System

Abstract

An object of a system according to an embodiment is to quickly provide a natural answer to an inquiry from a customer.SOLUTION: A system according to an embodiment includes a portal installation unit, a AI prompt generation unit, and a generation AI response unit. The portal installation unit installs a dedicated portal. An AI prompt generation part generates an AI prompt for inputting inquiry contents of a customer in a portal installation part. The generated AI response unit generates a natural response based on the prompt generated by the AI prompt generation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Previous technology had issues such as unnatural responses to customer inquiries and taking a long time to respond.

[0005] The system according to the embodiment aims to provide quick and natural responses to inquiries from customers. [Means for solving the problem]

[0006] The system according to the embodiment includes a portal installation unit, an AI prompt generation unit, and an AI answer generation unit. The portal installation unit installs a dedicated portal. The AI ​​prompt generation unit generates an AI prompt for inputting customer inquiries in the portal installation unit. The AI ​​answer generation unit generates natural answers based on the prompts generated by the AI ​​prompt generation unit. [Effects of the Invention]

[0007] The system according to the embodiment can quickly provide natural answers to inquiries from customers. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The inquiry response system according to an embodiment of the present invention aggregates customer inquiries into a dedicated customer portal and uses a generation AI to provide natural answers. This enables the inquiry response system to efficiently process customer inquiries, reduce the man-hours required by the sales department, and minimize response delays.

[0029] An inquiry response system according to an embodiment includes a portal installation unit, an AI prompt generation unit, and a generation AI response unit. The portal installation unit installs a dedicated customer portal. For example, the portal installation unit allows customers to access the portal through a web portal or a mobile application. The portal installation unit can centrally manage inquiry content and store it in a database. The AI ​​prompt generation unit generates AI prompts for inputting customer inquiry content in the portal installation unit. For example, the AI ​​prompt generation unit analyzes the customer's input content using natural language processing technology and presents appropriate confirmation questions. The AI ​​prompt generation unit can dynamically generate prompts based on a method for analyzing the user input. The generation AI response unit generates natural responses based on the prompts generated by the AI ​​prompt generation unit. For example, the generation AI generates responses taking into account grammatical accuracy and contextual suitability. The generation AI can also refer to past inquiry data to provide more appropriate answers. As a result, the inquiry response system according to an embodiment can efficiently process customer inquiries, reduce sales workload, and minimize response delays. For example, the system can minimize internal checks based on the inquiry content and provide quick responses. The system can also store the inquiry content in a database to help improve future inquiry responses.

[0030] The portal installation unit can introduce a personalized dashboard based on the user's behavior history, allowing the user to check the user's past inquiry history and solutions at a glance. For example, the portal installation unit makes it so that when a user logs in to a customer-specific portal, the past inquiry history and solutions are displayed on the dashboard. For example, a list of troubleshooting history that has been resolved in the past is displayed. The portal installation unit also personalizes and displays frequently asked questions and related solutions based on the user's behavior history. For example, questions that many users have searched for in the past are displayed preferentially. The portal installation unit also adds a function to automatically pin FAQs and solutions that the user has viewed in the past to the dashboard. For example, FAQs related to a specific product are always displayed. In this way, by introducing a personalized dashboard based on the user's behavior history, the user can check the user's past inquiry history and solutions at a glance.

[0031] The portal installation unit can add a function that allows the generation AI to automatically generate FAQs and present relevant FAQs before the user enters their inquiry. For example, when a user begins to enter their inquiry, the portal installation unit allows the generation AI to automatically search for relevant FAQs and display them in real time. For example, if the user enters "network connection problems," relevant FAQs will be displayed. The portal installation unit also adds a function that allows the generation AI to analyze past inquiry data and automatically generate frequently asked questions. For example, it automatically generates FAQs related to specific error messages. The portal installation unit also allows the generation AI to suggest related FAQs when the user enters their inquiry, allowing the user to easily resolve their inquiry by selecting those FAQs. For example, it displays "Is this FAQ helpful?" This allows the generation AI to automatically generate FAQs and present relevant FAQs before the user enters their inquiry, allowing the user to quickly find a solution.

[0032] The portal installation unit may integrate a video chat function to enable a user to directly interact with an expert in real time as needed. For example, the portal installation unit may add a video chat function to a customer portal to enable a user to interact with an expert in real time. For example, when a technical problem occurs, the user can talk directly with an expert to get a solution. The portal installation unit may also use the video chat function to enable a user to receive direct advice from an expert on how to use or troubleshoot a product. For example, the user may receive instructions on how to configure a product in real time. The portal installation unit may also integrate the video chat function to provide a user with an option to directly interact with an expert as needed when entering an inquiry. For example, a "Consult an expert via video chat" button may be displayed. Thus, by integrating the video chat function, the user can interact with an expert in real time as needed.

[0033] The portal installation unit sets up a community forum where users can share information with each other, and the generation AI can analyze the information in the forum and reflect it in responses. The portal installation unit, for example, sets up a community forum on a customer-only portal to provide a place where users can share information with each other. For example, users can post information on how to use a product or troubleshooting. The portal installation unit also has the generation AI analyze posts in the community forum and reflect this in responses to user inquiries. For example, it automatically extracts related solutions from past posts. The portal installation unit also has the generation AI automatically generate frequently asked questions and solutions based on user posts in the community forum and display them in the portal. For example, it displays a message saying, "Here is the solution to this problem." In this way, a community forum where users can share information with each other can be set up, and the generation AI analyzes that information and reflects it in responses, thereby providing a wider variety of solutions.

[0034] The AI ​​prompt generation unit can analyze the user's input and dynamically generate optimal check items based on past similar inquiry data. For example, the generation AI of the AI ​​prompt generation unit analyzes the user's input and automatically generates optimal check items based on past similar inquiry data. For example, it displays a prompt such as, "Please provide additional information regarding this problem." Furthermore, when a user enters an inquiry, the generation AI analyzes past data and dynamically presents related check items. For example, it displays a prompt such as, "Please provide details regarding this error message." Furthermore, the AI ​​prompt generation unit builds a system in which the generation AI analyzes the user's input in real time and dynamically generates optimal check items. For example, it displays a prompt such as, "Please provide details regarding the circumstances under which this problem occurred." In this way, by analyzing the user's input and dynamically generating optimal check items based on past similar inquiry data, the user can quickly provide the information they need.

