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The Integration of Machine Translation Technology in the Realm of Legal Interpretation

Received: 5 February 2024    Accepted: 21 February 2024    Published: 29 February 2024
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Abstract

This article aims to provide an overview of the application of machine translation technology in the field of legal translation, exploring its potential, challenges, and future directions. Firstly, it reviews the development process of machine translation technology, including rule-based methods, statistical machine translation, and the application of deep learning methods. Secondly, on the basis of in-depth deconstruction of the operating rules of the big language model, it is demonstrated that the highly modeled written legal language is highly consistent with the underlying logic of the big language model because of its standardization, accuracy and de-contextualization, so compared with other styles, machine translation technology will achieve better translation results in the field of legal translation. In addition, multimodal technology can also be applied to court interpretation, which greatly alleviates the shortage of qualified interpreters and maintains judicial justice. Furthermore, it discusses the human-machine collaborative model in legal translation, emphasizing the importance of human proofreading and review in ensuring translation accuracy and reliability. Lastly, it summarizes the prospects and challenges of machine translation technology in the field of legal translation. Through a systematic review and analysis of relevant literature, this article reveals the immense potential of machine translation technology in legal translation. It can significantly enhance the efficiency and quality of legal translation, thereby enhancing the capacity of legal language services.

Published in American Journal of Education and Information Technology (Volume 8, Issue 1)
DOI 10.11648/j.ajeit.20240801.13
Page(s) 21-28
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Machine Translation Technology, Legal Translation, Large Language Model, Human-Machine Collaboration

References
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[2] Wang Huasu, Li Zhi. Research on Translation Technology in the Era of Artificial Intelligence: Connotation, Classification, and Trends. Foreign Language Cultures; 2020 (1), pp. 86-95. https://doi.org/10.19967/j.cnki.flc.2020.01.010.
[3] Zhang Falian. Explore the Mechanism of Cultivating Multidisciplinary Legal English Talent in the New Era. Foreign Language Teaching, 2018 (5), pp. 44-47.
[4] Vaswani, A. Shazeer, N. Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., -Yeah. & Polosukhin, I. Attention is All You Need. In Advances in Neural Information Processing Systems, 2017, pp. 5998-6008.
[5] Bhandanau, D. Cho, K., & Bengio, Y. Neural Machine Translation by Jointly Learning to Align and Translate, arXiv, 2014.
[6] Goldman K J, Goldman S A, Kanellakis P C, et al. ISIS: Interface for a Semantic Information System. ACM SIGMOD Record, 1985, 14(4).
[7] Maruf S, Haffari G. Document Context Neural Machine Translation with Memory networks. arXiv, 2017.
[8] Li Kuixing, Zhang Xinhong. Law Texts and Legal Translations. Beijing: China Media Group, China International Publishing and Translation Corporation; 2010, pp. 10.
[9] Pang Qingyun. The Legal Language of China in the 21st Century. Shanghai: East China Normal University Press; 1997, pp. 6.
[10] Sarcevic, Suan, New Approach to Legal Translation. The Hague: Kluwer Law International; 1997.
[11] John Gimon, Cheng Chaoyang, and others. Introduction to Legal Linguistics. Beijing: Law Press; 2007, pp. 45.
[12] Russell, B. My Philosophical Development. London: Unwin, 1975.
[13] Maitland, Year Books of Edward II, pp. xxxiv.
[14] Swift, Gulliver’s Travels, pp. 297 (Crown ed. 1947).
[15] Wang Jian, Yang Baijun. The Prospects and Struggles of Court Interpretation in China. Journal of Sichuan University of Foreign Chinese Languages; 2007(03), pp. 115-120.
[16] He Fanyu. Enhancing the Ability of International Legal Communication to Highlight China's Atmosphere. People's Justice, 2021, (22), pp. 1. https://doi.org/10.19684/j.cnki.1002-4603.2021.22.005
[17] Liu Xinkai. A Programmatic Perspective on the Theoretical Study and Paths of China's Courtroom Interpretation. Translations: Interdisciplinary Studies; 2022, 3(02), pp. 96-110.
[18] Feng Quangong, Cui Qiliang. Translation and Editing Research: The focus of analysis and its developmental trends. Shanghai Translations; 2016(6), pp. 67-74+89+94.32.
[19] Wang Lv, Wang Xiangling. The training mode of translation and editing abilities cultivation in the era of ChatGPT. Foreign Language and Electronic Teaching; 2023, (04), pp. 16-23+115.
Cite This Article
  • APA Style

