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Generating Case Markers in Machine Translation

Kristina Toutanova and Hisami Suzuki


We study the use of rich syntax-based statistical models for generating grammatical case for the purpose of machine translation from a language which does not indicate case explicitly (English) to a language with a rich system of surface case markers (Japanese). We propose an extension of n-best re-ranking as a method of integrating such models into a statistical MT system and show that this method substantially outperforms standard n-best re-ranking. Our best performing model achieves a statistically significant improvement over the baseline MT system according to the BLEU metric. Human evaluation also confirms the results.


Publication typeInproceedings
Published inProceedings of NAACL
PublisherAssociation for Computational Linguistics
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