Natural Language Processing for Teaching Ancient Languages
Konstantin Schulz shows various applications of natural language processing (NLP) to the field of Classics, especially to Latin texts. He addresses different levels of linguistic analysis while also highlighting educational benefits and important theoretical pitfalls, especially in vocabulary learning. NLP can solve some problems reasonably well, like tailoring exercises to the learners' current state of knowledge. However, some tasks still prove to be too difficult for machines at the moment, e.g. reliable and highly accurate parsing of syntax for historical languages.
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Natural Language Processing for Teaching Ancient Languages
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- Faculty of Arts and Humanities; Department of History; Didactics of History
- University of Cologne; Departement of History; Department of Didactics of History and Public History
- University of Potsdam; Faculty of Philosophy; Chair of Classical Philology
- University of Murcia; Faculty of Education; Department of Didactics of Mathematics and Social Sciences
- Social Sciences Education Research Group (PHZH)
- Information for readers and authors
- Kiel University Publishing
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