Using a Large Monolingual Corpus to Improve Translation Accuracy

Authors:
Radu Soricut;Kevin Knight;Daniel Marcu
Affiliations:
-;-;-
Venue:
AMTA '02 Proceedings of the 5th Conference of the Association for Machine Translation in the Americas on Machine Translation: From Research to Real Users
Year:
2002

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Abstract

The existence of a phrase in a large monolingual corpus is very useful information, and so is its frequency. We introduce an alternative approach to automatic translation of phrases/sentences that operationalizes this observation. We use a statistical machine translation system to produce alternative translations and a large monolingual corpus to (re)rank these translations. Our results show that this combination yields better translations, especially when translating out-of-domain phrases/sentences. Our approach can be also used to automatically construct parallel corpora from monolingual resources.