Influencing the perceived emotions of music with intent

Music is an immensely powerful affective medium that pervades our everyday life. With ever advancing technology, the reproduction and application of music for emotive and information transfer purposes has never been more prevalent. In this paper we introduce a rule-based engine for influencing the perceived emotions of music. Based on empirical music psychology, we attempt to formalise the relationship between musical elements and their perceived emotion. We examine the modification to structural aspects of music to allow for a graduated transition between perceived emotive states. This engine is intended to provide music reproduction systems with a finer grained control over this affective medium; where perceived musical emotion can be influenced with intent. This intent comes from both an external application and the audience. Using a series of affective computing technologies, an audience’s response metrics and attitudes can be incorporated to model this intent. A generative feedback loop is set up between the external application, the influencing process and the audience’s response to this, which together shape the modification of musical structure. The effectiveness of our rule system for influencing perceived musical emotion was examined in earlier work, with a small test study providing generally encouraging results