Japanese Lexical Complexity for Non-Native Readers: A New Dataset

Yusuke Ide, Masato Mita, Adam Nohejl, Hiroki Ouchi, Taro Watanabe
6/30/2023
cs.CL

No official code found. Best implementation: naist-nlp/jalecon (6 stars, last commit 2023-07-04).

Abstract

Lexical complexity prediction (LCP) is the task of predicting the complexity of words in a text on a continuous scale. It plays a vital role in simplifying or annotating complex words to assist readers. To study lexical complexity in Japanese, we construct the first Japanese LCP dataset. Our dataset provides separate complexity scores for Chinese/Korean annotators and others to address the readers' L1-specific needs. In the baseline experiment, we demonstrate the effectiveness of a BERT-based system for Japanese LCP.

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A Dataset of Japanese Lexical Complexity for Non-Native Readers

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Cite this paper

@article{ide2023japanese,
  title  = {Japanese Lexical Complexity for Non-Native Readers: A New Dataset},
  author = {Yusuke Ide and Masato Mita and Adam Nohejl and Hiroki Ouchi and Taro Watanabe},
  year   = {2023},
  eprint = {2306.17399},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.17399v1}
}

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