With the rapid development of artificial intelligence technology, the application of robots in the field of preschool education has gradually become an important tool to improve the quality of education and interaction effect. In this paper, a deep learning-based intelligent interaction system for preschool education robots is proposed, aiming to optimize the interaction ability of robots in preschool education through deep learning technology. The system design includes the selection and optimization of the deep learning model, the application of multimodal data fusion technology, and the design and implementation of the interactive interface. Through the optimization of the deep learning model, the system is able to understand children's language and emotions more accurately and improve the quality of interaction between the educational robot and children. The system adopts multimodal data fusion technology, enabling the robot to provide personalized and flexible interactive experiences through the integrated analysis of speech, image and emotion data. The article explores the challenges facing the current technology, including issues of responsiveness, system stability, personalized learning support, and privacy protection. The study shows that the deep learning-based preschool education robot system can effectively promote children's cognitive development and emotional cultivation, and has broad application prospects and development potential.
Qianru Liu (Sun,) studied this question.