拼写纠正系列
java 实现中英文拼写检查和错误纠正?可我只会写 CRUD 啊!
单词拼写纠正-03-leetcode edit-distance 72.力扣编辑距离
NLP 开源项目
论文地址
可以参考:https://paperswithcode.com/task/chinese-spell-checking
论文梳理
Chinese Text Correction Papers
This repo aims to keep tracking related work in Chinese text correction, including Chinese Spell Checking (CSC) and Chinese Grammatical Error Correction (CGEC).
该仓库旨在跟踪与中文文本修正相关的工作,包括中文拼写检查(CSC)和中文语法错误修正(CGEC)。
2024
|paper|conference|resource|citation|labels| |:—:|:—:|:—:|:—:|:—:| |Chinese Spelling Correction as Rephrasing Language Model|AAAI2024|[pdf [code] |||
2023
|paper|conference|resource|citation|labels| |:—:|:—:|:—:|:—:|:—:| |A Frustratingly Easy Plug-and-Play Detection-and-Reasoning Module for Chinese Spelling Check|EMNLP2023|[pdf] [code] ||| |Disentangled Phonetic Representation for Chinese Spelling Correction|ACL2023|[pdf] [code] ||| |Rethinking Masked Language Modeling for Chinese Spelling Correction|ACL2023|[pdf] [code] ||| |PTCSpell: Pre-trained Corrector Based on Character Shape and Pinyin for Chinese Spelling Correction|ACL2023|[pdf]||| |Investigating Glyph-Phonetic Information for Chinese Spell Checking: What Works and What’s Next?|ACL2023|[pdf] [code] |-|| |Are Pre-trained Language Models Useful for Model Ensemble in Chinese Grammatical Error Correction?|ACL2023|[pdf] [code] |-|| |NaSGEC: a Multi-Domain Chinese Grammatical Error Correction Dataset from Native Speaker Texts|ACL2023|[pdf] [code] |||
2022
paper | conference | resource | citation | labels |
---|---|---|---|---|
Linguistic Rules-Based Corpus Generation for Native Chinese Grammatical Error Correction | EMNLP2022 | [pdf][code] | ||
FCGEC: Fine-Grained Corpus for Chinese Grammatical Error Correction | EMNLP2022 | [pdf][code] | ||
SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented Parser | EMNLP2022 | [pdf][code] | ||
Revisiting Grammatical Error Correction Evaluation and Beyond | EMNLP2022 | [pdf][code] | ||
From Spelling to Grammar: A New Framework for Chinese Grammatical Error Correction | EMNLP2022 | [pdf] | ||
Improving Chinese Spelling Check by Character Pronunciation Prediction: The Effects of Adaptivity and Granularity | EMNLP2022 | [pdf][code] | ||
Sequence-to-Action: Grammatical Error Correction with Action Guided Sequence Generation | AAAI2022 | [pdf] | ||
Non-Autoregressive Chinese ASR Error Correction with Phonological Training | NAACL2022 | [pdf] | ||
MuCGEC: a Multi-Reference Multi-Source Evaluation Dataset for Chinese Grammatical Error Correction | NAACL2022 | [pdf] [code] | ||
Improving Chinese Grammatical Error Detection via Data augmentation by Conditional Error Generation | ACL2022 | [pdf] | ||
CRASpell: A Contextual Typo Robust Approach to Improve Chinese Spelling Correction | ACL2022 | [pdf] [code] | ||
MDCSpell: A Multi-task Detector-Corrector Framework for Chinese Spelling Correction | ACL2022 | [pdf] | ||
The Past Mistake is the Future Wisdom: Error-driven Contrastive Probability Optimization for Chinese Spell Checking | ACL2022 | [pdf] |
2021
|paper|conference|resource|citation|labels| |:—:|:—:|:—:|:—:|:—:| |Correcting Chinese Spelling Errors with Phonetic Pre-training|ACL2021|[pdf] [code] ||| |Read, Listen, and See: Leveraging Multimodal Information Helps Chinese Spell Checking|ACL2021|[pdf] [code] ||| |PLOME: Pre-training with Misspelled Knowledge for Chinese Spelling Correction|ACL2021|[pdf] [code] ||| |Exploration and Exploitation: Two Ways to Improve Chinese Spelling Correction Models|ACL2021|[pdf] [code] ||| |PHMOSpell: Phonological and Morphological Knowledge Guided Chinese Spelling Check|ACL2021|[pdf] ||| |Global Attention Decoder for Chinese Spelling Error Correction|ACL2021|[pdf] ||| |Dynamic Connected Networks for Chinese Spelling Check|ACL2021|[pdf] ||| |Tail-to-Tail Non-Autoregressive Sequence Prediction for Chinese Grammatical Error Correction|ACL2021|[pdf] [code] ||| |SpellBERT: A Lightweight Pretrained Model for Chinese Spelling Check|EMNLP2021|[pdf] [code] ||| |DCSpell: A Detector-Corrector Framework for Chinese Spelling Error Correction|SIGIR2021|[pdf] ||| |Think Twice: A Post-Processing Approach for the Chinese Spelling Error Correction|AppliedScience|[pdf] |||
2020
|paper|conference|resource|citation|labels| |:—:|:—:|:—:|:—:|:—:| |Spelling Error Correction with Soft-Masked BERT|ACL2020|[pdf] ||| |Spellgcn: Incorporating phonological and visual similarities into language models for chinese spelling check|ACL2020|[pdf] [code] ||| |Chunk-based Chinese Spelling Check with Global Optimization|EMNLP2020|[pdf] ||| |MaskGEC: Improving Neural Grammatical Error Correction via Dynamic Masking|AAAL2020|[pdf] ||| |Combining ResNet and Transformer for Chinese Grammatical Error Diagnosis|AACL2020|[pdf] ||| |Overview of NLPTEA-2020 Shared Task for Chinese Grammatical Error Diagnosis|AACL2020|[pdf] || |
before
|paper|conference|resource|citation|labels| |:—:|:—:|:—:|:—:|:—:| |FASPell: A Fast, Adaptable, Simple, Powerful Chinese Spell Checker Based On DAE-Decoder Paradigm|EMNLP2019|[pdf] [code] ||| |A Hybrid Approach to Automatic Corpus Generation for Chinese Spelling Checking|EMNLP2018|[pdf] [code] || |
参考资料
https://github.com/nghuyong/Chinese-text-correction-papers/blob/main/Readme.md