Analysis and acoustic event classification of environmental data collected in sons al balco project

One of the challenges of citizen science projects is the processing of data gathered by the citizens, to obtain conclusions. In the project Sons al Balcó, we aim to study the effect of lockdown due to the COVID-19 pandemic on the perception of noise in Catalonia. In one of the activities of the proj...

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Bibliographic Details
Authors: Bonet-Solà, Daniel, Vidaña Vila, Ester, Alsina-Pagès, Rosa Ma
Format: article
Publication Date:2023
Country:España
Institution:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repository:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:20.500.14342/5692
Online Access:http://hdl.handle.net/20.500.14342/5692
https://www.doi.org/10.61782/fa.2023.0422
Access Level:Open access
Keyword:Noise annoyance
Acoustic event detection
Citizen science
Convolutional neural networks
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531/534
62
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oai_identifier_str oai:recercat.cat:20.500.14342/5692
network_acronym_str ES
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spelling Analysis and acoustic event classification of environmental data collected in sons al balco projectBonet-Solà, DanielVidaña Vila, EsterAlsina-Pagès, Rosa MaNoise annoyanceAcoustic event detectionCitizen scienceConvolutional neural networks502531/53462One of the challenges of citizen science projects is the processing of data gathered by the citizens, to obtain conclusions. In the project Sons al Balcó, we aim to study the effect of lockdown due to the COVID-19 pandemic on the perception of noise in Catalonia. In one of the activities of the project, citizens collaborated by sending short videos recorded with a mobile phone, together with a subjective questionnaire about the recorded soundscape on their home balcony. Following this purpose, the samples coming from citizens should be automatically analyzed in terms of acoustic event detection, in order to compare the objective data in the videos with the subjective impressions collected in the questionnaires. As a first step towards automatic acoustic event classification, this paper details and compares the acoustic samples of the two collecting campaigns of the project. While the 2020 campaign obtained 365 videos, the 2021 campaign obtained 237. Later, a convolutional neural network is trained to automatically detect and classify acoustic events even if they occur simultaneously. Results suggest that not all the categories are equally detected: the percentage of prevalence of an event in the dataset and its foregound-to- background ratio play a decisive role.info:eu-repo/semantics/publishedVersionForum Acusticum 2023Universitat Ramon Llull. La Salle2023info:eu-repo/semantics/article7 p.http://hdl.handle.net/20.500.14342/5692https://www.doi.org/10.61782/fa.2023.0422reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésProceedings of the 10th Convention of the European Acoustics Association Forum Acusticum 2023© L'autor/aAttribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:20.500.14342/56922026-05-29T05:05:01Z
dc.title.none.fl_str_mv Analysis and acoustic event classification of environmental data collected in sons al balco project
title Analysis and acoustic event classification of environmental data collected in sons al balco project
spellingShingle Analysis and acoustic event classification of environmental data collected in sons al balco project
Bonet-Solà, Daniel
Noise annoyance
Acoustic event detection
Citizen science
Convolutional neural networks
502
531/534
62
title_short Analysis and acoustic event classification of environmental data collected in sons al balco project
title_full Analysis and acoustic event classification of environmental data collected in sons al balco project
title_fullStr Analysis and acoustic event classification of environmental data collected in sons al balco project
title_full_unstemmed Analysis and acoustic event classification of environmental data collected in sons al balco project
title_sort Analysis and acoustic event classification of environmental data collected in sons al balco project
dc.creator.none.fl_str_mv Bonet-Solà, Daniel
Vidaña Vila, Ester
Alsina-Pagès, Rosa Ma
author Bonet-Solà, Daniel
author_facet Bonet-Solà, Daniel
Vidaña Vila, Ester
Alsina-Pagès, Rosa Ma
author_role author
author2 Vidaña Vila, Ester
Alsina-Pagès, Rosa Ma
author2_role author
author
dc.contributor.none.fl_str_mv Universitat Ramon Llull. La Salle
dc.subject.none.fl_str_mv Noise annoyance
Acoustic event detection
Citizen science
Convolutional neural networks
502
531/534
62
topic Noise annoyance
Acoustic event detection
Citizen science
Convolutional neural networks
502
531/534
62
description One of the challenges of citizen science projects is the processing of data gathered by the citizens, to obtain conclusions. In the project Sons al Balcó, we aim to study the effect of lockdown due to the COVID-19 pandemic on the perception of noise in Catalonia. In one of the activities of the project, citizens collaborated by sending short videos recorded with a mobile phone, together with a subjective questionnaire about the recorded soundscape on their home balcony. Following this purpose, the samples coming from citizens should be automatically analyzed in terms of acoustic event detection, in order to compare the objective data in the videos with the subjective impressions collected in the questionnaires. As a first step towards automatic acoustic event classification, this paper details and compares the acoustic samples of the two collecting campaigns of the project. While the 2020 campaign obtained 365 videos, the 2021 campaign obtained 237. Later, a convolutional neural network is trained to automatically detect and classify acoustic events even if they occur simultaneously. Results suggest that not all the categories are equally detected: the percentage of prevalence of an event in the dataset and its foregound-to- background ratio play a decisive role.
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.14342/5692
https://www.doi.org/10.61782/fa.2023.0422
url http://hdl.handle.net/20.500.14342/5692
https://www.doi.org/10.61782/fa.2023.0422
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Proceedings of the 10th Convention of the European Acoustics Association Forum Acusticum 2023
dc.rights.none.fl_str_mv © L'autor/a
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv © L'autor/a
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 7 p.
dc.publisher.none.fl_str_mv Forum Acusticum 2023
publisher.none.fl_str_mv Forum Acusticum 2023
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.812429

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