@inproceedings{wang-etal-2023-system,
title = "System Report for {CCL}23-Eval Task 8: {C}hinese Grammar Error Detection and Correction Using Multi-Granularity Information",
author = "Wang, Yixuan and
Liu, Yijun and
Sun, Bo and
Che, Wanxiang",
editor = "Sun, Maosong and
Qin, Bing and
Qiu, Xipeng and
Jiang, Jing and
Han, Xianpei",
booktitle = "Proceedings of the 22nd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)",
month = aug,
year = "2023",
address = "Harbin, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2023.ccl-3.30",
pages = "271--281",
abstract = "{``}This paper introduces our system at CCL-2023 Task: Chinese Essay Fluency Evaluation (CEFE).The CEFE task aims to study the identification and correction of grammatical errors in primaryand middle school students{'} test compositions. The evaluation has three tracks to examine therecognition of wrong sentence types, character-level error correction, and wrong sentence rewrit-ing. According to the task characteristics and data distribution of each track, we propose a token-level discriminative model based on sequence labeling for the multi-label classification task ofwrong sentences, an auto-encoder model based on edited labels for character-level error correc-tion and a seq2seq model obtained by pre-training on pseudo data and fine-tuning on labeleddata to solve the wrong sentence rewriting task. In the final evaluation results, the method weproposed won the first place in all three tracks according to the corresponding evaluation metrics.{''}",
language = "English",
}
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<abstract>“This paper introduces our system at CCL-2023 Task: Chinese Essay Fluency Evaluation (CEFE).The CEFE task aims to study the identification and correction of grammatical errors in primaryand middle school students’ test compositions. The evaluation has three tracks to examine therecognition of wrong sentence types, character-level error correction, and wrong sentence rewrit-ing. According to the task characteristics and data distribution of each track, we propose a token-level discriminative model based on sequence labeling for the multi-label classification task ofwrong sentences, an auto-encoder model based on edited labels for character-level error correc-tion and a seq2seq model obtained by pre-training on pseudo data and fine-tuning on labeleddata to solve the wrong sentence rewriting task. In the final evaluation results, the method weproposed won the first place in all three tracks according to the corresponding evaluation metrics.”</abstract>
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%0 Conference Proceedings
%T System Report for CCL23-Eval Task 8: Chinese Grammar Error Detection and Correction Using Multi-Granularity Information
%A Wang, Yixuan
%A Liu, Yijun
%A Sun, Bo
%A Che, Wanxiang
%Y Sun, Maosong
%Y Qin, Bing
%Y Qiu, Xipeng
%Y Jiang, Jing
%Y Han, Xianpei
%S Proceedings of the 22nd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
%D 2023
%8 August
%I Chinese Information Processing Society of China
%C Harbin, China
%G English
%F wang-etal-2023-system
%X “This paper introduces our system at CCL-2023 Task: Chinese Essay Fluency Evaluation (CEFE).The CEFE task aims to study the identification and correction of grammatical errors in primaryand middle school students’ test compositions. The evaluation has three tracks to examine therecognition of wrong sentence types, character-level error correction, and wrong sentence rewrit-ing. According to the task characteristics and data distribution of each track, we propose a token-level discriminative model based on sequence labeling for the multi-label classification task ofwrong sentences, an auto-encoder model based on edited labels for character-level error correc-tion and a seq2seq model obtained by pre-training on pseudo data and fine-tuning on labeleddata to solve the wrong sentence rewriting task. In the final evaluation results, the method weproposed won the first place in all three tracks according to the corresponding evaluation metrics.”
%U https://aclanthology.org/2023.ccl-3.30
%P 271-281
Markdown (Informal)
[System Report for CCL23-Eval Task 8: Chinese Grammar Error Detection and Correction Using Multi-Granularity Information](https://aclanthology.org/2023.ccl-3.30) (Wang et al., CCL 2023)
ACL