Linguistics and Computation (Center for the Study of Language and Information Publication Lecture Notes)

Cole, Jennifer S.; Green, Georgia M.; Morgan, Jerry L.

ISBN 10: 1881526828 / ISBN 13: 9781881526827

Edité par The Center for the Study of Language and Information Publications, 1995

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N° de réf. du vendeur 011624

Détails bibliographiques

• Titre: Linguistics and Computation (Center for the Study of Language and Information Publication Lecture Notes)
• Éditeur: The Center for the Study of Language and Information Publications
• Date de parution: 1995
• Langue: espagnol
• ISBN à 10 chiffres: 1881526828
• ISBN à 13 chiffres: 9781881526827
• Reliure: Encuadernación de tapa dura
• État de l'article: Muy bien

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Synopsis

This volume is a collection covering the diverse areas of psycholinguistics, syntax, computational linguistics and phonology. Abney's paper on Chunks provides an interesting new approach to phrase structure, motivated by psycholinguist data, something that is rarely done. Berwick and Fong provide a history of computational implementations of (Chomskyan) Transformational Grammar. Cole's phonology paper, arguing from Chamorro and English stress that cyclicity is not needed in phonology, is also preceded by a one-and-a-half-page introduction on why this is relevant to computation. Coleman's contribution summarises work on computational phonology and describes the York Talk speech synthesis system. Hirschberg and Sproat's paper describes a system they have written to assign pitch accent to unrestricted text in an RT&T text-to-speech system. This is very much applied natural language processing, but their system represents a more thorough-going attempt at doing this well than has been previously attempted, and this appears to be the first write-up of this work. Johnson and Moss introduce Stratified Feature Grammar, a formal model of language, inspired by Relational Grammar but formalised by using and extending tools developed in the unification grammar community. Finally, Nakazawa extends further Tomita's work so that computer science LR parsing methods can be applied to natural language grammars, here feature-based grammars.