Music-induced emotions can be predicted from a combination of brain activity and acoustic features.
Daly, Ian a,*; Williams, Duncan b; Hallowell, James a; Hwang, Faustina a; Kirke, Alexis b; Malik, Asad a; Weaver, James a; Miranda, Eduardo b; Nasuto, Slawomir J. a
[Article] Brain & Cognition. 101 Supplement C:1-11, December 2015.

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: It is widely acknowledged that music can communicate and induce a wide range of emotions in the listener. However, music is a highly-complex audio signal composed of a wide range of complex time- and frequency-varying components. Additionally, music-induced emotions are known to differ greatly between listeners. Therefore, it is not immediately clear what emotions will be induced in a given individual by a piece of music.

We attempt to predict the music-induced emotional response in a listener by measuring the activity in the listeners electroencephalogram (EEG). We combine these measures with acoustic descriptors of the music, an approach that allows us to consider music as a complex set of time-varying acoustic features, independently of any specific music theory. Regression models are found which allow us to predict the music-induced emotions of our participants with a correlation between the actual and predicted responses of up to Symbol.

(C) 2015Elsevier, Inc.