OCR and post-correction of historical Finnish texts
Senka Drobac, Pekka Kauppinen, Krister Lindén · DSpace repository (University of Tartu) · 2017
This paper presents experiments on Optical character recognition (OCR) as a combination of Ocropy software and data-driven spelling correction that uses Weighted Finite-State Methods.Both model training and testing were done on Finnish corpora of historical newspaper text and the best combination of OCR and post-processing models give 95.21% character recognition accuracy.