Birdsong of Bengalese finches follows Zipf's law, a pattern seen in human language

Scientists studying Bengalese finches discovered that the birds' vocalizations conform to Zipf's law, where a small set of sounds dominate usage while the majority appear infrequently. This distribution mirrors the frequency pattern of words in human languages and has also been documented in humpback whale songs, indicating a convergent feature across unrelated evolutionary lines. By applying a parsing algorithm—originally designed for whale song—that flags rare sound transitions, the researchers segmented hundreds of finch recordings and tallied each unit's frequency, finding a close fit to the Zipfian curve.

Simon Kirby of the University of Edinburgh, a co-author of the study, argues that such similarities point to a new way of categorizing communication systems based on cultural learning versus genetic encoding. He suggests the pattern may help young birds and whales acquire their songs, much as Zipfian distributions aid human infants in language learning. Computational linguist Richard Futrell noted that Zipf's law can arise from many processes, but the accumulating evidence strengthens the link between the law and learning. The findings appear in the journal Science Advances, and the team plans to explore additional linguistic parallels in animal communication.