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
Autore principale: Roma, Gerard
Altri autori: Xambó, Anna, Green, Owen, Tremblay, Pierre Alexandre
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MDPI AG
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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 
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