Controlling musical emotionality: an affective computational architecture for influencing musical emotions

Abstract

Emotions are a key part of creative endeavours, and a core problem for computational models of creativity. In this paper we discuss an affective computing architecture for the dynamic modification of music with a view to predictably affecting induced musical emotions. Extending previous work on the modification of perceived emotions in music, our system architecture aims to provide reliable control of both perceived and induced musical emotions: its emotionality. A rule-based system is used to modify a subset of musical features at two processing levels, namely score and performance. The interactive model leverages sensed listener affect by adapting the emotionality of the music modifications in real-time to assist the listener in reaching a desired emotional state.