Supporting Data for: Towards Sound Innovation Engines Using Pattern-Producing Networks and Audio Graphs

DOI

Data accompanying the article Towards Sound Innovation Engines Using Pattern-Producing Networks and Audio Graphs. The Innovation Engine algorithm is used to evolve sounds, where Quality Diversity search is guided by the YAMNet classifier to discover sounds.

This study proposes the application of a system for generative sound synthesis that automates the discovery of inspiring sounds using Quality Diversity algorithms and a discriminative model inspired by the Innovation Engine algorithm. The approach addresses the challenges composers face in creating and refining new tools to achieve their musical goals. By promoting diversity and fostering serendipitous discoveries, the proposed approach expands the composer’s palette and makes the entirety of the sonic domain more accessible. The study presents generated sound objects through an online explorer and as rendered sound files, as well as an experimental application showcasing the creative potential of the discovered sounds. Our proposed approach offers a promising direction for sonic design that embraces automation, serendipity, and creativity.

kromosynth-cli, 1.0.8

Identifier
DOI https://doi.org/10.18710/BAX9N5
Related Identifier IsCitedBy https://doi.org/10.1007/978-3-031-56992-0_14
Metadata Access https://dataverse.no/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.18710/BAX9N5
Provenance
Creator Jónsson, Björn Þór ORCID logo; Glette, Kyrre ORCID logo; Erdem, Çağrı ORCID logo; Fasciani, Stefano ORCID logo
Publisher DataverseNO
Contributor Jónsson, Björn Þór; University of Oslo; RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion
Publication Year 2024
Funding Reference The Research Council of Norway 262762
Rights CC0 1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Contact Jónsson, Björn Þór (University of Oslo)
Representation
Resource Type Generation data, genomes and elite maps, from evolutionary simulations.; Dataset
Format text/markdown; text/plain; application/zip; application/x-xz; text/x-sh; application/octet-stream
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Version 1.2
Discipline Humanities