Hierarchical Character Tagger for Short Text Spelling Error Correction

State-of-the-art approaches to spelling error correction problem include Transformer-based Seq2Seq models, which require large training sets and suffer from slow inference time; and sequence labeling models based on Transformer encoders like BERT, which involve token-level label space and therefore...

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Veröffentlicht in:	arXiv.org 2021-09
Hauptverfasser:	Gao, Mengyi, Xu, Canran, Shi, Peng
Format:	Artikel
Sprache:	eng
Schlagworte:	Coders Error correction Error correction & detection Free form Spelling Transformers
Online-Zugang:	Volltext
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