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Feature rich translation model for example-based machine translation

  • Yin Chen*
  • , Muyun Yang
  • , Sheng Li
  • , Hongfei Jiang
  • *Corresponding author for this work
  • Harbin Institute of Technology

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

Abstract

Most EBMT systems select the best example scored by the similarity between the input sentence and existing examples. However, there is still much matching and mutual-translation information unexplored from examples. This paper introduces log-linear translation model into EBMT in order to adequately incorporate different kinds of features inherited in the translation examples. Instead of designing translation model by human intuition, this paper formally constructs a multi-dimensional feature space to include various features of different aspects. In the experiments, the proposed model shows significantly better result.

Original languageEnglish
Title of host publicationComputer Processing of Oriental Languages - Beyond the Orient
Subtitle of host publicationThe Research Challenges Ahead - 21st International Conference, ICCPOL 2006, Proceedings
Pages355-362
Number of pages8
DOIs
StatePublished - 2006
Event21st International Conference on Computer Processing of Oriental Languages: Beyond the Orient: The Research Challenges Ahead, ICCPOL 2006 - Singapore, Singapore
Duration: 17 Dec 200619 Dec 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4285 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Computer Processing of Oriental Languages: Beyond the Orient: The Research Challenges Ahead, ICCPOL 2006
Country/TerritorySingapore
CitySingapore
Period17/12/0619/12/06

Keywords

  • EBMT
  • Feature space
  • Log-linear translation model

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