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Separability Assessment of Selected Types of Vehicle-Associated Noise

Abstract

Music Information Retrieval (MIR) area as well as development of speech and environmental information recognition techniques brought various tools in-tended for recognizing low-level features of acoustic signals based on a set of calculated parameters. In this study, the MIRtoolbox MATLAB tool, designed for music parameter extraction, is used to obtain a vector of parameters to check whether they are suitable for separation of selected types of vehicle-associated noise, i.e.: car, truck and motorcycle. Then, cross-correlation be-tween pairs of parameters is calculated. Parameters for which absolute value of cross-correlation factor is below a selected threshold, are chosen for fur-ther analysis. Subsequently, pairs of parameters found in the previous step are analyzed as a graph of low-correlated parameters with the use of the Bron-Kerbosch algorithm. Graph is checked for existence of cliques of parameters linked in all-to-all manner related to their low correlation. The largest clique of low-correlated parameters is then tested for suitability for separation into three vehicle noise classes. Behrens-Fisher statistic is used for this purpose. Results are visualized in the form of 2D and 3D scatter plots.

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Details

Category:
Conference activity
Type:
materiały konferencyjne indeksowane w Web of Science
Published in:
Advances in Intelligent Systems and Computing no. 506, pages 113 - 121,
ISSN: 2194-5357
Title of issue:
Multimedia and Network Information Systems strony 113 - 121
Language:
English
Publication year:
2016
Bibliographic description:
Kurowski A., Marciniuk K., Kostek B..: Separability Assessment of Selected Types of Vehicle-Associated Noise, W: Multimedia and Network Information Systems, 2016, ,.
DOI:
Digital Object Identifier (open in new tab) 10.1007/978-3-319-43982-2_10
Verified by:
Gdańsk University of Technology

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