Year: 2024
Type: article
Abstract: Reading classical English literature in today’s modern context can pose significant challenges, primarily due to the evolution of language over centuries. Classical texts' words, phrases, and sentence structures often differ greatly from contemporary usage, making comprehension difficult for modern readers. This study proposes a novel solution using Machine Translation (MT) techniques to bridge this gap and simplify the understanding of classical writings. In this work, Shakespeare’s play The Tragedy of Julius Caesar has been chosen as a benchmark for classical English, given its historical significance and rich linguistic complexity. The Llama2 Chat variant, a sophisticated Large Language Model (LLM), translates Shakespearean English into contemporary language, preserving the original intent and meaning while making the text more accessible. The study not only examines the translation process but also delves into the critical parameters of the LLM that influence its performance, such as its ability to interpret context, handle ambiguities, etc. This research aims to contribute to both the appreciation of classical literature and the advancement of AI in language processing.
Author: Sandeep M Asokan
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4406994655