MAVD : A dataset for sound event detection in urban environments
Pablo Zinemanas, Pablo Cancela, Martín Rocamora
Detection and Classification of Acoustic Scenes and Events, DCASE 2019, New York, NY, USA, 25–26 oct, page 263--267- 2019
Research group(s):  Procesamiento de Audio (gpa)
Department(s):  Procesamiento de Señales
Download the publication : ZCR19a.pdf [1.7MB]  


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. Index Terms : SED database, traffic noise, urban sound

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