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Improving Phrase-Based SMT Using Cross-Granularity Embedding Similarity.

, , , and . EAMT, page 129-140. European Association for Machine Translation, (2016)

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A hybrid architecture for robust MT using LFG-DOP. Journal of Experimental & Theoretical Artificial Intelligence, 11 (3): 441--471 (1999)wEBMT: Developing and Validating an Example-Based Machine Translation System using the World Wide Web., and . Computational Linguistics, 29 (3): 421-458 (2003)Enhancing Access to Online Education: Quality Machine Translation of MOOC Content., , , , , , , and . LREC, European Language Resources Association (ELRA), (2016)No Padding Please: Efficient Neural Handwriting Recognition., , and . ICDAR, page 355-362. IEEE, (2019)What types of word alignment improve statistical machine translation?, , , and . Mach. Transl., 26 (4): 289-323 (2012)HMM Word-to-Phrase Alignment with Dependency Constraints., and . SSST@COLING, page 101-109. Coling 2010 Organizing Committee, (2010)Towards a User-Friendly Webservice Architecture for Statistical Machine Translation in the PANACEA project., , , and . EAMT, European Association for Machine Translation, (2011)CCG Contextual labels in Hierarchical Phrase-Based SMT., , and . EAMT, European Association for Machine Translation, (2011)A human evaluation of English-Irish statistical and neural machine translation., , , , and . EAMT, page 431-440. European Association for Machine Translation, (2020)Extrinsic evaluation of web-crawlers in machine translation: a study on Croatian-English for the tourism domain., , , , , and . EAMT, page 221-224. European Association for Machine Translation, (2014)