Modeling Relevance in Statistical Machine Translation: Scoring Alignment, Context, and Annotations of Translation Instances
Machine translation has advanced considerably in recent years, primarily due to the availability of larger datasets. However, one cannot rely on the availability of copious, high-quality bilingual training data. In this work, we improve upon the state-of-the-art in machine translation with an instan...
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| Format: | Others |
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Research Showcase @ CMU
2012
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| Online Access: | http://repository.cmu.edu/dissertations/134 http://repository.cmu.edu/cgi/viewcontent.cgi?article=1142&context=dissertations |