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Talking About Muslims in Middle French: The Potential of Word-to-Vector Models for Studying Semantic Relationships in Medieval Languages

by Kimberly Lifton

Medieval vernaculars are notoriously tricky for digital humanists to work with because they lack standardized spelling. Especially when using out-of-the-box libraries and software, most Natural Language Processing (NLP) techniques simply do not work well for medieval languages. However, word-to-vector models have the capacity to handle noise like spelling variants when trained on a significant number of words. As part of my PhD project, which examines the representations of Muslims in textual sources during the rise of the Ottomans in the fifteenth century, I have created custom word-to-vector models using Middle French texts. These models capture the constellations of Muslim representations in Middle French texts at the word level. My methodology considers the exploratory potential of word-to-vector models for shaping research questions in a process that Gabor Mihaly Toth has aptly described as “semantic wanderings.”1
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  1. Gabor Mihaly Toth, “Women in Early Modern Handwritten News: Random Walks and Semantic Wandering in the Medici Archive,” Journal of Digital History 3.2 (2024). https://journalofdigitalhistory.org/en/article/jnkqqTTKW8km []