Implicit learning of recursive context-free grammars.

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 explor...

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Autores principales:	Martin Rohrmeier, Qiufang Fu, Zoltan Dienes
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/056bb91f593640d3b8170a8d4b35a8c7
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id	oai:doaj.org-article:056bb91f593640d3b8170a8d4b35a8c7
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spelling	oai:doaj.org-article:056bb91f593640d3b8170a8d4b35a8c72021-11-18T08:11:32ZImplicit learning of recursive context-free grammars.1932-620310.1371/journal.pone.0045885https://doaj.org/article/056bb91f593640d3b8170a8d4b35a8c72012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23094021/?tool=EBIhttps://doaj.org/toc/1932-6203Context-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.Martin RohrmeierQiufang FuZoltan DienesPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 10, p e45885 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Martin Rohrmeier Qiufang Fu Zoltan Dienes Implicit learning of recursive context-free grammars.
description	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.
format	article
author	Martin Rohrmeier Qiufang Fu Zoltan Dienes
author_facet	Martin Rohrmeier Qiufang Fu Zoltan Dienes
author_sort	Martin Rohrmeier
title	Implicit learning of recursive context-free grammars.
title_short	Implicit learning of recursive context-free grammars.
title_full	Implicit learning of recursive context-free grammars.
title_fullStr	Implicit learning of recursive context-free grammars.
title_full_unstemmed	Implicit learning of recursive context-free grammars.
title_sort	implicit learning of recursive context-free grammars.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/056bb91f593640d3b8170a8d4b35a8c7
work_keys_str_mv	AT martinrohrmeier implicitlearningofrecursivecontextfreegrammars AT qiufangfu implicitlearningofrecursivecontextfreegrammars AT zoltandienes implicitlearningofrecursivecontextfreegrammars
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Implicit learning of recursive context-free grammars.

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