Abstract
This paper describes the Neural Machine Translation (NMT) system of TencentFmRD for Chinese↔English news translation tasks of WMT 2018. Our systems are neural machine translation systems trained with our original system TenTrans. TenTrans is an improved NMT system based on Transformer self-attention mechanism. In addition to the basic settings of Transformer training, TenTrans uses multi-model fusion techniques, multiple features reranking, different segmentation models and joint learning. Finally, we adopt some data selection strategies to fine-tune the trained system and achieve a stable performance improvement. Our Chinese→English system achieved the second best BLEU scores and fourth best cased BLEU scores among all WMT18 submitted systems.- Anthology ID:
- W18-6413
- Volume:
- Proceedings of the Third Conference on Machine Translation: Shared Task Papers
- Month:
- October
- Year:
- 2018
- Address:
- Belgium, Brussels
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 410–417
- Language:
- URL:
- https://aclanthology.org/W18-6413
- DOI:
- 10.18653/v1/W18-6413
- Cite (ACL):
- Bojie Hu, Ambyer Han, and Shen Huang. 2018. TencentFmRD Neural Machine Translation for WMT18. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers, pages 410–417, Belgium, Brussels. Association for Computational Linguistics.
- Cite (Informal):
- TencentFmRD Neural Machine Translation for WMT18 (Hu et al., WMT 2018)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/W18-6413.pdf