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• W2401886177 abstract "Abstract Statistical machine translation (SMT) is gaining interest given that it can easily be adapted to any pair of languages. One of the main challenges in SMT is domain adaptation because the performance in translation drops when testing conditions deviate from training conditions. Many research works are arising to face this challenge. Research is focused on trying to exploit all kinds of material, if available. This paper provides an overview of research, which copes with the domain adaptation challenge in SMT." @default.
• W2401886177 created "2016-06-24" @default.
• W2401886177 creator A5074210163 @default.
• W2401886177 date "2015-10-30" @default.
• W2401886177 modified "2023-09-23" @default.
• W2401886177 title "Domain adaptation strategies in statistical machine translation: a brief overview" @default.
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• W2401886177 doi "https://doi.org/10.1017/s0269888915000119" @default.
• W2401886177 hasPublicationYear "2015" @default.
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