Language Evolution and Computation Bibliography

Recent iterated language learning studies have shown that artificial languages evolve over the generations towards regularity. This trend has been explained as a reflection of the learners' biases. We test whether this learning bias for regularity is affected by culturally acquired knowledge, specifically by familiarity and literacy. The results of non-iterated learning experiments with miniature artificial musical and spoken languages suggest that familiarity helps us learn and reproduce the signals of a language, but literacy is required for regularities to be faithfully replicated. This in turn indicates that, by modifying human learning biases, literacy may play a role in the evolution of linguistic structure.

This paper explores a structure ubiquitous in grammar, the embedded tree, and develops a proposal for how such embedded structures played a fundamental role in the evolution of consonants and vowels. Assuming that linguistic capabilities emerged as a cognitive system from a simply reactive system and that such a transition required the construction of an internal mapping of the system body (cf. Cruse 2003), we propose that this mapping was determined through articulation and acoustics. By creating distinctions between articulators in the vocal tract or by acoustic features of sounds, and then embedding these distinctions, the various possible properties of consonants and vowels emerged. These embedded distinctions represent paradigmatic options for the production of sounds, which provide the basic building blocks for prosodic structure. By anchoring these embedded structures in the anatomy and physiology of the vocal tract, the evolution of phonology itself can be explained by extra-linguistic factors.