Using Factor Oracles for Machine Improvisation

Gérard Assayag, Shlomo Dubnov

Abstract: We describe variable markov models we have used for statistical learning of musical sequences, then we present the factor oracle, a data structure proposed by Crochemore & al for string matching. We show the relation between this structure and the previous models and indicate how it can be adapted for learning musical sequences and generating improvisations in a real-time context.