System

Abstract

An object of the system according to the embodiment is to allow a user to specifically imagine a goal or a dream and maintain motivation toward the goal or the dream.SOLUTION: A system includes an objective input part, a diary generation part, a communication part, and an advertisement insertion part. The goal input unit inputs a goal and a dream of the user. A diary generation part generates a future diary on the basis of the target and dream input by the target input part. The communication unit realizes communication between the user and himself / herself in the future through the future diary generated by the diary generation unit. The ad insertion portion inserts corporate ads into the process of achieving goals.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has had the problem of making it difficult for users to visualize their goals and dreams concretely and maintain motivation to work towards them.

[0005] The system according to the embodiment aims to help users concretely visualize their goals and dreams and maintain their motivation to work towards them. [Means for solving the problem]

[0006] The system according to the embodiment includes a goal input unit, a diary creation unit, a communication unit, and an advertisement insertion unit. The goal input unit inputs the user's goals and dreams. The diary creation unit creates a future diary based on the goals and dreams input by the goal input unit. The communication unit realizes communication between the user and their future self through the future diary created by the diary creation unit. The advertisement insertion unit inserts corporate advertisements into the goal achievement process. [Effects of the Invention]

[0007] The system according to the embodiment allows users to visualize their goals and dreams in concrete terms and maintain their motivation to work towards them. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The future diary creation system according to an embodiment of the present invention is a system in which, when a user inputs their goals and dreams, it creates a diary of a future in which those goals have come true, allowing the user to communicate with their future self. This allows the user to recognize their happy self, whose dreams have come true, and to specifically learn about the process and actions taken to make their dreams come true. Furthermore, advertising revenue can be earned by inserting corporate advertisements.

[0029] A future diary generation system according to an embodiment includes a goal input unit, a diary generation unit, a communication unit, and an advertisement insertion unit. The goal input unit inputs a user's goals and dreams. For example, the user may input "I want to become a doctor." The diary generation unit generates a future diary entry based on the goals and dreams input by the goal input unit. For example, the generation AI may generate a diary entry such as, "In 2025, I finally became a doctor. I see many patients every day and live a fulfilling life." The communication unit enables communication between the user and their future self through the future diary entry generated by the diary generation unit. For example, if a user asks, "How did you become a doctor?", the generation AI may generate an answer to that question. The advertisement insertion unit inserts corporate advertisements into the goal achievement process. For example, it displays advertisements for related companies, such as, "Here are prep schools for entering medical school." This allows the future diary generation system according to an embodiment to concretely visualize the user's goals and dreams and learn the process of achieving them. Furthermore, inserting corporate advertisements can also generate business revenue.

[0030] When a user inputs their goals or dreams, the generation AI provides real-time feedback and advice to increase the specificity and achievability of the goal. For example, if a user inputs "I want to be a doctor," the generation AI will ask "What specific field of doctor do you want to be?" and then ask more specific questions such as "Which university's medical school are you aiming for?" to increase the specificity of the goal. The generation AI uses natural language processing technology to analyze the user's input and provide appropriate feedback. For example, the generation AI will evaluate the achievability of the goals entered by the user and provide specific advice. This makes it easier for users to set specific goals and dreams.

[0031] The goal input unit can refer to the history of goals and dreams entered by the user in the past and present success stories of other users with similar goals. For example, if a user enters "I want to become a doctor," the goal input unit presents success stories of other users who had the same goal in the past. For example, it displays a specific example such as "Mr. A entered medical school and is now working as an internist." The goal input unit saves the input data of past goals and dreams and searches for success stories of users with similar goals. For example, the goal input unit identifies success stories of users with similar goals based on keyword matches or goal categories. This allows users to refer to other success stories and increase their motivation to achieve their goals.

[0032] The diary generation unit can generate a more realistic and specific future diary entry by reflecting the user's past behavioral data and history. For example, if a user inputs "I want to become a doctor" and has past behavioral data such as "I passed the entrance exam for medical school," the generation AI will generate a specific diary entry such as "In 2025, I will have graduated from medical school and will be working as an internist." The generation AI analyzes the user's past behavioral data and history and reflects them in the future diary entry. For example, the generation AI generates future diary entries based on the user's past behavioral history and location information. This allows the user to imagine a more realistic future.

