Harris Hermansyah Setiajid
Universitas Sanata Dharma
JLTC 0039
Machine Translation (MT) has seen a significant surge in development and application due to advances in Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies (Knight & Koehn, 2018). MT systems have the potential to streamline translation processes, saving both time and resources. However, when it comes to legal translation, MT faces several challenges and limitations, particularly for language pairs such as English and Indonesian. This article will discuss these challenges and provide examples to illustrate the inherent complexities of legal translation in this language pair.
As the demand for efficient and accurate translation grows, Machine Translation (MT) has emerged as a potential solution for various applications. However, when it comes to legal translation, particularly in the context of the English-Indonesian language pair, MT faces a unique set of challenges and limitations. In this article, we delve into these complexities, exploring the challenges and constraints of MT in legal translation and examining the potential future prospects for overcoming these hurdles.
Terminology and Ambiguity
Legal translation involves the use of specialized terminology and often requires a deep understanding of the legal systems and concepts in both the source and target languages (Čavoški, 2016). In the English-Indonesian language pair, there are numerous legal terms with no direct equivalents, which can lead to ambiguity if not properly understood and translated by the MT system. For instance, the English term “statutory rape” has no direct equivalent in Indonesian. An inexperienced MT system might translate it as “pemerkosaan yang diatur oleh undang-undang,” which literally means “rape regulated by law” – a misleading and unclear translation.
Syntax and Grammar
English and Indonesian have different grammatical structures, and MT systems might struggle to produce accurate translations that retain the meaning and nuances of the original text. For example, the English phrase “The judge granted the motion to dismiss the case” can be translated into Indonesian as “Hakim mengabulkan gugatan untuk menolak kasus tersebut.” However, an MT system might incorrectly translate it as “Hakim memberikan gerakan untuk menolak kasus,” which translates back to English as “The judge gave the movement to reject the case,” resulting in a confusing and incorrect translation.
Cultural Differences and Context
Legal systems are deeply rooted in the cultural and historical context of a country, and legal terms often reflect these contexts (Gémar, 1995). MT systems might fail to capture these nuances, resulting in translations that are culturally inappropriate or lack contextual understanding. For instance, the term “jury” in English refers to a group of people selected to render a verdict in a legal case. In the Indonesian legal system, there is no equivalent concept, as the country does not practice trial by jury. A direct translation by an MT system might result in a confusing or misleading text for Indonesian readers.
Accuracy and Reliability
Legal translation requires a high level of accuracy, as any mistranslations can lead to severe consequences, such as misinterpretation of laws, contracts, or court rulings (Borja Albi & Prieto Ramos, 2013). MT systems, even the most advanced ones, might still produce errors that could have significant implications in the legal context. For example, the English term “binding agreement” might be translated by an MT system into Indonesian as “perjanjian mengikat,” which means “an agreement that binds.” While this translation is not entirely wrong, it lacks the legal nuance and specificity needed in a legal context.
While MT has made significant advancements in recent years, its application in the field of legal translation remains limited, particularly for language pairs like English and Indonesian. Challenges such as terminology, syntax, grammar, cultural differences, and the need for high accuracy and reliability make it difficult for MT systems to fully replace human translators in this context. Future research and development in AI and NLP technologies might help to address these challenges and improve the performance of MT systems in legal translation.
Collaborative approaches, such as post-editing, where human translators review and edit machine-generated translations, can also help to harness the potential of MT while mitigating its limitations (Garcia, 2011). This hybrid approach can leverage the efficiency and speed of MT while maintaining the quality and accuracy that only human expertise can provide.
To overcome these limitations and ensure accurate legal translations, it is crucial to involve professional human translators with expertise in both the source and target languages, as well as a deep understanding of the legal systems and cultural contexts involved (Cao, 2007). Furthermore, integrating MT systems with translation memories, glossaries, and specialized legal dictionaries could also improve the quality of machine-generated translations (Bogucki, 2013).
Collaborative approaches, such as post-editing, where human translators review and edit machine-generated translations, can also help to harness the potential of MT while mitigating its limitations (Garcia, 2011). This hybrid approach can leverage the efficiency and speed of MT while maintaining the quality and accuracy that only human expertise can provide.
Ultimately, as MT technology continues to evolve, its role in legal translation might expand, and the challenges and limitations discussed in this article may be mitigated. However, for the foreseeable future, human expertise will remain an indispensable element in the legal translation process, particularly for complex language pairs such as English and Indonesian.
References
Bogucki, Ł. (2013). Areas and Methods of Audiovisual Translation Research. Peter Lang.
Borja Albi, A., & Prieto Ramos, F. (Eds.). (2013). Legal Translation in Context: Professional Issues and Prospects. Peter Lang.
Cao, D. (2007). Translating Law. Multilingual Matters.
Čavoški, A. (2016). Legal Translation in the EU: The Paradox of Multilingualism. In L. Cheng, K. Sin, & A. Wagner (Eds.), The Ashgate Handbook of Legal Translation (pp. 89-104). Routledge.
Garcia, I. (2011). Translating by Post-Editing: Is it the Way Forward? Machine Translation, 25(3), 217-237.
Gémar, J.-C. (1995). Traduire ou l’art d’interpréter: Fonctions, statut et esthétique de la traduction. Presses de l’Université du Québec.
Knight, K., & Koehn, P. (2018). Machine Translation: A Concise History. In J. Hutchins (Ed.), Early Years in Machine Translation (pp. 1-16). Springer.