system

Abstract

Provide a system. [Solution] a means for inputting basic information of a user; means for inputting information relating to a user's mental state; means for transmitting the user input information to a server; a means for generating counseling content using a generative artificial intelligence model based on the information in the server; means for providing the generated counseling content to the user; means for inputting feedback from the user; means for transmitting said feedback to a server; means for improving the generative artificial intelligence model based on the feedback; A system including:

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] Currently, patients with depression and other mental health conditions face many challenges when seeking psychological counseling. For example, it can take a long time to find an appropriate specialist, long waiting times, and a lack of immediate support tailored to individual needs. These issues can hinder patients' early recovery. Furthermore, existing counseling systems often do not effectively utilize patient feedback, and data for improving service quality is not fully utilized. Given this background, there is a need for a means to provide prompt, personalized counseling and utilize feedback to continuously improve the system. [Means for solving the problem]

[0005] The present invention provides a means for inputting basic information and information about a user's mental state, and a means for transmitting this information to a server. The server also includes a means for generating optimal counseling content using a generative artificial intelligence model based on the information. The generated counseling content is provided to the user and visually displayed. The system further includes a means for collecting feedback from the user and transmitting it to the server. The server stores the collected feedback and builds a database, thereby continuously improving the generative artificial intelligence model and providing more accurate counseling advice. The present invention enables patients with mental symptoms to receive prompt and personalized support, and the quality of the system is improved by utilizing feedback.

[0006] "User" refers to a person who uses the system.

[0007] "Basic information" refers to initial data for identifying a user, such as age, gender, and name.

[0008] "Mental state" refers to the user's current emotional and psychological well-being.

[0009] "Means" refers to a device or software component that performs a specific function or process.

[0010] "Server" refers to the computer system that receives and processes user input information and generates and provides counseling content.

[0011] A "generative artificial intelligence model" refers to a machine learning model that generates appropriate counseling content based on input data.

[0012] "Counseling content" refers to psychological support and advice provided to users.

[0013] "Feedback" refers to the user's evaluation or opinion of the counseling content provided.

[0014] "Database" means a structured collection of information for storing and managing collected feedback data and other information.

[0015] "Visual display" refers to providing information to users in an easy-to-read format using text, images, diagrams, etc.

[0016] "Continuous improvement" refers to the iterative process of improving the performance of a system or model based on collected data. [Brief explanation of the drawings]

[0017] [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. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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, a 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), and an APU (Accelerated Processing Unit).

[0021] 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.

[0022] 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.

[0023] 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), Bluetooth (registered trademark), etc.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[0029] 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.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. 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 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] ---

[0039] The present invention is a system for collecting basic information and information on a user's mental state, and generating and providing appropriate counseling content based on this information. A specific embodiment of this system will be described below.

[0040] Collection of User Information

[0041] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Taro Tanaka, 35 years old, male."

[0042] Input of user's mental state

[0043] The device then displays questions about the user's current mental state, such as "How are you feeling today?" and "How is the quality of your sleep these days?" The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[0044] Sending information

[0045] The device sends the collected user information and mental state information to the server, which receives the information and stores it in a database.

[0046] Counseling content generation

[0047] Based on the stored information, the server uses a generative artificial intelligence model to generate counseling content appropriate for the user's situation. For example, the server might send a request to the AI ​​model saying, "This user is feeling a little depressed and has poor sleep quality. Please generate appropriate counseling advice." The AI ​​model then generates advice such as, "Try deep breathing exercises to relax."

[0048] Providing counseling content

[0049] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "Try these deep breathing exercises to relax." Specific exercise methods may also be displayed along with illustrations.

[0050] User Feedback

[0051] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[0052] Sending and processing feedback

[0053] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server continuously improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[0054] Processing flow with concrete examples

[0055] For example, if a user is feeling anxious, the following flow may occur.

[0056] 1. The device asks the user, "How are you feeling today?"

[0057] 2. The user types, "I feel anxious."

[0058] 3. The device sends the input information to the server.

[0059] 4. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[0060] 5. The terminal displays the generated counseling content to the user.

[0061] 6. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[0062] 7. The device sends the feedback to the server.

[0063] 8. The server improves the AI ​​model based on the feedback and stores it in a database.

[0064] As can be seen, the present invention allows users to receive prompt and personalized counseling, and through feedback the quality of the system is continually improved.

[0065] The processing flow will be explained below.

[0066] Processing Steps

[0067] Step 1:

[0068] The device displays the initial user registration screen, where the user enters basic information such as name, age, and gender.

[0069] Step 2:

[0070] The user enters basic information, and the device sends this information to the server. Specifically, information such as "Name: Taro Tanaka," "Age: 35," and "Gender: Male" is sent to the server in JSON format.

[0071] Step 3:

[0072] The server stores the received basic information in a database, which creates a profile for the user.

[0073] Step 4:

[0074] The device will display questions about the user's current mental state, such as "How are you feeling today?" and "How has your sleep been lately?"

[0075] Step 5:

[0076] The user answers each question, for example, selecting "Mood: slightly depressed" and "Sleep quality: poor."

[0077] Step 6:

[0078] The device sends the user's answers to the server, also in JSON format.

[0079] Step 7:

[0080] The server inputs the received information into a generative AI model and instructs it to generate optimal counseling content. Specifically, the AI ​​model requests, "Please provide advice appropriate for a user who is feeling a little depressed and has poor quality sleep."

[0081] Step 8:

[0082] The server receives the response from the AI ​​model and sends the generated counseling content to the device, for example, "Try deep breathing exercises to relax."

[0083] Step 9:

[0084] The device displays the counseling content to the user, who then checks the content displayed on the screen and also looks at specific exercise methods.

[0085] Step 10:

[0086] The user practices the counseling provided, for example, by following the on-screen instructions to perform deep breathing exercises.

[0087] Step 11:

[0088] The user enters feedback about the effectiveness of the advice, for example, "The deep breathing exercises were very effective."

[0089] Step 12:

[0090] The device sends the user's feedback to the server, which is also sent in JSON format.

[0091] Step 13:

[0092] The server stores the feedback in a database, which is used to improve the generative artificial intelligence model.

[0093] Step 14:

[0094] The server uses the accumulated feedback to tune the AI ​​model and use it to generate the next counseling session. Specifically, the feedback data is passed through an analysis algorithm to retrain the model.

[0095] Through these steps, users are provided with fast, personalized counseling and the system is continually improved.

[0096] Example 1

[0097] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0098] Conventional counseling systems have had the problem of being difficult to provide individualized support tailored to the user's mental state. Furthermore, the mechanism for collecting feedback and using it to improve the system has not been fully established, limiting the improvement of the accuracy of the counseling content. Furthermore, the counseling content provided is sometimes difficult to understand visually, making it difficult for users to put the system into practice.

[0099] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0100] In this invention, the server includes means for inputting basic information and information about a user's mental state, means for transmitting the input information, means for generating counseling content using a generative AI model, means for visually providing the generated counseling content, means for displaying specific examples of the counseling content together with illustrations, means for inputting user feedback, means for transmitting the feedback, and means for improving the generative AI model based on the feedback. This makes it easier to provide personalized counseling content and for users to put it into practice, and enables continuous improvement of the system through collected feedback.

[0101] "Basic user information" refers to basic data for identifying an individual, such as the user's name, age, and gender.

[0102] "Information about mental state" is data that indicates the user's current psychological state, including mood, sleep quality, stress level, and the like.

[0103] A "server" is a computer system that receives, stores, processes, and transmits data.

[0104] A "generative artificial intelligence model" is an artificial intelligence algorithm that generates new information based on given data, and examples of this include language models such as GPT-3 (registered trademark).

[0105] "Counseling content" refers to advice and support information generated based on the user's mental state.

[0106] "Visual means" are ways of presenting information in a format that is easy for users to understand, such as text or illustrations.

[0107] "Feedback" refers to the user's opinions and impressions regarding the effectiveness and satisfaction of the counseling content provided.

[0108] A database is a system for organizing and storing information, and is constructed so that it can be searched and used efficiently later.

[0109] An "illustration" is an image or diagram that visually explains information.

[0110] The present invention is a system for collecting basic information and information on a user's mental state, and generating and providing appropriate counseling content based on this information. A specific embodiment of this system will be described below.

[0111] Collection of User Information

[0112] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[0113] Input of user's mental state

[0114] The device then displays questions about the user's current mental state, such as "How are you feeling today?" and "How is the quality of your sleep these days?" The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly irritable" and "Sleep quality: average."

[0115] Sending information

[0116] The device sends the collected user information and mental state information to the server, which receives the information and stores it in a database.

[0117] Counseling content generation

[0118] Based on the stored information, the server uses a generative artificial intelligence model (such as GPT-3) to generate counseling content appropriate for the user's situation. For example, the server sends a request to the AI ​​model saying, "This user is somewhat irritable and has average sleep quality. Please generate appropriate counseling advice." The AI ​​model generates advice such as, "Try yoga or meditation at the end of the day to relax."

[0119] Providing counseling content

[0120] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "To relax, try yoga or meditation at the end of the day." Specific exercise methods may also be displayed with illustrations.

[0121] User Feedback

[0122] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[0123] Sending and processing feedback

[0124] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server continuously improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[0125] Processing flow with concrete examples

[0126] For example, if a user is feeling stressed, the following flow may occur.

[0127] 1. The device asks the user, "How are you feeling today?"

[0128] 2. The user types, "I'm feeling stressed."

[0129] 3. The device sends the input information to the server.

[0130] 4. The server receives the information and generates counseling content based on the AI ​​model, such as "Try taking deep breaths and calming your mind to reduce stress."

[0131] 5. The terminal displays the generated counseling content to the user.

[0132] 6. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[0133] 7. The device sends the feedback to the server.

[0134] 8. The server improves the AI ​​model based on the feedback and stores it in a database.

[0135] As can be seen, the present invention allows users to receive prompt and personalized counseling, and through feedback the quality of the system is continually improved.

[0136] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0137] System program processing steps

[0138] Step 1:

[0139] User Action:

[0140] A user accesses the system using a terminal.

[0141] Input: The user enters basic information (such as name, age, and gender) into the device's initial setup screen.

[0142] Output: Basic information is displayed on the terminal.

[0143] Specific behavior: The device provides the user with input fields such as "What is your name?", "How old are you?", and "What is your gender?", and the user enters the information accordingly.

[0144] Step 2:

[0145] User Action:

[0146] The user inputs information about the mental state into the terminal.

[0147] Input: The user answers questions like "How are you feeling today?" and "How have you been sleeping lately?"

[0148] Output: Terminal displays information about mental state.

[0149] Specific operation: The device presents the user with multiple-choice questions such as "How are you feeling today?" and "How has your sleep been lately?", and the user selects an answer from multiple options.

[0150] Step 3:

[0151] The device:

[0152] The terminal transmits the collected basic information and information regarding mental state to a server.

[0153] Input: Basic information and mental state information entered by the user.

[0154] Output: User information sent to the server.

[0155] Specific operation: The terminal displays the message "Sending user information..." and sends the information entered by the user to the server.

[0156] Step 4:

[0157] The server:

[0158] The server receives the transmitted information and stores it in a database.

[0159] Input: Basic information and mental state information about the user sent from the device.

[0160] Output: User information stored in the database.

[0161] Specific operation: The server records a log message such as "User information saved" and stores the information in the "User Information" table in the database.

[0162] Step 5:

[0163] The server:

[0164] The server generates counseling content using a generative AI model based on the stored information.

[0165] Input: User information retrieved from the database.

[0166] Output: Generated counseling content.

[0167] Data processing: Generates a prompt sentence based on the input information and sends a request to the generative AI model.

[0168] Specific operation: The server generates a prompt message saying, "This user is slightly irritable and has average sleep quality. Please generate appropriate counseling advice," and sends it to the AI ​​model (e.g., GPT-3). The AI ​​model receives the advice and returns the counseling content, "Try yoga or meditation at the end of the day to relax," to the server.

[0169] Step 6:

[0170] The server:

[0171] The server transmits the generated counseling content to the terminal.

[0172] Input: Generated counseling content.

[0173] Output: Counseling content sent to the device.

[0174] Specific operation: The server displays the message "Sending counseling content..." and sends the generated content to the terminal.

[0175] Step 7:

[0176] The device:

[0177] The terminal visually displays the generated counseling content to the user.

[0178] Input: Counseling content sent from the server.

[0179] Output: Counseling content displayed on the terminal.

[0180] Specific action: The device displays a message on the user's screen saying, "Try yoga or meditation at the end of the day to relax," along with illustrations of specific exercise methods.

[0181] Step 8:

[0182] User Action:

[0183] The user practices the counseling content provided and provides feedback on its effectiveness.

[0184] Input: Counseling content implementation results and feedback.

[0185] Output: Feedback typed into the terminal.

[0186] Specific behavior: The user enters feedback such as "This advice was helpful" or "I was satisfied with the advice."

[0187] Step 9:

[0188] The device:

[0189] The terminal sends the user's feedback to the server.

[0190] Input: Feedback entered by the user.

[0191] Output: Feedback sent to the server.

[0192] Specific operation: The device displays the message "Sending feedback..." and sends the feedback data to the server.

[0193] Step 10:

[0194] The server:

[0195] The server receives the feedback and stores it in a database.

[0196] Input: Feedback sent from the device.

[0197] Output: Feedback stored in a database.

[0198] Specific behavior: The server records a log message such as "Feedback saved" and stores the feedback data in the "feedback" table in the database.

[0199] Step 11:

[0200] The server:

[0201] The server improves the generative artificial intelligence model based on the feedback.

[0202] Input: Feedback stored in the database.

[0203] Output: An improved generative artificial intelligence model.

[0204] Specific operation: The server uses the accumulated feedback as training data for the AI ​​model to improve the accuracy of the counseling content from the next time onwards.

[0205] Through the above steps, the present invention realizes a series of processes for generating and providing counseling content based on individual information of the user, and improving the system through feedback.

[0206] (Application example 1)

[0207] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0208] In modern society, prompt and individualized care for users' mental health is important, but existing systems make it difficult to quickly provide counseling tailored to each individual user. Furthermore, brick-and-mortar counseling services lack tools that allow staff to effectively assess users' mental states and provide appropriate advice. Furthermore, there is a need for a system that utilizes feedback from users to continuously improve the quality of counseling. The purpose of this invention is to solve these problems.

[0209] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0210] In this invention, the server includes means for inputting basic information about a user, means for inputting information about the user's mental state, means for transmitting the user's input information to the server, means for generating counseling content in the server using a generative artificial intelligence model based on the information, means for providing the generated counseling content to the user, means for inputting feedback from the user, means for transmitting the feedback to the server, means for improving the generative artificial intelligence model based on the feedback, and means for evaluating the user's mental state using an information terminal used by staff in a physical store and visually providing the counseling content displayed on the information terminal, thereby making it possible to provide prompt and personalized counseling even in a physical store.

[0211] "Means for inputting basic user information" refers to devices or software that provide an interface for users to input personal information such as their name, age, and gender.

[0212] The "means for inputting information about the user's mental state" refers to a device or software that provides an interface for the user to input their current mood or psychological state in the form of a question or the like.

[0213] The "means for transmitting user input information to the server" refers to a device or software for transmitting the basic information and mental state information input by the user to the server via a network.

[0214] "Means for generating counseling content using a generative artificial intelligence model" refers to software or algorithms that use generative AI to generate counseling content appropriate for individual users based on collected information.

[0215] The "means for providing the generated counseling content to the user" refers to a device or software for displaying the generated counseling content on the user's terminal.

[0216] The "means for allowing the user to input feedback" refers to a device or software that provides an interface for the user to input feedback such as the usefulness and satisfaction level of the counseling provided.

[0217] The "means for transmitting feedback to the server" refers to a device or software for transmitting the feedback information input by the user to the server via a network.

[0218] "Means for improving the generative artificial intelligence model based on feedback" refers to software or algorithms that use collected feedback information to update the generative AI model and improve it so that it can generate more appropriate and effective counseling content.

[0219] "Means for evaluating the mental state of a user using an information terminal used by staff in a physical store and visually providing counseling content displayed on the information terminal" refers to devices or software that evaluate the mental state of a customer using a terminal such as a smartphone or tablet used by staff in a physical store, and visually display and provide counseling content generated based on the evaluation results.

[0220] MODE FOR CARRYING OUT THE INVENTION

[0221] System Overview

[0222] This system collects basic information about the user and information about their mental state, and uses a generative AI model on the server to generate counseling content and provide it to the user. Furthermore, it can collect feedback and use it to improve the generative AI model.

[0223] Hardware and software used

[0224] Hardware: Smartphones, smart glasses, tablets, servers

[0225] Software: Python, Flask, TENSORFLOW (registered trademark), SQLite

[0226] System Operation

[0227] 1. User Information Collection:

[0228] Users access the system using a device such as a smartphone or tablet, which displays an interface that prompts them to enter basic information such as their name, age, and gender.

[0229] Example: A user enters the information "Taro Tanaka, 35 years old, male."

[0230] 2. Mental state input:

[0231] The device also displays questions about your mental state, such as "How are you feeling today?" and "How has your sleep been lately?"

[0232] Example: User responds "Mood: Slightly depressed" and "Sleep quality: Poor."

[0233] 3. Transmission of information to the server:

[0234] The device sends the collected user information and mental state information to the server, which receives the information and stores it in an SQLite database.

[0235] 4. Counseling content generation:

[0236] Based on the stored information, the server sends a request to a generative artificial intelligence model using TensorFlow to generate appropriate counseling content.

[0237] Example: Generate advice such as "This user is feeling a bit depressed and has poor sleep quality. Try some deep breathing exercises to relax."

[0238] 5. Provision of counseling content:

[0239] The server transmits the generated counseling content to the terminal, which visually displays the generated counseling content to the user.

[0240] Example: The device displays "Try this deep breathing exercise to relax" on the user's screen.

[0241] 6. User Feedback:

[0242] Users put the provided counseling into practice and provide feedback on its effectiveness, including comments such as "The advice was helpful" and "I would like to use this service again."

[0243] 7. Submitting Feedback:

[0244] The device sends the collected feedback to a server, which receives it and stores it in a database. This feedback is used to continuously improve the generative AI model.

[0245] For example, enter your feedback as "Satisfied: 4 / 5" and "Helpful" and submit.

[0246] Specific prompt examples

[0247] Example prompt sentence:

[0248] "How are users feeling?"

[0249] "How's your sleep quality lately?"

[0250] "Try some deep breathing exercises to help you relax."

[0251] In this way, by linking various data inputs tailored to the purpose with generative AI models, it is possible to provide practical and valuable counseling content to users. Furthermore, by continuously improving the system using feedback, it is possible to achieve even more accurate counseling.

[0252] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0253] Step 1:

[0254] Collection of User Information

[0255] Users access the system using a smartphone or tablet. They enter basic information such as their name, age, and gender into the input interface. The device collects the input data and compiles it into a format that can be sent to the server.

[0256] Input: Basic user information such as name, age, and gender

[0257] Processing: The device formats the collected information

[0258] Output: User basic information formatted to send to the server

[0259] Step 2:

[0260] Mental state input

[0261] The device asks the user questions about their mental state, such as "How are you feeling today?" or "How has your sleep been lately?" The user selects the appropriate answer for each question.

[0262] Input: Information about your mental state, such as how you're feeling today and the quality of your recent sleep

[0263] Processing: The device collects the user's answers and formats them into a format that can be sent to the server.

