Auditory Attention Decoding in Four-Talker Environment with EEG

Auditory Attention Decoding (AAD) is a technique that determines the focus of a listener's attention in complex auditory scenes according to cortical neural responses. Existing research largely examines two-talker scenarios, insufficient for real-world complexity. This study introduced a new AAD database for a four-talker scenario with speeches from four distinct talkers simultaneously presented and spatially separated, and listeners' EEG was recorded. Temporal response functions (TRFs) analysis showed that attended speech TRFs are stronger than each unattended speech. AAD methods based on stimulus-reconstruction (SR) and cortical spatial lateralization were employed and compared. Results indicated decoding accuracy of 77.5% in 60s (chance level of 25%) using SR. Using auditory spatial attention detection (ASAD) methods also indicated high accuracy (94.7% with DenseNet-3D in 1s), demonstrating ASAD methods' generalization performance.