Robust automatic detector and feature extractor for dolphin whistles

A key in dolphin's conservation efforts is understanding their distribution and habitat preference. A common method for mapping dolphin's presence is the detection of their vocalizations. In this paper, we propose a novel detection technique for dolphin's whistles, referred to as ECV (Entropy, Correlation, and Viterbi algorithm). ECV is a robust detector of low complexity that automatically detects dolphin's whistles and extracts their spectral features, using a single receiver with only a few system parameters. The method employs a chain of decisions based on spectral entropy and time-domain correlation followed by constrained Viterbi algorithm to extract the whistles' features. Simulation results as well as performance over real recordings show a good trade-off between detection and false alarm, that compares well with the widely used PAMguard system.