title: Using feature vectors to detect frog calls in wireless sensor networks.
abstract: A method for detecting vocalization of giant barred frogs (Mixophyes iteratus) in noisy audio is proposed. Audio recordings from remote wireless sensor nodes were segmented into individual sounds and from each sound a small set of features was extracted. Feature vectors were compared to those of example calls using a Euclidean distance formula as a detection system. The system achieved a sensitivity of 0.85 with specificity of 0.92 when distinguishing M. iteratus calls from other species' calls and sensitivity of 0.88 with specificity 0.82 against background noise.
authors.affiliation: School of Information Technology and Electrical Engineering, University of Queensland, St Lucia, Queensland 4072, Australia. benjamin.croker@gmail.com
authors.forename: Benjamin
authors.initials: B
authors.lastname: Croker
authors.forename: Navinda
authors.initials: N
authors.lastname: Kottege
mesh_terms: D000818:Animals; D056727:Endangered Species; D009622:Noise; D011898:Ranidae / Q000502:physiology*; D012680:Sensitivity and Specificity; D013018:Sound Spectrography; D014828:Vocalization, Animal / Q000502:physiology*; D059015:Wireless Technology / Q000295:instrumentation*