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An integrated reordering model for statistical machine translation

  • National University of Defense Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we propose a phrase reordering model for statistical machine translation. The model is derived from the bracketing ITG, and integrates the local and global reordering model. We present a method to extract phrase pairs from a word-aligned bilingual corpus in which the alignments satisfy the ITG constraint, and we also extract the reordering information for the phrase pairs, which are used to build the re-ordering model. Through experiments, we show that this model obtains significant improvements over the baseline on a Chinese-English translation.

Original languageEnglish
Title of host publicationMICAI 2007
Subtitle of host publicationAdvances in Artificial Intelligence - 6th Mexican International Conference on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Pages955-965
Number of pages11
ISBN (Print)9783540766308
DOIs
StatePublished - 2007
Event6th Mexican International Conference on Artificial Intelligence, MICAI 2007 - Aguascalientes, Mexico
Duration: 4 Nov 200710 Nov 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4827 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th Mexican International Conference on Artificial Intelligence, MICAI 2007
Country/TerritoryMexico
CityAguascalientes
Period4/11/0710/11/07

Keywords

  • ITG
  • Reordering model
  • Statistical machine translation

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