Senka Drobac
Department of Modern Languages, University of Helsinki, Finland
Pekka Kauppinen
Department of Modern Languages, University of Helsinki, Finland
Krister Lindén
Department of Modern Languages, University of Helsinki, Finland
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Published in: Proceedings of the 21st Nordic Conference on Computational Linguistics, NoDaLiDa, 22-24 May 2017, Gothenburg, Sweden
Linköping Electronic Conference Proceedings 131:9, p. 70-76
NEALT Proceedings Series 29:9, p. 70-76
Published: 2017-05-08
ISBN: 978-91-7685-601-7
ISSN: 1650-3686 (print), 1650-3740 (online)
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.
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