Chinese word usage errors often occur in non-native Chinese learners' writing. It is very helpful for non-native Chinese learners to detect them automatically when learning writing. In this paper, we propose a novel approach, which takes advantages of different auxiliary tasks, such as POS-tagging prediction and word log frequency prediction, to help the task of Chinese word usage error detection. With the help of these auxiliary tasks, we achieve the state-of-the-art results on the performances on the HSK corpus data, without any other extra data.
@article{arxiv.1904.01783,
title = {Multi-task Learning for Chinese Word Usage Errors Detection},
author = {Jinbin Zhang and Heng Wang},
journal= {arXiv preprint arXiv:1904.01783},
year = {2019}
}
Comments
4 pages, 2 figures, 1 table, has been accepted as a conference paper of the 3rd IEEE International Conference on Computational Intelligence and Applications (ICCIA 2018)