System

Abstract

To provide a system.SOLUTION: A system includes: first means for acquiring specific information of a child including the age, gender, wishlist, current savings amount, target savings amount, deadline for achieving the goal, and means for earning allowance; second means for allowing the child's parent to digitally send allowance to the child using a remittance function; third means for acquiring the allowance sent by the parent and updating the current savings amount included in the specific information; fourth means for generating a first prompt sentence for outputting advice for reaching the target savings amount included in the specific information on the basis of the specific information and questions from the child; fifth means for generating the advice by inputting the generated first prompt sentence into a generative AI model; and sixth means for presenting the generated advice to the child through a user interface.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including a description and related instruction sentence regarding 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] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] Traditional methods of managing pocket money make it difficult for children to learn the importance of saving and set savings goals, and parents have limited options for sending pocket money to their children. [Means for solving the problem]

[0005] The present disclosure solves the above problems by providing a system for supporting management of children's pocket money. Specifically, the system includes a generating unit that generates specific information including information about a child that is pre-entered in a database, and advice on at least one of how to use and increase the child's savings.

[0006] In addition, in the above system, the generating unit tracks the progress of the child toward reaching the target savings amount, and generates the advice for reaching the target savings amount. The above system further includes an acquiring unit that acquires pocket money sent to the child by the child's parent. This encourages the child to save money toward his or her goal, and allows the child to acquire a sense of responsibility and awareness of saving.

[0007] The above describes the problem that the present disclosure aims to solve and the means for solving the problem.

[0008] "Specific information" refers to information relating to the child, such as the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and the method of obtaining the allowance.

[0009] The "savings target amount" is a specific savings goal that a child sets for his or her future goals. This helps children understand the meaning and purpose of saving and encourages them to save money.

[0010] "Progress tracking" refers to monitoring your child's progress toward their savings goal and tracking their progress toward achieving it, encouraging them to continue working toward their goal and giving them a sense of accomplishment in saving money.

[0011] The acquisition unit acquires, for example, pocket money for a child digitally transferred by the child's parent. "Digital remittance" refers to transferring money using electronic means. In the present system, a parent can digitally send pocket money to a child through an app. This allows the child to instantly receive the money and save it towards a savings goal. [Brief description of the drawings]

[0012] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 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. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 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. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 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] 4 is a sequence diagram showing a process flow of the data processing system according to the first embodiment. FIG. [Figure 12] 11 is a sequence diagram showing a process flow of the data processing system in application example 1. FIG. [Figure 13] FIG. 11 is a sequence diagram showing the flow of processing of the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 11 is a sequence diagram showing the flow of processing in the data processing system in application example 2 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), etc.

[0016] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0017] 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.

[0018] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0019] 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. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0020] [First embodiment]

[0021] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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 wide area network (WAN) and / or a local area network (LAN).

[0024] 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.

[0025] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] 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 (e.g., voice and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0027] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0028] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Fig. 2, 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. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process 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 process program 56 executed on the RAM 30.

[0030] 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.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output processing 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.

[0032] 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 a "server" and the smart device 14 will be referred to as a "terminal."

[0033] This embodiment includes the following elements: The data processing system 10 is an example of a "system" in this disclosure.

[0034] 1. Database: A database is provided for storing specific information including information about a child, such as the child's age, gender, wish list, current savings amount, goal savings amount, deadline for achieving the goal, and means of earning pocket money.

[0035] 2. Natural Language Processing Model: A natural language processing model is built to generate answers to children's questions.

[0036] 3. User Interface: A user interface is provided for children and parents to input information and receive answers and advice.

[0037] 4. Money transfer function: A money transfer function will be implemented that allows parents to send pocket money digitally to their children.

[0038] 5. Progress Tracking: Features are provided to track a child's progress towards their savings goal and provide advice on how to achieve it.

[0039] <Example>

[0040] For example, a parent can input certain information into the database through the device, and then when a child enters a question about how to spend or save money into the device, the natural language processing model on the server analyzes the question and generates an appropriate answer, which is then displayed to the child through a user interface.

[0041] Parents can also send their children digital pocket money through the app. When a parent sends money, a processor on the server adds the money to the child's current savings amount in the child's database. Children can see their progress toward their savings goal through progress tracking and receive advice on how to reach their goal.

[0042] The above is an example of a form for carrying out the present disclosure. This allows children to manage their pocket money and set savings goals, and allows parents to understand and support their children's savings situation.

[0043] The process flow will be explained below.

[0044] Step 1: Parents enter certain information.

[0045] The parent inputs specific information through the terminal.

[0046] The entered information is transmitted from the terminal to the server.

[0047] Step 2: A database stores the information on the server.

[0048] A processor on the server receives the information submitted by the user and stores it in a database.

[0049] The database stores certain information, including information about the child.

[0050] Step 3: Your child types their question into the device.

[0051] Children use the device to input questions about how to spend and save money.

[0052] Step 4: A natural language processing model on the server analyzes the question and generates an answer.

[0053] A processor on the server receives questions from the child and provides them as input to a natural language processing model.

[0054] A natural language processing model analyzes the posed question and generates an appropriate answer.

[0055] The generated answer is transmitted to the terminal by a processor on the server.

[0056] Step 5: Your answer will be displayed on your device.

[0057] The answer sent from the processor on the server is displayed on the child's device.

[0058] Children can review their answers and enter additional questions if necessary.

[0059] Step 6: Parents send pocket money digitally through the app.

[0060] Parents send their children digital pocket money through the app.

[0061] The money sent is added to the child's current savings in a database by a processor on the server.

[0062] Step 7: Your child can see their progress towards their savings goal through the progress tracker.

[0063] Kids can use the progress tracker to see how they are progressing towards their savings goal.

[0064] It also provides advice on how to achieve your goals.

[0065] The above is the specific flow of the program's processing. Users, including parents and children, input information, the processing is carried out on the server, and answers and advice are displayed on the device, and this flow is repeated.

[0066] As described above, the data processing system 10 is for children to manage their pocket money and set savings goals. Parents input specific information through their terminals. The information includes the child's age, sex, wish list, current savings amount, goal savings amount, deadline for achieving the goal, and means of earning pocket money. Based on this information, a generative AI is launched on the server.

[0067] Children input text to the generative AI, asking for advice on how to spend and increase their savings. The generative AI generates answers in natural language to the child's questions. For example, if a child asks, "How should I spend my pocket money?" the generative AI generates an answer such as, "When using your pocket money, I recommend saving it towards your goal first. Also, think about how to spend small amounts on things you need and for fun."

[0068] Parents can also digitally send their child pocket money through the app, which the child can then save towards a specific goal. For example, if a child wants to buy a new game, the parent can send the child pocket money through the app. The child can save the money and purchase the game by reaching the goal.

[0069] In the data processing system 10, a processor on the server uses the trends of changes in the current savings amount in the database as learning data to fine-tune the generative AI, which enables it to generate more appropriate advice and answers.

[0070] Data Processing System 10 is a useful tool for children to learn about money management and the importance of saving. By saving towards their own goals, children can develop a sense of responsibility and thriftiness. Parents can also keep track of their children's savings and provide appropriate support.

[0071] Example 1

[0072] Next, a description will be given of Example 1. In the following description, the data processing device 12 is referred to as a "server" and the smart device 14 is referred to as a "terminal."

[0073] Conventional children's savings management systems lack the functionality to specifically support how children should save more. It is also difficult for parents to easily transfer pocket money to their children, track their progress to reach their savings goal, and get the advice they need. This leads to issues with children's daily savings management and parents' support being insufficient.

[0074] 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.

[0075] In this invention, the server includes a means for storing specific information including information about the child previously input into the database, a natural language processing model means for analyzing questions from the child and generating answers, a user interface means for a parent or child to input information and receive the generated answers and advice, a remittance function means for digitally sending pocket money from the parent to the child, and a progress tracking function means for tracking the progress of the child's savings goal and providing advice for achieving the goal. This allows the child to efficiently and effectively manage and track the progress toward his or her savings goal, and also allows the parent to easily support the child's savings activity.

[0076] A "database" is a system for storing certain information, including information about children.

[0077] A "natural language processing model" is a machine learning model that analyzes questions from children and generates appropriate answers.

[0078] A "user interface" is a screen or operating means through which a parent or child can input information and receive generated answers and advice.

[0079] The "transfer function" is a feature that allows parents to digitally send pocket money to their children.

[0080] The "progress tracking feature" is a feature that tracks a child's progress toward their savings goal and provides advice on how to achieve that goal.

[0081] "Specific information" includes the child's age, sex, wish list, current savings amount, goal savings amount, deadline for achieving the goal, and means of obtaining the allowance.

[0082] A "submit button" is a button on the user interface that allows a parent or child to confirm input information and send it to a database or server.

[0083] "Progress" is information that indicates how much of the savings goal set by the child has been achieved.

[0084] "Advice" is advice provided about specific actions or methods for achieving savings goals.

[0085] "Payment system" means a system that provides online payment methods used when parents transfer money to their children.

[0086] The "dashboard" is a screen that utilizes a progress tracking function to visually display savings progress and advice.

[0087] This system provides multiple functions to support children's savings management. Specifically, it generates a program that includes a database, a natural language processing model, a user interface, a money transfer function, and a progress tracking function. The detailed process and concrete examples are described below.

[0088] Hardware and Software Used

[0089] 1. Database

[0090] The server uses a relational database to store the child's specific information (age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and method of earning the allowance).

[0091] 2. Natural Language Processing Models

[0092] The server uses a generative AI model (e.g., ChatGPT® by OpenAI®) to generate answers to the child's questions.

[0093] 3. User Interface

[0094] A user (parent or child) inputs information through a user interface built using a front-end framework and receives generated answers and advice.

[0095] 4. Money transfer function

[0096] Parents can send pocket money to their children digitally using an online payment system via their device (smartphone or PC).

[0097] 5. Progress Tracking

[0098] The server uses known libraries or the like to analyze the progress of the child's savings goal in the database and visualizes the data.

[0099] Example of program processing

[0100] example:

[0101] Parents input certain information into the database through a terminal. For example, the child's name is "Taro," his age is 10, his current savings amount is 500 yen, his goal amount is 3,000 yen, and the deadline for achieving the goal is three months from now.

[0102] Then, when the child Taro types a question into the terminal, such as "How can I save more money?", the natural language processing model (ChatGPT) on the server analyzes the question and generates an answer such as "Save your monthly allowance a little at a time and avoid buying unnecessary sweets," which is displayed to Taro through the user interface.

[0103] Furthermore, when Taro's parents transfer 1,000 yen, the server records the information in the database and updates Taro's current savings to 1,500 yen. Taro can use the progress tracking feature to check his progress toward reaching his savings goal and receive advice such as "save your pocket money by refraining from buying snacks to share with your friends."

[0104] Example prompt:

[0105] "Tell me how a 10-year-old can save more money."

[0106] This allows children to effectively manage their pocket money and set savings goals, and parents can also keep track of their children's savings situation and support them.

[0107] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0108] Step 1:

[0109] A user (parent or child) logs into the system via a terminal.

[0110] (Input) The user's email address and password.

[0111] (Data processing) The server checks the authentication information against the database and starts a session if it matches.

[0112] (Output) The user is logged in.

[0113] (Specific operation) A parent or child enters an email address and password on the login screen of the device and clicks the "Login" button. The server checks this against the authentication information in the database and performs the login process.

[0114] Step 2:

[0115] Parents enter their child's specific information into a database via a terminal.

[0116] (Input) Your child's name, age, gender, wish list, current savings amount, goal savings amount, deadline for reaching goal, and method of earning pocket money.

[0117] (Data processing) The server stores this information in a database.

[0118] (Output) The child's specific information is stored in a database.

[0119] (Specific operation) The parent enters the child's specific information into the input form on the terminal and clicks the send button. The server takes that information and stores it in the database.

[0120] Step 3:

[0121] The child enters a question into the system via a terminal.

[0122] (Input) A question from a child (e.g., "How can I increase my savings?").

[0123] (Data processing) The server receives the question and sends it as a prompt to the natural language processing model.

[0124] (Output) The question is sent to the server.

[0125] (Specific operation) The child enters a question on the question input screen of the device and clicks the send button. The server sends the question to the ChatGPT model.

[0126] Step 4:

[0127] The server uses natural language processing models to generate answers to questions.

[0128] (Input) A question from a child.

[0129] (Data Processing) A natural language processing model analyzes the question and generates an appropriate answer.

[0130] (Output) The generated answer.

[0131] (Specific operation) The server sends a question to the ChatGPT model, which analyzes it and generates an answer, which is returned to the server.

[0132] Step 5:

[0133] The server generates answers that are then displayed to the child through a user interface.

[0134] (Input) The generated answer.

[0135] (Data processing) The server receives the response and sends the information to the user interface.

[0136] (Output) The answer is displayed on the child's device.

[0137] (Specific Operation) The server sends the generated answer to the user interface, which displays it on the child's terminal.

[0138] Step 6:

[0139] Parents transfer money to their children through the device.

[0140] (Input) Amount to be sent and recipient information.

[0141] (Data processing) The server processes the remittance using an online payment system.

[0142] (Output) The success or failure status of the transfer.

[0143] (Specific operation) The parent inputs the amount to be transferred on the transfer screen and clicks the transfer button. The server processes the transfer via the payment system.

[0144] Step 7:

[0145] The server updates the remittance information in the database.

[0146] (Input) Remittance status and amount remitted.

[0147] (Data processing) The server updates the child's current savings amount in the database.

[0148] (Output) The updated savings amount.

[0149] (Specific operation) If the transfer is successful, the server adds the transferred amount to the child's current savings and updates the database.

[0150] Step 8:

[0151] Kids can use the progress tracker to see how they are progressing towards their savings goals and get advice.

[0152] (Input) Child's current savings amount and target savings amount.

[0153] (Data processing) The server analyzes the savings progress and generates advice.

[0154] (Output) Progress and advice.

[0155] (Specific operation) A child accesses the progress tracking screen and checks the current savings amount and the target savings amount. The server analyzes the progress data and displays advice.

[0156] (Application example 1)

[0157] 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."

[0158] In the conventional system, there is a lack of a mechanism for children to set savings goals and receive appropriate plans and advice for achieving those goals. In addition, there is insufficient means for parents to transfer pocket money to their children and keep track of how it is being used and the savings situation, which makes it difficult to improve children's financial literacy.

[0159] 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.

[0160] In this invention, the server includes a database means for storing specific information including information about the child, a generating means for generating advice on how to save and increase the child's money using a natural language processing model, a sending means for a parent to digitally send pocket money to the child using the sending function, and a progress tracking means for tracking the progress of the child's savings goal and providing advice for achieving the goal. This allows the child to make a more specific and appropriate savings plan, and the parent can not only digitally send pocket money but also grasp the child's savings situation in real time and support the child.

[0161] A "database means" is a device or system for storing and managing certain information, including information about children.

[0162] A "generator" is a mechanism or function that uses a natural language processing model to generate advice on how to save and grow money for children.

[0163] A "remittance method" is a mechanism or function that allows parents to digitally send pocket money to their children.

[0164] A "progress tracker" is a mechanism or function that tracks a child's progress toward their savings goal and provides advice for reaching that goal.

[0165] "Information about the child" refers to information such as the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and means of earning the allowance.

[0166] A "natural language processing model" is an artificial intelligence technique for understanding human language and generating appropriate responses.

[0167] "Specific information" is detailed information that includes individual data required for the system to manage.

[0168] A "savings goal" refers to the specific amount of savings and the deadline that a child sets to achieve.

[0169] The present invention is a system that provides advice on savings and how to save money by storing specific information, including information about the child, in a database. The system also includes digital remittance functions from parents and progress tracking functions.

[0170] 1. Generating the system program

[0171] Database Means

[0172] The server uses a database means to store information about the child, including the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and means of earning pocket money.

[0173] Natural Language Processing Models

[0174] A natural language processing model is used to analyze questions posed by children and generate appropriate advice. For example, OpenAI's GPT model is used to generate answers to questions.

[0175] Remittance Method

[0176] The remittance method operates through the device used by the parent, and the server receives the remittance data. This function allows parents to send pocket money to their children digitally.

[0177] Progress Tracking

[0178] The server monitors the child's progress toward the savings goal using a progress tracker, analyzes the child's progress toward the savings goal, and generates advice, if necessary, that provides specific steps to achieve the goal.

[0179] 2. Hardware and Software Used

[0180] The implementation of this system uses the following hardware and software:

[0181] Server: A central server to manage the database that stores the children's information and to implement the payment transfer and progress tracking mechanisms.

[0182] Device (smartphone or tablet): The device the parent uses to transfer money.

[0183] Natural Language Processing Model: Natural Language Processing algorithm based on OpenAI's GPT model.

