Learning Auxiliary Fronting with Grammatical Inference

Alexander Clark; Remi Eyraud

Learning Auxiliary Fronting with Grammatical Inference

Alexander Clark, Remi Eyraud

Philosophy

Research output: Chapter in Book/Report/Conference proceeding › Conference paper

15 Citations (Scopus)

Abstract

We present a simple context-free grammatical inference algorithm, and prove that it is capable of learning an interesting subclass of context-free languages. We also demonstrate that an implementation of this algorithm is capable of learning auxiliary fronting in polar interrogatives (AFIPI) in English. This has been one of the most important test cases in language acquisition over the last few decades. We demonstrate that learning can proceed even in the complete absence of examples of particular constructions, and thus that debates about the frequency of occurrence of such constructions are irrelevant. We discuss the implications of this on the type of innate learning biases that must be hypothesized to explain first language acquisition.

Original language	Undefined/Unknown
Title of host publication	Proceedings of CoNLL
Pages	125-132
Number of pages	8
Publication status	Published - 2006

Cite this

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abstract = "We present a simple context-free grammatical inference algorithm, and prove that it is capable of learning an interesting subclass of context-free languages. We also demonstrate that an implementation of this algorithm is capable of learning auxiliary fronting in polar interrogatives (AFIPI) in English. This has been one of the most important test cases in language acquisition over the last few decades. We demonstrate that learning can proceed even in the complete absence of examples of particular constructions, and thus that debates about the frequency of occurrence of such constructions are irrelevant. We discuss the implications of this on the type of innate learning biases that must be hypothesized to explain first language acquisition.",

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AB - We present a simple context-free grammatical inference algorithm, and prove that it is capable of learning an interesting subclass of context-free languages. We also demonstrate that an implementation of this algorithm is capable of learning auxiliary fronting in polar interrogatives (AFIPI) in English. This has been one of the most important test cases in language acquisition over the last few decades. We demonstrate that learning can proceed even in the complete absence of examples of particular constructions, and thus that debates about the frequency of occurrence of such constructions are irrelevant. We discuss the implications of this on the type of innate learning biases that must be hypothesized to explain first language acquisition.

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EP - 132

BT - Proceedings of CoNLL

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