[0035] The AI ​​prompt generation unit can add a function that analyzes a user's input speed and typing pattern, estimates the user's stress level, and adjusts prompts accordingly. For example, the AI ​​prompt generation unit adds a function that analyzes a user's input speed and typing pattern and estimates the user's stress level. For example, if the input is slow, a simple prompt is displayed. The AI ​​prompt generation unit also builds a system that monitors the user's input speed and typing pattern in real time and adjusts prompts to estimate the stress level. For example, if stress is high, an encouraging message is displayed. The AI ​​prompt generation unit also adds a function that estimates the user's stress level and dynamically adjusts the content and display method of the prompt. For example, if stress is low, detailed confirmation items are displayed. In this way, the AI ​​prompt generation unit analyzes the user's input speed and typing pattern, estimates the stress level, and adjusts prompts, thereby reducing the user's stress.

[0036] The AI ​​prompt generation unit can add a voice input function to the confirmation item input process, allowing the user to input the confirmation items by voice. For example, the AI ​​prompt generation unit adds a voice input function to the confirmation item input process, allowing the user to input the confirmation items by voice. For example, it displays a prompt such as, "Please tell me the product model number by voice." The AI ​​prompt generation unit also uses the voice input function to build a system in which, when the user inputs the confirmation items by voice, the generation AI analyzes the content and generates an appropriate response. For example, it displays a message such as, "Please tell me the error message by voice." The AI ​​prompt generation unit also adds a voice input function, allowing the user to input the confirmation items by voice, thereby reducing the effort required for input. For example, it displays a prompt such as, "Please tell me more about this problem by voice." In this way, adding the voice input function to the confirmation item input process allows the user to input the confirmation items by voice, thereby reducing the effort required for input.

[0037] The AI ​​prompt generation unit adds a function that allows users to upload images and videos to the confirmation item input process, allowing the generation AI to generate answers based on visual information. For example, the AI ​​prompt generation unit adds a function that allows users to upload images and videos to the confirmation item input process, allowing the user to provide visual information. For example, it displays a prompt such as, "Please upload a screenshot of the problem." The AI ​​prompt generation unit also uses the image and video upload function to build a system in which the generation AI analyzes the visual information and generates an appropriate answer. For example, it displays a prompt such as, "Please upload a photo of the product." The AI ​​prompt generation unit also allows users to upload images and videos, allowing the generation AI to generate answers based on visual information. For example, it displays a prompt such as, "Please upload a video about this problem." By adding a function that allows users to upload images and videos to the confirmation item input process, the generation AI can generate answers based on visual information and provide more specific solutions.

[0038] The generation AI answer unit can provide a more personalized answer by referring to the user's past inquiry history and solutions. For example, the generation AI answer unit references the user's past inquiry history and generates a personalized answer based on solutions to similar inquiries. For example, it provides an answer based on a history of solving the same problem in the past. The generation AI answer unit also analyzes the user's past inquiry history and generates a personalized answer based on specific patterns and trends. For example, if there are many inquiries about a specific product, it provides an answer specialized for that product. The generation AI answer unit also references the user's past solutions to provide a more specific and personalized answer. For example, it generates an answer based on troubleshooting steps that have been used to solve problems in the past. In this way, it is possible to provide a more personalized answer by referring to the user's past inquiry history and solutions.

[0039] The generation AI answer unit can improve the accuracy of answers by referring to related external data sources. For example, the generation AI may refer to official product documentation and generate answers based on accurate information. For example, it may provide answers based on product manuals and technical specifications. The generation AI answer unit may also analyze user reviews and generate answers based on actual usage experience. For example, it may provide answers based on how other users solved the same problem. The generation AI answer unit may also integrate external data sources to build a system in which the generation AI generates more accurate answers. For example, it may provide answers by combining official documentation and user reviews. This improves the accuracy of answers by referring to related external data sources.

[0040] The generation AI answer section can present multiple answer options for the user to choose from, allowing the user to select the most appropriate answer. For example, the generation AI answer section generates multiple answer options and allows the user to select the most appropriate answer. For example, it displays "The following solutions to this problem are available. Which one is most appropriate?" The generation AI answer section also presents multiple answer options for the user to choose from, building a system that provides the optimal answer based on the user's selection. For example, it displays "Please select from the options below." The generation AI answer section also achieves a more personalized response by presenting multiple answer options for the user to choose the most appropriate answer. For example, it displays "The following solutions to this problem are available. Which one is most appropriate?" This allows the user to select the most appropriate answer by presenting multiple answer options for the user to choose from.

[0041] The generation AI answer unit can visualize the answer content and provide it in infographics or video format. For example, when the generation AI generates an answer, the generation AI answer unit visualizes the answer content and provides it as infographics. For example, it shows the steps to solve a problem in diagrams. The generation AI answer unit also provides the answer content in video format to make it easier for users to understand visually. For example, it explains how to set up a product in a video. The generation AI answer unit also builds a system in which the generation AI visualizes the answer and allows users to intuitively understand. For example, it provides answers using infographics or videos. In this way, by visualizing the answer content and providing it in infographics or video format, it makes it easier for users to intuitively understand.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The portal installation unit can introduce a personalized dashboard based on the user's behavior history, allowing the user to check their past inquiry history and solutions at a glance. For example, when logging in to a customer-specific portal, past inquiry history and solutions can be displayed on the dashboard. A list of troubleshooting issues that have been resolved in the past is displayed. The portal installation unit also displays personalized frequently asked questions and related solutions based on the user's behavior history. Questions that many users have searched for in the past are displayed preferentially. The portal installation unit also adds a function to automatically pin FAQs and solutions that the user has viewed in the past to the dashboard. FAQs related to specific products are always displayed. In this way, by introducing a personalized dashboard based on the user's behavior history, the user can check their past inquiry history and solutions at a glance.

[0044] The portal setup unit can add a function that enables the generation AI to automatically generate FAQs and present relevant FAQs before the user enters their inquiry. For example, when a user begins to enter their inquiry, the generation AI automatically searches for relevant FAQs and displays them in real time. If the user enters "network connection problems," relevant FAQs will be displayed. The portal setup unit also adds a function that enables the generation AI to analyze past inquiry data and automatically generate frequently asked questions. FAQs related to specific error messages are automatically generated. The portal setup unit also enables the generation AI to suggest relevant FAQs when the user enters their inquiry, allowing the user to easily resolve their inquiry by selecting that FAQ. It displays the message, "Is this FAQ helpful?" This allows the generation AI to automatically generate FAQs and present relevant FAQs before the user enters their inquiry, allowing the user to quickly find a solution.

