Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/29353
Appears in Collections:Computing Science and Mathematics Conference Papers and Proceedings
Author(s): Brownlee, Alexander E I
Kim, Suk-Jun
Wang, Szu-Han
Chan, Stella
Lawson, Jamie A
Contact Email: alexander.brownlee@stir.ac.uk
Title: Crowd-Sourcing the Sounds of Places with a Web-Based Evolutionary Algorithm
Citation: Brownlee AEI, Kim S, Wang S, Chan S & Lawson JA (2019) Crowd-Sourcing the Sounds of Places with a Web-Based Evolutionary Algorithm. In: GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO 2019: The Genetic and Evolutionary Computation Conference, Prague, Czech Republic, 13.07.2019-17.07.2019. New York: ACM, pp. 131-132. https://doi.org/10.1145/3319619.3322028
Issue Date: Jul-2019
Conference Name: GECCO 2019: The Genetic and Evolutionary Computation Conference
Conference Dates: 2019-07-13 - 2019-07-17
Conference Location: Prague, Czech Republic
Abstract: The sounds we associate with particular places are tightly interwoven with our memories and sense of belonging. We describe a platform designed to assist in gathering the sounds a group of people associate with a place. A web-based evolutionary algorithm, with human-in-the-loop fitness evaluations, ranks and recombines sounds to find collections that the group rates as familiar. An experiment covering four geographical locations shows that the process does indeed find sounds deemed familiar by participants.
Status: AM - Accepted Manuscript
Rights: © ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO 2019: The Genetic and Evolutionary Computation Conference, Prague, Czech Republic, 13.07.2019-17.07.2019. New York: ACM, pp. 131-132 http://doi.acm.org/10.1145/3319619.3322028

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