MAVD-traffic dataset

This is a dataset for sound event detection in urban environments, which is the first of a series of datasets planned within an ongoing research project for urban noise monitoring in Montevideo city, Uruguay. The dataset is called MAVD for Montevideo Audio and Video Dataset. This release focuses on traffic noise, hence the name MAVD-traffic, as it is usually the predominant noise source in urban environments. Apart from audio recordings it also includes synchronized video files. The sound event annotations follow an ontology for traffic sounds that 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. Since the taxonomies follow a hierarchy it can be used with different levels of detail. The dataset was presented in: Pablo Zinemanas, Pablo Cancela and Martín Rocamora. "MAVD: a dataset for sound event detection in urban environments." DCASE 2019 Workshop, 25-26 October 2019, New York, USA When MAVD-traffic is used for academic research, we would highly appreciate it if scientific publications cite the previous paper.本数据集为城市环境声音事件检测专用数据集，是乌拉圭蒙得维的亚市城市噪声监测在研项目规划的系列数据集的首款成果。该数据集名为MAVD（Montevideo Audio and Video Dataset，蒙得维的亚音视频数据集）。本次发布版本聚焦交通噪声，因此命名为MAVD-traffic——因交通噪声通常为城市环境中的主导噪声源。数据集除包含音频录音外，还附带同步视频文件。其声音事件标注遵循一套交通声音本体，该本体由两类分类体系组合而成：一是车辆类型（如轿车、巴士）与车辆部件（如发动机、制动器），二是与之对应的动作类别（如怠速、加速）。由此，该本体可实现对交通声音的灵活且细致的描述。由于分类体系具备层级结构，可根据需求适配不同粒度的细节描述。该数据集已发表于以下文献：Pablo Zinemanas、Pablo Cancela与Martín Rocamora所著《MAVD：城市环境声音事件检测数据集》，发表于2019年10月25日至26日于美国纽约举办的DCASE 2019研讨会。若将MAVD-traffic用于学术研究，恳请相关科研论文引用上述文献。