Jump to Content

Learning to Create Piano Performances

Sageev Oore
Sander Dieleman
NIPS 2017 Workshop on Machine Learning and Creativity
Google Scholar

Abstract

Nearly all previous work on music generation has focused on creating pieces that are, effectively, musical scores. In contrast, we learn to create piano performances: besides predicting the notes to be played, we also predict expressive variations in the timing and musical dynamics (loudness). We provided samples generated by our system for informal feedback to a set of professional musicians and composers, and the samples were well-received. Overall, the comments indicate that our system is generating music that, while lacking high-level structure, does indeed sound very much like human performance, and is closely reminiscent of the classical piano repertoire.

Research Areas