Papers with Chinese spelling check
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. |
Chunk-based Chinese Spelling Check with Global Optimization (2020.findings-emnlp)
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| Challenge: | Chinese spelling check is a challenging task due to the characteristics of the language . previous studies only consider corrections with similar character pronunciation or shape . |
| Approach: | They propose a chunk-based framework to correct single-character and multi-character word errors uniformly. |
| Outcome: | The proposed framework achieves state-of-the-art performance on three benchmark datasets and optical character recognition datasets. |
Dynamic Connected Networks for Chinese Spelling Check (2021.findings-acl)
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| Challenge: | Chinese spelling check (CSC) is a task to detect and correct spelling errors in Chinese text. |
| Approach: | They propose a new architecture which generates Chinese characters via a Pinyin Enhanced Candidate Generator and then utilizes an attention-based network to model the dependencies between two adjacent Chinese characters. |
| Outcome: | The proposed method achieves state-of-the-art performance on three human-annotated datasets. |
A Hybrid Approach to Automatic Corpus Generation for Chinese Spelling Check (D18-1)
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| Challenge: | Chinese spelling check (CSC) is a challenging but meaningful task that serves as a preprocessing in many natural language processing(NLP) applications. |
| Approach: | They propose to construct Chinese spelling check corpus with automatically generated spelling errors, which are either visually or phonologically resembled characters, corresponding to OCR- and ASR-based methods. Experimental results demonstrate the effectiveness of the approach. |
| Outcome: | The proposed method is based on visual or phonologically similar spelling errors, and is validated with respect to three standard test sets. |
Improving Chinese Spelling Check by Character Pronunciation Prediction: The Effects of Adaptivity and Granularity (2022.emnlp-main)
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| Challenge: | Chinese spelling check (CSC) is a fundamental NLP task that detects and corrects spelling errors in Chinese texts. |
| Approach: | They propose an auxiliary task of Chinese pronunciation prediction to improve CSC . they propose adaptive weighting schemes and a delicate correction strategy . |
| Outcome: | The proposed auxiliary task improves Chinese pronunciation prediction on three benchmarks. |
CCTC: A Cross-Sentence Chinese Text Correction Dataset for Native Speakers (2022.coling-1)
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| Challenge: | Chinese text correction datasets focus on detecting and correcting Chinese spelling errors and grammatical errors. |
| Approach: | They propose a Chinese text correction dataset for native speakers . they manually annotated 1,500 Chinese texts written by native speakers. |
| Outcome: | The proposed dataset can detect and correct Chinese spelling errors and grammatical errors. |
Retrieval-Augmented Generation for Large Language Model based Few-shot Chinese Spell Checking (2025.coling-main)
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| Challenge: | Existing LLM-based Chinese spelling check methods rely on fixed prompt samples . existing methods are limited by technical bottlenecks, complex recognition environments, and individual differences . |
| Approach: | They propose a framework called RagID to provide well-chosen prompt samples . they propose to use semantic-based similarity search and iterative discriminator mechanism . |
| Outcome: | The proposed framework can provide well-chosen prompt samples and reduce overcorrection issues in Chinese spelling check tasks. |
DISC: Plug-and-Play Decoding Intervention with Similarity of Characters for Chinese Spelling Check (2025.acl-long)
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Ziheng Qiao, Houquan Zhou, Yumeng Liu, Zhenghua Li, Min Zhang, Bo Zhang, Chen Li, Ji Zhang, Fei Huang
| Challenge: | Chinese spelling check (CSC) tasks require that incorrect characters are usually similar to the correct ones in either phonetics or glyph. |
| Approach: | They propose a plug-and-play decoding intervention with similarity of characters module for Chinese spelling check (CSC) they propose to incorporate phonetic and glyph similarities only during the inference phase. |
| Outcome: | The proposed method significantly improves Chinese spelling check models on benchmarks and on benchmark datasets. |