Interactive Design of Business English Learning Resources Based on EDIPT Multimodal Model

Aiming at the problem that online video learning resources of business English are scattered and the learners are inefficient in acquiring learning resources, this paper designed a business English learning system based on the EDIPT model. In addition, aiming at the problem of multifeature fusion between low-level features and high-level semantic features in video scenes, this paper proposes a multi-modal video scene segmentation algorithm based on a deep network. By minimizing the square sum of distances in the time period, the shots are clustered, and finally, the semantic scene is obtained. The experimental results show that the algorithm has good performance in classification accuracy and can effectively segment video scenes, which is helpful for users to improve their comprehensive business English skills.