[0184] 3. Specific Examples

[0185] Example of a child asking a question: When a child uses a device to ask, "How can I save money quickly?", the natural language processing model analyzes the question and the server generates an answer such as, "Earn money by helping out or doing part-time work, and try to save your pocket money little by little," which is displayed on the device.

[0186] Examples of prompt statements

[0187] A question from a child: "How do I save money fast?"

[0188] This system not only gives children knowledge about saving, but also encourages them to achieve their goals in a fun way. At the same time, it also makes it easier for parents to support their children's savings goals, making it a system with high educational value.

[0189] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0190] Step 1:

[0191] Information storage by database means

[0192] The server receives as input certain information provided by the parent and the child, including the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and the means of earning the allowance. The server manages the information by storing this data in a database. The output is information about the child accurately stored in the database.

[0193] Step 2:

[0194] Entering and parsing questions

[0195] A child uses the device to input a question. As input, the device sends the child's text-based question (e.g., "How can I save more money quickly?") to the server. The server uses a natural language processing model (e.g., OpenAI's GPT model) to parse this input data. As an output of the analysis, we obtain an internal representation of the natural language processing model that understands the meaning of the child's question.

[0196] Step 3:

[0197] Generating Advice

[0198] Based on the analysis results, the server uses a natural language processing model to generate appropriate advice. Based on the generated prompt, a specific answer example (e.g., "Earn money by helping out or doing a part-time job, and try to save your pocket money little by little") is output. The generated advice is based on the child's input question.

[0199] Step 4:

[0200] Show Advice

[0201] The advice generated by the server is sent to the terminal and displayed on the child's terminal. The terminal provides a display interface so that the user (child) can view the advice. The output of this step is advice in natural language displayed on the terminal.

[0202] Step 5:

[0203] Entering and Processing Remittances

[0204] A parent uses a terminal to input information for transferring pocket money to a child. Input includes the amount to be transferred and information about the recipient (child). The terminal sends this information to a server. The server receives the transfer information and processes it by adding the amount to the child's current savings balance in a database. As an output of this process, the child's updated current savings balance is stored in the database.

[0205] Step 6:

[0206] Monitor progress and provide advice

[0207] The server periodically monitors the child's progress toward his / her savings goal. As input, the current savings amount and the goal amount are obtained from the database. The server analyzes these data and calculates the progress. Based on the progress, it generates additional advice (e.g., "You're 500 yen away from your goal. Keep trying!"). As output, advice reflecting the progress is generated and displayed on the child's device.

[0208] Through this process, children receive specific feedback on effective savings methods and progress, and parents can support their children's savings efforts by digitally transferring pocket money.

[0209] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0210] In addition to the elements described above, the embodiment of the present invention includes the following elements.

[0211] 1. Emotion Engine: An emotion engine is provided to recognize and analyze the child's emotions.

[0212] 2. Sensors: Sensors will be built into the system to recognize the child’s emotions.

[0213] 3. Emotion-based answer generation: The emotion engine analyzes the child's emotions and is adjusted to respond appropriately to the emotions when generating answers.

[0214] 4. User feedback: A function will be implemented to provide appropriate feedback on a child's emotions.

[0215] (Specific examples)

[0216] For example, a child enters a question about how to spend money through the device. The sensor recognizes the child's emotions when asking the question. The emotion engine analyzes the child's emotions and adjusts to respond appropriately to the emotions when generating answers. For example, if the user is feeling anxious or uncertain, the emotion engine generates advice that corresponds to that.

[0217] The generated answer is presented to the child. The system also provides appropriate feedback based on the child's emotions. For example, if the child feels happy or relieved about the answer, the system will provide positive feedback.

[0218] This is an example of a form for implementing the present disclosure. By combining the emotion engine and sensors, it is possible to recognize a child's emotions and provide appropriate answers and feedback.

[0219] The process flow will be explained below.

[0220] Step 1: The child types a question, including an emotion, into the device.

[0221] Children type questions about how to spend money into the device.

[0222] Questions can involve feelings and emotions.

[0223] Step 2: The sensor recognizes the child's emotions.

[0224] The device is equipped with sensors to recognize emotions.

[0225] The sensors detect changes in a child's facial expressions and voice and recognize emotions.

[0226] Step 3: The emotion engine on the server analyzes the emotion and generates an answer.

[0227] The emotion engine on the server analyzes the child's emotions and generates appropriate answers.

[0228] The emotion engine adjusts responses based on emotion to respond appropriately to a child's emotions.

[0229] Step 4: Your answer will be displayed on your device.

[0230] The answer sent by the processor on the server is displayed on the child's device.

[0231] Responses are emotion-adjusted and provide appropriate feedback to the child's emotions.

[0232] Step 5: Your child receives their answers and feedback.

[0233] The child will receive displayed answers and feedback.

[0234] Children may feel joy or relief in their answers or react to the feedback.

[0235] The above is a specific flow of processing in an embodiment that combines an emotion engine. A child inputs a question that includes emotion, the emotion is recognized by the sensor, and the emotion engine on the server analyzes the emotion and generates an answer. The generated answer is displayed on the terminal, and the child receives the answer and feedback. The combination of the emotion engine and the sensor provides a response appropriate to the child's emotion, realizing more effective communication.

[0236] Example 2

[0237] Next, a description will be given of Example 2. In the following description, the data processing device 12 is referred to as a "server" and the smart device 14 is referred to as a "terminal."

[0238] Conventional systems have difficulty in properly recognizing children's emotions and providing advice based on them. This has resulted in poor user experience and difficulty in providing appropriate feedback to children. In particular, there is a lack of emotion-based approaches, and there is a problem in that support for children to understand their own emotions and deal with them appropriately is insufficient.

[0239] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0240] In this invention, the server includes a means for acquiring specific information including information about the child previously inputted into a database, a means for receiving a question inputted by the child through the terminal, a means for collecting emotion data of the child using a sensor built into the terminal, a means for recognizing the emotion of the child using an emotion engine that analyzes the emotion data, a means for using a generative AI model that generates an appropriate answer based on the emotion data, a means for presenting the generated answer on the terminal, and a means for collecting emotion feedback of the child and generating an appropriate response based thereon. This makes it possible to appropriately analyze the emotion of the child in real time and provide advice or feedback based on the emotion.

[0241] A "database" is a system that systematically organizes and stores information so that it can be quickly searched and retrieved as needed.

[0242] "Specific information" refers to information about the child that has been pre-entered into the database, including the child's age, interests, goals, etc.

[0243] A "terminal" is a device that a user directly operates, and includes a PC, tablet, smartphone, etc.

[0244] A "sensor" is an electronic device for collecting user emotional data, including a camera, microphone, temperature sensor, etc.

[0245] "Emotional data" refers to information collected by sensors from a user's facial expressions, tone of voice, and physical movements.

[0246] An "emotion engine" is software or a system for analyzing emotion data to recognize a user's emotional state.

[0247] A "generative AI model" is an artificial intelligence model that generates appropriate answers based on input data, and a specific example would be a generative language model.

[0248] A "prompt" is an instruction given to a generative AI model that serves as the basis for the model to generate an appropriate answer.

[0249] "Feedback" refers to the response or reaction that the system provides to the user, and is generated adaptively based on the user's emotions.

[0250] "Real-time" refers to a time frame in which processing occurs immediately, without delay.

[0251] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0252] This invention relates to a system that recognizes a child's emotions and provides appropriate answers and feedback based on those emotions. The system is composed of sensors, an emotion engine, and a generative AI model as its main components.

[0253] Hardware and Software Used

[0254] 1. Sensors

[0255] The device is equipped with hardware such as a camera, microphone, and temperature sensor. As a specific example, a general-purpose camera and a general-purpose microphone are used.

[0256] 2. Emotion Engine

[0257] The server uses emotion analysis APIs from Microsoft® Azure® and IBM Watson® as its emotion engine, which analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[0258] 3. Generative AI Models

[0259] The server uses OpenAI's ChatGPT (registered trademark) as a generative AI model, which generates appropriate answers based on emotion data and input questions.

[0260] System Overview

[0261] In this system, the user inputs a question via the device, and the device's sensors collect the user's emotional data. The data is sent to the server, where the emotion engine analyzes it. Based on the analysis results, the generative AI model forms a prompt sentence and generates an appropriate answer. Finally, the generated answer is presented to the user via the device.

[0262] Examples

[0263] For example, if a child types "Teach me how to do my homework" into the device, the question is sent to the server along with sensor data collected through the camera and microphone. At the server, the emotion engine analyzes the child's facial expressions and tone of voice to recognize the child's emotional state of confusion. An appropriate answer is then generated by inputting the following prompt sentence into the generative AI model:

[0264] "My child asks, 'Tell me how to do my homework.' He's confused. Generate advice that takes this emotion into account."

[0265] The generated answer, "Don't try to do it all at once, but proceed little by little," is displayed on the device. Furthermore, if the user shows a relieved expression, the feedback data is sent again to the server, and positive feedback, "That's a great way of thinking!", is generated and displayed on the device.

[0266] As described above, this system is able to analyze children's emotions in real time and provide appropriate advice and feedback based on those emotions, thereby supporting children's emotions and providing a better user experience.

[0267] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0268] System processing steps

[0269] Step 1: User enters question

[0270] The user inputs a question via a terminal, either using a keyboard or a touch screen, and the input question is immediately transmitted to the system.

[0271] Input: The user's question text (e.g., "Can you help me with my homework?")

[0272] Output: The question text is sent from the terminal to the server.

[0273] Step 2: The device collects emotion data using sensors

[0274] The device is equipped with a camera, microphone, temperature sensor, etc. to collect user emotion data. The collected data is stored as image data, voice data, and temperature data.

[0275] Input: User's facial expression, tone of voice, body temperature

[0276] Output: Collected emotion data (image data, voice data, temperature data) is sent from the device to the server.

[0277] Specific actions: The camera captures a face and the microphone records a voice.

[0278] Step 3: The server analyzes the emotion data

[0279] The server receives the emotion data sent from the device and analyzes it with the emotion engine. The analysis identifies the user's emotional state (e.g. confusion, anxiety, joy). This analysis is mainly performed using facial expression recognition algorithms and voice analysis algorithms.

[0280] Input: Collected emotion data

[0281] Output: The user's emotional state (e.g. confused)

[0282] How it works: Facial expression recognition algorithms analyze facial features, and voice analysis algorithms analyze the tone of your voice.

[0283] Step 4: The server generates a sentiment-based answer

[0284] The server uses a generative AI model (e.g. ChatGPT by OpenAI) to generate an appropriate answer based on the analyzed emotional state. The prompt contains the user's question and their emotional state.

[0285] Input: User question text, parsed emotional state

[0286] Output: The generated answer text

[0287] Specific operation: Send a prompt to the generative AI model and receive a response

[0288] Example prompt:

[0289] "My child asks, 'Tell me how to do my homework.' He's confused. Generate advice that takes this emotion into account."

[0290] Step 5: The device presents the answer to the user

[0291] The terminal displays the answer sent from the server to the user. The generated answer is displayed in text format on the screen.

[0292] Input: Generated answer text

[0293] Output: The answer text is displayed on the device screen.

[0294] Specific action: The screen displays the message, "Don't try to do it all at once. It's better to proceed little by little."

[0295] Step 6: Collect user emotional feedback

[0296] The sensors again collect the user's reactions after viewing the answer, using cameras and microphones to capture the user's facial expressions and tone of voice.

[0297] Input: User's facial expressions, tone of voice

[0298] Output: Collected feedback data (image data, audio data) is sent from the device to the server.

[0299] Specific operation: The camera captures the face again and the microphone records the voice.

[0300] Step 7: The server parses the feedback and generates an appropriate response

[0301] The server analyzes the feedback data with an emotion engine and generates an appropriate response based on the user's emotional state, which may be further affirmation or additional advice.

[0302] Input: Collected feedback data

[0303] Output: The appropriate response text

[0304] Specific operation: Based on the analysis results, the emotion engine generates feedback such as "That's a great way of thinking!" and sends it to the device. Display on the device

[0305] (Application example 2)

[0306] 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."

[0307] In modern virtual stores, online shopping, especially for children, often involves anxiety and hesitation. Shopping experiences that ignore these emotions can be stressful for children, and may reduce shopping efficiency and satisfaction. In addition, conventional systems do not provide product suggestions or feedback that take into account children's emotional state, making it difficult to provide services that are tailored to individual users.

[0308] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0309] In this invention, the server includes specific information including information about the child previously inputted into a database, a generating means for generating advice about at least one of how to use and how to increase the savings of the child, an emotion recognizing means for recognizing the emotion of the child based on an emotion analyzing means, an information providing means for adjusting the advice according to the emotion based on the emotion recognizing means, a progress tracking means for tracking the progress to reach a target savings amount designated by the child, and a feedback providing means for providing feedback according to the emotion of the child based on the progress. This makes it possible to provide product suggestions and feedback based on the emotion of the child.

[0310] A "database" is an information storage system that stores information about children that has been entered in advance and performs various data processing based on this information.

[0311] "Specific Information" is personal data about a child and details about their behavior, feelings, preferences, etc.

[0312] "Generative" is a feature that uses existing data and algorithms to generate tailored advice and suggestions for children.

[0313] The "emotion analysis means" is a technology that uses an in-camera and microphone to analyze a child's facial expressions and tone of voice in real time to recognize their emotional state.

[0314] The "emotion recognition means" is a mechanism that uses the child's emotional state recognized by the emotion analysis means as is.

[0315] The "information provision means" is a function that adjusts and presents appropriate advice and product suggestions based on the emotion recognition means.

[0316] A "progress tracker" is a feature that tracks and monitors in real time the child's progress toward reaching a savings goal.

[0317] The "feedback providing means" is a function that provides appropriate feedback and product suggestions based on the progress and recognition of the child's emotions.

[0318] A system for implementing the present invention is constructed mainly using the following hardware and software.

[0319] Hardware:

[0320] 1. Front camera: Used to capture children's facial expressions.

[0321] 2. Microphone: Used to analyze the tone of the child's voice.

[0322] software:

[0323] 1. Software A: Software that performs real-time image processing.

[0324] 2. Module A: A face detection module used for face detection.

[0325] 3. Sentiment Engine: A library for performing sentiment analysis.

[0326] Specific behavior:

[0327] The server collects data on the child in real time through the front camera and microphone, and performs emotion analysis based on this data. Specifically, the following steps are taken:

[0328] 1. Data Acquisition:

[0329] The server captures the child's facial expressions using the front camera and obtains the tone of voice using the microphone.

[0330] 2. Emotion recognition:

[0331] The server analyzes the acquired data using an emotion engine and recognizes the child's emotions.

[0332] 3. Information provision:

[0333] Based on the emotions detected, information delivery methods are used to tailor advice and product suggestions.

[0334] For example, if a child is excited, the system will suggest similar popular products, and if the child looks anxious, it will present reassuring messages and other user reviews.

[0335] 4. Progress Tracking and Feedback:

[0336] A progress tracker tracks the child's progress towards reaching a savings goal.

[0337] The feedback mechanism provides appropriate feedback according to progress, for example sending encouraging messages when the user is approaching a goal.

[0338] Examples and prompts:

[0339] For example, if a child looks excited while browsing a virtual store using a head-mounted display, the server will suggest products such as a new stuffed toy or a popular picture book. On the other hand, if the child looks anxious, the server will suggest products that will give the child a sense of security, such as a science kit.

[0340] Example prompt:

[0341] "How can we make appropriate product suggestions based on the emotions a child displays while shopping in a virtual store?"

[0342] As described above, the server can use each means to provide product suggestions and feedback according to the child's emotions, allowing the child to enjoy online shopping with peace of mind.

[0343] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0344] Step 1:

[0345] Data Acquisition

[0346] The server captures the child's facial expressions and tone of voice in real time using the front camera and microphone. The input data is image data and voice data. The server processes the image data using software A and detects facial feature points using module A. At the same time, it sends the captured voice data to the emotion engine.

[0347] Step 2:

[0348] emotion recognition

[0349] The server passes the processed image data to the emotion engine, which recognizes the child's emotions based on facial features. Similarly, the voice data is analyzed by the emotion engine. The analysis results in a series of emotion tags such as "happy," "sad," and "excited" as output.

[0350] Step 3:

[0351] Providing information

[0352] The server runs an algorithm to generate appropriate advice or product suggestions based on the emotion tag. For example, if the emotion tag says "excited," the server might suggest a new stuffed toy or a picture book. The server sends the generated suggestion data to the device and displays it to the child.

[0353] Step 4:

[0354] Progress Tracking

[0355] The server tracks the child's progress toward the savings goal, calculating the progress based on the savings data received from the device, and presenting the progress as a percentage toward the goal to the feedback algorithm.

