@inproceedings{81f9481f4cc74e0f98847bdf8a55b385,
title = "Read, Listen, and See: Leveraging Multimodal Information Helps Chinese Spell Checking",
abstract = "Chinese Spell Checking (CSC) aims to detect and correct erroneous characters for user-generated text in Chinese language. Most of the Chinese spelling errors are misused semantically, phonetically or graphically similar characters. Previous attempts notice this phenomenon and try to utilize the similarity relationship for this task. However, these methods use either heuristics or handcrafted confusion sets to predict the correct character. In this paper, we propose a Chinese spell checker called REALISE, by directly leveraging the multimodal information of the Chinese characters. The REALISE model tackles the CSC task by (1) capturing the semantic, phonetic and graphic information of the input characters, and (2) selectively mixing the information in these modalities to predict the correct output. Experiments on the SIGHAN benchmarks show that the proposed model outperforms strong baselines by a large margin.",
author = "Xu, {Heng Da} and Zhongli Li and Qingyu Zhou and Chao Li and Zizhen Wang and Yunbo Cao and Heyan Huang and Mao, {Xian Ling}",
note = "Publisher Copyright: {\textcopyright} 2021 Association for Computational Linguistics; Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 ; Conference date: 01-08-2021 Through 06-08-2021",
year = "2021",
language = "English",
series = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
publisher = "Association for Computational Linguistics (ACL)",
pages = "716--728",
editor = "Chengqing Zong and Fei Xia and Wenjie Li and Roberto Navigli",
booktitle = "Findings of the Association for Computational Linguistics",
address = "United States",
}