Environmental sound classification using optimum allocation sampling based empirical mode decomposition

Saad Ahmad, Shubham Agrawal, Samta Joshi, Sachin Taran, Varun Bajaj, Fatih Demir and Abdulkadir Sengur

Physica A: Statistical Mechanics and its Applications, 2020, vol. 537, issue C

Abstract: Automatic environmental sound classification (ESC) is prominent in various fields like robotics, security, and crime investigation. In this paper, optimum allocation sampling (OAS)-based empirical mode method (EMD) is proposed for automatic ESC. The OAS provides the reduced homogeneous length sequence of each long length sound signal, which is further decomposed into band-limited intrinsic mode functions (IMFs) using EMD. The features namely approximate entropy (AE), permutation entropy (PE), log energy entropy (LE), interquartile range (IQR), and zero cross rate (ZCR) are extracted from the IMFs. The OAS-EMD based features used as input to multi-class least squares support vector machine (MC-LS-SVM) and extreme learning machine (ELM) classifiers for evaluation the performance of proposed method. Experimental results show an accuracy of 87.25% and 77.61% with MC-LS-SVM and ELM classifiers, respectively.

Keywords: Environmental sound classification; Optimum allocation sampling; Empirical mode decomposition; Multi-class least squares support vector machine; Extreme learning machine (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437119314955
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:537:y:2020:i:c:s0378437119314955

DOI: 10.1016/j.physa.2019.122613

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().