Affiliations: Foreign Language School, Zhengzhou Shengda University of Economics, Business and Management, Zhengzhou, Henan, China
Correspondence:
[*]
Corresponding author. Jinying Cui, Foreign Language School, Zhengzhou Shengda University of Economics, Business and Management, Zhengzhou, Henan, China. E-mail: nicolecui@163.com.
Abstract: The corpus software has many functions, such as keyword retrieval, context co-occurrence, word list generation and word frequency statistics. It can quickly and accurately provide various corpus and information, such as word-formation collocation, context, word frequency and so on. In this paper, the author analyzes the application of deep learning and target visual detection in English vocabulary online teaching. Deep learning is a kind of machine learning algorithm which includes multi-layer non-linear mapping and tries to obtain high-level abstract representation of data. By extracting features from information, the identifiable components in the image can be extracted. The results show that the application of corpus in College English vocabulary teaching can promote students’autonomous use of corpus in English vocabulary learning. The simulation experiment improves the performance of the system by choosing parameters, and the classification accuracy is more than 90%. Corpus can enable students to learn real and natural language and master natural collocation. At the same time, corpus can help students understand the semantic and pragmatic norms of words in communication and recognize the characteristics of register variants. Future research can use Map-reduce technology to accelerate the training process, save training time and test more hyperparameters.
Keywords: Corpus, deep learning, target recognition, natural language algorithms, data simulation
