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Context-extended phrase reordering model for pivot-based statistical machine translation

  • School of Computer Science and Technology, Harbin Institute of Technology

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

Abstract

For translation between language pairs which is lack of bilingual data, pivot-based SMT uses a pivot language as a bridge to generate source-target translation, inducing from source-pivot and pivot-target translation. However, due to the missing of the context information, the reordering model was hard to obtain with the conventional methods. In this paper, we present a context-extended phrase reordering model for pivot-based statistical machine translation by extending the context information in source, pivot and target language. Experimental results show that our method leads to significant improvements over the baseline system on European Parliament data.

Original languageEnglish
Title of host publicationProceedings of 2015 International Conference on Asian Language Processing, IALP 2015
EditorsBin Ma, Min Zhang, Yanfeng Lu, Minghui Dong, Wenliang Chen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages29-32
Number of pages4
ISBN (Electronic)9781467395953
DOIs
StatePublished - 12 Apr 2016
Externally publishedYes
EventInternational Conference on Asian Language Processing, IALP 2015 - Suzhou, China
Duration: 24 Oct 201525 Oct 2015

Publication series

NameProceedings of 2015 International Conference on Asian Language Processing, IALP 2015

Conference

ConferenceInternational Conference on Asian Language Processing, IALP 2015
Country/TerritoryChina
CitySuzhou
Period24/10/1525/10/15

Keywords

  • context
  • machine translation
  • pivot
  • reordering

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