A Brain-Computer Interface for Improving Auditory Attention in Multi-Talker Environments.

ABSTRACT: There is significant research in accurately determining the focus of a listener's attention in a multi-talker environment using auditory attention decoding (AAD) algorithms. These algorithms rely on neural signals to identify the intended speaker, assuming that these signals consistently reflect the listener's focus. However, some listeners struggle with this competing talkers task, leading to suboptimal tracking of the desired speaker due to potential interference from distractors. The goal of this study was to enhance a listener's attention to the target speaker in real time and investigate the underlying neural bases of this improvement. This paper describes a closed-loop neurofeedback system that decodes the auditory attention of the listener in real time, utilizing data from a non-inv

SUBMITTER: Haro S 

PROVIDER: S-EPMC12629276 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature