Classification and identification of frog sound based on entropy approach

Jedol Dayou, and Ng, Chee Han and Ho, Chong Mun and Abdul Hamid Ahmad, and Sithi V. Muniandy, and Mohd Noh Dalimin, (2011) Classification and identification of frog sound based on entropy approach. In: 2011 International Conference on Life Science and Technology, 7 - 9 January 2011, Mumbai, India.

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Abstract

A new classification method for animal sound identification using entropy-based approach is proposed. Entropy is a measure of information contents or complexity for a sequence of a signal. This study introduces three definitions of entropy - Shannon entropy, Rènyi entropy and Tsallis entropy, which are used in this paper as the features of extraction for the purpose of the pattern recognition of animal sounds. Sound samples from nine Microhylidae frogs are first segmented into syllables. Then, the features of each syllable are extracted using Shannon entropy, Rènyi entropy and Tsallis entropy. The nonparametric k-th nearest neighbours (k-NN) classifier is then used for frog sound identification system. The result shows that the entropy-based animal sound identification system has successfully identified most of the frog species.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Bioacoustics signal, entropy, frogs sound analysis
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: FACULTY > Faculty of Science and Natural Resources
Depositing User: Munira
Date Deposited: 08 Mar 2018 02:29
Last Modified: 08 Mar 2018 02:29
URI: http://eprints.ums.edu.my/id/eprint/19087

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