[0356] Step 5:

[0357] Provide feedback

[0358] The server runs a feedback algorithm based on the progress and emotion tag, for example generating an encouraging message if the progress is good, or a reassuring message if the emotion tag indicates anxiety, and sends this feedback to the device to be shown to the child.

[0359] Step 6:

[0360] Optimizations and improvements

[0361] The server collects user feedback and evaluates the effectiveness of the generated advice and product suggestions. Based on this, it optimizes the emotion recognition algorithm and information provision algorithm to improve the accuracy of suggestions from the next time onwards. Specifically, it fine-tunes the suggestion algorithm based on data on products actually purchased to make effective suggestions.

[0362] By repeating the above processing steps, the system will be able to provide optimal advice and product suggestions based on the child's emotions, allowing them to enjoy shopping with peace of mind.

[0363] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice 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 voice data.

[0364] 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<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 making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[0365] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0366] [Second embodiment]

[0367] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0368] 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.

[0369] 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 wide area network (WAN) and / or a local area network (LAN).

[0370] 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.

[0371] 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 the voice according to instructions from the processor 46.

[0372] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0373] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0374] Fig. 4 shows an example of 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.

[0375] 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.

[0376] 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.

[0377] 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.

[0378] 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 a "server" and the smart glasses 214 will be referred to as a "terminal".

[0379] This embodiment is composed of the following elements.

[0380] 1. Database: A database is provided for storing certain information including information about children.

[0381] 2. Natural Language Processing Model: A natural language processing model is built to generate answers to children's questions.

[0382] 3. User Interface: A user interface is provided for children and parents to input information and receive answers and advice.

[0383] 4. Money transfer function: A money transfer function will be implemented that allows parents to send pocket money digitally to their children.

[0384] 5. Progress Tracking: Features are provided to track a child's progress towards their savings goal and provide advice on how to achieve it.

[0385] (Specific examples)

[0386] For example, a parent can input certain information into the database through the device, and then when a child enters a question about how to spend or save money into the device, the natural language processing model on the server analyzes the question and generates an appropriate answer, which is then displayed to the child through a user interface.

[0387] Parents can also send their children digital pocket money through the app. When a parent sends money, a processor on the server adds the money to the child's current savings amount in the child's database. Children can see their progress toward their savings goal through progress tracking and receive advice on how to reach their goal.

[0388] The above is an example of a form for carrying out the present disclosure. This allows children to manage their pocket money and set savings goals, and allows parents to understand and support their children's savings situation.

[0389] The process flow will be explained below.

[0390] Step 1: Parents enter certain information.

[0391] The parent inputs specific information through the terminal.

[0392] The entered information is transmitted from the terminal to the server.

[0393] Step 2: A database stores the information on the server.

[0394] A processor on the server receives the information submitted by the user and stores it in a database.

[0395] The database stores certain information, including information about the child.

[0396] Step 3: Your child types their question into the device.

[0397] Children use the device to input questions about how to spend and save money.

[0398] Step 4: A natural language processing model on the server analyzes the question and generates an answer.

[0399] A processor on the server receives questions from the child and provides them as input to a natural language processing model.

[0400] A natural language processing model analyzes the posed question and generates an appropriate answer.

[0401] The generated answer is transmitted to the terminal by a processor on the server.

[0402] Step 5: Your answer will be displayed on your device.

[0403] The answer sent from the processor on the server is displayed on the child's device.

[0404] Children can review their answers and enter additional questions if necessary.

[0405] Step 6: Parents send pocket money digitally through the app.

[0406] Parents send their children digital pocket money through the app.

[0407] The money sent is added to the child's current savings in a database by a processor on the server.

[0408] Step 7: Your child can see their progress towards their savings goal through the progress tracker.

[0409] Kids can use the progress tracker to see how they are progressing towards their savings goal.

[0410] It also provides advice on how to achieve your goals.

[0411] The above is the specific flow of the program's processing. Users, including parents and children, input information, the processing is carried out on the server, and answers and advice are displayed on the device, and this flow is repeated.

[0412] Example 1

[0413] Next, a description will be given of Example 1. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0414] Conventional children's savings management systems lack the functionality to specifically support how children should save more. It is also difficult for parents to easily transfer pocket money to their children, track their progress to reach their savings goal, and get the advice they need. This leads to issues with children's daily savings management and parents' support being insufficient.

[0415] 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.

[0416] In this invention, the server includes a means for storing specific information including information about the child previously input into the database, a natural language processing model means for analyzing questions from the child and generating answers, a user interface means for a parent or child to input information and receive the generated answers and advice, a remittance function means for digitally sending pocket money from the parent to the child, and a progress tracking function means for tracking the progress of the child's savings goal and providing advice for achieving the goal. This allows the child to efficiently and effectively manage and track the progress toward his or her savings goal, and also allows the parent to easily support the child's savings activity.

[0417] A "database" is a system for storing certain information, including information about children.

[0418] A "natural language processing model" is a machine learning model that analyzes questions from children and generates appropriate answers.

[0419] A "user interface" is a screen or operating means through which a parent or child can input information and receive generated answers and advice.

[0420] The "transfer function" is a feature that allows parents to digitally send pocket money to their children.

[0421] The "progress tracking feature" is a feature that tracks a child's progress toward their savings goal and provides advice on how to achieve that goal.

[0422] "Specific information" includes the child's age, sex, wish list, current savings amount, goal savings amount, deadline for achieving the goal, and means of obtaining the allowance.

[0423] A "submit button" is a button on the user interface that allows a parent or child to confirm input information and send it to a database or server.

[0424] "Progress" is information that indicates how much of the savings goal set by the child has been achieved.

[0425] "Advice" is advice provided about specific actions or methods for achieving savings goals.

[0426] "Payment system" means a system that provides online payment methods used when parents transfer money to their children.

[0427] The "dashboard" is a screen that utilizes a progress tracking function to visually display savings progress and advice.

[0428] This system provides multiple functions to support children's savings management. Specifically, it generates a program that includes a database, a natural language processing model, a user interface, a money transfer function, and a progress tracking function. The detailed process and concrete examples are described below.

[0429] Hardware and Software Used

[0430] 1. Database

[0431] The server uses a relational database to store the child's specific information (age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and method of earning the allowance).

[0432] 2. Natural Language Processing Models

[0433] The server uses a generative AI model (e.g., OpenAI's ChatGPT) to generate answers to questions posed by the child.

[0434] 3. User Interface

[0435] A user (parent or child) inputs information through a user interface built using a front-end framework and receives generated answers and advice.

[0436] 4. Money transfer function

[0437] Parents can send pocket money to their children digitally using an online payment system via their device (smartphone or PC).

[0438] 5. Progress Tracking

[0439] The server uses known libraries or the like to analyze the progress of the child's savings goal in the database and visualizes the data.

[0440] Example of program processing

[0441] example:

[0442] Parents input certain information into the database through a terminal. For example, the child's name is "Taro," his age is 10, his current savings amount is 500 yen, his goal amount is 3,000 yen, and the deadline for achieving the goal is three months from now.

[0443] Then, when the child Taro types a question into the terminal, such as "How can I save more money?", the natural language processing model (ChatGPT) on the server analyzes the question and generates an answer such as "Save your monthly allowance a little at a time and avoid buying unnecessary sweets," which is displayed to Taro through the user interface.

[0444] Furthermore, when Taro's parents transfer 1,000 yen, the server records the information in the database and updates Taro's current savings to 1,500 yen. Taro can use the progress tracking feature to check his progress toward reaching his savings goal and receive advice such as "save your pocket money by refraining from buying snacks to share with your friends."

[0445] Example prompt:

[0446] "Tell me how a 10-year-old can save more money."

[0447] This allows children to effectively manage their pocket money and set savings goals, and parents can also keep track of their children's savings situation and support them.

[0448] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0449] Step 1:

[0450] A user (parent or child) logs into the system via a terminal.

[0451] (Input) The user's email address and password.

[0452] (Data processing) The server checks the authentication information against the database and starts a session if it matches.

[0453] (Output) The user is logged in.

[0454] (Specific operation) A parent or child enters an email address and password on the login screen of the device and clicks the "Login" button. The server checks this against the authentication information in the database and performs the login process.

[0455] Step 2:

[0456] Parents enter their child's specific information into a database via a terminal.

[0457] (Input) Your child's name, age, gender, wish list, current savings amount, goal savings amount, deadline for reaching goal, and method of earning pocket money.

[0458] (Data processing) The server stores this information in a database.

[0459] (Output) The child's specific information is stored in a database.

[0460] (Specific operation) The parent enters the child's specific information into the input form on the terminal and clicks the send button. The server takes that information and stores it in the database.

[0461] Step 3:

[0462] The child enters a question into the system via a terminal.

[0463] (Input) A question from a child (e.g., "How can I increase my savings?").

[0464] (Data processing) The server receives the question and sends it as a prompt to the natural language processing model.

[0465] (Output) The question is sent to the server.

[0466] (Specific operation) The child enters a question on the question input screen of the device and clicks the send button. The server sends the question to the ChatGPT model.

[0467] Step 4:

[0468] The server uses natural language processing models to generate answers to questions.

[0469] (Input) A question from a child.

[0470] (Data Processing) A natural language processing model analyzes the question and generates an appropriate answer.

[0471] (Output) The generated answer.

[0472] (Specific operation) The server sends a question to the ChatGPT model, which analyzes it and generates an answer, which is returned to the server.

[0473] Step 5:

[0474] The server generates answers that are then displayed to the child through a user interface.

[0475] (Input) The generated answer.

[0476] (Data processing) The server receives the response and sends the information to the user interface.

[0477] (Output) The answer is displayed on the child's device.

[0478] (Specific Operation) The server sends the generated answer to the user interface, which displays it on the child's terminal.

[0479] Step 6:

[0480] Parents transfer money to their children through the device.

[0481] (Input) Amount to be sent and recipient information.

[0482] (Data processing) The server processes the remittance using an online payment system.

[0483] (Output) The success or failure status of the transfer.

[0484] (Specific operation) The parent inputs the amount to be transferred on the transfer screen and clicks the transfer button. The server processes the transfer via the payment system.

[0485] Step 7:

[0486] The server updates the remittance information in the database.

[0487] (Input) Remittance status and amount remitted.

[0488] (Data processing) The server updates the child's current savings amount in the database.

[0489] (Output) The updated savings amount.

[0490] (Specific operation) If the transfer is successful, the server adds the transferred amount to the child's current savings and updates the database.

[0491] Step 8:

[0492] Kids can use the progress tracker to see how they are progressing towards their savings goals and get advice.

[0493] (Input) Child's current savings amount and target savings amount.

[0494] (Data processing) The server analyzes the savings progress and generates advice.

[0495] (Output) Progress and advice.

[0496] (Specific operation) A child accesses the progress tracking screen and checks the current savings amount and the target savings amount. The server analyzes the progress data and displays advice.

[0497] (Application example 1)

[0498] 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".

[0499] In the conventional system, there is a lack of a mechanism for children to set savings goals and receive appropriate plans and advice for achieving those goals. In addition, there is insufficient means for parents to transfer pocket money to their children and keep track of how it is being used and the savings situation, which makes it difficult to improve children's financial literacy.

[0500] 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.

[0501] In this invention, the server includes a database means for storing specific information including information about the child, a generating means for generating advice on how to save and increase the child's money using a natural language processing model, a sending means for a parent to digitally send pocket money to the child using the sending function, and a progress tracking means for tracking the progress of the child's savings goal and providing advice for achieving the goal. This allows the child to make a more specific and appropriate savings plan, and the parent can not only digitally send pocket money but also grasp the child's savings situation in real time and support the child.

[0502] A "database means" is a device or system for storing and managing specific information, including information about children.

[0503] A "generator" is a mechanism or function that uses a natural language processing model to generate advice on how to save and grow money for children.

[0504] A "remittance method" is a mechanism or function that allows parents to digitally send pocket money to their children.

[0505] A "progress tracker" is a mechanism or function that tracks a child's progress toward their savings goal and provides advice for reaching that goal.

[0506] "Information about the child" refers to information such as the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and means of earning the allowance.

[0507] A "natural language processing model" is an artificial intelligence technique for understanding human language and generating appropriate responses.

[0508] "Specific information" is detailed information that includes individual data required for the system to manage.

[0509] A "savings goal" refers to the specific amount of savings and the deadline that a child sets to achieve.

[0510] The present invention is a system that provides advice on savings and how to save money by storing specific information, including information about the child, in a database. The system also includes digital remittance functions from parents and progress tracking functions.

[0511] 1. Generating the system program

[0512] Database Means

[0513] The server uses a database means to store information about the child, including the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and means of earning pocket money.

[0514] Natural Language Processing Models

[0515] A natural language processing model is used to analyze questions posed by children and generate appropriate advice. For example, OpenAI's GPT model is used to generate answers to questions.

[0516] Remittance Method

[0517] The remittance method operates through the device used by the parent, and the server receives the remittance data. This function allows parents to send pocket money to their children digitally.

[0518] Progress Tracking

[0519] The server monitors the child's progress toward the savings goal using a progress tracker, analyzes the child's progress toward the savings goal, and generates advice, if necessary, that provides specific steps to achieve the goal.

[0520] 2. Hardware and Software Used

[0521] The implementation of this system uses the following hardware and software:

[0522] Server: A central server to manage the database that stores the children's information and to implement the payment transfer and progress tracking mechanisms.

[0523] Device (smartphone or tablet): The device the parent uses to transfer money.

[0524] Natural Language Processing Model: Natural Language Processing algorithm based on OpenAI's GPT model.

[0525] 3. Specific Examples

[0526] Example of a child asking a question: When a child uses a device to ask, "How can I save money quickly?", the natural language processing model analyzes the question and the server generates an answer such as, "Earn money by helping out or doing part-time work, and try to save your pocket money little by little," which is displayed on the device.

[0527] Examples of prompt statements

[0528] A question from a child: "How do I save money fast?"

[0529] This system not only gives children knowledge about saving, but also encourages them to achieve their goals in a fun way. At the same time, it also makes it easier for parents to support their children's savings goals, making it a system with high educational value.

[0530] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0531] Step 1:

[0532] Information storage by database means

[0533] The server receives as input certain information provided by the parent and the child, including the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and the means of earning the allowance. The server manages the information by storing this data in a database. The output is information about the child accurately stored in the database.

[0534] Step 2:

[0535] Entering and parsing questions

[0536] A child uses the device to input a question. As input, the device sends the child's text-based question (e.g., "How can I save more money quickly?") to the server. The server uses a natural language processing model (e.g., OpenAI's GPT model) to parse this input data. As an output of the analysis, we obtain an internal representation of the natural language processing model that understands the meaning of the child's question.

[0537] Step 3:

[0538] Generating Advice

[0539] Based on the analysis results, the server uses a natural language processing model to generate appropriate advice. Based on the generated prompt, a specific answer example (e.g., "Earn money by helping out or doing a part-time job, and try to save your pocket money little by little") is output. The generated advice is based on the child's input question.

[0540] Step 4:

[0541] Show Advice

[0542] The advice generated by the server is sent to the terminal and displayed on the child's terminal. The terminal provides a display interface so that the user (child) can view the advice. The output of this step is advice in natural language displayed on the terminal.

[0543] Step 5:

[0544] Entering and Processing Remittances

[0545] A parent uses a terminal to input information for transferring pocket money to a child. Input includes the amount to be transferred and information about the recipient (child). The terminal sends this information to a server. The server receives the transfer information and processes it by adding the amount to the child's current savings balance in a database. As an output of this process, the child's updated current savings balance is stored in the database.

[0546] Step 6:

[0547] Monitor progress and provide advice

[0548] The server periodically monitors the child's progress toward his / her savings goal. As input, the current savings amount and the goal amount are obtained from the database. The server analyzes these data and calculates the progress. Based on the progress, it generates additional advice (e.g., "You're 500 yen away from your goal. Keep trying!"). As output, advice reflecting the progress is generated and displayed on the child's device.

[0549] Through this process, children receive specific feedback on effective savings methods and progress, and parents can support their children's savings efforts by digitally transferring pocket money.

[0550] In addition, 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.

[0551] In addition to the elements described above, the embodiment of the present invention includes the following elements.

[0552] 1. Emotion Engine: An emotion engine is provided to recognize and analyze the child's emotions.

[0553] 2. Sensors: Sensors will be built into the system to recognize the child’s emotions.

[0554] 3. Emotion-based answer generation: The emotion engine analyzes the child's emotions and is adjusted to respond appropriately to the emotions when generating answers.

[0555] 4. User feedback: A function will be implemented to provide appropriate feedback on a child's emotions.

