Intelligent Analysis Strategy of Pragmatic Failure in Cross-Cultural Communication Based on Convolution Neural Network

Abstract

The study of pragmatic failure in cross-cultural communication is a subject of great theoretical significance and practical value in contemporary linguistic research. This paper takes pragmatic failures in cross-cultural communication as the research object, and tries to make the discussion systematic, theoretical, and scientific. With this feature, the complexity of the convolutional network will be greatly reduced. In the convolution layer, the convolution operation can make the features of the initial speech more obvious, and it can also have certain effect on the noise reduction of speech. It is of great theoretical and practical significance to use convolutional neural network to study the intelligent analysis strategies of pragmatic failure in cross-cultural communication. In this paper, the intelligent analysis strategy of pragmatic failure in cross-cultural communication based on deep convolution neural network is taken as the research object, and an optimized end-to-end deep convolution neural network model is proposed. Experimental results show that the overall recognition rate of this algorithm is improved by 59.8%. Especially, the efficiency of obtaining results is basically maintained at 61.8%. The intelligent analysis strategy of pragmatic failure in cross-cultural communication based on convolutional neural network reduces redundant calculation and shortens training time to some extent, and this algorithm can better reflect the advantages of accelerating network convergence compared with simple network.