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.