Abstract
Songs produced by migrating whales were recorded off the coast of Queensland, Australia over 6 consecutive weeks in 2003. Approximately 50 songs were analyzed using information theory techniques. The average length of the songs estimated by correlation analysis was approximately 100 units, with song sessions lasting from 300 to over 3100 units. Song entropy, a measure of structural constraints and complexity, was estimated using three different methodologies: (1) the independently identically distributed model; (2) first- order Markov model; and (3) the nonparametric sliding window match length (SWML) method, as described in Suzuki et al. [J. Acoust. Soc. Am. 119, 1849 (2006)]. The analysis finds the songs of migrating Australian whales are consistent with the hierarchical structure proposed by Payne and McVay (Science 173, 585-597 (1971)], and recently confirmed by Suzuki et al. for singers on the breeding grounds. Both the SWML entropy estimates and the song lengths for the Australian singers were lower than that reported by Suzuki et al. for Hawaiian whales in 1976-1978. These lower SWML entropy values indicate a higher level of predictability within songs. The average total information in the Australian sequence of song units was approximately 35 bits/song. Aberrant songs (10%) yielded entropies similar to the typical songs. [Sponsored by ONR and DSTO.]