Research on English grammar error correction algorithm based on deep learning

Shengqin Bi

doi:10.1117/12.3003912

11 October 2023 Research on English grammar error correction algorithm based on deep learning

Shengqin Bi

Proceedings Volume 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023); 128000O (2023) https://doi.org/10.1117/12.3003912
Event: 6th International Conference on Computer Information Science and Application Technology (CISAT 2023), 2023, Hangzhou, China

Abstract

Automatic grammatical correction (GEC) is one of the more difficult tasks in syntactic analysis for natural language processing. Non-native speakers often have difficulty understanding grammatical nuances, and grammatical correction in natural language contains grammatical errors and collocation errors. Compared with statistical classification-based error correction models, deep classification error correction models are a big improvement, but deep classification grammar error correction models can only correct for closed-form class errors. To address the above problems, this paper explores the automatic English grammar error correction algorithm from two ideas: using deep classification models and treating the grammar error correction problem as machine translation, and locating grammatical errors by building encoder-decoder sequence-to-sequence (seq2seq) models to understand the semantic and word expression differences between incorrect and correct sentences in order to improve the operational efficiency of model training and the basic ability to correct errors. This study uses the TensorFlow framework for the empirical validation of the used models to test the effectiveness of using the seq2seq error correction algorithm model with an attention mechanism.

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

Citation Download Citation

Shengqin Bi "Research on English grammar error correction algorithm based on deep learning", Proc. SPIE 12800, Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023), 128000O (11 October 2023); https://doi.org/10.1117/12.3003912

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KEYWORDS

Error control coding

Education and training

Error analysis

Deep learning

Data modeling

Data processing

Process modeling

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