Abstract
We describe here the experiments we performed for the news translation shared task of WMT 2019. We focused on the new German-to-French language direction, and mostly used current standard approaches to develop a Neural Machine Translation system. We make use of the Tensor2Tensor implementation of the Transformer model. After carefully cleaning the data and noting the importance of the good use of recent monolingual data for the task, we obtain our final result by combining the output of a diverse set of trained models through the use of their”checkpoint agreement”.
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CITATION STYLE
Cromieres, F., & Kurohashi, S. (2019). Kyoto University participation to the WMT 2019 news shared task. In WMT 2019 - 4th Conference on Machine Translation, Proceedings of the Conference (Vol. 2, pp. 163–167). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w19-5312
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