Intelligent Algorithms of English Semantic Analysis Based on Deep Learning Technology

The grammatical relationship between words often plays an important role in word understanding and word processing, and is widely used in fields such as information retrieval, word processing, dictionaries, and understanding construction. This article aims to study an intelligent algorithm for English translation analysis based on deep learning technology. It highlights the research background and the importance of semantic analysis, and explains the research status. To show the relevant science and technology used, the word checking algorithm studied in this article uses the two word embedding methods to process the data in the training corpus. Then it will be used as the input of the long and short-term memory neural network. Finally, the algorithm is realized by training the neural network to obtain the language model. The trained language model is used to predict the output of the word at a specific location and compare it with the original word and feed it back to the user. In this paper, the average F-value of the semantic analysis of English composition under 5 themes is 95.00%.