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Automatic Recognition of Bird Species Using Human Factor Cepstral Coefficients

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Book cover Smart Computing and Informatics

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 77))

Abstract

Identification of bird species based on their song is very important task from biodiversity point of view. In order to develop an automatic system of recognition of bird species, a system using signal processing and pattern recognition techniques has gained huge importance. In this paper, we compare the performance of mel frequency cepstral coefficients and human factor cepstral coefficients combined with time- and frequency-based features. Gaussian mixture models have been used for developing feature models, and maximum likelihood estimation is used for classification. Further, selective features have been used in order to increase the performance of the system. With the proposed method, a maximum accuracy of 97.72% has been achieved for a data set of ten bird species.

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Authors and Affiliations

  1. Department of Electronics and Telecommunication, College of Engineering, Pune, India

    Arti V. Bang & Priti P. Rege

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  1. Arti V. Bang
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  2. Priti P. Rege
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Correspondence to Arti V. Bang .

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Editors and Affiliations

  1. Department of Computer Science and Engineering, PVP Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India

    Suresh Chandra Satapathy

  2. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

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Bang, A.V., Rege, P.P. (2018). Automatic Recognition of Bird Species Using Human Factor Cepstral Coefficients. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Computing and Informatics . Smart Innovation, Systems and Technologies, vol 77. Springer, Singapore. https://doi.org/10.1007/978-981-10-5544-7_35

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  • DOI: https://doi.org/10.1007/978-981-10-5544-7_35

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5543-0

  • Online ISBN: 978-981-10-5544-7

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