Emergence of combinatorial structure and economy through iterated learning with continuous acoustic signals

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Human speech has combinatorial structure, but it is still unclear how this type of organization emerged in the course of language evolution. There are two positions in the debate about the evolution of combinatorial structure: one stresses the importance of distinctiveness, while the other stresses economy and efficient reuse of building blocks. Different sources of evidence can be used to investigate the origins of combinatorial structure, such as emerging sign languages, animal communication systems, analysis of modern language and computer simulations but each source has its problems. In this article it is demonstrated that a novel empirical method from the field of language evolution can help to gain insight into the emergence of phonological combinatorial organization. This method, experimental iterated learning, allows investigating cultural evolution and the development of structure over time with human participants. We present data from an experiment in which combinatorial structure emerges in artificial whistled languages. We show that our experiment can give insight into the role of distinctiveness and reuse of building blocks and how they interact. We argue that experimental iterated learning offers a valuable new tool for investigating questions on evolutionary phonology and phonetics.