Título:
MAVD: A dataset for sound event detection in urban environments.
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Director:
Compilador:
Autor:
Zinemanas, Pablo
Cancela, Pablo
Rocamora, Martín
Cancela, Pablo
Rocamora, Martín
Tutor:
Tipo de documento:
Ponencia
Editor:
Palabras clave:
SED database
Traffic noise
Urban sound
Traffic noise
Urban sound
Descriptores:
Año de publicación:
2019
Contenido:
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.
Descripción:
Editorial:
New York University
EN:
Detection and Classification of Acoustic Scenes and Events, DCASE 2019, New York, NY, USA, 25–26 oct, page 263--267
Financiadores:
Citación:
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
Citación:
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Documento del Gobiberno:
URI:
https://hdl.handle.net/20.500.12008/25415
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Licencia:
Licencia Creative Commons Atribución - No Comercial - Sin Derivadas (CC - By-NC-ND 4.0)
Cobertura geográfica:
Departamento de Montevideo, Uruguay
Cobertura temporal:
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| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| ZCR19a.pdf | Versión definitiva | 1.69 MB | Adobe PDF |