An AI Based Automatic Translator for Ancient Hieroglyphic Language—From Scanned Images to English Text
Recent advancements in the fields of Machine Learning and Deep Learning made a huge transformation in other fields that are not related to Computer Science. In this work, a new framework is proposed to tackle the problem of translating the old Egyptian Hieroglyphic writings to English language throu...
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Format: | Article |
Language: | English |
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IEEE
2023-01-01
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Series: | IEEE Access |
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Online Access: | https://ieeexplore.ieee.org/document/10103702/ |
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author | Asmaa Sobhy Mahmoud Helmy Michael Khalil Sarah Elmasry Youtham Boules Nermin Negied |
author_facet | Asmaa Sobhy Mahmoud Helmy Michael Khalil Sarah Elmasry Youtham Boules Nermin Negied |
author_sort | Asmaa Sobhy |
collection | DOAJ |
description | Recent advancements in the fields of Machine Learning and Deep Learning made a huge transformation in other fields that are not related to Computer Science. In this work, a new framework is proposed to tackle the problem of translating the old Egyptian Hieroglyphic writings to English language through deploying both Image Processing and Natural Language Processing techniques combined with AI approaches. Our primary goal is to design an application that completely revolutionizes a tourist’s experience while navigating Egyptian Historical sites. This work utilize different AI techniques to automatically convert the scanned photos of hieroglyphic language to understandable and readable English language, through two main sub-tasks: The automatic detection and recognizing of the scanned glyphs images and the translation of them into English language. Different data sources of this low-resource language were explored and augmented to train and test our models. Results of different models and algorithms are assessed and analyzed to evaluate our work. State-of-the-art results are achieved compared to literature in both automatic glyphs recognition, and glyphs-to-English translation. |
first_indexed | 2024-04-09T16:08:27Z |
format | Article |
id | doaj.art-391893fcaf7142c9a4f77d2b9d968528 |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-04-09T16:08:27Z |
publishDate | 2023-01-01 |
publisher | IEEE |
record_format | Article |
series | IEEE Access |
spelling | doaj.art-391893fcaf7142c9a4f77d2b9d9685282023-04-24T23:00:38ZengIEEEIEEE Access2169-35362023-01-0111387963880410.1109/ACCESS.2023.326798110103702An AI Based Automatic Translator for Ancient Hieroglyphic Language—From Scanned Images to English TextAsmaa Sobhy0Mahmoud Helmy1Michael Khalil2Sarah Elmasry3Youtham Boules4Nermin Negied5https://orcid.org/0000-0002-6168-4667Faculty of Electrical and Computer Engineering, University of Ottawa, Ottawa, ON, CanadaFaculty of Electrical and Computer Engineering, University of Ottawa, Ottawa, ON, CanadaFaculty of Electrical and Computer Engineering, University of Ottawa, Ottawa, ON, CanadaFaculty of Electrical and Computer Engineering, University of Ottawa, Ottawa, ON, CanadaFaculty of Electrical and Computer Engineering, University of Ottawa, Ottawa, ON, CanadaSchool of Communication and Information Engineering, Zewail City of Science and Technology, Giza, EgyptRecent advancements in the fields of Machine Learning and Deep Learning made a huge transformation in other fields that are not related to Computer Science. In this work, a new framework is proposed to tackle the problem of translating the old Egyptian Hieroglyphic writings to English language through deploying both Image Processing and Natural Language Processing techniques combined with AI approaches. Our primary goal is to design an application that completely revolutionizes a tourist’s experience while navigating Egyptian Historical sites. This work utilize different AI techniques to automatically convert the scanned photos of hieroglyphic language to understandable and readable English language, through two main sub-tasks: The automatic detection and recognizing of the scanned glyphs images and the translation of them into English language. Different data sources of this low-resource language were explored and augmented to train and test our models. Results of different models and algorithms are assessed and analyzed to evaluate our work. State-of-the-art results are achieved compared to literature in both automatic glyphs recognition, and glyphs-to-English translation.https://ieeexplore.ieee.org/document/10103702/Machine translationglyphimage processingclassificationobject detectionnatural language processing |
spellingShingle | Asmaa Sobhy Mahmoud Helmy Michael Khalil Sarah Elmasry Youtham Boules Nermin Negied An AI Based Automatic Translator for Ancient Hieroglyphic Language—From Scanned Images to English Text IEEE Access Machine translation glyph image processing classification object detection natural language processing |
title | An AI Based Automatic Translator for Ancient Hieroglyphic Language—From Scanned Images to English Text |
title_full | An AI Based Automatic Translator for Ancient Hieroglyphic Language—From Scanned Images to English Text |
title_fullStr | An AI Based Automatic Translator for Ancient Hieroglyphic Language—From Scanned Images to English Text |
title_full_unstemmed | An AI Based Automatic Translator for Ancient Hieroglyphic Language—From Scanned Images to English Text |
title_short | An AI Based Automatic Translator for Ancient Hieroglyphic Language—From Scanned Images to English Text |
title_sort | ai based automatic translator for ancient hieroglyphic language x2014 from scanned images to english text |
topic | Machine translation glyph image processing classification object detection natural language processing |
url | https://ieeexplore.ieee.org/document/10103702/ |
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