Young, Michael W.. 2007. 'NN Music: Improvising with a 'Living' Computer'. In: International Computer Music Conference. San Francisco 2007. [Conference or Workshop Item]

Preview	Text (Publisher's version. Copyright the author.) ICMCYoung07.pdf Download (167kB) | Preview
Preview	Text (Poster. Copyright the author.) ICMCYoung07poster.pdf Download (412kB) | Preview

Abstract or Description

This paper proposes attributes of a living computer music, the product of a live algorithm. It illustrates how these attributes can inform creative design with reference to a real-time system for solo performer-machine collaboration, Neural Network Music, and the PQƒ framework proposed for live algorithms. Improvisation is treated as a classification problem at a high level of musical behaviour which can be measured statistically and train a multilayer perceptron neural network. Network outputs shape a stochastic-based synthesis engine. Mappings are covertly assigned, revisited by both player and machine as a performance develops. As the timing and choice of mapping is unknown, both participants are invited to learn and adapt to a responsive sonic environment which is created afresh on each performance. This offers a novel real-time application of feed-forward neural networks and a challenging, creative technological platform for freely improvised music.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Originally published in Proceedings of the conference, ISBN 0-973192-5-1. Copyright remains with the author.
Keywords:	improvised music; neural networks
Departments, Centres and Research Units:	Music
Dates:	Date Event 2007 Published
Event Location:	San Francisco
Date range:	2007
Item ID:	111
Date Deposited:	21 Apr 2008 17:21
Last Modified:	29 Apr 2020 15:28
URI:	https://research.gold.ac.uk/id/eprint/111

View statistics for this item...

Edit Record (login required)