Syntactic Islands and Learning Biases: Combining Experimental Syntax and Computational Modeling to Investigate the Language Acquisition Problem

Autor/inn/en	Pearl, Lisa; Sprouse, Jon
Titel	Syntactic Islands and Learning Biases: Combining Experimental Syntax and Computational Modeling to Investigate the Language Acquisition Problem
Quelle	In: Language Acquisition: A Journal of Developmental Linguistics, 20 (2013) 1, S.23-68 (46 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1048-9223
DOI	10.1080/10489223.2012.738742
Schlagwörter	Logical Thinking; Syntax; Brain; Learning Strategies; Language Acquisition; Computational Linguistics; Grammar; Language Universals; Linguistic Theory; Children; Child Language; Linguistic Input; Language Research; Language Processing + Suchen Sie Ihr Suchwort? Gehirn; Learning methode; Learning techniques; Lernmethode; Lernstrategie; Sprachaneignung; Spracherwerb; Linguistics; Computerlinguistik; Grammatik; Linguistische Theorie; Child; Kind; Kinder; 'Children''s language'; Kindersprache; Sprachbildung; Sprachforschung; Sprachverarbeitung
Abstract	The induction problems facing language learners have played a central role in debates about the types of learning biases that exist in the human brain. Many linguists have argued that some of the learning biases necessary to solve these language induction problems must be both innate and language-specific (i.e., the Universal Grammar (UG) hypothesis). Though there have been several recent high-profile investigations of the necessary learning bias types for different linguistic phenomena, the UG hypothesis is still the dominant assumption for a large segment of linguists due to the lack of studies addressing central phenomena in generative linguistics. To address this, we focus on how to learn constraints on long-distance dependencies, also known as syntactic island constraints. We use formal acceptability judgment data to identify the target state of learning for syntactic island constraints and conduct a corpus analysis of child-directed data to affirm that there does appear to be an induction problem when learning these constraints. We then create a computational learning model that implements a learning strategy capable of successfully learning the pattern of acceptability judgments observed in formal experiments, based on realistic input. Importantly, this model does not explicitly encode syntactic constraints. We discuss learning biases required by this model in detail as they highlight the potential problems posed by syntactic island effects for any theory of syntactic acquisition. We find that, although the proposed learning strategy requires fewer complex and domain-specific components than previous theories of syntactic island learning, it still raises difficult questions about how the specific biases required by syntactic islands arise in the learner. We discuss the consequences of these results for theories of acquisition and theories of syntax. (Contains 5 tables, 6 figures, and 14 footnotes.) (As Provided).
Anmerkungen	Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10