Music Generation from Statistical Models

Abstract

This paper discusses the use of statistical models for the problem of musical style imitation. Statistical models are created from extant pieces in a stylistic corpus, and have an objective goal which is to accurately classify new pieces. The process of music generation is equated with the problem of sampling from a statistical model. In principle there is no need to make the classical distinction between analytic and synthetic models of music. This paper presents several methods for sampling from an analytic statistical model, and proposes a new approach that maintains the intra opus pattern repetition within an extant piece. A major component of creativity is the adaptation of extant art works, and this is also an efficient way to sample pieces from complex statistical models.