Research on Data Augmentation for Chinese-Japanese Neural Machine Translation Based on Conversions between Traditional Chinese and Simplified Chinese

Author:

张 津一

Publisher

Hans Publishers

Subject

Earth-Surface Processes

Reference39 articles.

1. Bahdanau, D., Cho, K. and Bengio, Y. (2014) Neural Machine Translation by Jointly Learning to Align and Translate. The International Conference on Learning Representations (ICLR), Banff, 14-16 April 2014, 1-15.

2. Effective Approaches to Attention-based Neural Machine Translation

3. Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L. and Polosukhin, I. (2017) Attention Is All You Need. 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, 4-9 December 2017, 5998-6008.

4. Nakazawa, T., Yaguchi, M., Uchimoto, K., Utiyama, M., Sumita, E., Kurohashi, S. and Isahara, H. (2016) ASPEC: Asian Scientific Paper Excerpt Corpus. Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC 2016), Portorož, 23-28 May 2016, 2204-2208.

5. 徐一平, 曹大峰. 汉日对译语料库的研制与应用研究: 论文集[M]. 北京: 外语教学与研究出版社, 2002.

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