Adaptation of the translation model for statistical machine translation based on information retrieval

Almut Silja Hildebrand, Matthias Eck, Stephan Vogel, Alex Waibel

Research output: Contribution to conferencePaper

Abstract

In this paper we present experiments concerning translation model adaptation for statistical machine translation. We develop a method to adapt translation models using information retrieval. The approach selects sentences similar to the test set to form an adapted training corpus. The method allows a better use of additionally available out-of-domain training data or finds in-domain data in a mixed corpus. The adapted translation models significantly improve the translation performance compared to competitive baseline systems.

Original languageEnglish
Pages133-142
Number of pages10
Publication statusPublished - 1 Dec 2005
Event10th Annual Conference on European Association for Machine Translation, EAMT 2005 - Budapest, Hungary
Duration: 30 May 200531 May 2005

Other

Other10th Annual Conference on European Association for Machine Translation, EAMT 2005
CountryHungary
CityBudapest
Period30/5/0531/5/05

    Fingerprint

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Software

Cite this

Hildebrand, A. S., Eck, M., Vogel, S., & Waibel, A. (2005). Adaptation of the translation model for statistical machine translation based on information retrieval. 133-142. Paper presented at 10th Annual Conference on European Association for Machine Translation, EAMT 2005, Budapest, Hungary.