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User Modeling in Language Learning with Macaronic Texts.

, , , and . ACL (1), The Association for Computer Linguistics, (2016)

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Robust Document Representations for Cross-Lingual Information Retrieval in Low-Resource Settings., , , , , , , , and . MTSummit (1), page 12-20. European Association for Machine Translation, (2019)Character-Aware Decoder for Translation into Morphologically Rich Languages., , , and . MTSummit (1), page 244-255. European Association for Machine Translation, (2019)CASMACAT: Cognitive Analysis and Statistical Methods for Advanced Computer Aided Translation., , , and . MTSummit (European projects), (2013)An Alignment-Based Approach to Semi-Supervised Bilingual Lexicon Induction with Small Parallel Corpora., , and . MTSummit (1), page 293-304. Association for Machine Translation in the Americas, (2021)Selective addition of corpus-extracted phrasal lexical rules to a rule-based machine translation system., , and . MTSummit, (2009)Levenshtein Training for Word-level Quality Estimation., , , and . EMNLP (1), page 6724-6733. Association for Computational Linguistics, (2021)Simulated multiple reference training improves low-resource machine translation., , , and . EMNLP (1), page 82-89. Association for Computational Linguistics, (2020)Vecalign: Improved Sentence Alignment in Linear Time and Space., and . EMNLP/IJCNLP (1), page 1342-1348. Association for Computational Linguistics, (2019)TICO-19: the Translation Initiative for COvid-19., , , , , , , , , and 8 other author(s). NLP4COVID@EMNLP, Association for Computational Linguistics, (2020)A Survey of Qualitative Error Analysis for Neural Machine Translation Systems., , , , and . AMTA (2), page 48-77. Association for Machine Translation in the Americas, (2020)