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Improved Statistical Machine Translation with Hybrid Phrasal Paraphrases Derived from Monolingual Text and a Shallow Lexical Resource
2010
Conference of the Association for Machine Translation in the Americas
Paraphrase generation is useful for various NLP tasks. But pivoting techniques for paraphrasing have limited applicability due to their reliance on parallel texts, although they benefit from linguistic knowledge implicit in the sentence alignment. Distributional paraphrasing has wider applicability, but doesn't benefit from any linguistic knowledge. We combine a distributional semantic distance measure (based on a non-annotated corpus) with a shallow linguistic resource to create a hybrid
dblp:conf/amta/Marton10
fatcat:67c5iv7uvjcb5ob4uc4ceazyty