Academic Journal of Humanities & Social Sciences, 2023, 6(24); doi: 10.25236/AJHSS.2023.062403.
Yon Jee Kwun (Yang Yikun)1, Yon Jee Eean (Yang Yiyan)2
1Foreign Language School, Gannan Normal University, Ganzhou, China
2School of Information Management, Jiangxi University of Finance and Economics, Nanchang, China
This article highlights the pivotal role played by domain-specific English parallel corpus (DSEPC) in Neural Machine Translation (NMT) model training by applying DSEPC that can be utilized to train the model and improve the quality of rendered translations. After empirical study, it turns out that DSEPC can further augment the accuracy and fluency of translations. Therefore, the access to domain-specific corpora is imperative for effective and high-quality NMT model training.
Corpus-based Machine Translation; Domain-specific English Parallel Corpus; Neural Machine Translation; Translation Efficacy
Yon Jee Kwun (Yang Yikun), Yon Jee Eean (Yang Yiyan). An Empirical Validation of Domain-Specific English Parallel Corpus for Mechanical Translation Efficacy Enhancement. Academic Journal of Humanities & Social Sciences (2023) Vol. 6, Issue 24: 13-18. https://doi.org/10.25236/AJHSS.2023.062403.
[1] Hierons, Robert M. Machine Learning. Tom M. Mitchell. Published by McGraw-Hill, Maidenhead, U.K., International Student Edition, 1997. ISBN: 0-07-115467-1, 414 Pages. Price: U.K. £22.99, Soft Cover. no. 3, Sept. 1999, pp. 191–93, doi:10.1002/(sici)1099-1689(199909)9:3<191::aid-stvr184> 3.0.co;2-e.
[2] Sutskever, Ilya, Oriol Vinyals, and Quoc V. Le. "Sequence to sequence learning with neural networks." Advances in neural information processing systems 27 (2014).
[3] Sennrich, Rico, et al. Improving Neural Machine Translation Models with Monolingual Data. Aug. 2016, doi:10.18653/v1/p16-1009.
[4] Artetxe, Mikel, et al. Unsupervised Statistical Machine Translation. Sept. 2018, doi:10.18653/v1/d18-1399.
[5] Artetxe, Mikel, et al. An Effective Approach to Unsupervised Machine Translation. Feb. 2019, doi:10.18653/v1/p19-1019.
[6] Johnson, Melvin, et al. “Google’s Multilingual Neural Machine Translation System: Enabling Zero-Shot Translation.” Transactions of the Association for Computational Linguistics, vol. 5, Oct. 2017, pp. 339–51, doi: 10.1162/tacl_a_00065.