NN Music: Improvising with a `Living' Computer

Authors:
Michael Young
Affiliations:
Music Department, Goldsmiths, University of London, London, UK SE14 6NW
Venue:
Computer Music Modeling and Retrieval. Sense of Sounds
Year:
2008

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Abstract

A live algorithm describes an ideal autonomous performance system able to engage in performance with abilities analogous, if not identical, to a human musician. This paper proposes five attributes of a live algorithm: adaptability, empowerment, intimacy, opacity and unimagined music. These attributes are explored in NN Music, a performer-machine system for Max/MSP that fosters listening and learning. Live improvisation is encoded statistically to train a feed-forward neural network, mapped to stochastic processes for musical output. Through adaptation, mappings are learnt and covertly assigned, to be revisited by both player and machine as a performance develops.