Language model adaptation for statistical machine translation based on information retrieval

Matthias Eck, Stephan Vogel, Alex Waibel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

41 Citations (Scopus)

Abstract

Language modeling is an important part for both speech recognition and machine translation systems. Adaptation has been successfully applied to language models for speech recognition. In this paper we present experiments concerning language model adaptation for statistical machine translation. We develop a method to adapt language models using information retrieval methods. The adapted language models drastically reduce perplexity over a general language model and we can show that it is possible to improve the translation quality of a statistical machine translation using those adapted language models instead of a general language model.

Original languageEnglish
Title of host publicationProceedings of the 4th International Conference on Language Resources and Evaluation, LREC 2004
PublisherEuropean Language Resources Association (ELRA)
Pages327-330
Number of pages4
ISBN (Electronic)2951740816, 9782951740815
Publication statusPublished - 1 Jan 2004
Externally publishedYes
Event4th International Conference on Language Resources and Evaluation, LREC 2004 - Lisbon, Portugal
Duration: 26 May 200428 May 2004

Other

Other4th International Conference on Language Resources and Evaluation, LREC 2004
CountryPortugal
CityLisbon
Period26/5/0428/5/04

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ASJC Scopus subject areas

  • Library and Information Sciences
  • Education
  • Language and Linguistics
  • Linguistics and Language

Cite this

Eck, M., Vogel, S., & Waibel, A. (2004). Language model adaptation for statistical machine translation based on information retrieval. In Proceedings of the 4th International Conference on Language Resources and Evaluation, LREC 2004 (pp. 327-330). European Language Resources Association (ELRA).