[0264] Output: Formatted mental state information to send to the server

[0265] Step 3:

[0266] Sending information to the server

[0267] The device sends the collected user information and mental state information to a server, which receives the information and stores it in an SQLite database.

[0268] Input: User basic information and mental state information

[0269] Processing: The device sends the information to the server, which stores it in a database

[0270] Output: User basic information and mental state information stored in the database

[0271] Step 4:

[0272] Counseling content generation

[0273] Based on the information stored in the database, the server sends a request to a generative artificial intelligence model using TensorFlow to generate appropriate counseling content.

[0274] Input: User basic information and mental state information

[0275] Processing: The server inputs information into the generative AI model, which then generates counseling content.

[0276] Output: Generated counseling content

[0277] Step 5:

[0278] Providing counseling content

[0279] The server transmits the generated counseling content to the terminal, which visually displays the generated counseling content to the user.

[0280] Input: Generated counseling content

[0281] Processing: The server sends the counseling content to the terminal, and the terminal displays the content.

[0282] Output: Visually displayed counseling content

[0283] Step 6:

[0284] User Feedback

[0285] Users put the provided counseling into practice and provide feedback on its effectiveness, including comments such as "The advice was helpful" and "I would like to use this service again."

[0286] Input: Feedback on counseling content

[0287] Processing: The device collects the feedback and formats it to be sent to the server.

[0288] Output: Formatted feedback to send to the server

[0289] Step 7:

[0290] Send and save feedback

[0291] The device sends the collected feedback to a server, which receives it and stores it in a database. This feedback is used to continuously improve the generative AI model.

[0292] Input: Feedback

[0293] Processing: The server stores the feedback in a database and updates the generative AI model.

[0294] Output: Feedback and improved generative AI models stored in a database

[0295] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0296] ---

[0297] The present invention provides a system that collects basic information and information about a user's mental state, and further recognizes the user's emotions using an emotion engine, thereby providing more appropriate counseling content. Specific embodiments of this system are described below.

[0298] Collection of User Information

[0299] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[0300] Input of user's mental state

[0301] The device then displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[0302] Sending information

[0303] The device sends the collected basic information and information about mental state to a server, which receives the information and stores it in a database.

[0304] Emotion recognition

[0305] The device is equipped with an emotion engine that recognizes the user's emotions. The emotion engine recognizes emotion data by analyzing the user's facial expressions and tone of voice. For example, when a user speaks into the camera, emotions such as "anxiety" or "sadness" are recognized from their facial expressions.

[0306] Sending emotional data

[0307] The emotion data recognized by the emotion engine is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[0308] Counseling content generation

[0309] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate for the user's situation. For example, the server might send a request to the AI ​​model saying, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." The AI ​​model then generates advice such as, "Try deep breathing exercises to relax."

[0310] Providing counseling content

[0311] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "Try these deep breathing exercises to relax." Specific exercise methods may also be displayed along with illustrations.

[0312] User Feedback

[0313] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[0314] Sending and processing feedback

[0315] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server uses the accumulated feedback to improve the generative AI model and increase the accuracy of future counseling content.

[0316] Processing flow with concrete examples

[0317] For example, if a user is feeling anxious, the following flow may occur.

[0318] 1. The device asks the user, "How are you feeling today?"

[0319] 2. The user types, "I feel anxious."

[0320] 3. The device uses an emotion engine to recognize "anxiety" from the user's facial expression.

[0321] 4. The device sends the input information and emotion data to the server.

[0322] 5. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[0323] 6. The terminal displays the generated counseling content to the user.

[0324] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[0325] 8. The device sends the feedback to the server.

[0326] 9. The server improves the AI ​​model based on the feedback and stores it in a database.

[0327] As described above, the present invention allows users to receive prompt and personalized counseling, and by utilizing emotion data in addition, more accurate counseling content can be provided. The quality of the system is continuously improved through feedback.

[0328] The processing flow will be explained below.

[0329] Processing Steps

[0330] Step 1:

[0331] The terminal displays the initial user registration screen to the user, who enters basic information such as name, age, and gender.

[0332] Step 2:

[0333] The user enters basic information, and the device sends this information to the server, specifically, data such as name, age, and gender in JSON format.

[0334] Step 3:

[0335] The server stores the received basic information in a database, which creates a profile for the user.

[0336] Step 4:

[0337] The device will prompt the user with questions about their current mental state, such as "How are you feeling today?" or "How's the quality of your sleep lately?"

[0338] Step 5:

[0339] The user answers each question, for example, selecting "Mood: slightly depressed" and "Sleep quality: poor."

[0340] Step 6:

[0341] The device sends the user's answers to the server, also in JSON format.

[0342] Step 7:

[0343] The emotion engine installed in the device recognizes the user's emotions. Specifically, it uses the device's camera and microphone to analyze the user's facial expressions and tone of voice. For example, the emotion engine recognizes "anxiety."

[0344] Step 8:

[0345] The terminal transmits the emotion data to the server, along with the basic information and mental state data.

[0346] Step 9:

[0347] The server inputs the received information into a generative AI model and instructs it to generate optimal counseling content. Specifically, it requests, "This user is feeling a little depressed, has poor sleep quality, and is also feeling anxious. Please generate appropriate counseling advice."

[0348] Step 10:

[0349] The server receives the response from the AI ​​model and sends the generated counseling content to the device, for example, "Try deep breathing exercises to relax."

[0350] Step 11:

[0351] The device displays the counseling content to the user, who then checks the content displayed on the screen and also looks at specific exercise methods.

[0352] Step 12:

[0353] The user practices the counseling provided, for example, by following the on-screen instructions to perform deep breathing exercises.

[0354] Step 13:

[0355] The user enters feedback about the effectiveness of the advice, for example, "The deep breathing exercises were very effective."

[0356] Step 14:

[0357] The device sends the user's feedback to the server, which is also sent in JSON format.

[0358] Step 15:

[0359] The server stores the feedback in a database, which is used to improve the generative artificial intelligence model.

[0360] Step 16:

[0361] The server uses the accumulated feedback to tune the AI ​​model and use it to generate the next counseling session. Specifically, the feedback data is passed through an analysis algorithm to retrain the model.

[0362] Through these steps, the system provides users with fast and personalized counseling, and the system is continuously improved. By using emotion data recognized by the emotion engine, the system can provide more accurate counseling content.

[0363] Example 2

[0364] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0365] Conventional counseling systems only provide counseling content based on the user's basic information and mental state, and have the problem of difficulty in responding to the user's real-time emotional state. Therefore, there is a need to provide more accurate and personalized counseling by incorporating emotional data such as the user's facial expressions and tone of voice.

[0366] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting basic information about the user, means for inputting information about the user's mental state, means for analyzing the user's facial expression and tone of voice using a terminal equipped with an emotion analysis engine and recognizing emotion data, means for transmitting this to the server, means for generating counseling content based on this information using a generative AI model, means for visually providing the generated counseling content, means for inputting user feedback, means for transmitting the feedback to the server and storing it, and means for improving the generative AI model based on these. This makes it possible to provide personalized counseling that reflects the user's real-time emotion data.

[0367] "User" refers to an individual who uses the system.

[0368] "Basic Information" refers to personal data such as name, age, and gender provided by the User.

[0369] "Mental state information" is data about emotions and psychological states input by the user, including answers to questions such as "How are you feeling today?"

[0370] "Server" refers to a central computer system for processing and storing information on a network.

[0371] A "generative artificial intelligence model" refers to an artificial intelligence engine that generates responses such as counseling content based on user input information.

[0372] "Counseling content" refers to advice and instructions for the user generated by the generative artificial intelligence model.

[0373] "Feedback" refers to the user's opinions and thoughts regarding the counseling content provided.

[0374] "Emotion analysis engine" refers to software and hardware components for analyzing a user's facial expressions and tone of voice to recognize emotional data.

[0375] "Terminal" refers to a device (smartphone, tablet, PC, etc.) that a user uses to access the system.

[0376] "Database" refers to a system for systematically storing and managing information on a server.

[0377] The present invention provides a system that collects basic information and information about a user's mental state, and further recognizes the user's emotions using an emotion analysis engine, thereby providing more appropriate counseling content. Specific embodiments of this system are described below.

[0378] Collection of User Information

[0379] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and prompts the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[0380] Input of user's mental state

[0381] Next, the device displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, they might answer "Mood: slightly depressed" or "Sleep quality: poor."

[0382] Sending information

[0383] The user's basic information and mental state information are sent from the device to the server, which receives the information and stores it in a database.

[0384] Emotion recognition

[0385] The device is equipped with an emotion analysis engine that analyzes the user's facial expressions and tone of voice to recognize emotional data. For example, when a user speaks to the camera, emotions such as "anxiety" or "sadness" can be detected from their facial expressions.

[0386] Sending emotional data

[0387] The recognized emotion data is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[0388] Counseling content generation

[0389] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate for the user's situation. The prompt might be something like, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." Based on this prompt, the generative AI model (e.g., GPT-4 (registered trademark)) generates advice such as, "Try deep breathing exercises to relax."

[0390] Providing counseling content

[0391] The generated counseling content is sent from the server to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display "Try some deep breathing exercises to relax," along with specific exercise instructions along with diagrams.

[0392] User Feedback

[0393] The user puts the counseling provided into practice and provides feedback on its effectiveness, for example, "The advice was helpful."

[0394] Sending and processing feedback

[0395] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[0396] The process flow with concrete examples, for example, if the user is feeling anxious, is as follows:

[0397] 1. The device asks the user, "How are you feeling today?"

[0398] 2. The user types, "I feel anxious."

[0399] 3. The device uses an emotion analysis engine to recognize "anxiety" from the user's facial expression.

[0400] 4. The device sends the input information and emotion data to the server.

[0401] 5. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[0402] 6. The terminal displays the generated counseling content to the user.

[0403] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[0404] 8. The device sends the feedback to the server.

[0405] 9. The server improves the AI ​​model based on the feedback and stores it in a database.

[0406] As described above, the present invention allows users to receive prompt and personalized counseling. By also utilizing emotion data, more accurate counseling content is provided, and feedback allows for continuous improvement of the system's quality.

[0407] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0408] Step 1:

[0409] A user accesses the system using a terminal. The terminal displays an initial setup screen and prompts the user to enter basic information (such as name, age, and gender). When the user enters "Yamada Taro, 30 years old, male," the terminal temporarily stores this information. The entered basic information is sent to the server.

[0410] Step 2:

[0411] The device displays questions about the user's mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. If the user answers "Mood: slightly depressed" or "Sleep quality: poor," this information is also temporarily stored on the device. Information about the mental state is also sent to the server.

[0412] Step 3:

[0413] The server receives the basic information and mental state information sent from the device and stores it in a database. Specifically, data such as "User name: Yamada Taro," "Age: 30," "Mood: slightly depressed," and "Sleep quality: poor" are stored.

[0414] Step 4:

[0415] The emotion analysis engine installed in the device analyzes the user's facial expressions and tone of voice to recognize emotional data. For example, when a user speaks into the camera, the emotion analysis engine recognizes emotions such as "anxiety" or "sadness" from their facial expressions. The analyzed emotional data is temporarily stored on the device.

[0416] Step 5:

[0417] The device sends the recognized emotion data along with basic information and mental state data to the server. The server receives this and stores it in a database. Specifically, additional data such as "emotion: anxiety" is stored.

[0418] Step 6:

[0419] The server generates counseling content using a generative AI model based on the stored basic information, mental state information, and emotion data. The prompt text is, "This user is slightly depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." Based on this prompt text, the generative AI model generates advice such as, "Try deep breathing exercises to relax."

[0420] Step 7:

[0421] The server sends the generated counseling content to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal screen may display "Try deep breathing exercises for relaxation" along with illustrations of specific exercise methods.

[0422] Step 8:

[0423] The user puts the counseling provided into practice and inputs feedback about its effectiveness, such as "This advice was helpful."

[0424] Step 9:

[0425] The device sends the user's feedback to the server. The server receives the feedback and stores it in a database. The accumulated feedback is used to improve the generative AI model, helping to increase the quality of the system. For example, the AI ​​model will be able to generate more appropriate counseling content based on the user's feedback from the next time onwards.

[0426] (Application example 2)

[0427] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0428] Conventional counseling systems generate counseling content based only on the user's basic information and mental state, which limits their accuracy. Furthermore, they lack the means to recognize the user's emotions in real time, making it difficult to provide optimal counseling for each individual user. As a result, user satisfaction declines, and the effectiveness of the system is not fully realized.

[0429] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting basic information and information about the mental state of the user, means for analyzing the user's emotions, and means for generating counseling content using a generative artificial intelligence model based on the information and emotion analysis data. This makes it possible to provide personalized counseling content that reflects the user's current emotional state in real time.

[0430] "Basic user information" refers to personal identification information such as the user's name, age, and gender.

[0431] "Information about mental state" is information about the user's current mood and psychological state.

[0432] "Means for analyzing emotions" refers to technology or devices for recognizing and analyzing a user's emotions based on their facial expressions and tone of voice.

[0433] A "generative artificial intelligence model" is an artificial intelligence model that generates appropriate output, i.e., counseling content, based on input data.

[0434] "Counseling content" refers to advice and support provided according to the user's mental state and emotions.

[0435] "Feedback" refers to the user's evaluation and impressions of the counseling content provided.

[0436] A "server" is a computer system that receives input information from a user, processes it, and returns generated counseling content to the user.

[0437] A "database" is a storage system that stores collected user information and feedback so that it can be referenced as needed.

[0438] The "visual display means" refers to a display or other display device for providing the generated counseling content to the user in the form of text, images, or the like.

[0439] "User input information" refers to basic information and information relating to mental state that a user provides to the system.

[0440] The present invention provides a system that collects basic information and information about a user's mental state, recognizes emotions using an emotion engine, and provides more appropriate counseling content. Specific embodiments of this system are described below.

[0441] Collection of User Information

[0442] First, a user accesses the system using a smartphone application. When the user first accesses the system, the application prompts the user to enter basic information. This information includes name, age, and gender. For example, the user enters "Yamada Taro, 30 years old, male."

[0443] Input of user's mental state

[0444] The smartphone application also displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[0445] Sending information

[0446] The smartphone application sends the collected basic information and information about mental state to a server, which receives the information and stores it in a database.

[0447] Emotion recognition

[0448] The emotion engine uses the smartphone's camera and microphone to recognize the user's emotions. The emotion engine recognizes emotion data by analyzing the user's facial expressions and tone of voice. For example, when a user speaks into the camera, emotions such as "anxiety" or "sadness" are recognized from their facial expressions.

[0449] Sending emotional data

[0450] The emotion data recognized by the emotion engine is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[0451] Counseling content generation

[0452] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate for the user's situation. For example, the server sends a request to the generative AI model saying, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." The generative AI model then generates advice such as, "Try deep breathing exercises to relax."

[0453] Providing counseling content

[0454] The server receives the generated counseling content and sends it to a smartphone application. The application visually displays the generated counseling content to the user. For example, the device may display a message on the user's screen saying, "Try these deep breathing exercises to relax." Specific exercise instructions may also be displayed along with illustrations.

[0455] User Feedback

[0456] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[0457] Sending and processing feedback

[0458] The smartphone application collects user feedback and sends it to a server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server uses the accumulated feedback to improve the generative AI model and increase the accuracy of future counseling content.

[0459] Processing flow with concrete examples

[0460] For example, if a user is feeling anxious, the following flow may occur.

[0461] 1. A smartphone application asks the user, "How are you feeling today?"

[0462] 2. The user types, "I feel anxious."

[0463] 3. The smartphone's camera and microphone use an emotion engine to recognize "anxiety" from the user's facial expression.

[0464] 4. The smartphone application sends the input information and emotion data to the server.

[0465] 5. The server receives the information and generates counseling content based on a generative artificial intelligence model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[0466] 6. The smartphone application displays the generated counseling content to the user.

[0467] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[0468] 8. The smartphone application sends the feedback to the server.

[0469] 9. The server improves the generative AI model based on the feedback and stores it in a database.

[0470] To illustrate, here's an example prompt:

[0471] Customer is feeling anxious, provide suitable advice.

[0472] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0473] Step 1:

[0474] The user accesses the smartphone application and inputs basic information and information about their mental state.

[0475] Input: User inputs basic information (name, age, gender) and mental state (mood, sleep quality, etc.).

[0476] Output: Collected basic and mental status information data.

[0477] Specific operation: The user enters information according to the initial setup screen of the app, and the app temporarily saves that information.

[0478] Step 2:

[0479] The smartphone's camera and microphone are used to recognize the user's emotions. The emotion engine analyzes facial expressions and tone of voice to generate emotion data.

[0480] Input: User's facial expression video and audio data.

[0481] Output: Parsed emotion data (e.g., "anxiety", "sadness", etc.).

[0482] How it works: The app uses a camera and microphone to capture the user's facial expressions and voice in real time, and the emotion engine analyzes them.

[0483] Step 3:

[0484] The smartphone application sends the collected basic information, mental state information, and emotion data to a server.

[0485] Input: User's basic information, mental state information, and emotional data.

[0486] Output: All data sent to the server.

[0487] Specific operation: The app batches data into packets and sends them over the network to the server.

[0488] Step 4:

[0489] The server stores the received information in a database.

[0490] Input: Basic information, mental state information, emotional data.

[0491] Output: Information stored in a database.

[0492] Specific operation: The server analyzes the received data and stores it in the database in the appropriate format.

[0493] Step 5:

[0494] The server generates counseling content using a generative artificial intelligence model. Information is input as prompts to the model, and counseling content is output.

[0495] Input: Basic information, mental state information, emotion data. Prompt text: "This user is slightly depressed, has poor sleep quality, and is anxious according to the emotion engine. Please generate appropriate counseling advice."

[0496] Output: Generated counseling content.

[0497] Specific operation: The server sends a prompt to the generative artificial intelligence model, which generates appropriate counseling content.

[0498] Step 6:

[0499] The server sends the generated counseling content to the smartphone application.

[0500] Input: Generated counseling content.

[0501] Output: Counseling content sent to the smartphone application.

[0502] Specific operation: The server sends the generated counseling content to the app via the network.

[0503] Step 7:

[0504] A smartphone application visually displays the generated counseling content to the user.

[0505] Input: Counseling content submitted.

[0506] Output: The counseling content that the user sees.

[0507] Specific operation: The app displays the counseling content received in text and images.

[0508] Step 8:

[0509] Users put the provided counseling content into practice and enter the results into the app as feedback.

[0510] Input: User feedback information.

[0511] Output: Feedback input data.

[0512] Specific operation: The user performs the advice and enters the results in the app's feedback screen.

[0513] Step 9:

[0514] The smartphone application sends the user's feedback to a server.

[0515] Input: User feedback information.

[0516] Output: Feedback information sent to the server.

[0517] Specific operation: The app collects feedback information and compiles it into packets, which are then sent over the network to a server.

[0518] Step 10:

[0519] The server stores the received feedback in a database and uses a generative artificial intelligence model to improve the accuracy of future counseling sessions.

[0520] Input: User feedback information.

[0521] Output: Feedback information stored in a database, an improved generative artificial intelligence model.

[0522] Specific operation: The server stores the received feedback in a database and uses that data to learn and improve the generative artificial intelligence model.

[0523] 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.

[0524] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[0525] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0526] [Second embodiment]

[0527] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0528] 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.

