Statistical Learning of Complex Questions


The problem of auxiliary fronting in complex polar questions occupies a prominent position within the nature versus nurture controversy in language acquisition. We employ a model of statistical learning which uses sequential and semantic information to produce utterances from a bag of words. This linear learner is capable of generating grammatical questions without exposure to these structures in its training environment. We show that the model performs superior to n-gram learners on this task. Implications for nativist theories of language acquisition are discussed.

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