15.2637, Books: Computational Linguistics/Syntax: Creswell

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Thu Sep 23 13:46:38 UTC 2004


LINGUIST List: Vol-15-2637. Thu Sep 23 2004. ISSN: 1068 - 4875.

Subject: 15.2637, Books: Computational Linguistics/Syntax: Creswell

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===========================Directory==============================

1)
Date: 22-Sep-2004
From: Dylan Maiden < dylan.maiden at taylorandfrancis.com >
Subject: Syntactic Form and Discourse Function in Natural Language Generation: Creswell


	
-------------------------Message 1 ----------------------------------
Date: Thu, 23 Sep 2004 09:45:04
From: Dylan Maiden < dylan.maiden at taylorandfrancis.com >
Subject: Syntactic Form and Discourse Function in Natural Language Generation: Creswell
Title: Syntactic Form and Discourse Function in Natural Language Generation
Series Title: Outstanding Dissertations in Linguistics

Publication Year: 2004
Publisher: Routledge (Taylor and Francis)
	      http://www.routledge.com/

Author: Cassandre Yvonne Creswell

Hardback: ISBN: 0415971047 Pages: 240 Price: 80.00 (U.S. $)

Abstract:

Users of natural languages have many word orders with which to encode
the same truth-conditional meaning. They choose contextually
appropriate strings from these many ways with little conscious effort
and with effective communicative results. Previous computational
models of when English speakers produce non-canonical word orders,
like topicalization, left-dislocation, and clefts, fail-either by
overgenerating these statistically rare forms or by undergenerating.
The primary goal of this book is to present a better model of when
speakers choose to produce certain non-canonical word orders by
incorporating the effects of discourse context and speaker goals on
syntactic choice. The theoretical model is then used as a basis for
building a probabilistic classifier that can select the most
human-like word order based on the surrounding discourse context. The
model of discourse context used is a methodological advance both from
a theoretical and an engineering perspective. It is built up from
individual linguistic features, ones more easily and reliably
annotated than the direct annotation of a discourse or rhetorical
structure for a text. This book makes extensive use of previously
unexamined naturally occurring corpus data of non-canonical word
order in English, both to illustrate the points of the theoretical
model and to train the statistical model.

Linguistic Field(s): Computational Linguistics; Syntax

Written In: English
(Language Code: ENG)
	
See this book announcement on our website:
http://linguistlist.org/get-book.html?BookID=11594


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