Journal ArticleDOI
A method for detecting whistles, moans, and other frequency contour sounds.
TLDR
An algorithm is presented for the detection of frequency contour sounds-whistles of dolphins and many other odontocetes, moans of baleen whales, chirps of birds, and numerous other animal and non-animal sounds.Abstract:
An algorithm is presented for the detection of frequency contour sounds-whistles of dolphins and many other odontocetes, moans of baleen whales, chirps of birds, and numerous other animal and non-animal sounds. The algorithm works by tracking spectral peaks over time, grouping together peaks in successive time slices in a spectrogram if the peaks are sufficiently near in frequency and form a smooth contour over time. The algorithm has nine parameters, including the ones needed for spectrogram calculation and normalization. Finding optimal values for all of these parameters simultaneously requires a search of parameter space, and a grid search technique is described. The frequency contour detection method and parameter optimization technique are applied to the problem of detecting "boing" sounds of minke whales from near Hawaii. The test data set contained many humpback whale sounds in the frequency range of interest. Detection performance is quantified, and the method is found to work well at detecting boings, with a false-detection rate of 3% for the target missed-call rate of 25%. It has also worked well anecdotally for other marine and some terrestrial species, and could be applied to any species that produces a frequency contour, or to non-animal sounds as well.read more
Citations
More filters
Journal ArticleDOI
A generalized baleen whale call detection and classification system
TL;DR: A generalized automated detection and classification system (DCS) was developed to efficiently and accurately identify low-frequency baleen whale calls and classifies calls based on attributes of the resulting pitch tracks using quadratic discriminant function analysis (QDFA).
Journal ArticleDOI
Automatic detection and classification of odontocete whistles.
TL;DR: Methods for the fully automatic detection and species classification of odontocete whistles are described and a classifier has been developed specifically to work with fragmented whistle detections.
Journal ArticleDOI
Comparing marine mammal acoustic habitats in Atlantic and Pacific sectors of the High Arctic: year-long records from Fram Strait and the Chukchi Plateau
Sue E. Moore,Kathleen M. Stafford,Humfrey Melling,Catherine L. Berchok,Øystein Wiig,Kit M. Kovacs,Christian Lydersen,Jackie Richter-Menge +7 more
TL;DR: Examination of species-specific marine mammal calls recorded from autumn 2008–2009 revealed distinctly different acoustic habitats at each site, providing a provisional baseline for the comparison of underwater acoustic habitats between Pacific and Atlantic sectors of the High Arctic.
Journal ArticleDOI
Marine mammal acoustic detections in the northeastern Chukchi Sea, September 2007–July 2011
David E. Hannay,Julien Delarue,Xavier Mouy,Bruce Martin,Del Leary,Julie N. Oswald,Jonathan Vallarta +6 more
TL;DR: In this article, a wide area of the northeastern Chukchi Sea off the coast of Alaska from Cape Lisburne to Barrow, at distances from 8 km to 200 km from the coast, was studied.
Journal ArticleDOI
Social vocalizations of big brown bats vary with behavioral context.
Marie A. Gadziola,Marie A. Gadziola,Jasmine M. S. Grimsley,Paul A. Faure,Jeffrey J. Wenstrup,Jeffrey J. Wenstrup +5 more
TL;DR: A paradigm that could evoke aggressive vocalizations while monitoring heart rate as an objective measure of internal physiological state is designed and revealed a complex acoustic communication system among big brown bats in which acoustic cues and call structure signal the emotional state of a caller.
References
More filters
Proceedings Article
The DET Curve in Assessment of Detection Task Performance
TL;DR: The DET Curve is introduced as a means of representing performance on detection tasks that involve a tradeoff of error types and why it is likely to produce approximately linear curves.
Journal ArticleDOI
Estimating cetacean population density using fixed passive acoustic sensors: an example with Blainville's beaked whales.
TL;DR: Methods are developed for estimating the size/density of cetacean populations using data from a set of fixed passive acoustic sensors, potentially applicable to a wide variety of marine and terrestrial species that are hard to survey using conventional visual methods.
Journal ArticleDOI
Recognizing transient low-frequency whale sounds by spectrogram correlation.
TL;DR: The method described here, spectrogram correlation, is well-suited to recognition of animal sounds consisting of tones and frequency sweeps and could be especially useful for detecting a call type when relatively few instances of the call type are known.
Journal ArticleDOI
Underwater Sounds from the Blue Whale, Balaenoptera musculus
TL;DR: The most powerful low-frequency sounds were recorded from blue whales, Balaenoptera musculus, off the Chilean coast as mentioned in this paper, and these three-part sounds lasted about 36.5 seconds, and ranged in frequency from 12.5 to 200 Hz.
Journal ArticleDOI
Facts about signature whistles of bottlenose dolphins, Tursiops truncatus
Laela S. Sayigh,Laela S. Sayigh,H. Carter Esch,Randall S. Wells,Randall S. Wells,Randall S. Wells,Vincent M. Janik +6 more
TL;DR: Twenty whistles were randomly selected from each of 20 bottlenose dolphins from recordings made during brief capture–release events in Sarasota Bay, FL, U.S.A., and 10 judges were asked to visually group spectrograms based on similarity of their contours, and judges consistently grouped whistles according to the identity of the vocalizer.