Sparse coding of humpback whale songs for their survey

Male humpback whales emit songs during the breeding season. These songs are made with successive vocalizations called sound units. The study of these songs is based on the classification of these sound units, especially to extract the song theme of the singers in a specific area during a specific season. Recently, some approaches are proposed for automatic classification of these sound units. This paper introduces the sparse coding as a robust unsupervised classifier to generate efficient time-frequency representation of the calls of the whale. Secondly, the subunit shows to be interesting to analyze the evolution of the humpback whale songs during two years. It is statistically shown that the shortest units are the most stable (occurring with similar time frequency shape across the two years), while the longest units are evolving from one year to one other.