Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks
Title
Hybrid approaches to machine translation [electronic resource] / Marta R. Costa-jussà, Reinhard Rapp, Patrik Lambert, Kurt Eberle, Rafael E. Banchs, Bogdan Babych, editors.
ISBN
9783319213118 (electronic book)
3319213113 (electronic book)
9783319213101
Published
Switzerland : Springer, 2016.
Language
English
Description
1 online resource (ix, 205 pages) : illustrations.
Call Number
QA76.9.N38
Dewey Decimal Classification
006.3/5
004
Summary
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 techniques. These combinations typically involve hybridization of different traditional paradigms, such as the introduction of linguistic knowledge into statistical approaches to MT, the incorporation of data-driven components into rule-based approaches, or statistical and rule-based pre- and post-processing for both types of MT architectures. The book is of interest primarily to MT specialists, but also - in the wider fields of Computational Linguistics, Machine Learning and Data Mining - to translators and managers of translation companies and departments who are interested in recent developments concerning automated translation tools.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed July 21, 2016).
Series
Theory and applications of natural language processing.
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. .
