Meta Ensemble for Japanese-Chinese Neural Machine Translation: Kyoto-U+ECNU Participation to WAT 2020
Zhuoyuan Mao, Yibin Shen, Chenhui Chu, Sadao Kurohashi, Cheqing Jin
Abstract
This paper describes the Japanese-Chinese Neural Machine Translation (NMT) system submitted by the joint team of Kyoto University and East China Normal University (Kyoto-U+ECNU) to WAT 2020 (Nakazawa et al.,2020). We participate in APSEC Japanese-Chinese translation task. We revisit several techniques for NMT including various architectures, different data selection and augmentation methods, denoising pre-training, and also some specific tricks for Japanese-Chinese translation. We eventually perform a meta ensemble to combine all of the models into a single model. BLEU results of this meta ensembled model rank the first both on 2 directions of ASPEC Japanese-Chinese translation.- Anthology ID:
- 2020.wat-1.5
- Volume:
- Proceedings of the 7th Workshop on Asian Translation
- Month:
- December
- Year:
- 2020
- Address:
- Suzhou, China
- Venue:
- WAT
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 64–71
- Language:
- URL:
- https://aclanthology.org/2020.wat-1.5
- DOI:
- Cite (ACL):
- Zhuoyuan Mao, Yibin Shen, Chenhui Chu, Sadao Kurohashi, and Cheqing Jin. 2020. Meta Ensemble for Japanese-Chinese Neural Machine Translation: Kyoto-U+ECNU Participation to WAT 2020. In Proceedings of the 7th Workshop on Asian Translation, pages 64–71, Suzhou, China. Association for Computational Linguistics.
- Cite (Informal):
- Meta Ensemble for Japanese-Chinese Neural Machine Translation: Kyoto-U+ECNU Participation to WAT 2020 (Mao et al., WAT 2020)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2020.wat-1.5.pdf
- Data
- ASPEC, OpenSubtitles, WikiMatrix