Automatic Classification of Cetacean Vocalizations Using an Aural Classifier.

摘要

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 active-sonar echoes from man-made (i.e. metallic) structures and naturally occurring clutter sources 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 the method should be able to classify marine mammal vocalizations since these calls possess many of the acoustic attributes of music.