Learning to Create Piano Performances

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