Machine Translation Quality Evaluation Model Based on Data Mining Algorithm

Author:

Liu Lei,Lu Nan

Publisher

Springer Nature Singapore

Reference12 articles.

1. Antony, P.J.: Machine translation approaches and survey for indian languages. Chin. J. Comput. Linguist. 18(1), 47–78 (2017)

2. Choi, H., Cho, K., Bengio, Y.: Context-dependent word representation for neural machine translation. Comput. Speech  Lang. 45, 149–160 (2017)

3. Moorkens, J,, Castilho, S., Gaspari, F., et al.: Machine Translation: Technologies and Applications Translation Quality Assessment Volume 1 (From Principles to Practice): Crowdsourcing and Translation Quality: Novel Approaches in the Language Industry and Translation Studies (2018). https://doi.org/10.1007/978-3-319-91241-7(Chapter4):69-93

4. Chatzikoumi, E.: How to evaluate machine translation: A review of automated and human metrics. Nat. Lang. Eng. 26(2), 1–25 (2019)

5. Cheesman, T., Flanagan, K., et al.: Multi-Retranslation corpora: Visibility, variation, value, and virtue. Digital Scholarship  Humanities 32(4), 739–760 (2017)

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