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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|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 > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Institution:||Queensland University of Technology|
|Deposited On:||29 May 2014 01:48|
|Last Modified:||09 Sep 2015 05:52|
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