System

A system comprising:

• a communication interface coupled to a packet-switched network;
• a storage device;
• and
• circuitry configured to:
• acquire, via the communication interface, entity-related electronic information, preprocess the electronic information by performing multimodal analysis comprising language analysis to extract expression-tendency and emotion-tendency information, and image and video feature extraction to extract subject-feature and scene-feature information, and integrate the extracted information into a structured personality profile;
• construct a dialogue data processing model by generating a system-level instruction prompt comprising the structured personality profile, characteristic expression patterns, and relational context descriptors, and storing the instruction prompt in the storage device;
• generate feature vectors for memory elements derived from the electronic information, store the feature vectors in an approximate nearest neighbor index, receive user input from a terminal device, convert the user input into a prompt feature vector, perform similarity search to identify related memory elements, rank the memory elements by a weighted relevance score, and generate integrated prompt information combining the dialogue data processing model, context information from the ranked memory elements, and the user input;
• input the integrated prompt information to a generative neural network model to generate a response sentence, analyze an emotional state of the user by applying an emotion classification model to the user input to produce an emotional state label, and adjust at least one of a response tone parameter and a dialogue progression parameter based on the emotional state label;
• and
• transmit the response sentence to the terminal device via the communication interface and store a dialogue history comprising the integrated prompt information and the response sentence.

A method comprising:

• acquiring, via a communication interface coupled to a packet-switched network, entity-related electronic information, preprocessing the electronic information by performing multimodal analysis to extract expression-tendency information, emotion-tendency information, subject-feature information, and scene-feature information, and integrating the extracted information to generate personality information;
• constructing a dialogue data processing model serving as an assumed personality based on the personality information by using a generative neural network model;
• generating feature vectors for memory elements derived from the electronic information, storing the feature vectors in a memory index structure, receiving a prompt sentence from a terminal device, converting the prompt sentence into a prompt feature vector, performing similarity search to identify related memory elements, and generating integrated prompt information combining dialogue control information, context information from the identified memory elements, and the prompt sentence;
• inputting the integrated prompt information to the generative neural network model to generate a response sentence;
• analyzing an emotional state of a user based on the prompt sentence, and adjusting at least one of a response content parameter, a response tone parameter, and a dialogue progression parameter of the integrated prompt information based on the analyzed emotional state;
• and
• transmitting the response sentence to the terminal device via the communication interface.