@inproceedings{aleksandrova-pouliot-2023-cefr,
title = "{CEFR}-based Contextual Lexical Complexity Classifier in {E}nglish and {F}rench",
author = "Aleksandrova, Desislava and
Pouliot, Vincent",
editor = {Kochmar, Ekaterina and
Burstein, Jill and
Horbach, Andrea and
Laarmann-Quante, Ronja and
Madnani, Nitin and
Tack, Ana{\"\i}s and
Yaneva, Victoria and
Yuan, Zheng and
Zesch, Torsten},
booktitle = "Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.bea-1.43",
doi = "10.18653/v1/2023.bea-1.43",
pages = "518--527",
abstract = "This paper describes a CEFR-based classifier of single-word and multi-word lexical complexity in context from a second language learner perspective in English and in French, developed as an analytical tool for the pedagogical team of the language learning application Mauril. We provide an overview of the required corpora and the way we transformed it into rich contextual representations that allow the disambiguation and accurate labelling in context of polysemous occurrences of a given lexical item. We report evaluation results for all models, including two multi-lingual lexical classifiers evaluated on novel French datasets created for this experiment. Finally, we share the perspective of Mauril{'}s pedagogical team on the limitations of such systems.",
}
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%0 Conference Proceedings
%T CEFR-based Contextual Lexical Complexity Classifier in English and French
%A Aleksandrova, Desislava
%A Pouliot, Vincent
%Y Kochmar, Ekaterina
%Y Burstein, Jill
%Y Horbach, Andrea
%Y Laarmann-Quante, Ronja
%Y Madnani, Nitin
%Y Tack, Anaïs
%Y Yaneva, Victoria
%Y Yuan, Zheng
%Y Zesch, Torsten
%S Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F aleksandrova-pouliot-2023-cefr
%X This paper describes a CEFR-based classifier of single-word and multi-word lexical complexity in context from a second language learner perspective in English and in French, developed as an analytical tool for the pedagogical team of the language learning application Mauril. We provide an overview of the required corpora and the way we transformed it into rich contextual representations that allow the disambiguation and accurate labelling in context of polysemous occurrences of a given lexical item. We report evaluation results for all models, including two multi-lingual lexical classifiers evaluated on novel French datasets created for this experiment. Finally, we share the perspective of Mauril’s pedagogical team on the limitations of such systems.
%R 10.18653/v1/2023.bea-1.43
%U https://aclanthology.org/2023.bea-1.43
%U https://doi.org/10.18653/v1/2023.bea-1.43
%P 518-527
Markdown (Informal)
[CEFR-based Contextual Lexical Complexity Classifier in English and French](https://aclanthology.org/2023.bea-1.43) (Aleksandrova & Pouliot, BEA 2023)
ACL