AAD

In this paper, presented at EUSIPCO 2024, we present a probabilistic gain control system steered by brain-decoded auditory attention decoding algorithms.

In this article, we perform absolute attention decoding to speech based on EEG signals, to determine whether a subject is attending to the speech or not.

In this preprint, we present a new unsupervised method to estimate the performance of the stimulus reconstruction algorithm for EEG-based auditory attention decoding.

In this article, we try to uncover potential biases of the CSP-based decoding of the spatial focus of auditory attention, using a multi-talker audiovisual EEG experiment.

In this article, presented at ICASSP 2023, we present an update of the unsupervised stimulus decoder that avoids its inherent bias to the initialization.

In this article, publlished in IEEE Journal of Biomedical and Health Informatics, we present a new time-adapative unsupervised stimulus decoder for AAD.

In this article, published in IEEE Signal Processing Magazine, we provide a broad review and a statistically grounded comparative study of EEG-based AAD algorithms and address the main signal processing challenges in this field.

In this article, presented at ICASSP 2021, we present a novel method to decode the spatial focus of auditory attention from EEG using Riemmanian geometry-based classifiers.