POSTECH submission on duolingo shared task

Abstract

This paper describes POSTECH’s submission to the 2020 Duolingo Shared Task on Simultaneous Translation And Paraphrase for Langauge Education (STAPLE) for the English-Korean language pair. In this paper, we propose a transfer learning based simultaneous translation model by extending BART. We pre-trained BART with Korean Wikipedia and a Korean news dataset, and fine-tuned it with an additional web-crawled parallel corpus and the 2020 Duolingo official training dataset. In our experiments on the 2020 Duolingo test dataset, our submission achieves 0.312 in weighted macro F1 score, and ranks second among the submitted En-Ko systems.