Abstract

A wide range of species use acoustic communication, increasing their own fitness by transmitting signals to alter the behaviour of con- or hetero-specifics. These signals contain “information” of some sort – but what is the nature of that information, and how is it represented acoustically? By understanding how information is encoded, and how animal perception is converted into understanding, we can uncover clues to the cognitive processes taking place in the animals’ brains, and also gain clues to the evolution of human language. In this talk, I will present some of my recent work on animal acoustic sequences, and some novel mathematical techniques for analysing them. How can we define complexity in acoustic communication, and what role does vocal complexity play in social behaviour, such as in the highly diverse mimicry of the mockingbird? How do dolphins process subtle acoustic differences, to distinguish between their individually characteristic signature whistles? Can we decode species-specific acoustic information to aid conservation of endangered animals such as the red wolf? And what is the process by which many species generate long sequences of distinct syllables? These sequences may appear random, but by comparing them to different stochastic models, we find that traditional assumptions of Markovian vocal sequence production poorly describe the sequence repertoire, challenging traditional models of language evolution. Mathematical methods for analysing animal acoustic communication offer the potential of unlocking the information contained within; allowing us to develop and test new hypotheses of behavioural ecology, and social and behavioural evolution.