[0556] (Specific examples)

[0557] For example, a child enters a question about how to spend money through the device. The sensor recognizes the child's emotions when asking the question. The emotion engine analyzes the child's emotions and adjusts to respond appropriately to the emotions when generating answers. For example, if the user is feeling anxious or uncertain, the emotion engine generates advice that corresponds to that.

[0558] The generated answer is presented to the child. The system also implements a feature to provide appropriate feedback to the child based on their emotions. For example, if the child feels happy or relieved about the answer, the system will provide positive feedback.

[0559] This is an example of a form for implementing the present disclosure. By combining the emotion engine and sensors, it is possible to recognize a child's emotions and provide appropriate answers and feedback.

[0560] The process flow will be explained below.

[0561] Step 1: The child types a question, including an emotion, into the device.

[0562] Children type questions about how to spend money into the device.

[0563] Questions can involve feelings and emotions.

[0564] Step 2: The sensor recognizes the child's emotions.

[0565] The device is equipped with sensors to recognize emotions.

[0566] The sensors detect changes in a child's facial expressions and voice and recognize emotions.

[0567] Step 3: The emotion engine on the server analyzes the emotion and generates an answer.

[0568] The emotion engine on the server analyzes the child's emotions and generates appropriate answers.

[0569] The emotion engine adjusts responses based on emotion to respond appropriately to a child's emotions.

[0570] Step 4: Your answer will be displayed on your device.

[0571] The answer sent by the processor on the server is displayed on the child's device.

[0572] Responses are emotion-adjusted and provide appropriate feedback to the child's emotions.

[0573] Step 5: Your child receives their answers and feedback.

[0574] The child will receive displayed answers and feedback.

[0575] Children may feel joy or relief in their answers or react to the feedback.

[0576] The above is a specific flow of processing in an embodiment that combines an emotion engine. A child inputs a question that includes emotion, the emotion is recognized by the sensor, and the emotion engine on the server analyzes the emotion and generates an answer. The generated answer is displayed on the terminal, and the child receives the answer and feedback. The combination of the emotion engine and the sensor provides a response appropriate to the child's emotion, realizing more effective communication.

[0577] Example 2

[0578] Next, a description will be given of Example 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0579] Conventional systems have difficulty in properly recognizing children's emotions and providing advice based on them. This has resulted in poor user experience and difficulty in providing appropriate feedback to children. In particular, there is a lack of emotion-based approaches, and there is a problem in that support for children to understand their own emotions and deal with them appropriately is insufficient.

[0580] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0581] In this invention, the server includes a means for acquiring specific information including information about the child previously inputted into a database, a means for receiving a question inputted by the child through the terminal, a means for collecting emotion data of the child using a sensor built into the terminal, a means for recognizing the emotion of the child using an emotion engine that analyzes the emotion data, a means for using a generative AI model that generates an appropriate answer based on the emotion data, a means for presenting the generated answer on the terminal, and a means for collecting emotion feedback of the child and generating an appropriate response based thereon. This makes it possible to appropriately analyze the emotion of the child in real time and provide advice or feedback based on the emotion.

[0582] A "database" is a system that systematically organizes and stores information so that it can be quickly searched and retrieved as needed.

[0583] "Specific information" refers to information about the child that has been pre-entered into the database, including the child's age, interests, goals, etc.

[0584] A "terminal" is a device that a user directly operates, and includes a PC, tablet, smartphone, etc.

[0585] A "sensor" is an electronic device for collecting user emotional data, including a camera, microphone, temperature sensor, etc.

[0586] "Emotional data" refers to information collected by sensors from a user's facial expressions, tone of voice, and physical movements.

[0587] An "emotion engine" is software or a system for analyzing emotion data to recognize a user's emotional state.

[0588] A "generative AI model" is an artificial intelligence model that generates appropriate answers based on input data, and a specific example would be a generative language model.

[0589] A "prompt" is an instruction given to a generative AI model that serves as the basis for the model to generate an appropriate answer.

[0590] "Feedback" refers to the response or reaction that the system provides to the user, and is generated adaptively based on the user's emotions.

[0591] "Real-time" refers to a time frame in which processing occurs immediately, without delay.

[0592] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0593] This invention relates to a system that recognizes a child's emotions and provides appropriate answers and feedback based on those emotions. The main components of this system are a sensor, an emotion engine, and a generative AI model.

[0594] Hardware and Software Used

[0595] 1. Sensors

[0596] The device is equipped with hardware such as a camera, microphone, and temperature sensor. As a specific example, a general-purpose camera and a general-purpose microphone are used.

[0597] 2. Emotion Engine

[0598] The server uses IBM Watson's emotion analysis API as an emotion engine, which analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[0599] 3. Generative AI Models

[0600] The server uses OpenAI's ChatGPT as a generative AI model, which generates appropriate answers based on emotion data and input questions.

[0601] System Overview

[0602] In this system, the user inputs a question via the device, and the device's sensors collect the user's emotional data. The data is sent to the server, where the emotion engine analyzes it. Based on the analysis results, the generative AI model forms a prompt sentence and generates an appropriate answer. Finally, the generated answer is presented to the user via the device.

[0603] Examples

[0604] For example, if a child types "Teach me how to do my homework" into the device, the question is sent to the server along with sensor data collected through the camera and microphone. At the server, the emotion engine analyzes the child's facial expressions and tone of voice to recognize the child's emotional state of confusion. An appropriate answer is then generated by inputting the following prompt sentence into the generative AI model:

[0605] "My child asks, 'Tell me how to do my homework.' He's confused. Generate advice that takes this emotion into account."

[0606] The generated answer, "Don't try to do it all at once, but proceed little by little," is displayed on the device. Furthermore, if the user shows a relieved expression, the feedback data is sent again to the server, and positive feedback, "That's a great way of thinking!", is generated and displayed on the device.

[0607] As described above, this system is able to analyze children's emotions in real time and provide appropriate advice and feedback based on those emotions, thereby supporting children's emotions and providing a better user experience.

[0608] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0609] System processing steps

[0610] Step 1: User enters question

[0611] The user inputs a question via a terminal, either using a keyboard or a touch screen, and the input question is immediately transmitted to the system.

[0612] Input: The user's question text (e.g. "Can you help me with my homework?")

[0613] Output: The question text is sent from the terminal to the server.

[0614] Step 2: The device collects emotion data using sensors

[0615] The device is equipped with a camera, microphone, temperature sensor, etc. to collect user emotion data. The collected data is stored as image data, voice data, and temperature data.

[0616] Input: User's facial expression, tone of voice, body temperature

[0617] Output: Collected emotion data (image data, voice data, temperature data) is sent from the device to the server.

[0618] Specific actions: The camera captures a face and the microphone records a voice.

[0619] Step 3: The server analyzes the emotion data

[0620] The server receives the emotion data sent from the device and analyzes it with the emotion engine. The analysis identifies the user's emotional state (e.g. confusion, anxiety, joy). This analysis is mainly performed using facial expression recognition algorithms and voice analysis algorithms.

[0621] Input: Collected emotion data

[0622] Output: The user's emotional state (e.g. confused)

[0623] How it works: Facial expression recognition algorithms analyze facial features, and voice analysis algorithms analyze the tone of your voice.

[0624] Step 4: The server generates a sentiment-based answer

[0625] The server uses a generative AI model (e.g. ChatGPT by OpenAI) to generate an appropriate answer based on the analyzed emotional state. The prompt contains the user's question and their emotional state.

[0626] Input: User question text, parsed emotional state

[0627] Output: The generated answer text

[0628] Specific operation: Send a prompt to the generative AI model and receive a response

[0629] Example prompt:

[0630] "My child asks, 'Tell me how to do my homework.' He's confused. Generate advice that takes this emotion into account."

[0631] Step 5: The device presents the answer to the user

[0632] The terminal displays the answer sent from the server to the user. The generated answer is displayed in text format on the screen.

[0633] Input: Generated answer text

[0634] Output: The answer text is displayed on the device screen.

[0635] Specific action: The screen displays the message, "Don't try to do it all at once. It's better to proceed little by little."

[0636] Step 6: Collect user emotional feedback

[0637] The sensors again collect the user's reactions after viewing the answer, using cameras and microphones to capture the user's facial expressions and tone of voice.

[0638] Input: User's facial expressions, tone of voice

[0639] Output: Collected feedback data (image data, audio data) is sent from the device to the server.

[0640] Specific operation: The camera captures the face again and the microphone records the voice.

[0641] Step 7: The server parses the feedback and generates an appropriate response

[0642] The server analyzes the feedback data with an emotion engine and generates an appropriate response based on the user's emotional state, which may be further affirmation or additional advice.

[0643] Input: Collected feedback data

[0644] Output: The appropriate response text

[0645] Specific operation: Based on the analysis results, the emotion engine generates feedback such as "That's a great way of thinking!" and sends it to the device. Display on the device

[0646] (Application example 2)

[0647] 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".

[0648] In modern virtual stores, online shopping, especially for children, often involves anxiety and hesitation. Shopping experiences that ignore these emotions can be stressful for children, and may reduce shopping efficiency and satisfaction. In addition, conventional systems do not provide product suggestions or feedback that take into account children's emotional state, making it difficult to provide services that are tailored to individual users.

[0649] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0650] In this invention, the server includes specific information including information about the child previously inputted into a database, a generating means for generating advice about at least one of how to use and how to increase the savings of the child, an emotion recognizing means for recognizing the emotion of the child based on an emotion analyzing means, an information providing means for adjusting the advice according to the emotion based on the emotion recognizing means, a progress tracking means for tracking the progress to reach a target savings amount designated by the child, and a feedback providing means for providing feedback according to the emotion of the child based on the progress. This makes it possible to provide product suggestions and feedback based on the emotion of the child.

[0651] A "database" is an information storage system that stores information about children that has been entered in advance and performs various data processing based on this information.

[0652] "Specific Information" is personal data about a child and details about their behavior, feelings, preferences, etc.

[0653] "Generative" is a feature that uses existing data and algorithms to generate tailored advice and suggestions for children.

[0654] The "emotion analysis means" is a technology that uses an in-camera and microphone to analyze a child's facial expressions and tone of voice in real time to recognize their emotional state.

[0655] The "emotion recognition means" is a mechanism that uses the child's emotional state recognized by the emotion analysis means as is.

[0656] The "information provision means" is a function that adjusts and presents appropriate advice and product suggestions based on the emotion recognition means.

[0657] A "progress tracker" is a feature that tracks and monitors in real time the child's progress toward reaching a savings goal.

[0658] The "feedback providing means" is a function that provides appropriate feedback and product suggestions based on the progress and recognition of the child's emotions.

[0659] A system for implementing the present invention is constructed mainly using the following hardware and software.

[0660] Hardware:

[0661] 1. Front camera: Used to capture children's facial expressions.

[0662] 2. Microphone: Used to analyze the tone of the child's voice.

[0663] software:

[0664] 1. Software A: Software that performs real-time image processing.

[0665] 2. Module A: A face detection module used for face detection.

[0666] 3. Sentiment Engine: A library for performing sentiment analysis.

[0667] Specific behavior:

[0668] The server collects data on the child in real time through the front camera and microphone, and performs emotion analysis based on this data. Specifically, the following steps are taken:

[0669] 1. Data Acquisition:

[0670] The server captures the child's facial expressions using the front camera and obtains the tone of voice using the microphone.

[0671] 2. Emotion recognition:

[0672] The server analyzes the acquired data using an emotion engine and recognizes the child's emotions.

[0673] 3. Information provision:

[0674] Based on the emotions detected, information delivery methods are used to tailor advice and product suggestions.

[0675] For example, if a child is excited, the system will suggest similar popular products, and if the child looks anxious, it will present reassuring messages and other user reviews.

[0676] 4. Progress Tracking and Feedback:

[0677] A progress tracker tracks the child's progress towards reaching a savings goal.

[0678] The feedback mechanism provides appropriate feedback according to progress, for example sending encouraging messages when the user is approaching a goal.

[0679] Examples and prompts:

[0680] For example, if a child looks excited while browsing a virtual store using a head-mounted display, the server will suggest products such as a new stuffed toy or a popular picture book. On the other hand, if the child looks anxious, the server will suggest products that will give the child a sense of security, such as a science kit.

[0681] Example prompt:

[0682] "How can we make appropriate product suggestions based on the emotions a child displays while shopping in a virtual store?"

[0683] As described above, the server can use each means to provide product suggestions and feedback according to the child's emotions, allowing the child to enjoy online shopping with peace of mind.

[0684] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0685] Step 1:

[0686] Data Acquisition

[0687] The server captures the child's facial expressions and tone of voice in real time using the front camera and microphone. The input data is image data and voice data. The server processes the image data using software A and detects facial feature points using module A. At the same time, it sends the captured voice data to the emotion engine.

[0688] Step 2:

[0689] emotion recognition

[0690] The server passes the processed image data to the emotion engine, which recognizes the child's emotions based on facial features. Similarly, the voice data is analyzed by the emotion engine. As a result, a set of emotion tags such as "happy," "sad," and "excited" are obtained as output.

[0691] Step 3:

[0692] Providing information

[0693] The server runs an algorithm to generate appropriate advice or product suggestions based on the emotion tag. For example, if the emotion tag says "excited," the server might suggest a new stuffed toy or a picture book. The server sends the generated suggestion data to the device and displays it to the child.

[0694] Step 4:

[0695] Progress Tracking

[0696] The server tracks the child's progress toward the savings goal, calculating the progress based on the savings data received from the device, and presenting the progress as a percentage toward the goal to the feedback algorithm.

[0697] Step 5:

[0698] Provide feedback

[0699] The server runs a feedback algorithm based on the progress and emotion tag, for example generating an encouraging message if the progress is good, or a reassuring message if the emotion tag indicates anxiety, and sends this feedback to the device to be shown to the child.

[0700] Step 6:

[0701] Optimizations and improvements

[0702] The server collects user feedback and evaluates the effectiveness of the generated advice and product suggestions. Based on this, it optimizes the emotion recognition algorithm and information provision algorithm to improve the accuracy of suggestions from the next time onwards. Specifically, it fine-tunes the suggestion algorithm based on data on products actually purchased to make effective suggestions.

[0703] By repeating the above processing steps, the system will be able to provide optimal advice and product suggestions based on the child's emotions, allowing them to enjoy shopping with peace of mind.

[0704] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the 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.

[0705] 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 making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[0706] 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 smart glasses 214.

[0707] [Third embodiment]

[0708] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0709] 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.

[0710] 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 wide area network (WAN) and / or a local area network (LAN).

[0711] 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.

[0712] 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 the voice according to instructions from the processor 46.

[0713] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0714] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0715] Fig. 6 shows an example of 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.

[0716] 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.

[0717] 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.

[0718] In the headset type terminal 314, 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.

[0719] 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".

[0720] This embodiment is composed of the following elements.

[0721] 1. Database: A database is provided for storing certain information including information about children.

[0722] 2. Natural Language Processing Model: A natural language processing model is built to generate answers to children's questions.

[0723] 3. User Interface: A user interface is provided for children and parents to input information and receive answers and advice.

[0724] 4. Money transfer function: A money transfer function will be implemented that allows parents to send pocket money digitally to their children.

[0725] 5. Progress Tracking: Features are provided to track a child's progress towards their savings goal and provide advice on how to achieve it.

[0726] (Specific examples)

[0727] For example, a parent can input certain information into the database through the device, and then when a child enters a question about how to spend or save money into the device, the natural language processing model on the server analyzes the question and generates an appropriate answer, which is then displayed to the child through a user interface.

[0728] Parents can also send their children digital pocket money through the app. When a parent sends money, a processor on the server adds the money to the child's current savings amount in the child's database. Children can see their progress toward their savings goal through progress tracking and receive advice on how to reach their goal.

[0729] The above is an example of a form for carrying out the present disclosure. This allows children to manage their pocket money and set savings goals, and allows parents to understand and support their children's savings situation.

[0730] The process flow will be explained below.

[0731] Step 1: Parents enter certain information.

[0732] The parent inputs specific information through the terminal.

[0733] The entered information is transmitted from the terminal to the server.

[0734] Step 2: A database stores the information on the server.

[0735] A processor on the server receives the information submitted by the user and stores it in a database.

[0736] The database stores certain information, including information about the child.

[0737] Step 3: Your child types their question into the device.

[0738] Children use the device to input questions about how to spend and save money.

[0739] Step 4: A natural language processing model on the server analyzes the question and generates an answer.

[0740] A processor on the server receives questions from the child and provides them as input to a natural language processing model.

[0741] A natural language processing model analyzes the posed question and generates an appropriate answer.

[0742] The generated answer is transmitted to the terminal by a processor on the server.

[0743] Step 5: Your answer will be displayed on your device.

