Whale song has remarkable similarities to human speech in terms of efficiency

(Press-News.org) Whale song can be as efficient as – and, in some cases, more efficient than – human communication, according to a new study in Science Advances. Meanwhile, new unrelated research in Science further investigates whale song’s adherence to a universal linguistic law, as observed in recordings of humpback whales.

 

Natural selection favors the pithy over the longwinded. For example, yelling “Duck!” is faster and far more effective than shouting “Be careful, there is an incoming projectile, and you need to move out of the way!” Two linguistic laws of abbreviation called Menzerath’s law and Zipf’s law calculate such efficiencies in vocalization. The former describes how efficiency increases when longer words or songs have shorter elements, such as syllables and notes. The latter says that efficiency increases when individual elements that are used more frequently are shorter. The independent work in Science Advances applies both Menzerath’s law and Zipf’s law to whale song, analyzing sequences from a total of 16 species of cetaceans, including dolphins and both toothed and baleen whales. Here, Mason Youngblood examined components within 65,511 whale song sequences and 51 human languages, defining efficiency by Menzerath’s law first. Vocalizations by 11 out of 16 species displayed Menzerath’s law at a degree equal to or greater than that seen in human speech. The exceptions were killer whales, Hector’s dolphins, Commerson’s dolphins, Heaviside’s dolphins, and North Pacific right whales. Youngblood then examined Zipf’s law. Only humpback and blue whales followed this law, and humpbacks alone followed the law to the extent seen in human speech.

 

In the unassociated study in Science, Inbal Arnon and colleagues applied quantitative methods typically used to evaluate infant speech and found that the culturally evolved learnability of human languages also applies to humpback whale song. In human language, structurally coherent units exhibit a frequency distribution that follows a power law, also known as a Zipfian distribution – an attribute that facilitates learning and likely enhances the accurate preservation of language across generations. Humpback whale song presents a compelling parallel to human language, as it is one of the most intricate vocal displays in the animal kingdom and is also passed down through cultural transmission. These songs are highly structured, consisting of nested hierarchical components – sound elements forming phrases, phrases repeating into themes, and themes combining into songs. If the statistical properties of human language arise from cultural transmission, similar patterns should be detectable in whale song. Arnon et al. used infant-inspired speech segmentation techniques to analyze 8 years of recorded humpback whale song data and discovered hidden structures within whale songs that exhibit striking parallels to human language. Specifically, these songs contain statistically coherent subsequences that conform to Zipfian distribution. Moreover, the lengths of these subsequences adhere to Zipf’s law of brevity, an efficiency-driven principle found in numerous species, including humans. This striking parallel between two evolutionarily distant species underscores the profound role of learning and cultural transmission in shaping communication across species, challenging the notion that such structural properties are exclusive to human language. “From what is known, humpback whale song and bird song exhibit patterns that follow these laws and principles without conveying the semantic meanings that human languages do. To this extent, we should perhaps be comparing whale songs to human music,” Andrew Whiten and Mason Youngblood write in a Perspective associated with the study in Science. “What these important parallels highlight is that communication systems in distantly related species may nevertheless converge toward similar structures, especially those that are complex, culturally learned, and effective.”

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