[0033] The diary generation unit can add specific events and episodes related to the user's goals to the future diary, enhancing the sense of realism. For example, if a user inputs, "I want to be a doctor," and the generation AI generates, "In 2025, I will have graduated from medical school and will be working as an internist," the diary generation unit can add further specific episodes such as, "I will be seeing many patients every day and living a fulfilling life." The generation AI generates specific events and episodes related to the user's goals. For example, the generation AI generates the contents of the future diary based on events and important events related to the user's goals. This allows the user to feel that the future diary is more realistic.

[0034] The communication unit allows the generation AI to provide consistent answers by referring to the user's past question history when answering questions as the future self. For example, if the user asks their future self, "How did you become a doctor?", the generation AI will refer to the past question history and provide a consistent answer such as, "I first enrolled in medical school, then completed an internship and obtained my qualifications." The generation AI saves the user's past question history and refers to it to maintain the consistency of answers. For example, the generation AI generates consistent answers based on the content of past questions and the answer history. This allows the user to obtain consistent answers, making communication with their future self more reliable.

[0035] The communication unit can enable communication with the future self not only in chat format but also in voice dialogue format. For example, if a user asks their future self, "How did you become a doctor?", the generation AI will respond in voice dialogue format, "I first enrolled in medical school, then completed an internship and obtained my qualifications." This allows the user to experience more realistic communication. The generation AI realizes voice dialogue format communication using voice recognition technology and voice synthesis technology. For example, the generation AI recognizes the user's voice and generates an appropriate voice response. This allows the user to communicate with their future self not only in chat format but also in voice dialogue format.

[0036] The ad insertion unit can reflect the user's past purchase history and interests in the goal-achievement process presented by the generation AI and display highly relevant advertisements. For example, if a user inputs "I want to become a doctor," and the generation AI suggests, "First, you need to enroll in medical school, then complete an internship to obtain qualifications," the ad insertion unit will take the user's past purchase history into consideration and display highly relevant advertisements such as, "Here are reference books for preparing for medical school entrance exams." The generation AI analyzes the user's past purchase history and interests to identify highly relevant advertisements. For example, the generation AI can display appropriate advertisements based on the user's past purchases and search history. This can increase the effectiveness of advertising by displaying advertisements that are highly relevant to the user.

[0037] The ad insertion unit uses the emotion estimation function to analyze the emotional response of a user when viewing an advertisement and can prioritize displaying advertisements that evoke positive emotions. For example, when a user inputs "I want to become a doctor" and the generation AI displays "You must first enroll in medical school, then complete an internship to obtain a license," the ad insertion unit uses the emotion estimation function to analyze whether an advertisement such as "Click here for reference books to help you prepare for the medical school entrance exam" evokes positive emotions in the user and prioritizes displaying advertisements that evoke positive reactions. The emotion estimation function estimates the user's emotions using facial expression recognition technology and voice analysis technology. For example, the emotion estimation function analyzes changes in the user's facial expressions and tone of voice to calculate an emotion score. This allows the user to view the advertisement with positive emotions.

[0038] The ad insertion unit can display corporate advertisements not only in text format but also in image and video format, providing visually appealing advertisements. For example, when a user inputs "I want to be a doctor" and the generation AI displays "You must first enroll in medical school, then complete an internship to obtain the qualification," the ad insertion unit displays not only text advertisements but also image and video advertisements for study guides for medical school entrance exams. The generation AI displays corporate advertisements not only in text format but also in image and video format. For example, the generation AI displays advertisements using still images, animated images, streaming videos, etc. This can increase the effectiveness of advertisements by providing visually appealing advertisements.

[0039] The ad insertion unit can provide the content of the ad in the form of a story related to the user's goals and dreams, so that the ad itself can increase the user's motivation. For example, when a user inputs "I want to be a doctor" and the generation AI displays "You must first enroll in medical school, then complete an internship to obtain the qualification," the ad insertion unit can provide an advertisement for a study guide for medical school entrance exams in the form of a story about a successful doctor, thereby increasing the user's motivation. The generation AI provides the content of the ad in the form of a story related to the user's goals and dreams. For example, the generation AI can generate advertisements in the form of a story or a series of episodes. This can increase the effectiveness of the advertisement by allowing the advertisement itself to increase the user's motivation.

[0040] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0041] The future diary generation system can also be equipped with a health management unit that acquires the user's health data and provides health management advice to help them achieve their goals. For example, if a user inputs, "I want to complete a marathon," the health management unit will provide an appropriate training plan and dietary advice based on the user's current health condition. The health management unit will analyze the user's heart rate, number of steps, sleep data, etc., and generate specific advice to help them achieve their goals. This allows the user to receive support to achieve their goals in a healthy manner.

