The Combination of Neural Tracking and Alpha Power Lateralization for Auditory Attention Detection

J Speech Lang Hear Res. 2021 Sep 14;64(9):3603-3616. doi: 10.1044/2021_JSLHR-20-00608. Epub 2021 Aug 17.

Abstract

Purpose The acoustic source that is attended to by the listener in a mixture can be identified with a certain accuracy on the basis of their neural response recorded during listening, and various phenomena may be used to detect attention. For example, neural tracking (NT) and alpha power lateralization (APL) may be utilized in order to obtain information concerning attention. However, these methods of auditory attention detection (AAD) are typically tested in different experimental setups, which makes it impossible to compare their accuracy. The aim of this study is to compare the accuracy of AAD based on NT, APL, and their combination for a dichotic natural speech listening task. Method Thirteen adult listeners were presented with dichotic speech stimuli and instructed to attend to one of them. Electroencephalogram of the subjects was continuously recorded during the experiment using a set of 32 active electrodes. The accuracy of AAD was evaluated for trial lengths of 50, 25, and 12.5 s. AAD was tested for various parameters of NT- and APL-based modules. Results The obtained results suggest that NT of natural running speech provides similar accuracy to APL. The statistically significant improvement of the accuracy of AAD using a combined method has been observed not only for the longest duration of test samples (50 s, p = .005) but also for shorter ones (25 s, p = .011). Conclusions It seems that the combination of standard NT and APL significantly increases the effectiveness of accurate identification of the traced signal perceived by a listener under dichotic conditions. It has been demonstrated that, under certain conditions, the combination of NT and APL may provide a benefit for AAD in cocktail party scenarios.

MeSH terms

  • Acoustic Stimulation
  • Adult
  • Attention
  • Auditory Perception
  • Electroencephalography
  • Humans
  • Speech
  • Speech Perception*