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

机译:深度学习算法中英语教学语法分析研究

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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.
机译:在英语教学中,语法是一个非常重要的部分。基于SEQ2SEQ模型,使用深入学习算法设计了一种基于注意机制,Word Embedding和CNN SEQ2Seq的语法分析方法,然后在核上完成算法训练,并在Conil-2014上进行了测试。实验结果表明,与基本SEQ2SEQ相比,SEQ2Seq注意力提高了33.43%;在本研究和CAMB中提出的方法之间的比较中,前者的P值比CAMB大的59.33%,R值较大8.9%,值为42.91%。最后,在分析实际学生的语法作业中,所提出的方法也表现出良好的表现。实验结果表明,本研究中设计的方法在语法分析中是有效的,可以在实际的英语教学中应用和推广。

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