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- W2976188758 abstract "Automatic Chinese spelling checking and correction (CSC) is currently a challenging task especially when the sentence is complex in semantics and expressions. Meanwhile, a CSC model normally requires a huge amount of training corpus which is usually unavailable. To capture the semantic information of sentences, this paper proposes an approach (named as DPL-Corr) based on character-based pre-trained contextual representations, which helps to significantly improve the performance of CSC. In DPL-Corr, the module of spelling checking is a sequence-labeling model enhanced by deep contextual semantics analysis, and the module of spelling correction is a masked language model integrated with multilayer filtering to obtain the final corrections. Based on experiments on SIGHAN 2015 dataset, DPL-Corr achieves a significantly better performance of CSC than conventional models." @default.
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- W2976188758 date "2019-01-01" @default.
- W2976188758 modified "2023-09-23" @default.
- W2976188758 title "Automatic Chinese Spelling Checking and Correction Based on Character-Based Pre-trained Contextual Representations" @default.
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- W2976188758 doi "https://doi.org/10.1007/978-3-030-32236-6_49" @default.
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