@article{ref1,
title="Automatic classification of road vehicles considering their pass-by acoustic signature",
journal="Journal of the Acoustical Society of America",
year="2013",
author="Valero Gonzalez, Xavier and Alías Pujol, Francesc",
volume="133",
number="5",
pages="3322-3322",
abstract="In order to assess the impact of environmental noise on a community, it is essential to accurately describe all the aspects and characteristics of the encountered noises. In this context, it would be of special interest to dispose of environmental noise monitoring stations capable of not only measuring the noise levels but also identifying the sources producing those levels. To offer such functionality, an algorithm to automatically recognize the noise sources is required. According to previous works, designing algorithms able to optimally distinguishing between road vehicle noise sources (i.e., light vehicles, heavy vehicles, and motorbikes) is a challenging issue. This paper proposes a recognition scheme that takes into account the perceived characteristics of road vehicles pass-by, which may be divided into different phases: approaching, passing and receding. By taking independent decisions for the pass-by phases, the proposed recognition scheme is able to improve the recognition of road traffic vehicles with respect to a traditional recognition scheme, specifically in 7% for light vehicles and in 4% for heavy vehicles.<p /> <p>Language: en</p>",
language="en",
issn="0001-4966",
doi="10.1121/1.4805552",
url="http://dx.doi.org/10.1121/1.4805552"
}