SRPOL’s System for the IWSLT 2020 End-to-End Speech Translation Task

This paper describes the submission to IWSLT 2020 We took part in the offline End-to-End English to German TED lectures translation task. We based our solution on our last year's submission We used a slightly altered Transformer(Vaswani et al., 2017) architecture with ResNet-like(He et al., 2016) convolutional layer preparing the audio input to Transformer encoder. To improve the model's quality of translation we introduced two regularization techniques and trained on machine translated Librispeech(Panayotov et al., 2015) corpus in addition to iwsltcorpus, TEDLIUM2(Rousseau et al., 2014) and Must C(Di Gangi et al., 2019) corpora. Our best model scored almost 3 BLEU higher than last year's model. To segment 2020 test set we used exactly the same procedure as last year.