Estimating translation probabilities considering semantic recoverability of phrase retranslation

Hyoung Gyu Lee, Min Jeong Kim, Ying Xiu Quan, Hae-Chang Rim, So Young Park

Research output: Contribution to journalArticle

Abstract

The general method for estimating phrase translation probabilities consists of sequential processes: word alignment, phrase pair extraction, and phrase translation probability calculation. However, during this sequential process, errors may propagate from the word alignment step through the translation probability calculation step. In this paper, we propose a new method for estimating phrase translation probabilities that reduce the effects of error propagation. By considering the semantic recoverability of phrase retranslation, our method identifies incorrect phrase pairs that have propagated from alignment errors. Furthermore, we define retranslation similarity which represents the semantic recoverability of phrase retranslation, and use this when computing translation probabilities. Experimental results show that the proposed phrase translation estimation method effectively prevents a PBSMT system from selecting incorrect phrase pairs, and consistently improves the translation quality in various language pairs.

Original languageEnglish
Pages (from-to)897-901
Number of pages5
JournalIEICE Transactions on Information and Systems
VolumeE95-D
Issue number3
DOIs
Publication statusPublished - 2012 Mar 1

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Keywords

  • Phrase retranslation
  • Phrase translation probability
  • Semantic recoverability
  • Statistical machine translation

ASJC Scopus subject areas

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

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