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New paper on automated categorization

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Subject: New paper on automated categorization
From: Volker Deecke <>
Date: Mon, 9 Jan 2006 12:07:31 EST
Dear Colleagues,

I would like to draw your attention to the following paper, published in the 
January edition of the Journal of the Acoustical Society of America:

Deecke, V.B. and Janik, V.M. 2006. Automated categorization of bioacoustic 
signals: Avoiding perceptual pitfalls. Journal of the Acoustical Society of 
America 119(1): 645-653.

Dividing the acoustic repertoires of animals into biologically
relevant categories presents a widespread problem in the study of
animal sound communication, essential to any comparison of repertoires
between contexts, individuals, populations, or species. Automated
procedures allow rapid, repeatable, and objective categorization, but
often perform poorly at detecting biologically meaningful sound
classes. Arguably this is because many automated methods fail to
address the nonlinearities of animal sound perception. We present a
new method of categorization that incorporates dynamic time-warping
and an adaptive resonance theory (ART) neural network. This method was
tested on 104 randomly chosen whistle contours from four captive
bottlenose dolphins (Tursiops truncatus), as well as 50 frequency
contours extracted from calls of transient killer whales (Orcinus
orca). The dolphin data included known biologically meaningful
categories in the form of 42 stereotyped whistles produced when each
individual was isolated from its group. The automated procedure
correctly grouped all but two stereotyped whistles into separate
categories, thus performing as well as human observers. The
categorization of killer whale calls largely corresponded to visual
and aural categorizations by other researchers. These results suggest
that this methodology provides a repeatable and objective means of
dividing bioacoustic signals into biologically meaningful categories.

Automated categorization, automated classification, killer whale, bottlenose 
dolphin, signature whistle, neural network, call recognition, repertoire size, 
dynamic time-warping

Best regards

Volker Deecke

Volker Deecke, Ph.D.

Marine Mammal Research Unit   Cetacean Research Lab
University of BC              Vancouver Aquarium Marine Science Centre
AERL Bldg., 2202 Main Mall    P.O. Box 3232
Vancouver, BC, V6T 1Z4        Vancouver, BC V6B 3X8
Canada                        Canada 

Phone:  +1.604.822.9150       +1.604.659.3429/3430
Fax:    +1.604.822.8180       +1.604.659.3599


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