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Multilevel Annoyance Modelling of Short Environmental Sound Recordings

Author

Listed:
  • Ferran Orga

    (Grup de recerca en Tecnologies Mèdia, La Salle—URL, Quatre Camins, 30, 08022 Barcelona, Spain
    These authors contributed equally to this work and share the first author position.)

  • Andrew Mitchell

    (Institute for Environmental Design and Engineering, The Bartlett, University College London (UCL), Central House, 14 Upper Woburn Place, London WC1H 0NN, UK
    These authors contributed equally to this work and share the first author position.)

  • Marc Freixes

    (Grup de recerca en Tecnologies Mèdia, La Salle—URL, Quatre Camins, 30, 08022 Barcelona, Spain)

  • Francesco Aletta

    (Institute for Environmental Design and Engineering, The Bartlett, University College London (UCL), Central House, 14 Upper Woburn Place, London WC1H 0NN, UK)

  • Rosa Ma Alsina-Pagès

    (Grup de recerca en Tecnologies Mèdia, La Salle—URL, Quatre Camins, 30, 08022 Barcelona, Spain)

  • Maria Foraster

    (ISGlobal, Parc de Recerca Biomèdica de Barcelona (PRBB), Doctor Aiguader, 88, 08003 Barcelona, Spain
    Universitat Pompeu Fabra (UPF), 08018 Barcelona, Spain
    CIBER Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
    PHAGEX Research Group, Blanquerna School of Health Science, Universitat Ramon Llull, 08025 Barcelona, Spain)

Abstract

The recent development and deployment of Wireless Acoustic Sensor Networks (WASN) present new ways to address urban acoustic challenges in a smart city context. A focus on improving quality of life forms the core of smart-city design paradigms and cannot be limited to simply measuring objective environmental factors, but should also consider the perceptual, psychological and health impacts on citizens. This study therefore makes use of short (1–2.7 s) recordings sourced from a WASN in Milan which were grouped into various environmental sound source types and given an annoyance rating via an online survey with N = 100 participants. A multilevel psychoacoustic model was found to achieve an overall R 2 = 0.64 which incorporates Sharpness as a fixed effect regardless of the sound source type and Roughness, Impulsiveness and Tonality as random effects whose coefficients vary depending on the sound source. These results present a promising step toward implementing an on-sensor annoyance model which incorporates psychoacoustic features and sound source type, and is ultimately not dependent on sound level.

Suggested Citation

  • Ferran Orga & Andrew Mitchell & Marc Freixes & Francesco Aletta & Rosa Ma Alsina-Pagès & Maria Foraster, 2021. "Multilevel Annoyance Modelling of Short Environmental Sound Recordings," Sustainability, MDPI, vol. 13(11), pages 1-13, May.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:11:p:5779-:d:559159
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    References listed on IDEAS

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    1. G. N. Wilkinson & C. E. Rogers, 1973. "Symbolic Description of Factorial Models for Analysis of Variance," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 22(3), pages 392-399, November.
    2. Edward Frees & Jee-Seon Kim, 2006. "Multilevel Model Prediction," Psychometrika, Springer;The Psychometric Society, vol. 71(1), pages 79-104, March.
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    Cited by:

    1. Andrew Mitchell & Mercede Erfanian & Christopher Soelistyo & Tin Oberman & Jian Kang & Robert Aldridge & Jing-Hao Xue & Francesco Aletta, 2022. "Effects of Soundscape Complexity on Urban Noise Annoyance Ratings: A Large-Scale Online Listening Experiment," IJERPH, MDPI, vol. 19(22), pages 1-16, November.

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