On using prefiltration in HMM-based bird species recognition

Automatic bird species recognition method using their voices is presented in this paper. The selected bird species have been detected by hidden Markov models (HMM) classifier using Mel-frequency cepstral coefficients (MFCC). In order to support recognition process, analysed signals have been appropr...

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Bibliographic Details
Main Authors: Wielgat, R., Swietojanski, P., Potempa, T., Krol, D.
Format: Conference Proceeding
Language:English
Subjects:
Birds
Feature extraction
Harmonic analysis
Hidden Markov models
Mel frequency cepstral coefficient
Noise measurement
Power harmonic filters
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Summary:Automatic bird species recognition method using their voices is presented in this paper. The selected bird species have been detected by hidden Markov models (HMM) classifier using Mel-frequency cepstral coefficients (MFCC). In order to support recognition process, analysed signals have been appropriately filtered before classification in the so called prefiltration process. The prefiltration strategy assumed using n-th order IIR Butterworth filter bank. Each filter from the filter bank was applied for band pass filtration in the bird species-specific and signal type band. Increase of recognition accuracy has been observed in case of prefiltration with properly chosen filter order. Experiments have been carried out on the set of bird voices containing 30 bird species, one of which is endangered with extinction.
DOI:10.1109/ICSES.2012.6382258