Google Research

Learning to Create Piano Performances

NIPS 2017 Workshop on Machine Learning and Creativity


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

Learn more about how we do research

We maintain a portfolio of research projects, providing individuals and teams the freedom to emphasize specific types of work