Decoding the Attended Speaker From EEG Using Adaptive Evaluation Intervals Captures Fluctuations in Attentional Listening - Jaeger, Manuela; Mirkovic, Bojana; Bleichner, Martin G.; Debener, Stefan (Frontiers in Neuroscience, 2020)
Listeners differ in their ability to attend to a speech stream in the presence of a competing sound. Differences in speech intelligibility in noise cannot be fully explained by the hearing ability which suggests the involvement of additional cognitive factors. A better understanding of the temporal fluctuations in the ability to pay selective auditory attention to a desired speech stream may help in explaining these variabilities. In order to better understand the temporal dynamics of selective auditory attention, we developed an online auditory attention decoding (AAD) processing pipeline based on speech envelope tracking in the electroencephalogram (EEG). Participants had to attend to one audiobook story while a second one had to be ignored. Online AAD was applied to track the attention towards the target speech signal. Individual temporal attention profiles were computed by combining an established AAD method with an adaptive staircase procedure. The individual decoding performance over time was analysed and linked to behavioural performance as well as subjective ratings of listening effort, motivation, and fatigue. The grand average attended speaker decoding profile derived in the online experiment indicated performance above chance level. Parameters describing the individual AAD performance in each testing block indicated significant differences in decoding performance over time to be closely related to the behavioural performance in the selective listening task. Further, an exploratory analysis indicated that subjects with poor decoding performance reported higher listening effort and fatigue compared to good performers. Taken together our results show that online EEG based AAD in a complex listening situation is feasible. Adaptive attended speaker decoding profiles over time could be used as an objective measure of behavioural performance and listening effort. The developed online processing pipeline could also serve as a basis for future EEG based near real-time auditory neurofeedback systems.