UConn Library, School of Engineering to Expand Handwritten Text Recognition
From UConn Today:
The UConn Library and the School of Engineering are working to develop new technology that applies machine learning to handwriting text recognition that will allow researchers to have improved access to handwritten historic documents.
Handwritten documents are essential for researchers, but are often inaccessible because they are unable to be searched even after they are digitized. The Connecticut Digital Archive, a project of the UConn Library, is working to change that with a $24,277 grant awarded through the Catalyst Fund of LYRASIS, a nonprofit organization that supports access to academic, scientific, and cultural heritage.
Archives and special collections from across Connecticut fill the Connecticut Digital Archive (CTDA), providing online access to a treasure of historic materials. However, the irregularity in the handwriting in many of the manuscripts leaves the historical information in these documents inaccessible to Optical Character Recognition (OCR), a transfer method used for more than 20 years to assist in document discoverability.
About Gary Price
Gary Price (firstname.lastname@example.org) is a librarian, writer, consultant, and frequent conference speaker based in the Washington D.C. metro area. He earned his MLIS degree from Wayne State University in Detroit. Price has won several awards including the SLA Innovations in Technology Award and Alumnus of the Year from the Wayne St. University Library and Information Science Program. From 2006-2009 he was Director of Online Information Services at Ask.com. Gary is also the co-founder of infoDJ an innovation research consultancy supporting corporate product and business model teams with just-in-time fact and insight finding.