Note: This paper was originally written for L700 - "Language Acquisition" - a class taught by Laurent Dekydtspotter and Stephen Franks at Indiana University, Winter Semester, 2000. It is partly an elaboration of another paper Schemata: Bootstrapping Language Acquisition that is also available. The entire text is available here in PDF format. Below is the introduction and the bibliography. The paper itself is not completely proof-read but has been supplied regardless for time considerations.
This paper was also presented as "Ling Lunch" on Dec. 4, 2000 - the talk handout and overheads are also available.
A similar presentation by the same name was presented at BOOT-LA (A conference on Language Acquisition) on April 23rd, 2003. The power point from the presentation is available here. A recording of the talk (38 min) is available here.
If you prefer another format or have any questions or comments, feel free to E-mail me.

Schema Theorem in Language Acquisition: A Rags to Riches Story

by Sean McLennan

December 13, 2000




1. Introduction

Learning a language is a Herculean task; one that children perform with relative easy. Exposed only to a language environment one ripe with errors, incomplete utterances, and no "goodness" information a child can quickly and expertly acquire a communication system that is symbolic, combinatorial, productive, and expressive. With appropriate awe, linguists have posited that such a feat could not be performed without a boot-strapping mechanism of some sort; since Chomsky (1965) we have assumed that the language stimuli to which a child is exposed is impoverished and that to compensate for poor or indeterminate quality and inadequate quantity of input, humans come with a stock set of discrete, symbolic features and parameters commonly known Universal Grammar.

Considering the state of academic thought in Linguistics, Psychology, Computer Science all the areas that have contributed to the modern study of Cognitive Science this claim was both warranted and understandable. However, while other disciplines have increasingly shunned logical, symbolic, and a temporal models of intelligence and behavior due to overwhelming evidence to the contrary, modern theoretical linguistics has remained committed to the same framework.

This, I believe, is due to three reasons: 1) Linguists remain convinced that language can be 100% dissociated from other cognitive abilities; 2) Linguists remain convinced that language can be "lifted out" of the physical bodies within which it is instantiated; and 3) in general other disciplines are linguistically naive and have little respect for what linguists do. Given these facts, it is unsurprising that Linguistics as a field would be swayed by research performed in other areas. I believe that the "Poverty of Stimulus" argument in particular has held up over time because no one has provided linguists with a differing view of what constitutes the "input" (i.e. the language data), nor what constitutes the resulting phenomena (i.e. language, itself). If neither of these well-defined entities are challenged, there is no reason to challenge the underlying intuitions that gave rise to "Poverty of Stimulus".

The purpose then of this paper is to present a differing view of one of those well-defined entities the input. I maintain that what constitutes linguistic input differs dramatically from what we have previously thought and provide a new conception that is more parsimonious with current research in other cognitive disciplines. I argue that we can better understand this new notion of input and how it can give rise to a system as complicated as language through an abstracted form of Schema Theorem which has been used as a domain specific explanation of how Genetic Algorithms perform efficiently. Finally, I present a first step in trying to experimentally support to this new conception of input via a computational model of the acquisition of grammar.


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