[0529] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[0530] 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.

[0531] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0532] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0533] 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.

[0534] 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.

[0535] 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 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.

[0536] 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.

[0537] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0538] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0539] ---

[0540] The present invention is a system for collecting basic information and information on a user's mental state, and generating and providing appropriate counseling content based on this information. A specific embodiment of this system will be described below.

[0541] Collection of User Information

[0542] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Taro Tanaka, 35 years old, male."

[0543] Input of user's mental state

[0544] The device then displays questions about the user's current mental state, such as "How are you feeling today?" and "How is the quality of your sleep these days?" The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[0545] Sending information

[0546] The device sends the collected user information and mental state information to the server, which receives the information and stores it in a database.

[0547] Counseling content generation

[0548] Based on the stored information, the server uses a generative artificial intelligence model to generate counseling content appropriate for the user's situation. For example, the server might send a request to the AI ​​model saying, "This user is feeling a little depressed and has poor sleep quality. Please generate appropriate counseling advice." The AI ​​model then generates advice such as, "Try deep breathing exercises to relax."

[0549] Providing counseling content

[0550] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "Try these deep breathing exercises to relax." Specific exercise methods may also be displayed along with illustrations.

[0551] User Feedback

[0552] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[0553] Sending and processing feedback

[0554] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server continuously improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[0555] Processing flow with concrete examples

[0556] For example, if a user is feeling anxious, the following flow may occur.

[0557] 1. The device asks the user, "How are you feeling today?"

[0558] 2. The user types, "I feel anxious."

[0559] 3. The device sends the input information to the server.

[0560] 4. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[0561] 5. The terminal displays the generated counseling content to the user.

[0562] 6. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[0563] 7. The device sends the feedback to the server.

[0564] 8. The server improves the AI ​​model based on the feedback and stores it in a database.

[0565] As can be seen, the present invention allows users to receive prompt and personalized counseling, and through feedback the quality of the system is continually improved.

[0566] The processing flow will be explained below.

[0567] Processing Steps

[0568] Step 1:

[0569] The device displays the initial user registration screen, where the user enters basic information such as name, age, and gender.

[0570] Step 2:

[0571] The user enters basic information, and the device sends this information to the server. Specifically, information such as "Name: Taro Tanaka," "Age: 35," and "Gender: Male" is sent to the server in JSON format.

[0572] Step 3:

[0573] The server stores the received basic information in a database, which creates a profile for the user.

[0574] Step 4:

[0575] The device will display questions about the user's current mental state, such as "How are you feeling today?" and "How has your sleep been lately?"

[0576] Step 5:

[0577] The user answers each question, for example, selecting "Mood: slightly depressed" and "Sleep quality: poor."

[0578] Step 6:

[0579] The device sends the user's answers to the server, also in JSON format.

[0580] Step 7:

[0581] The server inputs the received information into a generative AI model and instructs it to generate optimal counseling content. Specifically, the AI ​​model requests, "Please provide advice appropriate for a user who is feeling a little depressed and has poor quality sleep."

[0582] Step 8:

[0583] The server receives the response from the AI ​​model and sends the generated counseling content to the device, for example, "Try deep breathing exercises to relax."

[0584] Step 9:

[0585] The device displays the counseling content to the user, who then checks the content displayed on the screen and also looks at specific exercise methods.

[0586] Step 10:

[0587] The user practices the counseling provided, for example, by following the on-screen instructions to perform deep breathing exercises.

[0588] Step 11:

[0589] The user enters feedback about the effectiveness of the advice, for example, "The deep breathing exercises were very effective."

[0590] Step 12:

[0591] The device sends the user's feedback to the server, which is also sent in JSON format.

[0592] Step 13:

[0593] The server stores the feedback in a database, which is used to improve the generative artificial intelligence model.

[0594] Step 14:

[0595] The server uses the accumulated feedback to tune the AI ​​model and use it to generate the next counseling session. Specifically, the feedback data is passed through an analysis algorithm to retrain the model.

[0596] Through these steps, users are provided with fast, personalized counseling and the system is continually improved.

[0597] Example 1

[0598] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0599] Conventional counseling systems have had the problem of being difficult to provide individualized support tailored to the user's mental state. Furthermore, the mechanism for collecting feedback and using it to improve the system has not been fully established, limiting the improvement of the accuracy of the counseling content. Furthermore, the counseling content provided is sometimes difficult to understand visually, making it difficult for users to put the system into practice.

[0600] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0601] In this invention, the server includes means for inputting basic information and information about a user's mental state, means for transmitting the input information, means for generating counseling content using a generative AI model, means for visually providing the generated counseling content, means for displaying specific examples of the counseling content together with illustrations, means for inputting user feedback, means for transmitting the feedback, and means for improving the generative AI model based on the feedback. This makes it easier to provide personalized counseling content and for users to put it into practice, and enables continuous improvement of the system through collected feedback.

[0602] "Basic user information" refers to basic data for identifying an individual, such as the user's name, age, and gender.

[0603] "Information about mental state" is data that indicates the user's current psychological state, including mood, sleep quality, stress level, and the like.

[0604] A "server" is a computer system that receives, stores, processes, and transmits data.

[0605] A "generative artificial intelligence model" is an artificial intelligence algorithm that generates new information based on given data, and examples of this include language models such as GPT-3.

[0606] "Counseling content" refers to advice and support information generated based on the user's mental state.

[0607] "Visual means" are ways of presenting information in a format that is easy for users to understand, such as text or illustrations.

[0608] "Feedback" refers to the user's opinions and impressions regarding the effectiveness and satisfaction of the counseling content provided.

[0609] A database is a system for organizing and storing information, and is constructed so that it can be searched and used efficiently later.

[0610] An "illustration" is an image or diagram that visually explains information.

[0611] The present invention is a system for collecting basic information and information on a user's mental state, and generating and providing appropriate counseling content based on this information. A specific embodiment of this system will be described below.

[0612] Collection of User Information

[0613] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[0614] Input of user's mental state

[0615] The device then displays questions about the user's current mental state, such as "How are you feeling today?" and "How is the quality of your sleep these days?" The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly irritable" and "Sleep quality: average."

[0616] Sending information

[0617] The device sends the collected user information and mental state information to the server, which receives the information and stores it in a database.

[0618] Counseling content generation

[0619] Based on the stored information, the server uses a generative artificial intelligence model (such as GPT-3) to generate counseling content appropriate for the user's situation. For example, the server sends a request to the AI ​​model saying, "This user is somewhat irritable and has average sleep quality. Please generate appropriate counseling advice." The AI ​​model generates advice such as, "Try yoga or meditation at the end of the day to relax."

[0620] Providing counseling content

[0621] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "To relax, try yoga or meditation at the end of the day." Specific exercise methods may also be displayed with illustrations.

[0622] User Feedback

[0623] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[0624] Sending and processing feedback

[0625] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server continuously improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[0626] Processing flow with concrete examples

[0627] For example, if a user is feeling stressed, the following flow may occur.

[0628] 1. The device asks the user, "How are you feeling today?"

[0629] 2. The user types, "I'm feeling stressed."

[0630] 3. The device sends the input information to the server.

[0631] 4. The server receives the information and generates counseling content based on the AI ​​model, such as "Try taking deep breaths and calming your mind to reduce stress."

[0632] 5. The terminal displays the generated counseling content to the user.

[0633] 6. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[0634] 7. The device sends the feedback to the server.

[0635] 8. The server improves the AI ​​model based on the feedback and stores it in a database.

[0636] As can be seen, the present invention allows users to receive prompt and personalized counseling, and through feedback the quality of the system is continually improved.

[0637] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0638] System program processing steps

[0639] Step 1:

[0640] User Action:

[0641] A user accesses the system using a terminal.

[0642] Input: The user enters basic information (such as name, age, and gender) into the device's initial setup screen.

[0643] Output: Basic information is displayed on the terminal.

[0644] Specific behavior: The device provides the user with input fields such as "What is your name?", "How old are you?", and "What is your gender?", and the user enters the information accordingly.

[0645] Step 2:

[0646] User Action:

[0647] The user inputs information about the mental state into the terminal.

[0648] Input: The user answers questions like "How are you feeling today?" and "How have you been sleeping lately?"

[0649] Output: Terminal displays information about mental state.

[0650] Specific operation: The device presents the user with multiple-choice questions such as "How are you feeling today?" and "How has your sleep been lately?", and the user selects an answer from multiple options.

[0651] Step 3:

[0652] The device:

[0653] The terminal transmits the collected basic information and information regarding mental state to a server.

[0654] Input: Basic information and mental state information entered by the user.

[0655] Output: User information sent to the server.

[0656] Specific operation: The terminal displays the message "Sending user information..." and sends the information entered by the user to the server.

[0657] Step 4:

[0658] The server:

[0659] The server receives the transmitted information and stores it in a database.

[0660] Input: Basic information and mental state information about the user sent from the device.

[0661] Output: User information stored in the database.

[0662] Specific operation: The server records a log message such as "User information saved" and stores the information in the "User Information" table in the database.

[0663] Step 5:

[0664] The server:

[0665] The server generates counseling content using a generative AI model based on the stored information.

[0666] Input: User information retrieved from the database.

[0667] Output: Generated counseling content.

[0668] Data processing: Generates a prompt sentence based on the input information and sends a request to the generative AI model.

[0669] Specific operation: The server generates a prompt message saying, "This user is slightly irritable and has average sleep quality. Please generate appropriate counseling advice," and sends it to the AI ​​model (e.g., GPT-3). The AI ​​model receives the advice and returns the counseling content, "Try yoga or meditation at the end of the day to relax," to the server.

[0670] Step 6:

[0671] The server:

[0672] The server transmits the generated counseling content to the terminal.

[0673] Input: Generated counseling content.

[0674] Output: Counseling content sent to the device.

[0675] Specific operation: The server displays the message "Sending counseling content..." and sends the generated content to the terminal.

[0676] Step 7:

[0677] The device:

[0678] The terminal visually displays the generated counseling content to the user.

[0679] Input: Counseling content sent from the server.

[0680] Output: Counseling content displayed on the terminal.

[0681] Specific action: The device displays a message on the user's screen saying, "Try yoga or meditation at the end of the day to relax," along with illustrations of specific exercise methods.

[0682] Step 8:

[0683] User Action:

[0684] The user practices the counseling content provided and provides feedback on its effectiveness.

[0685] Input: Counseling content implementation results and feedback.

[0686] Output: Feedback typed into the terminal.

[0687] Specific behavior: The user enters feedback such as "This advice was helpful" or "I was satisfied with the advice."

[0688] Step 9:

[0689] The device:

[0690] The terminal sends the user's feedback to the server.

[0691] Input: Feedback entered by the user.

[0692] Output: Feedback sent to the server.

[0693] Specific operation: The device displays the message "Sending feedback..." and sends the feedback data to the server.

[0694] Step 10:

[0695] The server:

[0696] The server receives the feedback and stores it in a database.

[0697] Input: Feedback sent from the device.

[0698] Output: Feedback stored in a database.

[0699] Specific behavior: The server records a log message such as "Feedback saved" and stores the feedback data in the "feedback" table in the database.

[0700] Step 11:

[0701] The server:

[0702] The server improves the generative artificial intelligence model based on the feedback.

[0703] Input: Feedback stored in the database.

[0704] Output: An improved generative artificial intelligence model.

[0705] Specific operation: The server uses the accumulated feedback as training data for the AI ​​model to improve the accuracy of the counseling content from the next time onwards.

[0706] Through the above steps, the present invention realizes a series of processes for generating and providing counseling content based on individual information of the user, and improving the system through feedback.

[0707] (Application example 1)

[0708] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0709] In modern society, prompt and individualized care for users' mental health is important, but existing systems make it difficult to quickly provide counseling tailored to each individual user. Furthermore, brick-and-mortar counseling services lack tools that allow staff to effectively assess users' mental states and provide appropriate advice. Furthermore, there is a need for a system that utilizes feedback from users to continuously improve the quality of counseling. The purpose of this invention is to solve these problems.

[0710] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0711] In this invention, the server includes means for inputting basic information about a user, means for inputting information about the user's mental state, means for transmitting the user's input information to the server, means for generating counseling content in the server using a generative artificial intelligence model based on the information, means for providing the generated counseling content to the user, means for inputting feedback from the user, means for transmitting the feedback to the server, means for improving the generative artificial intelligence model based on the feedback, and means for evaluating the user's mental state using an information terminal used by staff in a physical store and visually providing the counseling content displayed on the information terminal, thereby making it possible to provide prompt and personalized counseling even in a physical store.

[0712] "Means for inputting basic user information" refers to devices or software that provide an interface for users to input personal information such as their name, age, and gender.

[0713] The "means for inputting information about the user's mental state" refers to a device or software that provides an interface for the user to input their current mood or psychological state in the form of a question or the like.

[0714] The "means for transmitting user input information to the server" refers to a device or software for transmitting the basic information and mental state information input by the user to the server via a network.

[0715] "Means for generating counseling content using a generative artificial intelligence model" refers to software or algorithms that use generative AI to generate counseling content appropriate for individual users based on collected information.

[0716] The "means for providing the generated counseling content to the user" refers to a device or software for displaying the generated counseling content on the user's terminal.

[0717] The "means for allowing the user to input feedback" refers to a device or software that provides an interface for the user to input feedback such as the usefulness and satisfaction level of the counseling provided.

[0718] The "means for transmitting feedback to the server" refers to a device or software for transmitting the feedback information input by the user to the server via a network.

[0719] "Means for improving the generative artificial intelligence model based on feedback" refers to software or algorithms that use collected feedback information to update the generative AI model and improve it so that it can generate more appropriate and effective counseling content.

[0720] "Means for evaluating the mental state of a user using an information terminal used by staff in a physical store and visually providing counseling content displayed on the information terminal" refers to devices or software that evaluate the mental state of a customer using a terminal such as a smartphone or tablet used by staff in a physical store, and visually display and provide counseling content generated based on the evaluation results.

[0721] MODE FOR CARRYING OUT THE INVENTION

[0722] System Overview

[0723] This system collects basic information about the user and information about their mental state, and uses a generative AI model on the server to generate counseling content and provide it to the user. Furthermore, it can collect feedback and use it to improve the generative AI model.

[0724] Hardware and software used

[0725] Hardware: Smartphones, smart glasses, tablets, servers

[0726] Software: Python, Flask, TensorFlow, SQLite

[0727] System Operation

[0728] 1. User Information Collection:

[0729] Users access the system using a device such as a smartphone or tablet, which displays an interface that prompts them to enter basic information such as their name, age, and gender.

[0730] Example: A user enters the information "Taro Tanaka, 35 years old, male."

[0731] 2. Mental state input:

[0732] The device also displays questions about your mental state, such as "How are you feeling today?" and "How has your sleep been lately?"

[0733] Example: User responds "Mood: Slightly depressed" and "Sleep quality: Poor."

[0734] 3. Transmission of information to the server:

[0735] The device sends the collected user information and mental state information to the server, which receives the information and stores it in an SQLite database.

[0736] 4. Counseling content generation:

[0737] Based on the stored information, the server sends a request to a generative artificial intelligence model using TensorFlow to generate appropriate counseling content.

[0738] Example: Generate advice such as "This user is feeling a bit depressed and has poor sleep quality. Try some deep breathing exercises to relax."

[0739] 5. Provision of counseling content:

[0740] The server transmits the generated counseling content to the terminal, which visually displays the generated counseling content to the user.

[0741] Example: The device displays "Try this deep breathing exercise to relax" on the user's screen.

[0742] 6. User Feedback:

[0743] Users put the provided counseling into practice and provide feedback on its effectiveness, including comments such as "The advice was helpful" and "I would like to use this service again."

[0744] 7. Submitting Feedback:

[0745] The device sends the collected feedback to a server, which receives it and stores it in a database. This feedback is used to continuously improve the generative AI model.

[0746] For example, enter your feedback as "Satisfied: 4 / 5" and "Helpful" and submit.

[0747] Specific prompt examples

[0748] Example prompt sentence:

[0749] "How are users feeling?"

[0750] "How's your sleep quality lately?"

[0751] "Try some deep breathing exercises to help you relax."

[0752] In this way, by linking various data inputs tailored to the purpose with generative AI models, it is possible to provide practical and valuable counseling content to users. Furthermore, by continuously improving the system using feedback, it is possible to achieve even more accurate counseling.

[0753] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0754] Step 1:

[0755] Collection of User Information

[0756] Users access the system using a smartphone or tablet. They enter basic information such as their name, age, and gender into the input interface. The device collects the input data and compiles it into a format that can be sent to the server.

[0757] Input: Basic user information such as name, age, and gender

[0758] Processing: The device formats the collected information

[0759] Output: User basic information formatted to send to the server

[0760] Step 2:

[0761] Mental state input

[0762] The device asks the user questions about their mental state, such as "How are you feeling today?" or "How has your sleep been lately?" The user selects the appropriate answer for each question.

[0763] Input: Information about your mental state, such as how you're feeling today and the quality of your recent sleep

[0764] Processing: The device collects the user's answers and formats them into a format that can be sent to the server.

[0765] Output: Formatted mental state information to send to the server

[0766] Step 3:

[0767] Sending information to the server

[0768] The device sends the collected user information and mental state information to a server, which receives the information and stores it in an SQLite database.

[0769] Input: User basic information and mental state information

[0770] Processing: The device sends the information to the server, which stores it in a database

[0771] Output: User basic information and mental state information stored in the database

[0772] Step 4:

[0773] Counseling content generation

[0774] Based on the information stored in the database, the server sends a request to a generative artificial intelligence model using TensorFlow to generate appropriate counseling content.

[0775] Input: User basic information and mental state information

[0776] Processing: The server inputs information into the generative AI model, which then generates counseling content.

[0777] Output: Generated counseling content

[0778] Step 5:

[0779] Providing counseling content

[0780] The server transmits the generated counseling content to the terminal, which visually displays the generated counseling content to the user.

[0781] Input: Generated counseling content

[0782] Processing: The server sends the counseling content to the terminal, and the terminal displays the content.

[0783] Output: Visually displayed counseling content

[0784] Step 6:

[0785] User Feedback

[0786] Users put the provided counseling into practice and provide feedback on its effectiveness, including comments such as "The advice was helpful" and "I would like to use this service again."

[0787] Input: Feedback on counseling content

[0788] Processing: The device collects the feedback and formats it to be sent to the server.

[0789] Output: Formatted feedback to send to the server

[0790] Step 7:

[0791] Send and save feedback

[0792] The device sends the collected feedback to a server, which receives it and stores it in a database. This feedback is used to continuously improve the generative AI model.

[0793] Input: Feedback

[0794] Processing: The server stores the feedback in a database and updates the generative AI model.

[0795] Output: Feedback and improved generative AI models stored in a database

[0796] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0797] ---

[0798] The present invention provides a system that collects basic information and information about a user's mental state, and further recognizes the user's emotions using an emotion engine, thereby providing more appropriate counseling content. Specific embodiments of this system are described below.

[0799] Collection of User Information

[0800] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[0801] Input of user's mental state

[0802] The device then displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[0803] Sending information

[0804] The device sends the collected basic information and information about mental state to a server, which receives the information and stores it in a database.

[0805] Emotion recognition

[0806] The device is equipped with an emotion engine that recognizes the user's emotions. The emotion engine recognizes emotion data by analyzing the user's facial expressions and tone of voice. For example, when a user speaks into the camera, emotions such as "anxiety" or "sadness" are recognized from their facial expressions.

