[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]
|
Luong, M.T., Pham, H. and Manning, C.D. (2015) Effective Approaches to Attention-Based Neural Machine Translation. Proceedings 2015 Conference on Empirical Methods in Natural Language Processing, Lisbon, 17-21 September 2015, 1412-1421. https://doi.org/10.18653/v1/D15-1166
|
[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.
|
[6]
|
Zhang, J., Tian, Y., Han, M., Mao, J. and Matsumoto, T. (2022) WCC-JC: A Web-Crawled Corpus for Japanese-Chinese Neural Machine Translation. Applied Sciences, 12, Article No. 6002.
https://doi.org/10.3390/app12126002
|
[7]
|
Zhang, J., Tian, Y., Han, M., Mao, J., Wen, F., Guo, C., Gao, Z. and Matsumoto, T. (2023) WCC-JC 2.0: A Web-Crawled and Manually Aligned Parallel Corpus for Japanese-Chinese Neural Machine Translation. Electronics, 12, Article No. 1140. https://doi.org/10.3390/electronics12051140
|
[8]
|
Sennrich, R., Haddow, B. and Birch, A. (2016) Improving Neural Machine Translation Models with Monolingual Data. Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, Volume 1, 86-96.
https://doi.org/10.18653/v1/P16-1009
|
[9]
|
中澤敏明, C. Chu, 黒橋禎夫. 日中共通漢字の整理とこれを利用した日中機械翻訳の高度化[EB/OL]. Japio Year Book: 258-261. https://cir.nii.ac.jp/crid/1523669555917032960, 2023-05-24.
|
[10]
|
Mao, Z., Cromieres, F., Dabre, R., Song, H. and Kurohashi, S. (2020) JASS: Japanese-Specific Sequence to Sequence Pre-Training for Neural Machine Translation. LREC 2020 12th International Conference on Language Resources and Evaluation, Marseille, 11-16 May 2020, 3683-3691.
|
[11]
|
Xu, C., Hu, B., Jiang, Y., Feng, K., Wang, Z., Huang, S. and Zhu, J. (2020) Dynamic Curriculum Learning for Low- Resource Neural Machine Translation. Proceedings of the 28th International Conference on Computational Linguistics, Barcelona, 8-13 December 2020, 3977-3989. https://doi.org/10.18653/v1/2020.coling-main.352
|
[12]
|
Dou, Z.Y., Anastasopoulos, A. and Neubig, G. (2020) Dynamic Data Selection and Weighting for Iterative Back- Translation. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 16-20 November 2020, 5894-5904. https://doi.org/10.18653/v1/2020.emnlp-main.475
|
[13]
|
Araabi, A. and Monz, C. (2020) Optimizing Transformer for Low-Resource Neural Machine Translation. Proceedings of the 28th International Conference on Computational Linguistics, Barcelona, 8-13 December 2020, 3429-3435.
https://doi.org/10.18653/v1/2020.coling-main.304
|
[14]
|
Ngo, T., Nguyen, P., Ha, T., Dinh, K. and Nguyen, L. (2020) Improving Multilingual Neural Machine Translation for Low-Resource Languages: French, English—Vietnamese. The 3rd Workshop on Technologies for MT of Low Resource Languages, 4-7 December 2020, 55-61.
|
[15]
|
Amittai, A., He, X. and Gao, J. (2011) Domain Adaptation via Pseudo In-Domain Data Selection. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Association for Computational Linguistics, Cedarville, 355-362.
|
[16]
|
Marlies, W., Bisazza, A. and Monz, C. (2017) Dynamic Data Selection for Neural Machine Translation. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP), Copenhagen, 7-11 September 2017, 1400-1410.
|
[17]
|
Zhang, P., Xu, X. and Xiong, D. (2018) Active Learning for Neural Machine Translation. 2018 International Conference on Asian Language Processing (IALP), Indonesia, 15-17 November 2018, 153-158.
https://doi.org/10.1109/IALP.2018.8629116
|
[18]
|
Wang, R., Utiyama, M., Finch, A.M., Liu, L., Chen, K. and Sumita, E. (2018) Sentence Selection and Weighting for Neural Machine Translation Domain Adaptation. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 26, 1727-1741. https://doi.org/10.1109/TASLP.2018.2837223
|
[19]
|
Song, K., Zhang, Y., Yu, H., Luo, W., Wang, K. and Zhang, M. (2019) Code-Switching for Enhancing NMT with Pre-Specified Translation. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1, 449-459.
|
[20]
|
李毅鹏. 中日双语平行语料库之日语科技语标注技术[J]. 企业导报, 2015(2): 175-176.
