• K. Sanjana Reddy
• K Nitheesh
• K sai prasanna
• P venkata pratima

: This paper proposes a novel approach for translating Hieroglyphic images into text using Natural Language Processing(NLP) techniques and the VGG-16 Convolutional Neural Network(CNN) architecture. Hieroglyphs pose a unique challenge due to their complex visual representation and diverse meaning, requiring advanced computational methods for accurate interpretation. Although there are a lot of automatic translators available these days, there hasn't been much progress made in the hieroglyphic language, an ancient Egyptian language which is a low resource language. Therefore, in order to address the issue of translating hieroglyphic language, we are putting forth a novel framework. This could be the next revolutionary advancement in artificial intelligence, utilizing deep learning algorithms and natural language processing techniques. The first step involves pre-processing the hieroglyphic images to enhance clarity and remove noise, preparing them for feature extraction. The VGG-16 CNN is then employed to extract high-level features from the pre-processed images, capturing intricate details crucial for deciphering hieroglyphic symbols. Next, a hybrid NLP model is utilized to process the extracted features and generate textual representations of the hieroglyphs. This model combines deep learning techniques with linguistic rules and contextual analysis to accurately translate visual hieroglyphs into meaningful text. The experimental results demonstrate promising accuracy rates in hieroglyphic image translation, showcasing the potential of integrating NLP and deep learning methodologies for deciphering ancient scripts. This research contributes to the field of digital archaeology and cultural preservation by providing an automated tool for interpreting and understanding hieroglyphic inscriptions. This work's fundamental goal is to improve visitors' experiences at authentic Egyptian sites while also assisting with research and development.

Hieroglyphic language, Translations, AI, Deep Learning, NLP, Image processing, Tourist experience.

"AN AI BASED AUTOMATIC TRANSLATOR FOR ANCIENT HEIROGLYPHIC LANGUAGE-FROM SCANNED IMAGES TO ENGLISH TEXT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.a726-a732, July-2024, Available :http://www.jetir.org/papers/JETIR2407071.pdf

"AN AI BASED AUTOMATIC TRANSLATOR FOR ANCIENT HEIROGLYPHIC LANGUAGE-FROM SCANNED IMAGES TO ENGLISH TEXT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. ppa726-a732, July-2024, Available at : http://www.jetir.org/papers/JETIR2407071.pdf