[0807] Sending emotional data

[0808] The emotion data recognized by the emotion engine is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[0809] Counseling content generation

[0810] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate for the user's situation. For example, the server might send a request to the AI ​​model saying, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." The AI ​​model then generates advice such as, "Try deep breathing exercises to relax."

[0811] Providing counseling content

[0812] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "Try these deep breathing exercises to relax." Specific exercise methods may also be displayed along with illustrations.

[0813] User Feedback

[0814] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[0815] Sending and processing feedback

[0816] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server uses the accumulated feedback to improve the generative AI model and increase the accuracy of future counseling content.

[0817] Processing flow with concrete examples

[0818] For example, if a user is feeling anxious, the following flow may occur.

[0819] 1. The device asks the user, "How are you feeling today?"

[0820] 2. The user types, "I feel anxious."

[0821] 3. The device uses an emotion engine to recognize "anxiety" from the user's facial expression.

[0822] 4. The device sends the input information and emotion data to the server.

[0823] 5. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[0824] 6. The terminal displays the generated counseling content to the user.

[0825] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[0826] 8. The device sends the feedback to the server.

[0827] 9. The server improves the AI ​​model based on the feedback and stores it in a database.

[0828] As described above, the present invention allows users to receive prompt and personalized counseling, and by utilizing emotion data in addition, more accurate counseling content can be provided. The quality of the system is continuously improved through feedback.

[0829] The processing flow will be explained below.

[0830] Processing Steps

[0831] Step 1:

[0832] The terminal displays the initial user registration screen to the user, who enters basic information such as name, age, and gender.

[0833] Step 2:

[0834] The user enters basic information, and the device sends this information to the server, specifically, data such as name, age, and gender in JSON format.

[0835] Step 3:

[0836] The server stores the received basic information in a database, which creates a profile for the user.

[0837] Step 4:

[0838] The device will prompt the user with questions about their current mental state, such as "How are you feeling today?" or "How's the quality of your sleep lately?"

[0839] Step 5:

[0840] The user answers each question, for example, selecting "Mood: slightly depressed" and "Sleep quality: poor."

[0841] Step 6:

[0842] The device sends the user's answers to the server, also in JSON format.

[0843] Step 7:

[0844] The emotion engine installed in the device recognizes the user's emotions. Specifically, it uses the device's camera and microphone to analyze the user's facial expressions and tone of voice. For example, the emotion engine recognizes "anxiety."

[0845] Step 8:

[0846] The terminal transmits the emotion data to the server, along with the basic information and mental state data.

[0847] Step 9:

[0848] The server inputs the received information into a generative AI model and instructs it to generate optimal counseling content. Specifically, it requests, "This user is feeling a little depressed, has poor sleep quality, and is also feeling anxious. Please generate appropriate counseling advice."

[0849] Step 10:

[0850] The server receives the response from the AI ​​model and sends the generated counseling content to the device, for example, "Try deep breathing exercises to relax."

[0851] Step 11:

[0852] The device displays the counseling content to the user, who then checks the content displayed on the screen and also looks at specific exercise methods.

[0853] Step 12:

[0854] The user practices the counseling provided, for example, by following the on-screen instructions to perform deep breathing exercises.

[0855] Step 13:

[0856] The user enters feedback about the effectiveness of the advice, for example, "The deep breathing exercises were very effective."

[0857] Step 14:

[0858] The device sends the user's feedback to the server, which is also sent in JSON format.

[0859] Step 15:

[0860] The server stores the feedback in a database, which is used to improve the generative artificial intelligence model.

[0861] Step 16:

[0862] The server uses the accumulated feedback to tune the AI ​​model and use it to generate the next counseling session. Specifically, the feedback data is passed through an analysis algorithm to retrain the model.

[0863] Through these steps, the system provides users with fast and personalized counseling, and the system is continuously improved. By using emotion data recognized by the emotion engine, the system can provide more accurate counseling content.

[0864] Example 2

[0865] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0866] Conventional counseling systems only provide counseling content based on the user's basic information and mental state, and have the problem of difficulty in responding to the user's real-time emotional state. Therefore, there is a need to provide more accurate and personalized counseling by incorporating emotional data such as the user's facial expressions and tone of voice.

[0867] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting basic information about the user, means for inputting information about the user's mental state, means for analyzing the user's facial expression and tone of voice using a terminal equipped with an emotion analysis engine and recognizing emotion data, means for transmitting this to the server, means for generating counseling content based on this information using a generative AI model, means for visually providing the generated counseling content, means for inputting user feedback, means for transmitting the feedback to the server and storing it, and means for improving the generative AI model based on these. This makes it possible to provide personalized counseling that reflects the user's real-time emotion data.

[0868] "User" refers to an individual who uses the system.

[0869] "Basic Information" refers to personal data such as name, age, and gender provided by the User.

[0870] "Mental state information" is data about emotions and psychological states input by the user, including answers to questions such as "How are you feeling today?"

[0871] "Server" refers to a central computer system for processing and storing information on a network.

[0872] A "generative artificial intelligence model" refers to an artificial intelligence engine that generates responses such as counseling content based on user input information.

[0873] "Counseling content" refers to advice and instructions for the user generated by the generative artificial intelligence model.

[0874] "Feedback" refers to the user's opinions and thoughts regarding the counseling content provided.

[0875] "Emotion analysis engine" refers to software and hardware components for analyzing a user's facial expressions and tone of voice to recognize emotional data.

[0876] "Terminal" refers to a device (smartphone, tablet, PC, etc.) that a user uses to access the system.

[0877] "Database" refers to a system for systematically storing and managing information on a server.

[0878] The present invention provides a system that collects basic information and information about a user's mental state, and further recognizes the user's emotions using an emotion analysis engine, thereby providing more appropriate counseling content. Specific embodiments of this system are described below.

[0879] Collection of User Information

[0880] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and prompts the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[0881] Input of user's mental state

[0882] Next, the device displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, they might answer "Mood: slightly depressed" or "Sleep quality: poor."

[0883] Sending information

[0884] The user's basic information and mental state information are sent from the device to the server, which receives the information and stores it in a database.

[0885] Emotion recognition

[0886] The device is equipped with an emotion analysis engine that analyzes the user's facial expressions and tone of voice to recognize emotional data. For example, when a user speaks to the camera, emotions such as "anxiety" or "sadness" can be detected from their facial expressions.

[0887] Sending emotional data

[0888] The recognized emotion data is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[0889] Counseling content generation

[0890] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate to the user's situation. The prompt might be something like, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." Based on this prompt, the generative AI model (e.g., GPT-4) generates advice such as, "Try deep breathing exercises to relax."

[0891] Providing counseling content

[0892] The generated counseling content is sent from the server to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display "Try some deep breathing exercises to relax," along with specific exercise instructions along with diagrams.

[0893] User Feedback

[0894] The user puts the counseling provided into practice and provides feedback on its effectiveness, for example, "The advice was helpful."

[0895] Sending and processing feedback

[0896] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[0897] The process flow with concrete examples, for example, if the user is feeling anxious, is as follows:

[0898] 1. The device asks the user, "How are you feeling today?"

[0899] 2. The user types, "I feel anxious."

[0900] 3. The device uses an emotion analysis engine to recognize "anxiety" from the user's facial expression.

[0901] 4. The device sends the input information and emotion data to the server.

[0902] 5. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[0903] 6. The terminal displays the generated counseling content to the user.

[0904] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[0905] 8. The device sends the feedback to the server.

[0906] 9. The server improves the AI ​​model based on the feedback and stores it in a database.

[0907] As described above, the present invention allows users to receive prompt and personalized counseling. By also utilizing emotion data, more accurate counseling content is provided, and feedback allows for continuous improvement of the system's quality.

[0908] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0909] Step 1:

[0910] A user accesses the system using a terminal. The terminal displays an initial setup screen and prompts the user to enter basic information (such as name, age, and gender). When the user enters "Yamada Taro, 30 years old, male," the terminal temporarily stores this information. The entered basic information is sent to the server.

[0911] Step 2:

[0912] The device displays questions about the user's mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. If the user answers "Mood: slightly depressed" or "Sleep quality: poor," this information is also temporarily stored on the device. Information about the mental state is also sent to the server.

[0913] Step 3:

[0914] The server receives the basic information and mental state information sent from the device and stores it in a database. Specifically, data such as "User name: Yamada Taro," "Age: 30," "Mood: slightly depressed," and "Sleep quality: poor" are stored.

[0915] Step 4:

[0916] The emotion analysis engine installed in the device analyzes the user's facial expressions and tone of voice to recognize emotional data. For example, when a user speaks into the camera, the emotion analysis engine recognizes emotions such as "anxiety" or "sadness" from their facial expressions. The analyzed emotional data is temporarily stored on the device.

[0917] Step 5:

[0918] The device sends the recognized emotion data along with basic information and mental state data to the server. The server receives this and stores it in a database. Specifically, additional data such as "emotion: anxiety" is stored.

[0919] Step 6:

[0920] The server generates counseling content using a generative AI model based on the stored basic information, mental state information, and emotion data. The prompt text is, "This user is slightly depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." Based on this prompt text, the generative AI model generates advice such as, "Try deep breathing exercises to relax."

[0921] Step 7:

[0922] The server sends the generated counseling content to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal screen may display "Try deep breathing exercises for relaxation" along with illustrations of specific exercise methods.

[0923] Step 8:

[0924] The user puts the counseling provided into practice and inputs feedback about its effectiveness, such as "This advice was helpful."

[0925] Step 9:

[0926] The device sends the user's feedback to the server. The server receives the feedback and stores it in a database. The accumulated feedback is used to improve the generative AI model, helping to increase the quality of the system. For example, the AI ​​model will be able to generate more appropriate counseling content based on the user's feedback from the next time onwards.

[0927] (Application example 2)

[0928] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0929] Conventional counseling systems generate counseling content based only on the user's basic information and mental state, which limits their accuracy. Furthermore, they lack the means to recognize the user's emotions in real time, making it difficult to provide optimal counseling for each individual user. As a result, user satisfaction declines, and the effectiveness of the system is not fully realized.

[0930] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting basic information and information about the mental state of the user, means for analyzing the user's emotions, and means for generating counseling content using a generative artificial intelligence model based on the information and emotion analysis data. This makes it possible to provide personalized counseling content that reflects the user's current emotional state in real time.

[0931] "Basic user information" refers to personal identification information such as the user's name, age, and gender.

[0932] "Information about mental state" is information about the user's current mood and psychological state.

[0933] "Means for analyzing emotions" refers to technology or devices for recognizing and analyzing a user's emotions based on their facial expressions and tone of voice.

[0934] A "generative artificial intelligence model" is an artificial intelligence model that generates appropriate output, i.e., counseling content, based on input data.

[0935] "Counseling content" refers to advice and support provided according to the user's mental state and emotions.

[0936] "Feedback" refers to the user's evaluation and impressions of the counseling content provided.

[0937] A "server" is a computer system that receives input information from a user, processes it, and returns generated counseling content to the user.

[0938] A "database" is a storage system that stores collected user information and feedback so that it can be referenced as needed.

[0939] The "visual display means" refers to a display or other display device for providing the generated counseling content to the user in the form of text, images, or the like.

[0940] "User input information" refers to basic information and information relating to mental state that a user provides to the system.

[0941] The present invention provides a system that collects basic information and information about a user's mental state, recognizes emotions using an emotion engine, and provides more appropriate counseling content. Specific embodiments of this system are described below.

[0942] Collection of User Information

[0943] First, a user accesses the system using a smartphone application. When the user first accesses the system, the application prompts the user to enter basic information. This information includes name, age, and gender. For example, the user enters "Yamada Taro, 30 years old, male."

[0944] Input of user's mental state

[0945] The smartphone application also displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[0946] Sending information

[0947] The smartphone application sends the collected basic information and information about mental state to a server, which receives the information and stores it in a database.

[0948] Emotion recognition

[0949] The emotion engine uses the smartphone's camera and microphone to recognize the user's emotions. The emotion engine recognizes emotion data by analyzing the user's facial expressions and tone of voice. For example, when a user speaks into the camera, emotions such as "anxiety" or "sadness" are recognized from their facial expressions.

[0950] Sending emotional data

[0951] The emotion data recognized by the emotion engine is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[0952] Counseling content generation

[0953] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate for the user's situation. For example, the server sends a request to the generative AI model saying, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." The generative AI model then generates advice such as, "Try deep breathing exercises to relax."

[0954] Providing counseling content

[0955] The server receives the generated counseling content and sends it to a smartphone application. The application visually displays the generated counseling content to the user. For example, the device may display a message on the user's screen saying, "Try these deep breathing exercises to relax." Specific exercise instructions may also be displayed along with illustrations.

[0956] User Feedback

[0957] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[0958] Sending and processing feedback

[0959] The smartphone application collects user feedback and sends it to a server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server uses the accumulated feedback to improve the generative AI model and increase the accuracy of future counseling content.

[0960] Processing flow with concrete examples

[0961] For example, if a user is feeling anxious, the following flow may occur.

[0962] 1. A smartphone application asks the user, "How are you feeling today?"

[0963] 2. The user types, "I feel anxious."

[0964] 3. The smartphone's camera and microphone use an emotion engine to recognize "anxiety" from the user's facial expression.

[0965] 4. The smartphone application sends the input information and emotion data to the server.

[0966] 5. The server receives the information and generates counseling content based on a generative artificial intelligence model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[0967] 6. The smartphone application displays the generated counseling content to the user.

[0968] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[0969] 8. The smartphone application sends the feedback to the server.

[0970] 9. The server improves the generative AI model based on the feedback and stores it in a database.

[0971] To illustrate, here's an example prompt:

[0972] Customer is feeling anxious, provide suitable advice.

[0973] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0974] Step 1:

[0975] The user accesses the smartphone application and inputs basic information and information about their mental state.

[0976] Input: User inputs basic information (name, age, gender) and mental state (mood, sleep quality, etc.).

[0977] Output: Collected basic and mental status information data.

[0978] Specific operation: The user enters information according to the initial setup screen of the app, and the app temporarily saves that information.

[0979] Step 2:

[0980] The smartphone's camera and microphone are used to recognize the user's emotions. The emotion engine analyzes facial expressions and tone of voice to generate emotion data.

[0981] Input: User's facial expression video and audio data.

[0982] Output: Parsed emotion data (e.g., "anxiety", "sadness", etc.).

[0983] How it works: The app uses a camera and microphone to capture the user's facial expressions and voice in real time, and the emotion engine analyzes them.

[0984] Step 3:

[0985] The smartphone application sends the collected basic information, mental state information, and emotion data to a server.

[0986] Input: User's basic information, mental state information, and emotional data.

[0987] Output: All data sent to the server.

[0988] Specific operation: The app batches data into packets and sends them over the network to the server.

[0989] Step 4:

[0990] The server stores the received information in a database.

[0991] Input: Basic information, mental state information, emotional data.

[0992] Output: Information stored in a database.

[0993] Specific operation: The server analyzes the received data and stores it in the database in the appropriate format.

[0994] Step 5:

[0995] The server generates counseling content using a generative artificial intelligence model. Information is input as prompts to the model, and counseling content is output.

[0996] Input: Basic information, mental state information, emotion data. Prompt text: "This user is slightly depressed, has poor sleep quality, and is anxious according to the emotion engine. Please generate appropriate counseling advice."

[0997] Output: Generated counseling content.

[0998] Specific operation: The server sends a prompt to the generative artificial intelligence model, which generates appropriate counseling content.

[0999] Step 6:

[1000] The server sends the generated counseling content to the smartphone application.

[1001] Input: Generated counseling content.

[1002] Output: Counseling content sent to the smartphone application.

[1003] Specific operation: The server sends the generated counseling content to the app via the network.

[1004] Step 7:

[1005] A smartphone application visually displays the generated counseling content to the user.

[1006] Input: Counseling content submitted.

[1007] Output: The counseling content that the user sees.

[1008] Specific operation: The app displays the counseling content received in text and images.

[1009] Step 8:

[1010] Users put the provided counseling content into practice and enter the results into the app as feedback.

[1011] Input: User feedback information.

[1012] Output: Feedback input data.

[1013] Specific operation: The user performs the advice and enters the results in the app's feedback screen.

[1014] Step 9:

[1015] The smartphone application sends the user's feedback to a server.

[1016] Input: User feedback information.

[1017] Output: Feedback information sent to the server.

[1018] Specific operation: The app collects feedback information and compiles it into packets, which are then sent over the network to a server.

[1019] Step 10:

[1020] The server stores the received feedback in a database and uses a generative artificial intelligence model to improve the accuracy of future counseling sessions.

[1021] Input: User feedback information.

[1022] Output: Feedback information stored in a database, an improved generative artificial intelligence model.

[1023] Specific operation: The server stores the received feedback in a database and uses that data to learn and improve the generative artificial intelligence model.

[1024] 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.

[1025] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1026] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1027] [Third embodiment]

[1028] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1029] 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.

[1030] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[1031] 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.

[1032] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1033] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1034] 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.

[1035] 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.

[1036] 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 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.

[1037] 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.

[1038] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1039] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1040] ---

[1041] The present invention is a system for collecting basic information and information on a user's mental state, and generating and providing appropriate counseling content based on this information. A specific embodiment of this system will be described below.

[1042] Collection of User Information

[1043] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Taro Tanaka, 35 years old, male."

[1044] Input of user's mental state

[1045] The device then displays questions about the user's current mental state, such as "How are you feeling today?" and "How is the quality of your sleep these days?" The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[1046] Sending information

[1047] The device sends the collected user information and mental state information to the server, which receives the information and stores it in a database.

[1048] Counseling content generation

[1049] Based on the stored information, the server uses a generative artificial intelligence model to generate counseling content appropriate for the user's situation. For example, the server might send a request to the AI ​​model saying, "This user is feeling a little depressed and has poor sleep quality. Please generate appropriate counseling advice." The AI ​​model then generates advice such as, "Try deep breathing exercises to relax."

[1050] Providing counseling content

[1051] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "Try these deep breathing exercises to relax." Specific exercise methods may also be displayed along with illustrations.

[1052] User Feedback

[1053] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[1054] Sending and processing feedback

[1055] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server continuously improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[1056] Processing flow with concrete examples

[1057] For example, if a user is feeling anxious, the following flow may occur.

[1058] 1. The device asks the user, "How are you feeling today?"

[1059] 2. The user types, "I feel anxious."

[1060] 3. The device sends the input information to the server.

[1061] 4. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[1062] 5. The terminal displays the generated counseling content to the user.

[1063] 6. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[1064] 7. The device sends the feedback to the server.

[1065] 8. The server improves the AI ​​model based on the feedback and stores it in a database.

[1066] As can be seen, the present invention allows users to receive prompt and personalized counseling, and through feedback the quality of the system is continually improved.

[1067] The processing flow will be explained below.

[1068] Processing Steps

[1069] Step 1:

[1070] The device displays the initial user registration screen, where the user enters basic information such as name, age, and gender.

[1071] Step 2:

[1072] The user enters basic information, and the device sends this information to the server. Specifically, information such as "Name: Taro Tanaka," "Age: 35," and "Gender: Male" is sent to the server in JSON format.

[1073] Step 3:

[1074] The server stores the received basic information in a database, which creates a profile for the user.

