Machine Translation: A View from the Lexicon

Overview

This book describes a novel, cross-linguistic approach to machine translation that solves certain classes of syntactic and lexical divergences by means of a lexical conceptual structure that can be composed and decomposed in language-specific ways. This approach allows the translator to operate uniformly across many languages, while still accounting for knowledge that is specific to each language.The translation model can be used to map a source-language sentence to a target-language sentence in a principled ...

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Overview

This book describes a novel, cross-linguistic approach to machine translation that solves certain classes of syntactic and lexical divergences by means of a lexical conceptual structure that can be composed and decomposed in language-specific ways. This approach allows the translator to operate uniformly across many languages, while still accounting for knowledge that is specific to each language.The translation model can be used to map a source-language sentence to a target-language sentence in a principled fashion. It is built on the basis of a parametric approach,making it easy to change from one language to another (by setting syntactic switches for each language and providing lexical descriptions for each language) without having to write a whole new processor for each language.Dorr's approach advances the field of machine translation in a number of important ways: it provides a uniform processor in which the same syntactic and lexical-semantic processing modules are used for each language; it is interlingual, able to derive an underlying language-independent form of the source language that allows any of the three target languages -Spanish, English, or German - to be produced from this form; and it describes a systematic mapping between the lexical-semantic level and the syntactic level that allows the appropriate target-language words to be selected and realized, despite the potential for syntactic and lexical divergences.Bonnie Jean Dorr is Assistant Professor in the Computer Science Department at theUniversity of Maryland.

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Editorial Reviews

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Describes a novel, cross-linguistic approach to machine translation that solves certain classes of syntactic and lexical conceptual structures that can be composed and decomposed in language-specific ways. This approach allows the translator to operate uniformly across many languages, while still accounting for knowledge that is specific to each language. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780262519847
  • Publisher: MIT Press
  • Publication date: 6/29/1993
  • Series: Artificial Intelligence Series
  • Pages: 456
  • Product dimensions: 8.90 (w) x 5.90 (h) x 1.10 (d)

Meet the Author

Bonnie Jean Dorr is Assistant Professor in the Computer Science Department at the University of Maryland.

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Table of Contents

Series Foreword
Preface
Acknowledgments
1 Introduction 1
I Syntactic Component
2 Syntactic Processing 43
3 Morphological Processing 79
II Lexical-Semantic Component
4 The Interlingual Representation 95
5 Parameterization of the Interlingua 163
6 Generation from the Interlingua 193
7 Formalization of Machine Translation Divergences 233
III Application of the Model
8 Translation Examples 285
9 Current and Future Research: Tense, Aspect, and Lexical Acquisition 319
10 Conclusions 351
A. Summary of Divergence Examples with Respect to Syntactic Parameters and Principles 355
B. Morphological Rules 357
C. Linguistic Coverage of Extended Set of Primitives 363
D. Screen Dumps of Divergence Examples 369
E. Selection Charts for When, While, Before, and After 391
Bibliography 395
Index 423
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