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Hybrid Approaches to Machine Translation

This volume provides an overview of the field of Hybrid Machine Translation (MT) and presents some of the latest research conducted by linguists and practitioners from different multidisciplinary areas. Nowadays, most important developments in MT are achieved by combining data-driven and rule-based...

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Corporate Author: SpringerLink (Online service)
Other Authors: Costa-jussà, Marta R. (Editor, http://id.loc.gov/vocabulary/relators/edt), Rapp, Reinhard. (Editor, http://id.loc.gov/vocabulary/relators/edt), Lambert, Patrik. (Editor, http://id.loc.gov/vocabulary/relators/edt), Eberle, Kurt. (Editor, http://id.loc.gov/vocabulary/relators/edt), Banchs, Rafael E. (Editor, http://id.loc.gov/vocabulary/relators/edt), Babych, Bogdan. (Editor, http://id.loc.gov/vocabulary/relators/edt)
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edition:1st ed. 2016.
Series:Theory and Applications of Natural Language Processing,
Subjects:
Natural language processing (Computer science).
Computational linguistics.
Translation and interpretation.
Natural Language Processing (NLP).
Computational Linguistics.
Translation.
Online Access:https://doi.org/10.1007/978-3-319-21311-8
Table of Contents:
  • Preface
  • Foreword
  • Chapter 1. Hybrid Machine Translation Overview
  • Part 1: Adding Linguistics into SMT
  • Chapter 2. Controllent Ascent: Imbuing Statistical MT with Linguistic knowledge
  • Chapter 3. Hybrid Word Alignment
  • Chapter 4. Syntax in SMT
  • Part 2. Using Machine Learning in MT
  • Chapter 5. Machine Learning in RBMT
  • Chapter 6. Language-Independent Hybrid MT
  • Part 3. Hybrid NLP tools useful for MT
  • Chapter 7. Use of Dependency Parsers in MT
  • Chapter 8. Word Sense Disambiguation in MT. .

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