[0045] The portal installation unit may integrate a video chat function to enable users to directly interact with experts in real time, as needed. For example, a video chat function may be added to a customer portal to enable users to interact with experts in real time. When a technical problem occurs, users can speak directly with an expert to get a solution. The portal installation unit may also use the video chat function to enable users to receive direct advice from experts on how to use and troubleshoot a product. Users may receive instructions on how to configure the product in real time. The portal installation unit may also integrate a video chat function to provide users with the option to directly interact with an expert when entering a query, as needed. A "Consult an expert via video chat" button may be displayed. Thus, by integrating the video chat function, users may interact with experts in real time, as needed.

[0046] The portal installation unit sets up a community forum where users can share information with each other, and the generation AI can analyze the information in the forum and reflect it in its answers. For example, a community forum can be set up on a customer-only portal to provide a place for users to share information with each other. Information on how to use the product and troubleshooting can be posted. The portal installation unit also has the generation AI analyze posts in the community forum and reflect this in answers to users' inquiries. Relevant solutions are automatically extracted from past posts. The portal installation unit also has the generation AI automatically generate frequently asked questions and solutions based on users' posts in the community forum, and display them in the portal. It displays a message saying, "Here is the solution to this problem." In this way, a community forum can be set up where users can share information with each other, and the generation AI analyzes that information and reflects it in answers, making it possible to provide a wider variety of solutions.

[0047] The AI ​​prompt generation unit can analyze the user's input and dynamically generate optimal check items based on past similar inquiry data. For example, the generation AI analyzes the user's input and automatically generates optimal check items based on past similar inquiry data. It displays a prompt such as, "Please provide additional information about this problem." In addition, when a user enters an inquiry, the AI ​​prompt generation unit analyzes past data and dynamically presents related check items. It displays a prompt such as, "Please provide more details about this error message." In addition, the AI ​​prompt generation unit builds a system in which the generation AI analyzes the user's input in real time and dynamically generates optimal check items. It displays a prompt such as, "Please provide more details about the circumstances under which this problem occurred." In this way, by analyzing the user's input and dynamically generating optimal check items based on past similar inquiry data, the user can quickly provide the information they need.

[0048] The AI ​​prompt generation unit can add a voice input function to the confirmation item input process, allowing the user to input confirmation items by voice. For example, adding a voice input function to the confirmation item input process allows the user to input confirmation items by voice. A prompt such as "Please tell me the product model number by voice" is displayed. The AI ​​prompt generation unit also uses the voice input function to build a system in which, when the user inputs confirmation items by voice, the generation AI analyzes the content and generates an appropriate response. A prompt such as "Please tell me the error message by voice" is displayed. The AI ​​prompt generation unit also adds a voice input function, allowing the user to input confirmation items by voice, reducing the effort required for input. A prompt such as "Please tell me more about this problem by voice" is displayed. In this way, adding a voice input function to the confirmation item input process allows the user to input confirmation items by voice, reducing the effort required for input.

[0049] The AI ​​prompt generation unit adds a function that allows users to upload images and videos to the confirmation item input process, allowing the generation AI to generate answers based on visual information. For example, adding a function that allows users to upload images and videos to the confirmation item input process allows users to provide visual information. A prompt such as "Please upload a screenshot of the problem" is displayed. The AI ​​prompt generation unit also uses the image and video upload function to build a system in which the generation AI analyzes the visual information and generates appropriate answers. A prompt such as "Please upload a photo of the product" is displayed. The AI ​​prompt generation unit also allows users to upload images and videos, allowing the generation AI to generate answers based on visual information. A prompt such as "Please upload a video about this problem" is displayed. By adding a function that allows users to upload images and videos to the confirmation item input process, the generation AI can generate answers based on visual information and provide more specific solutions.

[0050] The generation AI answer section can provide more personalized answers by referencing the user's past inquiry history and solutions. For example, the generation AI can refer to the user's past inquiry history and generate a personalized answer based on solutions to similar inquiries. Answers are provided based on a history of solving the same problem in the past. The generation AI answer section can also analyze the user's past inquiry history and generate personalized answers based on specific patterns and trends. If there are many inquiries about a particular product, answers specific to that product can be provided. The generation AI answer section can also refer to the user's past solutions to provide more specific and personalized answers. Answers are generated based on troubleshooting steps that have been used to solve problems in the past. In this way, more personalized answers can be provided by referencing the user's past inquiry history and solutions.

[0051] The generation AI answer section can improve the accuracy of answers by referencing relevant external data sources. For example, the generation AI may refer to the official product documentation and generate answers based on accurate information. Answers are provided based on the product's manual and technical specifications. The generation AI answer section may also analyze user reviews and generate answers based on actual usage experience. Answers are provided based on how other users have solved the same problem. The generation AI answer section may also integrate external data sources to build a system where the generation AI generates more accurate answers. Answers are provided by combining official documentation and user reviews. This improves the accuracy of answers by referencing relevant external data sources.

[0052] The generation AI answer section can present multiple answer options for the user to choose from, allowing the user to select the most appropriate answer. For example, the generation AI can generate multiple answer options and allow the user to select the most appropriate answer, displaying "The following are solutions to this problem. Which one is most appropriate?" The generation AI answer section can also present multiple answer options for the user to choose from, building a system that provides the optimal answer based on the user's selection, displaying "Please choose from the options below." The generation AI answer section can also achieve a more personalized response by presenting multiple answer options and allowing the user to select the most appropriate answer, displaying "The following are solutions to this problem. Which one is most appropriate?" This allows the user to select the most appropriate answer by presenting multiple answer options for the user to choose from.

[0053] The generation AI answer section can visualize the answer and provide it in infographics or video format. For example, when the generation AI generates an answer, it visualizes the answer and provides it as infographics. The steps to solve the problem are illustrated. The generation AI answer section also provides the answer in video format to make it easier for users to understand visually. A video is provided explaining how to set up the product. The generation AI answer section also builds a system in which the generation AI visualizes the answer and allows users to intuitively understand. Answers are provided using infographics or video. In this way, the answer can be visualized and provided in infographics or video format to make it easier for users to intuitively understand.

