
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.