TY - GEN
T1 - ANALYSIS AND ACOUSTIC EVENT CLASSIFICATION OF ENVIRONMENTAL DATA COLLECTED IN SONS AL BALCÓ PROJECT
AU - Bonet-Solà, Daniel
AU - Vidaña-Vila, Ester
AU - Alsina-Pagès, Rosa Ma
N1 - Publisher Copyright:
© 2023 E.V-V, RM.A-P This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2023
Y1 - 2023
N2 - A difficulty encountered in citizen science projects is the processing and analysis of data collected by participants in order to draw conclusions. The project Sons al Balcó started with the aim of studying the effect of lockdown due to the COVID-19 pandemic on the perception of noise in Catalonia, asking the citizens to evaluate the soundscape from their homes. 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 or window. 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 has been trained to automatically detect and classify acoustic events even if they occur simultaneously. The findings indicate that the detection rates of different categories are not uniform, with the prevalence percentage of an event in the dataset and its foreground-to-background ratio being important determining factors.
AB - A difficulty encountered in citizen science projects is the processing and analysis of data collected by participants in order to draw conclusions. The project Sons al Balcó started with the aim of studying the effect of lockdown due to the COVID-19 pandemic on the perception of noise in Catalonia, asking the citizens to evaluate the soundscape from their homes. 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 or window. 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 has been trained to automatically detect and classify acoustic events even if they occur simultaneously. The findings indicate that the detection rates of different categories are not uniform, with the prevalence percentage of an event in the dataset and its foreground-to-background ratio being important determining factors.
KW - acoustic event detection
KW - citizen science
KW - convolutional neural networks
KW - noise annoyance
UR - http://www.scopus.com/inward/record.url?scp=85182166947&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85182166947
T3 - Proceedings of Forum Acusticum
BT - Forum Acusticum 2023 - 10th Convention of the European Acoustics Association, EAA 2023
PB - European Acoustics Association, EAA
T2 - 10th Convention of the European Acoustics Association, EAA 2023
Y2 - 11 September 2023 through 15 September 2023
ER -