abs/2105.06844
Autor:
Monesi, Mohammad Jalilpour, Accou, Bernd, Montoya-Martinez, Jair, Francart, Tom, Van Hamme, Hugo
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 l
Externí odkaz:
http://arxiv.org/abs/2002.10988
Akademický článek
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Autor:
Accou, Bernd, Bollens, Lies, Gillis, Marlies, Verheijen, Wendy, Van hamme, Hugo, Francart, Tom
Publikováno v:
Data (2306-5729); Aug2024, Vol. 9 Issue 8, p94, 18p
Autor:
Accou, Bernd1,2 (AUTHOR) bernd.accou@kuleuven.be, Vanthornhout, Jonas1 (AUTHOR), hamme, Hugo Van2 (AUTHOR), Francart, Tom1 (AUTHOR) tom.francart@kuleuven.be
Publikováno v:
Scientific Reports. 1/16/2023, Vol. 13 Issue 1, p1-12. 12p.
Akademický článek
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Stimulus-evoked brain response data has a notoriously low signal-to-noise ratio (SNR) and high inter-subject variability. Multiple techniques have been proposed to alleviate this problem, such as averaging, denoising source separation (DSS) and (mult
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b80fcf671d9d77256d47319141d1c98