Intelligent Error Correction of College English Spoken Grammar Based on the GA‐MLP‐NN Algorithm

Abstract

With the development of neural networks in deep learning, artificial intelligence machine learning has become the main focus of researchers. In College English grammar detection, oral grammar is the most error rate content. So, this paper optimizes MLP based on GA in the deep learning neural network and then studies the intelligent image correction of College English spoken grammar. The main direction is to discuss and analyze GA-MLP-NN algorithm technology first and then predict the error correction model of spoken language grammar by combining the optimized algorithm. The results show that GA-MLP-NN provides excellent accuracy for the prediction of the whole syntax error correction model. Then, the paper studies the deep learning technology to build an intelligent image error correction model of College English spoken grammar. The results show that the effect of intelligent correction of spoken grammar is very fast and accurate.

Research and Analysis on the Integration of Artificial Intelligence in College English Teaching

“…In college English grammar detection, oral grammar is the content with the highest error rate. Du [3] proposed in the research of intelligent error correction of college oral English grammar based on GA-MLP-NN algorithm that compared with the traditional multilayer perceptron prediction, the optimized algorithm signi cantly improves the running e ciency of the model and shortens the prediction time. During the university period, in the large-scale classroom teaching, teachers often cannot interact e ectively with every student, which leads to a signi cant reduction in teaching effect.…”