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Bootstrapping a Hybrid MT System to a New Language Pair

Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)

DOI:10.63317/2w8gknttkj4c

Abstract

The usual concern when opting for a rule-based or a hybrid machine translation (MT) system is how much effort is required to adapt the system to a different language pair or a new domain. In this paper, we describe a way of adapting an existing hybrid MT system to a new language pair, and show that such a system can outperform a standard phrase-based statistical machine translation system with an average of 10 persons/month of work. This is specifically important in the case of domain-specific MT for which there is not enough parallel data for training a statistical machine translation system.

Details

Paper ID
lrec2016-main-438
Pages
pp. 2762-2765
BibKey
rodrigues-etal-2016-bootstrapping
Editors
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asunción Moreno, Jan Odijk, Stelios Piperidis
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
978-2-9517408-9-1
Conference
Tenth International Conference on Language Resources and Evaluation
Location
Portorož, Slovenia
Date
23 - 28 May 2016

Authors

  • JR

    João António Rodrigues

  • NR

    Nuno Rendeiro

  • AQ

    Andreia Querido

  • Sanja Štajner

  • AB

    António Branco

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