[0054] The processing flow of the first embodiment will be briefly explained below.

[0055] Step 1: The portal setup department sets up a dedicated portal for customers. For example, customers can access it through a web portal or a mobile application. The portal setup department can also centrally manage inquiries and store them in a database. Step 2: The AI ​​prompt generation unit generates an AI prompt for the customer to enter their inquiry in the portal installation unit. For example, it uses natural language processing technology to analyze the customer's input and present appropriate confirmation items. The AI ​​prompt generation unit can also dynamically generate prompts based on how the user input is analyzed. Step 3: The generation AI answer unit generates natural answers based on the prompts generated by the AI ​​prompt generation unit. For example, the generation AI generates answers taking into account grammatical accuracy and contextual suitability. The generation AI can also refer to past inquiry data to provide more appropriate answers.

[0056] (Example 2) The inquiry response system according to an embodiment of the present invention aggregates customer inquiries into a dedicated customer portal and uses a generation AI to provide natural answers. This enables the inquiry response system to efficiently process customer inquiries, reduce the man-hours required by the sales department, and minimize response delays.

[0057] An inquiry response system according to an embodiment includes a portal installation unit, an AI prompt generation unit, and a generation AI response unit. The portal installation unit installs a dedicated customer portal. For example, the portal installation unit allows customers to access the portal through a web portal or a mobile application. The portal installation unit can centrally manage inquiry content and store it in a database. The AI ​​prompt generation unit generates AI prompts for inputting customer inquiry content in the portal installation unit. For example, the AI ​​prompt generation unit analyzes the customer's input content using natural language processing technology and presents appropriate confirmation questions. The AI ​​prompt generation unit can dynamically generate prompts based on a method for analyzing the user input. The generation AI response unit generates natural responses based on the prompts generated by the AI ​​prompt generation unit. For example, the generation AI generates responses taking into account grammatical accuracy and contextual suitability. The generation AI can also refer to past inquiry data to provide more appropriate answers. As a result, the inquiry response system according to an embodiment can efficiently process customer inquiries, reduce sales workload, and minimize response delays. For example, the system can minimize internal checks based on the inquiry content and provide quick responses. The system can also store the inquiry content in a database to help improve future inquiry responses.

[0058] The portal installation unit can introduce a personalized dashboard based on the user's behavior history, allowing the user to check the user's past inquiry history and solutions at a glance. For example, the portal installation unit makes it so that when a user logs in to a customer-specific portal, the past inquiry history and solutions are displayed on the dashboard. For example, a list of troubleshooting history that has been resolved in the past is displayed. The portal installation unit also personalizes and displays frequently asked questions and related solutions based on the user's behavior history. For example, questions that many users have searched for in the past are displayed preferentially. The portal installation unit also adds a function to automatically pin FAQs and solutions that the user has viewed in the past to the dashboard. For example, FAQs related to a specific product are always displayed. In this way, by introducing a personalized dashboard based on the user's behavior history, the user can check the user's past inquiry history and solutions at a glance.

[0059] The portal installation unit can add a function that allows the generation AI to automatically generate FAQs and present relevant FAQs before the user enters their inquiry. For example, when a user begins to enter their inquiry, the portal installation unit allows the generation AI to automatically search for relevant FAQs and display them in real time. For example, if the user enters "network connection problems," relevant FAQs will be displayed. The portal installation unit also adds a function that allows the generation AI to analyze past inquiry data and automatically generate frequently asked questions. For example, it automatically generates FAQs related to specific error messages. The portal installation unit also allows the generation AI to suggest related FAQs when the user enters their inquiry, allowing the user to easily resolve their inquiry by selecting those FAQs. For example, it displays "Is this FAQ helpful?" This allows the generation AI to automatically generate FAQs and present relevant FAQs before the user enters their inquiry, allowing the user to quickly find a solution.

[0060] The portal installation unit can use the emotion estimation function to analyze the emotional state of the user when accessing the portal and dynamically change the interface design to reduce stress. For example, when the user accesses the portal, the portal installation unit analyzes the emotional state in real time using a camera or microphone and provides an interface design to reduce stress. For example, the portal installation unit changes the color and layout to a more relaxing one. Furthermore, the portal installation unit uses the emotion estimation function to display encouraging messages or relaxing content on the interface when the user is feeling stressed. For example, it displays "Please relax and proceed slowly." Furthermore, the portal installation unit simplifies the portal navigation and operation procedures according to the user's emotional state to reduce stress. For example, if the emotional state is negative, it reduces the number of operation procedures. In this way, the user's experience is improved by using the emotion estimation function to analyze the user's emotional state and dynamically changing the interface design to reduce stress.

[0061] The portal installation unit may integrate a video chat function to enable a user to directly interact with an expert in real time as needed. For example, the portal installation unit may add a video chat function to a customer portal to enable a user to interact with an expert in real time. For example, when a technical problem occurs, the user can talk directly with an expert to get a solution. The portal installation unit may also use the video chat function to enable a user to receive direct advice from an expert on how to use or troubleshoot a product. For example, the user may receive instructions on how to configure a product in real time. The portal installation unit may also integrate the video chat function to provide a user with an option to directly interact with an expert as needed when entering an inquiry. For example, a "Consult an expert via video chat" button may be displayed. Thus, by integrating the video chat function, the user can interact with an expert in real time as needed.

[0062] The portal installation unit sets up a community forum where users can share information with each other, and the generation AI can analyze the information in the forum and reflect it in responses. The portal installation unit, for example, sets up a community forum on a customer-only portal to provide a place where users can share information with each other. For example, users can post information on how to use a product or troubleshooting. The portal installation unit also has the generation AI analyze posts in the community forum and reflect this in responses to user inquiries. For example, it automatically extracts related solutions from past posts. The portal installation unit also has the generation AI automatically generate frequently asked questions and solutions based on user posts in the community forum and display them in the portal. For example, it displays a message saying, "Here is the solution to this problem." In this way, a community forum where users can share information with each other can be set up, and the generation AI analyzes that information and reflects it in responses, thereby providing a wider variety of solutions.

