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Addressing data sparsity for neural machine translation between morphologically rich languages., , , and . Mach. Transl., 34 (1): 1-20 (2020)The LIUM ASR and SLT systems for IWSLT 2015., , , , and . IWSLT (Evaluation Campaign), (2015)Lak_NLP at IberLEF-2022 DETESTS task: Automatic Classification of Stereotypes in Text., and . IberLEF@SEPLN, volume 3202 of CEUR Workshop Proceedings, CEUR-WS.org, (2022)Demonstration of a Neural Machine Translation System with Online Learning for Translators., , , , , , , and . ACL (3), page 70-74. Association for Computational Linguistics, (2019)A User Study of the Incremental Learning in NMT., , , , , , , and . EAMT, page 319-328. European Association for Machine Translation, (2020)SEECAT: ASR & Eye-tracking enabled computer-assisted translation., , , , , , , and . EAMT, page 81-88. European Association for Machine Translation, (2014)Deep Dive Machine Translation., , , , , , , , , and 9 other author(s). European Language Equality, Springer, (2023)How Much Does Tokenization Affect Neural Machine Translation?, , , , and . CoRR, (2018)A Review of Text Classification Models from Bayesian to Transformers., , and . SwissText, volume 3361 of CEUR Workshop Proceedings, page 12-17. CEUR-WS.org, (2022)The Multilingual Anonymisation Toolkit for Public Administrations (MAPA) Project., , , , , , , , , and 9 other author(s). EAMT, page 471-472. European Association for Machine Translation, (2020)