Hybrid framework for categorising sounds of mysticete whales

This study addresses a problem belonging to the domain of whale audio processing, more specifically the automatic classification of sounds produced by the Mysticete species. The specific task is quite challenging given the vast repertoire of the involved species, the adverse acoustic conditions and the nearly inexistent prior scientific work. Two feature sets coming from different domains (frequency and wavelet) were designed to tackle the problem. These are modelled by means of a hybrid technique taking advantage of the merits of a generative and a discriminative classifier. The dataset includes five species (Blue, Fin, Bowhead, Southern Right, and Humpback) and it is publicly available at http://www.mobysound.org/. The authors followed a thorough experimental procedure and achieved quite encouraging recognition rates.