Vocal communication is a primary communication method of killer and pilot whales, and is used for transmitting a broad range of messages and information for short and long distance. The large variation in call types of these species makes it challenging to categorize them. In this study, sounds recorded by audio sensors carried by ten killer whales and eight pilot whales close to the coasts of Norway, Iceland, and the Bahamas were analyzed using computer methods and citizen scientists as part of the Whale FM project. Results show that the computer analysis automatically separated the killer whales into Icelandic and Norwegian whales, and the pilot whales were separated into Norwegian long-finned and Bahamas short-finned pilot whales, showing that at least some whales from these two locations have different acoustic repertoires that can be sensed by the computer analysis. The citizen science analysis was also able to separate the whales to locations by their sounds, but the separation was somewhat less accurate compared to the computer method.
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February 2014
February 01 2014
Classification of large acoustic datasets using machine learning and crowdsourcing: Application to whale calls
Lior Shamir;
Lior Shamir
a)
Lawrence Technological University
, 21000 Ten Mile Road, Southfield, Michigan 48075
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Carol Yerby;
Carol Yerby
Lawrence Technological University
, 21000 Ten Mile Road, Southfield, Michigan 48075
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Robert Simpson;
Robert Simpson
University of Oxford, Denys Wilkinson Building
, Keble Road, Oxford, OX1 3RH, United Kingdom
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Alexander M. von Benda-Beckmann;
Alexander M. von Benda-Beckmann
The Netherlands Organization for Applied Scientific Research
, P.O. Box 96864, The Hague, Zuid Holland, 2509 JG, The Netherlands
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Peter Tyack;
Peter Tyack
University of St. Andrews, St. Andrews, Fife
, KY16 9ST, Scotland, United Kingdom
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Filipa Samarra;
Filipa Samarra
University of St. Andrews, St. Andrews, Fife
, KY16 9ST, Scotland, United Kingdom
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Patrick Miller;
Patrick Miller
University of St. Andrews, St. Andrews, Fife
, KY16 9ST, Scotland, United Kingdom
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John Wallin
John Wallin
Middle Tennessee State University
, 1301 East Main Street, Murfreesboro, Tennessee 37130
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Lior Shamir
a)
Carol Yerby
Robert Simpson
Alexander M. von Benda-Beckmann
Peter Tyack
Filipa Samarra
Patrick Miller
John Wallin
Lawrence Technological University
, 21000 Ten Mile Road, Southfield, Michigan 48075a)
Author to whom correspondence should be addressed. Electronic mail: [email protected]
J. Acoust. Soc. Am. 135, 953–962 (2014)
Article history
Received:
April 07 2013
Accepted:
December 17 2013
Citation
Lior Shamir, Carol Yerby, Robert Simpson, Alexander M. von Benda-Beckmann, Peter Tyack, Filipa Samarra, Patrick Miller, John Wallin; Classification of large acoustic datasets using machine learning and crowdsourcing: Application to whale calls. J. Acoust. Soc. Am. 1 February 2014; 135 (2): 953–962. https://doi.org/10.1121/1.4861348
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