    Jie, Z. (2024). The Integration of Machine Translation Technology in the Realm of Legal Interpretation. American Journal of Education and Information Technology, 8(1), 21-28. https://doi.org/10.11648/j.ajeit.20240801.13

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    ACS Style

    Jie, Z. The Integration of Machine Translation Technology in the Realm of Legal Interpretation. Am. J. Educ. Inf. Technol. 2024, 8(1), 21-28. doi: 10.11648/j.ajeit.20240801.13

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    AMA Style

    Jie Z. The Integration of Machine Translation Technology in the Realm of Legal Interpretation. Am J Educ Inf Technol. 2024;8(1):21-28. doi: 10.11648/j.ajeit.20240801.13

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  • @article{10.11648/j.ajeit.20240801.13,
      author = {Zhu Jie},
      title = {The Integration of Machine Translation Technology in the Realm of Legal Interpretation},
      journal = {American Journal of Education and Information Technology},
      volume = {8},
      number = {1},
      pages = {21-28},
      doi = {10.11648/j.ajeit.20240801.13},
      url = {https://doi.org/10.11648/j.ajeit.20240801.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajeit.20240801.13},
      abstract = {This article aims to provide an overview of the application of machine translation technology in the field of legal translation, exploring its potential, challenges, and future directions. Firstly, it reviews the development process of machine translation technology, including rule-based methods, statistical machine translation, and the application of deep learning methods. Secondly, on the basis of in-depth deconstruction of the operating rules of the big language model, it is demonstrated that the highly modeled written legal language is highly consistent with the underlying logic of the big language model because of its standardization, accuracy and de-contextualization, so compared with other styles, machine translation technology will achieve better translation results in the field of legal translation. In addition, multimodal technology can also be applied to court interpretation, which greatly alleviates the shortage of qualified interpreters and maintains judicial justice. Furthermore, it discusses the human-machine collaborative model in legal translation, emphasizing the importance of human proofreading and review in ensuring translation accuracy and reliability. Lastly, it summarizes the prospects and challenges of machine translation technology in the field of legal translation. Through a systematic review and analysis of relevant literature, this article reveals the immense potential of machine translation technology in legal translation. It can significantly enhance the efficiency and quality of legal translation, thereby enhancing the capacity of legal language services.
    },
     year = {2024}
    }
    

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    JO  - American Journal of Education and Information Technology
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    AB  - This article aims to provide an overview of the application of machine translation technology in the field of legal translation, exploring its potential, challenges, and future directions. Firstly, it reviews the development process of machine translation technology, including rule-based methods, statistical machine translation, and the application of deep learning methods. Secondly, on the basis of in-depth deconstruction of the operating rules of the big language model, it is demonstrated that the highly modeled written legal language is highly consistent with the underlying logic of the big language model because of its standardization, accuracy and de-contextualization, so compared with other styles, machine translation technology will achieve better translation results in the field of legal translation. In addition, multimodal technology can also be applied to court interpretation, which greatly alleviates the shortage of qualified interpreters and maintains judicial justice. Furthermore, it discusses the human-machine collaborative model in legal translation, emphasizing the importance of human proofreading and review in ensuring translation accuracy and reliability. Lastly, it summarizes the prospects and challenges of machine translation technology in the field of legal translation. Through a systematic review and analysis of relevant literature, this article reveals the immense potential of machine translation technology in legal translation. It can significantly enhance the efficiency and quality of legal translation, thereby enhancing the capacity of legal language services.
    
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Author Information
  • English Department, Henan University of Economics and Law, Zhengzhou, China

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