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The NiuTrans End-to-End Speech Translation System for IWSLT 2021 Offline Task
This paper describes the submission of the NiuTrans end-to-end speech
translation system for the IWSLT 2021 offline task, which translates from the
English audio to German text directly without intermediate transcription. We
use the Transformer-based model architecture and enhance it by Conformer,
relative position encoding, and stacked acoustic and textual encoding. To
augment the training data, the English transcriptions are translated to German
translations. Finally, we employ ensemble decoding to integrate the predictions
from several models trained with the different datasets. Combining these
techniques, we achieve 33.84 BLEU points on the MuST-C En-De test set, which
shows the enormous potential of the end-to-end model.Comment: IWSLT 202