[0744] The answer sent from the processor on the server is displayed on the child's device.

[0745] Children can review their answers and enter additional questions if necessary.

[0746] Step 6: Parents send pocket money digitally through the app.

[0747] Parents send their children digital pocket money through the app.

[0748] The money sent is added to the child's current savings in a database by a processor on the server.

[0749] Step 7: Your child can see their progress towards their savings goal through the progress tracker.

[0750] Kids can use the progress tracker to see how they are progressing towards their savings goal.

[0751] It also provides advice on how to achieve your goals.

[0752] The above is the specific flow of the program's processing. Users, including parents and children, input information, the processing is carried out on the server, and answers and advice are displayed on the device, and this flow is repeated.

[0753] Example 1

[0754] 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".

[0755] Conventional children's savings management systems lack the functionality to specifically support how children should save more. It is also difficult for parents to easily transfer pocket money to their children, track their progress to reach their savings goal, and get the advice they need. This leads to issues with children's daily savings management and parents' support being insufficient.

[0756] 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.

[0757] In this invention, the server includes a means for storing specific information including information about the child previously input into the database, a natural language processing model means for analyzing questions from the child and generating answers, a user interface means for a parent or child to input information and receive the generated answers and advice, a remittance function means for digitally sending pocket money from the parent to the child, and a progress tracking function means for tracking the progress of the child's savings goal and providing advice for achieving the goal. This allows the child to efficiently and effectively manage and track the progress toward his or her savings goal, and also allows the parent to easily support the child's savings activity.

[0758] A "database" is a system for storing certain information, including information about children.

[0759] A "natural language processing model" is a machine learning model that analyzes questions from children and generates appropriate answers.

[0760] A "user interface" is a screen or operating means through which a parent or child can input information and receive generated answers and advice.

[0761] The "transfer function" is a feature that allows parents to digitally send pocket money to their children.

[0762] The "progress tracking feature" is a feature that tracks a child's progress toward their savings goal and provides advice on how to achieve that goal.

[0763] "Specific information" includes the child's age, sex, wish list, current savings amount, goal savings amount, deadline for achieving the goal, and means of obtaining the allowance.

[0764] A "submit button" is a button on the user interface that allows a parent or child to confirm input information and send it to a database or server.

[0765] "Progress" is information that indicates how much of the savings goal set by the child has been achieved.

[0766] "Advice" is advice provided about specific actions or methods for achieving savings goals.

[0767] "Payment system" means a system that provides online payment methods used when parents transfer money to their children.

[0768] The "dashboard" is a screen that utilizes a progress tracking function to visually display savings progress and advice.

[0769] This system provides multiple functions to support children's savings management. Specifically, it generates a program that includes a database, a natural language processing model, a user interface, a money transfer function, and a progress tracking function. The detailed process and concrete examples are described below.

[0770] Hardware and Software Used

[0771] 1. Database

[0772] The server uses a relational database to store the child's specific information (age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and method of earning the allowance).

[0773] 2. Natural Language Processing Models

[0774] The server uses a generative AI model (e.g., OpenAI's ChatGPT) to generate answers to questions posed by the child.

[0775] 3. User Interface

[0776] A user (parent or child) inputs information through a user interface built using a front-end framework and receives generated answers and advice.

[0777] 4. Money transfer function

[0778] Parents can send pocket money to their children digitally using an online payment system via their device (smartphone or PC).

[0779] 5. Progress Tracking

[0780] The server uses known libraries or the like to analyze the progress of the child's savings goal in the database and visualizes the data.

[0781] Example of program processing

[0782] example:

[0783] Parents input certain information into the database through a terminal. For example, the child's name is "Taro," his age is 10, his current savings amount is 500 yen, his goal amount is 3,000 yen, and the deadline for achieving the goal is three months from now.

[0784] Then, when the child Taro types a question into the terminal, such as "How can I save more money?", the natural language processing model (ChatGPT) on the server analyzes the question and generates an answer such as "Save your monthly allowance a little at a time and avoid buying unnecessary sweets," which is displayed to Taro through the user interface.

[0785] Furthermore, when Taro's parents transfer 1,000 yen, the server records the information in the database and updates Taro's current savings to 1,500 yen. Taro can use the progress tracking feature to check his progress toward reaching his savings goal and receive advice such as "save your pocket money by refraining from buying snacks to share with your friends."

[0786] Example prompt:

[0787] "Tell me how a 10-year-old can save more money."

[0788] This allows children to effectively manage their pocket money and set savings goals, and parents can also keep track of their children's savings situation and support them.

[0789] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0790] Step 1:

[0791] A user (parent or child) logs into the system via a terminal.

[0792] (Input) The user's email address and password.

[0793] (Data processing) The server checks the authentication information against the database and starts a session if it matches.

[0794] (Output) The user is logged in.

[0795] (Specific operation) A parent or child enters an email address and password on the login screen of the device and clicks the "Login" button. The server checks this against the authentication information in the database and performs the login process.

[0796] Step 2:

[0797] Parents enter their child's specific information into a database via a terminal.

[0798] (Input) Your child's name, age, gender, wish list, current savings amount, goal savings amount, deadline for reaching goal, and method of earning pocket money.

[0799] (Data processing) The server stores this information in a database.

[0800] (Output) The child's specific information is stored in a database.

[0801] (Specific operation) The parent enters the child's specific information into the input form on the terminal and clicks the send button. The server takes that information and stores it in the database.

[0802] Step 3:

[0803] The child enters a question into the system via a terminal.

[0804] (Input) A question from a child (e.g., "How can I increase my savings?").

[0805] (Data processing) The server receives the question and sends it as a prompt to the natural language processing model.

[0806] (Output) The question is sent to the server.

[0807] (Specific operation) The child enters a question on the question input screen of the device and clicks the send button. The server sends the question to the ChatGPT model.

[0808] Step 4:

[0809] The server uses natural language processing models to generate answers to questions.

[0810] (Input) A question from a child.

[0811] (Data Processing) A natural language processing model analyzes the question and generates an appropriate answer.

[0812] (Output) The generated answer.

[0813] (Specific operation) The server sends a question to the ChatGPT model, which analyzes it and generates an answer, which is returned to the server.

[0814] Step 5:

[0815] The server generates answers that are then displayed to the child through a user interface.

[0816] (Input) The generated answer.

[0817] (Data processing) The server receives the response and sends the information to the user interface.

[0818] (Output) The answer is displayed on the child's device.

[0819] (Specific Operation) The server sends the generated answer to the user interface, which displays it on the child's terminal.

[0820] Step 6:

[0821] Parents transfer money to their children through the device.

[0822] (Input) Amount to be sent and recipient information.

[0823] (Data processing) The server processes the remittance using an online payment system.

[0824] (Output) The success or failure status of the transfer.

[0825] (Specific operation) The parent inputs the amount to be transferred on the transfer screen and clicks the transfer button. The server processes the transfer via the payment system.

[0826] Step 7:

[0827] The server updates the remittance information in the database.

[0828] (Input) Remittance status and amount remitted.

[0829] (Data processing) The server updates the child's current savings amount in the database.

[0830] (Output) The updated savings amount.

[0831] (Specific operation) If the transfer is successful, the server adds the transferred amount to the child's current savings and updates the database.

[0832] Step 8:

[0833] Kids can use the progress tracker to see how they are progressing towards their savings goals and get advice.

[0834] (Input) Child's current savings amount and target savings amount.

[0835] (Data processing) The server analyzes the savings progress and generates advice.

[0836] (Output) Progress and advice.

[0837] (Specific operation) A child accesses the progress tracking screen and checks the current savings amount and the target savings amount. The server analyzes the progress data and displays advice.

[0838] (Application example 1)

[0839] 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."

[0840] Conventional systems lack mechanisms for children to set savings goals and provide appropriate plans and advice for achieving those goals. In addition, there are insufficient means for parents to transfer pocket money to their children and keep track of how it is being used and the savings situation, which makes it difficult to improve children's financial literacy.

[0841] 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.

[0842] In this invention, the server includes a database means for storing specific information including information about the child, a generating means for generating advice on how to save and increase the child's money using a natural language processing model, a sending means for a parent to digitally send pocket money to the child using the sending function, and a progress tracking means for tracking the progress of the child's savings goal and providing advice for achieving the goal. This allows the child to make a more specific and appropriate savings plan, and the parent can not only digitally send pocket money but also grasp the child's savings situation in real time and support the child.

[0843] A "database means" is a device or system for storing and managing certain information, including information about children.

[0844] A "generator" is a mechanism or function that uses a natural language processing model to generate advice on how to save and grow money for children.

[0845] A "remittance method" is a mechanism or function that allows parents to digitally send pocket money to their children.

[0846] A "progress tracker" is a mechanism or function that tracks a child's progress toward their savings goal and provides advice for reaching that goal.

[0847] "Information about the child" refers to information such as the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and means of earning the allowance.

[0848] A "natural language processing model" is an artificial intelligence technique for understanding human language and generating appropriate responses.

[0849] "Specific information" is detailed information that includes individual data required for the system to manage.

[0850] A "savings goal" refers to the specific amount of savings and the deadline that a child aims to achieve.

[0851] The present invention is a system that provides advice on savings and how to save money by storing specific information, including information about the child, in a database. The system also includes digital remittance functions from parents and progress tracking functions.

[0852] 1. Generating the system program

[0853] Database Means

[0854] The server uses a database means to store information about the child, including the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and means of earning pocket money.

[0855] Natural Language Processing Models

[0856] A natural language processing model is used to analyze questions posed by children and generate appropriate advice. For example, OpenAI's GPT model is used to generate answers to questions.

[0857] Remittance Method

[0858] The remittance method operates through the device used by the parent, and the server receives the remittance data. This function allows parents to send pocket money to their children digitally.

[0859] Progress Tracking

[0860] The server monitors the child's progress toward the savings goal using a progress tracker, analyzes the child's progress toward the savings goal, and generates advice, if necessary, that provides specific steps to achieve the goal.

[0861] 2. Hardware and Software Used

[0862] The implementation of this system uses the following hardware and software:

[0863] Server: A central server to manage the database that stores the children's information and to implement the payment transfer and progress tracking mechanisms.

[0864] Device (smartphone or tablet): The device the parent uses to transfer money.

[0865] Natural Language Processing Model: Natural Language Processing algorithm based on OpenAI's GPT model.

[0866] 3. Specific Examples

[0867] Example of a child asking a question: When a child uses a device to ask, "How can I save money quickly?", the natural language processing model analyzes the question and the server generates an answer such as, "Earn money by helping out or doing part-time work, and try to save your pocket money little by little," which is displayed on the device.

[0868] Examples of prompt statements

[0869] A question from a child: "How do I save money fast?"

[0870] This system not only gives children knowledge about saving, but also encourages them to achieve their goals in a fun way. At the same time, it also makes it easier for parents to support their children's savings goals, making it a system with high educational value.

[0871] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0872] Step 1:

[0873] Information storage by database means

[0874] The server receives as input certain information provided by the parent and the child, including the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and the means of earning the allowance. The server manages the information by storing this data in a database. The output is information about the child accurately stored in the database.

[0875] Step 2:

[0876] Entering and parsing questions

[0877] A child uses the device to input a question. As input, the device sends the child's text-based question (e.g., "How can I save more money quickly?") to the server. The server uses a natural language processing model (e.g., OpenAI's GPT model) to parse this input data. As an output of the analysis, we obtain an internal representation of the natural language processing model that understands the meaning of the child's question.

[0878] Step 3:

[0879] Generating Advice

[0880] Based on the analysis results, the server uses a natural language processing model to generate appropriate advice. Based on the generated prompt, a specific answer example (e.g., "Earn money by helping out or doing a part-time job, and try to save your pocket money little by little") is output. The generated advice is based on the child's input question.

[0881] Step 4:

[0882] Show Advice

[0883] The advice generated by the server is sent to the terminal and displayed on the child's terminal. The terminal provides a display interface so that the user (child) can view the advice. The output of this step is advice in natural language displayed on the terminal.

[0884] Step 5:

[0885] Entering and Processing Remittances

[0886] A parent uses a terminal to input information for transferring pocket money to a child. Input includes the amount to be transferred and information about the recipient (child). The terminal sends this information to a server. The server receives the transfer information and processes it by adding the amount to the child's current savings balance in a database. As an output of this process, the child's updated current savings balance is stored in the database.

[0887] Step 6:

[0888] Monitor progress and provide advice

[0889] The server periodically monitors the child's progress toward his / her savings goal. As input, the current savings amount and the goal amount are obtained from the database. The server analyzes these data and calculates the progress. Based on the progress, it generates additional advice (e.g., "You're 500 yen away from your goal. Keep trying!"). As output, advice reflecting the progress is generated and displayed on the child's device.

[0890] Through this process, children receive specific feedback on effective savings methods and progress, and parents can support their children's savings efforts by digitally transferring pocket money.

[0891] In addition, 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.

[0892] In addition to the elements described above, the embodiment of the present invention includes the following elements.

[0893] 1. Emotion Engine: An emotion engine is provided to recognize and analyze the child's emotions.

[0894] 2. Sensors: Sensors will be built into the system to recognize the child’s emotions.

[0895] 3. Emotion-based answer generation: The emotion engine analyzes the child's emotions and is adjusted to respond appropriately to the emotions when generating answers.

[0896] 4. User feedback: A function will be implemented to provide appropriate feedback on a child's emotions.

[0897] (Specific examples)

[0898] For example, a child enters a question about how to spend money through the device. The sensor recognizes the child's emotions when asking the question. The emotion engine analyzes the child's emotions and adjusts to respond appropriately to the emotions when generating answers. For example, if the user is feeling anxious or uncertain, the emotion engine generates advice that corresponds to that.

[0899] The generated answer is presented to the child. The system also provides appropriate feedback based on the child's emotions. For example, if the child feels happy or relieved about the answer, the system will provide positive feedback.

[0900] This is an example of a form for implementing the present disclosure. By combining the emotion engine and sensors, it is possible to recognize a child's emotions and provide appropriate answers and feedback.

[0901] The process flow will be explained below.

[0902] Step 1: The child types a question, including an emotion, into the device.

[0903] Children type questions about how to spend money into the device.

[0904] Questions can involve feelings and emotions.

[0905] Step 2: The sensor recognizes the child's emotions.

[0906] The device is equipped with sensors to recognize emotions.

[0907] The sensors detect changes in a child's facial expressions and voice and recognize emotions.

[0908] Step 3: The emotion engine on the server analyzes the emotion and generates an answer.

[0909] The emotion engine on the server analyzes the child's emotions and generates appropriate answers.

[0910] The emotion engine adjusts responses based on emotion to respond appropriately to a child's emotions.

[0911] Step 4: Your answer will be displayed on your device.

[0912] The answer sent by the processor on the server is displayed on the child's device.

[0913] Responses are emotion-adjusted and provide appropriate feedback to the child's emotions.

[0914] Step 5: Your child receives their answers and feedback.

[0915] The child will receive displayed answers and feedback.

[0916] Children may feel joy or relief in their answers or react to the feedback.

[0917] The above is a specific flow of processing in an embodiment that combines an emotion engine. A child inputs a question that includes emotion, the emotion is recognized by the sensor, and the emotion engine on the server analyzes the emotion and generates an answer. The generated answer is displayed on the terminal, and the child receives the answer and feedback. The combination of the emotion engine and the sensor provides a response appropriate to the child's emotion, realizing more effective communication.

[0918] Example 2

[0919] 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".

[0920] Conventional systems have difficulty in properly recognizing children's emotions and providing advice based on them. This has resulted in poor user experience and difficulty in providing appropriate feedback to children. In particular, there is a lack of emotion-based approaches, and there is a problem in that support for children to understand their own emotions and deal with them appropriately is insufficient.

[0921] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0922] In this invention, the server includes a means for acquiring specific information including information about the child previously inputted into a database, a means for receiving a question inputted by the child through the terminal, a means for collecting emotion data of the child using a sensor built into the terminal, a means for recognizing the emotion of the child using an emotion engine that analyzes the emotion data, a means for using a generative AI model that generates an appropriate answer based on the emotion data, a means for presenting the generated answer on the terminal, and a means for collecting emotion feedback of the child and generating an appropriate response based thereon. This makes it possible to appropriately analyze the emotion of the child in real time and provide advice or feedback based on the emotion.

[0923] A "database" is a system that systematically organizes and stores information so that it can be quickly searched and retrieved as needed.

[0924] "Specific information" refers to information about the child that has been pre-entered into the database, including the child's age, interests, goals, etc.

[0925] A "terminal" is a device that a user directly operates, and includes a PC, tablet, smartphone, etc.

[0926] A "sensor" is an electronic device for collecting user emotional data, including a camera, microphone, temperature sensor, etc.

