Supporting Data for: Towards Sound Innovation Engines Using Pattern-Producing Networks and Audio Graphshttps://doi.org/10.18710/BAX9N5Jónsson, Björn ÞórGlette, KyrreErdem, ÇağrıFasciani, StefanoDataverseNO2024-01-182026-02-25T12:34:36ZData 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.Arts and HumanitiesComputer and Information ScienceSound SynthesisQuality Diversity SearchInnovation EnginesEnglishB. T. Jónsson, C. Erdem, S. Fasciani, and K. Glette, “Towards Sound Innovation Engines Using Pattern-Producing Networks and Audio Graphs,” in Artificial Intelligence in Music, Sound, Art and Design, vol. 14633, C. Johnson, S. M. Rebelo, and I. Santos, Eds., in Lecture Notes in Computer Science, vol. 14633. , Cham: Springer Nature Switzerland, 2024, pp. 211–227. doi: 10.1007/978-3-031-56992-0_14., doi, 10.1007/978-3-031-56992-0_14, https://link.springer.com/10.1007/978-3-031-56992-0_142024-01-18Jónsson, Björn ÞórRITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion2023-11-072023-03-012023-10-31Generation data, genomes and elite maps, from evolutionary simulations.Rendered sound objects from genomes discovered during evolutionary simulations.CC BY 4.0