OPPO’s Machine Translation System for the IWSLT 2020 Open Domain Translation Task

Qian Zhang, Xiaopu Li, Dawei Dang, Tingxun Shi, Di Ai, Zhengshan Xue, Jie Hao


Abstract
In this paper, we demonstrate our machine translation system applied for the Chinese-Japanese bidirectional translation task (aka. open domain translation task) for the IWSLT 2020. Our model is based on Transformer (Vaswani et al., 2017), with the help of many popular, widely proved effective data preprocessing and augmentation methods. Experiments show that these methods can improve the baseline model steadily and significantly.
Anthology ID:
2020.iwslt-1.13
Volume:
Proceedings of the 17th International Conference on Spoken Language Translation
Month:
July
Year:
2020
Address:
Online
Venues:
ACL | IWSLT | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
114–121
Language:
URL:
https://www.aclweb.org/anthology/2020.iwslt-1.13
DOI:
10.18653/v1/2020.iwslt-1.13
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.iwslt-1.13.pdf
Video:
 http://slideslive.com/38929611