Abstract
This paper describes the Kingsoft AI Lab's submission to the WMT2019 news translation shared task. We participated in two language directions: English→Chinese and Chinese→English. For both language directions, we trained several variants of Transformer models using the provided parallel data enlarged with a large quantity of back-translated monolingual data. The best translation result was obtained with ensemble and reranking techniques. According to automatic metrics (BLEU) our Chinese→English system reached the second highest score, and our English→Chinese system reached the second highest score for this subtask.
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CITATION STYLE
Guo, X., Liu, C., Li, X., Wang, Y., Li, G., Wang, F., … Li, C. (2019). Kingsoft’s neural machine translation system for WMT19. In WMT 2019 - 4th Conference on Machine Translation, Proceedings of the Conference (Vol. 2, pp. 196–202). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w19-5317
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