Michalcová, Anna; et al. · PyLaia · Published May 18, 2025

Old Czech Handwriting (with spaces)

Text Recognition

Description

This model is based on ground truth from four Old Czech sources: 1) Padeřov Bible (Vienna, Austrian National Library, shelfmark Cod. 1175, 1432–1435), Zenodo: https://doi.org/10.5281/zenodo.7467034. 2) Cistercian Bible (New York, The Morgan Library & Museum, shelfmark MS M.752, 1456). 3) New Testament of Martin Lupáč (Vienna, Austrian National Library, shelfmark Cod. 1175, 1440), Zenodo: https://doi.org/10.5281/zenodo.10619017. 4) Prague Bible (Vienna, Österreichische Nationalbibliothek, shelfmark Ink 13.C.5, 1488), Zenodo: https://doi.org/10.5281/zenodo.14524858. It can be used on Old Czech manuscripts written in bastard, primarily from the 14th and 15th centuries. The transcription rules were based on semi-diplomatic transcription rules set by Pero OCR and “Směrnice pro vydávání starších českých textů” by Jiří Daňhelka. https://vokabular.ujc.cas.cz/moduly/edicnipoznamka.aspx?id=DanhelkaSmernice Abbreviations were tagged and expanded. This model was trained on transcription, where spaces were created between words based on Jiří Daňhelka’s semi-diplomatic transcription rules (see above), regardless of the form in the manuscripts, and produced within the HTR Winter School 2022, 2023, and 2024. All authors who contributed to creation of this model are named on respective Zenodo pages of the datasets.

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Very low error rate4.92% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 4.92% on its validation set. As a rule of thumb, a CER below 10% is considered good for most handwritten material.

Measured on the model's own validation data. Results on your documents may differ depending on handwriting style, document condition, language, and how closely your material resembles the training data.

Words121,340
Lines21,866
Training Pages228
Model ID341425
Languages
Czech