[0927] "Emotional data" refers to information collected by sensors from a user's facial expressions, tone of voice, and physical movements.

[0928] An "emotion engine" is software or a system for analyzing emotion data to recognize a user's emotional state.

[0929] A "generative AI model" is an artificial intelligence model that generates appropriate answers based on input data, and a specific example would be a generative language model.

[0930] A "prompt" is an instruction given to a generative AI model that serves as the basis for the model to generate an appropriate answer.

[0931] "Feedback" refers to the response or reaction that the system provides to the user, and is generated adaptively based on the user's emotions.

[0932] "Real-time" refers to a time frame in which processing occurs immediately, without delay.

[0933] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0934] This invention relates to a system that recognizes a child's emotions and provides appropriate answers and feedback based on those emotions. The main components of this system are a sensor, an emotion engine, and a generative AI model.

[0935] Hardware and Software Used

[0936] 1. Sensors

[0937] The device is equipped with hardware such as a camera, microphone, and temperature sensor. As a specific example, a general-purpose camera and a general-purpose microphone are used.

[0938] 2. Emotion Engine

[0939] The server uses IBM Watson's emotion analysis API as an emotion engine, which analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[0940] 3. Generative AI Models

[0941] The server uses OpenAI's ChatGPT as a generative AI model, which generates appropriate answers based on emotion data and input questions.

[0942] System Overview

[0943] In this system, the user inputs a question via the device, and the device's sensors collect the user's emotional data. The data is sent to the server, where the emotion engine analyzes it. Based on the analysis results, the generative AI model forms a prompt sentence and generates an appropriate answer. Finally, the generated answer is presented to the user via the device.

[0944] Examples

[0945] For example, if a child types "Teach me how to do my homework" into the device, the question is sent to the server along with sensor data collected through the camera and microphone. At the server, the emotion engine analyzes the child's facial expressions and tone of voice to recognize the child's emotional state of confusion. An appropriate answer is then generated by inputting the following prompt sentence into the generative AI model:

[0946] "A child asks, 'Tell me how to do my homework.' He's confused. Generate advice that takes this emotion into account."

[0947] The generated answer, "Don't try to do it all at once, but proceed little by little," is displayed on the device. Furthermore, if the user shows a relieved expression, the feedback data is sent again to the server, and positive feedback, "That's a great way of thinking!", is generated and displayed on the device.

[0948] As described above, this system is able to analyze children's emotions in real time and provide appropriate advice and feedback based on those emotions, thereby supporting children's emotions and providing a better user experience.

[0949] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0950] System processing steps

[0951] Step 1: User enters question

[0952] The user inputs a question via a terminal, either using a keyboard or a touch screen, and the input question is immediately transmitted to the system.

[0953] Input: The user's question text (e.g., "Can you help me with my homework?")

[0954] Output: The question text is sent from the terminal to the server.

[0955] Step 2: The device collects emotion data using sensors

[0956] The device is equipped with a camera, microphone, temperature sensor, etc. to collect user emotion data. The collected data is stored as image data, voice data, and temperature data.

[0957] Input: User's facial expression, tone of voice, body temperature

[0958] Output: Collected emotion data (image data, voice data, temperature data) is sent from the device to the server.

[0959] Specific actions: The camera captures a face and the microphone records a voice.

[0960] Step 3: The server analyzes the emotion data

[0961] The server receives the emotion data sent from the device and analyzes it with the emotion engine. The analysis identifies the user's emotional state (e.g. confusion, anxiety, joy). This analysis is mainly performed using facial expression recognition algorithms and voice analysis algorithms.

[0962] Input: Collected emotion data

[0963] Output: The user's emotional state (e.g. confused)

[0964] How it works: Facial expression recognition algorithms analyze facial features, and voice analysis algorithms analyze the tone of your voice.

[0965] Step 4: The server generates a sentiment-based answer

[0966] The server uses a generative AI model (e.g. ChatGPT by OpenAI) to generate an appropriate answer based on the analyzed emotional state. The prompt contains the user's question and their emotional state.

[0967] Input: User question text, parsed emotional state

[0968] Output: The generated answer text

[0969] Specific operation: Send a prompt to the generative AI model and receive a response

[0970] Example prompt:

[0971] "My child asks, 'Tell me how to do my homework.' He's confused. Generate advice that takes this emotion into account."

[0972] Step 5: The device presents the answer to the user

[0973] The terminal displays the answer sent from the server to the user. The generated answer is displayed in text format on the screen.

[0974] Input: Generated answer text

[0975] Output: The answer text is displayed on the device screen.

[0976] Specific action: The screen displays the message, "Don't try to do it all at once. It's better to proceed little by little."

[0977] Step 6: Collect user emotional feedback

[0978] The sensors again collect the user's reactions after viewing the answer, using cameras and microphones to capture the user's facial expressions and tone of voice.

[0979] Input: User's facial expressions, tone of voice

[0980] Output: Collected feedback data (image data, audio data) is sent from the device to the server.

[0981] Specific operation: The camera captures the face again and the microphone records the voice.

[0982] Step 7: The server parses the feedback and generates an appropriate response

[0983] The server analyzes the feedback data with an emotion engine and generates an appropriate response based on the user's emotional state, which may be further affirmation or additional advice.

[0984] Input: Collected feedback data

[0985] Output: The appropriate response text

[0986] Specific operation: Based on the analysis results, the emotion engine generates feedback such as "That's a great way of thinking!" and sends it to the device. Display on the device

[0987] (Application example 2)

[0988] 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".

[0989] In modern virtual stores, online shopping, especially for children, often involves anxiety and hesitation. Shopping experiences that ignore these emotions can be stressful for children, and may reduce shopping efficiency and satisfaction. In addition, conventional systems do not provide product suggestions or feedback that take into account children's emotional state, making it difficult to provide services that are tailored to individual users.

[0990] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0991] In this invention, the server includes specific information including information about the child previously inputted into a database, a generating means for generating advice about at least one of how to use and how to increase the savings of the child, an emotion recognizing means for recognizing the emotion of the child based on an emotion analyzing means, an information providing means for adjusting the advice according to the emotion based on the emotion recognizing means, a progress tracking means for tracking the progress to reach a target savings amount designated by the child, and a feedback providing means for providing feedback according to the emotion of the child based on the progress. This makes it possible to provide product suggestions and feedback based on the emotion of the child.

[0992] A "database" is an information storage system that stores information about children that has been entered in advance and performs various data processing based on this information.

[0993] "Specific Information" is personal data about a child and details about their behavior, feelings, preferences, etc.

[0994] "Generative" is a feature that uses existing data and algorithms to generate tailored advice and suggestions for children.

[0995] The "emotion analysis means" is a technology that uses an in-camera and microphone to analyze a child's facial expressions and tone of voice in real time to recognize their emotional state.

[0996] The "emotion recognition means" is a mechanism that uses the child's emotional state recognized by the emotion analysis means as is.

[0997] The "information provision means" is a function that adjusts and presents appropriate advice and product suggestions based on the emotion recognition means.

[0998] A "progress tracker" is a feature that tracks and monitors in real time the child's progress toward reaching a savings goal.

[0999] The "feedback providing means" is a function that provides appropriate feedback and product suggestions based on the progress and recognition of the child's emotions.

[1000] A system for implementing the present invention is constructed mainly using the following hardware and software.

[1001] Hardware:

[1002] 1. Front camera: Used to capture children's facial expressions.

[1003] 2. Microphone: Used to analyze the tone of the child's voice.

[1004] software:

[1005] 1. Software A: Software that performs real-time image processing.

[1006] 2. Module A: A face detection module used for face detection.

[1007] 3. Sentiment Engine: A library for performing sentiment analysis.

[1008] Specific behavior:

[1009] The server collects data on the child in real time through the front camera and microphone, and performs emotion analysis based on this data. Specifically, the following steps are taken:

[1010] 1. Data Acquisition:

[1011] The server captures the child's facial expressions using the front camera and obtains the tone of voice using the microphone.

[1012] 2. Emotion recognition:

[1013] The server analyzes the acquired data using an emotion engine and recognizes the child's emotions.

[1014] 3. Information provision:

[1015] Based on the emotions detected, information delivery methods are used to tailor advice and product suggestions.

[1016] For example, if a child is excited, the system will suggest similar popular products, and if the child looks anxious, it will present reassuring messages and other user reviews.

[1017] 4. Progress Tracking and Feedback:

[1018] A progress tracker tracks the child's progress towards reaching a savings goal.

[1019] The feedback mechanism provides appropriate feedback according to progress, for example sending encouraging messages when the user is approaching a goal.

[1020] Examples and prompts:

[1021] For example, if a child looks excited while browsing a virtual store using a head-mounted display, the server will suggest products such as a new stuffed toy or a popular picture book. On the other hand, if the child looks anxious, the server will suggest products that will give the child a sense of security, such as a science kit.

[1022] Example prompt:

[1023] "How can we make appropriate product suggestions based on the emotions a child displays while shopping in a virtual store?"

[1024] As described above, the server can use each means to provide product suggestions and feedback according to the child's emotions, allowing the child to enjoy online shopping with peace of mind.

[1025] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1026] Step 1:

[1027] Data Acquisition

[1028] The server captures the child's facial expressions and tone of voice in real time using the front camera and microphone. The input data is image data and voice data. The server processes the image data using software A and detects facial feature points using module A. At the same time, it sends the captured voice data to the emotion engine.

[1029] Step 2:

[1030] emotion recognition

[1031] The server passes the processed image data to the emotion engine, which recognizes the child's emotions based on facial features. Similarly, the voice data is analyzed by the emotion engine. As a result, a set of emotion tags such as "happy," "sad," and "excited" are obtained as output.

[1032] Step 3:

[1033] Providing information

[1034] The server runs an algorithm to generate appropriate advice or product suggestions based on the emotion tag. For example, if the emotion tag says "excited," the server might suggest a new stuffed toy or a picture book. The server sends the generated suggestion data to the device and displays it to the child.

[1035] Step 4:

[1036] Progress Tracking

[1037] The server tracks the child's progress toward the savings goal, calculating the progress based on the savings data received from the device, and presenting the progress as a percentage toward the goal to the feedback algorithm.

[1038] Step 5:

[1039] Provide feedback

[1040] The server runs a feedback algorithm based on the progress and emotion tag, for example generating an encouraging message if the progress is good, or a reassuring message if the emotion tag indicates anxiety, and sends this feedback to the device to be shown to the child.

[1041] Step 6:

[1042] Optimizations and improvements

[1043] The server collects user feedback and evaluates the effectiveness of the generated advice and product suggestions. Based on this, it optimizes the emotion recognition algorithm and information provision algorithm to improve the accuracy of suggestions from the next time onwards. Specifically, it fine-tunes the suggestion algorithm based on data on products actually purchased to make effective suggestions.

[1044] By repeating the above processing steps, the system will be able to provide optimal advice and product suggestions based on the child's emotions, allowing them to enjoy shopping with peace of mind.

[1045] 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 voice indicating a user input for 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.

[1046] 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 making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[1047] 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.

[1048] [Fourth embodiment]

[1049] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1050] 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.

[1051] 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 wide area network (WAN) and / or a local area network (LAN).

[1052] 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. In addition, the microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1053] 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 the voice according to instructions from the processor 46.

[1054] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a 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 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1055] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1056] The control target 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, legs, etc. The posture and behavior of the robot 414 are controlled by controlling the motors of the arms, hands, legs, etc. 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.

[1057] Fig. 8 shows an example of 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.

[1058] 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.

[1059] 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.

[1060] In the robot 414, 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.

[1061] Next, a description will be given of the specific processing 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".

[1062] This embodiment is composed of the following elements.

[1063] 1. Database: A database is provided for storing certain information including information about children.

[1064] 2. Natural Language Processing Model: A natural language processing model is built to generate answers to children's questions.

[1065] 3. User Interface: A user interface is provided for children and parents to input information and receive answers and advice.

[1066] 4. Money transfer function: A money transfer function will be implemented that allows parents to send pocket money digitally to their children.

[1067] 5. Progress Tracking: Features are provided to track a child's progress towards their savings goal and provide advice on how to achieve it.

[1068] (Specific examples)

[1069] For example, a parent can input certain information into the database through the device, and then when a child enters a question about how to spend or save money into the device, the natural language processing model on the server analyzes the question and generates an appropriate answer, which is then displayed to the child through a user interface.

[1070] Parents can also send their children digital pocket money through the app. When a parent sends money, a processor on the server adds the money to the child's current savings amount in the child's database. Children can see their progress toward their savings goal through progress tracking and receive advice on how to reach their goal.

[1071] The above is an example of a form for carrying out the present disclosure. This allows children to manage their pocket money and set savings goals, and allows parents to understand and support their children's savings situation.

[1072] The process flow will be explained below.

[1073] Step 1: Parents enter certain information.

[1074] The parent inputs specific information through the terminal.

[1075] The entered information is transmitted from the terminal to the server.

[1076] Step 2: A database stores the information on the server.

[1077] A processor on the server receives the information submitted by the user and stores it in a database.

[1078] The database stores certain information, including information about the child.

[1079] Step 3: Your child types their question into the device.

[1080] Children use the device to input questions about how to spend and save money.

[1081] Step 4: A natural language processing model on the server analyzes the question and generates an answer.

[1082] A processor on the server receives questions from the child and provides them as input to a natural language processing model.

[1083] A natural language processing model analyzes the posed question and generates an appropriate answer.

[1084] The generated answer is transmitted to the terminal by a processor on the server.

[1085] Step 5: Your answer will be displayed on your device.

[1086] The answer sent from the processor on the server is displayed on the child's device.

[1087] Children can review their answers and enter additional questions if necessary.

[1088] Step 6: Parents send pocket money digitally through the app.

[1089] Parents send their children digital pocket money through the app.

[1090] The money sent is added to the child's current savings in a database by a processor on the server.

[1091] Step 7: Your child can see their progress towards their savings goal through the progress tracker.

[1092] Kids can use the progress tracker to see how they are progressing towards their savings goal.

[1093] It also provides advice on how to achieve your goals.

[1094] The above is the specific flow of the program's processing. Users, including parents and children, input information, the processing is carried out on the server, and answers and advice are displayed on the device, and this flow is repeated.

[1095] Example 1

[1096] Next, a description will be given of Example 1. In the following description, the data processing device 12 is referred to as a "server" and the robot 414 is referred to as a "terminal."

[1097] Conventional children's savings management systems lack the functionality to specifically support how children should save more. It is also difficult for parents to easily transfer pocket money to their children, track their progress to reach their savings goal, and get the advice they need. This leads to issues with children's daily savings management and parents' support being insufficient.

[1098] 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.

[1099] In this invention, the server includes a means for storing specific information including information about the child previously input into the database, a natural language processing model means for analyzing questions from the child and generating answers, a user interface means for a parent or child to input information and receive the generated answers and advice, a remittance function means for digitally sending pocket money from the parent to the child, and a progress tracking function means for tracking the progress of the child's savings goal and providing advice for achieving the goal. This allows the child to efficiently and effectively manage and track the progress toward his or her savings goal, and also allows the parent to easily support the child's savings activity.

[1100] A "database" is a system for storing certain information, including information about children.

[1101] A "natural language processing model" is a machine learning model that analyzes questions from children and generates appropriate answers.

[1102] A "user interface" is a screen or operating means through which a parent or child can input information and receive generated answers and advice.

[1103] The "transfer function" is a feature that allows parents to digitally send pocket money to their children.

[1104] The "progress tracking feature" is a feature that tracks a child's progress toward their savings goal and provides advice on how to achieve that goal.

[1105] "Specific information" includes the child's age, sex, wish list, current savings amount, goal savings amount, deadline for achieving the goal, and means of obtaining the allowance.

[1106] A "submit button" is a button on the user interface that allows a parent or child to confirm input information and send it to a database or server.

[1107] "Progress" is information that indicates how much of the savings goal set by the child has been achieved.

[1108] "Advice" is advice provided about specific actions or methods for achieving savings goals.

[1109] "Payment system" means a system that provides online payment methods used when parents transfer money to their children.

[1110] The "dashboard" is a screen that utilizes a progress tracking function to visually display savings progress and advice.

[1111] This system provides multiple functions to support children's savings management. Specifically, it generates a program that includes a database, a natural language processing model, a user interface, a money transfer function, and a progress tracking function. The detailed process and concrete examples are described below.

[1112] Hardware and Software Used

[1113] 1. Database

[1114] The server uses a relational database to store the child's specific information (age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and method of earning the allowance).

[1115] 2. Natural Language Processing Models

[1116] The server uses a generative AI model (e.g., OpenAI's ChatGPT) to generate answers to questions posed by the child.