[0042] The future diary generation system can also include an event information section that provides event and community information related to achieving goals based on the user's hobbies and interests. For example, if a user inputs "I want to be a guitarist," the event information section will provide information on nearby guitar lessons and music events. The event information section analyzes the user's interests and past event participation history to identify highly relevant event information. This makes it easier for the user to take concrete action toward achieving their goals.

[0043] The future diary generation system can also be equipped with a progress management unit that visualizes the user's progress toward achieving their goal. For example, if a user inputs, "I want to finish writing a novel," the progress management unit will display the user's writing status in graphs and charts, allowing the user to visually check their progress toward achieving their goal. The progress management unit analyzes the user's input data and behavioral history and updates the progress status in real time. This makes it easier for the user to maintain motivation toward achieving their goal.

[0044] The future diary generation system can also be equipped with a schedule management unit that manages the user's schedule to achieve their goals. For example, if a user inputs, "I want to complete a full marathon," the schedule management unit will display training plans and dates of important events in a calendar format, supporting the user in progressing toward their goal in a planned manner. The schedule management unit will analyze the user's goals and daily schedule and propose an optimal training plan. This will allow the user to take action to achieve their goals efficiently.

[0045] The future diary generation system can also be equipped with a feedback unit that provides feedback to the user toward achieving their goal. For example, if a user inputs, "I want to be able to speak English fluently," the feedback unit will evaluate the user's learning progress and suggest specific areas for improvement and next steps. The feedback unit will analyze the user's learning data and test results and generate appropriate feedback. This will allow the user to effectively study toward achieving their goal.

[0046] The processing flow of the first embodiment will be briefly explained below.

[0047] Step 1: The goal input unit inputs the user's goals and dreams. For example, the user inputs "I want to be a doctor." Step 2: The diary generation unit generates a future diary based on the goals and dreams entered by the goal input unit. For example, the generation AI might generate a diary entry such as, "In 2025, I have finally become a doctor. I see many patients every day and live a fulfilling life." Step 3: The communication unit enables communication between the user and their future self through the future diary created by the diary generation unit. For example, if the user asks, "How did you become a doctor?", the generation AI generates an answer to that question. Step 4: The ad insertion unit inserts corporate advertisements into the goal achievement process. For example, it displays advertisements for related companies in the form of "Click here for preparatory schools for entering medical school."

[0048] (Example 2) The future diary creation system according to an embodiment of the present invention is a system in which, when a user inputs their goals and dreams, it creates a diary of a future in which those goals have come true, allowing the user to communicate with their future self. This allows the user to recognize their happy self, whose dreams have come true, and to specifically learn about the process and actions taken to make their dreams come true. Furthermore, advertising revenue can be earned by inserting corporate advertisements.

[0049] A future diary generation system according to an embodiment includes a goal input unit, a diary generation unit, a communication unit, and an advertisement insertion unit. The goal input unit inputs a user's goals and dreams. For example, the user may input "I want to become a doctor." The diary generation unit generates a future diary entry based on the goals and dreams input by the goal input unit. For example, the generation AI may generate a diary entry such as, "In 2025, I finally became a doctor. I see many patients every day and live a fulfilling life." The communication unit enables communication between the user and their future self through the future diary entry generated by the diary generation unit. For example, if a user asks, "How did you become a doctor?", the generation AI may generate an answer to that question. The advertisement insertion unit inserts corporate advertisements into the goal achievement process. For example, it displays advertisements for related companies, such as, "Here are prep schools for entering medical school." This allows the future diary generation system according to an embodiment to concretely visualize the user's goals and dreams and learn the process of achieving them. Furthermore, inserting corporate advertisements can also generate business revenue.

[0050] When a user inputs their goals or dreams, the generation AI provides real-time feedback and advice to increase the specificity and achievability of the goal. For example, if a user inputs "I want to be a doctor," the generation AI will ask "What specific field of doctor do you want to be?" and then ask more specific questions such as "Which university's medical school are you aiming for?" to increase the specificity of the goal. The generation AI uses natural language processing technology to analyze the user's input and provide appropriate feedback. For example, the generation AI will evaluate the achievability of the goals entered by the user and provide specific advice. This makes it easier for users to set specific goals and dreams.

