activity
20202025
most citedThe role of vowel and consonant onsets in neural tracking of natural speech

2 citations · 3 across the 7 of their papers we have counts for

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6 papers · 1 filter

eess.SP2025

Post-processing of EEG-based Auditory Attention Decoding Decisions via Hidden Markov Models

Nicolas Heintz, Tom Francart, Alexander Bertrand

Auditory attention decoding (AAD) algorithms exploit brain signals, such as electroencephalography (EEG), to identify which speaker a listener is focusing on in a multi-speaker env…

eess.SP2025

Unsupervised EEG-based decoding of absolute auditory attention with canonical correlation analysis

Nicolas Heintz, Tom Francart, Alexander Bertrand

We propose a fully unsupervised algorithm that detects from encephalography (EEG) recordings when a subject actively listens to sound, versus when the sound is ignored. This proble…

eess.SP2024

Linear stimulus reconstruction works on the KU Leuven audiovisual, gaze-controlled auditory attention decoding dataset

Simon Geirnaert, Iustina Rotaru, Tom Francart +1

In a recent paper, we presented the KU Leuven audiovisual, gaze-controlled auditory attention decoding (AV-GC-AAD) dataset, in which we recorded electroencephalography (EEG) signal…

eess.SP2024

Stimulus-Informed Generalized Canonical Correlation Analysis for Group Analysis of Neural Responses to Natural Stimuli

Simon Geirnaert, Yuanyuan Yao, Tom Francart +1

Various new brain-computer interface technologies or neuroscience applications require decoding stimulus-following neural responses to natural stimuli such as speech and video from…

eess.SP2023

Detecting post-stroke aphasia using EEG-based neural envelope tracking of natural speech

Pieter De Clercq, Jill Kries, Ramtin Mehraram +3

[Objective]. After a stroke, one-third of patients suffer from aphasia, a language disorder that impairs communication ability. The standard behavioral tests used to diagnose aphas…

eess.SP2020

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…