Supervised neural machine translation based on data augmentation and improved training \& inference process
2019-11-01WS 2019Unverified0· sign in to hype
Yixuan Tong, Liang Liang, Boyan Liu, Shanshan Jiang, Bin Dong
Unverified — Be the first to reproduce this paper.
ReproduceAbstract
This is the second time for SRCB to participate in WAT. This paper describes the neural machine translation systems for the shared translation tasks of WAT 2019. We participated in ASPEC tasks and submitted results on English-Japanese, Japanese-English, Chinese-Japanese, and Japanese-Chinese four language pairs. We employed the Transformer model as the baseline and experimented relative position representation, data augmentation, deep layer model, ensemble. Experiments show that all these methods can yield substantial improvements.