Automatic quality evaluation and (semi-) automatic improvement of OCR models for historical printings

U. Springmann, F. Fink, K. U. Schulz

Good OCR results for historical printings rely on the availability of recognition models trained on diplomatic transcriptions as ground truth, which is both a scarce resource and t…