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Strategies for reducing and correcting OCR error

Publikationsart Peer-reviewed
Publikationsform Buchbeitrag (peer-reviewed)
Autor/in Volk Martin, Furrer Lenz, Sennrich Rico,
Projekt Domain-specific Statistical Machine Translation
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Buchbeitrag (peer-reviewed)

Buch Language Technology for Cultural Heritage
Herausgeber/in , Zervanou Kalliopi; , Sporleder Caroline; , van den Bosch Antal
Verlag Springer, Berlin
Seite(n) 3 - 22
ISBN 978-3-642-20226-1
Titel der Proceedings Language Technology for Cultural Heritage


In this paper we describe our efforts in reducing and correcting OCR errors in the context of building a large multilingual heritage corpus of Alpine texts which is based on digitizing the publications of various Alpine clubs. We have already digitized the yearbooks of the Swiss Alpine Club from its start in 1864 until 1995 with more than 75,000 pages resulting in 29 million running words. Since these books have come out continuously, they represent a unique basis for historical, cultural and linguistic research. We used commercial OCR systems for the conversion from the scanned images to searchable text. This poses several challenges. For example, the built-in lexicons of the OCR systems do not cover the 19th century German spelling, the Swiss German spelling variants and the plethora of toponyms that are characteristic of our text genre. We also realized that different OCR systems make different recognition errors. We therefore run two OCR systems over all our scanned pages and merge the output. Merging is especially tricky at spots where both systems result in partially correct word groups. We describe our strategies for reducing OCR errors by enlarging the systems? lexicons and by two post-correction methods namely, merging the output of two OCR systems and auto- correction based on additional lexical resources.