Transformer-based Optical Text Recognition for Low-Resource Languages: A Case Study on Bengali and Nepali

This study proposes a transformer-based model for accurate optical text recognition in Bengali and Nepali, two low-resource languages with unique script characteristics. The model achieves low character and word error rates, demonstrating its potential for practical applications like document digitization and text extraction.