Robust Automatic Detector And Feature Extractor For Dolphin Whistles

A key in Dolphin’s conservation efforts is population
estimation in their natural environment. A common
method for mapping Dolphin’s appearance 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 shows a good trade off between detection
and false alarm, that compares well with the widely used
PAMguard system.

Robust Automatic Detector And Feature Extractor For Dolphin Whistles
Robust Automatic Detector And Feature Extractor For Dolphin Whistles
Robust Automatic Detector And Feature Extractor For Dolphin Whistles
Collaboration:

Published Paper:

Robust Automatic Detector And Feature Extractor For Dolphin Whistles, IEEE Oceans 2019, Marseille France