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Information Theoretic Approach Based on Entropy for Classification of Bioacoustics Signals

A new hybrid method for automated frog sound identification by incorporating entropy and spectral centroid concept is proposed. Entropy has important physical implications as the amount of “disorder” of a system. This study explores the use of various definitions ofentropies such as the Shannon entr...

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Main Authors: Ng, Chee Han, Sithi V. Muniandy, Jedol Dayou, Ho, Chong Mun, Abdul Hamid Ahmad, Mohd. Noh Dalimin
Format: Article
Language:English
Published: American Institute of Physics Inc. 2010
Subjects:
Q Science (General)
QL Zoology
Online Access:https://eprints.ums.edu.my/id/eprint/21533/1/Information%20Theoretic%20Approach%20Based%20on%20Entropy%20for%20Classification%20of%20Bioacoustics%20Signals.pdf
https://eprints.ums.edu.my/id/eprint/21533/
https://doi.org/10.1063/1.3469668
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spelling my.ums.eprints.215332019-03-08T08:14:42Z https://eprints.ums.edu.my/id/eprint/21533/ Information Theoretic Approach Based on Entropy for Classification of Bioacoustics Signals Ng, Chee Han Sithi V. Muniandy Jedol Dayou Ho, Chong Mun Abdul Hamid Ahmad Mohd. Noh Dalimin Q Science (General) QL Zoology A new hybrid method for automated frog sound identification by incorporating entropy and spectral centroid concept is proposed. Entropy has important physical implications as the amount of “disorder” of a system. This study explores the use of various definitions ofentropies such as the Shannon entropy, Kolmogorov‐Rényi entropy and Tsallis entropy as measure of information contents or complexity for the purpose of the pattern recognitionof bioacoustics signal. Each of these definitions of entropies characterizes different aspects of the signal. The entropies are combined with other standard pattern recognition tools such as the Fourier spectral analysis to form a hybrid spectral‐entropic classification scheme. The efficiency of the system is tested using a database of sound syllables are obtained from a number of species of Microhylidae frogs. Nonparametric k‐NN classifier is used to recognize the frog species based on the spectral‐entropic features. The result showed that the k‐NN classifier based on the selected features is able to identify the species of the frogs with relativity good accuracy compared to features relying on spectral contents alone. The robustness of the developed system is also tested for different noise levels. American Institute of Physics Inc. 2010 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/21533/1/Information%20Theoretic%20Approach%20Based%20on%20Entropy%20for%20Classification%20of%20Bioacoustics%20Signals.pdf Ng, Chee Han and Sithi V. Muniandy and Jedol Dayou and Ho, Chong Mun and Abdul Hamid Ahmad and Mohd. Noh Dalimin (2010) Information Theoretic Approach Based on Entropy for Classification of Bioacoustics Signals. AIP Conference Proceedings, 1250 (1). ISSN 0094243X https://doi.org/10.1063/1.3469668
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
topic Q Science (General)
QL Zoology
spellingShingle Q Science (General)
QL Zoology
Ng, Chee Han
Sithi V. Muniandy
Jedol Dayou
Ho, Chong Mun
Abdul Hamid Ahmad
Mohd. Noh Dalimin
Information Theoretic Approach Based on Entropy for Classification of Bioacoustics Signals
description A new hybrid method for automated frog sound identification by incorporating entropy and spectral centroid concept is proposed. Entropy has important physical implications as the amount of “disorder” of a system. This study explores the use of various definitions ofentropies such as the Shannon entropy, Kolmogorov‐Rényi entropy and Tsallis entropy as measure of information contents or complexity for the purpose of the pattern recognitionof bioacoustics signal. Each of these definitions of entropies characterizes different aspects of the signal. The entropies are combined with other standard pattern recognition tools such as the Fourier spectral analysis to form a hybrid spectral‐entropic classification scheme. The efficiency of the system is tested using a database of sound syllables are obtained from a number of species of Microhylidae frogs. Nonparametric k‐NN classifier is used to recognize the frog species based on the spectral‐entropic features. The result showed that the k‐NN classifier based on the selected features is able to identify the species of the frogs with relativity good accuracy compared to features relying on spectral contents alone. The robustness of the developed system is also tested for different noise levels.
format Article
author Ng, Chee Han
Sithi V. Muniandy
Jedol Dayou
Ho, Chong Mun
Abdul Hamid Ahmad
Mohd. Noh Dalimin
author_facet Ng, Chee Han
Sithi V. Muniandy
Jedol Dayou
Ho, Chong Mun
Abdul Hamid Ahmad
Mohd. Noh Dalimin
author_sort Ng, Chee Han
title Information Theoretic Approach Based on Entropy for Classification of Bioacoustics Signals
title_short Information Theoretic Approach Based on Entropy for Classification of Bioacoustics Signals
title_full Information Theoretic Approach Based on Entropy for Classification of Bioacoustics Signals
title_fullStr Information Theoretic Approach Based on Entropy for Classification of Bioacoustics Signals
title_full_unstemmed Information Theoretic Approach Based on Entropy for Classification of Bioacoustics Signals
title_sort information theoretic approach based on entropy for classification of bioacoustics signals
publisher American Institute of Physics Inc.
publishDate 2010
url https://eprints.ums.edu.my/id/eprint/21533/1/Information%20Theoretic%20Approach%20Based%20on%20Entropy%20for%20Classification%20of%20Bioacoustics%20Signals.pdf
https://eprints.ums.edu.my/id/eprint/21533/
https://doi.org/10.1063/1.3469668
_version_ 1760229854977982464
score 13.211869

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