|
[21]
|
Caswell, I., Chelba, C. and Grangier, D. (2019) Tagged Back-Translation. Proceedings of the Fourth Conference on Machine Translation (WMT), Volume 1, 53-63. https://doi.org/10.18653/v1/W19-5206
|
[22]
|
Khatri, J. and Bhattacharyya, P. (2020) Filtering Back-Translated Data in Unsupervised Neural Machine Translation. Proceedings of the 28th International Conference on Computational Linguistics, Barcelona, 8-13 December 2020, 4334-4339. https://doi.org/10.18653/v1/2020.coling-main.383
|
[23]
|
Wei, H., Zhang, Z., Chen, B. and Luo, W. (2020) Iterative Domain-Repaired Back-Translation. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 16-20 November 2020, 5884-5893.
https://doi.org/10.18653/v1/2020.emnlp-main.474
|
[24]
|
Abdulmumin, I., Galadanci, B.S. and Isa, A. (2021). Enhanced Back-Translation for Low Resource Neural Machine Translation Using Self-training. In: Misra, S. and Muhammad-Bello, B., eds., ICTA 2020: Communications in Computer and Information Science, vol 1350, Springer, Cham. https://doi.org/10.1007/978-3-030-69143-1_28
|
[25]
|
Pham, H., Wang, X., Yang, Y. and Neubig, G. (2021) Meta Back-Translation.
https://doi.org/10.48550/arXiv.2102.07847
|
[26]
|
尤丛丛, 高盛祥, 余正涛, 毛存礼, 潘润海. 基于同义词数据增强的汉越神经机器翻译方法[J]. 计算机工程与科学, 2021, 43(8): 1497-1502.
|
[27]
|
贾承勋, 赖华, 余正涛, 文永华, 于志强. 基于短语替换的汉越伪平行句对生成[J]. 中文信息学报, 2021, 35(8): 47-55.
|
[28]
|
赵志耘, 石崇德, 何彦青, 高影繁, 姚长青. 面向科技文献的中日机器翻译合作研究[J]. 情报工程, 2017, 3(3): 4-9.
|
[29]
|
Zhuang, Y., Zhang, Y. and Wang, L. (2020) LIT Team’s System Description for Japanese-Chinese Machine Translation Task in IWSLT 2020. Proceedings of the 17th International Conference on Spoken Language Translation, 9-10 July 2020, 109-113. https://doi.org/10.18653/v1/2020.iwslt-1.12
|
[30]
|
Hagiwara, M. (2020) Octanove Labs’ Japanese-Chinese Open Domain Translation System. Proceedings of the 17th International Conference on Spoken Language Translation, 9-10 July 2020, 166-171.
https://doi.org/10.18653/v1/2020.iwslt-1.20
|
[31]
|
Zhang, J. and Matsumoto, T. (2019) Corpus Augmentation for Neural Machine Translation with Chinese-Japanese Parallel Corpora. Applied Sciences, 9, Article No. 2036. https://doi.org/10.3390/app9102036
|
[32]
|
Zhang, J. and Matsumoto, T. (2017) Improving Character Level Japanese-Chinese Neural Machine Translation with Radicals as an Additional Input Feature. Proceedings of the 2017 International Conference on Asian Language Processing (IALP), Singapore, 5-7 December 2017, 172-175. https://doi.org/10.1109/IALP.2017.8300572
|
[33]
|
Zhang, J. and Matsumoto, T. (2019) Character Decomposition for Japanese-Chinese Character-Level Neural Machine Translation. Proceedings of the 2019 International Conference on Asian Language Processing (IALP), Shanghai, 15-17 November 2019, 35-40. https://doi.org/10.1109/IALP48816.2019.9037677
|
[34]
|
Meng, Y., Li, X., Sun, X., Han, Q., Yuan, A. and Li, J. (2019) Is Word Segmentation Necessary for Deep Learning of Chinese Representations? Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, 28 July-2 August 2019, 3242-3252.
|
[35]
|
Papineni, K., Roukos, S., Ward, T. and Zhu, W. (2002) Bleu: A Method for Automatic Evaluation of Machine Translation. Annual Meeting of the Association for Computational Linguistics, Philadephia, 6-12 July 2002, 311-318.
https://doi.org/10.3115/1073083.1073135
|
[36]
|
“结巴”中文分词[EB/OL]. http://github.com/fxsjy/jieba, 2020-01-20.
|
[37]
|
MeCab: Yet Another Part-of-Speech and Morphological Analyzer. http://taku910.github.io/mecab
|
[38]
|
Chu, C., Nakazawa, T. and Kurohashi, S. (2012) Chinese Characters Mapping Table of Japanese, Traditional Chinese and Simplified Chinese. Proceedings 8th Conference on International Language Resources and Evaluation (LREC’12), Istanbul, 21-27 May 2012, 2149-2152.
|
[39]
|
Klein, G., Kim, Y., Deng, Y., Senellart, J. and Rush, A. (2017) OpenNMT: Open-Source Toolkit for Neural Machine Translation. Proceedings of ACL 2017, System Demonstrations, Vancouver, 30 July-4 August 2017, 67-72.
https://doi.org/10.18653/v1/P17-4012
|