Implicit learning of recursive context-free grammars

Rohrmeier, Martin, Fu, Qiufang and Dienes, Zoltan (2012) Implicit learning of recursive context-free grammars. PLoS ONE, 7 (10). e45885. ISSN 1932-6203

PDF - Published Version
Available under License Creative Commons Attribution.

Download (623kB) | Preview


Context-free grammars are fundamental for the description of linguistic syntax. However, most artificial grammar learning
experiments have explored learning of simpler finite-state grammars, while studies exploring context-free grammars have
not assessed awareness and implicitness. This paper explores the implicit learning of context-free grammars employing
features of hierarchical organization, recursive embedding and long-distance dependencies. The grammars also featured
the distinction between left- and right-branching structures, as well as between centre- and tail-embedding, both
distinctions found in natural languages. People acquired unconscious knowledge of relations between grammatical classes
even for dependencies over long distances, in ways that went beyond learning simpler relations (e.g. n-grams) between
individual words. The structural distinctions drawn from linguistics also proved important as performance was greater for
tail-embedding than centre-embedding structures. The results suggest the plausibility of implicit learning of complex
context-free structures, which model some features of natural languages. They support the relevance of artificial grammar
learning for probing mechanisms of language learning and challenge existing theories and computational models of
implicit learning.

Item Type: Article
Schools and Departments: School of Psychology > Psychology
Subjects: B Philosophy. Psychology. Religion
Depositing User: Lene Hyltoft
Date Deposited: 13 Nov 2013 09:44
Last Modified: 02 Jul 2019 22:00

View download statistics for this item

📧 Request an update