Handwritten to English: AI Manuscript Decoder

Addressing real-time translation and accessibility challenges in historical manuscripts written in the Devanagiri script, this research introduces an implementation of Optical Character Recognition (OCR) seamlessly integrated with intelligent agents. By combining Multimodal OCR and Neural Machine Translation (NMT) systems, methodology enables seamless recognition and translation of text into contemporary languages with spoken output. Overcoming accuracy challenges and linguistic nuances specific to historical manuscripts, the system enhances inclusivity for researchers and enthusiasts. The Multimodal OCR ensures adaptability to diverse manuscript formats, while the NMT guarantees precise translations. The inclusion of intelligent agents enhances system responsiveness, optimizing real-time processing. The integration of spoken output further broadens accessibility, cultivating a more inclusive and enriched experience for a diverse audience.