Title :
Bird Species Recognition by Wavelet Transformation of a Section of Birdsong
Author :
Chou, Chih-Hsun ; Liu, Pang-Hsin
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Chung Hua Univ., Hsinchu, Taiwan
Abstract :
In this study, a method for birdsong recognition is proposed. In this method, after detecting the range of each syllable, birdsong sections containing a period of syllables were segmented. For each syllable of a birdsong section, the first five orders MFCCs were computed, and the same order MFCCs of all syllables were aligned so that wavelet transformation can be applied to compute the feature vector of the birdsong section. By using neural network as the classifier, the proposed method was applied to recognize the birdsongs of 420 bird species.
Keywords :
acoustic signal processing; neural nets; wavelet transforms; zoology; MFCC; bird species recognition; birdsong recognition; neural network; wavelet transformation; Birds; Computer science; Conferences; Feature extraction; Histograms; Mel frequency cepstral coefficient; Neural networks; Pervasive computing; Power harmonic filters; Prototypes; Birdsong recognition; Mel-frequency cepstral coefficients; syllable segmentation; wavelet transformation;
Conference_Titel :
Ubiquitous, Autonomic and Trusted Computing, 2009. UIC-ATC '09. Symposia and Workshops on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4244-4902-6
Electronic_ISBN :
978-0-7695-3737-5
DOI :
10.1109/UIC-ATC.2009.85
