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Using Monolingual Data in Neural Machine Translation: a Systematic Study., and . WMT, page 144-155. Association for Computational Linguistics, (2018)Learning Morphological Normalization for Translation from and into Morphologically Rich Languages., and . Prague Bull. Math. Linguistics, (2017)LIMSI$@$WMT'17., , , , and . WMT, page 257-264. Association for Computational Linguistics, (2017)LIMSI@IWSLT'16: MT Track., , , , , and . IWSLT, International Workshop on Spoken Language Translation, (2016)Using Monolingual Data in Neural Machine Translation: a Systematic Study., and . CoRR, (2019)Two-Step MT: Predicting Target Morphology., , , and . IWSLT, International Workshop on Spoken Language Translation, (2016)Lingua Custodia at WMT'19: Attempts to Control Terminology.. WMT (2), page 147-154. Association for Computational Linguistics, (2019)Normalisation automatique du vocabulaire source pour traduire depuis une langue à morphologie riche (Learning Morphological Normalization for Translation from Morphologically Rich Languages)., and . TALN, page 16-31. ATALA, (2017)Morphology-aware alignments for translation to and from a synthetic language., and . IWSLT, (2015)Évaluation morphologique pour la traduction automatique : adaptation au français (Morphological Evaluation for Machine Translation : Adaptation to French)., and . CORIA-TALN-RJC (TALN), page 61-74. ATALA, (2018)