The cognitive roots of regularization in language

Regularization occurs when the output a learner produces is less variable than the linguistic data they observed. In an artificial language learning experiment, we show that there exist at least two independent sources of regularization bias in cognition: a domain-general source based on cognitive l...

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Bibliographic Details
Published in:Cognition 2019-03, Vol.184, p.53-68
Main Authors: Ferdinand, Vanessa, Kirby, Simon, Smith, Kenny
Format: Article
Language:English
Subjects:
Adolescent
Adult
Aged
Artificial languages
Cognition
Cognitive ability
Cognitive bias
Cognitive load
Cultural change
Cultural factors
Cultural transmission
Domain generality
Domain specificity
Encoding (Cognitive process)
Entropy
Evolution
Female
Frequency learning
Humans
Language
Language acquisition
Language Development
Language evolution
Learning
Linguistics
Male
Middle Aged
Models, Psychological
Origin of language
Regularisation
Regularity
Young Adult
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Summary:Regularization occurs when the output a learner produces is less variable than the linguistic data they observed. In an artificial language learning experiment, we show that there exist at least two independent sources of regularization bias in cognition: a domain-general source based on cognitive load and a domain-specific source triggered by linguistic stimuli. Both of these factors modulate how frequency information is encoded and produced, but only the production-side modulations result in regularization (i.e. cause learners to eliminate variation from the observed input). We formalize the definition of regularization as the reduction of entropy and find that entropy measures are better at identifying regularization behavior than frequency-based analyses. Using our experimental data and a model of cultural transmission, we generate predictions for the amount of regularity that would develop in each experimental condition if the artificial language were transmitted over several generations of learners. Here we find that the effect of cognitive constraints can become more complex when put into the context of cultural evolution: although learning biases certainly carry information about the course of language evolution, we should not expect a one-to-one correspondence between the micro-level processes that regularize linguistic datasets and the macro-level evolution of linguistic regularity.
ISSN:0010-0277
1873-7838
DOI:10.1016/j.cognition.2018.12.002