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Informationen zum Autor Cassandre Creswell earned her B.A. in linguistics at the University of Illinois at Urbana-Champaign. She has a M.S.E. in computer and information science and a Ph.D. in linguistics from the University of Pennsylvania. She currently resides in Toronto, Canada. Klappentext 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. 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. 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. Zusammenfassung Interest in statistical natural language generation is rapidly increasing. This work sheds important light from theoretical linguistics on the type of information crucial to statistical NLG algorithms. Inhaltsverzeichnis Acknowledgements Tables Figures Chapter 1: Introduction Chapter 2: Background: Previous Work and Relevant Theory Chapter 3: A Goal-Based Model of Syntactic Choice Chapter 4: An Empirical Study of Discourse Structure and Non-Canonical Word Order Chapter 5: Conclusions and Future Directions Bibliography Index
