MAVD: A dataset for sound event detection in urban environments.

Zinemanas, Pablo - Cancela, Pablo - Rocamora, Martín

Resumen:

We describe the public release of a dataset for sound event detection in urban environments, namely MAVD, which is the first of a series of datasets planned within an ongoing research project for urban noise monitoring in Montevideo city, Uruguay. This release focuses on traffic noise, MAVD-traffic, as it is usually the predominant noise source in urban environments. An ontology for traffic sounds is proposed, which is the combination of a set of two taxonomies: vehicle types (e.g. car, bus) and vehicle components (e.g. engine, brakes), and a set of actions related to them (e.g. idling, accelerating). Thus, the proposed ontology allows for a flexible and detailed description of traffic sounds. We also provide a baseline of the performance of state-of-the-art sound event detection systems applied to the dataset.


Detalles Bibliográficos
2019
SED database
Traffic noise
Urban sound
Inglés
Universidad de la República
COLIBRI
https://hdl.handle.net/20.500.12008/25415
https://doi.org/10.33682/kfmf-zv94
Acceso abierto
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
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author Zinemanas, Pablo
author2 Cancela, Pablo
Rocamora, Martín
author2_role author
author
author_facet Zinemanas, Pablo
Cancela, Pablo
Rocamora, Martín
author_role author
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dc.contributor.filiacion.none.fl_str_mv Zinemanas Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería.
Cancela Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería.
Rocamora Martín, Universidad de la República (Uruguay). Facultad de Ingeniería.
dc.coverage.spatial.es.fl_str_mv Departamento de Montevideo, Uruguay
dc.creator.none.fl_str_mv Zinemanas, Pablo
Cancela, Pablo
Rocamora, Martín
dc.date.accessioned.none.fl_str_mv 2020-09-29T19:17:37Z
dc.date.available.none.fl_str_mv 2020-09-29T19:17:37Z
dc.date.issued.none.fl_str_mv 2019
dc.description.abstract.none.fl_txt_mv We describe the public release of a dataset for sound event detection in urban environments, namely MAVD, which is the first of a series of datasets planned within an ongoing research project for urban noise monitoring in Montevideo city, Uruguay. This release focuses on traffic noise, MAVD-traffic, as it is usually the predominant noise source in urban environments. An ontology for traffic sounds is proposed, which is the combination of a set of two taxonomies: vehicle types (e.g. car, bus) and vehicle components (e.g. engine, brakes), and a set of actions related to them (e.g. idling, accelerating). Thus, the proposed ontology allows for a flexible and detailed description of traffic sounds. We also provide a baseline of the performance of state-of-the-art sound event detection systems applied to the dataset.
dc.format.extent.es.fl_str_mv 5 p.
dc.format.mimetype.es.fl_str_mv application/pdf
dc.identifier.citation.es.fl_str_mv Zinemanas, P., Cancela, P. y Rocamora, M. MAVD: A dataset for sound event detection in urban environments. [en línea]. EN: Detection and Classification of Acoustic Scenes and Events, 2019, New York, USA, 25–26 oct. New York : New York University, 2019. 5 p. DOI: https://doi.org/10.33682/kfmf-zv94
dc.identifier.doi.none.fl_str_mv https://doi.org/10.33682/kfmf-zv94
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12008/25415
dc.language.iso.none.fl_str_mv en
eng
dc.publisher.es.fl_str_mv New York University
dc.relation.ispartof.es.fl_str_mv Detection and Classification of Acoustic Scenes and Events, DCASE 2019, New York, NY, USA, 25–26 oct, page 263--267
dc.rights.license.none.fl_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.source.none.fl_str_mv reponame:COLIBRI
instname:Universidad de la República
instacron:Universidad de la República
dc.subject.es.fl_str_mv SED database
Traffic noise
Urban sound
dc.title.none.fl_str_mv MAVD: A dataset for sound event detection in urban environments.
dc.type.es.fl_str_mv Ponencia
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
description We describe the public release of a dataset for sound event detection in urban environments, namely MAVD, which is the first of a series of datasets planned within an ongoing research project for urban noise monitoring in Montevideo city, Uruguay. This release focuses on traffic noise, MAVD-traffic, as it is usually the predominant noise source in urban environments. An ontology for traffic sounds is proposed, which is the combination of a set of two taxonomies: vehicle types (e.g. car, bus) and vehicle components (e.g. engine, brakes), and a set of actions related to them (e.g. idling, accelerating). Thus, the proposed ontology allows for a flexible and detailed description of traffic sounds. We also provide a baseline of the performance of state-of-the-art sound event detection systems applied to the dataset.
