The Continuator system is an attempt to bridge the gap between two classes of traditionally incompatible musical systems: 1) interactive musical systems, limited in their ability to generate stylistically consistent material, and 2) music composition systems, which are fundamentally not interactive. The purpose of Continuator is to extend the technical ability of musicians with stylistically consistent, automatically learnt musical material. This requires the ability for the system to build operational representations of musical styles in real time, and to adapt quickly to external musical information. The Continuator is based on a Markov model of musical styles augmented to account for efficient real time learning of musical styles and to arbitrary external bias. The paper describes the main technical issues at stake concerning the integration of an agnostic learning scheme in an interactive instrument, and reports on real-world experiments performed with various musicians.
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