The invention discloses an intelligent accompanying method and
system fusing distributed learning and privacy multistage regulation, and the method comprises the steps: collecting the multi-
modal interaction data of a user, constructing a local cognitive stage map and an emotion evaluation model, and carrying out the semantic sensitive modeling and
differential privacy disturbance
processing according to a privacy strategy set by the user. Dynamic transfer learning and asynchronous contrast training of desensitized data are completed at edge nodes, and the desensitized data are uploaded to a cloud for aggregation, so that a multi-
branch elastic strategy is generated, and accompanying requirements under different cognitive states and task situations are met. Meanwhile, the accompanying behavior style is dynamically adjusted through strategy feedback and a context matching mechanism, and personalized
adaptation of language preference and ethical sensitivity of the user is achieved. The
system has cross-
modal privacy protection, multi-level model generalization, cultural expression
adaptation and long-term accompanying evolution capabilities, improves the safety, individuation and ethical consistency of intelligent accompanying, and is suitable for various scenes such as education, health and psychological support.