WeChat Neural Machine Translation Systems for WMT20

• URL: http://arxiv.org/abs/2010.00247v2
• Date: Mon, 5 Oct 2020 16:01:01 GMT
• Title: WeChat Neural Machine Translation Systems for WMT20
• Authors: Fandong Meng, Jianhao Yan, Yijin Liu, Yuan Gao, Xianfeng Zeng, Qinsong Zeng, Peng Li, Ming Chen, Jie Zhou, Sifan Liu and Hao Zhou
• Abstract summary: Our system is based on the Transformer with effective variants and the DTMT architecture. In our experiments, we employ data selection, several synthetic data generation approaches, advanced finetuning approaches and self-bleu based model ensemble. Our constrained Chinese to English system achieves 36.9 case-sensitive BLEU score, which is the highest among all submissions.
• Score: 61.03013964996131
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We participate in the WMT 2020 shared news translation task on Chinese to English. Our system is based on the Transformer (Vaswani et al., 2017a) with effective variants and the DTMT (Meng and Zhang, 2019) architecture. In our experiments, we employ data selection, several synthetic data generation approaches (i.e., back-translation, knowledge distillation, and iterative in-domain knowledge transfer), advanced finetuning approaches and self-bleu based model ensemble. Our constrained Chinese to English system achieves 36.9 case-sensitive BLEU score, which is the highest among all submissions.

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