Project “Bulliot, Bibracte et moi" · PyLaia · Published November 28, 2022

BBM Bulliot French C19th handwritten 2021

Text Recognition

Description

“Bulliot, Bibracte et moi”, winner of a French Ministry of Culture's call for Innovative Digital Services, is a “citizen science” project dedicated to transcript, the notebooks of Jacques-Gabriel Bulliot (1817-1902), who initiated the first excavations at the Bibracte archaeological site between 1867 and 1895 (https://bbm.hypotheses.org). This model was trained in 2021 by Emmanuelle Perrin and Philippe Chassignet (project managers CNRS - Archéorient - UMR 5133, Lyon, France) with the participation of François Chagnot - Jean-Robert Grousset - Sylvie Grousset - Myriam Guillaumet - Isabelle Lagoutte - Marie-Hélène Lidec - Christine Pélardy Seignol - Bruno Ragon - Jean-Claude Seignol - Didier Vernet.

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Low error rate8.2% CER

Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 8.2% on its validation set. As a rule of thumb, a CER below 10% is considered good for most handwritten material. This is a larger model trained on diverse material, which generally makes it more robust across different handwriting styles. That said, larger training sets also make it harder to push the CER down further.

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.

Words146,466
Lines23,509
Training Pages790
Model ID48300
Centuries
19th c.