Lexical Simplification Using Word Embedding to Approximate Word Sense

Abstract

Authentic English passages are not always appropriate for learners due to their vocabulary level; hence teachers sometimes have to modify the text by making sentences simpler or replacing difficult words with easier ones. This process, however, takes time and could be a burden for teachers. The present study aims to build an automatic lexical simplification system that can assist teachers in preparing materials for classes and examinations. The proposed system first selects target words based on CEFR levels and then lists candidates from a thesaurus. Then, the paraphrasablity of each candidate is examined using a word embedding method. The results show that the proposed method can provide correct candidates for more cases than the baseline and existing methods and is robust even when the target is a polysemous word.