Active OCR: Tightening the Loop in Human Computing for OCR Correction

FAIN: HD-51568-12

University of Maryland, College Park (College Park, MD 20742-5141)
Travis Robert Brown (Project Director: October 2011 to November 2014)

The development of a proof-of-concept correction tool to improve optical character recognition in humanities text collections.

We propose a proof-of-concept application that will experiment with the use of active learning and other iterative techniques for the correction of eighteenth-century texts provided by the HathiTrust Digital Library and the 2,231 ECCO text transcriptions released into the public domain by Gale and distributed by the Text Creation Partnership (TCP) and 18thConnect. In an application based on active learning or a similar approach, the user could identify dozens or hundreds of difficult characters that appear in the articles from that same time period, and the system would use this new knowledge to improve optical character recognition (OCR) across the entire corpus. A portion of our efforts will focus on the need to incentivize engagement in tasks of this type, whether they are traditionally crowdsourced or through a more active, iterative process like the one we propose. We intend to examine how explorations of a users' preferences can improve their engagement with corpora of materials.