Separability Assessment of Selected Types of Vehicle-Associated Noise - Publication - Bridge of Knowledge

Your account

login

Search

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.

Citations

  • 3

    CrossRef

  • 0

    Web of Science

  • 8

    Scopus

Authors (3)

Cite as

Full text

full text is not available in portal

Keywords

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

seen 172 times

Recommended for you

Testing Watermark Robustness against Application of Audio Restoration Algorithms

2013

Modeling the effect of electric vehicles on noise levels in the vicinity of rural road sections

2023

Evaluation of sound event detection, classification and localization in the presence of background noise for acoustic surveillance of hazardous situations

2014

Detection, classification and localization of acoustic events in the presence of background noise for acoustic surveillance of hazardous situations

2016
Meta Tags