Realization and Optimization of English Smart Teaching Environment based on Real-Time Action Data Computer Acquisition Algorithm

Realization and optimization of English smart teaching environment based on real-time action data computer acquisition algorithm is studied in the paper. Data preprocessing is needed to improve the proportion of useful data before action recognition. In this paper, the method of looking for standardized modulus is used to reduce the deviation caused by absolute data. The vector extracted from the data of human inherent limb structure can be used as a standard vector because it is less affected by the change of human action. The core idea of the algorithm is: firstly initialize the weights of each training sample in the sample set, then train and update the weights to obtain different weak classifiers, and then arrange the weak classifiers according to their classification ability from low to high. With this integration, the designed model is then implemented through the analysis of the smart systems. Through the systematci test and verification, the performance is validated.