Using feature vectors to detect frog calls in wireless sensor networks | Zendy

Benjamin Croker | Zendy; Navinda Kottege | Zendy

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Using feature vectors to detect frog calls in wireless sensor networks

Author(s) -

Benjamin Croker,

Navinda Kottege

Publication year - 2012

Publication title -

the journal of the acoustical society of america

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.619

H-Index - 187

eISSN - 1520-8524

pISSN - 0001-4966

DOI - 10.1121/1.3702792

Subject(s) - sensitivity (control systems) , computer science , feature (linguistics) , euclidean distance , noise (video) , feature vector , pattern recognition (psychology) , set (abstract data type) , artificial intelligence , wireless sensor network , wireless , speech recognition , acoustics , physics , telecommunications , computer network , engineering , philosophy , linguistics , image (mathematics) , programming language , electronic engineering

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.

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