Published November 13, 2023 | Version v1
Conference paper Open

Emotional Impact of Source Localization in Music Using Machine Learning and EEG: a proof-of-concept study


Little is currently known about how varied source locations affect a listener's emotional reaction to music. Here, using spectral features extracted from electrophysiology (EEG) data, we tested through machine learning whether four music source positions (front, back, left, and right) could be accurately distinguished according to the type of valence in a subject-wise manner. The findings demonstrate that distinct EEG correlates can reliably classify the four source locations and that the effect is stronger when music with a negative emotional valence is played outside of the listener's visual field. This proof-of-concept study may pave the way for advanced spatial audio analysis approaches in music information retrieval by considering the listener's emotional impact depending on the source direction of incidence.



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