System

A system comprising:

• circuitry configured to:
• receive, via a communication interface coupled to a packet-switched network, a prompt sentence from a terminal device, and perform natural language processing including tokenization, morphological analysis, transformer-based semantic embedding, intent classification, and named entity recognition to extract customer need information and constraint condition information as structured records with budget fields, feature flags, and priority scores;
• execute structured database queries on a product information storage device using the extracted constraint condition information as equality and range conditions on indexed product attribute columns, rank retrieved candidate product records by a relevance scoring function, and construct a structured prompt template assembling the prompt sentence, the customer need information, and top-ranked candidate product attributes;
• operate a transformer-based generative neural network model using the structured prompt template as input to generate a personalized proposal sentence with constrained decoding that prevents tokens contradicting known product attributes, and transmit the personalized proposal sentence to the terminal device via the communication interface;
• receive voice data from the terminal device, execute a speech recognition model to convert the voice data to recognized utterance text, compute acoustic feature vectors including pitch contour values, energy levels, speech rate values, and pause pattern features for temporal segments, and apply a sequential neural network classifier to the acoustic feature vectors to generate psychological state information including engagement level, anxiety indicator, and interest trend signals;
• and
• construct guidance model input data including the recognized utterance text, the psychological state information, and negotiation context, operate the generative neural network model using the guidance model input data to generate a guidance sentence specifying response policy, emphasis points, and revision suggestions, and transmit the guidance sentence to the terminal device via the communication interface.

A method comprising:

• receiving, via a communication interface coupled to a packet-switched network, a prompt sentence expressed in natural language from a terminal device, and performing natural language processing on the prompt sentence including morphological analysis, semantic embedding computation, and intent classification to extract customer need information and constraint condition information as structured records;
• executing query processing on a product information storage device using the customer need information and the constraint condition information as structured query conditions, and ranking candidate product records by a relevance scoring function combining attribute match scores and rating values;
• constructing model input data by assembling the prompt sentence, the customer need information, and the ranked candidate product records into a structured context sequence, and operating a generative neural network model using the model input data to generate a personalized proposal and transmit the personalized proposal to the terminal device via the communication interface;
• receiving, via the communication interface, voice data acquired by a sound collection device of the terminal device during a negotiation, performing speech recognition processing and acoustic feature analysis processing on the voice data to extract pitch contours, energy levels, speech rate values, and pause pattern features, and applying a psychological state classifier to the extracted features to generate psychological state information including an estimated engagement level and anxiety indicator;
• and
• constructing guidance model input data including the personalized proposal, recognized utterance text, and the psychological state information, and operating the generative neural network model using the guidance model input data to generate a guidance output including a response policy and explanation emphasis points, and transmitting the guidance output to the terminal device via the communication interface.