[0063] The portal installation unit can use the emotion estimation function to analyze emotions in response to inquiries entered into the portal by a user in real time and provide guidance for eliciting positive emotions. For example, when a user enters an inquiry into the portal, the portal installation unit uses the emotion estimation function to analyze emotions in real time and display guidance for eliciting positive emotions. For example, it displays, "If you have any problems, we will find a solution quickly." The portal installation unit also uses the emotion estimation function to display encouraging messages or advice for eliciting positive emotions when the user is feeling negative emotions. For example, it displays, "Don't worry, we will find a solution quickly." The portal installation unit also provides interactive guidance for eliciting positive emotions according to the user's emotional state. For example, if the user is feeling stressed, it displays relaxing content. In this way, the user's experience is improved by using the emotion estimation function to analyze the user's emotions in real time and providing guidance for eliciting positive emotions.

[0064] The AI ​​prompt generation unit can analyze the user's input and dynamically generate optimal check items based on past similar inquiry data. For example, the generation AI of the AI ​​prompt generation unit analyzes the user's input and automatically generates optimal check items based on past similar inquiry data. For example, it displays a prompt such as, "Please provide additional information regarding this problem." Furthermore, when a user enters an inquiry, the generation AI analyzes past data and dynamically presents related check items. For example, it displays a prompt such as, "Please provide details regarding this error message." Furthermore, the AI ​​prompt generation unit builds a system in which the generation AI analyzes the user's input in real time and dynamically generates optimal check items. For example, it displays a prompt such as, "Please provide details regarding the circumstances under which this problem occurred." In this way, by analyzing the user's input and dynamically generating optimal check items based on past similar inquiry data, the user can quickly provide the information they need.

[0065] The AI ​​prompt generation unit can add a function that analyzes a user's input speed and typing pattern, estimates the user's stress level, and adjusts prompts accordingly. For example, the AI ​​prompt generation unit adds a function that analyzes a user's input speed and typing pattern and estimates the user's stress level. For example, if the input is slow, a simple prompt is displayed. The AI ​​prompt generation unit also builds a system that monitors the user's input speed and typing pattern in real time and adjusts prompts to estimate the stress level. For example, if stress is high, an encouraging message is displayed. The AI ​​prompt generation unit also adds a function that estimates the user's stress level and dynamically adjusts the content and display method of the prompt. For example, if stress is low, detailed confirmation items are displayed. In this way, the AI ​​prompt generation unit analyzes the user's input speed and typing pattern, estimates the stress level, and adjusts prompts, thereby reducing the user's stress.

[0066] The AI ​​prompt generation unit can use the emotion estimation function to analyze the emotions a user feels when entering confirmation items and display a support message to alleviate negative emotions. For example, the AI ​​prompt generation unit uses the emotion estimation function to analyze the emotions a user feels when entering confirmation items in real time and display a support message to alleviate negative emotions. For example, it may display, "Please relax and enter." The AI ​​prompt generation unit also analyzes the user's emotional state and, if the user is feeling negative, displays an encouraging message or advice. For example, it may display, "It's okay, we'll find a solution right away." The AI ​​prompt generation unit also uses the emotion estimation function to display relaxing content or a support message if the user is feeling stressed. For example, it may display, "Take a deep breath and proceed slowly." In this way, the user experience is improved by using the emotion estimation function to analyze the user's emotions and displaying a support message to alleviate negative emotions.

[0067] The AI ​​prompt generation unit can add a voice input function to the confirmation item input process, allowing the user to input the confirmation items by voice. For example, the AI ​​prompt generation unit adds a voice input function to the confirmation item input process, allowing the user to input the confirmation items by voice. For example, it displays a prompt such as, "Please tell me the product model number by voice." The AI ​​prompt generation unit also uses the voice input function to build a system in which, when the user inputs the confirmation items by voice, the generation AI analyzes the content and generates an appropriate response. For example, it displays a message such as, "Please tell me the error message by voice." The AI ​​prompt generation unit also adds a voice input function, allowing the user to input the confirmation items by voice, thereby reducing the effort required for input. For example, it displays a prompt such as, "Please tell me more about this problem by voice." In this way, adding the voice input function to the confirmation item input process allows the user to input the confirmation items by voice, thereby reducing the effort required for input.

[0068] The AI ​​prompt generation unit adds a function that allows users to upload images and videos to the confirmation item input process, allowing the generation AI to generate answers based on visual information. For example, the AI ​​prompt generation unit adds a function that allows users to upload images and videos to the confirmation item input process, allowing the user to provide visual information. For example, it displays a prompt such as, "Please upload a screenshot of the problem." The AI ​​prompt generation unit also uses the image and video upload function to build a system in which the generation AI analyzes the visual information and generates an appropriate answer. For example, it displays a prompt such as, "Please upload a photo of the product." The AI ​​prompt generation unit also allows users to upload images and videos, allowing the generation AI to generate answers based on visual information. For example, it displays a prompt such as, "Please upload a video about this problem." By adding a function that allows users to upload images and videos to the confirmation item input process, the generation AI can generate answers based on visual information and provide more specific solutions.

[0069] The AI ​​prompt generation unit can use the emotion estimation function to analyze the emotions of the user when entering confirmation items in real time and provide interactive guidance to elicit positive emotions. For example, the AI ​​prompt generation unit uses the emotion estimation function to analyze the emotions of the user when entering confirmation items in real time and provide interactive guidance to elicit positive emotions. For example, it may display a message such as, "Please relax and enter." The AI ​​prompt generation unit may also analyze the user's emotional state and display encouraging messages or advice to elicit positive emotions. For example, it may display a message such as, "It's okay, we'll find a solution right away." The AI ​​prompt generation unit may also use the emotion estimation function to display relaxing content or support messages when the user is feeling stressed. For example, it may display a message such as, "Take a deep breath and proceed slowly." In this way, the user's experience is improved by using the emotion estimation function to analyze the user's emotions in real time and provide interactive guidance to elicit positive emotions.

