On Determining Multiple Languages through Technological Examination for Conservation Management Using Machine Learning

Abstract

This study delves into the intricate linguistic history of Quang Nam province, a region rich in cultural and linguistic layers that existed long time ago. By analyzing place names and linguistic strata, the research uncovers traces of Mon Khmer and Austronesian languages, highlighting the region’s deep historical connections and multilingualism within Cham Pa society. To further explore these linguistic complexities, we employed an interdisciplinary approach that integrates insights from comparative linguistics, archaeology, and cultural studies. A key contribution of this research is the application of advanced information technology, specifically data mining and artificial intelligence, to the preservation and analysis of this linguistic heritage. Using the YOLO-v8 deep learning model, we developed a system capable of accurately recognizing and classifying handwritten place names. The YOLO-v8 model, renowned for its powerful object detection capabilities, was instrumental in automating the analysis of large datasets, achieving high levels of accuracy in the recognition of diverse linguistic characters. This integration of AI not only enhances our ability to study historical language use but also provides an efficient and scalable solution for archiving and managing valuable cultural data. The results of this study contribute to both the field of linguistic conservation and the development of AI-based tools for heritage preservation, ensuring the longevity and accessibility of the rich linguistic diversity of the region for future research.