Steps Towards Mining Manuscript Images for Untranscribed Texts: A Case Study From the Syriac Collection at the Vatican Library

Steps Towards Mining Manuscript Images for Untranscribed Texts: A Case Study From the Syriac Collection at the Vatican LibraryCEUR Workshop Proceedings 3834Syriaca.org: The Syriac Reference PortalThe National Endowment for the HumanitiesThe International Balzan Prize FoundationDavid A. Michelsoncbsc_adminRecord added to Zotero bycbsc_adminSyriaca.org: The Syriac Reference Portalhttp://syriaca.org/cbss/VLPGWKQM/tei

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2025-05-20-05:00

Born digital.

CREATED: This bibl record was autogenerated from a Zotero record.LuigiBambaciGeorge AntonKirazChristineRoughanMatthieuFreyderDanielStökl Ben EzraSteps Towards Mining Manuscript Images for Untranscribed Texts: A Case Study From the Syriac Collection at the Vatican Libraryhttp://syriaca.org/cbss/VLPGWKQMhttps://www.zotero.org/groups/a_comprehensive_bibliography_on_syriac_studies/items/VLPGWKQMhttps://www.zotero.org/groups/4861694/items/VLPGWKQMWouterHaveralsMarijnKoolenLaureThompsonComputational Humanities Research 2024: Proceedings of the Computational Humanities Research Conference 2024, Aarhus, Denmark, December 4-6, 2024[s.n.]CEUR-WS.org202448-64CEUR Workshop Proceedings 3834Digital libraries and databases of texts are invaluable resources for researchers, yet their reliance on printed editions can lead to significant gaps and potentially exclude works without printed reproductions. The Simtho database of Syriac serves as a pertinent example: it is derived primarily from OCR of scholarly editions, but how representative are these of the language’s extensive literary tradition, transmitted and preserved in manuscript form for centuries? Taking the Simtho database and a selection of the Vatican Library’s Syriac manuscript collection as a case study, we propose a pipeline that aligns a corpus of e-texts with a set of digitised manuscript images, in order to ascertain the presence or absence of texts between the e-text and manuscript corpora and thus contribute to their enrichment. We delve into the complexities of this task, evaluating both effective tools for alignment and approaches to detect factors that can contribute to alignment failures. This case study is intended as a first step towards foundational methodologies applicable to larger-scale manuscript processing efforts. Bambaci, Luigi, George Anton Kiraz, Christine Roughan, Matthieu Freyder, and Daniel Stökl Ben Ezra. “Steps Towards Mining Manuscript Images for Untranscribed Texts: A Case Study From the Syriac Collection at the Vatican Library.” In Computational Humanities Research 2024: Proceedings of the Computational Humanities Research Conference 2024, Aarhus, Denmark, December 4-6, 2024, edited by Wouter Haverals, Marijn Koolen, and Laure Thompson, 48–64. CEUR Workshop Proceedings 3834. [s.n.]: CEUR-WS.org, 2024. Luigi Bambaci et al., Steps Towards Mining Manuscript Images for Untranscribed Texts: A Case Study From the Syriac Collection at the Vatican Library, in Computational Humanities Research 2024: Proceedings of the Computational Humanities Research Conference 2024, Aarhus, Denmark, December 4-6, 2024, ed. Wouter Haverals, Marijn Koolen, and Laure Thompson, CEUR Workshop Proceedings 3834 ([s.n.]: CEUR-WS.org, 2024), 48–64.