[0070] The generation AI answer unit can provide a more personalized answer by referring to the user's past inquiry history and solutions. For example, the generation AI answer unit references the user's past inquiry history and generates a personalized answer based on solutions to similar inquiries. For example, it provides an answer based on a history of solving the same problem in the past. The generation AI answer unit also analyzes the user's past inquiry history and generates a personalized answer based on specific patterns and trends. For example, if there are many inquiries about a specific product, it provides an answer specialized for that product. The generation AI answer unit also references the user's past solutions to provide a more specific and personalized answer. For example, it generates an answer based on troubleshooting steps that have been used to solve problems in the past. In this way, it is possible to provide a more personalized answer by referring to the user's past inquiry history and solutions.

[0071] The generation AI answer unit can improve the accuracy of answers by referring to related external data sources. For example, the generation AI may refer to official product documentation and generate answers based on accurate information. For example, it may provide answers based on product manuals and technical specifications. The generation AI answer unit may also analyze user reviews and generate answers based on actual usage experience. For example, it may provide answers based on how other users solved the same problem. The generation AI answer unit may also integrate external data sources to build a system in which the generation AI generates more accurate answers. For example, it may provide answers by combining official documentation and user reviews. This improves the accuracy of answers by referring to related external data sources.

[0072] The generation AI answer unit can use the emotion estimation function to take into account the user's emotional state and provide an answer that the user can empathize with emotionally. The generation AI answer unit, for example, uses the emotion estimation function to analyze the user's emotional state in real time and generate an answer that the user can empathize with emotionally. For example, if the user is feeling stressed, an answer including an encouraging message is provided. The generation AI answer unit also builds a system that takes into account the user's emotional state and provides an answer that the generation AI can empathize with emotionally. For example, if the user is feeling anxious, an answer that gives a sense of security is provided. The generation AI answer unit also uses the emotion estimation function to generate an answer that corresponds to the user's emotions. For example, if the user is feeling happy, an answer including positive feedback is provided. In this way, the user's experience is improved by using the emotion estimation function to take into account the user's emotional state and provide an answer that the user can empathize with emotionally.

[0073] The generation AI answer section can present multiple answer options for the user to choose from, allowing the user to select the most appropriate answer. For example, the generation AI answer section generates multiple answer options and allows the user to select the most appropriate answer. For example, it displays "The following solutions to this problem are available. Which one is most appropriate?" The generation AI answer section also presents multiple answer options for the user to choose from, building a system that provides the optimal answer based on the user's selection. For example, it displays "Please select from the options below." The generation AI answer section also achieves a more personalized response by presenting multiple answer options for the user to choose the most appropriate answer. For example, it displays "The following solutions to this problem are available. Which one is most appropriate?" This allows the user to select the most appropriate answer by presenting multiple answer options for the user to choose from.

[0074] The generation AI answer unit can visualize the answer content and provide it in infographics or video format. For example, when the generation AI generates an answer, the generation AI answer unit visualizes the answer content and provides it as infographics. For example, it shows the steps to solve a problem in diagrams. The generation AI answer unit also provides the answer content in video format to make it easier for users to understand visually. For example, it explains how to set up a product in a video. The generation AI answer unit also builds a system in which the generation AI visualizes the answer and allows users to intuitively understand. For example, it provides answers using infographics or videos. In this way, by visualizing the answer content and providing it in infographics or video format, it makes it easier for users to intuitively understand.

[0075] The generation AI answer unit can use the emotion estimation function to monitor the user's emotional reactions in real time and dynamically adjust the content of the answer. For example, the generation AI answer unit uses the emotion estimation function to monitor the user's emotional reactions in real time when the generation AI generates an answer and dynamically adjust the content of the answer. For example, if the user is feeling anxious, an answer that gives a sense of security is provided. The generation AI answer unit also builds a system that monitors the user's emotional reactions in real time and adjusts the content of the answer based on that data. For example, if the user is feeling stressed, an answer including an encouraging message is provided. The generation AI answer unit also uses the emotion estimation function to generate answers according to the user's emotional reactions. For example, if the user is feeling happy, an answer including positive feedback is provided. In this way, the user's experience is improved by using the emotion estimation function to monitor the user's emotional reactions in real time and dynamically adjusting the content of the answer.

[0076] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0077] The portal installation unit can introduce a personalized dashboard based on the user's behavior history, allowing the user to check their past inquiry history and solutions at a glance. For example, when logging in to a customer-specific portal, past inquiry history and solutions can be displayed on the dashboard. A list of troubleshooting issues that have been resolved in the past is displayed. The portal installation unit also displays personalized frequently asked questions and related solutions based on the user's behavior history. Questions that many users have searched for in the past are displayed preferentially. The portal installation unit also adds a function to automatically pin FAQs and solutions that the user has viewed in the past to the dashboard. FAQs related to specific products are always displayed. In this way, by introducing a personalized dashboard based on the user's behavior history, the user can check their past inquiry history and solutions at a glance.

[0078] The portal setup unit can add a function that enables the generation AI to automatically generate FAQs and present relevant FAQs before the user enters their inquiry. For example, when a user begins to enter their inquiry, the generation AI automatically searches for relevant FAQs and displays them in real time. If the user enters "network connection problems," relevant FAQs will be displayed. The portal setup unit also adds a function that enables the generation AI to analyze past inquiry data and automatically generate frequently asked questions. FAQs related to specific error messages are automatically generated. The portal setup unit also enables the generation AI to suggest relevant FAQs when the user enters their inquiry, allowing the user to easily resolve their inquiry by selecting that FAQ. It displays the message, "Is this FAQ helpful?" This allows the generation AI to automatically generate FAQs and present relevant FAQs before the user enters their inquiry, allowing the user to quickly find a solution.

[0079] The portal installation unit uses the emotion estimation function to analyze the emotional state of the user when accessing the portal and dynamically change the interface design to reduce stress. For example, when the user accesses the portal, the emotional state is analyzed in real time using a camera or microphone, and an interface design to reduce stress is provided. The color and layout are changed to a more relaxing color scheme. The portal installation unit also uses the emotion estimation function to display encouraging messages or relaxing content on the interface if the user is feeling stressed, such as displaying "Please relax and proceed slowly." The portal installation unit also simplifies portal navigation and operation procedures according to the user's emotional state to reduce stress. If the emotional state is negative, the operation procedures are reduced. In this way, the user's experience is improved by using the emotion estimation function to analyze the user's emotional state and dynamically changing the interface design to reduce stress.

