| dc.description.abstract | This study proposes to recognize words in Sinhalese inscriptions using computational techniques as inscriptions
form a foundational element of Sri Lanka’s historical record and cultural heritage. Computational Archaeology
plays a vital role in fields of Archaeology, Linguistics, and Anthropology. There is a significant advancement in
using computational techniques to recognize text on inscriptions since manual interpretation and transcription are
highly effort intensive, resource demanding and prone to inaccuracies. The model trained and evaluated on a
curated dataset of 300 tokenized Sinhalese inscription images. The performance of You Only Look Once (YOLO);
a deep learning model, was analyzed based on standard evaluation metrics—accuracy, precision, recall, and F1
score. Results indicate promising average accuracy of 90% and demonstrates YOLOv5’s superiority in handling
the unique challenges of ancient Sinhalese epigraphy such as irregular layouts, paleographic variations, and
surface degradation compared to Optical Character Recognition systems. This research not only seeks to preserve
and enhance access to Sri Lanka’s rich cultural heritage but also provides a wider scope for linguistic and scholarly
inquiry by facilitating more efficient analysis of ancient texts through automated recognition of Sinhalese
inscriptions. | en_US |
