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IMS' Systems for the IWSLT 2021 Low-Resource Speech Translation Task

أنظمة IMS لمهمة ترجمة الكلام منخفضة الموارد IWSLT 2021

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 Publication date 2021
and research's language is English
 Created by Shamra Editor




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This paper describes the submission to the IWSLT 2021 Low-Resource Speech Translation Shared Task by IMS team. We utilize state-of-the-art models combined with several data augmentation, multi-task and transfer learning approaches for the automatic speech recognition (ASR) and machine translation (MT) steps of our cascaded system. Moreover, we also explore the feasibility of a full end-to-end speech translation (ST) model in the case of very constrained amount of ground truth labeled data. Our best system achieves the best performance among all submitted systems for Congolese Swahili to English and French with BLEU scores 7.7 and 13.7 respectively, and the second best result for Coastal Swahili to English with BLEU score 14.9.



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