mlsanityData to 7 Oct 2026

Investigating Glyph Phonetic Information for Chinese Spell Checking: What Works and What's Next

arXiv 2212.04068 ↗First posted 8 Dec 2022cs.CL cs.AIcited by 0

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Abstract (arXiv)

While pre-trained Chinese language models have demonstrated impressive performance on a wide range of NLP tasks, the Chinese Spell Checking (CSC) task remains a challenge. Previous research has explored using information such as glyphs and phonetics to improve the ability to distinguish misspelled characters, with good results. However, the generalization ability of these models is not well understood: it is unclear whether they incorporate glyph-phonetic information and, if so, whether this information is fully utilized. In this paper, we aim to better understand the role of glyph-phonetic information in the CSC task and suggest directions for improvement. Additionally, we propose a new, more challenging, and practical setting for testing the generalizability of CSC models. All code is made publicly available.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 43 references that are in the map. First posted on arXiv 8 Dec 2022.

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19 of 43 references.

References · 19

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7 more
  1. 2021Read, Listen, and See: Leveraging Multimodal Information Helps Chinese Spell Checkingcited by 52
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  3. 2018Robust Neural Machine Translation with Joint Textual and Phonetic Embeddingcited by 19
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