Creative Improvised Interaction with Generative Musical Systems

Shlomo Dubnov, Gerard Assayag, Vignesh Gokul

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In this paper we survey the methods for control and cre-ative interaction with pre-trained generative models for au-dio and music. By using reduced (lossy) encoding and sym-bolization steps we are able to examine the level of information that is passing between the environment (the musician) and the agent (machine improvisation). We further use the concept of music information dynamics to find an optimal symbolization in terms of predictive information measure. Methods and strategies for generative models are surveyed in this paper and their implications for creative interaction with the machine are discussed in the musical improvisation framework.

Original languageEnglish
Title of host publicationProceedings - 5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022
PublisherInstitute of Electrical and Electronics Engineers
Pages121-126
Number of pages6
ISBN (Electronic)9781665495486
DOIs
StatePublished - 1 Jan 2022
Externally publishedYes
Event5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022 - Virtual, Online, United States
Duration: 2 Aug 20224 Aug 2022

Publication series

NameProceedings - 5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022

Conference

Conference5th International Conference on Multimedia Information Processing and Retrieval, MIPR 2022
Country/TerritoryUnited States
CityVirtual, Online
Period2/08/224/08/22

Keywords

  • Creative Interaction
  • Distributed Co Creativity
  • Generative Models
  • Music Synthesis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing
  • Safety, Risk, Reliability and Quality
  • Media Technology

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