System

A system comprising:

• a communication interface coupled to a packet-switched network;
• and
• circuitry configured to:
• acquire voice information from a terminal device via the communication interface, convert the voice information into character information by speech recognition, and extract acoustic features comprising pitch contour, speaking rate, pause duration, and energy variation;
• generate a prompt comprising the character information, the acoustic features as numerical parameters, evaluation items including linguistic complexity metrics and vocabulary diversity indicators, and an output format specification, and input the prompt to a generative neural network model to obtain analysis result data comprising a risk category label, a numerical risk score, a confidence value, and risk pattern descriptors;
• acquire behavior data from the terminal device comprising interaction frequency, response latency, and session duration, generate a supplementary prompt including the behavior data, and compute a composite risk level by weighted aggregation of component risk scores;
• store the analysis result data and the composite risk level in a storage device with time-series information, generate transition information comprising trend direction, rate of change, and historical baseline comparison, and detect anomalous transitions by threshold comparison;
• generate output information comprising an explanatory sentence and action recommendation based on the analysis result data and the transition information, and transmit the output information and any alert notifications to the terminal device and to additional terminal devices via the packet-switched network;
• and
• receive feedback information from the terminal device and update prompt-generation parameters based on the feedback.

A method comprising:

• acquiring, by circuitry coupled to a packet-switched network, voice information from a terminal device and converting the voice information into character information by speech recognition;
• generating a prompt comprising the character information, evaluation items, and an output format specification for risk-level assessment, and inputting the prompt to a generative neural network model to obtain analysis result data by extracting and classifying risk patterns;
• storing the analysis result data in a storage device with time-series information and generating transition information of the risk level;
• generating output information comprising an explanatory sentence and action recommendation based on the analysis result data and the transition information;
• and
• transmitting the output information to the terminal device via the packet-switched network.