Machine learning and music generation

Abstract

Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods which model style through explicitly formalized rules, and data mining methods which apply machine learning to induce statistical models of musical style.