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The past fifteen years have seen great changes in the field of language acquisition. New experimental methods have yielded insights into the linguistic knowledge of ever younger children, and interest has grown in the phonological, syntactic, and semantic aspects of the lexicon. Computational investigations of language acquisition have also changed, reflecting, among other things, the profound shift in the field of natural language processing from hand-crafted grammars to grammars that are learned automatically from samples of naturally occurring language.Each of the four research papers in this book takes a novel formal approach to a particular problem in language acquisition. In the first paper, J. M. Siskind looks at developmentally inspired models of word learning. In the second, M. R. Brent and T. A. Cartwright look at how children could discover the sounds of words, given that word boundaries are not marked by any acoustic analog of the spaces between written words. In the third, P. Resnik measures the association between verbs and the semantic categories of their arguments that children likely use as clues to verb meanings. Finally, P. Niyogi and R. C. Berwick address the setting of syntactic parameters such as headedness--for example, whether the direct object comes before or after the verb.
List of contents
Advances in the computational study of language acquisition, Michael R. Brent; a computational study of cross-situational techniques for learning word-to-word mappings, Jeffrey Mark Siskind; distributional regularity and phonotactic constraints are useful for segmentation, Michael R. Brent and Timothy A. Cartwright; selectional constraints - an information-theoretic model and its computational realization, Philip Resnik; a language learning model for finite parameter spaces, Partha Niyogi and Robert C. Berwick.
