Automatic classification of humpback whale social calls (original) (raw)
The Journal of the Acoustical Society of America
Acoustic methods are becoming increasingly common in the study of marine mammal populations and behavior. Automating the detection and classification of whale vocalizations has been a central aim of these methods. The focus has primarily been on intra-species detection and classification, however, humpback whale (Megaptera novaeangliae) social call detection and classification has largely remained a manual task in the bioacoustics community. To automate this process, we processed spectrograms of calls using PCA-based and connected-component-based methods, and derived features from relative power in the frequency bins of these spectrograms. We then used these features to train and test a supervised Hidden Markov Model (HMM) algorithm to investigate classification feasibility.
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