@inproceedings{b1b33f64b2b94e72b214f2f5b2e9665c,
title = "A dataset and taxonomy for urban sound research",
abstract = "Automatic urban sound classification is a growing area of research with applications in multimedia retrieval and urban informatics. In this paper we identify two main barriers to research in this area - the lack of a common taxonomy and the scarceness of large, real-world, annotated data. To address these issues we present a taxonomy of urban sounds and a new dataset, UrbanSound, containing 27 hours of audio with 18.5 hours of annotated sound event occurrences across 10 sound classes. The challenges presented by the new dataset are studied through a series of experiments using a baseline classification system.",
keywords = "Classification, Dataset, Taxonomy, Urban sound",
author = "Justin Salamon and Christopher Jacoby and Bello, {Juan Pablo}",
year = "2014",
month = nov,
day = "3",
doi = "10.1145/2647868.2655045",
language = "English (US)",
series = "MM 2014 - Proceedings of the 2014 ACM Conference on Multimedia",
publisher = "Association for Computing Machinery",
pages = "1041--1044",
booktitle = "MM 2014 - Proceedings of the 2014 ACM Conference on Multimedia",
note = "2014 ACM Conference on Multimedia, MM 2014 ; Conference date: 03-11-2014 Through 07-11-2014",
}