{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T14:04:52Z","timestamp":1761314692351,"version":"build-2065373602"},"reference-count":29,"publisher":"Association for Computing Machinery (ACM)","issue":"11","funder":[{"name":"Yunnan Fundamental Research Projects","award":["202401CF070121, 202401BC070021, and 202301AS070047"],"award-info":[{"award-number":["202401CF070121, 202401BC070021, and 202301AS070047"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62306129, U21B2027, 62366027, and 62266028"],"award-info":[{"award-number":["62306129, U21B2027, 62366027, and 62266028"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Yunnan Provincial Major Science and Technology Special Plan Projects","award":["202103AA080015, 202202AD080003, and 202203AA080004"],"award-info":[{"award-number":["202103AA080015, 202202AD080003, and 202203AA080004"]}]},{"name":"Kunming University of Science and Technology \u201cDouble First-rate\u201d Construction Joint Project","award":["202301BE070001-027, 202201BE070001-021"],"award-info":[{"award-number":["202301BE070001-027, 202201BE070001-021"]}]},{"name":"Yunnan High and New Technology Industry Project","award":["201606"],"award-info":[{"award-number":["201606"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2025,11,30]]},"abstract":"<jats:p>\n                    Due to the strong representation capability of pre-trained language models, Chinese spelling correction models have significantly improved. However, pre-trained language models focus on contextualized information and treat all words equally, thus ignoring the entity information. In practical application, entity words are the most difficult part to handle in various artificial intelligence tasks, i.e., machine translation, optical character recognition, and automatic speech recognition. To address this issue, we first construct an entity-focused Chinese spelling correction (EFCSC) dataset , the first public spelling correction corpus to emphasize entity errors. Furthermore, we propose an entity knowledge injected language model (EKILM) designed for entity-focused spelling correction, which injects entity information into pre-trained language models, thus ensuring traditional spelling correction models pay more attention to entity words. Experiments on several benchmark datasets show that our proposed model outperforms all strong baseline models, leading to state-of-the-art results on all datasets. Extensive experiments and detailed analyses demonstrate that our proposed model enhances entity error correction ability without damaging the normal spelling correction performance. Our code and dataset will be released at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/DPloved\/EFCSC\">https:\/\/github.com\/DPloved\/EFCSC<\/jats:ext-link>\n                    to facilitate future research.\n                  <\/jats:p>","DOI":"10.1145\/3765761","type":"journal-article","created":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T11:04:53Z","timestamp":1756983893000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Entity-focused Chinese Spelling Correction: Dataset and Approach"],"prefix":"10.1145","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-2885-5034","authenticated-orcid":false,"given":"Xiao","family":"Liu","sequence":"first","affiliation":[{"name":"Faculty of Information Engineering and Automation Kunming, Kunming University of Science and Technology","place":["Kunming, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8912-6458","authenticated-orcid":false,"given":"Shichang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation Kunming, Kunming University of Science and