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Pregled bibliografske jedinice broj: 1162326

Development of a multi-level predictive soundscape model to assess the soundscapes of public spaces during the COVID-19 lockdowns


Mitchell, Andrew; Oberman, Tin; Aletta, Francesco; Kang, Jian
Development of a multi-level predictive soundscape model to assess the soundscapes of public spaces during the COVID-19 lockdowns // The Journal of the Acoustical Society of America 150, A293 (2021)
Seattle, Sjedinjene Američke Države: Acoustical Society of America (ASA), 2021. str. A293-A293 doi:10.1121/10.0008334 (predavanje, međunarodna recenzija, sažetak, znanstveni)


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Naslov
Development of a multi-level predictive soundscape model to assess the soundscapes of public spaces during the COVID-19 lockdowns

Autori
Mitchell, Andrew ; Oberman, Tin ; Aletta, Francesco ; Kang, Jian

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
The Journal of the Acoustical Society of America 150, A293 (2021) / - : Acoustical Society of America (ASA), 2021, A293-A293

Skup
181st Meeting Acoustical Society of America

Mjesto i datum
Seattle, Sjedinjene Američke Države, 29.11.-03.12.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
soundscape ; COVID-19 ; lockdown ; multi-level model ; public space

Sažetak
The recent developments in the standardization of soundscape as both a research and engineering field have highlighted the need for models which can predict likely soundscape assessment from objective measurements. Such a need was highlighted during the COVID-19 lockdowns. The unprecedented restrictions in human activity presented a unique opportunity to investigate the urban noise impacts of drastic reductions in traffic noise and human sounds, but simultaneously made it impossible to carry out standard methods of soundscape assessment (i.e., in-person surveys or soundwalks). To address this, a multi-level linear regression model was developed based on an existing database of soundscape surveys and binaural recordings to predict how the soundscapes of 13 locations in London and Venice would have likely been perceived during the lockdowns based on objective measurements. To build this model, a feature selection process was applied to an extended suite of psychoacoustic metrics and a variable characterising the context of each location to identify a minimum set of input features and model structure. This presentation will demonstrate the development of this model, its application in the COVID case study and corresponding results, and will discuss the potential for future applications of a similar predictive soundscape modelling framework.

Izvorni jezik
Engleski

Znanstvena područja
Arhitektura i urbanizam, Interdisciplinarne tehničke znanosti



POVEZANOST RADA


Ustanove:
Arhitektonski fakultet, Zagreb

Profili:

Avatar Url Tin Oberman (autor)

Poveznice na cjeloviti tekst rada:

doi asa.scitation.org

Citiraj ovu publikaciju:

Mitchell, Andrew; Oberman, Tin; Aletta, Francesco; Kang, Jian
Development of a multi-level predictive soundscape model to assess the soundscapes of public spaces during the COVID-19 lockdowns // The Journal of the Acoustical Society of America 150, A293 (2021)
Seattle, Sjedinjene Američke Države: Acoustical Society of America (ASA), 2021. str. A293-A293 doi:10.1121/10.0008334 (predavanje, međunarodna recenzija, sažetak, znanstveni)
Mitchell, A., Oberman, T., Aletta, F. & Kang, J. (2021) Development of a multi-level predictive soundscape model to assess the soundscapes of public spaces during the COVID-19 lockdowns. U: The Journal of the Acoustical Society of America 150, A293 (2021) doi:10.1121/10.0008334.
@article{article, year = {2021}, pages = {A293-A293}, DOI = {10.1121/10.0008334}, keywords = {soundscape, COVID-19, lockdown, multi-level model, public space}, doi = {10.1121/10.0008334}, title = {Development of a multi-level predictive soundscape model to assess the soundscapes of public spaces during the COVID-19 lockdowns}, keyword = {soundscape, COVID-19, lockdown, multi-level model, public space}, publisher = {Acoustical Society of America (ASA)}, publisherplace = {Seattle, Sjedinjene Ameri\v{c}ke Dr\v{z}ave} }
@article{article, year = {2021}, pages = {A293-A293}, DOI = {10.1121/10.0008334}, keywords = {soundscape, COVID-19, lockdown, multi-level model, public space}, doi = {10.1121/10.0008334}, title = {Development of a multi-level predictive soundscape model to assess the soundscapes of public spaces during the COVID-19 lockdowns}, keyword = {soundscape, COVID-19, lockdown, multi-level model, public space}, publisher = {Acoustical Society of America (ASA)}, publisherplace = {Seattle, Sjedinjene Ameri\v{c}ke Dr\v{z}ave} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Citati:





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