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Hodge, LEW, Baumann-Pickering S, Hildebrand JA, Bell JT, Cummings EW, Foley HJ, McAlarney RJ, McLellan WA, Pabst DA, Swaim ZT, Waples DM, Read AJ.  2018.  Heard but not seen: Occurrence of Kogia spp. along the western North Atlantic shelf break. Marine Mammal Science. 34:1141-1153.   10.1111/mms.12498   AbstractWebsite
Roch, MA, Brandes ST, Patel B, Barkley Y, Baumann-Pickering S, Soldevilla MS.  2011.  Automated extraction of odontocete whistle contours. Journal of the Acoustical Society of America. 130:2212-2223.   10.1121/1.3624821   AbstractWebsite

Many odontocetes produce frequency modulated tonal calls known as whistles. The ability to automatically determine time x frequency tracks corresponding to these vocalizations has numerous applications including species description, identification, and density estimation. This work develops and compares two algorithms on a common corpus of nearly one hour of data collected in the Southern California Bight and at Palmyra Atoll. The corpus contains over 3000 whistles from bottlenose dolphins, long- and short-beaked common dolphins, spinner dolphins, and melon-headed whales that have been annotated by a human, and released to the Moby Sound archive. Both algorithms use a common signal processing front end to determine time x frequency peaks from a spectrogram. In the first method, a particle filter performs Bayesian filtering, estimating the contour from the noisy spectral peaks. The second method uses an adaptive polynomial prediction to connect peaks into a graph, merging graphs when they cross. Whistle contours are extracted from graphs using information from both sides of crossings. The particle filter was able to retrieve 71.5% (recall) of the human annotated tonals with 60.8% of the detections being valid (precision). The graph algorithm's recall rate was 80.0% with a precision of 76.9%. (C) 2011 Acoustical Society of America. [DOI: 10.1121/1.3624821]