Technology","place":["Kunming, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8586-9980","authenticated-orcid":false,"given":"Ying","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation Kunming, Kunming University of Science and Technology","place":["Kunming, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4170-2566","authenticated-orcid":false,"given":"Xin","family":"Chen","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation Kunming, Kunming University of Science and Technology","place":["Kunming, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6411-4734","authenticated-orcid":false,"given":"Zhengtao","family":"Yu","sequence":"additional","affiliation":[{"name":"Faculty of Information Engineering and Automation, Kunming University of Science and Technology","place":["Kunming, China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2025,10,24]]},"reference":[{"key":"e_1_3_2_2_2","first-page":"871","volume-title":"Proceedings of the ACL","author":"Cheng Xingyi","year":"2020","unstructured":"Xingyi Cheng, Weidi Xu, Kunlong Chen, Shaohua Jiang, Feng Wang, Taifeng Wang, Wei Chu, and Yuan Qi. 2020. SpellGCN: Incorporating phonological and visual similarities into language models for chinese spelling check. In Proceedings of the ACL. 871\u2013881."},{"key":"e_1_3_2_3_2","first-page":"7887","volume-title":"Proceedings of the ICASSP","author":"Das Nilaksh","year":"2022","unstructured":"Nilaksh Das, Duen Horng Chau, Monica Sunkara, Sravan Bodapati, Dhanush Bekal, and Katrin Kirchhoff. 2022. Listen, know and spell: Knowledge-infused subword modeling for improving ASR performance of OOV named entities. In Proceedings of the ICASSP. 7887\u20137891."},{"key":"e_1_3_2_4_2","first-page":"4171","volume-title":"Proceedings of the NAACL","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of deep bidirectional transformers for language understanding. In Proceedings of the NAACL. 4171\u20134186."},{"key":"e_1_3_2_5_2","first-page":"2363","volume-title":"Proceedings of the ACL","author":"Dong Rui","year":"2018","unstructured":"Rui Dong and David Smith. 2018. Multi-input attention for unsupervised OCR correction. In Proceedings of the ACL. 2363\u20132372."},{"key":"e_1_3_2_6_2","first-page":"11514","volume-title":"Proceedings of the EMNLP Findings","author":"Huang Haojing","year":"2023","unstructured":"Haojing Huang, Jingheng Ye, Qingyu Zhou, Yinghui Li, Yangning Li, Feng Zhou, and Hai-Tao Zheng. 2023. A frustratingly easy plug-and-play detection-and-reasoning module for Chinese spelling check. In Proceedings of the EMNLP Findings. 11514\u201311525."},{"key":"e_1_3_2_7_2","first-page":"5958","volume-title":"Proceedings of the ACL","author":"Huang Li","year":"2021","unstructured":"Li Huang, Junjie Li, Weiwei Jiang, Zhiyu Zhang, Minchuan Chen, Shaojun Wang, and Jing Xiao. 2021. PHMOSpell: Phonological and morphological knowledge guided Chinese spelling check. In Proceedings of the ACL. 5958\u20135967."},{"key":"e_1_3_2_8_2","first-page":"3544","volume-title":"Proceedings of the EMNLP","author":"Ji Tuo","year":"2021","unstructured":"Tuo Ji, Hang Yan, and Xipeng Qiu. 2021. SpellBERT: A lightweight pretrained model for Chinese spelling check. In Proceedings of the EMNLP. 3544\u20133551."},{"key":"e_1_3_2_9_2","volume-title":"Proceedings of the ICLR","author":"Kingma Diederik P.","year":"2015","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for stochastic optimization. In Proceedings of the ICLR."},{"key":"e_1_3_2_10_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.703"},{"key":"e_1_3_2_11_2","first-page":"1542","volume-title":"Proceedings of the Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023, Taipei, Taiwan, October 31 - Nov. 3, 2023","author":"Li Rongjun","year":"2023","unstructured":"Rongjun Li and Wei Peng. 2023. Dictionary-driven Chinese ASR entity correction with controllable decoding. In Proceedings of the Asia Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2023, Taipei, Taiwan, October 31 - Nov. 3, 2023. 1542\u20131548."},{"key":"e_1_3_2_12_2","first-page":"238","volume-title":"Proceedings of the EMNLP Findings","author":"Li Yinghui","year":"2022","unstructured":"Yinghui Li, Shirong Ma, Qingyu Zhou, Zhongli Li, Yangning Li, Shulin Huang, Ruiyang Liu, Chao Li, Yunbo Cao, and Haitao Zheng. 2022. Learning from the dictionary: Heterogeneous knowledge guided fine-tuning for Chinese spell checking. In Proceedings of the EMNLP Findings. 238\u2013249."},{"key":"e_1_3_2_13_2","first-page":"13509","volume-title":"Proceedings of the ACL","author":"Liang Zihong","year":"2023","unstructured":"Zihong Liang, Xiaojun Quan, and Qifan Wang. 2023. Disentangled phonetic representation for Chinese spelling correction. In Proceedings of the ACL. 13509\u201313521."},{"key":"e_1_3_2_14_2","first-page":"18662","volume-title":"Proceedings of the AAAI","author":"Liu Linfeng","year":"2024","unstructured":"Linfeng Liu, Hongqiu Wu, and Hai Zhao. 2024. Chinese spelling correction as rephrasing language model. In Proceedings of the AAAI. 18662\u201318670."},{"key":"e_1_3_2_15_2","first-page":"2991","volume-title":"Proceedings of the ACL","author":"Liu Shulin","year":"2021","unstructured":"Shulin Liu, Tao Yang, Tianchi Yue, Feng Zhang, and Di Wang. 2021. PLOME: Pre-training with misspelled knowledge for Chinese spelling correction. In Proceedings of the ACL. 2991\u20133000."},{"key":"e_1_3_2_16_2","article-title":"General and domain-adaptive Chinese spelling check with error-consistent pretraining","author":"Lv Qi","year":"2023","unstructured":"Qi Lv, Ziqiang Cao, Lei Geng, Chunhui Ai, Xu Yan, and Guohong Fu. 2023. General and domain-adaptive Chinese spelling check with error-consistent pretraining. ACM Trans. Asian Low Resour. Lang. Inf. Process. 22, 5 (2023), 124:1\u2013124:18.","journal-title":"ACM Trans. Asian Low Resour. Lang. Inf. Process."},{"key":"e_1_3_2_17_2","first-page":"3800","volume-title":"Proceedings of theEMNLP Findings","author":"Sun Rui","year":"2022","unstructured":"Rui Sun, Xiuyu Wu, and Yunfang Wu. 2022. An error-guided correction model for Chinese spelling error correction. In Proceedings of theEMNLP Findings. 3800\u20133810."},{"key":"e_1_3_2_18_2","doi-asserted-by":"crossref","first-page":"32","DOI":"10.18653\/v1\/W15-3106","volume-title":"Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing","author":"Tseng Yuen-Hsien","year":"2015","unstructured":"Yuen-Hsien Tseng, Lung-Hao Lee, Li-Ping Chang, and Hsin-Hsi Chen. 2015. Introduction to SIGHAN 2015 bake-off for Chinese spelling check. In Proceedings of the 8th SIGHAN Workshop on Chinese Language Processing. 32\u201337."},{"key":"e_1_3_2_19_2","first-page":"2437","volume-title":"Proceedings of the ACL Findings","author":"Wang Baoxin","year":"2021","unstructured":"Baoxin Wang, Wanxiang Che, Dayong Wu, Shijin Wang, Guoping Hu, and Ting Liu. 2021. Dynamic connected networks for Chinese spelling check. In Proceedings of the ACL Findings. 2437\u20132446."},{"key":"e_1_3_2_20_2","volume-title":"Proceedings of the ICLR","author":"Wang Wei","year":"2020","unstructured":"Wei Wang, Bin Bi, Ming Yan, Chen Wu, Jiangnan Xia, Zuyi Bao, Liwei Peng, and Luo Si. 2020. StructBERT: Incorporating language structures into pre-training for deep language understanding. In Proceedings of the ICLR."},{"key":"e_1_3_2_21_2","first-page":"1982","volume-title":"Proceedings of the INTERSPEECH","author":"Wang Xiaoqiang","year":"2021","unstructured":"Xiaoqiang Wang, Yanqing Liu, Sheng Zhao, and Jinyu Li. 2021. A light-weight contextual spelling correction model for customizing transducer-based speech recognition systems. In Proceedings of the INTERSPEECH. 