A study of Grammar Analysis in English Teaching With Deep Learning Algorithm

Authors

  • Gang Zhang Henan Medical College

DOI:

https://doi.org/10.3991/ijet.v15i18.15425

Keywords:

deep learning, English teaching, seq2seq attention mechanism, recall rate

Abstract


In English teaching, grammar is a very important part. Based on the seq2seq model, a grammar analysis method combining the attention mechanism, word embedding and CNN seq2seq was designed using the deep learning algorithm, then the algorithm training was completed on NUCLE, and it was tested on CoNIL-2014. The experimental results showed that of seq2seq+attention improved 33.43% compared to the basic seq2seq; in the comparison between the method proposed in this study and CAMB, the P value of the former was 59.33% larger than that of CAMB, the R value was 8.9% larger, and the value of was 42.91% larger. Finally, in the analysis of the actual students' grammar homework, the proposed method also showed a good performance. The experimental results show that the method designed in this study is effective in grammar analysis and can be applied and popularized in actual English teaching.

Downloads

Published

2020-09-25

How to Cite

Zhang, G. (2020). A study of Grammar Analysis in English Teaching With Deep Learning Algorithm. International Journal of Emerging Technologies in Learning (iJET), 15(18), pp. 20–30. https://doi.org/10.3991/ijet.v15i18.15425

Issue

Section

Papers