Eliminating unpredictable variation through iterated learning.
نویسندگان
چکیده
Human languages may be shaped not only by the (individual psychological) processes of language acquisition, but also by population-level processes arising from repeated language learning and use. One prevalent feature of natural languages is that they avoid unpredictable variation. The current work explores whether linguistic predictability might result from a process of iterated learning in simple diffusion chains of adults. An iterated artificial language learning methodology was used, in which participants were organised into diffusion chains: the first individual in each chain was exposed to an artificial language which exhibited unpredictability in plural marking, and subsequent learners were exposed to the language produced by the previous learner in their chain. Diffusion chains, but not isolate learners, were found to cumulatively increase predictability of plural marking by lexicalising the choice of plural marker. This suggests that such gradual, cumulative population-level processes offer a possible explanation for regularity in language.
منابع مشابه
Structural priming in artificial languages and the regularisation of unpredictable variation
We present a novel experimental technique using artificial language learning to investigate the relationship between structural priming during communicative interaction, and linguistic regularity. We use unpredictable variation as a test-case, because it is a wellestablished paradigm to study learners’ biases during acquisition, transmission and interaction. We trained participants on artificia...
متن کاملEliminating unpredictable linguistic variation through interaction
Languages tend not to exhibit unpredictable variation. We explore alignment/accommodation during interaction as a mechanism to explain this cross-linguistic tendency. Specifically, we test the hypothesis (derived from historical linguistics) that interactions between categorical and variable users are inherently asymmetric: while variable users (of e.g. a grammatical marker) can accommodate to ...
متن کاملThe differential effects of transmission and interaction on linguistic variation
Variation in natural language is constrained: languages tend to lose competing variants over time, and where variation persists, its use tends to be conditioned on grammatical or sociolinguistic context. We had adult participants learn and communicate with artificial languages exhibiting unpredictable variation in plural marking. Using an iterated learning procedure, the languages produced by p...
متن کاملThomas’ theorem meets Bayes’ rule: a model of the iterated learning of language
We develop a Bayesian Iterated Learning Model (BILM) that models the cultural evolution of language as it is transmitted over generations of learners. We study the outcome of iterated learning in relation to the behavior of individual agents (their biases) and the social structure through which they transmit their behavior. BILM makes individual learning biases explicit and offers a direct comp...
متن کاملThe Evolution of Meaning-space Structure through Iterated Learning
In order to persist, language must be transmitted from generation to generation through a repeated cycle of use and learning. This process of iterated learning has been explored extensively in recent years using computational and mathematical models. These models have shown how compositional syntax provides language with a stability advantage and that iterated learning can induce linguistic ada...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Cognition
دوره 116 3 شماره
صفحات -
تاریخ انتشار 2010