Automatic Selection of Pareto-Optimal Topologies of Hidden Markov Models Using Multicriteria Evolutionary Algorithms

Swietojanski, Paweł; Wielgat, Robert; Zieliński, Tomasz P.

doi:10.1007/978-3-642-20525-5_23

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2012

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“…The cited papers as well as the authors' previous experience [6] confirm that statistical framework based on Gaussian mixture models is a suitable tool for building acoustic models representing bird sounds, for which reason [3][4][5]8] parameters are commonly used. Among other feature extractors, cepstral coefficients (CC) [7] and human-factor cepstral coefficients (HFCC) [8] are also encountered.…”

Section: Introductionmentioning

confidence: 55%

On using prefiltration in HMM-based bird species recognition

Wielgat

Swietojanski

Potempa

et al. 2012

2012 International Conference on Signals and Electronic Systems (ICSES)

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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.

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