Stefan Karcher, a graduate student at Heidelberg University has written a fascinating blog post explaining how he has been using Transkribus to process nineteenth-century German sermons.
Karcher took the opportunity to train his own Automated Text Recognition models. He used around 30,000 transcribed words of training data to generate a model that can produce transcripts of his documents with a Character Error Rate of 8-10%. The blog post notes that these transcripts are a useful and efficient basis for his research and includes a description of how these automated transcripts can be analysed with Voyant Tools.
Do you want to train your own Automated Text Recognition model?
Leverage the power of Transkribus to get the most out of your historical documents.