Reading Georgian Manuscripts Automatically on the eScriptorium Platform

The article outlines the development of means for an automatic reading of Georgian manuscripts on the eScriptorium platform and the first results achieved with them. After an overview of the efforts undertaken in applying Optical Character Recognition (OCR) to Georgian printed books since the late 1980’s and a short introduction into the basics of the eScriptorium approach to Handwritten Text Recognition (HCR) and its functionalities, it exemplifies the application of the three core procedures of eScriptorium, which consist in the automatic segmentation of text-covered regions and lines, the automatic transcription of the detected lines based on manual input and the training of appropriate models, and the alignment with existing electronic texts in order to provide reliable ground truth for further training. With a total of 292 manually transcribed pages and 3812 pages with aligned (but not yet always corrected) text that have been processed so far, there is a strong material basis for further improvement of the models and the reading results depending on them.

Authors

Publication Details

Journal
Digital Kartvelology
Published
2024-12-27
DOI
https://doi.org/10.62235/dk.3.2024.8508
Citations
1
Primary Topic
Digital Humanities and Scholarship
Type
article
Field-Weighted Citation Impact
3.91

Funders

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article

Reading Georgian Manuscripts Automatically on the eScriptorium Platform

Daniel Stökl Ben Ezra, Jost Gippert
1 citations
Digital Kartvelology
Digital Humanities and Scholarship
3.91
article

Reading Georgian Manuscripts Automatically on the eScriptorium Platform

Daniel Stökl Ben Ezra, Jost Gippert
article en
1 citations

Abstract

The article outlines the development of means for an automatic reading of Georgian manuscripts on the eScriptorium platform and the first results achieved with them. After an overview of the efforts undertaken in applying Optical Character Recognition (OCR) to Georgian printed books since the late 1980’s and a short introduction into the basics of the eScriptorium approach to Handwritten Text Recognition (HCR) and its functionalities, it exemplifies the application of the three core procedures of eScriptorium, which consist in the automatic segmentation of text-covered regions and lines, the automatic transcription of the detected lines based on manual input and the training of appropriate models, and the alignment with existing electronic texts in order to provide reliable ground truth for further training. With a total of 292 manually transcribed pages and 3812 pages with aligned (but not yet always corrected) text that have been processed so far, there is a strong material basis for further improvement of the models and the reading results depending on them.

Digital KartvelologyVol. 3
European Commission, Deutsche Forschungsgemeinschaft, Universität Hamburg, HORIZON EUROPE Framework Programme
Quality Education
Openalex Percentile: Top 5%
Digital Humanities and Scholarship
3.91
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Reading Georgian Manuscripts Automatically on the eScriptorium Platform — Daniel Stökl Ben Ezra, Jost Gippert · Digital Kartvelology (2024) | TGRS Research Map | TGRS