Crowd-sourcing the sounds of places with a web-based evolutionary algorithm

Alexander E.I. Brownlee, Suk Jun Kim, Szu Han Wang, Stella Chan, Jamie A. Lawson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 itness evaluations, ranks and recombines sounds to ind collections that the group rates as familiar. An experiment covering four geographical locations shows that the process does indeed ind sounds deemed familiar by participants.

Original languageEnglish
Title of host publicationGECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery, Inc
Pages131-132
Number of pages2
ISBN (Electronic)9781450367486
DOIs
Publication statusPublished - 13 Jul 2019
Event2019 Genetic and Evolutionary Computation Conference, GECCO 2019 - Prague, Czech Republic
Duration: 13 Jul 201917 Jul 2019

Publication series

NameGECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion

Conference

Conference2019 Genetic and Evolutionary Computation Conference, GECCO 2019
CountryCzech Republic
CityPrague
Period13/07/1917/07/19

Keywords

  • Human-in-the-loop
  • Mood
  • Sound
  • Soundscapes

Fingerprint Dive into the research topics of 'Crowd-sourcing the sounds of places with a web-based evolutionary algorithm'. Together they form a unique fingerprint.

  • Cite this

    Brownlee, A. E. I., Kim, S. J., Wang, S. H., Chan, S., & Lawson, J. A. (2019). Crowd-sourcing the sounds of places with a web-based evolutionary algorithm. In GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion (pp. 131-132). (GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion). Association for Computing Machinery, Inc. https://doi.org/10.1145/3319619.3322028