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GECCO
2007
Springer

Inducing a generative expressive performance model using a sequential-covering genetic algorithm

9 years 8 months ago
Inducing a generative expressive performance model using a sequential-covering genetic algorithm
In this paper, we describe an evolutionary approach to inducing a generative model of expressive music performance for Jazz saxophone. We begin with a collection of audio recordings of real Jazz saxophone performances from which we extract a symbolic representation of the musician’s expressive performance. We then apply an evolutionary algorithm to the symbolic representation in order to obtain computational models for different aspects of expressive performance. Finally, we use these models to automatically synthesize performances with the expressiveness that characterizes the music generated by a professional saxophonist. Categories and Subject Descriptors J.5 [Computer Applications]: Arts and Humanities General Terms Algorithms Keywords Genetic Algorithms, Expressive Music Performance
Rafael Ramirez, Amaury Hazan
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where GECCO
Authors Rafael Ramirez, Amaury Hazan
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