Natural Language Processing for Teaching Ancient Languages. Schulz, K. In Teaching Classics in the Digital Age, pages 37–48, August, 2021.
Paper doi abstract bibtex 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.
@inproceedings{schulz_natural_2021,
title = {Natural {Language} {Processing} for {Teaching} {Ancient} {Languages}},
copyright = {https://creativecommons.org/licenses/by-sa/4.0/},
isbn = {978-3-928794-61-9},
url = {https://macau.uni-kiel.de/receive/macau_mods_00001368},
doi = {10.38072/2703-0784/p19},
abstract = {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.},
language = {en},
urldate = {2021-08-17},
booktitle = {Teaching {Classics} in the {Digital} {Age}},
author = {Schulz, Konstantin},
month = aug,
year = {2021},
keywords = {scientific},
pages = {37--48},
}
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