Abstract

This article presents a long-term inter-disciplinary research project situated at the intersection of the scientific disciplines of Musicology and Artificial Intelligence. The goal is to develop AI, and in particular machine learning and data mining, methods to study the complex phenomenon of expressive music performance. Formulating formal, quantitative models of expressive performance is one of the big open research problems in contemporary (empirical and cognitive) musicology. Our project develops a new direction in this field: we use inductive learning techniques to discover general and valid expression principles from (large amounts of) real performance data. The project is currently starting its third year and is planned to continue for at least four more years. In the

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