Towards Single Word Lexical Complexity Prediction

David Alfter, Elena Volodina


Abstract
In this paper we present work-in-progress where we investigate the usefulness of previously created word lists to the task of single-word lexical complexity analysis and prediction of the complexity level for learners of Swedish as a second language. The word lists used map each word to a single CEFR level, and the task consists of predicting CEFR levels for unseen words. In contrast to previous work on word-level lexical complexity, we experiment with topics as additional features and show that linking words to topics significantly increases accuracy of classification.
Anthology ID:
W18-0508
Volume:
Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venue:
BEA
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
79–88
Language:
URL:
https://aclanthology.org/W18-0508
DOI:
10.18653/v1/W18-0508
Bibkey:
Cite (ACL):
David Alfter and Elena Volodina. 2018. Towards Single Word Lexical Complexity Prediction. In Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 79–88, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
Towards Single Word Lexical Complexity Prediction (Alfter & Volodina, BEA 2018)
Copy Citation:
PDF:
https://preview.aclanthology.org/author-url/W18-0508.pdf