HieroGlyphTranslator: Automatic Recognition and Translation of Egyptian Hieroglyphs to English
By: Ahmed Nasser , Marwan Mohamed , Alaa Sherif and more
Potential Business Impact:
Translates ancient Egyptian drawings into English words.
Egyptian hieroglyphs, the ancient Egyptian writing system, are composed entirely of drawings. Translating these glyphs into English poses various challenges, including the fact that a single glyph can have multiple meanings. Deep learning translation applications are evolving rapidly, producing remarkable results that significantly impact our lives. In this research, we propose a method for the automatic recognition and translation of ancient Egyptian hieroglyphs from images to English. This study utilized two datasets for classification and translation: the Morris Franken dataset and the EgyptianTranslation dataset. Our approach is divided into three stages: segmentation (using Contour and Detectron2), mapping symbols to Gardiner codes, and translation (using the CNN model). The model achieved a BLEU score of 42.2, a significant result compared to previous research.
Similar Papers
HieroLM: Egyptian Hieroglyph Recovery with Next Word Prediction Language Model
Computation and Language
Restores ancient Egyptian writing lost to time.
Advanced Deep Learning Approaches for Automated Recognition of Cuneiform Symbols
Computation and Language
Lets computers read ancient clay tablet writing.
Neural Style Transfer for Synthesising a Dataset of Ancient Egyptian Hieroglyphs
Machine Learning (CS)
Makes computers understand old Egyptian writing.