A study of control methods for percussive sound synthesis based on gans
Mostra el registre complet Registre parcial de l'ítem
- dc.contributor.author Ramires, António
- dc.contributor.author Juras, Jordan
- dc.contributor.author Parker, Julian D.
- dc.contributor.author Serra, Xavier
- dc.date.accessioned 2023-02-10T07:36:27Z
- dc.date.available 2023-02-10T07:36:27Z
- dc.date.issued 2022
- dc.description Comunicació presentada a 25th International Conference on Digital Audio Effects (DAFx20in22), celebrat del 6 al 10 de setembre de 2022 a Viena, Àustria.
- dc.description.abstract The process of creating drum sounds has seen significant evolution in the past decades. The development of analogue drum synthesizers, such as the TR-808, and modern sound design tools in Digital Audio Workstations led to a variety of drum timbres that defined entire musical genres. Recently, drum synthesis research has been revived with a new focus on training generative neural networks to create drum sounds. Different interfaces have previously been proposed to control the generative process, from low-level latent space navigation to high-level semantic feature parameterisation, but no comprehensive analysis has been presented to evaluate how each approach relates to the creative process. We aim to evaluate how different interfaces support creative control over drum generation by conducting a user study based on the Creative Support Index. We experiment with both a supervised method that decodes semantic latent space directions and an unsupervised Closed-Form Factorization approach from computer vision literature to parameterise the generation process and demonstrate that the latter is the preferred means to control a drum synthesizer based on the StyleGAN2 network architecture.
- dc.description.sponsorship This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska Curie grant agreement No 765068, MIP-Frontiers.
- dc.format.mimetype application/pdf
- dc.identifier.citation Ramires A, Juras J, Parker JD, Serra X. A study of control methods for percussive sound synthesis based on gans. In: Evangelista G, Holighaus N, editors. Proceedings of the 25th International Conference on Digital Audio Effects (DAFx20in22); 2022 Sep 6-10; Vienna, Austria. [Vienna]: DAFx; 2022. p. 224-31.
- dc.identifier.issn 2413-6700
- dc.identifier.uri http://hdl.handle.net/10230/55717
- dc.language.iso eng
- dc.publisher Institute of Electrical and Electronics Engineers (IEEE)
- dc.relation.ispartof Evangelista G, Holighaus N, editors. Proceedings of the 25th International Conference on Digital Audio Effects (DAFx20in22); 2022 Sep 6-10; Vienna, Austria. [Vienna]: DAFx; 2022. p. 224-31.
- dc.relation.isreferencedby https://github.com/AudioCommons/timbral_models
- dc.relation.isreferencedby https://aframires.github.io/stylegan2-ada-pytorch/
- dc.relation.isreferencedby https://github.com/AudioCommons/ac-audio-extractor
- dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/765068
- dc.rights © 2022 António Ramires et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, adaptation, and reproduction in any medium, provided the original author and source are credited.
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by/4.0/
- dc.subject.other Música--Aspectes fisiològics
- dc.title A study of control methods for percussive sound synthesis based on gans
- dc.type info:eu-repo/semantics/article
- dc.type.version info:eu-repo/semantics/publishedVersion