Linguistically Motivated Statistical Machine Translation: Models and Algorithms

✍ Scribed by Deyi Xiong, Min Zhang (auth.)

Publisher: Springer-Verlag Singapur
Year: 2015
Tongue: English
Leaves: 159
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book provides a wide variety of algorithms and models to integrate linguistic knowledge into Statistical Machine Translation (SMT). It helps advance conventional SMT to linguistically motivated SMT by enhancing the following three essential components: translation, reordering and bracketing models. It also serves the purpose of promoting the in-depth study of the impacts of linguistic knowledge on machine translation. Finally it provides a systematic introduction of Bracketing Transduction Grammar (BTG) based SMT, one of the state-of-the-art SMT formalisms, as well as a case study of linguistically motivated SMT on a BTG-based platform.

✦ Table of Contents

Front Matter....Pages i-xii
Introduction....Pages 1-13
BTG-Based SMT....Pages 15-42
Syntactically Annotated Reordering....Pages 43-70
Semantically Informed Reordering....Pages 71-79
Lexicalized Bracketing....Pages 81-92
Linguistically Motivated Bracketing....Pages 93-106
Translation Rule Selection with Document-Level Semantic Information....Pages 107-124
Translation Error Detection with Linguistic Features....Pages 125-135
Closing Remarks....Pages 137-140
Back Matter....Pages 141-152

✦ Subjects

Computational Linguistics

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