Chinese Grammatical Error Correction Using Statistical and Neural Models

Zhou, Junpei; Li, Chen; Liu, Hengyou; Bao, Zuyi; Xu, Guangwei; Li, Linlin

doi:10.1007/978-3-319-99501-4_10

“…YouDao [50] incorporated the vanilla transformer as the main neural translation model. AliGM [55] took the statistical language and machine translation models and the seq2seq with attention architecture as the neural machine translation to solve the grammatical problems. As for BLCU [56], the convolutional sequence-tosequence model was introduced as the main model.…”

Section: Comparison In Cgec Taskmentioning

confidence: 99%

Pre-Training-Based Grammatical Error Correction Model for the Written Language of Chinese Hearing Impaired Students

Chen

¹

,

Zhang

²

2022

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Exaggerated anticipatory anxiety is common in social anxiety disorder (SAD). Neuroimaging studies have revealed altered neural activity in response to social stimuli in SAD, but fewer studies have examined neural activity during anticipation of feared social stimuli in SAD. The current study examined the time course and magnitude of activity in threat processing brain regions during speech anticipation in socially anxious individuals and healthy controls (HC). Method Participants (SAD n = 58; HC n = 16) underwent functional magnetic resonance imaging (fMRI) during which they completed a 90s control anticipation task and 90s speech anticipation task.

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“…Precision Recall F 0.5 YouDao (Fu, Huang, and Duan 2018) 35.24 18.64 29.91 AliGM (Zhou et al 2018) 41.00 13.75 29.36 BLCU (Ren, Yang, and…”

Section: Modelmentioning

confidence: 99%

“…We denote them as GECToR-BERT, GECToR-XLNet and GECToR (Ensemble) respectively. For the Chinese GEC task, we compare S2A to several best performing systems evaluated on the NLPCC-2018 dataset, including three top systems in the NLPCC-2018 challenge (YouDao (Fu, Huang, and Duan 2018), AliGM (Zhou et al 2018), BLCU (Ren, Yang, and Xun 2018)), the seq2seq baseline Char Transformer, and the current state-of-the-art method MaskGEC (Zhao and Wang 2020). Note that the proposed S2A model is orthogonal to MaskGEC, and we also report our results enhanced with the data augmentation method of MaskGEC.…”

Section: Baselinesmentioning

confidence: 99%

Sequence-to-Action: Grammatical Error Correction with Action Guided Sequence Generation

Li

¹

,

Guo

²

,

Zhu

³

et al. 2022

AAAI

15

0

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Exaggerated anticipatory anxiety is common in social anxiety disorder (SAD). Neuroimaging studies have revealed altered neural activity in response to social stimuli in SAD, but fewer studies have examined neural activity during anticipation of feared social stimuli in SAD. The current study examined the time course and magnitude of activity in threat processing brain regions during speech anticipation in socially anxious individuals and healthy controls (HC). Method Participants (SAD n = 58; HC n = 16) underwent functional magnetic resonance imaging (fMRI) during which they completed a 90s control anticipation task and 90s speech anticipation task.

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“…• AliGM (Zhou et al 2018): The Chinese GEC system developed by Alibaba, which combines NMT-based approaches, SMT-based approaches and a rule-based approach together with various modules.…”

Section: Baselinesmentioning

confidence: 99%

MaskGEC: Improving Neural Grammatical Error Correction via Dynamic Masking

Zhao

¹

,

Wang

²

2020

AAAI

Get access via publisher Add to dashboard Cite

Exaggerated anticipatory anxiety is common in social anxiety disorder (SAD). Neuroimaging studies have revealed altered neural activity in response to social stimuli in SAD, but fewer studies have examined neural activity during anticipation of feared social stimuli in SAD. The current study examined the time course and magnitude of activity in threat processing brain regions during speech anticipation in socially anxious individuals and healthy controls (HC). Method Participants (SAD n = 58; HC n = 16) underwent functional magnetic resonance imaging (fMRI) during which they completed a 90s control anticipation task and 90s speech anticipation task.

show abstract

Chinese Grammatical Error Correction Using Statistical and Neural Models

Cited by 34 publications

References 17 publications

Pre-Training-Based Grammatical Error Correction Model for the Written Language of Chinese Hearing Impaired Students

Pre-Training-Based Grammatical Error Correction Model for the Written Language of Chinese Hearing Impaired Students

Sequence-to-Action: Grammatical Error Correction with Action Guided Sequence Generation

MaskGEC: Improving Neural Grammatical Error Correction via Dynamic Masking

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