Papers with SIGHAN14
Two Issues with Chinese Spelling Correction and A Refinement Solution (2024.acl-short)
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| Challenge: | Existing models contain many spelling errors, resulting in performance bottlenecks and performance issues. |
| Approach: | They propose to fix the SIGHAN datasets and re-evaluate four representative Chinese Spelling Correction models using the fixed datasets. |
| Outcome: | The proposed model improves the models in all metrics by notable margins. |
WSpeller: Robust Word Segmentation for Enhancing Chinese Spelling Check (2022.findings-emnlp)
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| Challenge: | Chinese spelling check (CSC) detects and corrects spelling errors in Chinese texts. |
| Approach: | They propose a Chinese spelling check model that takes into account word segmentation and a module that can assist the correction module by predicting correct word segmentations from sentences containing spelling errors. |
| Outcome: | The proposed model outperforms baselines on SIGHAN13, SIGHEN14, and SIGHAN15 and maintains equal performance on SSGHAN14. |