Master 2013 2014
Stages de la spécialité SAR
Live algorithms with complexity matching

Site :Goldsmiths, Computing Department
Lieu :Goldsmiths University, Computing Department
Encadrant : Tim Blackwell
Dates :01/03/2014 au 31/07/2014
Rémunération :none
Mots-clés : Parcours ATIAM : Informatique musicale


This project aims to develop a live algorithm (autonomous machine improviser) that uses complexity measures to match internally generated music to the incoming music stream. The system would have to (a) measure the complexity (Kolmogorov, as estimated by LZ compression, Shannon entropy, entropy rate, excess entropy...) of incoming audio and/or midi, and (b) find matching content, either by using a complexity measure as a fitness function, or by tuning pre-calibrated parameters.


P. Crutchfield and D. P. Feldman, "Regularities Unseen, Randomness Observed : Levels of Entropy Convergence", CHAOS 13:1 (2003) 25-54.

Li, Ming and Sleep, M. Ronan (2004) Melody Classification using a Similarity Metric based on Kolmogorov Complexity. In : Proceedings of the Sound and Music Computing Conference (SMC’04), 2004-10-20 - 2004-10-22, Paris.

Ming Li and Ronan Sleep. Genre classification via an lz78-based string kernel. In : Proceedings of the 6th International Conference on Music Information Retrieval (ISMIR 2005), pp252-259

Music Complexity : A multi-faceted description of audio content. Sebastian Streich, PhD thesis, Universitat Pompeu Fabra, 2006

Young, M. and Blackwell, T. ’Live Algorithms for Music : Can Computers Be Improvisers ?’ in George E. Lewis and Benjamin Piekut (eds) Oxford Handbook of Critical Improvisation Studies, Vols. 1&2. New York : Oxford University Press. 2014. DOI : 10.1093/oxfordhb/9780199892921.013.002 

Blackwell, T., Young, M. and Bown, O. ’Live Algorithms’, in J. McCormack, M.D’Inverno and M.Boden (eds), Computers and Creativity. Springer, Berlin 2012. ISBN 978-3-642-31726-2