Context-Aware Algorithmic Composition in the Style of Classical Composers using Machine Learning

Abstract

This paper describes the development of a framework for generating classical music in a given style by training on compositions using an Recurrent Neural Network. We detail a novel technique of encoding sequences of musical notes into sequences of vectors suitable for training, in a way that preserves certain high-level music properties such as key and time signature. We then present the architecture of the neural network used and how we train on notes encoded in this way.