Real-Time Tracking of Selective Auditory Attention From M/EEG: A Bayesian Filtering Approach.

ABSTRACT: Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon. Results from several decades of studying this phenomenon have culminated in recent years in various promising attempts to decode the attentional state of a listener in a competing-speaker environment from non-invasive neuroimaging recordings such as magnetoencephalography (MEG) and electroencephalography (EEG). To this end, most existing approaches compute correlation-based measures by either regressing the features of each speech stream to the M/EEG channels (the decoding approach) or vice versa (the encoding approach). To produce robust results, these procedures require multiple trials for training purposes. Also, their

SUBMITTER: Miran S 

PROVIDER: S-EPMC5938416 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature