Abstract
Human vocalization systems are characterized by complex structural properties. They are combinatorial, based on the systematic reuse of phonemes, and the set of repertoires in human languages is characterized by both strong statistical regularities—universals—and a great diversity. Besides, they are conventional codes culturally shared in each community of speakers. What are the origins of the forms of speech? What are the mechanisms that permitted their evolution in the course of phylogenesis and cultural evolution? How can a shared speech code be formed in a community of individuals? This chapter focuses on the way the concept of self-organization, and its interaction with natural selection, can throw light on these three questions. In particular, a computational model is presented which shows that a basic neural equipment for adaptive holistic vocal imitation, coupling directly motor and perceptual representations in the brain, can generate spontaneously shared combinatorial systems of vocalizations in a society of babbling individuals. Furthermore, we show how morphological and physiological innate constraints can interact with these self-organized mechanisms to account for both the formation of statistical regularities and diversity in vocalization systems.
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Notes
- 1.
We only give here a general description of the system: a detailed mathematical description is available in (Oudeyer 2006).
- 2.
Connections between the two maps evolve according to Hebb’s law: those that link neurons that are often activated in a correlated manner are reinforced, whereas those that link neurons with uncorrelated activation become weaker. These connections are initially random, and through babbling and Hebb’s law, they self-organize and finally allow the robot to find motor commands that correspond to a given sound that he perceives.
- 3.
Neurons adapt to stimuli through sensitization: their dynamics is such that if a stimulus S is perceived, then they are modified such that if the same stimulus S would be presented just afterwards they would be more activated than the first time, and the amount of modification depends exponentially on their activation (strongly activated neurons are modified most).
- 4.
- 5.
This term was introduced in (Gould and Vrba 1982). It refers to the use of a biological feature/structure for a function A which is different than the function B for which it was initially evolutionary selected.
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Acknowledgments
This work was in major part achieved in the Sony Computer Science Laboratory, Paris, and benefited from the support of Luc Steels.
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Oudeyer, PY. (2013). Self-Organization: Complex Dynamical Systems in the Evolution of Speech. In: Binder, PM., Smith, K. (eds) The Language Phenomenon. The Frontiers Collection. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36086-2_9
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