[1075] Step 4:

[1076] The device will display questions about the user's current mental state, such as "How are you feeling today?" and "How has your sleep been lately?"

[1077] Step 5:

[1078] The user answers each question, for example, selecting "Mood: slightly depressed" and "Sleep quality: poor."

[1079] Step 6:

[1080] The device sends the user's answers to the server, also in JSON format.

[1081] Step 7:

[1082] The server inputs the received information into a generative AI model and instructs it to generate optimal counseling content. Specifically, the AI ​​model requests, "Please provide advice appropriate for a user who is feeling a little depressed and has poor quality sleep."

[1083] Step 8:

[1084] The server receives the response from the AI ​​model and sends the generated counseling content to the device, for example, "Try deep breathing exercises to relax."

[1085] Step 9:

[1086] The device displays the counseling content to the user, who then checks the content displayed on the screen and also looks at specific exercise methods.

[1087] Step 10:

[1088] The user practices the counseling provided, for example, by following the on-screen instructions to perform deep breathing exercises.

[1089] Step 11:

[1090] The user enters feedback about the effectiveness of the advice, for example, "The deep breathing exercises were very effective."

[1091] Step 12:

[1092] The device sends the user's feedback to the server, which is also sent in JSON format.

[1093] Step 13:

[1094] The server stores the feedback in a database, which is used to improve the generative artificial intelligence model.

[1095] Step 14:

[1096] The server uses the accumulated feedback to tune the AI ​​model and use it to generate the next counseling session. Specifically, the feedback data is passed through an analysis algorithm to retrain the model.

[1097] Through these steps, users are provided with fast, personalized counseling and the system is continually improved.

[1098] Example 1

[1099] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1100] Conventional counseling systems have had the problem of being difficult to provide individualized support tailored to the user's mental state. Furthermore, the mechanism for collecting feedback and using it to improve the system has not been fully established, limiting the improvement of the accuracy of the counseling content. Furthermore, the counseling content provided is sometimes difficult to understand visually, making it difficult for users to put the system into practice.

[1101] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1102] In this invention, the server includes means for inputting basic information and information about a user's mental state, means for transmitting the input information, means for generating counseling content using a generative AI model, means for visually providing the generated counseling content, means for displaying specific examples of the counseling content together with illustrations, means for inputting user feedback, means for transmitting the feedback, and means for improving the generative AI model based on the feedback. This makes it easier to provide personalized counseling content and for users to put it into practice, and enables continuous improvement of the system through collected feedback.

[1103] "Basic user information" refers to basic data for identifying an individual, such as the user's name, age, and gender.

[1104] "Information about mental state" is data that indicates the user's current psychological state, including mood, sleep quality, stress level, and the like.

[1105] A "server" is a computer system that receives, stores, processes, and transmits data.

[1106] A "generative artificial intelligence model" is an artificial intelligence algorithm that generates new information based on given data, and examples of this include language models such as GPT-3.

[1107] "Counseling content" refers to advice and support information generated based on the user's mental state.

[1108] "Visual means" are ways of presenting information in a format that is easy for users to understand, such as text or illustrations.

[1109] "Feedback" refers to the user's opinions and impressions regarding the effectiveness and satisfaction of the counseling content provided.

[1110] A database is a system for organizing and storing information, and is constructed so that it can be searched and used efficiently later.

[1111] An "illustration" is an image or diagram that visually explains information.

[1112] The present invention is a system for collecting basic information and information on a user's mental state, and generating and providing appropriate counseling content based on this information. A specific embodiment of this system will be described below.

[1113] Collection of User Information

[1114] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[1115] Input of user's mental state

[1116] The device then displays questions about the user's current mental state, such as "How are you feeling today?" and "How is the quality of your sleep these days?" The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly irritable" and "Sleep quality: average."

[1117] Sending information

[1118] The device sends the collected user information and mental state information to the server, which receives the information and stores it in a database.

[1119] Counseling content generation

[1120] Based on the stored information, the server uses a generative artificial intelligence model (such as GPT-3) to generate counseling content appropriate for the user's situation. For example, the server sends a request to the AI ​​model saying, "This user is somewhat irritable and has average sleep quality. Please generate appropriate counseling advice." The AI ​​model generates advice such as, "Try yoga or meditation at the end of the day to relax."

[1121] Providing counseling content

[1122] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "To relax, try yoga or meditation at the end of the day." Specific exercise methods may also be displayed with illustrations.

[1123] User Feedback

[1124] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[1125] Sending and processing feedback

[1126] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server continuously improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[1127] Processing flow with concrete examples

[1128] For example, if a user is feeling stressed, the following flow may occur.

[1129] 1. The device asks the user, "How are you feeling today?"

[1130] 2. The user types, "I'm feeling stressed."

[1131] 3. The device sends the input information to the server.

[1132] 4. The server receives the information and generates counseling content based on the AI ​​model, such as "Try taking deep breaths and calming your mind to reduce stress."

[1133] 5. The terminal displays the generated counseling content to the user.

[1134] 6. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[1135] 7. The device sends the feedback to the server.

[1136] 8. The server improves the AI ​​model based on the feedback and stores it in a database.

[1137] As can be seen, the present invention allows users to receive prompt and personalized counseling, and through feedback the quality of the system is continually improved.

[1138] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1139] System program processing steps

[1140] Step 1:

[1141] User Action:

[1142] A user accesses the system using a terminal.

[1143] Input: The user enters basic information (such as name, age, and gender) into the device's initial setup screen.

[1144] Output: Basic information is displayed on the terminal.

[1145] Specific behavior: The device provides the user with input fields such as "What is your name?", "How old are you?", and "What is your gender?", and the user enters the information accordingly.

[1146] Step 2:

[1147] User Action:

[1148] The user inputs information about the mental state into the terminal.

[1149] Input: The user answers questions like "How are you feeling today?" and "How have you been sleeping lately?"

[1150] Output: Terminal displays information about mental state.

[1151] Specific operation: The device presents the user with multiple-choice questions such as "How are you feeling today?" and "How has your sleep been lately?", and the user selects an answer from multiple options.

[1152] Step 3:

[1153] The device:

[1154] The terminal transmits the collected basic information and information regarding mental state to a server.

[1155] Input: Basic information and mental state information entered by the user.

[1156] Output: User information sent to the server.

[1157] Specific operation: The terminal displays the message "Sending user information..." and sends the information entered by the user to the server.

[1158] Step 4:

[1159] The server:

[1160] The server receives the transmitted information and stores it in a database.

[1161] Input: Basic information and mental state information about the user sent from the device.

[1162] Output: User information stored in the database.

[1163] Specific operation: The server records a log message such as "User information saved" and stores the information in the "User Information" table in the database.

[1164] Step 5:

[1165] The server:

[1166] The server generates counseling content using a generative AI model based on the stored information.

[1167] Input: User information retrieved from the database.

[1168] Output: Generated counseling content.

[1169] Data processing: Generates a prompt sentence based on the input information and sends a request to the generative AI model.

[1170] Specific operation: The server generates a prompt message saying, "This user is slightly irritable and has average sleep quality. Please generate appropriate counseling advice," and sends it to the AI ​​model (e.g., GPT-3). The AI ​​model receives the advice and returns the counseling content, "Try yoga or meditation at the end of the day to relax," to the server.

[1171] Step 6:

[1172] The server:

[1173] The server transmits the generated counseling content to the terminal.

[1174] Input: Generated counseling content.

[1175] Output: Counseling content sent to the device.

[1176] Specific operation: The server displays the message "Sending counseling content..." and sends the generated content to the terminal.

[1177] Step 7:

[1178] The device:

[1179] The terminal visually displays the generated counseling content to the user.

[1180] Input: Counseling content sent from the server.

[1181] Output: Counseling content displayed on the terminal.

[1182] Specific action: The device displays a message on the user's screen saying, "Try yoga or meditation at the end of the day to relax," along with illustrations of specific exercise methods.

[1183] Step 8:

[1184] User Action:

[1185] The user practices the counseling content provided and provides feedback on its effectiveness.

[1186] Input: Counseling content implementation results and feedback.

[1187] Output: Feedback typed into the terminal.

[1188] Specific behavior: The user enters feedback such as "This advice was helpful" or "I was satisfied with the advice."

[1189] Step 9:

[1190] The device:

[1191] The terminal sends the user's feedback to the server.

[1192] Input: Feedback entered by the user.

[1193] Output: Feedback sent to the server.

[1194] Specific operation: The device displays the message "Sending feedback..." and sends the feedback data to the server.

[1195] Step 10:

[1196] The server:

[1197] The server receives the feedback and stores it in a database.

[1198] Input: Feedback sent from the device.

[1199] Output: Feedback stored in a database.

[1200] Specific behavior: The server records a log message such as "Feedback saved" and stores the feedback data in the "feedback" table in the database.

[1201] Step 11:

[1202] The server:

[1203] The server improves the generative artificial intelligence model based on the feedback.

[1204] Input: Feedback stored in the database.

[1205] Output: An improved generative artificial intelligence model.

[1206] Specific operation: The server uses the accumulated feedback as training data for the AI ​​model to improve the accuracy of the counseling content from the next time onwards.

[1207] Through the above steps, the present invention realizes a series of processes for generating and providing counseling content based on individual information of the user, and improving the system through feedback.

[1208] (Application example 1)

[1209] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1210] In modern society, prompt and individualized care for users' mental health is important, but existing systems make it difficult to quickly provide counseling tailored to each individual user. Furthermore, brick-and-mortar counseling services lack tools that allow staff to effectively assess users' mental states and provide appropriate advice. Furthermore, there is a need for a system that utilizes feedback from users to continuously improve the quality of counseling. The purpose of this invention is to solve these problems.

[1211] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1212] In this invention, the server includes means for inputting basic information about a user, means for inputting information about the user's mental state, means for transmitting the user's input information to the server, means for generating counseling content in the server using a generative artificial intelligence model based on the information, means for providing the generated counseling content to the user, means for inputting feedback from the user, means for transmitting the feedback to the server, means for improving the generative artificial intelligence model based on the feedback, and means for evaluating the user's mental state using an information terminal used by staff in a physical store and visually providing the counseling content displayed on the information terminal, thereby making it possible to provide prompt and personalized counseling even in a physical store.

[1213] "Means for inputting basic user information" refers to devices or software that provide an interface for users to input personal information such as their name, age, and gender.

[1214] The "means for inputting information about the user's mental state" refers to a device or software that provides an interface for the user to input their current mood or psychological state in the form of a question or the like.

[1215] The "means for transmitting user input information to the server" refers to a device or software for transmitting the basic information and mental state information input by the user to the server via a network.

[1216] "Means for generating counseling content using a generative artificial intelligence model" refers to software or algorithms that use generative AI to generate counseling content appropriate for individual users based on collected information.

[1217] The "means for providing the generated counseling content to the user" refers to a device or software for displaying the generated counseling content on the user's terminal.

[1218] The "means for allowing the user to input feedback" refers to a device or software that provides an interface for the user to input feedback such as the usefulness and satisfaction level of the counseling provided.

[1219] The "means for transmitting feedback to the server" refers to a device or software for transmitting the feedback information input by the user to the server via a network.

[1220] "Means for improving the generative artificial intelligence model based on feedback" refers to software or algorithms that use collected feedback information to update the generative AI model and improve it so that it can generate more appropriate and effective counseling content.

[1221] "Means for evaluating the mental state of a user using an information terminal used by staff in a physical store and visually providing counseling content displayed on the information terminal" refers to devices or software that evaluate the mental state of a customer using a terminal such as a smartphone or tablet used by staff in a physical store, and visually display and provide counseling content generated based on the evaluation results.

[1222] MODE FOR CARRYING OUT THE INVENTION

[1223] System Overview

[1224] This system collects basic information about the user and information about their mental state, and uses a generative AI model on the server to generate counseling content and provide it to the user. Furthermore, it can collect feedback and use it to improve the generative AI model.

[1225] Hardware and software used

[1226] Hardware: Smartphones, smart glasses, tablets, servers

[1227] Software: Python, Flask, TensorFlow, SQLite

[1228] System Operation

[1229] 1. User Information Collection:

[1230] Users access the system using a device such as a smartphone or tablet, which displays an interface that prompts them to enter basic information such as their name, age, and gender.

[1231] Example: A user enters the information "Taro Tanaka, 35 years old, male."

[1232] 2. Mental state input:

[1233] The device also displays questions about your mental state, such as "How are you feeling today?" and "How has your sleep been lately?"

[1234] Example: User responds "Mood: Slightly depressed" and "Sleep quality: Poor."

[1235] 3. Transmission of information to the server:

[1236] The device sends the collected user information and mental state information to the server, which receives the information and stores it in an SQLite database.

[1237] 4. Counseling content generation:

[1238] Based on the stored information, the server sends a request to a generative artificial intelligence model using TensorFlow to generate appropriate counseling content.

[1239] Example: Generate advice such as "This user is feeling a bit depressed and has poor sleep quality. Try some deep breathing exercises to relax."

[1240] 5. Provision of counseling content:

[1241] The server transmits the generated counseling content to the terminal, which visually displays the generated counseling content to the user.

[1242] Example: The device displays "Try this deep breathing exercise to relax" on the user's screen.

[1243] 6. User Feedback:

[1244] Users put the provided counseling into practice and provide feedback on its effectiveness, including comments such as "The advice was helpful" and "I would like to use this service again."

[1245] 7. Submitting Feedback:

[1246] The device sends the collected feedback to a server, which receives it and stores it in a database. This feedback is used to continuously improve the generative AI model.

[1247] For example, enter your feedback as "Satisfied: 4 / 5" and "Helpful" and submit.

[1248] Specific prompt examples

[1249] Example prompt sentence:

[1250] "How are users feeling?"

[1251] "How's your sleep quality lately?"

[1252] "Try some deep breathing exercises to help you relax."

[1253] In this way, by linking various data inputs tailored to the purpose with generative AI models, it is possible to provide practical and valuable counseling content to users. Furthermore, by continuously improving the system using feedback, it is possible to achieve even more accurate counseling.

[1254] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1255] Step 1:

[1256] Collection of User Information

[1257] Users access the system using a smartphone or tablet. They enter basic information such as their name, age, and gender into the input interface. The device collects the input data and compiles it into a format that can be sent to the server.

[1258] Input: Basic user information such as name, age, and gender

[1259] Processing: The device formats the collected information

[1260] Output: User basic information formatted to send to the server

[1261] Step 2:

[1262] Mental state input

[1263] The device asks the user questions about their mental state, such as "How are you feeling today?" or "How has your sleep been lately?" The user selects the appropriate answer for each question.

[1264] Input: Information about your mental state, such as how you're feeling today and the quality of your recent sleep

[1265] Processing: The device collects the user's answers and formats them into a format that can be sent to the server.

[1266] Output: Formatted mental state information to send to the server

[1267] Step 3:

[1268] Sending information to the server

[1269] The device sends the collected user information and mental state information to a server, which receives the information and stores it in an SQLite database.

[1270] Input: User basic information and mental state information

[1271] Processing: The device sends the information to the server, which stores it in a database

[1272] Output: User basic information and mental state information stored in the database

[1273] Step 4:

[1274] Counseling content generation

[1275] Based on the information stored in the database, the server sends a request to a generative artificial intelligence model using TensorFlow to generate appropriate counseling content.

[1276] Input: User basic information and mental state information

[1277] Processing: The server inputs information into the generative AI model, which then generates counseling content.

[1278] Output: Generated counseling content

[1279] Step 5:

[1280] Providing counseling content

[1281] The server transmits the generated counseling content to the terminal, which visually displays the generated counseling content to the user.

[1282] Input: Generated counseling content

[1283] Processing: The server sends the counseling content to the terminal, and the terminal displays the content.

[1284] Output: Visually displayed counseling content

[1285] Step 6:

[1286] User Feedback

[1287] Users put the provided counseling into practice and provide feedback on its effectiveness, including comments such as "The advice was helpful" and "I would like to use this service again."

[1288] Input: Feedback on counseling content

[1289] Processing: The device collects the feedback and formats it to be sent to the server.

[1290] Output: Formatted feedback to send to the server

[1291] Step 7:

[1292] Send and save feedback

[1293] The device sends the collected feedback to a server, which receives it and stores it in a database. This feedback is used to continuously improve the generative AI model.

[1294] Input: Feedback

[1295] Processing: The server stores the feedback in a database and updates the generative AI model.

[1296] Output: Feedback and improved generative AI models stored in a database

[1297] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1298] ---

[1299] The present invention provides a system that collects basic information and information about a user's mental state, and further recognizes the user's emotions using an emotion engine, thereby providing more appropriate counseling content. Specific embodiments of this system are described below.

[1300] Collection of User Information

[1301] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[1302] Input of user's mental state

[1303] The device then displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[1304] Sending information

[1305] The device sends the collected basic information and information about mental state to a server, which receives the information and stores it in a database.

[1306] Emotion recognition

[1307] The device is equipped with an emotion engine that recognizes the user's emotions. The emotion engine recognizes emotion data by analyzing the user's facial expressions and tone of voice. For example, when a user speaks into the camera, emotions such as "anxiety" or "sadness" are recognized from their facial expressions.

[1308] Sending emotional data

[1309] The emotion data recognized by the emotion engine is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[1310] Counseling content generation

[1311] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate for the user's situation. For example, the server might send a request to the AI ​​model saying, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." The AI ​​model then generates advice such as, "Try deep breathing exercises to relax."

[1312] Providing counseling content

[1313] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "Try these deep breathing exercises to relax." Specific exercise methods may also be displayed along with illustrations.

[1314] User Feedback

[1315] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[1316] Sending and processing feedback

[1317] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server uses the accumulated feedback to improve the generative AI model and increase the accuracy of future counseling content.

[1318] Processing flow with concrete examples

[1319] For example, if a user is feeling anxious, the following flow may occur.

[1320] 1. The device asks the user, "How are you feeling today?"

[1321] 2. The user types, "I feel anxious."

[1322] 3. The device uses an emotion engine to recognize "anxiety" from the user's facial expression.

[1323] 4. The device sends the input information and emotion data to the server.

[1324] 5. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[1325] 6. The terminal displays the generated counseling content to the user.

[1326] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[1327] 8. The device sends the feedback to the server.

[1328] 9. The server improves the AI ​​model based on the feedback and stores it in a database.

[1329] As described above, the present invention allows users to receive prompt and personalized counseling, and by utilizing emotion data in addition, more accurate counseling content can be provided. The quality of the system is continuously improved through feedback.

[1330] The processing flow will be explained below.

[1331] Processing Steps

[1332] Step 1:

[1333] The terminal displays the initial user registration screen to the user, who enters basic information such as name, age, and gender.

[1334] Step 2:

[1335] The user enters basic information, and the device sends this information to the server, specifically, data such as name, age, and gender in JSON format.

[1336] Step 3:

[1337] The server stores the received basic information in a database, which creates a profile for the user.

[1338] Step 4:

[1339] The device will prompt the user with questions about their current mental state, such as "How are you feeling today?" or "How's the quality of your sleep lately?"

[1340] Step 5:

[1341] The user answers each question, for example, selecting "Mood: slightly depressed" and "Sleep quality: poor."

[1342] Step 6:

[1343] The device sends the user's answers to the server, also in JSON format.

[1344] Step 7:

[1345] The emotion engine installed in the device recognizes the user's emotions. Specifically, it uses the device's camera and microphone to analyze the user's facial expressions and tone of voice. For example, the emotion engine recognizes "anxiety."

