Music Plus One

par/by Christopher Raphael
School of Informatics
Indiana University

I will discuss my ongoing work in creating a computer system that simulates a sensitively conducted orchestra in a non-improvisatory composition for soloist and orchestra. My accompaniment system synthesizes a number of knowledge sources including the musical score, on-line analysis of the soloist's performance, and the musical interpretations demonstrated by both the soloist and orchestra in rehearsal. I present a probabilistic model --- a Bayesian Belief Network that represents these disparate knowledge sources in a coherent framework. During live performance, my system "listens" to the soloist by using a hidden Markov model and conducts the orchestra through principled real-time decision-making engine that incorporates all currently available information for each decision. I will provide a live demonstration of my system.