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 the University of Maryland.
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Bonnie Jean Dorr is Assistant Professor in the Computer Science Department at the University of Maryland.
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Front Cover | Front Flap | Table of Contents | First Pages | Index | Back Flap | Back Cover | Surprise Me!
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The task of designing a machine translation system is difficult because, in order to achieve a desirable degree of accuracy, such a system must capture language-independent information while still systematically processing many types of language-specific phenomena in each of the individual languages. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
demotional divergence, promotional divergence, marie gern, word gern, brach ins, juan suele, conflational divergence, hause gewöhnlich, lexical selection procedure, other divergence types, categorial divergence, act acc ach, constituent order parameter, ich esse gern, juan entró, machine translation divergences, verb soler, thematic divergence, interlingual form, interlingual system, dar puñaladas, interlingual approach, aspectual realization, interlingual representation, stab event Key Phrases - Capitalized Phrases (CAPs): (learn more)
Generate Phrase, Case Filter, Past Perf, Pres Perf, Boss des Diebestrios, Mary John, Subjacency Constraint, Bill Frühstück, Der Geldschrank, Binding Conditions, Exiting Compose, Full Coverage Constraint, Yesterday John, Entering Compose New!
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Front Cover | Front Flap | Table of Contents | First Pages | Index | Back Flap | Back Cover | Surprise Me!
The task of designing a machine translation system is difficult because, in order to achieve a desirable degree of accuracy, such a system must capture language-independent information while still systematically processing many types of language-specific phenomena in each of the individual languages. Read the first page Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
demotional divergence, promotional divergence, marie gern, word gern, brach ins, juan suele, conflational divergence, hause gewöhnlich, lexical selection procedure, other divergence types, categorial divergence, act acc ach, constituent order parameter, ich esse gern, juan entró, machine translation divergences, verb soler, thematic divergence, interlingual form, interlingual system, dar puñaladas, interlingual approach, aspectual realization, interlingual representation, stab event Key Phrases - Capitalized Phrases (CAPs): (learn more)
Generate Phrase, Case Filter, Past Perf, Pres Perf, Boss des Diebestrios, Mary John, Subjacency Constraint, Bill Frühstück, Der Geldschrank, Binding Conditions, Exiting Compose, Full Coverage Constraint, Yesterday John, Entering Compose New!
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Front Cover | Front Flap | Table of Contents | First Pages | Index | Back Flap | Back Cover | Surprise Me!
Citations (learn more)
This book cites 89
books:
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12
books
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- Artificial Intelligence (3rd Edition) by Winston on 6 pages
- Parameter Setting (Studies in Theoretical Psycholinguistics) by Thomas Roeper on 5 pages
- Computational Linguistics: An Introduction (Studies in Natural Language Processing) by Ralph Grishman on 5 pages
- Lexical Semantics (Cambridge Textbooks in Linguistics) by D. A. Cruse on 4 pages
- Machine Translation: Theoretical and Methodological Issues (Studies in Natural Language Processing) by Sergei Nirenburg on 4 pages
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- Envisioning Machine Translation in the Information Future : 4th Conference of the Association for Machine Translation in the Americas, AMTA 2000 Cuernavaca, Mexico by John S. White on page 53, and page 155
- Predicative Forms in Natural Language and in Lexical Knowledge Bases (Text, Speech and Language Technology) by P. Saint-Dizier on page 201, and page 255
- Solving the Frame Problem: A Mathematical Investigation of the Common Sense Law of Inertia (Artificial Intelligence) by Murray Shanahan in Back Matter
- Computational Lexical Semantics (Studies in Natural Language Processing) by Patrick Saint-Dizier on page 392
- Word Sense Disambiguation: Algorithms and Applications (Text, Speech and Language Technology) by Eneko Agirre in Back Matter
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