An Automated Music Improviser Using a Genetic Algorithm Driven Synthesis Engine

  • Matthew John Yee-King
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4448)


This paper describes an automated computer improviser which attempts to follow and improvise against the frequencies and timbres found in an incoming audio stream. The improviser is controlled by an ever changing set of sequences which are generated by analysing the incoming audio stream (which may be a feed from a live musician) for its physical and musical properties such as pitch and amplitude. Control data from these sequences is passed to the synthesis engine where it is used to configure sonic events. These sonic events are generated using sound synthesis algorithms designed by an unsupervised genetic algorithm where the fitness function compares snapshots of the incoming audio to snapshots of the audio output of the evolving synthesizers in the spectral domain in order to drive the population to match the incoming sounds. The sound generating performance system and sound designing evolutionary system operate in real time in parallel to produce an interactive stream of synthesised sound. An overview of related systems is provided, this system is described then some preliminary results are presented.


Synthesis Algorithm Target Sound Music Information Retrieval Audio Output Interactive Genetic Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Matthew John Yee-King
    • 1
  1. 1.Creative Systems Lab, Department of Informatics, University of Sussex, BrightonUK

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