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EEG-based Auditory Attention Decoding Towards Neuro-Steered Hearing Devices

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Document pages: 25 pages

Abstract: People suffering from hearing impairment often have difficultiesparticipating in conversations in so-called `cocktail party scenarios withmultiple people talking simultaneously. Although advanced algorithms exist tosuppress background noise in these situations, a hearing device also needsinformation on which of these speakers the user actually aims to attend to. Thecorrect (attended) speaker can then be enhanced using this information, and allother speakers can be treated as background noise. Recent neuroscientificadvances have shown that it is possible to determine the focus of auditoryattention from non-invasive neurorecording techniques, such aselectroencephalography (EEG). Based on these new insights, a multitude ofauditory attention decoding (AAD) algorithms have been proposed, which could,combined with the appropriate speaker separation algorithms and miniaturizedEEG sensor devices, lead to so-called neuro-steered hearing devices. In thispaper, we provide a broad review and a statistically grounded comparative studyof EEG-based AAD algorithms and address the main signal processing challengesin this field.

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