Context Models for OOV Word Translation in Low-Resource Languages

AMTA, pp. 54-67, 2018.

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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Out-of-vocabulary word translation is a major problem for the translation of low-resource languages that suffer from a lack of parallel training data. This paper evaluates the contributions of target-language context models towards the translation of OOV words, specifically in those cases where OOV translations are derived from external k...More

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