[0080] The portal installation unit may integrate a video chat function to enable users to directly interact with experts in real time, as needed. For example, a video chat function may be added to a customer portal to enable users to interact with experts in real time. When a technical problem occurs, users can speak directly with an expert to get a solution. The portal installation unit may also use the video chat function to enable users to receive direct advice from experts on how to use and troubleshoot a product. Users may receive instructions on how to configure the product in real time. The portal installation unit may also integrate a video chat function to provide users with the option to directly interact with an expert when entering a query, as needed. A "Consult an expert via video chat" button may be displayed. Thus, by integrating the video chat function, users may interact with experts in real time, as needed.

[0081] The portal installation unit sets up a community forum where users can share information with each other, and the generation AI can analyze the information in the forum and reflect it in its answers. For example, a community forum can be set up on a customer-only portal to provide a place for users to share information with each other. Information on how to use the product and troubleshooting can be posted. The portal installation unit also has the generation AI analyze posts in the community forum and reflect this in answers to users' inquiries. Relevant solutions are automatically extracted from past posts. The portal installation unit also has the generation AI automatically generate frequently asked questions and solutions based on users' posts in the community forum, and display them in the portal. It displays a message saying, "Here is the solution to this problem." In this way, a community forum can be set up where users can share information with each other, and the generation AI analyzes that information and reflects it in answers, making it possible to provide a wider variety of solutions.

[0082] The portal installation unit can use the emotion estimation function to analyze emotions in real time regarding the inquiry content entered by the user into the portal and provide guidance to elicit positive emotions. For example, when a user enters an inquiry content into the portal, the emotion estimation function is used to analyze emotions in real time and display guidance to elicit positive emotions, such as displaying "If you have any problems, we will find a solution quickly." The portal installation unit also uses the emotion estimation function to display encouraging messages and advice to elicit positive emotions when the user is feeling negative emotions, such as displaying "It's okay, we will find a solution quickly." The portal installation unit also provides interactive guidance to elicit positive emotions according to the user's emotional state, such as displaying relaxing content when the user is feeling stressed. In this way, the user's experience is improved by using the emotion estimation function to analyze the user's emotions in real time and providing guidance to elicit positive emotions.

[0083] The AI ​​prompt generation unit can analyze the user's input and dynamically generate optimal check items based on past similar inquiry data. For example, the generation AI analyzes the user's input and automatically generates optimal check items based on past similar inquiry data. It displays a prompt such as, "Please provide additional information about this problem." In addition, when a user enters an inquiry, the AI ​​prompt generation unit analyzes past data and dynamically presents related check items. It displays a prompt such as, "Please provide more details about this error message." In addition, the AI ​​prompt generation unit builds a system in which the generation AI analyzes the user's input in real time and dynamically generates optimal check items. It displays a prompt such as, "Please provide more details about the circumstances under which this problem occurred." In this way, by analyzing the user's input and dynamically generating optimal check items based on past similar inquiry data, the user can quickly provide the information they need.

[0084] The AI ​​prompt generation unit can add a function that analyzes a user's input speed and typing pattern, estimates the user's stress level, and adjusts the prompts accordingly. For example, a function can be added that analyzes a user's input speed and typing pattern to estimate the stress level. If the input is slow, a simple prompt can be displayed. The AI ​​prompt generation unit can also build a system that monitors the user's input speed and typing pattern in real time to estimate the stress level and adjusts the prompts accordingly. If the stress level is high, an encouraging message can be displayed. The AI ​​prompt generation unit can also add a function that estimates the user's stress level and dynamically adjusts the content and display method of the prompts. If the stress level is low, detailed confirmation items can be displayed. In this way, the system can analyze the user's input speed and typing pattern, estimate the stress level, and adjust the prompts accordingly, thereby reducing the user's stress.

[0085] The AI ​​prompt generation unit can add a voice input function to the confirmation item input process, allowing the user to input confirmation items by voice. For example, adding a voice input function to the confirmation item input process allows the user to input confirmation items by voice. A prompt such as "Please tell me the product model number by voice" is displayed. The AI ​​prompt generation unit also uses the voice input function to build a system in which, when the user inputs confirmation items by voice, the generation AI analyzes the content and generates an appropriate response. A prompt such as "Please tell me the error message by voice" is displayed. The AI ​​prompt generation unit also adds a voice input function, allowing the user to input confirmation items by voice, reducing the effort required for input. A prompt such as "Please tell me more about this problem by voice" is displayed. In this way, adding a voice input function to the confirmation item input process allows the user to input confirmation items by voice, reducing the effort required for input.

[0086] The AI ​​prompt generation unit adds a function that allows users to upload images and videos to the confirmation item input process, allowing the generation AI to generate answers based on visual information. For example, adding a function that allows users to upload images and videos to the confirmation item input process allows users to provide visual information. A prompt such as "Please upload a screenshot of the problem" is displayed. The AI ​​prompt generation unit also uses the image and video upload function to build a system in which the generation AI analyzes the visual information and generates appropriate answers. A prompt such as "Please upload a photo of the product" is displayed. The AI ​​prompt generation unit also allows users to upload images and videos, allowing the generation AI to generate answers based on visual information. A prompt such as "Please upload a video about this problem" is displayed. By adding a function that allows users to upload images and videos to the confirmation item input process, the generation AI can generate answers based on visual information and provide more specific solutions.

[0087] The AI ​​prompt generation unit can use the emotion estimation function to analyze the emotions a user feels when entering confirmation items and display a support message to alleviate negative emotions. For example, the emotion estimation function can be used to analyze the emotions a user feels when entering confirmation items in real time and display a support message to alleviate negative emotions, such as "Please relax and enter." The AI ​​prompt generation unit can also analyze the user's emotional state and display encouraging messages or advice if the user is feeling negative, such as "It's okay, we'll find a solution right away." The AI ​​prompt generation unit can also use the emotion estimation function to display relaxing content or support messages if the user is feeling stressed, such as "Take a deep breath and proceed slowly." This improves the user experience by using the emotion estimation function to analyze the user's emotions and displaying support messages to alleviate negative emotions.

[0088] The generation AI answer section can provide more personalized answers by referencing the user's past inquiry history and solutions. For example, the generation AI can refer to the user's past inquiry history and generate a personalized answer based on solutions to similar inquiries. Answers are provided based on a history of solving the same problem in the past. The generation AI answer section can also analyze the user's past inquiry history and generate personalized answers based on specific patterns and trends. If there are many inquiries about a particular product, answers specific to that product can be provided. The generation AI answer section can also refer to the user's past solutions to provide more specific and personalized answers. Answers are generated based on troubleshooting steps that have been used to solve problems in the past. In this way, more personalized answers can be provided by referencing the user's past inquiry history and solutions.