[1117] 3. User Interface

[1118] A user (parent or child) inputs information through a user interface built using a front-end framework and receives generated answers and advice.

[1119] 4. Money transfer function

[1120] Parents can send pocket money to their children digitally using an online payment system via their device (smartphone or PC).

[1121] 5. Progress Tracking

[1122] The server uses known libraries or the like to analyze the progress of the child's savings goal in the database and visualizes the data.

[1123] Example of program processing

[1124] example:

[1125] Parents input certain information into the database through a terminal. For example, the child's name is "Taro," his age is 10, his current savings amount is 500 yen, his goal amount is 3,000 yen, and the deadline for achieving the goal is three months from now.

[1126] Then, when the child Taro types a question into the terminal, such as "How can I save more money?", the natural language processing model (ChatGPT) on the server analyzes the question and generates an answer such as "Save your monthly allowance a little at a time and avoid buying unnecessary sweets," which is displayed to Taro through the user interface.

[1127] Furthermore, when Taro's parents transfer 1,000 yen, the server records the information in the database and updates Taro's current savings to 1,500 yen. Taro can use the progress tracking feature to check his progress toward reaching his savings goal and receive advice such as "save your pocket money by refraining from buying snacks to share with your friends."

[1128] Example prompt:

[1129] "Tell me how a 10-year-old can save more money."

[1130] This allows children to effectively manage their pocket money and set savings goals, and parents can also keep track of their children's savings situation and support them.

[1131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1132] Step 1:

[1133] A user (parent or child) logs into the system via a terminal.

[1134] (Input) The user's email address and password.

[1135] (Data processing) The server checks the authentication information against the database and starts a session if it matches.

[1136] (Output) The user is logged in.

[1137] (Specific operation) A parent or child enters an email address and password on the login screen of the device and clicks the "Login" button. The server checks this against the authentication information in the database and performs the login process.

[1138] Step 2:

[1139] Parents enter their child's specific information into a database via a terminal.

[1140] (Input) Your child's name, age, gender, wish list, current savings amount, goal savings amount, deadline for reaching goal, and method of earning pocket money.

[1141] (Data processing) The server stores this information in a database.

[1142] (Output) The child's specific information is stored in a database.

[1143] (Specific operation) The parent enters the child's specific information into the input form on the terminal and clicks the send button. The server takes that information and stores it in the database.

[1144] Step 3:

[1145] The child enters a question into the system via a terminal.

[1146] (Input) A question from a child (e.g., "How can I increase my savings?").

[1147] (Data processing) The server receives the question and sends it as a prompt to the natural language processing model.

[1148] (Output) The question is sent to the server.

[1149] (Specific operation) The child enters a question on the question input screen of the device and clicks the send button. The server sends the question to the ChatGPT model.

[1150] Step 4:

[1151] The server uses natural language processing models to generate answers to questions.

[1152] (Input) A question from a child.

[1153] (Data Processing) A natural language processing model analyzes the question and generates an appropriate answer.

[1154] (Output) The generated answer.

[1155] (Specific operation) The server sends a question to the ChatGPT model, which analyzes it and generates an answer, which is returned to the server.

[1156] Step 5:

[1157] The server generates answers that are then displayed to the child through a user interface.

[1158] (Input) The generated answer.

[1159] (Data processing) The server receives the response and sends the information to the user interface.

[1160] (Output) The answer is displayed on the child's device.

[1161] (Specific Operation) The server sends the generated answer to the user interface, which displays it on the child's terminal.

[1162] Step 6:

[1163] Parents transfer money to their children through the device.

[1164] (Input) Amount to be sent and recipient information.

[1165] (Data processing) The server processes the remittance using an online payment system.

[1166] (Output) The success or failure status of the transfer.

[1167] (Specific operation) The parent inputs the amount to be transferred on the transfer screen and clicks the transfer button. The server processes the transfer via the payment system.

[1168] Step 7:

[1169] The server updates the remittance information in the database.

[1170] (Input) Remittance status and amount remitted.

[1171] (Data processing) The server updates the child's current savings amount in the database.

[1172] (Output) The updated savings amount.

[1173] (Specific operation) If the transfer is successful, the server adds the transferred amount to the child's current savings and updates the database.

[1174] Step 8:

[1175] Kids can use the progress tracker to see how they are progressing towards their savings goals and get advice.

[1176] (Input) Child's current savings amount and target savings amount.

[1177] (Data processing) The server analyzes the savings progress and generates advice.

[1178] (Output) Progress and advice.

[1179] (Specific operation) A child accesses the progress tracking screen and checks the current savings amount and the target savings amount. The server analyzes the progress data and displays advice.

[1180] (Application example 1)

[1181] 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."

[1182] Conventional systems lack mechanisms for children to set savings goals and provide appropriate plans and advice for achieving those goals. In addition, there are insufficient means for parents to transfer pocket money to their children and keep track of how it is being used and the savings situation, which makes it difficult to improve children's financial literacy.

[1183] 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.

[1184] In this invention, the server includes a database means for storing specific information including information about the child, a generating means for generating advice on how to save and increase the child's money using a natural language processing model, a sending means for a parent to digitally send pocket money to the child using the sending function, and a progress tracking means for tracking the progress of the child's savings goal and providing advice for achieving the goal. This allows the child to make a more specific and appropriate savings plan, and the parent can not only digitally send pocket money but also grasp the child's savings situation in real time and support the child.

[1185] A "database means" is a device or system for storing and managing specific information, including information about children.

[1186] A "generator" is a mechanism or function that uses a natural language processing model to generate advice on how to save and grow money for children.

[1187] A "remittance method" is a mechanism or function that allows parents to digitally send pocket money to their children.

[1188] A "progress tracker" is a mechanism or function that tracks a child's progress toward their savings goal and provides advice for reaching that goal.

[1189] "Information about the child" refers to information such as the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and means of earning the allowance.

[1190] A "natural language processing model" is an artificial intelligence technique for understanding human language and generating appropriate responses.

[1191] "Specific information" is detailed information that includes individual data required for the system to manage.

[1192] A "savings goal" refers to the specific amount of savings and the deadline that a child sets to achieve.

[1193] The present invention is a system that provides advice on savings and how to save money by storing specific information, including information about the child, in a database. The system also includes digital remittance functions from parents and progress tracking functions.

[1194] 1. Generating the system program

[1195] Database Means

[1196] The server uses a database means to store information about the child, including the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and means of earning pocket money.

[1197] Natural Language Processing Models

[1198] A natural language processing model is used to analyze questions posed by children and generate appropriate advice. For example, OpenAI's GPT model is used to generate answers to questions.

[1199] Remittance Method

[1200] The remittance method operates through the device used by the parent, and the server receives the remittance data. This function allows parents to send pocket money to their children digitally.

[1201] Progress Tracking

[1202] The server monitors the child's progress toward the savings goal using a progress tracker, analyzes the child's progress toward the savings goal, and generates advice, if necessary, that provides specific steps to achieve the goal.

[1203] 2. Hardware and Software Used

[1204] The implementation of this system uses the following hardware and software:

[1205] Server: A central server to manage the database that stores the children's information and to implement the payment transfer and progress tracking mechanisms.

[1206] Device (smartphone or tablet): The device the parent uses to transfer money.

[1207] Natural Language Processing Model: Natural Language Processing algorithm based on OpenAI's GPT model.

[1208] 3. Specific Examples

[1209] Example of a child asking a question: When a child uses a device to ask, "How can I save money quickly?", the natural language processing model analyzes the question and the server generates an answer such as, "Earn money by helping out or doing part-time work, and try to save your pocket money little by little," which is displayed on the device.

[1210] Examples of prompt statements

[1211] A question from a child: "How do I save money fast?"

[1212] This system not only gives children knowledge about saving, but also encourages them to achieve their goals in a fun way. At the same time, it also makes it easier for parents to support their children's savings goals, making it a system with high educational value.

[1213] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1214] Step 1:

[1215] Information storage by database means

[1216] The server receives as input certain information provided by the parent and the child, including the child's age, gender, wish list, current savings amount, goal savings amount, deadline for reaching the goal, and the means of earning the allowance. The server manages the information by storing this data in a database. The output is information about the child accurately stored in the database.

[1217] Step 2:

[1218] Entering and parsing questions

[1219] A child uses the device to input a question. As input, the device sends the child's text-based question (e.g., "How can I save more money quickly?") to the server. The server uses a natural language processing model (e.g., OpenAI's GPT model) to parse this input data. As an output of the analysis, we obtain an internal representation of the natural language processing model that understands the meaning of the child's question.

[1220] Step 3:

[1221] Generating Advice

[1222] Based on the analysis results, the server uses a natural language processing model to generate appropriate advice. Based on the generated prompt, a specific answer example (e.g., "Earn money by helping out or doing a part-time job, and try to save your pocket money little by little") is output. The generated advice is based on the child's input question.

[1223] Step 4:

[1224] Show Advice

[1225] The advice generated by the server is sent to the terminal and displayed on the child's terminal. The terminal provides a display interface so that the user (child) can view the advice. The output of this step is advice in natural language displayed on the terminal.

[1226] Step 5:

[1227] Entering and Processing Remittances

[1228] A parent uses a terminal to input information for transferring pocket money to a child. Input includes the amount to be transferred and information about the recipient (child). The terminal sends this information to a server. The server receives the transfer information and processes it by adding the amount to the child's current savings balance in a database. As an output of this process, the child's updated current savings balance is stored in the database.

[1229] Step 6:

[1230] Monitor progress and provide advice

[1231] The server periodically monitors the child's progress toward his / her savings goal. As input, the current savings amount and the goal amount are obtained from the database. The server analyzes these data and calculates the progress. Based on the progress, it generates additional advice (e.g., "You're 500 yen away from your goal. Keep trying!"). As output, advice reflecting the progress is generated and displayed on the child's device.

[1232] Through this process, children receive specific feedback on effective savings methods and progress, and parents can support their children's savings efforts by digitally transferring pocket money.

[1233] In addition, 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.

[1234] In addition to the elements described above, the embodiment of the present invention includes the following elements.

[1235] 1. Emotion Engine: An emotion engine is provided to recognize and analyze the child's emotions.

[1236] 2. Sensors: Sensors will be built into the system to recognize the child’s emotions.

[1237] 3. Emotion-based answer generation: The emotion engine analyzes the child's emotions and is adjusted to respond appropriately to the emotions when generating answers.

[1238] 4. User feedback: A function will be implemented to provide appropriate feedback on a child's emotions.

[1239] (Specific examples)

[1240] For example, a child enters a question about how to spend money through the device. The sensor recognizes the child's emotions when asking the question. The emotion engine analyzes the child's emotions and adjusts to respond appropriately to the emotions when generating answers. For example, if the user is feeling anxious or uncertain, the emotion engine generates advice that corresponds to that.

[1241] The generated answer is presented to the child. The system also provides appropriate feedback based on the child's emotions. For example, if the child feels happy or relieved about the answer, the system will provide positive feedback.

[1242] This is an example of a form for implementing the present disclosure. By combining the emotion engine and sensors, it is possible to recognize a child's emotions and provide appropriate answers and feedback.

[1243] The process flow will be explained below.

[1244] Step 1: The child types a question, including an emotion, into the device.

[1245] Children type questions about how to spend money into the device.

[1246] Questions can involve feelings and emotions.

[1247] Step 2: The sensor recognizes the child's emotions.

[1248] The device is equipped with sensors to recognize emotions.

[1249] The sensors detect changes in a child's facial expressions and voice and recognize emotions.

[1250] Step 3: The emotion engine on the server analyzes the emotion and generates an answer.

[1251] The emotion engine on the server analyzes the child's emotions and generates appropriate answers.

[1252] The emotion engine adjusts responses based on emotion to respond appropriately to a child's emotions.

[1253] Step 4: Your answer will be displayed on your device.

[1254] The answer sent by the processor on the server is displayed on the child's device.

[1255] Responses are emotion-adjusted and provide appropriate feedback to the child's emotions.

[1256] Step 5: Your child receives their answers and feedback.

[1257] The child will receive displayed answers and feedback.

[1258] Children may feel joy or relief in their answers or react to the feedback.

[1259] The above is a specific flow of processing in an embodiment that combines an emotion engine. A child inputs a question that includes emotion, the emotion is recognized by the sensor, and the emotion engine on the server analyzes the emotion and generates an answer. The generated answer is displayed on the terminal, and the child receives the answer and feedback. The combination of the emotion engine and the sensor provides a response appropriate to the child's emotion, realizing more effective communication.

[1260] Example 2

[1261] 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".

[1262] Conventional systems have difficulty in properly recognizing children's emotions and providing advice based on them. This has resulted in poor user experience and difficulty in providing appropriate feedback to children. In particular, there is a lack of emotion-based approaches, and there is a problem in that support for children to understand their own emotions and deal with them appropriately is insufficient.

[1263] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1264] In this invention, the server includes a means for acquiring specific information including information about the child previously inputted into a database, a means for receiving a question inputted by the child through the terminal, a means for collecting emotion data of the child using a sensor built into the terminal, a means for recognizing the emotion of the child using an emotion engine that analyzes the emotion data, a means for using a generative AI model that generates an appropriate answer based on the emotion data, a means for presenting the generated answer on the terminal, and a means for collecting emotion feedback of the child and generating an appropriate response based thereon. This makes it possible to appropriately analyze the emotion of the child in real time and provide advice or feedback based on the emotion.

[1265] A "database" is a system that systematically organizes and stores information so that it can be quickly searched and retrieved as needed.

[1266] "Specific information" refers to information about the child that has been pre-entered into the database, including the child's age, interests, goals, etc.

[1267] A "terminal" is a device that a user directly operates, and includes a PC, tablet, smartphone, etc.

[1268] A "sensor" is an electronic device for collecting user emotional data, including a camera, microphone, temperature sensor, etc.

[1269] "Emotional data" refers to information collected by sensors from a user's facial expressions, tone of voice, and physical movements.

[1270] An "emotion engine" is software or a system for analyzing emotion data to recognize a user's emotional state.

[1271] A "generative AI model" is an artificial intelligence model that generates appropriate answers based on input data, and a specific example would be a generative language model.

[1272] A "prompt" is an instruction given to a generative AI model that serves as the basis for the model to generate an appropriate answer.

[1273] "Feedback" refers to the response or reaction that the system provides to the user, and is generated adaptively based on the user's emotions.

[1274] "Real-time" refers to a time frame in which processing occurs immediately, without delay.

[1275] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1276] This invention relates to a system that recognizes a child's emotions and provides appropriate answers and feedback based on those emotions. The main components of this system are a sensor, an emotion engine, and a generative AI model.

[1277] Hardware and Software Used

[1278] 1. Sensors

[1279] The device is equipped with hardware such as a camera, microphone, and temperature sensor. As a specific example, a general-purpose camera and a general-purpose microphone are used.

[1280] 2. Emotion Engine

[1281] The server uses IBM Watson's emotion analysis API as an emotion engine, which analyzes the user's facial expressions and tone of voice to recognize their emotional state.

[1282] 3. Generative AI Models

[1283] The server uses OpenAI's ChatGPT as a generative AI model, which generates appropriate answers based on emotion data and input questions.

[1284] System Overview

[1285] In this system, the user inputs a question via the device, and the device's sensors collect the user's emotional data. The data is sent to the server, where the emotion engine analyzes it. Based on the analysis results, the generative AI model forms a prompt sentence and generates an appropriate answer. Finally, the generated answer is presented to the user via the device.

[1286] Examples

[1287] For example, if a child types "Teach me how to do my homework" into the device, the question is sent to the server along with sensor data collected through the camera and microphone. At the server, the emotion engine analyzes the child's facial expressions and tone of voice to recognize the child's emotional state of confusion. An appropriate answer is then generated by inputting the following prompt sentence into the generative AI model:

[1288] "A child asks, 'Tell me how to do my homework.' He's confused. Generate advice that takes this emotion into account."

[1289] The generated answer, "Don't try to do it all at once, but proceed little by little," is displayed on the device. Furthermore, if the user shows a relieved expression, the feedback data is sent again to the server, and positive feedback, "That's a great way of thinking!", is generated and displayed on the device.

[1290] As described above, this system is able to analyze children's emotions in real time and provide appropriate advice and feedback based on those emotions, thereby supporting children's emotions and providing a better user experience.

[1291] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1292] System processing steps

[1293] Step 1: User enters question

[1294] The user inputs a question via a terminal, either using a keyboard or a touch screen, and the input question is immediately transmitted to the system.

[1295] Input: The user's question text (e.g., "Can you help me with my homework?")

[1296] Output: The question text is sent from the terminal to the server.

[1297] Step 2: The device collects emotion data using sensors

[1298] The device is equipped with a camera, microphone, temperature sensor, etc. to collect user emotion data. The collected data is stored as image data, voice data, and temperature data.

