Cognitive Science webinar - in person

All known languages are made up of statistically coherent sequences - words - whose frequency distribution follows a power law known as a Zipfian distribution. Despite the ubiquity of these features across languages their origins are poorly understood. In this talk, I will argue that they arise because they facilitate learning and therefore emerge through the process of cultural transmission of language. I will present a set of results on the learnability sources and consequences of such distributions in human language. We will then summarise results from an experiment in which non-linguistic sequences evolve as they are transmitted from generation to generation of participants. By using insights from infant speech segmentation, we analyse those sequences and observe the emergence of Zipf's law over generations. This work makes a prediction that we should find Zipfian distribution of statistically coherent sequences wherever systems culturally evolve, including in other species. However, so far these features have only been found in humans. In the second part of the talk I will turn to the culturally evolving song of humpback whales and apply the same analytic technique to 8 years of whale recordings. Together with Ellen Garland and Simon Kirby, we show, for the first time in another species, that these characteristic statistical properties are indeed present in whale song. By doing so, we demonstrate a deep commonality between two species separated by tens of millions of years of evolution but united by both having culture.