To analyse the great number of handwritten newsletters that circulated in early modernity and that have been preserved up today, the Euronews Project have combined different Digital Humanities techniques.

Handwritten Text Recognition (HTR) enables computers to transform images of handwritten documents into text. In recent years, it has become a well-known and widely used technology among digital humanists, historians, and archivists because of its potential to transform the scholarship and answer new research questions. Automatically transcribing digitalised archival sources makes the documents searchable, while the resulting transcriptions can be analysed applying text analysis methods. Within the Euronews Project, we are experimenting with HTR on a corpus of ten volumes of letters and newsletters written in Italian by three different hands. The variety of hands and languages is one of the main challenges in training a satisfactory HTR model. After several months of training, we have achieved a 94% accurate model, which means that 94 out of 100 automatically transcribed characters are correct. We will further our research in this field and train a model capable of transcribing more hands with increasing accuracy in order to apply HTR to all newsletters that have been digitalised but not yet transcribed due to time constraints.

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