The structure of humpback whale (Megaptera novaeangliae) songs was examined using information theory techniques. The song is an ordered sequence of individual sound elements separated by gaps of silence. Song samples were converted into sequences of discrete symbols by both human and automated classifiers. This paper analyzes the song structure in these symbol sequences using information entropy estimators and autocorrelation estimators. Both parametric and nonparametric entropy estimators are applied to the symbol sequences representing the songs. The results provide quantitative evidence consistent with the hierarchical structure proposed for these songs by Payne and McVay [Science 173, 587–
Information entropy of humpback whale songsa)
Current address: Speech and Hearing Bioscience and Technology, Harvard-MIT Division of Health Science and Technology, Massachusetts Institute of Technology, Cambridge, MA 02139.
Ryuji Suzuki, John R. Buck, Peter L. Tyack; Information entropy of humpback whale songs. J. Acoust. Soc. Am. 1 March 2006; 119 (3): 1849–1866. https://doi.org/10.1121/1.2161827
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