RTGAC: RoBERTa-TCN-GRU-CRF combined attention mechanism for grammar error detection in spoken Chinese

Linna Zheng; Aishan Wumaier; Jiangtao He

doi:10.1117/12.3009580

16 October 2023 RTGAC: RoBERTa-TCN-GRU-CRF combined attention mechanism for grammar error detection in spoken Chinese

Linna Zheng, Aishan Wumaier, Jiangtao He

Proceedings Volume 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023); 128032A (2023) https://doi.org/10.1117/12.3009580
Event: 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), 2023, Wuhan, China

Abstract

Grammar automatic error detection can help language learners identify whether there are errors in their own written text. For the grammatical error detection task of spoken Chinese in this paper, one of the most obvious shortcomings of this task is that the data set is small. In this case, there may be some sparse features in the training data set. To solve this problem, we propose a Chinese grammar error detection method combining Temporal Convolutional Network (TCN) and Threshold Recurrent Unit (GRU). To verify the effectiveness of the model framework proposed in this paper, we test our method on the Chinese spoken grammar dataset and Chinese text writing dataset respectively. By comparing the prediction effects of various deep learning models, the proposed model has a high F1 value in Chinese spoken grammar error detection and Chinese text writing grammar error detection.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Linna Zheng, Aishan Wumaier, and Jiangtao He "RTGAC: RoBERTa-TCN-GRU-CRF combined attention mechanism for grammar error detection in spoken Chinese", Proc. SPIE 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023), 128032A (16 October 2023); https://doi.org/10.1117/12.3009580

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