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eess.SP2026
Why Performance Metrics Overpromise in Auditory Attention Decoding: an Information-Theoretic Reappraisal
Nicolas Heintz, Simon Geirnaert, Tom Francart +1
Auditory attention decoding (AAD) algorithms are predominantly evaluated in a steady state where a listener continuously attends to the same speaker, using metrics such as accuracy…
eess.SP2026
A Multi-decoder Neural Tracking Method for Accurately Predicting Speech Intelligibility
Rien Sonck, Bernd Accou, Tom Francart +1
Objective: EEG-based methods can predict speech intelligibility, but their accuracy and robustness lag behind behavioral tests, which typically show test-retest differences under 1…
eess.SP2025
Performance Modeling for Correlation-based Neural Decoding of Auditory Attention to Speech
Simon Geirnaert, Jonas Vanthornhout, Tom Francart +1
Correlation-based auditory attention decoding (AAD) algorithms exploit neural tracking mechanisms to determine listener attention among competing speech sources via, e.g., electroe…