Accession Number : ADA573485
Title : Automatic Classification of Cetacean Vocalizations Using an Aural Classifier
Descriptive Note : Annual rept.
Corporate Author : DEFENCE RESEARCH AND DEVELOPMENT ATLANTIC DARTMOUTH (CANADA)
Personal Author(s) : Hines, Paul C ; Binder, Carolyn M
Report Date : 30 Sep 2012
Pagination or Media Count : 9
Abstract : LONG-TERM GOALS: To develop a robust automatic classifier with a high probability of detection and a low false alarm rate that can classify vocalizations from a variety of cetacean species. In this research, we wish to apply a unique automatic classifier developed by the PI that uses perceptual signal features - features similar to those employed by the human auditory system to classify cetacean species vocalizations and reject anthropogenic false alarms. This aural classifier has been successfully used to distinguish between active-sonar echoes from man-made (i.e. metallic) structures and naturally occurring clutter sources [1, 2] and performs as well or better than expert sonar operators . Many of the features were inspired by research directed at discriminating the timbre of different musical instruments a passive classification problem which suggests it should be able to classify marine mammal vocalizations since these calls possess many of the acoustic attributes of music.
Descriptors : *CLASSIFICATION , *MARINE BIOLOGICAL NOISE , BIOACOUSTICS , CETACEA
Subject Categories : Biological Oceanography
Distribution Statement : APPROVED FOR PUBLIC RELEASE