ABSTRACT 

Humpback whale song is comprised of well-structured distinct levels of organisation: combinations of sounds, repetition of combinations, and a sequence of repetitions, which have no clear silent intervals. This continuous sound output can be hard to delimit, rather, it could be interpreted as a long series of states of a system. Recurrence plots are graphical representations of such series of states and have been used to describe animal behaviour previously. Here, we aim to apply this tool to visualise and recognise structures traditionally used in inferences about behaviour (songs and themes) in the series of units manually extracted from recordings of humpback whales. Data from the Abrolhos bank, Brazil were subjected to these analyses. Our analytical tool has proven efficient in identifying themes and songs from continuous recordings avoiding some of the human perception bias and caveats. Furthermore, our song extraction is robust to errors coming from both manual and automated transcriptions, constructing a level of description largely independent of the first stage of analysis.