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Compact Speech Translation Models via Discrete Speech Units Pretraining., , and . CoRR, (2024)Survey of Low-Resource Machine Translation., , , , and . Comput. Linguistics, 48 (3): 673-732 (2022)Dynamic Masking for Improved Stability in Spoken Language Translation., and . CoRR, (2020)Controlling Politeness in Neural Machine Translation via Side Constraints., , and . HLT-NAACL, page 35-40. The Association for Computational Linguistics, (2016)Findings of the IWSLT 2022 Evaluation Campaign., , , , , , , , , and 33 other author(s). IWSLT@ACL, page 98-157. Association for Computational Linguistics, (2022)Exploring Unsupervised Pretraining Objectives for Machine Translation., , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 2956-2971. Association for Computational Linguistics, (2021)Improving Neural Machine Translation Models with Monolingual Data., , and . ACL (1), The Association for Computer Linguistics, (2016)Adaptive Feature Selection for End-to-End Speech Translation., , , and . EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 2533-2544. Association for Computational Linguistics, (2020)SLTEV: Comprehensive Evaluation of Spoken Language Translation., , , and . EACL (System Demonstrations), page 71-79. Association for Computational Linguistics, (2021)Prosody in Cascade and Direct Speech-to-Text Translation: a case study on Korean Wh-Phrases., , , and . EACL (Findings), page 674-683. Association for Computational Linguistics, (2024)