relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/98/
title: A Systematic Comparison between Various Statistical Alignment Models for Statistical English-Vietnamese Phrase-Based Translation
creator: Hoang, Cuong
creator: Le, Anh Cuong
creator: Pham, Bao Son
subject: Information Technology (IT)
description: In statistical phrase-based machine translation, the step of phrase learning heavily relies on word alignments. This paper provides a systematic comparison of applying various statistical alignment models for statistical English-Vietnamese phrase-based machine translation. We will also invest a heuristic method for elevating the translation quality of using higher word-alignment models by improving the quality of lexical modelling. In detail, we will experimentally show that taking up the lexical translation seems to be an appropriate approach to force "higher" word-based translation models be able to efficiently "boost" their merits. We hope this work will be a reliable comparison benchmark for other studies on using and improving the statistical alignment models for English-Vietnamese machine translation systems.
date: 2012-08-17
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Hoang, Cuong and Le, Anh Cuong and Pham, Bao Son  (2012) A Systematic Comparison between Various Statistical Alignment Models for Statistical English-Vietnamese Phrase-Based Translation.  In: 2012 Fourth International Conference on Knowledge and Systems Engineering (KSE), 17-19 August 2012, Danang, Vietnam.