A Tool for Facilitating OCR Postediting in Historical Documents

Alberto Poncelas, Mohammad Aboomar, Jan Buts, James Hadley, Andy Way


Abstract
Optical character recognition (OCR) for historical documents is a complex procedure subject to a unique set of material issues, including inconsistencies in typefaces and low quality scanning. Consequently, even the most sophisticated OCR engines produce errors. This paper reports on a tool built for postediting the output of Tesseract, more specifically for correcting common errors in digitized historical documents. The proposed tool suggests alternatives for word forms not found in a specified vocabulary. The assumed error is replaced by a presumably correct alternative in the post-edition based on the scores of a Language Model (LM). The tool is tested on a chapter of the book An Essay Towards Regulating the Trade and Employing the Poor of this Kingdom (Cary, 1719). As demonstrated below, the tool is successful in correcting a number of common errors. If sometimes unreliable, it is also transparent and subject to human intervention.
Anthology ID:
2020.lt4hala-1.7
Volume:
Proceedings of LT4HALA 2020 - 1st Workshop on Language Technologies for Historical and Ancient Languages
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Rachele Sprugnoli, Marco Passarotti
Venue:
LT4HALA
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
47–51
Language:
English
URL:
https://aclanthology.org/2020.lt4hala-1.7
DOI:
Bibkey:
Cite (ACL):
Alberto Poncelas, Mohammad Aboomar, Jan Buts, James Hadley, and Andy Way. 2020. A Tool for Facilitating OCR Postediting in Historical Documents. In Proceedings of LT4HALA 2020 - 1st Workshop on Language Technologies for Historical and Ancient Languages, pages 47–51, Marseille, France. European Language Resources Association (ELRA).
Cite (Informal):
A Tool for Facilitating OCR Postediting in Historical Documents (Poncelas et al., LT4HALA 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lt4hala-1.7.pdf
Code
 alberto-poncelas/tesseract_postprocess