[1346] Step 8:

[1347] The terminal transmits the emotion data to the server, along with the basic information and mental state data.

[1348] Step 9:

[1349] The server inputs the received information into a generative AI model and instructs it to generate optimal counseling content. Specifically, it requests, "This user is feeling a little depressed, has poor sleep quality, and is also feeling anxious. Please generate appropriate counseling advice."

[1350] Step 10:

[1351] The server receives the response from the AI ​​model and sends the generated counseling content to the device, for example, "Try deep breathing exercises to relax."

[1352] Step 11:

[1353] The device displays the counseling content to the user, who then checks the content displayed on the screen and also looks at specific exercise methods.

[1354] Step 12:

[1355] The user practices the counseling provided, for example, by following the on-screen instructions to perform deep breathing exercises.

[1356] Step 13:

[1357] The user enters feedback about the effectiveness of the advice, for example, "The deep breathing exercises were very effective."

[1358] Step 14:

[1359] The device sends the user's feedback to the server, which is also sent in JSON format.

[1360] Step 15:

[1361] The server stores the feedback in a database, which is used to improve the generative artificial intelligence model.

[1362] Step 16:

[1363] The server uses the accumulated feedback to tune the AI ​​model and use it to generate the next counseling session. Specifically, the feedback data is passed through an analysis algorithm to retrain the model.

[1364] Through these steps, the system provides users with fast and personalized counseling, and the system is continuously improved. By using emotion data recognized by the emotion engine, the system can provide more accurate counseling content.

[1365] Example 2

[1366] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1367] Conventional counseling systems only provide counseling content based on the user's basic information and mental state, and have the problem of difficulty in responding to the user's real-time emotional state. Therefore, there is a need to provide more accurate and personalized counseling by incorporating emotional data such as the user's facial expressions and tone of voice.

[1368] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting basic information about the user, means for inputting information about the user's mental state, means for analyzing the user's facial expression and tone of voice using a terminal equipped with an emotion analysis engine and recognizing emotion data, means for transmitting this to the server, means for generating counseling content based on this information using a generative AI model, means for visually providing the generated counseling content, means for inputting user feedback, means for transmitting the feedback to the server and storing it, and means for improving the generative AI model based on these. This makes it possible to provide personalized counseling that reflects the user's real-time emotion data.

[1369] "User" refers to an individual who uses the system.

[1370] "Basic Information" refers to personal data such as name, age, and gender provided by the User.

[1371] "Mental state information" is data about emotions and psychological states input by the user, including answers to questions such as "How are you feeling today?"

[1372] "Server" refers to a central computer system for processing and storing information on a network.

[1373] A "generative artificial intelligence model" refers to an artificial intelligence engine that generates responses such as counseling content based on user input information.

[1374] "Counseling content" refers to advice and instructions for the user generated by the generative artificial intelligence model.

[1375] "Feedback" refers to the user's opinions and thoughts regarding the counseling content provided.

[1376] "Emotion analysis engine" refers to software and hardware components for analyzing a user's facial expressions and tone of voice to recognize emotional data.

[1377] "Terminal" refers to a device (smartphone, tablet, PC, etc.) that a user uses to access the system.

[1378] "Database" refers to a system for systematically storing and managing information on a server.

[1379] The present invention provides a system that collects basic information and information about a user's mental state, and further recognizes the user's emotions using an emotion analysis engine, thereby providing more appropriate counseling content. Specific embodiments of this system are described below.

[1380] Collection of User Information

[1381] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and prompts the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[1382] Input of user's mental state

[1383] Next, the device displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, they might answer "Mood: slightly depressed" or "Sleep quality: poor."

[1384] Sending information

[1385] The user's basic information and mental state information are sent from the device to the server, which receives the information and stores it in a database.

[1386] Emotion recognition

[1387] The device is equipped with an emotion analysis engine that analyzes the user's facial expressions and tone of voice to recognize emotional data. For example, when a user speaks to the camera, emotions such as "anxiety" or "sadness" can be detected from their facial expressions.

[1388] Sending emotional data

[1389] The recognized emotion data is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[1390] Counseling content generation

[1391] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate to the user's situation. The prompt might be something like, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." Based on this prompt, the generative AI model (e.g., GPT-4) generates advice such as, "Try deep breathing exercises to relax."

[1392] Providing counseling content

[1393] The generated counseling content is sent from the server to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display "Try some deep breathing exercises to relax," along with specific exercise instructions along with diagrams.

[1394] User Feedback

[1395] The user puts the counseling provided into practice and provides feedback on its effectiveness, for example, "The advice was helpful."

[1396] Sending and processing feedback

[1397] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[1398] The process flow with concrete examples, for example, if the user is feeling anxious, is as follows:

[1399] 1. The device asks the user, "How are you feeling today?"

[1400] 2. The user types, "I feel anxious."

[1401] 3. The device uses an emotion analysis engine to recognize "anxiety" from the user's facial expression.

[1402] 4. The device sends the input information and emotion data to the server.

[1403] 5. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[1404] 6. The terminal displays the generated counseling content to the user.

[1405] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[1406] 8. The device sends the feedback to the server.

[1407] 9. The server improves the AI ​​model based on the feedback and stores it in a database.

[1408] As described above, the present invention allows users to receive prompt and personalized counseling. By also utilizing emotion data, more accurate counseling content is provided, and feedback allows for continuous improvement of the system's quality.

[1409] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1410] Step 1:

[1411] A user accesses the system using a terminal. The terminal displays an initial setup screen and prompts the user to enter basic information (such as name, age, and gender). When the user enters "Yamada Taro, 30 years old, male," the terminal temporarily stores this information. The entered basic information is sent to the server.

[1412] Step 2:

[1413] The device displays questions about the user's mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. If the user answers "Mood: slightly depressed" or "Sleep quality: poor," this information is also temporarily stored on the device. Information about the mental state is also sent to the server.

[1414] Step 3:

[1415] The server receives the basic information and mental state information sent from the device and stores it in a database. Specifically, data such as "User name: Yamada Taro," "Age: 30," "Mood: slightly depressed," and "Sleep quality: poor" are stored.

[1416] Step 4:

[1417] The emotion analysis engine installed in the device analyzes the user's facial expressions and tone of voice to recognize emotional data. For example, when a user speaks into the camera, the emotion analysis engine recognizes emotions such as "anxiety" or "sadness" from their facial expressions. The analyzed emotional data is temporarily stored on the device.

[1418] Step 5:

[1419] The device sends the recognized emotion data along with basic information and mental state data to the server. The server receives this and stores it in a database. Specifically, additional data such as "emotion: anxiety" is stored.

[1420] Step 6:

[1421] The server generates counseling content using a generative AI model based on the stored basic information, mental state information, and emotion data. The prompt text is, "This user is slightly depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." Based on this prompt text, the generative AI model generates advice such as, "Try deep breathing exercises to relax."

[1422] Step 7:

[1423] The server sends the generated counseling content to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal screen may display "Try deep breathing exercises for relaxation" along with illustrations of specific exercise methods.

[1424] Step 8:

[1425] The user puts the counseling provided into practice and inputs feedback about its effectiveness, such as "This advice was helpful."

[1426] Step 9:

[1427] The device sends the user's feedback to the server. The server receives the feedback and stores it in a database. The accumulated feedback is used to improve the generative AI model, helping to increase the quality of the system. For example, the AI ​​model will be able to generate more appropriate counseling content based on the user's feedback from the next time onwards.

[1428] (Application example 2)

[1429] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1430] Conventional counseling systems generate counseling content based only on the user's basic information and mental state, which limits their accuracy. Furthermore, they lack the means to recognize the user's emotions in real time, making it difficult to provide optimal counseling for each individual user. As a result, user satisfaction declines, and the effectiveness of the system is not fully realized.

[1431] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting basic information and information about the mental state of the user, means for analyzing the user's emotions, and means for generating counseling content using a generative artificial intelligence model based on the information and emotion analysis data. This makes it possible to provide personalized counseling content that reflects the user's current emotional state in real time.

[1432] "Basic user information" refers to personal identification information such as the user's name, age, and gender.

[1433] "Information about mental state" is information about the user's current mood and psychological state.

[1434] "Means for analyzing emotions" refers to technology or devices for recognizing and analyzing a user's emotions based on their facial expressions and tone of voice.

[1435] A "generative artificial intelligence model" is an artificial intelligence model that generates appropriate output, i.e., counseling content, based on input data.

[1436] "Counseling content" refers to advice and support provided according to the user's mental state and emotions.

[1437] "Feedback" refers to the user's evaluation and impressions of the counseling content provided.

[1438] A "server" is a computer system that receives input information from a user, processes it, and returns generated counseling content to the user.

[1439] A "database" is a storage system that stores collected user information and feedback so that it can be referenced as needed.

[1440] The "visual display means" refers to a display or other display device for providing the generated counseling content to the user in the form of text, images, or the like.

[1441] "User input information" refers to basic information and information relating to mental state that a user provides to the system.

[1442] The present invention provides a system that collects basic information and information about a user's mental state, recognizes emotions using an emotion engine, and provides more appropriate counseling content. Specific embodiments of this system are described below.

[1443] Collection of User Information

[1444] First, a user accesses the system using a smartphone application. When the user first accesses the system, the application prompts the user to enter basic information. This information includes name, age, and gender. For example, the user enters "Yamada Taro, 30 years old, male."

[1445] Input of user's mental state

[1446] The smartphone application also displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[1447] Sending information

[1448] The smartphone application sends the collected basic information and information about mental state to a server, which receives the information and stores it in a database.

[1449] Emotion recognition

[1450] The emotion engine uses the smartphone's camera and microphone to recognize the user's emotions. The emotion engine recognizes emotion data by analyzing the user's facial expressions and tone of voice. For example, when a user speaks into the camera, emotions such as "anxiety" or "sadness" are recognized from their facial expressions.

[1451] Sending emotional data

[1452] The emotion data recognized by the emotion engine is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[1453] Counseling content generation

[1454] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate for the user's situation. For example, the server sends a request to the generative AI model saying, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." The generative AI model then generates advice such as, "Try deep breathing exercises to relax."

[1455] Providing counseling content

[1456] The server receives the generated counseling content and sends it to a smartphone application. The application visually displays the generated counseling content to the user. For example, the device may display a message on the user's screen saying, "Try these deep breathing exercises to relax." Specific exercise instructions may also be displayed along with illustrations.

[1457] User Feedback

[1458] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[1459] Sending and processing feedback

[1460] The smartphone application collects user feedback and sends it to a server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server uses the accumulated feedback to improve the generative AI model and increase the accuracy of future counseling content.

[1461] Processing flow with concrete examples

[1462] For example, if a user is feeling anxious, the following flow may occur.

[1463] 1. A smartphone application asks the user, "How are you feeling today?"

[1464] 2. The user types, "I feel anxious."

[1465] 3. The smartphone's camera and microphone use an emotion engine to recognize "anxiety" from the user's facial expression.

[1466] 4. The smartphone application sends the input information and emotion data to the server.

[1467] 5. The server receives the information and generates counseling content based on a generative artificial intelligence model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[1468] 6. The smartphone application displays the generated counseling content to the user.

[1469] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[1470] 8. The smartphone application sends the feedback to the server.

[1471] 9. The server improves the generative AI model based on the feedback and stores it in a database.

[1472] To illustrate, here's an example prompt:

[1473] Customer is feeling anxious, provide suitable advice.

[1474] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1475] Step 1:

[1476] The user accesses the smartphone application and inputs basic information and information about their mental state.

[1477] Input: User inputs basic information (name, age, gender) and mental state (mood, sleep quality, etc.).

[1478] Output: Collected basic and mental status information data.

[1479] Specific operation: The user enters information according to the initial setup screen of the app, and the app temporarily saves that information.

[1480] Step 2:

[1481] The smartphone's camera and microphone are used to recognize the user's emotions. The emotion engine analyzes facial expressions and tone of voice to generate emotion data.

[1482] Input: User's facial expression video and audio data.

[1483] Output: Parsed emotion data (e.g., "anxiety", "sadness", etc.).

[1484] How it works: The app uses a camera and microphone to capture the user's facial expressions and voice in real time, and the emotion engine analyzes them.

[1485] Step 3:

[1486] The smartphone application sends the collected basic information, mental state information, and emotion data to a server.

[1487] Input: User's basic information, mental state information, and emotional data.

[1488] Output: All data sent to the server.

[1489] Specific operation: The app batches data into packets and sends them over the network to the server.

[1490] Step 4:

[1491] The server stores the received information in a database.

[1492] Input: Basic information, mental state information, emotional data.

[1493] Output: Information stored in a database.

[1494] Specific operation: The server analyzes the received data and stores it in the database in the appropriate format.

[1495] Step 5:

[1496] The server generates counseling content using a generative artificial intelligence model. Information is input as prompts to the model, and counseling content is output.

[1497] Input: Basic information, mental state information, emotion data. Prompt text: "This user is slightly depressed, has poor sleep quality, and is anxious according to the emotion engine. Please generate appropriate counseling advice."

[1498] Output: Generated counseling content.

[1499] Specific operation: The server sends a prompt to the generative artificial intelligence model, which generates appropriate counseling content.

[1500] Step 6:

[1501] The server sends the generated counseling content to the smartphone application.

[1502] Input: Generated counseling content.

[1503] Output: Counseling content sent to the smartphone application.

[1504] Specific operation: The server sends the generated counseling content to the app via the network.

[1505] Step 7:

[1506] A smartphone application visually displays the generated counseling content to the user.

[1507] Input: Counseling content submitted.

[1508] Output: The counseling content that the user sees.

[1509] Specific operation: The app displays the counseling content received in text and images.

[1510] Step 8:

[1511] Users put the provided counseling content into practice and enter the results into the app as feedback.

[1512] Input: User feedback information.

[1513] Output: Feedback input data.

[1514] Specific operation: The user performs the advice and enters the results in the app's feedback screen.

[1515] Step 9:

[1516] The smartphone application sends the user's feedback to a server.

[1517] Input: User feedback information.

[1518] Output: Feedback information sent to the server.

[1519] Specific operation: The app collects feedback information and compiles it into packets, which are then sent over the network to a server.

[1520] Step 10:

[1521] The server stores the received feedback in a database and uses a generative artificial intelligence model to improve the accuracy of future counseling sessions.

[1522] Input: User feedback information.

[1523] Output: Feedback information stored in a database, an improved generative artificial intelligence model.

[1524] Specific operation: The server stores the received feedback in a database and uses that data to learn and improve the generative artificial intelligence model.

[1525] 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.

[1526] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[1527] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1528] [Fourth embodiment]

[1529] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1530] 7, a 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.

[1531] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the 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).

[1532] 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.

[1533] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1534] 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 surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1535] 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.

[1536] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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.

[1537] 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.

[1538] 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 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.

[1539] 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.

[1540] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1541] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1542] ---

[1543] The present invention is a system for collecting basic information and information on a user's mental state, and generating and providing appropriate counseling content based on this information. A specific embodiment of this system will be described below.

[1544] Collection of User Information

[1545] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Taro Tanaka, 35 years old, male."

[1546] Input of user's mental state

[1547] The device then displays questions about the user's current mental state, such as "How are you feeling today?" and "How is the quality of your sleep these days?" The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[1548] Sending information

[1549] The device sends the collected user information and mental state information to the server, which receives the information and stores it in a database.

[1550] Counseling content generation

[1551] Based on the stored information, the server uses a generative artificial intelligence model to generate counseling content appropriate for the user's situation. For example, the server might send a request to the AI ​​model saying, "This user is feeling a little depressed and has poor sleep quality. Please generate appropriate counseling advice." The AI ​​model then generates advice such as, "Try deep breathing exercises to relax."

[1552] Providing counseling content

[1553] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "Try these deep breathing exercises to relax." Specific exercise methods may also be displayed along with illustrations.

[1554] User Feedback

[1555] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[1556] Sending and processing feedback

[1557] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server continuously improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[1558] Processing flow with concrete examples

[1559] For example, if a user is feeling anxious, the following flow may occur.

[1560] 1. The device asks the user, "How are you feeling today?"

[1561] 2. The user types, "I feel anxious."

[1562] 3. The device sends the input information to the server.

[1563] 4. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[1564] 5. The terminal displays the generated counseling content to the user.

[1565] 6. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[1566] 7. The device sends the feedback to the server.

[1567] 8. The server improves the AI ​​model based on the feedback and stores it in a database.

[1568] As can be seen, the present invention allows users to receive prompt and personalized counseling, and through feedback the quality of the system is continually improved.

[1569] The processing flow will be explained below.

[1570] Processing Steps

[1571] Step 1:

[1572] The device displays the initial user registration screen, where the user enters basic information such as name, age, and gender.

[1573] Step 2:

[1574] The user enters basic information, and the device sends this information to the server. Specifically, information such as "Name: Taro Tanaka," "Age: 35," and "Gender: Male" is sent to the server in JSON format.

[1575] Step 3:

[1576] The server stores the received basic information in a database, which creates a profile for the user.

[1577] Step 4:

[1578] The device will display questions about the user's current mental state, such as "How are you feeling today?" and "How has your sleep been lately?"

[1579] Step 5:

[1580] The user answers each question, for example, selecting "Mood: slightly depressed" and "Sleep quality: poor."

[1581] Step 6:

[1582] The device sends the user's answers to the server, also in JSON format.

[1583] Step 7:

[1584] The server inputs the received information into a generative AI model and instructs it to generate optimal counseling content. Specifically, the AI ​​model requests, "Please provide advice appropriate for a user who is feeling a little depressed and has poor quality sleep."

[1585] Step 8:

[1586] The server receives the response from the AI ​​model and sends the generated counseling content to the device, for example, "Try deep breathing exercises to relax."

[1587] Step 9:

[1588] The device displays the counseling content to the user, who then checks the content displayed on the screen and also looks at specific exercise methods.

[1589] Step 10:

[1590] The user practices the counseling provided, for example, by following the on-screen instructions to perform deep breathing exercises.

[1591] Step 11:

[1592] The user enters feedback about the effectiveness of the advice, for example, "The deep breathing exercises were very effective."

[1593] Step 12:

[1594] The device sends the user's feedback to the server, which is also sent in JSON format.

[1595] Step 13:

[1596] The server stores the feedback in a database, which is used to improve the generative artificial intelligence model.

[1597] Step 14:

[1598] The server uses the accumulated feedback to tune the AI ​​model and use it to generate the next counseling session. Specifically, the feedback data is passed through an analysis algorithm to retrain the model.

[1599] Through these steps, users are provided with fast, personalized counseling and the system is continually improved.

[1600] Example 1

[1601] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1602] Conventional counseling systems have had the problem of being difficult to provide individualized support tailored to the user's mental state. Furthermore, the mechanism for collecting feedback and using it to improve the system has not been fully established, limiting the improvement of the accuracy of the counseling content. Furthermore, the counseling content provided is sometimes difficult to understand visually, making it difficult for users to put the system into practice.

[1603] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1604] In this invention, the server includes means for inputting basic information and information about a user's mental state, means for transmitting the input information, means for generating counseling content using a generative AI model, means for visually providing the generated counseling content, means for displaying specific examples of the counseling content together with illustrations, means for inputting user feedback, means for transmitting the feedback, and means for improving the generative AI model based on the feedback. This makes it easier to provide personalized counseling content and for users to put it into practice, and enables continuous improvement of the system through collected feedback.

