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dc.contributor.authorHermann, Thomas
dc.date.accessioned2018-07-25T18:07:24Z
dc.date.available2018-07-25T18:07:24Z
dc.date.issued2018-06
dc.identifier.citationHermann, T. "Wave Space Sonification". Presented at the 24th International Conference on Auditory Display (ICAD2018), June 10-15, 2018, Michigan Technological University, Houghton, MI, USA.en_US
dc.identifier.urihttp://hdl.handle.net/1853/60087
dc.description.abstractThis paper introducesWave Space Sonification (WSS), a novel class of sonification techniques for time- (or space-) indexed data. WSS doesn’t fall into the classes of Audification, Parameter- Mapping Sonification or Model-based Sonification and thus constitutes a novel class of sonification techniques. It realizes a different link between data and their auditory representation, by scanning a scalar field – defined as wave space – along a data-driven trajectory. This allows both the highly controlled definition of the auditory representation for any area of interest, as well as subtle yet acoustically complex sound variations as the overall pattern changes. To illustrate Wave Space Sonification (WSS), we introduce three different WSS instances, (i) the Static Canonical WSS, (ii) Data-driven Localized WSS and (iii), Granular Wave Space Sonification (GWSS), and we demonstrate the different methods with sonification examples from various data domains. We discuss the technique and its relation to other sonification approaches and finally outline productive application areas.en_US
dc.publisherGeorgia Institute of Technologyen_US
dc.rightsLicensed under Creative Commons Attribution Non-Commercial 4.0 International License.en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectAuditory displayen_US
dc.subjectWSSen_US
dc.subjectNovel sonification techniquesen_US
dc.titleWave Space Sonificationen_US
dc.typeProceedingsen_US
dc.contributor.corporatenameBielefeld University. Ambient Intelligence Groupen_US
dc.publisher.originalInternational Community on Auditory Display
dc.identifier.doihttps://doi.org/10.21785/icad2018.026en_US


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Licensed under Creative Commons Attribution Non-Commercial 4.0 International License.
Except where otherwise noted, this item's license is described as Licensed under Creative Commons Attribution Non-Commercial 4.0 International License.