Abstract
This paper describes our submitted systems for CCMT-2020 shared translation tasks. We build our neural machine translation system based on Google’s Transformer architecture. We also employ some effective techniques such as back translation, data selection, ensemble translation, fine-tuning and reranking to improve our system.
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Wang, D., Liu, Z., Jiang, Q., Sun, Z., Huang, S., Chen, J. (2020). NJUNLP’s Machine Translation System for CCMT-2020 Uighur \(\rightarrow \) Chinese Translation Task. In: Li, J., Way, A. (eds) Machine Translation. CCMT 2020. Communications in Computer and Information Science, vol 1328. Springer, Singapore. https://doi.org/10.1007/978-981-33-6162-1_7
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DOI: https://doi.org/10.1007/978-981-33-6162-1_7
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