Handwritten Text Recognition

Artificial intelligence transforms discoverability of handwritten manuscripts.

Handwritten Text Recognition is going to transform scholarship and the types of questions researchers can ask. The technology has tremendous potential.
Dr Patrick Spero, Director, American Philosophical Society Library

Adam Matthew Digital is the first publisher to utilise artificial intelligence to offer Handwritten Text Recognition (HTR) for its handwritten manuscript collections.

The HTR application takes advantage of the latest advances in neural networks and uses complex algorithms to determine probable combinations of characters to find the search term.

This enables relevant handwritten text to be identified at document level with automated searches deployed through the metadata, allowing users to easily navigate between highlighted search results.

Handwritten Text Recognition (HTR) has now been enhanced to provide editable, fully searchable transcriptions of handwritten assets, generated in-platform with a single click. 

HTR Transcriptions are displayed alongside the original asset, and provide an additional source of data for your users to search, extending the discoverability of your collections and allowing users to explore much more deeply, adding depth and scope to their research.

Discover more about HTR Transcriptions at quartexcollections.com

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Discover more about Handwritten Text Recognition:

  • The Impact of Handwritten Text Recognition (HTR)

  • Making Handwritten Text Recognition Work For You


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