A review of computer-based methods for the automated detection, extraction, and classification of marine mammal sounds.

Abstract

Passive acoustic systems used to study and monitor marine mammals generate enormous datasets which are costly and time-consuming to analyze. As part of a Joint Industry Programme sponsored effort, we reviewed automated and semi-automated methods and software packages available to detect, extract, and classify marine mammal sounds; identified gaps in capabilities and knowledge; and suggested ways forward. Because of the variability in marine mammal sounds, no single method is effective for all species. While spectrogram correlation works well for stereotyped calls, more general methods like band-limited threshold detection are more effective for variable sounds. Feature extraction is a rapidly evolving field, but a reliable, automated method has yet to be successfully implemented into existing software. A major gap in our capabilities is the ability to reliably detect and classify the highly variable signals produced by some species. The development of effective, efficient, and standardized methods applicable to many species will require large, validated datasets. The acquisition, maintenance, and availability of such datasets will entail concerted, collaborative efforts. Development of common datasets and organization of workshops that focus on furthering detection, extraction, and classification methods are two ways to address these important issues in the automated analysis of marine mammal sounds.