Computer-Based Music Research: Artificial Intelligence Models of Musical Expression (START-Programm)

The goal of this project is to use Artificial Intelligence methods to study the phenomenon of expressive music performance. The focus of the project is on developing and using machine learning and data mining methods for the analysis of expressive performance data. The goal is to gain a deeper understanding of this complex domain of human competence and to contribute new methods to the (relatively new) branch of musicology that tries to develop quantitative models and theories of musical expression. By musical expression, we mean the variations in tempo, timing, dynamics, articulation, etc. that performers apply when playing and ``interpreting'' a piece. Our goal is to study real expressive performances with machine learning methods, in order to discover some fundamental patterns or principles that characterize ``sensible'' musical performances, and to elucidate the relation between structural aspects of the music and typical or musically ``sensible'' performance patterns. The ultimate result would be a formal model that explains or predicts those aspects of expressive variation that seem to be common to most typical performances and can thus be regarded as fundamental principles.