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This paper describes the submission of the NiuTrans end-to-end speechtranslation system for the IWSLT 2021 offline task, which translates from theEnglish audio to German text directly without intermediate transcription. Weuse the Transformer-based model architecture and enhance it by Conformer,relative position encoding, and stacked acoustic and textual encoding. Toaugment the training data, the English transcriptions are translated to Germantranslations. Finally, we employ ensemble decoding to integrate the predictionsfrom several models trained with the different datasets. Combining thesetechniques, we achieve 33.84 BLEU points on the MuST-C En-De test set, whichshows the enormous potential of the end-to-end model.

The NiuTrans End-to-End Speech Translation System for IWSLT 2021 Offline Task