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Model trained on 11th century manuscripts to produce graphematic transcription (Latin).

Name: Model trained on 11th century manuscripts to produce graphematic transcription (Latin).
Creator: Michael Schonhardt

descriptionPublicationkeyboard_double_arrow_right Other ORP type Under curationPublisher:Zenodo

Authors: Michael Schonhardt;

doi: 10.5281/zenodo.13741957

Model trained on 11th century manuscripts to produce graphematic transcription (Latin).

- Summary

Abstract

This model has been trained as part of the ongoing edition project Burchards Dekret Digital (www.burchards-dekret-digital.de), funded by the Academy of Sciences and Literature Mainz. It is the project's first high-quality model specifically designed to produce a graphematic transcription based on a predefined set of special characters (https://github.com/michaelscho/transpy?tab=readme-ov-file#special-characters) in accordance with the MUFI standard. The model was trained on five 11th-century manuscripts that can be traced to the episcopal scriptorium in Worms: Bamberg, SB, Msc.Can.6 (https://mdz-nbn-resolving.de/urn:nbn:de:bvb:12-bsb00140701-0), Frankfurt, UB, Ms. Barth. 50 (https://sammlungen.ub.uni-frankfurt.de/msma/urn/urn:nbn:de:hebis:30:2-12488), Köln, EDD, Cod. 119 (https://digital.dombibliothek-koeln.de/urn/urn:nbn:de:hbz:kn28-3-3241), Vatican, BAV, Pal.lat.585 (https://digi.vatlib.it/mss/detail/Pal.lat.585), and Vatican, BAV, Pal.lat.586 (https://digi.vatlib.it/mss/detail/Pal.lat.586). However, it also works well as a base model for later medieval scripts. The model was trained by Dr. Michael Schonhardt (Universität Kassel, https://orcid.org/0000-0002-2750-1900). Transcriptions were provided and proofread by Helena Geitz, Daniel Gneckow, Dr. Andreas Grote, Prof. Dr. Lotte Kéry, Dr. Birgit Kynast, Dr. Hans-Christian Lehner, Dr. Melanie Panse-Buchwalter, Michaela Parma, Dr. Cornelia Scherer, Dr. Michael Schonhardt and Dr. des. Elena Vanelli. The project is led by Prof. Dr. Ingrid Baumgärtner, Prof. Dr. Klaus Herbers and Prof. Dr. Ludger Körntgen. The model was trained in 54 epochs using a learning rate of 0.0008 and a batch size of 64.

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