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Orchestra in a Box: A System for Real-Time Musical Accompaniment

We describe a computer system that plays a responsive and sensitive accompaniment to a live musician in a piece of non-improvised music. The system of composed of three components “Listen,” “Anticipate” and “Synthesize.” Listen analyzes the soloist’s acoustic signal and estimates note onset times using a hidden Markov model. Synthesize plays a prerecorded audio file back at variable rate using a phase vocoder. Anticipate creates a Bayesian network that mediates between Listen and Synthesize. The system has a learning phase, analogous to a series of rehearsals, in which model parameters for the network are estimated from training data. In performance, the system synthesizes the musical score, the training data, and the on-line analysis of the soloist’s acoustic signal using a principled decision-making engine, based on the Bayesian network. A live demonstration will be given using the aria Mi Chiamano Mimi from Puccini’s opera La Bohème.