@inproceedings{degraeuwe-saggion-2022-lexical,
title = "Lexical Simplification in Foreign Language Learning: Creating Pedagogically Suitable Simplified Example Sentences",
author = "Degraeuwe, Jasper and
Saggion, Horacio",
editor = "{\v{S}}tajner, Sanja and
Saggion, Horacio and
Ferr{\'e}s, Daniel and
Shardlow, Matthew and
Sheang, Kim Cheng and
North, Kai and
Zampieri, Marcos and
Xu, Wei",
booktitle = "Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Virtual)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.tsar-1.9",
doi = "10.18653/v1/2022.tsar-1.9",
pages = "98--110",
abstract = "This study presents a lexical simplification (LS) methodology for foreign language (FL) learning purposes, a barely explored area of automatic text simplification (TS). The method, targeted at Spanish as a foreign language (SFL), includes a customised complex word identification (CWI) classifier and generates substitutions based on masked language modelling. Performance is calculated on a custom dataset by means of a new, pedagogically-oriented evaluation. With 43{\%} of the top simplifications being found suitable, the method shows potential for simplifying sentences to be used in FL learning activities. The evaluation also suggests that, though still crucial, meaning preservation is not always a prerequisite for successful LS. To arrive at grammatically correct and more idiomatic simplifications, future research could study the integration of association measures based on co-occurrence data.",
}
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%0 Conference Proceedings
%T Lexical Simplification in Foreign Language Learning: Creating Pedagogically Suitable Simplified Example Sentences
%A Degraeuwe, Jasper
%A Saggion, Horacio
%Y Štajner, Sanja
%Y Saggion, Horacio
%Y Ferrés, Daniel
%Y Shardlow, Matthew
%Y Sheang, Kim Cheng
%Y North, Kai
%Y Zampieri, Marcos
%Y Xu, Wei
%S Proceedings of the Workshop on Text Simplification, Accessibility, and Readability (TSAR-2022)
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates (Virtual)
%F degraeuwe-saggion-2022-lexical
%X This study presents a lexical simplification (LS) methodology for foreign language (FL) learning purposes, a barely explored area of automatic text simplification (TS). The method, targeted at Spanish as a foreign language (SFL), includes a customised complex word identification (CWI) classifier and generates substitutions based on masked language modelling. Performance is calculated on a custom dataset by means of a new, pedagogically-oriented evaluation. With 43% of the top simplifications being found suitable, the method shows potential for simplifying sentences to be used in FL learning activities. The evaluation also suggests that, though still crucial, meaning preservation is not always a prerequisite for successful LS. To arrive at grammatically correct and more idiomatic simplifications, future research could study the integration of association measures based on co-occurrence data.
%R 10.18653/v1/2022.tsar-1.9
%U https://aclanthology.org/2022.tsar-1.9
%U https://doi.org/10.18653/v1/2022.tsar-1.9
%P 98-110
Markdown (Informal)
[Lexical Simplification in Foreign Language Learning: Creating Pedagogically Suitable Simplified Example Sentences](https://aclanthology.org/2022.tsar-1.9) (Degraeuwe & Saggion, TSAR 2022)
ACL