William Hey (1736 – 1819) was an English surgeon who worked at Leeds General Infirmary, served as mayor of Leeds and as president of the Leeds Philosophical and Literary Society.
The team in Special Collections at the library of the University of Leeds (one of the READ project MOU partners) are interested in creating digital transcriptions of the writings of this notable local figure.
They have transcribed around 15,000 words from Hey’s medical casebooks in our Transkribus platform and used this data to train two Automated Text Recognition models to recognise Hey’s writing.
The first model was trained solely on the Hey papers, the second model included the pre-exisiting ‘English Writing M1’ model as part of the training process. The ‘English Writing M1’ model is trained to recognise the writing of the English philosopher Jeremy Bentham (1748 – 1832) and his secretaries – it is freely available to all Transkribus users for their experiments.
The results were very good, reflecting both the relative simplicity of Hey’s handwriting and the amount of training data for eighteenth-century English writing that has already been submitted in Transkribus by various other research and archival teams.
The best results for the automated recognition of Hey’s writing came with the latter model – it can produce transcripts of papers written by Hey with a Character Error Rate (CER) of just 8%. This means that more than 90% of the characters are transcribed correctly by the software – and this is a very good starting point for manually correcting and improving the quality of these transcripts with a view to making them available to archival users. The Special Collections team also hope to improve the accuracy of their model by transcribing more words of training data.
To find out how to prepare training data for Automated Text Recognition and train your own model in Transkribus, take a look at our How to Guides: