Chinese Spelling Correction: A Comprehensive Survey of Progress, Challenges, and Opportunities
This is an incremental survey that addresses the need for a structured understanding of CSC for researchers in natural language processing.
This survey tackles the problem of Chinese Spelling Correction (CSC) by providing a comprehensive overview of its evolution, analyzing methods from pre-trained to large language models, and identifying challenges in datasets, with the result being a first-of-its-kind resource to guide future research.
Chinese Spelling Correction (CSC) is a critical task in natural language processing, aimed at detecting and correcting spelling errors in Chinese text. This survey provides a comprehensive overview of CSC, tracing its evolution from pre-trained language models to large language models, and critically analyzing their respective strengths and weaknesses in this domain. Moreover, we further present a detailed examination of existing benchmark datasets, highlighting their inherent challenges and limitations. Finally, we propose promising future research directions, particularly focusing on leveraging the potential of LLMs and their reasoning capabilities for improved CSC performance. To the best of our knowledge, this is the first comprehensive survey dedicated to the field of CSC. We believe this work will serve as a valuable resource for researchers, fostering a deeper understanding of the field and inspiring future advancements.