Evaluation Rules for Evolutionary Generation of Drum Patterns in Jazz Solos

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10198)

Abstract

The learning of improvisation in jazz and other music styles requires years of practice. For music scholars which do not play in a band, technical solutions for automatic generation of accompaniment on home computers are very helpful. They may support the learning process and significantly improve the experience to play with other musicians. However, many up-to-date approaches can not interact with a solo player, generating static or random patterns without a direct musical dialogue between a soloist and accompanying instruments. In this paper, we present a novel system for the generation of drum patterns based on an evolutionary algorithm. As the main extension to existing solutions, we propose a set of musically meaningful jazz-related rules for the real-time validation and adjustment of generated drum patterns. In the evaluation study, musicians agreed that the system can be successfully used for learning of jazz improvisation and that the wide range of parameters helps to adapt the response of the virtual drummer to the needs of individual scholars (Examples of generated music are available at http://sig-ma.de/wp-content/uploads/2017/01/JazzDrumPatterns.zip.).

Keywords

Evolutionary music generation Rhythm generation Jazz solo accompaniment 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Fabian Ostermann
    • 1
  • Igor Vatolkin
    • 1
  • Günter Rudolph
    • 1
  1. 1.Fakultät für InformatikTechnische Universität DortmundDortmundGermany

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