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EMNLP Findings2024

Bi-DCSpell: A Bi-directional Detector-Corrector Interactive Framework for Chinese Spelling Check

Haiming Wu, Hanqing Zhang, Richeng Xuan, Dawei Song

摘要

Chinese Spelling Check (CSC) aims to detect and correct potentially misspelled characters in Chinese sentences. Naturally, it involves the detection and correction subtasks, which interact with each other dynamically. Such interactions are bi-directional, i.e., the detection result would help reduce the risk of over-correction and under-correction while the knowledge learnt from correction would help prevent false detection. Current CSC approaches are of two types: correction-only or single-directional detection-to-correction interactive frameworks. Nonetheless, they overlook the bi-directional interactions between detection and correction. This paper aims to fill the gap by proposing a Bi-directional Detector-Corrector framework for CSC (Bi-DCSpell). Notably, Bi-DCSpell contains separate detection and correction encoders, followed by a novel interactive learning module facilitating bi-directional feature interactions between detection and correction to improve each other's representation learning. Extensive experimental results demonstrate a robust correction performance of Bi-DCSpell on widely used benchmarking datasets while possessing a satisfactory detection ability.

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它引用的 Paper12

  1. Spelling Error Correction with Soft-Masked BERTShaohua Zhang, Haoran Huang, Jicong Liu, Hang LiACL 2020 · 204 次引用
  2. SpellGCN: Incorporating Phonological and Visual Similarities into Language Models for Chinese Spelling CheckXingyi Cheng, Weidi Xu, Kunlong Chen, Shaohua Jiang 等ACL 2020 · 139 次引用
  3. Read, Listen, and See: Leveraging Multimodal Information Helps Chinese Spell CheckingHeng-Da Xu, Zhongli Li, Qingyu Zhou, Chao Li 等ACL Findings 2021 · 91 次引用
  4. Correcting Chinese Spelling Errors with Phonetic Pre-trainingRuiqing Zhang, Chao Pang, Chuanqiang Zhang, Shuohuan Wang 等ACL Findings 2021 · 67 次引用
  5. Dynamic Connected Networks for Chinese Spelling CheckBaoxin Wang, Wanxiang Che, Dayong Wu, Shijin Wang 等ACL Findings 2021 · 55 次引用

相关 Paper

  1. UMRSpell: Unifying the Detection and Correction Parts of Pre-trained Models towards Chinese Missing, Redundant, and Spelling CorrectionZheyu He, Yujin Zhu, Linlin Wang, Liang XuACL 2023 · 8 次引用
  2. MDCSpell: A Multi-task Detector-Corrector Framework for Chinese Spelling CorrectionChenxi Zhu, Ziqiang Ying, Boyu Zhang, Feng MaoACL Findings 2022 · 39 次引用
  3. PTCSpell: Pre-trained Corrector Based on Character Shape and Pinyin for Chinese Spelling CorrectionXiao Wei, Jianbao Huang, Hang Yu, Qian LiuACL Findings 2023 · 11 次引用
  4. PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling CorrectionShulin Liu, Tao Yang, Tianchi Yue, Feng Zhang 等ACL 2021
  5. Disentangled Phonetic Representation for Chinese Spelling CorrectionZihong Liang, Xiaojun Quan, Qifan WangACL 2023 · 12 次引用
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