Low False Alarm Rate Chinese Misspelling Detection Model Based on BERT Task Model

Jyun-Yi Shen, Tao-Hsing Chang


Anthology ID:
2020.rocling-1.29
Volume:
Proceedings of the 32nd Conference on Computational Linguistics and Speech Processing (ROCLING 2020)
Month:
September
Year:
2020
Address:
Taipei, Taiwan
Editors:
Jenq-Haur Wang, Ying-Hui Lai
Venue:
ROCLING
SIG:
Publisher:
The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
Note:
Pages:
319–330
Language:
URL:
https://aclanthology.org/2020.rocling-1.29
DOI:
Bibkey:
Cite (ACL):
Jyun-Yi Shen and Tao-Hsing Chang. 2020. Low False Alarm Rate Chinese Misspelling Detection Model Based on BERT Task Model. In Proceedings of the 32nd Conference on Computational Linguistics and Speech Processing (ROCLING 2020), pages 319–330, Taipei, Taiwan. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP).
Cite (Informal):
Low False Alarm Rate Chinese Misspelling Detection Model Based on BERT Task Model (Shen & Chang, ROCLING 2020)
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PDF:
https://preview.aclanthology.org/nschneid-patch-4/2020.rocling-1.29.pdf