Article
Optimal Representation of Anuran Call Spectrum in Environmental Monitoring Systems Using Wireless Sensor Networks
Author/s | Luque Sendra, Amalia
Gómez-Bellido, Jesús Carrasco Muñoz, Alejandro Barbancho Concejero, Julio |
Editor | Aguayo-González, Francisco
León de Mora, Carlos |
Department | Universidad de Sevilla. Departamento de Ingeniería del Diseño Universidad de Sevilla. Departamento de Tecnología Electrónica |
Publication Date | 2018 |
Deposit Date | 2018-09-07 |
Published in |
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Abstract | The analysis and classification of the sounds produced by certain animal species, notably anurans, have revealed these amphibians to be a potentially strong indicator of temperature fluctuations and therefore of the existence ... The analysis and classification of the sounds produced by certain animal species, notably anurans, have revealed these amphibians to be a potentially strong indicator of temperature fluctuations and therefore of the existence of climate change. Environmental monitoring systems using Wireless Sensor Networks are therefore of interest to obtain indicators of global warming. For the automatic classification of the sounds recorded on such systems, the proper representation of the sound spectrum is essential since it contains the information required for cataloguing anuran calls. The present paper focuses on this process of feature extraction by exploring three alternatives: the standardized MPEG-7, the Filter Bank Energy (FBE), and the Mel Frequency Cepstral Coefficients (MFCC). Moreover, various values for every option in the extraction of spectrum features have been considered. Throughout the paper, it is shown that representing the frame spectrum with pure FBE offers slightly worse results than using the MPEG-7 features. This performance can easily be increased, however, by rescaling the FBE in a double dimension: vertically, by taking the logarithm of the energies; and, horizontally, by applying mel scaling in the filter banks. On the other hand, representing the spectrum in the cepstral domain, as in MFCC, has shown additional marginal improvements in classification performance. |
Funding agencies | Universidad de Sevilla |
Project ID. | Telefónica Chair "Intelligence Networks" |
Citation | Luque Sendra, A., Gómez-Bellido, J., Carrasco Muñoz, A. y Barbancho Concejero, J. (2018). Optimal Representation of Anuran Call Spectrum in Environmental Monitoring Systems Using Wireless Sensor Networks. Sensor, 18 (6), 1-31. |
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