[1605] "Basic user information" refers to basic data for identifying an individual, such as the user's name, age, and gender.

[1606] "Information about mental state" is data that indicates the user's current psychological state, including mood, sleep quality, stress level, and the like.

[1607] A "server" is a computer system that receives, stores, processes, and transmits data.

[1608] A "generative artificial intelligence model" is an artificial intelligence algorithm that generates new information based on given data, and examples of this include language models such as GPT-3.

[1609] "Counseling content" refers to advice and support information generated based on the user's mental state.

[1610] "Visual means" are ways of presenting information in a format that is easy for users to understand, such as text or illustrations.

[1611] "Feedback" refers to the user's opinions and impressions regarding the effectiveness and satisfaction of the counseling content provided.

[1612] A database is a system for organizing and storing information, and is constructed so that it can be searched and used efficiently later.

[1613] An "illustration" is an image or diagram that visually explains information.

[1614] The present invention is a system for collecting basic information and information on a user's mental state, and generating and providing appropriate counseling content based on this information. A specific embodiment of this system will be described below.

[1615] Collection of User Information

[1616] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[1617] Input of user's mental state

[1618] The device then displays questions about the user's current mental state, such as "How are you feeling today?" and "How is the quality of your sleep these days?" The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly irritable" and "Sleep quality: average."

[1619] Sending information

[1620] The device sends the collected user information and mental state information to the server, which receives the information and stores it in a database.

[1621] Counseling content generation

[1622] Based on the stored information, the server uses a generative artificial intelligence model (such as GPT-3) to generate counseling content appropriate for the user's situation. For example, the server sends a request to the AI ​​model saying, "This user is somewhat irritable and has average sleep quality. Please generate appropriate counseling advice." The AI ​​model generates advice such as, "Try yoga or meditation at the end of the day to relax."

[1623] Providing counseling content

[1624] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "To relax, try yoga or meditation at the end of the day." Specific exercise methods may also be displayed with illustrations.

[1625] User Feedback

[1626] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[1627] Sending and processing feedback

[1628] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server continuously improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[1629] Processing flow with concrete examples

[1630] For example, if a user is feeling stressed, the following flow may occur.

[1631] 1. The device asks the user, "How are you feeling today?"

[1632] 2. The user types, "I'm feeling stressed."

[1633] 3. The device sends the input information to the server.

[1634] 4. The server receives the information and generates counseling content based on the AI ​​model, such as "Try taking deep breaths and calming your mind to reduce stress."

[1635] 5. The terminal displays the generated counseling content to the user.

[1636] 6. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[1637] 7. The device sends the feedback to the server.

[1638] 8. The server improves the AI ​​model based on the feedback and stores it in a database.

[1639] As can be seen, the present invention allows users to receive prompt and personalized counseling, and through feedback the quality of the system is continually improved.

[1640] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1641] System program processing steps

[1642] Step 1:

[1643] User Action:

[1644] A user accesses the system using a terminal.

[1645] Input: The user enters basic information (such as name, age, and gender) into the device's initial setup screen.

[1646] Output: Basic information is displayed on the terminal.

[1647] Specific behavior: The device provides the user with input fields such as "What is your name?", "How old are you?", and "What is your gender?", and the user enters the information accordingly.

[1648] Step 2:

[1649] User Action:

[1650] The user inputs information about the mental state into the terminal.

[1651] Input: The user answers questions like "How are you feeling today?" and "How have you been sleeping lately?"

[1652] Output: Terminal displays information about mental state.

[1653] Specific operation: The device presents the user with multiple-choice questions such as "How are you feeling today?" and "How has your sleep been lately?", and the user selects an answer from multiple options.

[1654] Step 3:

[1655] The device:

[1656] The terminal transmits the collected basic information and information regarding mental state to a server.

[1657] Input: Basic information and mental state information entered by the user.

[1658] Output: User information sent to the server.

[1659] Specific operation: The terminal displays the message "Sending user information..." and sends the information entered by the user to the server.

[1660] Step 4:

[1661] The server:

[1662] The server receives the transmitted information and stores it in a database.

[1663] Input: Basic information and mental state information about the user sent from the device.

[1664] Output: User information stored in the database.

[1665] Specific operation: The server records a log message such as "User information saved" and stores the information in the "User Information" table in the database.

[1666] Step 5:

[1667] The server:

[1668] The server generates counseling content using a generative AI model based on the stored information.

[1669] Input: User information retrieved from the database.

[1670] Output: Generated counseling content.

[1671] Data processing: Generates a prompt sentence based on the input information and sends a request to the generative AI model.

[1672] Specific operation: The server generates a prompt message saying, "This user is slightly irritable and has average sleep quality. Please generate appropriate counseling advice," and sends it to the AI ​​model (e.g., GPT-3). The AI ​​model receives the advice and returns the counseling content, "Try yoga or meditation at the end of the day to relax," to the server.

[1673] Step 6:

[1674] The server:

[1675] The server transmits the generated counseling content to the terminal.

[1676] Input: Generated counseling content.

[1677] Output: Counseling content sent to the device.

[1678] Specific operation: The server displays the message "Sending counseling content..." and sends the generated content to the terminal.

[1679] Step 7:

[1680] The device:

[1681] The terminal visually displays the generated counseling content to the user.

[1682] Input: Counseling content sent from the server.

[1683] Output: Counseling content displayed on the terminal.

[1684] Specific action: The device displays a message on the user's screen saying, "Try yoga or meditation at the end of the day to relax," along with illustrations of specific exercise methods.

[1685] Step 8:

[1686] User Action:

[1687] The user practices the counseling content provided and provides feedback on its effectiveness.

[1688] Input: Counseling content implementation results and feedback.

[1689] Output: Feedback typed into the terminal.

[1690] Specific behavior: The user enters feedback such as "This advice was helpful" or "I was satisfied with the advice."

[1691] Step 9:

[1692] The device:

[1693] The terminal sends the user's feedback to the server.

[1694] Input: Feedback entered by the user.

[1695] Output: Feedback sent to the server.

[1696] Specific operation: The device displays the message "Sending feedback..." and sends the feedback data to the server.

[1697] Step 10:

[1698] The server:

[1699] The server receives the feedback and stores it in a database.

[1700] Input: Feedback sent from the device.

[1701] Output: Feedback stored in a database.

[1702] Specific behavior: The server records a log message such as "Feedback saved" and stores the feedback data in the "feedback" table in the database.

[1703] Step 11:

[1704] The server:

[1705] The server improves the generative artificial intelligence model based on the feedback.

[1706] Input: Feedback stored in the database.

[1707] Output: An improved generative artificial intelligence model.

[1708] Specific operation: The server uses the accumulated feedback as training data for the AI ​​model to improve the accuracy of the counseling content from the next time onwards.

[1709] Through the above steps, the present invention realizes a series of processes for generating and providing counseling content based on individual information of the user, and improving the system through feedback.

[1710] (Application example 1)

[1711] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1712] In modern society, prompt and individualized care for users' mental health is important, but existing systems make it difficult to quickly provide counseling tailored to each individual user. Furthermore, brick-and-mortar counseling services lack tools that allow staff to effectively assess users' mental states and provide appropriate advice. Furthermore, there is a need for a system that utilizes feedback from users to continuously improve the quality of counseling. The purpose of this invention is to solve these problems.

[1713] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1714] In this invention, the server includes means for inputting basic information about a user, means for inputting information about the user's mental state, means for transmitting the user's input information to the server, means for generating counseling content in the server using a generative artificial intelligence model based on the information, means for providing the generated counseling content to the user, means for inputting feedback from the user, means for transmitting the feedback to the server, means for improving the generative artificial intelligence model based on the feedback, and means for evaluating the user's mental state using an information terminal used by staff in a physical store and visually providing the counseling content displayed on the information terminal, thereby making it possible to provide prompt and personalized counseling even in a physical store.

[1715] "Means for inputting basic user information" refers to devices or software that provide an interface for users to input personal information such as their name, age, and gender.

[1716] The "means for inputting information about the user's mental state" refers to a device or software that provides an interface for the user to input their current mood or psychological state in the form of a question or the like.

[1717] The "means for transmitting user input information to the server" refers to a device or software for transmitting the basic information and mental state information input by the user to the server via a network.

[1718] "Means for generating counseling content using a generative artificial intelligence model" refers to software or algorithms that use generative AI to generate counseling content appropriate for individual users based on collected information.

[1719] The "means for providing the generated counseling content to the user" refers to a device or software for displaying the generated counseling content on the user's terminal.

[1720] The "means for allowing the user to input feedback" refers to a device or software that provides an interface for the user to input feedback such as the usefulness and satisfaction level of the counseling provided.

[1721] The "means for transmitting feedback to the server" refers to a device or software for transmitting the feedback information input by the user to the server via a network.

[1722] "Means for improving the generative artificial intelligence model based on feedback" refers to software or algorithms that use collected feedback information to update the generative AI model and improve it so that it can generate more appropriate and effective counseling content.

[1723] "Means for evaluating the mental state of a user using an information terminal used by staff in a physical store and visually providing counseling content displayed on the information terminal" refers to devices or software that evaluate the mental state of a customer using a terminal such as a smartphone or tablet used by staff in a physical store, and visually display and provide counseling content generated based on the evaluation results.

[1724] MODE FOR CARRYING OUT THE INVENTION

[1725] System Overview

[1726] This system collects basic information about the user and information about their mental state, and uses a generative AI model on the server to generate counseling content and provide it to the user. Furthermore, it can collect feedback and use it to improve the generative AI model.

[1727] Hardware and software used

[1728] Hardware: Smartphones, smart glasses, tablets, servers

[1729] Software: Python, Flask, TensorFlow, SQLite

[1730] System Operation

[1731] 1. User Information Collection:

[1732] Users access the system using a device such as a smartphone or tablet, which displays an interface that prompts them to enter basic information such as their name, age, and gender.

[1733] Example: A user enters the information "Taro Tanaka, 35 years old, male."

[1734] 2. Mental state input:

[1735] The device also displays questions about your mental state, such as "How are you feeling today?" and "How has your sleep been lately?"

[1736] Example: User responds "Mood: Slightly depressed" and "Sleep quality: Poor."

[1737] 3. Transmission of information to the server:

[1738] The device sends the collected user information and mental state information to the server, which receives the information and stores it in an SQLite database.

[1739] 4. Counseling content generation:

[1740] Based on the stored information, the server sends a request to a generative artificial intelligence model using TensorFlow to generate appropriate counseling content.

[1741] Example: Generate advice such as "This user is feeling a bit depressed and has poor sleep quality. Try some deep breathing exercises to relax."

[1742] 5. Provision of counseling content:

[1743] The server transmits the generated counseling content to the terminal, which visually displays the generated counseling content to the user.

[1744] Example: The device displays "Try this deep breathing exercise to relax" on the user's screen.

[1745] 6. User Feedback:

[1746] Users put the provided counseling into practice and provide feedback on its effectiveness, including comments such as "The advice was helpful" and "I would like to use this service again."

[1747] 7. Submitting Feedback:

[1748] The device sends the collected feedback to a server, which receives it and stores it in a database. This feedback is used to continuously improve the generative AI model.

[1749] For example, enter your feedback as "Satisfied: 4 / 5" and "Helpful" and submit.

[1750] Specific prompt examples

[1751] Example prompt sentence:

[1752] "How are users feeling?"

[1753] "How's your sleep quality lately?"

[1754] "Try some deep breathing exercises to help you relax."

[1755] In this way, by linking various data inputs tailored to the purpose with generative AI models, it is possible to provide practical and valuable counseling content to users. Furthermore, by continuously improving the system using feedback, it is possible to achieve even more accurate counseling.

[1756] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1757] Step 1:

[1758] Collection of User Information

[1759] Users access the system using a smartphone or tablet. They enter basic information such as their name, age, and gender into the input interface. The device collects the input data and compiles it into a format that can be sent to the server.

[1760] Input: Basic user information such as name, age, and gender

[1761] Processing: The device formats the collected information

[1762] Output: User basic information formatted to send to the server

[1763] Step 2:

[1764] Mental state input

[1765] The device asks the user questions about their mental state, such as "How are you feeling today?" or "How has your sleep been lately?" The user selects the appropriate answer for each question.

[1766] Input: Information about your mental state, such as how you're feeling today and the quality of your recent sleep

[1767] Processing: The device collects the user's answers and formats them into a format that can be sent to the server.

[1768] Output: Formatted mental state information to send to the server

[1769] Step 3:

[1770] Sending information to the server

[1771] The device sends the collected user information and mental state information to a server, which receives the information and stores it in an SQLite database.

[1772] Input: User basic information and mental state information

[1773] Processing: The device sends the information to the server, which stores it in a database

[1774] Output: User basic information and mental state information stored in the database

[1775] Step 4:

[1776] Counseling content generation

[1777] Based on the information stored in the database, the server sends a request to a generative artificial intelligence model using TensorFlow to generate appropriate counseling content.

[1778] Input: User basic information and mental state information

[1779] Processing: The server inputs information into the generative AI model, which then generates counseling content.

[1780] Output: Generated counseling content

[1781] Step 5:

[1782] Providing counseling content

[1783] The server transmits the generated counseling content to the terminal, which visually displays the generated counseling content to the user.

[1784] Input: Generated counseling content

[1785] Processing: The server sends the counseling content to the terminal, and the terminal displays the content.

[1786] Output: Visually displayed counseling content

[1787] Step 6:

[1788] User Feedback

[1789] Users put the provided counseling into practice and provide feedback on its effectiveness, including comments such as "The advice was helpful" and "I would like to use this service again."

[1790] Input: Feedback on counseling content

[1791] Processing: The device collects the feedback and formats it to be sent to the server.

[1792] Output: Formatted feedback to send to the server

[1793] Step 7:

[1794] Send and save feedback

[1795] The device sends the collected feedback to a server, which receives it and stores it in a database. This feedback is used to continuously improve the generative AI model.

[1796] Input: Feedback

[1797] Processing: The server stores the feedback in a database and updates the generative AI model.

[1798] Output: Feedback and improved generative AI models stored in a database

[1799] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1800] ---

[1801] The present invention provides a system that collects basic information and information about a user's mental state, and further recognizes the user's emotions using an emotion engine, thereby providing more appropriate counseling content. Specific embodiments of this system are described below.

[1802] Collection of User Information

[1803] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and provides an interface for the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[1804] Input of user's mental state

[1805] The device then displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[1806] Sending information

[1807] The device sends the collected basic information and information about mental state to a server, which receives the information and stores it in a database.

[1808] Emotion recognition

[1809] The device is equipped with an emotion engine that recognizes the user's emotions. The emotion engine recognizes emotion data by analyzing the user's facial expressions and tone of voice. For example, when a user speaks into the camera, emotions such as "anxiety" or "sadness" are recognized from their facial expressions.

[1810] Sending emotional data

[1811] The emotion data recognized by the emotion engine is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[1812] Counseling content generation

[1813] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate for the user's situation. For example, the server might send a request to the AI ​​model saying, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." The AI ​​model then generates advice such as, "Try deep breathing exercises to relax."

[1814] Providing counseling content

[1815] The server receives the generated counseling content and sends it to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display on the user's screen, "Try these deep breathing exercises to relax." Specific exercise methods may also be displayed along with illustrations.

[1816] User Feedback

[1817] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[1818] Sending and processing feedback

[1819] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server uses the accumulated feedback to improve the generative AI model and increase the accuracy of future counseling content.

[1820] Processing flow with concrete examples

[1821] For example, if a user is feeling anxious, the following flow may occur.

[1822] 1. The device asks the user, "How are you feeling today?"

[1823] 2. The user types, "I feel anxious."

[1824] 3. The device uses an emotion engine to recognize "anxiety" from the user's facial expression.

[1825] 4. The device sends the input information and emotion data to the server.

[1826] 5. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[1827] 6. The terminal displays the generated counseling content to the user.

[1828] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[1829] 8. The device sends the feedback to the server.

[1830] 9. The server improves the AI ​​model based on the feedback and stores it in a database.

[1831] As described above, the present invention allows users to receive prompt and personalized counseling, and by utilizing emotion data in addition, more accurate counseling content can be provided. The quality of the system is continuously improved through feedback.

[1832] The processing flow will be explained below.

[1833] Processing Steps

[1834] Step 1:

[1835] The terminal displays the initial user registration screen to the user, who enters basic information such as name, age, and gender.

[1836] Step 2:

[1837] The user enters basic information, and the device sends this information to the server, specifically, data such as name, age, and gender in JSON format.

[1838] Step 3:

[1839] The server stores the received basic information in a database, which creates a profile for the user.

[1840] Step 4:

[1841] The device will prompt the user with questions about their current mental state, such as "How are you feeling today?" or "How's the quality of your sleep lately?"

[1842] Step 5:

[1843] The user answers each question, for example, selecting "Mood: slightly depressed" and "Sleep quality: poor."

[1844] Step 6:

[1845] The device sends the user's answers to the server, also in JSON format.

[1846] Step 7:

[1847] The emotion engine installed in the device recognizes the user's emotions. Specifically, it uses the device's camera and microphone to analyze the user's facial expressions and tone of voice. For example, the emotion engine recognizes "anxiety."

[1848] Step 8:

[1849] The terminal transmits the emotion data to the server, along with the basic information and mental state data.

[1850] Step 9:

[1851] The server inputs the received information into a generative AI model and instructs it to generate optimal counseling content. Specifically, it requests, "This user is feeling a little depressed, has poor sleep quality, and is also feeling anxious. Please generate appropriate counseling advice."

[1852] Step 10:

[1853] The server receives the response from the AI ​​model and sends the generated counseling content to the device, for example, "Try deep breathing exercises to relax."

[1854] Step 11:

[1855] The device displays the counseling content to the user, who then checks the content displayed on the screen and also looks at specific exercise methods.

[1856] Step 12:

[1857] The user practices the counseling provided, for example, by following the on-screen instructions to perform deep breathing exercises.

[1858] Step 13:

[1859] The user enters feedback about the effectiveness of the advice, for example, "The deep breathing exercises were very effective."

[1860] Step 14:

[1861] The device sends the user's feedback to the server, which is also sent in JSON format.

[1862] Step 15:

[1863] The server stores the feedback in a database, which is used to improve the generative artificial intelligence model.

[1864] Step 16:

[1865] The server uses the accumulated feedback to tune the AI ​​model and use it to generate the next counseling session. Specifically, the feedback data is passed through an analysis algorithm to retrain the model.

[1866] Through these steps, the system provides users with fast and personalized counseling, and the system is continuously improved. By using emotion data recognized by the emotion engine, the system can provide more accurate counseling content.

[1867] Example 2

[1868] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1869] Conventional counseling systems only provide counseling content based on the user's basic information and mental state, and have the problem of difficulty in responding to the user's real-time emotional state. Therefore, there is a need to provide more accurate and personalized counseling by incorporating emotional data such as the user's facial expressions and tone of voice.

[1870] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting basic information about the user, means for inputting information about the user's mental state, means for analyzing the user's facial expression and tone of voice using a terminal equipped with an emotion analysis engine and recognizing emotion data, means for transmitting this to the server, means for generating counseling content based on this information using a generative AI model, means for visually providing the generated counseling content, means for inputting user feedback, means for transmitting the feedback to the server and storing it, and means for improving the generative AI model based on these. This makes it possible to provide personalized counseling that reflects the user's real-time emotion data.

