Online EEG-Based Emotion Prediction and Music Generation for Inducing Affective States

抄録

Music is often used for emotion induction because it can change the emotions of people. However, since we subjectively feel different emotions when listening to music, we propose an emotion induction system that generates music that is adapted to each individual. Our system automatically generates suitable music for emotion induction based on the emotions predicted from an electroencephalogram (EEG). We examined three elements for constructing our system: 1) a music generator that creates music that induces emotions that resemble the inputs, 2) emotion prediction using EEG in real-time, and 3) the control of a music generator using the predicted emotions for making music that is suitable for inducing emotions. We constructed our proposed system using these elements and evaluated it. The results showed its effectiveness for inducing emotions and suggest that feedback loops that tailor stimuli to individuals can successfully induce emotions.