LIT Team’s System Description for Japanese-Chinese Machine Translation Task in IWSLT 2020

Yimeng Zhuang, Yuan Zhang, Lijie Wang


Abstract
This paper describes the LIT Team’s submission to the IWSLT2020 open domain translation task, focusing primarily on Japanese-to-Chinese translation direction. Our system is based on the organizers’ baseline system, but we do more works on improving the Transform baseline system by elaborate data pre-processing. We manage to obtain significant improvements, and this paper aims to share some data processing experiences in this translation task. Large-scale back-translation on monolingual corpus is also investigated. In addition, we also try shared and exclusive word embeddings, compare different granularity of tokens like sub-word level. Our Japanese-to-Chinese translation system achieves a performance of BLEU=34.0 and ranks 2nd among all participating systems.
Anthology ID:
2020.iwslt-1.12
Volume:
Proceedings of the 17th International Conference on Spoken Language Translation
Month:
July
Year:
2020
Address:
Online
Editors:
Marcello Federico, Alex Waibel, Kevin Knight, Satoshi Nakamura, Hermann Ney, Jan Niehues, Sebastian Stüker, Dekai Wu, Joseph Mariani, Francois Yvon
Venue:
IWSLT
SIG:
SIGSLT
Publisher:
Association for Computational Linguistics
Note:
Pages:
109–113
Language:
URL:
https://aclanthology.org/2020.iwslt-1.12
DOI:
10.18653/v1/2020.iwslt-1.12
Bibkey:
Cite (ACL):
Yimeng Zhuang, Yuan Zhang, and Lijie Wang. 2020. LIT Team’s System Description for Japanese-Chinese Machine Translation Task in IWSLT 2020. In Proceedings of the 17th International Conference on Spoken Language Translation, pages 109–113, Online. Association for Computational Linguistics.
Cite (Informal):
LIT Team’s System Description for Japanese-Chinese Machine Translation Task in IWSLT 2020 (Zhuang et al., IWSLT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.iwslt-1.12.pdf