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Using Automated Text Recognition (ATR) to uncover and conserve hidden indigenous voices
Hear from Wiley publishers on how AI technology is transforming access to primary source research, the impact on research and the role libraries play. Examples will be drawn from the recently completed digitisation of the RAI archive.
Our speakers are excited to share the ways in which ATR will transform digital research by supporting unprecedented efficiency, enhanced reach and search results, and access to unique manuscript content, enabling focus on insightful rather than time-consuming work.
Primary source materials and digital archives fundamentally change traditional research, providing researchers the opportunity to view and expand upon historical context, documents, and materials through access to images of manuscripts, reports, drawings, maps, photographs, periodicals, and more.
Automated Text Recognition (ATR) is an AI-driven image recognition program that analyses handwritten documents, runs the images against a variety of datasets to determine the best match, then attempts to recognize words within these handwritten documents.
This breakthrough AI dedicated to manuscript exploration accelerates research work, making handwritten content fully discoverable via search, and turning handwriting into easily readable typeset that can be seamlessly utilized for data analysis, quoted, and cited.
The implementation of ATR will transform the nature of manuscript research and open the field to new researchers struggling with the requirements and skillset needed for intensive manuscript reading.
Through ATR, manuscripts and printed materials will come close to parity in their discoverability for the first time.
Ray Abruzzi: Publisher, Wiley Digital Archives
Simon Bell, Associate Publisher, Wiley Digital Archives