Title :
The BIO-acoustic feature extraction and classification of bat echolocation calls
Author :
Mirzaei, Golrokh ; Majid, Mohammad Wadood ; Ross, James ; Jamali, Mohsin M. ; Gorsevski, Peter V. ; Frizado, Joseph P. ; Bingman, Verner P.
Author_Institution :
Dept. of Electr. & Comp Sci., Univ. of Toledo, Toledo, OH, USA
Abstract :
There are reports that large number of bat fatalities occur near wind turbines. Acoustic characteristics can be employed for bat call recognition to better understand the effects of turbines on different bat species. Acoustic features of bat echolocation calls are extracted based on three different techniques: Short Time Fourier Transform (STFT), Mel Frequency Cepstrum Coefficient (MFCC) and Discrete Wavelet Transform (DWT). These features are fed into an Evolutionary Neural Network (ENN) for their classification at the species level using acoustic features. Results from different feature extraction techniques are compared based on classification accuracy. The technique can identify bats and will contribute towards developing mitigation procedures for reducing bat fatalities.
Keywords :
Fourier transforms; acoustic signal processing; bioacoustics; cepstral analysis; discrete wavelet transforms; evolutionary computation; feature extraction; neural nets; signal classification; wind turbines; acoustic characteristics; bat call recognition; bat echolocation calls; bat fatalities; bat species; bio-acoustic feature extraction; classification accuracy; discrete wavelet transform; evolutionary neural network; feature classification; mel frequency cepstrum coefficient; short time Fourier transform; wind turbines; Discrete wavelet transforms; Feature extraction; Filter banks; Mel frequency cepstral coefficient; Time frequency analysis;
Conference_Titel :
Electro/Information Technology (EIT), 2012 IEEE International Conference on
Conference_Location :
Indianapolis, IN
Print_ISBN :
978-1-4673-0819-9
DOI :
10.1109/EIT.2012.6220700