[1299] Input: User's facial expression, tone of voice, body temperature

[1300] Output: Collected emotion data (image data, voice data, temperature data) is sent from the device to the server.

[1301] Specific actions: The camera captures a face and the microphone records a voice.

[1302] Step 3: The server analyzes the emotion data

[1303] The server receives the emotion data sent from the device and analyzes it with the emotion engine. The analysis identifies the user's emotional state (e.g. confusion, anxiety, joy). This analysis is mainly performed using facial expression recognition algorithms and voice analysis algorithms.

[1304] Input: Collected emotion data

[1305] Output: The user's emotional state (e.g. confused)

[1306] How it works: Facial expression recognition algorithms analyze facial features, and voice analysis algorithms analyze the tone of your voice.

[1307] Step 4: The server generates a sentiment-based answer

[1308] The server uses a generative AI model (e.g. ChatGPT by OpenAI) to generate an appropriate answer based on the analyzed emotional state. The prompt contains the user's question and their emotional state.

[1309] Input: User question text, parsed emotional state

[1310] Output: The generated answer text

[1311] Specific operation: Send a prompt to the generative AI model and receive a response

[1312] Example prompt:

[1313] "My child asks, 'Tell me how to do my homework.' He's confused. Generate advice that takes this emotion into account."

[1314] Step 5: The device presents the answer to the user

[1315] The terminal displays the answer sent from the server to the user. The generated answer is displayed in text format on the screen.

[1316] Input: Generated answer text

[1317] Output: The answer text is displayed on the device screen.

[1318] Specific action: The screen displays the message, "Don't try to do it all at once. It's better to proceed little by little."

[1319] Step 6: Collect user emotional feedback

[1320] The sensors again collect the user's reactions after viewing the answer, using cameras and microphones to capture the user's facial expressions and tone of voice.

[1321] Input: User's facial expressions, tone of voice

[1322] Output: Collected feedback data (image data, audio data) is sent from the device to the server.

[1323] Specific operation: The camera captures the face again and the microphone records the voice.

[1324] Step 7: The server parses the feedback and generates an appropriate response

[1325] The server analyzes the feedback data with an emotion engine and generates an appropriate response based on the user's emotional state, which may be further affirmation or additional advice.

[1326] Input: Collected feedback data

[1327] Output: The appropriate response text

[1328] Specific operation: Based on the analysis results, the emotion engine generates feedback such as "That's a great way of thinking!" and sends it to the device. Display on the device

[1329] (Application example 2)

[1330] 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".

[1331] In modern virtual stores, online shopping, especially for children, often involves anxiety and hesitation. Shopping experiences that ignore these emotions can be stressful for children, and may reduce shopping efficiency and satisfaction. In addition, conventional systems do not provide product suggestions or feedback that take into account children's emotional state, making it difficult to provide services that are tailored to individual users.

[1332] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1333] In this invention, the server includes specific information including information about the child previously inputted into a database, a generating means for generating advice about at least one of how to use and how to increase the savings of the child, an emotion recognizing means for recognizing the emotion of the child based on an emotion analyzing means, an information providing means for adjusting the advice according to the emotion based on the emotion recognizing means, a progress tracking means for tracking the progress to reach a target savings amount designated by the child, and a feedback providing means for providing feedback according to the emotion of the child based on the progress. This makes it possible to provide product suggestions and feedback based on the emotion of the child.

[1334] A "database" is an information storage system that stores information about children that has been entered in advance and performs various data processing based on this information.

[1335] "Specific Information" is personal data about a child and details about their behavior, feelings, preferences, etc.

[1336] "Generative" is a feature that uses existing data and algorithms to generate tailored advice and suggestions for children.

[1337] The "emotion analysis means" is a technology that uses an in-camera and microphone to analyze a child's facial expressions and tone of voice in real time to recognize their emotional state.

[1338] The "emotion recognition means" is a mechanism that uses the child's emotional state recognized by the emotion analysis means as is.

[1339] The "information provision means" is a function that adjusts and presents appropriate advice and product suggestions based on the emotion recognition means.

[1340] A "progress tracker" is a feature that tracks and monitors in real time the child's progress toward reaching a savings goal.

[1341] The "feedback providing means" is a function that provides appropriate feedback and product suggestions based on the progress and recognition of the child's emotions.

[1342] A system for implementing the present invention is constructed mainly using the following hardware and software.

[1343] Hardware:

[1344] 1. Front camera: Used to capture children's facial expressions.

[1345] 2. Microphone: Used to analyze the tone of the child's voice.

[1346] software:

[1347] 1. Software A: Software that performs real-time image processing.

[1348] 2. Module A: A face detection module used for face detection.

[1349] 3. Sentiment Engine: A library for performing sentiment analysis.

[1350] Specific behavior:

[1351] The server collects data on the child in real time through the front camera and microphone, and performs emotion analysis based on this data. Specifically, the following steps are taken:

[1352] 1. Data Acquisition:

[1353] The server captures the child's facial expressions using the front camera and obtains the tone of voice using the microphone.

[1354] 2. Emotion recognition:

[1355] The server analyzes the acquired data using an emotion engine and recognizes the child's emotions.

[1356] 3. Information provision:

[1357] Based on the emotions detected, information delivery methods are used to tailor advice and product suggestions.

[1358] For example, if a child is excited, the system will suggest similar popular products, and if the child looks anxious, it will present reassuring messages and other user reviews.

[1359] 4. Progress Tracking and Feedback:

[1360] A progress tracker tracks the child's progress towards reaching a savings goal.

[1361] The feedback mechanism provides appropriate feedback according to progress, for example sending encouraging messages when the user is approaching a goal.

[1362] Examples and prompts:

[1363] For example, if a child looks excited while browsing a virtual store using a head-mounted display, the server will suggest products such as a new stuffed toy or a popular picture book. On the other hand, if the child looks anxious, the server will suggest products that will give the child a sense of security, such as a science kit.

[1364] Example prompt:

[1365] "How can we make appropriate product suggestions based on the emotions a child displays while shopping in a virtual store?"

[1366] As described above, the server can use each means to provide product suggestions and feedback according to the child's emotions, allowing the child to enjoy online shopping with peace of mind.

[1367] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1368] Step 1:

[1369] Data Acquisition

[1370] The server captures the child's facial expressions and tone of voice in real time using the front camera and microphone. The input data is image data and voice data. The server processes the image data using software A and detects facial feature points using module A. At the same time, it sends the captured voice data to the emotion engine.

[1371] Step 2:

[1372] emotion recognition

[1373] The server passes the processed image data to the emotion engine, which recognizes the child's emotions based on facial features. Similarly, the voice data is analyzed by the emotion engine. The analysis results in a series of emotion tags such as "happy," "sad," and "excited" as output.

[1374] Step 3:

[1375] Providing information

[1376] The server runs an algorithm to generate appropriate advice or product suggestions based on the emotion tag. For example, if the emotion tag says "excited," the server might suggest a new stuffed toy or a picture book. The server sends the generated suggestion data to the device and displays it to the child.

[1377] Step 4:

[1378] Progress Tracking

[1379] The server tracks the child's progress toward the savings goal, calculating the progress based on the savings data received from the device, and presenting the progress as a percentage toward the goal to the feedback algorithm.

[1380] Step 5:

[1381] Provide feedback

[1382] The server runs a feedback algorithm based on the progress and emotion tag, for example generating an encouraging message if the progress is good, or a reassuring message if the emotion tag indicates anxiety, and sends this feedback to the device to be shown to the child.

[1383] Step 6:

[1384] Optimizations and improvements

[1385] The server collects user feedback and evaluates the effectiveness of the generated advice and product suggestions. Based on this, it optimizes the emotion recognition algorithm and information provision algorithm to improve the accuracy of suggestions from the next time onwards. Specifically, it fine-tunes the suggestion algorithm based on data on products actually purchased to make effective suggestions.

[1386] By repeating the above processing steps, the system will be able to provide optimal advice and product suggestions based on the child's emotions, allowing them to enjoy shopping with peace of mind.

[1387] 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 a voice indicating a user input for 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.

[1388] 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 making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to 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.

[1389] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the robot 414.

[1390] The emotion identification model 59 as an emotion engine may determine the emotion of the user according to a specific mapping. Specifically, the emotion identification model 59 may determine the emotion of the user according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the emotion of the robot, and the identification processing unit 290 may perform identification processing using the emotion of the robot.

[1391] FIG. 9 is a diagram showing 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. The closer to the center of the concentric circles, the more primitive emotions are arranged. The more outside the concentric circles, the more emotions that represent states and actions that arise from a state of mind are arranged. Emotions are a concept that includes emotions and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions that occur in the brain are arranged. On the right side of the concentric circles, emotions that are generally induced by situational judgment are arranged. On the upper and lower sides of the concentric circles, emotions that are generally generated from reactions that occur in the brain and are induced by situational judgment are arranged. In addition, on the upper side of the concentric circles, emotions of "pleasure" are arranged, and on the lower side, emotions of "discomfort" are arranged. In this way, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1392] These emotions are distributed in the three o'clock direction of emotion map 400 and usually 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.

[1393] The inside of emotion map 400 represents what is going on inside one's mind, and the outside of emotion map 400 represents behavior, so the further out you go on emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1394] Here, human emotions are based on various balances such as posture and blood sugar level, and when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. Emotions can also be created for robots, cars, motorcycles, etc., based on various balances such as posture and battery level, so that when these balances are far from the ideal, it indicates an unpleasant state, and when they are close to the ideal, it indicates a pleasant state. The emotion map may be generated, for example, based on the emotion map of Dr. Mitsuyoshi (Research on speech emotion recognition and emotion brain physiological signal analysis system, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). On the left half of the emotion map, emotions belonging to an area called "reaction" where sensation is dominant are lined up. On the right half of the emotion map, emotions belonging to an area called "situation" where situation recognition is dominant are lined up.

[1395] The emotion map defines two emotions that promote learning. The first is the negative emotion around the middle of "repentance" or "remorse" on the situation side. In other words, this is 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 the positive emotion around "desire" on the response side. In other words, this is when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1396] The emotion identification model 59 inputs the user input to a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the emotion of the user. This neural network is pre-trained based on multiple learning data that are combinations of the 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, "relief," "calm," and "encouraging," have similar emotion values.

[1397] Although the system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, the system according to the present disclosure is not necessarily implemented in 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 that runs on a personal computer, or an application that runs on a smartphone or the like. The method according to the present disclosure may be provided to a user in the form of SaaS (Software as a Service).

[1398] In the above embodiment, an example is 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 the external device may generate data according to input data.

[1399] 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 Universal Serial Bus (USB) 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.

[1400] In addition, 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 upon request from the data processing device 12.

[1401] 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.

[1402] As the hardware resource for executing the specific process, various processors as shown below can be used. An example of the processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing the specific process by executing software, i.e., a program. Another example of the processor is a dedicated electric circuit, which is a processor having a circuit configuration designed exclusively for executing the specific process, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), or an Application Specific Integrated Circuit (ASIC). Each processor has a built-in or connected memory, and each processor executes the specific process by using the memory.

[1403] The hardware resource that executes the specific process may be one of these various processors, or may be a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[1404] As an example of a configuration using one 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 configuration using a processor that realizes the functions of the 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.

[1405] Furthermore, more specifically, the hardware structure of these various processors can be an electric circuit that combines circuit elements such as semiconductor elements. The specific processes described above are merely examples. It goes without saying that unnecessary steps may be deleted, new steps may be added, or the order of processes may be changed without departing from the spirit of the invention.

[1406] The above description and illustrations are detailed descriptions 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, function, action, and effect is an example of the configuration, function, action, and effect 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 description and illustrations, within the scope of the gist of the technology of the present disclosure. In addition, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the above description and illustrations omit explanations of technical common sense that do not require explanation in order to enable the implementation of the technology of the present disclosure.

[1407] All publications, patent applications, and standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or standard was specifically and individually indicated to be incorporated by reference.

[1408] The following is further disclosed regarding the above embodiment.

[1409] (1) a generating unit that generates specific information including information about a child that is input in advance into a database, and advice on at least one of how to use and how to increase savings that the child saves; system.

[1410] (2) The generating unit tracks the progress of the child in reaching a target savings amount and generates the advice for reaching the target savings amount. 1. The system described in (1).

[1411] (3) An acquisition unit that acquires pocket money sent to the child by the child's parent, The system described in (1) or (2).

[1412] (4) an emotion engine that recognizes an emotion of the child and reflects the recognized emotion of the child in the advice generated by the generation unit; The system according to (1), (2) or (3).

[1413] "Example 1"

[1414] (Claim 1) means for storing specific information including information about the child that has been previously entered into the database; A natural language processing model means for analyzing questions from children and generating answers; user interface means for a parent or child to input information and receive generated answers and advice; A digital money transfer function that allows parents to send pocket money to their children, a progress tracking feature for tracking the child's progress toward their savings goal and providing advice for reaching the goal; A system including:

[1415] (Claim 2) a means for inputting a child's question; A means for generating answers to questions utilizing a natural language processing model; and means for displaying the generated answers to the child through a user interface. 2. The system of claim 1.

[1416] (Claim 3) A way for parents to transfer money to their children through the device, further comprising means for updating the remittance information into the database; 2. The system of claim 1.

[1417] "Application example 1"

[1418] (Claim 1) database means for storing specific information including information regarding children; a generating means for generating advice on how to save and grow for a child using a natural language processing model; A money transfer method that allows parents to digitally send pocket money to their children using the remittance function, a progress tracker to track a child's progress towards their savings goal and provide advice on how to achieve that goal; A system including:

[1419] (Claim 2) 2. The system of claim 1, wherein the progress tracking means tracks the child's progress toward reaching a savings goal and generates advice for reaching the savings goal.

[1420] (Claim 3) The system according to claim 1, wherein the remittance means includes an acquisition means for digitally acquiring pocket money remitted by a parent to a child and reflecting the money in the child's savings.

[1421] "Example 2 of combining emotion engines"

[1422] (Claim 1) means for obtaining specific information, including information about the child, that has been previously entered into a database; means for receiving a question input by the child via a terminal; A means for collecting emotion data of a child using a sensor built into the terminal; means for recognizing a child's emotion using an emotion engine that analyzes the emotion data; a means for using a generative AI model to generate an appropriate response based on the emotion data; means for presenting the generated answer on a terminal; means for collecting said child's emotional feedback and generating an appropriate response based thereon; A system including:

[1423] (Claim 2) 2. The system of claim 1, wherein the generative AI model generates prompt sentences corresponding to a child's emotional data.

[1424] (Claim 3) 2. The system of claim 1, wherein the emotion engine includes algorithms that analyze a child's tone of voice and facial expressions.

[1425] "Application example 2 when combining emotion engines"

[1426] (Claim 1) identifying information, including information about the child, that has been pre-entered into the database; a generating means for generating advice on at least one of how to use and how to increase the savings saved by the child; emotion recognition means for recognizing an emotion of the child based on the emotion analysis means; an information providing means for adjusting the advice according to the emotion based on the emotion recognition means; progress tracking means for tracking progress towards reaching said child specified savings goal; a feedback providing means for providing feedback according to the child's emotions based on the progress; A system including:

[1427] (Claim 2) The feedback providing means presents appropriate candidate products based on the child's emotion recognition. 2. The system of claim 1.

[1428] (Claim 3) a receiving means for receiving pocket money for the child remitted by a guardian of the child; 2. The system of claim 1. [Explanation of symbols]

[1429] 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 first means for acquiring specific information including the child's age, sex, wish list, current savings amount, goal savings amount, deadline for achieving the goal, and means for obtaining the allowance; A second means for a parent of the child to digitally send pocket money to the child using a money transfer function; A third means for acquiring pocket money remitted from the parent and updating a current savings amount included in the specific information; a fourth means for generating a first prompt sentence based on the specific information and a question from the child, for outputting advice for reaching the target savings amount included in the specific information; a fifth means for inputting the generated first prompt sentence into a generative AI model to generate the advice; a sixth means for presenting the generated advice to the child through a user interface; A system including:

2. A seventh means for collecting emotion data of the child using a sensor built into the terminal; an eighth means for recognizing an emotion of the child using an emotion engine that analyzes the emotion data; Including, the fourth means generates a second prompt sentence for outputting an answer that takes into consideration the child's feelings, based on the child's feelings, the specific information, and a question from the child; The fifth means inputs the generated second prompt sentence into a generative AI model to generate the answer. The system of claim 1 .

3. the fourth means generates a third prompt sentence for suggesting a product corresponding to the child's emotion while shopping in the virtual store, based on the child's emotion; The fifth means inputs the generated third prompt sentence into a generative AI model to suggest the product. The system of claim 2.

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