Artificial sign language learning: a method for evolutionary linguistics
Previous research in evolutionary linguistics has made wide use of artificial language learning (ALL) paradigms, where learners are taught artificial languages in laboratory experiments and are subsequently tested about the language they have learnt. The ALL framework has proved particularly useful in the study of the evolution of language, allowing the manipulation of specific linguistic phenomena that cannot be isolated for study in natural languages. Furthermore, using ALL in populations of learners, for example with iterated learning methods, has highlighted the importance of cultural evolutionary processes in the evolution of linguistic structure.
In this talk, I present a methodology for studying the evolution of language in experimental populations. In the artificial sign language learning (ASLL) methodology I demonstrate, participants learn manual signaling systems that are used to interact with other participants. The research I present attempts to present a controlled study of the evolutionary mechanisms that drive linguistic structure, whilst providing an experimental companion to some of the only available evidence of language emergence and evolution in natural languages: emerging sign languages.
I detail two experiments that investigate the role of cultural evolutionary processes in the evolution of systematic linguistic structure. In the first study, I demonstrate how the combination of interaction and transmission to new learners leads to structured and efficient systems, in comparison to either interaction or transmission alone. In the second experiment, I expand the method to investigate complex grammatical constructions, investigating the emergence of systematic spatial modulation in novel communication systems, and providing a comparison to research on the emergence of spatial reference systems in natural sign languages.
The findings from these experiments offer a more precise understanding of the roles that different cultural mechanisms play in the evolution of language, and further builds a bridge between data collected from natural languages in the early stages of their evolution and the more controllable environments of experimental linguistic research.
13 APRIL 2017 | MPI Room 163 | 15.45 – 17.00