Affiliations: [a] School of Foreign Studies, North Minzu University, Yinchuan, Ningxia, China
| [b] Department of Public Studies, Jiangxi Health Vocational College, Nanchang, Jiangxi, China
Correspondence:
[*]
Corresponding author. Lijun Zhang, Department of Public Studies, Jiangxi Health Vocational College, Nanchang, Jiangxi, China. E-mail: [email protected].
Abstract: Cross-cultural English teaching is limited by the influence of traditional teaching models, resulting in poor teaching results. In order to improve the efficiency of cross-cultural English teaching, with the support of AI emotion recognition and neural network algorithm, this paper builds a cross-cultural O2O English teaching system with intelligent recognition and management. Moreover, this research uses background models to detect and track targets, to realize the full recognition of students’ emotions, and to facilitate teachers to effectively control online teaching. In addition, combined with online and offline teaching, this study uses neural network algorithm to stabilize the system and perform data processing, construct an overall O2O English teaching model according to actual needs, and formulate the corresponding teaching process. In order to verify the performance of the model, this study starts from two aspects: system performance test and system practice effect and uses statistical methods to collect and process data. The test results show that the model constructed in this paper has good performance and meets expectations.
Keywords: AI emotion recognition, neural network, cross-cultural, English
teaching, O2O