[1871] "User" refers to an individual who uses the system.

[1872] "Basic Information" refers to personal data such as name, age, and gender provided by the User.

[1873] "Mental state information" is data about emotions and psychological states input by the user, including answers to questions such as "How are you feeling today?"

[1874] "Server" refers to a central computer system for processing and storing information on a network.

[1875] A "generative artificial intelligence model" refers to an artificial intelligence engine that generates responses such as counseling content based on user input information.

[1876] "Counseling content" refers to advice and instructions for the user generated by the generative artificial intelligence model.

[1877] "Feedback" refers to the user's opinions and thoughts regarding the counseling content provided.

[1878] "Emotion analysis engine" refers to software and hardware components for analyzing a user's facial expressions and tone of voice to recognize emotional data.

[1879] "Terminal" refers to a device (smartphone, tablet, PC, etc.) that a user uses to access the system.

[1880] "Database" refers to a system for systematically storing and managing information on a server.

[1881] The present invention provides a system that collects basic information and information about a user's mental state, and further recognizes the user's emotions using an emotion analysis engine, thereby providing more appropriate counseling content. Specific embodiments of this system are described below.

[1882] Collection of User Information

[1883] First, a user accesses the system using a terminal. The terminal displays an initial setup screen and prompts the user to enter basic information. Basic information includes name, age, gender, etc. For example, the user enters information such as "Yamada Taro, 30 years old, male."

[1884] Input of user's mental state

[1885] Next, the device displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, they might answer "Mood: slightly depressed" or "Sleep quality: poor."

[1886] Sending information

[1887] The user's basic information and mental state information are sent from the device to the server, which receives the information and stores it in a database.

[1888] Emotion recognition

[1889] The device is equipped with an emotion analysis engine that analyzes the user's facial expressions and tone of voice to recognize emotional data. For example, when a user speaks to the camera, emotions such as "anxiety" or "sadness" can be detected from their facial expressions.

[1890] Sending emotional data

[1891] The recognized emotion data is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[1892] Counseling content generation

[1893] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate to the user's situation. The prompt might be something like, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." Based on this prompt, the generative AI model (e.g., GPT-4) generates advice such as, "Try deep breathing exercises to relax."

[1894] Providing counseling content

[1895] The generated counseling content is sent from the server to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal may display "Try some deep breathing exercises to relax," along with specific exercise instructions along with diagrams.

[1896] User Feedback

[1897] The user puts the counseling provided into practice and provides feedback on its effectiveness, for example, "The advice was helpful."

[1898] Sending and processing feedback

[1899] The device collects user feedback and sends it to the server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server improves the generative AI model based on the accumulated feedback, improving the accuracy of future counseling content.

[1900] The process flow with concrete examples, for example, if the user is feeling anxious, is as follows:

[1901] 1. The device asks the user, "How are you feeling today?"

[1902] 2. The user types, "I feel anxious."

[1903] 3. The device uses an emotion analysis engine to recognize "anxiety" from the user's facial expression.

[1904] 4. The device sends the input information and emotion data to the server.

[1905] 5. The server receives the information and generates counseling content based on the AI ​​model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[1906] 6. The terminal displays the generated counseling content to the user.

[1907] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[1908] 8. The device sends the feedback to the server.

[1909] 9. The server improves the AI ​​model based on the feedback and stores it in a database.

[1910] As described above, the present invention allows users to receive prompt and personalized counseling. By also utilizing emotion data, more accurate counseling content is provided, and feedback allows for continuous improvement of the system's quality.

[1911] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1912] Step 1:

[1913] A user accesses the system using a terminal. The terminal displays an initial setup screen and prompts the user to enter basic information (such as name, age, and gender). When the user enters "Yamada Taro, 30 years old, male," the terminal temporarily stores this information. The entered basic information is sent to the server.

[1914] Step 2:

[1915] The device displays questions about the user's mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. If the user answers "Mood: slightly depressed" or "Sleep quality: poor," this information is also temporarily stored on the device. Information about the mental state is also sent to the server.

[1916] Step 3:

[1917] The server receives the basic information and mental state information sent from the device and stores it in a database. Specifically, data such as "User name: Yamada Taro," "Age: 30," "Mood: slightly depressed," and "Sleep quality: poor" are stored.

[1918] Step 4:

[1919] The emotion analysis engine installed in the device analyzes the user's facial expressions and tone of voice to recognize emotional data. For example, when a user speaks into the camera, the emotion analysis engine recognizes emotions such as "anxiety" or "sadness" from their facial expressions. The analyzed emotional data is temporarily stored on the device.

[1920] Step 5:

[1921] The device sends the recognized emotion data along with basic information and mental state data to the server. The server receives this and stores it in a database. Specifically, additional data such as "emotion: anxiety" is stored.

[1922] Step 6:

[1923] The server generates counseling content using a generative AI model based on the stored basic information, mental state information, and emotion data. The prompt text is, "This user is slightly depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." Based on this prompt text, the generative AI model generates advice such as, "Try deep breathing exercises to relax."

[1924] Step 7:

[1925] The server sends the generated counseling content to the terminal. The terminal visually displays the generated counseling content to the user. For example, the terminal screen may display "Try deep breathing exercises for relaxation" along with illustrations of specific exercise methods.

[1926] Step 8:

[1927] The user puts the counseling provided into practice and inputs feedback about its effectiveness, such as "This advice was helpful."

[1928] Step 9:

[1929] The device sends the user's feedback to the server. The server receives the feedback and stores it in a database. The accumulated feedback is used to improve the generative AI model, helping to increase the quality of the system. For example, the AI ​​model will be able to generate more appropriate counseling content based on the user's feedback from the next time onwards.

[1930] (Application example 2)

[1931] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1932] Conventional counseling systems generate counseling content based only on the user's basic information and mental state, which limits their accuracy. Furthermore, they lack the means to recognize the user's emotions in real time, making it difficult to provide optimal counseling for each individual user. As a result, user satisfaction declines, and the effectiveness of the system is not fully realized.

[1933] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for inputting basic information and information about the mental state of the user, means for analyzing the user's emotions, and means for generating counseling content using a generative artificial intelligence model based on the information and emotion analysis data. This makes it possible to provide personalized counseling content that reflects the user's current emotional state in real time.

[1934] "Basic user information" refers to personal identification information such as the user's name, age, and gender.

[1935] "Information about mental state" is information about the user's current mood and psychological state.

[1936] "Means for analyzing emotions" refers to technology or devices for recognizing and analyzing a user's emotions based on their facial expressions and tone of voice.

[1937] A "generative artificial intelligence model" is an artificial intelligence model that generates appropriate output, i.e., counseling content, based on input data.

[1938] "Counseling content" refers to advice and support provided according to the user's mental state and emotions.

[1939] "Feedback" refers to the user's evaluation and impressions of the counseling content provided.

[1940] A "server" is a computer system that receives input information from a user, processes it, and returns generated counseling content to the user.

[1941] A "database" is a storage system that stores collected user information and feedback so that it can be referenced as needed.

[1942] The "visual display means" refers to a display or other display device for providing the generated counseling content to the user in the form of text, images, or the like.

[1943] "User input information" refers to basic information and information relating to mental state that a user provides to the system.

[1944] The present invention provides a system that collects basic information and information about a user's mental state, recognizes emotions using an emotion engine, and provides more appropriate counseling content. Specific embodiments of this system are described below.

[1945] Collection of User Information

[1946] First, a user accesses the system using a smartphone application. When the user first accesses the system, the application prompts the user to enter basic information. This information includes name, age, and gender. For example, the user enters "Yamada Taro, 30 years old, male."

[1947] Input of user's mental state

[1948] The smartphone application also displays questions about the user's current mental state. For example, questions such as "How are you feeling today?" and "How is the quality of your sleep these days?" are displayed. The user selects the appropriate option for each question and enters their answer. For example, the user answers "Mood: slightly depressed" and "Sleep quality: poor."

[1949] Sending information

[1950] The smartphone application sends the collected basic information and information about mental state to a server, which receives the information and stores it in a database.

[1951] Emotion recognition

[1952] The emotion engine uses the smartphone's camera and microphone to recognize the user's emotions. The emotion engine recognizes emotion data by analyzing the user's facial expressions and tone of voice. For example, when a user speaks into the camera, emotions such as "anxiety" or "sadness" are recognized from their facial expressions.

[1953] Sending emotional data

[1954] The emotion data recognized by the emotion engine is sent to the server along with basic information and mental state data, which is then received and stored in a database.

[1955] Counseling content generation

[1956] Based on the stored information, the server uses a generative AI model to generate counseling content appropriate for the user's situation. For example, the server sends a request to the generative AI model saying, "This user is feeling a little depressed, has poor sleep quality, and, according to the emotion engine, feels anxious. Please generate appropriate counseling advice." The generative AI model then generates advice such as, "Try deep breathing exercises to relax."

[1957] Providing counseling content

[1958] The server receives the generated counseling content and sends it to a smartphone application. The application visually displays the generated counseling content to the user. For example, the device may display a message on the user's screen saying, "Try these deep breathing exercises to relax." Specific exercise instructions may also be displayed along with illustrations.

[1959] User Feedback

[1960] The user puts the counseling provided into practice and provides feedback on its effectiveness, such as "The advice was helpful" or "I was satisfied with the advice."

[1961] Sending and processing feedback

[1962] The smartphone application collects user feedback and sends it to a server. The server receives the feedback and stores it in a database. The stored feedback is used to improve the quality of the system. The server uses the accumulated feedback to improve the generative AI model and increase the accuracy of future counseling content.

[1963] Processing flow with concrete examples

[1964] For example, if a user is feeling anxious, the following flow may occur.

[1965] 1. A smartphone application asks the user, "How are you feeling today?"

[1966] 2. The user types, "I feel anxious."

[1967] 3. The smartphone's camera and microphone use an emotion engine to recognize "anxiety" from the user's facial expression.

[1968] 4. The smartphone application sends the input information and emotion data to the server.

[1969] 5. The server receives the information and generates counseling content based on a generative artificial intelligence model, such as "When you feel anxious, try taking a deep breath and calming yourself."

[1970] 6. The smartphone application displays the generated counseling content to the user.

[1971] 7. The user practices deep breathing and provides feedback on the results, saying, "This advice was helpful."

[1972] 8. The smartphone application sends the feedback to the server.

[1973] 9. The server improves the generative AI model based on the feedback and stores it in a database.

[1974] To illustrate, here's an example prompt:

[1975] Customer is feeling anxious, provide suitable advice.

[1976] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1977] Step 1:

[1978] The user accesses the smartphone application and inputs basic information and information about their mental state.

[1979] Input: User inputs basic information (name, age, gender) and mental state (mood, sleep quality, etc.).

[1980] Output: Collected basic and mental status information data.

[1981] Specific operation: The user enters information according to the initial setup screen of the app, and the app temporarily saves that information.

[1982] Step 2:

[1983] The smartphone's camera and microphone are used to recognize the user's emotions. The emotion engine analyzes facial expressions and tone of voice to generate emotion data.

[1984] Input: User's facial expression video and audio data.

[1985] Output: Parsed emotion data (e.g., "anxiety", "sadness", etc.).

[1986] How it works: The app uses a camera and microphone to capture the user's facial expressions and voice in real time, and the emotion engine analyzes them.

[1987] Step 3:

[1988] The smartphone application sends the collected basic information, mental state information, and emotion data to a server.

[1989] Input: User's basic information, mental state information, and emotional data.

[1990] Output: All data sent to the server.

[1991] Specific operation: The app batches data into packets and sends them over the network to the server.

[1992] Step 4:

[1993] The server stores the received information in a database.

[1994] Input: Basic information, mental state information, emotional data.

[1995] Output: Information stored in a database.

[1996] Specific operation: The server analyzes the received data and stores it in the database in the appropriate format.

[1997] Step 5:

[1998] The server generates counseling content using a generative artificial intelligence model. Information is input as prompts to the model, and counseling content is output.

[1999] Input: Basic information, mental state information, emotion data. Prompt text: "This user is slightly depressed, has poor sleep quality, and is anxious according to the emotion engine. Please generate appropriate counseling advice."

[2000] Output: Generated counseling content.

[2001] Specific operation: The server sends a prompt to the generative artificial intelligence model, which generates appropriate counseling content.

[2002] Step 6:

[2003] The server sends the generated counseling content to the smartphone application.

[2004] Input: Generated counseling content.

[2005] Output: Counseling content sent to the smartphone application.

[2006] Specific operation: The server sends the generated counseling content to the app via the network.

[2007] Step 7:

[2008] A smartphone application visually displays the generated counseling content to the user.

[2009] Input: Counseling content submitted.

[2010] Output: The counseling content that the user sees.

[2011] Specific operation: The app displays the counseling content received in text and images.

[2012] Step 8:

[2013] Users put the provided counseling content into practice and enter the results into the app as feedback.

[2014] Input: User feedback information.

[2015] Output: Feedback input data.

[2016] Specific operation: The user performs the advice and enters the results in the app's feedback screen.

[2017] Step 9:

[2018] The smartphone application sends the user's feedback to a server.

[2019] Input: User feedback information.

[2020] Output: Feedback information sent to the server.

[2021] Specific operation: The app collects feedback information and compiles it into packets, which are then sent over the network to a server.

[2022] Step 10:

[2023] The server stores the received feedback in a database and uses a generative artificial intelligence model to improve the accuracy of future counseling sessions.

[2024] Input: User feedback information.

[2025] Output: Feedback information stored in a database, an improved generative artificial intelligence model.

[2026] Specific operation: The server stores the received feedback in a database and uses that data to learn and improve the generative artificial intelligence model.

[2027] 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.

[2028] 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> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. 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 voice, text data indicating text, and image data indicating an image is also input. 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.

[2029] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[2030] 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.

[2031] FIG. 9 is a diagram illustrating 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 actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect 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.

[2032] 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.

[2033] 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).

[2034] 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 indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, 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 indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2035] 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."

[2036] 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.

[2037] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2038] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2039] 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.

[2040] 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.

[2041] 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.

[2042] The hardware resource for executing a specific process can be any of the following processors: An example of a processor 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. Another example of a processor is 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.

[2043] The hardware resource that executes the specific processing 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 processing may be a single processor.

[2044] 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.

[2045] 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.

[2046] 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.

[2047] 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.

[2048] The following is further disclosed regarding the above embodiment.

[2049] (Claim 1)

[2050] a means for inputting basic information of a user;

[2051] means for inputting information relating to a user's mental state;

[2052] means for transmitting the user input information to a server;

[2053] a means for generating counseling content using a generative artificial intelligence model based on the information in the server;

[2054] means for providing the generated counseling content to the user;

[2055] means for inputting feedback from the user;

[2056] means for transmitting said feedback to a server;

[2057] means for improving the generative artificial intelligence model based on the feedback;

[2058] A system including:

[2059] (Claim 2)

[2060] 2. The system of claim 1, further comprising means in said server for storing said feedback and constructing a database.

[2061] (Claim 3)

[2062] 2. The system according to claim 1, further comprising means for visually displaying the counseling content.

[2063] (Claim 4)

[2064] 2. The system according to claim 1, further comprising means for providing appropriate counseling advice based on the information input by the user.

[2065] "Example 1"

[2066] (Claim 1)

[2067] a means for inputting basic information of a user;

[2068] means for inputting information relating to a user's mental state;

[2069] means for transmitting the input information to a server;

[2070] a means for generating counseling content using a generative artificial intelligence model based on the information in the server;

[2071] a means for visually providing the generated counseling content to a user;

[2072] a means for displaying specific examples of the counseling content together with illustrations;

[2073] a means for inputting user feedback;

[2074] means for transmitting said feedback to a server;

[2075] a means for improving the generative artificial intelligence model based on the feedback;

[2076] A system including:

[2077] (Claim 2)

[2078] 2. The system of claim 1, further comprising means in said server for storing said feedback and constructing a database.

[2079] (Claim 3)

[2080] 2. The system according to claim 1, further comprising means for visually displaying the counseling content and means for displaying specific examples together with illustrations.

[2081] "Application Example 1"

[2082] (Claim 1)

[2083] a means for inputting basic information of a user;

[2084] means for inputting information relating to a user's mental state;

[2085] means for transmitting the user input information to a server;

[2086] a means for generating counseling content using a generative artificial intelligence model based on the information in the server;

[2087] means for providing the generated counseling content to the user;

[2088] means for inputting feedback from the user;

[2089] means for transmitting said feedback to a server;

[2090] means for improving the generative artificial intelligence model based on the feedback;

[2091] In a physical store, staff members use information terminals to assess the user's mental state.

[2092] a means for visually providing the counseling content displayed on the information terminal;

[2093] A system including:

[2094] (Claim 2)

[2095] 10. The system of claim 1, further comprising means for storing said feedback and building a database.

[2096] (Claim 3)

[2097] 2. The system according to claim 1, further comprising means for visually displaying the counseling content.

[2098] "Example 2: Combining Emotion Engines"

[2099] (Claim 1)

[2100] a means for inputting basic information of a user;

[2101] means for inputting information relating to a user's mental state;

[2102] means for transmitting the user input information to a server;

[2103] a means for generating counseling content using a generative artificial intelligence model based on the information in the server;

[2104] means for providing the generated counseling content to the user;

[2105] means for inputting feedback from the user;

[2106] means for transmitting said feedback to a server;

[2107] means for improving the generative artificial intelligence model based on the feedback;

[2108] A terminal including an emotion analysis engine that recognizes the emotions of a user is provided,

[2109] The emotion analysis engine analyzes the user's facial expression and tone of voice;

[2110] means for transmitting the analyzed emotion data to the server;

[2111] A system including:

[2112] (Claim 2)

[2113] 2. The system of claim 1, further comprising means for storing the feedback and emotion data in the server and constructing a database.

[2114] (Claim 3)

[2115] 2. The system according to claim 1, further comprising means for visually displaying the counseling content.

[2116] "Application example 2 when combining emotion engines"

[2117] (Claim 1)

[2118] a means for inputting basic information of a user;

[2119] means for inputting information relating to a user's mental state;

[2120] means for transmitting the user input information to a server;

[2121] means for analyzing the user's emotions;

[2122] a means for generating counseling content using a generative artificial intelligence model based on the information and emotion analysis data in the server;

[2123] means for providing the generated counseling content to the user;

[2124] means for inputting feedback from the user;

[2125] means for transmitting said feedback to a server;

[2126] means for improving the generative artificial intelligence model based on the feedback;

[2127] A system including:

[2128] (Claim 2)

[2129] 2. The system of claim 1, further comprising means in said server for storing said feedback and constructing a database.

[2130] (Claim 3)

[2131] 2. The system according to claim 1, further comprising means for visually displaying the counseling content. [Explanation of symbols]

[2132] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting basic information of a user; means for inputting information relating to a user's mental state; means for transmitting the user input information to a server; a means for generating counseling content using a generative artificial intelligence model based on the information in the server; means for providing the generated counseling content to the user; means for inputting feedback from the user; means for transmitting said feedback to a server; means for improving the generative artificial intelligence model based on the feedback; A system including:

2. 2. The system of claim 1, further comprising means in said server for storing said feedback and constructing a database.

3. 2. The system according to claim 1, further comprising means for visually displaying said counseling content.

4. 2. The system according to claim 1, further comprising means for providing appropriate counseling advice based on the input information of the user.

Images