Researchers at the Viterbi School of Engineering of the University of Southern California conducted studies using AI to explain the effects of music on our mind, body, and emotions.
There’s a song for every mood and event. But, why we feel what we feel when listening to a certain kind of music or song? Why some songs make us happy, energetic and others emotional, and so forth? Well, we may have finally an answer to these questions, courtesy Artificial Intelligence.
Different kinds of audio musical features were predictive of different response types (neural, physiological and self-reported judgments). This finding gives credence to using a multi-pronged, multi-perspective approach to studying music listening experiences; in other words, different aspects of music affect our brain, body, and behavior, and affect the measured responses in different ways.
Tim Greer, lead author of the study and computer science PhD student at the University of Southern California and a member of the USC Signal Analysis and Interpretation Laboratory (SAIL).
The study began by selecting 120 pieces with the words “happy” or “sad” and which were judged by eight human judges. The pieces in which at least 75% of the human judges agreed on were included in another survey. Finally, a happy song, a sad short song and a sad long song was chosen.
These three songs were then listened to by 40 adult participants and their brains were scanned through an MRI scanner through this process. For a physiological response, the same process was followed among 60 different participants with their heart activity and electrodermal (activity) skin conductance collected. Each song was listened to twice, once for rating emotion and the other for enjoyment.
Researchers believe that this study can be applied to areas like scientific music studies, understanding different music emotions and music therapy. It could also help the music industry for composers to understand how they can get a better response from the audience.
