Automated species recognition in environmental recordings

Duan, Shufei (2014) Automated species recognition in environmental recordings. PhD thesis, Queensland University of Technology.


Faunal vocalisations are vital indicators for environmental change and faunal vocalisation analysis can provide information for answering ecological questions. Therefore, automated species recognition in environmental recordings has become a critical research area. This thesis presents an automated species recognition approach named Timed and Probabilistic Automata. A small lexicon for describing animal calls is defined, six algorithms for acoustic component detection are developed, and a series of species recognisers are built and evaluated.The presented automated species recognition approach yields significant improvement on the analysis performance over a real world dataset, and may be transferred to commercial software in the future.

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ID Code: 71390
Item Type: QUT Thesis (PhD)
Supervisor: Zhang, Jinglan, Roe, Paul, & Towsey, Michael
Keywords: Automated Species Recognition, Animal Call Structure, Acoustic Component, Acoustic Component Definition, Acoustic Component Detection, Timed and Probabilistic Automata, Syntactic Pattern Recognition
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 29 May 2014 01:48
Last Modified: 21 Jun 2017 14:49

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