Artificial intelligence powered OCR models for digitizing ayurveda manuscripts

Abstract

This article presents a novel approach to transcribe Ayurveda manuscripts using Optical Character Recognition (OCR) technology enhanced with machine learning and forensic handwriting analysis techniques. Traditional transcription methods for these manuscripts are time-consuming and challenging due to diverse scripts and handwriting styles. The proposed methodology involves collecting manuscript samples from various sources and training OCR models to recognize the nuances of these scripts. By incorporating forensic handwriting principles, such as consistency and natural variation, the OCR models achieve greater accuracy.

Additionally, the development of user-friendly interfaces allows scholars to train these models without needing technical expertise, streamlining the digitization process. Preliminary results show that this approach significantly improves transcription accuracy compared to conventional OCR software. This method offers a scalable solution for digitizing Ayurveda texts, preserving cultural heritage, and accelerating research in Ayurveda medicine. Future research will focus on refining OCR models and expanding their application to other scripts and languages.