Context adaptation in statistical machine translation using models with exponentially decaying cache

  • Authors:
  • Jörg Tiedemann

  • Affiliations:
  • Uppsala University, Uppsala/Sweden

  • Venue:
  • DANLP 2010 Proceedings of the 2010 Workshop on Domain Adaptation for Natural Language Processing
  • Year:
  • 2010

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Abstract

We report results from a domain adaptation task for statistical machine translation (SMT) using cache-based adaptive language and translation models. We apply an exponential decay factor and integrate the cache models in a standard phrase-based SMT decoder. Without the need for any domain-specific resources we obtain a 2.6% relative improvement on average in BLEU scores using our dynamic adaptation procedure.