1982\u20131986."},{"key":"e_1_3_2_22_2","first-page":"4333","volume-title":"Proceedings of the COLING","author":"Wang Yi-Cheng","year":"2024","unstructured":"Yi-Cheng Wang, Hsin-Wei Wang, Bi-Cheng Yan, Chi-Han Lin, and Berlin Chen. 2024. DANCER: Entity description augmented named entity corrector for automatic speech recognition. In Proceedings of the COLING. 4333\u20134342."},{"key":"e_1_3_2_23_2","first-page":"769","volume-title":"Proceedings of the WSDM","author":"Wang Yue","year":"2024","unstructured":"Yue Wang, Zilong Zheng, Zecheng Tang, Juntao Li, Zhihui Liu, Kunlong Chen, Jinxiong Chang, Qishen Zhang, Zhongyi Liu, and Min Zhang. 2024. Towards better Chinese spelling check for search engines: A new dataset and strong baseline. In Proceedings of the WSDM. 769\u2013778."},{"key":"e_1_3_2_24_2","first-page":"35","volume-title":"Proceedings of the 7th SIGHAN Workshop on Chinese Language Processing","author":"Wu Shih-Hung","year":"2013","unstructured":"Shih-Hung Wu, Chao-Lin Liu, and Lung-Hao Lee. 2013. Chinese spelling check evaluation at SIGHAN bake-off 2013. In Proceedings of the 7th SIGHAN Workshop on Chinese Language Processing. 35\u201342."},{"key":"e_1_3_2_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.csl.2023.101540"},{"key":"e_1_3_2_26_2","first-page":"716","volume-title":"Proceedings of the ACL Findings","author":"Xu Heng-Da","year":"2021","unstructured":"Heng-Da Xu, Zhongli Li, Qingyu Zhou, Chao Li, Zizhen Wang, Yunbo Cao, Heyan Huang, and Xian-Ling Mao. 2021. Read, listen, and see: Leveraging multimodal information helps Chinese spell checking. In Proceedings of the ACL Findings. 716\u2013728."},{"key":"e_1_3_2_27_2","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/W14-6820"},{"key":"e_1_3_2_28_2","first-page":"882","volume-title":"Proceedings of the ACL","author":"Zhang Shaohua","year":"2020","unstructured":"Shaohua Zhang, Haoran Huang, Jicong Liu, and Hang Li. 2020. Spelling error correction with soft-masked BERT. In Proceedings of the ACL. 882\u2013890."},{"key":"e_1_3_2_29_2","first-page":"3118","volume-title":"Proceedings of the NAACL","author":"Zhang Yue","year":"2022","unstructured":"Yue Zhang, Zhenghua Li, Zuyi Bao, Jiacheng Li, Bo Zhang, Chen Li, Fei Huang, and Min Zhang. 2022. MuCGEC: A multi-reference multi-source evaluation dataset for Chinese grammatical error correction. In Proceedings of the NAACL. 3118\u20133130."},{"key":"e_1_3_2_30_2","first-page":"1244","volume-title":"Proc. of ACL Findings","author":"Zhu Chenxi","year":"2022","unstructured":"Chenxi Zhu, Ziqiang Ying, Boyu Zhang, and Feng Mao. 2022. MDCSpell: A multi-task detector-corrector framework for Chinese spelling correction. In Proc. of ACL Findings. 1244\u20131253."}],"container-title":["ACM Transactions on Asian and Low-Resource Language Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3765761","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,24]],"date-time":"2025-10-24T14:01:47Z","timestamp":1761314507000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3765761"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,24]]},"references-count":29,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2025,11,30]]}},"alternative-id":["10.1145\/3765761"],"URL":"https:\/\/doi.org\/10.1145\/3765761","relation":{},"ISSN":["2375-4699","2375-4702"],"issn-type":[{"type":"print","value":"2375-4699"},{"type":"electronic","value":"2375-4702"}],"subject":[],"published":{"date-parts":[[2025,10,24]]},"assertion":[{"value":"2025-03-19","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-08-29","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-10-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}