DocumentCode :
238078
Title :
An automatic method to detect the presence of elephant
Author :
Mohapatra, Arpit Sourav ; Solanki, S.S.
Author_Institution :
Dept. of Electron. & Commun. Eng., Birla Inst. of Technol., Ranchi, India
fYear :
2014
fDate :
8-10 May 2014
Firstpage :
1515
Lastpage :
1518
Abstract :
In this paper an approach has been discussed to automatically detect the presence of elephant by the detection of a low frequency sound produced by elephant called rumble. A detection system has been developed which uses features of rumbles as input to recognize the rumbles. Feature extraction techniques have been used to extract the features of rumble which includes the greenwood function cepstral coefficients (GFCC) and first three formant frequencies. The GFCC features have been extracted in a procedure similar to mel frequency cepstral coefficients (MFCC) extraction while the formant frequencies have been extracted using linear predictive coding (LPC). A robust feature vector has been created by cascading the formant frequencies to the GFCC features. The detection system has been developed using feed forward neural network which is trained using backpropagation algorithm.
Keywords :
audio signal processing; backpropagation; feedforward neural nets; linear predictive coding; zoology; GFCC features; LPC; MFCC; backpropagation algorithm; elephant presence detection; feature extraction techniques; feed forward neural network; formant frequencies; greenwood function cepstral coefficients; linear predictive coding; low frequency sound; mel frequency cepstral coefficients extraction; robust feature vector; rumble; Artificial neural networks; Biological neural networks; Feature extraction; Neurons; Noise; Resonant frequency; Testing; GFCC; LPC; MFCC; Rumbles; STFT; formant;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
Conference_Location :
Ramanathapuram
Print_ISBN :
978-1-4799-3913-8
Type :
conf
DOI :
10.1109/ICACCCT.2014.7019359
Filename :
7019359
Link To Document :
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