TU Darmstadt · PyLaia · Published December 3, 2020
DAT 18. Jh M3b_Pylaia
Text Recognition
Description
19th century newspaper. Fraktur.
130 pages OCR correction and proofing.
Print style for umlaut varies throughout (superscript "e" vs öäü).
Since no applicable Pylaia model was available for training,
the training set includes the HTR model data for DAT 18. Jh M1 and M2.
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Use this modelOpen in Transkribus
Very low error rate0.3% CER
Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 0.3% 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.
Words102,875
Lines17,029
Training Pages253
Model ID28419