Papers by Keqiang Wang
Global Attention Decoder for Chinese Spelling Error Correction (2021.findings-acl)
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| Challenge: | Existing methods for Chinese spelling error correction focus on local contextual information, thus misleading the user and reducing performance. |
| Approach: | They propose a global attention decoder that learns the global relationship of correct input characters and candidates of potential error characters. |
| Outcome: | The proposed method outperforms all competitor models by a large margin of up to 6.2% on three human-annotated datasets. |