eu_rights_str_mv openAccess
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identifier_str_mv Zinemanas, P., Cancela, P. y Rocamora, M. MAVD: A dataset for sound event detection in urban environments. [en línea]. EN: Detection and Classification of Acoustic Scenes and Events, 2019, New York, USA, 25–26 oct. New York : New York University, 2019. 5 p. DOI: https://doi.org/10.33682/kfmf-zv94
instacron_str Universidad de la República
institution Universidad de la República
instname_str Universidad de la República
language eng
language_invalid_str_mv en
network_acronym_str COLIBRI
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publishDate 2019
reponame_str COLIBRI
repository.mail.fl_str_mv mabel.seroubian@seciu.edu.uy
repository.name.fl_str_mv COLIBRI - Universidad de la República
repository_id_str 4771
rights_invalid_str_mv Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
spelling Zinemanas Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería.Cancela Pablo, Universidad de la República (Uruguay). Facultad de Ingeniería.Rocamora Martín, Universidad de la República (Uruguay). Facultad de Ingeniería.Departamento de Montevideo, Uruguay2020-09-29T19:17:37Z2020-09-29T19:17:37Z2019Zinemanas, P., Cancela, P. y Rocamora, M. MAVD: A dataset for sound event detection in urban environments. [en línea]. EN: Detection and Classification of Acoustic Scenes and Events, 2019, New York, USA, 25–26 oct. New York : New York University, 2019. 5 p. DOI: https://doi.org/10.33682/kfmf-zv94https://hdl.handle.net/20.500.12008/25415https://doi.org/10.33682/kfmf-zv94We describe the public release of a dataset for sound event detection in urban environments, namely MAVD, which is the first of a series of datasets planned within an ongoing research project for urban noise monitoring in Montevideo city, Uruguay. This release focuses on traffic noise, MAVD-traffic, as it is usually the predominant noise source in urban environments. An ontology for traffic sounds is proposed, which is the combination of a set of two taxonomies: vehicle types (e.g. car, bus) and vehicle components (e.g. engine, brakes), and a set of actions related to them (e.g. idling, accelerating). Thus, the proposed ontology allows for a flexible and detailed description of traffic sounds. We also provide a baseline of the performance of state-of-the-art sound event detection systems applied to the dataset.Submitted by Ribeiro Jorge (jribeiro@fing.edu.uy) on 2020-09-25T21:16:19Z No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) ZCR19a.pdf: 1770181 bytes, checksum: 5dbb614a7844123e98341a4402e02c2c (MD5)Approved for entry into archive by Machado Jimena (jmachado@fing.edu.uy) on 2020-09-29T17:42:09Z (GMT) No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) ZCR19a.pdf: 1770181 bytes, checksum: 5dbb614a7844123e98341a4402e02c2c (MD5)Made available in DSpace by Luna Fabiana (fabiana.luna@fic.edu.uy) on 2020-09-29T19:17:37Z (GMT). No. of bitstreams: 2 license_rdf: 23149 bytes, checksum: 1996b8461bc290aef6a27d78c67b6b52 (MD5) ZCR19a.pdf: 1770181 bytes, checksum: 5dbb614a7844123e98341a4402e02c2c (MD5) Previous issue date: 20195 p.application/pdfenengNew York UniversityDetection and Classification of Acoustic Scenes and Events, DCASE 2019, New York, NY, USA, 25–26 oct, page 263--267Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. 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- Universidad de la Repúblicafalse
spellingShingle MAVD: A dataset for sound event detection in urban environments.
Zinemanas, Pablo
SED database
Traffic noise
Urban sound
status_str publishedVersion
title MAVD: A dataset for sound event detection in urban environments.
title_full MAVD: A dataset for sound event detection in urban environments.
title_fullStr MAVD: A dataset for sound event detection in urban environments.
title_full_unstemmed MAVD: A dataset for sound event detection in urban environments.
title_short MAVD: A dataset for sound event detection in urban environments.
title_sort MAVD: A dataset for sound event detection in urban environments.
topic SED database
Traffic noise
Urban sound
url https://hdl.handle.net/20.500.12008/25415
https://doi.org/10.33682/kfmf-zv94

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