Bridging the Gap between Pre-Training and Fine-Tuning for End-to-End Speech Translation
Table 5: BLEU of Transformer-based models on tst2013 set. ‘-’: failed training.
['System', 'tst2013']
In this setting, we use character-level decoding strategy due to its better performance. Only in-domain MT data is used during pre-training. It can be seen that our TCEN framework works well on Transformer-based architecture and it outperforms the ‘pretrain+MTL’ baseline by 2.1 BLEU scores.