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2018 | OriginalPaper | Chapter

A Classifier-Based Preordering Approach for English-Vietnamese Statistical Machine Translation

Authors : Viet Hong Tran, Huyen Thuong Vu, Vinh Van Nguyen, Minh Le Nguyen

Published in: Computational Linguistics and Intelligent Text Processing

Publisher: Springer International Publishing

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Abstract

Reordering is of essential importance problem for phrase based statistical machine translation (SMT). In this paper, we propose an approach to automatically learn reordering rules as preprocessing step based on a dependency parser in phrase-based statistical machine translation for English to Vietnamese. We used dependency parsing and rules extracting from training the features-rich discriminative classifiers for reordering source-side sentences. We evaluated our approach on English-Vietnamese machine translation tasks, and showed that it outperform the baseline phrase-based SMT system.

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previous chapter Fast-Syntax-Matching-Based Japanese-Chinese Limited Machine Translation
next chapter Quality Estimation for English-Hungarian Machine Translation Systems with Optimized Semantic Features
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Metadata
Title
A Classifier-Based Preordering Approach for English-Vietnamese Statistical Machine Translation
Authors
Viet Hong Tran
Huyen Thuong Vu
Vinh Van Nguyen
Minh Le Nguyen
Copyright Year
2018
Book
Computational Linguistics and Intelligent Text Processing

Print ISBN: 978-3-319-75486-4

Electronic ISBN: 978-3-319-75487-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-75487-1_7

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