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DH Seminar: Artificial Intelligence in Archives: Handwritten Text Recognition with Transkribus

A Digital Humanities seminar
Date21 November 2018
Time16:00 to 17:30
PlaceDigital Humanities Laboratory, Seminar room 1

Digital Humanities Lab seminar series. Dr Louise Seaward (UCL): ‘Artificial Intelligence in Archives: Handwritten Text Recognition with Transkribus’. Join us for drinks and nibbles following the paper!

Dr Louise Seaward has been a research associate at the Bentham Project since March 2015 and became the coordinator of the Transcribe Bentham crowdsourcing initiative in January 2016.  She also works as part of the Recognition and Enrichment of Archival Documents (READ) project, which is training computers to process handwritten text.  Aside from Bentham and Digital Humanities, her other research interests relate to the political and cultural history of eighteenth-century Europe.  She received her PhD in History from the University of Leeds in 2013 and has published articles on the history of censorship in eighteenth-century France and Switzerland.


The automated recognition of handwritten historical documents is now a reality.  Transkribus (https://transkribus.eu/Transkribus/) is a research infrastructure for the automated recognition, transcription and searching of handwritten historical collections.  This paper will summarise the technical workings of handwriting recognition, providing evidence of its accuracy and exploring some of the issues which arise when processing documents with difficult handwriting or complex layouts.  It will discuss real-world examples to show how numerous scholars and archives are already benefiting from this technology: from providing full-text search of digital collections to establishing a more efficient workflow for scholarly editing projects.  The paper will emphasise the potential benefits of integrating innovative technology into cultural heritage projects and institutions but also consider the challenge of providing a sustainable and useful service to a large user base working with a vast range of documents.

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