Tools
ToolsGingrich, O., Renaud, A., Emets, E., Soraghan, S. and Villanueva-Ablanedo, D., 2020. KIMA: The Wheel—Voice Turned into Vision: A participatory, immersive visual soundscape installation. Leonardo, 53 (5), 479-484.
Full text available as:
|
PDF
LeonardoPaper_Redacted.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. 8MB | |
|
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
DOI: 10.1162/leon_a_01698
Abstract
Over the last five years, KIMA, an art and research project on sound and vision, has investigated visual properties of sound. Previous iterations of KIMA focused on digital representations of cymatics—physical sound patterns—as medium for performance. The current development incorporates neural networks and machine learning strategies to explore visual expressions of sound in participatory music creation. The project, displayed on a 360 degree canvas at the London Roundhouse, prompted the audience to explore their own voice as intelligent, real-time visual representation. Machine learning algorithms played a key role in meaningful interpretation of sound as visual form. The resulting immersive performance turned the audience into co-creators of the piece.
| Item Type: | Article |
|---|---|
| ISSN: | 0024-094X |
| Uncontrolled Keywords: | Sound Art; Immersive Sound; Visual Sound; Participatory Art; Machine Learning |
| Group: | Faculty of Media & Communication |
| ID Code: | 31795 |
| Deposited By: | Symplectic RT2 |
| Deposited On: | 15 Feb 2019 16:50 |
| Last Modified: | 14 Mar 2022 14:14 |
Downloads
Downloads per month over past year
| Repository Staff Only - |