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Exploring the Alignment of Transcriptions to Images of Encrypted Manuscripts
Stockholm University, Faculty of Humanities, Department of Linguistics.ORCID iD: 0000-0002-4838-6518
2024 (English)In: Proceedings of the 7th International Conference on Historical Cryptology HistoCrypt 2024 / [ed] Michelle Waldispühl; Beáta Megyesi, Tartu University Library , 2024, p. 103-107Conference paper, Published paper (Refereed)
Abstract [en]

The automatic transcription of encrypted manuscripts is a challenge due to the different handwriting styles and the often invented symbol alphabets. Many transcription methods require annotated sources, including symbol locations. However, most existing transcriptions are provided at line or page level, making it necessary to find the bounding boxes of the transcribed symbols in the image, a process referred to as alignment. So, in this work, we develop several alignment methods, and discuss their performance on encrypted documents with various symbol sets.

Place, publisher, year, edition, pages
Tartu University Library , 2024. p. 103-107
Series
NEALT Proceedings Series, ISSN 1736-8197, E-ISSN 1736-6305 ; 53
Keywords [en]
Encrypted manuscripts, Text-to-image alignment, Transcription alignment, Deep learning, Sequence learning
National Category
Natural Language Processing
Research subject
Computational Linguistics
Identifiers
URN: urn:nbn:se:su:diva-229160DOI: 10.58009/aere-perennius0096ISBN: 978-99-1683-384-1 (print)OAI: oai:DiVA.org:su-229160DiVA, id: diva2:1857887
Conference
The 7th International Conference on Historical Cryptology (HistoCrypt 2024), Oxford and Bletchley Park, UK, June 25-27, 2024
Projects
DECRYPT
Funder
Swedish Research Council, 2018-06074Available from: 2024-05-14 Created: 2024-05-14 Last updated: 2025-02-07Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
  • de-DE
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  • nn-NB
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Output format
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