[0089] The generation AI answer section can improve the accuracy of answers by referencing relevant external data sources. For example, the generation AI may refer to the official product documentation and generate answers based on accurate information. Answers are provided based on the product's manual and technical specifications. The generation AI answer section may also analyze user reviews and generate answers based on actual usage experience. Answers are provided based on how other users have solved the same problem. The generation AI answer section may also integrate external data sources to build a system where the generation AI generates more accurate answers. Answers are provided by combining official documentation and user reviews. This improves the accuracy of answers by referencing relevant external data sources.

[0090] The generation AI answer unit can use the emotion estimation function to consider the user's emotional state and provide an emotionally empathetic answer. For example, the emotion estimation function is used to analyze the user's emotional state in real time and generate an emotionally empathetic answer. If the user is feeling stressed, an answer including an encouraging message is provided. The generation AI answer unit also considers the user's emotional state and builds a system in which the generation AI provides an emotionally empathetic answer. If the user is feeling anxious, an answer that gives a sense of security is provided. The generation AI answer unit also uses the emotion estimation function to generate an answer according to the user's emotions. If the user is feeling happy, an answer including positive feedback is provided. In this way, the user's experience is improved by using the emotion estimation function to consider the user's emotional state and provide an emotionally empathetic answer.

[0091] The generation AI answer section can present multiple answer options for the user to choose from, allowing the user to select the most appropriate answer. For example, the generation AI can generate multiple answer options and allow the user to select the most appropriate answer, displaying "The following are solutions to this problem. Which one is most appropriate?" The generation AI answer section can also present multiple answer options for the user to choose from, building a system that provides the optimal answer based on the user's selection, displaying "Please choose from the options below." The generation AI answer section can also achieve a more personalized response by presenting multiple answer options and allowing the user to select the most appropriate answer, displaying "The following are solutions to this problem. Which one is most appropriate?" This allows the user to select the most appropriate answer by presenting multiple answer options for the user to choose from.

[0092] The generation AI answer section can visualize the answer and provide it in infographics or video format. For example, when the generation AI generates an answer, it visualizes the answer and provides it as infographics. The steps to solve the problem are illustrated. The generation AI answer section also provides the answer in video format to make it easier for users to understand visually. A video is provided explaining how to set up the product. The generation AI answer section also builds a system in which the generation AI visualizes the answer and allows users to intuitively understand. Answers are provided using infographics or video. In this way, the answer can be visualized and provided in infographics or video format to make it easier for users to intuitively understand.

[0093] The generation AI answer unit can use the emotion estimation function to monitor the user's emotional reactions in real time and dynamically adjust the content of the answer. For example, using the emotion estimation function, the generation AI can monitor the user's emotional reactions in real time when generating an answer and dynamically adjust the content of the answer. If the user is feeling anxious, an answer that gives a sense of security is provided. The generation AI answer unit can also build a system that monitors the user's emotional reactions in real time and the generation AI adjusts the content of the answer based on that data. If the user is feeling stressed, an answer containing an encouraging message is provided. The generation AI answer unit can also use the emotion estimation function to generate an answer based on the user's emotional reactions. If the user is feeling happy, an answer containing positive feedback is provided. In this way, the user's experience is improved by using the emotion estimation function to monitor the user's emotional reactions in real time and dynamically adjusting the content of the answer.

[0094] The processing flow of the second embodiment will be briefly explained below.

[0095] Step 1: The portal setup department sets up a dedicated portal for customers. For example, customers can access it through a web portal or a mobile application. The portal setup department can also centrally manage inquiries and store them in a database. Step 2: The AI ​​prompt generation unit generates an AI prompt for the customer to enter their inquiry in the portal installation unit. For example, it uses natural language processing technology to analyze the customer's input and present appropriate confirmation items. The AI ​​prompt generation unit can also dynamically generate prompts based on how the user input is analyzed. Step 3: The generation AI answer unit generates natural answers based on the prompts generated by the AI ​​prompt generation unit. For example, the generation AI generates answers taking into account grammatical accuracy and contextual suitability. The generation AI can also refer to past inquiry data to provide more appropriate answers.

[0096] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0097] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0098] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0099] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0100] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0101] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0102] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0103] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0104] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0105] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0106] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0107] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0108] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0109] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0110] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0111] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0112] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0113] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0114] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0115] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0116] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0117] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0118] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0119] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0120] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0121] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0122] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0123] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0124] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0125] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0126] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0127] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0128] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0129] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0130] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0131] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0132] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0133] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0134] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0135] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0136] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0137] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0138] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0139] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0140] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0141] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0142] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0143] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0144] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0145] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0146] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0147] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0148] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0149] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0150] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0151] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0152] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0153] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0154] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0155] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0156] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0157] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0158] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0159] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0160] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0161] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0162] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0163] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a portal installation unit that installs a dedicated portal; an AI prompt generation unit that generates an AI prompt for inputting customer inquiry details in the portal installation unit; and an AI answer generation unit that generates a natural answer based on the prompt generated by the AI ​​prompt generation unit. A system characterized by:

2. The portal installation unit Add a function that automatically generates FAQs using AI and presents relevant FAQs before the user even types their query.

2. The system of claim 1.

3. The portal installation unit Integrate video chat functionality to allow users to interact directly with experts in real time when needed 2. The system of claim 1.

4. The AI ​​prompt generation unit: Analyzes user input and dynamically generates optimal confirmation questions based on past similar inquiry data 2. The system of claim 1.

5. The generation AI response unit: Refer to the user's past inquiry history and solutions to provide more personalized answers 2. The system of claim 1.

6. The portal installation unit Analyzes the emotional state of users when they access a portal and dynamically changes the interface design to reduce stress.

2. The system of claim 1.

7. The AI ​​prompt generation unit: Analyze the emotions of users when they enter their confirmation information and display support messages to reduce negative emotions.

2. The system of claim 1.

8. The generation AI response unit: Consider the user's emotional state and provide emotionally relatable answers 2. The system of claim 1.

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