title: Model-based automated detection of echolocation calls using the link detector.
abstract: The link detector combines a model-based spectral peak tracker with an echo filter to detect echolocation calls of bats. By processing calls in the spectrogram domain, the links detector separates calls that overlap in time, including call harmonics and echoes. The links detector was validated by using an artificial recording environment, including synthetic calls, atmospheric absorption, and echoes, which provided control of signal-to-noise ratio and an absolute ground truth. Maximum hit rate (2% false positive rate) for the links detector was 87% compared to 1.5% for a spectral peak detector. The difference in performance was due to the ability of the links detector to filter out echoes. Detection range varied across species from 13 to more than 20 m due to call bandwidth and frequency range. Global features of calls detected by the links detector were compared to those of synthetic calls. The error in all estimates increased as the range increased, and estimates of minimum frequency and frequency of most energy were more accurate compared to maximum frequency. The links detector combines local and global features to automatically detect calls within the machine learning paradigm and detects overlapping calls and call harmonics in a unified framework.
authors.affiliation: Department of Biology, University of Western Ontario, London, Ontario, Canada. mskowro2@uwo.ca
authors.forename: Mark D
authors.initials: MD
authors.lastname: Skowronski
authors.forename: M Brock
authors.initials: MB
authors.lastname: Fenton
mesh_terms: D000162:Acoustics; D000818:Animals; D002685:Chiroptera; D003198:Computer Simulation; D004455:Echolocation / Q000502:physiology*; D001330:Electronic Data Processing; D004777:Environment; D008954:Models, Biological