Detection and classification of call types in the vocalizations of north-east pacific blue whales
Résumé
Characterization of marine mammal vocalizations is of great help for understanding underwater issues such as underwater communication, sonar detection and localization, marine mammal monitoring, ect. The vocalizations of the North-East Pacific (NEPAC) blue whales are known to be made of at least three different call types: the A call, the B call and the C call. This study aims at the development of a wholly automatic process of detection and classification for the two most common call types of the NEPAC population which are the A call and the B call. We created one template for the A call and one for the B call in order to extract features with matchfiltering operations. Features are then analyzed and we show that a simple Gaussian Mixture Model classifier can be used to accurately track and identify the call types in 24 hours long records. The proposed methodology is applied to real data sets recorded by seismic sensors gathered thanks to the Keck Foundation.