A General Framework for Visualization of Sound Collections in Musical Interfaces
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| Pubblicato in: | Applied Sciences vol. 11, no. 24 (2021), p. 11926 |
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| Autore principale: | |
| Altri autori: | , , |
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MDPI AG
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| Accesso online: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 045 | 2 | |b d20210101 |b d20211231 | |
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| 100 | 1 | |a Roma, Gerard |u Centre for Research into New Music (CeReNeM), University of Huddersfield, Huddersfield HD1 3DH, UK; <email>o.green@hud.ac.uk</email> (O.G.); <email>p.a.tremblay@hud.ac.uk</email> (P.A.T.) | |
| 245 | 1 | |a A General Framework for Visualization of Sound Collections in Musical Interfaces | |
| 260 | |b MDPI AG |c 2021 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a While audio data play an increasingly central role in computer-based music production, interaction with large sound collections in most available music creation and production environments is very often still limited to scrolling long lists of file names. This paper describes a general framework for devising interactive applications based on the content-based visualization of sound collections. The proposed framework allows for a modular combination of different techniques for sound segmentation, analysis, and dimensionality reduction, using the reduced feature space for interactive applications. We analyze several prototypes presented in the literature and describe their limitations. We propose a more general framework that can be used flexibly to devise music creation interfaces. The proposed approach includes several novel contributions with respect to previously used pipelines, such as using unsupervised feature learning, content-based sound icons, and control of the output space layout. We present an implementation of the framework using the SuperCollider computer music language, and three example prototypes demonstrating its use for data-driven music interfaces. Our results demonstrate the potential of unsupervised machine learning and visualization for creative applications in computer music. | |
| 653 | |a Software | ||
| 653 | |a Musicians & conductors | ||
| 653 | |a Signal processing | ||
| 653 | |a Audio recordings | ||
| 653 | |a Digital audio workstations | ||
| 653 | |a Visualization | ||
| 653 | |a Sound | ||
| 653 | |a Musical instruments | ||
| 653 | |a Magnetic tape | ||
| 653 | |a Machine learning | ||
| 653 | |a Computer music | ||
| 653 | |a Design | ||
| 653 | |a Algorithms | ||
| 653 | |a Interfaces | ||
| 700 | 1 | |a Xambó, Anna |u Music, Technology and Innovation (MTI<sup>2</sup>), De Montfort University, Leicester LE1 9BH, UK; <email>anna.xambo@dmu.ac.uk</email> | |
| 700 | 1 | |a Green, Owen |u Centre for Research into New Music (CeReNeM), University of Huddersfield, Huddersfield HD1 3DH, UK; <email>o.green@hud.ac.uk</email> (O.G.); <email>p.a.tremblay@hud.ac.uk</email> (P.A.T.) | |
| 700 | 1 | |a Tremblay, Pierre Alexandre |u Centre for Research into New Music (CeReNeM), University of Huddersfield, Huddersfield HD1 3DH, UK; <email>o.green@hud.ac.uk</email> (O.G.); <email>p.a.tremblay@hud.ac.uk</email> (P.A.T.) | |
| 773 | 0 | |t Applied Sciences |g vol. 11, no. 24 (2021), p. 11926 | |
| 786 | 0 | |d ProQuest |t Publicly Available Content Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2612738872/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/2612738872/fulltextwithgraphics/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2612738872/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |