AI-Driven Intralingual Translation across Historical Varieties

Abstract

This article examines how Artificial Intelligence (AI) can transform intralingual translation, with a focus on historical varieties, particularly Early Modern English. It explores the foundations of AI-based translation, addressing both the challenges and opportunities of applying this technology to linguistic change over time. Drawing from models in linguistics, natural language processing, and historical linguistics, the study investigates the modernization of Early Modern English, using literary and specialized texts to demonstrate AI’s effectiveness in handling complex vocabulary and syntax. The paper also evaluates AI's impact on fields like historical linguistics and digital humanities, discussing both the benefits and the limitations, such as the risk of anachronism and the need for human oversight. Additionally, it considers how AI-driven translation can contribute to the digitization and accessibility of historical texts, broadening access to linguistic resources and enhancing appreciation for language evolution.

Keywords

• Early Modern English
• Literary texts
• Specialized texts
• Intralingual translation
• Modernization
• AI