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Archivists, textual scholars, and historians often produce digital editionsof historical documents. Using markup schemes such as those of the TextEncoding Initiative and EpiDoc, these digital editions often record documents'semantic regions (such as notes and figures) and physical features (such aspage and line breaks) as well as transcribing their textual content. Wedescribe methods for exploiting this semantic markup as distant supervision fortraining and evaluating layout analysis models. In experiments with severalmodel architectures on the half-million pages of the Deutsches Textarchiv(DTA), we find a high correlation of these region-level evaluation methods withpixel-level and word-level metrics. We discuss the possibilities for improvingaccuracy with self-training and the ability of models trained on the DTA togeneralize to other historical printed books.

Digital Editions as Distant Supervision for Layout Analysis of Printed Books