Transcription Alignment for Highly Fragmentary Historical Manuscripts: The Dead Sea Scrolls

Daniel Stokl Ben Ezra, Bronson Brown-Devost, Nachum Dershowitz, Alexey Pechorin, Benjamin Kiessling

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Most of the Dead Sea Scrolls have now been digitally transcribed and imaged to very high standards. Our goal is to align the transcriptions with the text visible in the image, glyph by (often fragmentary) glyph. This involves several tasks, normally considered in isolation: (A) Baseline segmentation. (B) Line polygon extraction. (C) Automated transcription by handwritten character recognition, to aid in alignment. (D) Alignment of the Unicode characters in a line transcription with the characters in the image of that line. The task is frustrated by the degraded nature of the frequently very small and/or warped fragments with many broken letters, substantially different allographs, ligatures, and scribal idiosyncrasies. Furthermore, a great number of inconsistencies between current cataloguing systems for the data need to be resolved. For each task, we apply state-of-the-art machine-learning methods in addition to more traditional techniques, each presenting significant difficulties on account of the poor state of most fragments' preservation. We have built ground-truth datasets and have managed to achieve good results with well-preserved fragments by leveraging heavily augmented transfer learning from prior work with medieval manuscripts.

Original languageEnglish
Title of host publicationProceedings - 2020 17th International Conference on Frontiers in Handwriting Recognition, ICFHR 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages361-366
Number of pages6
ISBN (Electronic)9781728199665
DOIs
StatePublished - Sep 2020
Event17th International Conference on Frontiers in Handwriting Recognition, ICFHR 2020 - Dortmund, Germany
Duration: 7 Sep 202010 Sep 2020

Publication series

NameProceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR
Volume2020-September
ISSN (Print)2167-6445
ISSN (Electronic)2167-6453

Conference

Conference17th International Conference on Frontiers in Handwriting Recognition, ICFHR 2020
Country/TerritoryGermany
CityDortmund
Period7/09/2010/09/20

Funding

FundersFunder number
Deutsch-Israelische Projektkooperation871127
Horizon 2020 Framework Programme

    Keywords

    • historical manuscripts
    • image segmentation
    • transcription alignment

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