Utilizing global syntactic tree features for phrase reordering

Yeon Soo Lee, Hyoung Gyu Lee, Hae Chang Rim, Young Sook Hwang

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In phrase-based statistical machine translation, long distance reordering problem is one of the most challenging issues when translating syntactically distant language pairs. In this paper, we propose a novel reordering model to solve this problem. In our model, reordering is affected by the overall structures of sentences such as listings, reduplications, and modifications as well as the relationships of adjacent phrases. To this end, we reflect global syntactic contexts including the parts that are not yet translated during the decoding process.

Original languageEnglish
Pages (from-to)1694-1698
Number of pages5
JournalIEICE Transactions on Information and Systems
VolumeE97-D
Issue number6
DOIs
Publication statusPublished - 2014 Jun

Keywords

  • Global syntactic tree features
  • Phrase reordering model
  • Phrase-based statistical machine translation

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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