[0051] The goal input unit can refer to the history of goals and dreams entered by the user in the past and present success stories of other users with similar goals. For example, if a user enters "I want to become a doctor," the goal input unit presents success stories of other users who had the same goal in the past. For example, it displays a specific example such as "Mr. A entered medical school and is now working as an internist." The goal input unit saves the input data of past goals and dreams and searches for success stories of users with similar goals. For example, the goal input unit identifies success stories of users with similar goals based on keyword matches or goal categories. This allows users to refer to other success stories and increase their motivation to achieve their goals.

[0052] The goal input unit uses the emotion estimation function to analyze the emotions a user feels when entering a goal and display an encouraging message to elicit positive emotions. For example, when a user enters "I want to be a doctor," the goal input unit analyzes the user's facial expression and voice, and if the user feels nervous or anxious, displays an encouraging message such as "You can definitely become a doctor!" The emotion estimation function estimates the user's emotions using facial expression recognition technology and voice analysis technology. For example, the emotion estimation function analyzes changes in the user's facial expression and tone of voice to calculate an emotion score. This allows the user to set a goal while maintaining positive emotions.

[0053] The diary generation unit can generate a more realistic and specific future diary entry by reflecting the user's past behavioral data and history. For example, if a user inputs "I want to become a doctor" and has past behavioral data such as "I passed the entrance exam for medical school," the generation AI will generate a specific diary entry such as "In 2025, I will have graduated from medical school and will be working as an internist." The generation AI analyzes the user's past behavioral data and history and reflects them in the future diary entry. For example, the generation AI generates future diary entries based on the user's past behavioral history and location information. This allows the user to imagine a more realistic future.

[0054] The diary generation unit can add specific events and episodes related to the user's goals to the future diary, enhancing the sense of realism. For example, if a user inputs, "I want to be a doctor," and the generation AI generates, "In 2025, I will have graduated from medical school and will be working as an internist," the diary generation unit can add further specific episodes such as, "I will be seeing many patients every day and living a fulfilling life." The generation AI generates specific events and episodes related to the user's goals. For example, the generation AI generates the contents of the future diary based on events and important events related to the user's goals. This allows the user to feel that the future diary is more realistic.

[0055] The diary generation unit can use the emotion estimation function to adjust the content of future diary entries so that they evoke positive emotions in the user. For example, if a user inputs "I want to be a doctor" and the generation AI generates "In 2025, I will have graduated from medical school and be working as an internist," the diary generation unit can use the emotion estimation function to adjust the content to something more positive, such as "I see many patients every day and receive words of gratitude." The emotion estimation function estimates the user's emotions using facial expression recognition technology and voice analysis technology. For example, the emotion estimation function analyzes changes in the user's facial expression and tone of voice to calculate an emotion score. This allows the user to feel positive emotions through their future diary entries.

[0056] The communication unit allows the generation AI to provide consistent answers by referring to the user's past question history when answering questions as the future self. For example, if the user asks their future self, "How did you become a doctor?", the generation AI will refer to the past question history and provide a consistent answer such as, "I first enrolled in medical school, then completed an internship and obtained my qualifications." The generation AI saves the user's past question history and refers to it to maintain the consistency of answers. For example, the generation AI generates consistent answers based on the content of past questions and the answer history. This allows the user to obtain consistent answers, making communication with their future self more reliable.

[0057] The communication unit can enable communication with the future self not only in chat format but also in voice dialogue format. For example, if a user asks their future self, "How did you become a doctor?", the generation AI will respond in voice dialogue format, "I first enrolled in medical school, then completed an internship and obtained my qualifications." This allows the user to experience more realistic communication. The generation AI realizes voice dialogue format communication using voice recognition technology and voice synthesis technology. For example, the generation AI recognizes the user's voice and generates an appropriate voice response. This allows the user to communicate with their future self not only in chat format but also in voice dialogue format.

[0058] The communication unit uses the emotion estimation function to adjust answers to questions the user poses to their future self so that they evoke positive emotions in the user. For example, if a user asks their future self, "How did you become a doctor?", the generative AI will use the emotion estimation function to provide a positive answer such as, "I first enrolled in medical school, then completed an internship and obtained my qualifications. I'm sure you can be just as successful!" The emotion estimation function estimates the user's emotions using facial expression recognition and voice analysis technologies. For example, the emotion estimation function analyzes changes in the user's facial expressions and tone of voice to calculate an emotion score. This allows the user to communicate with their future self with positive emotions.

[0059] The ad insertion unit can reflect the user's past purchase history and interests in the goal-achievement process presented by the generation AI and display highly relevant advertisements. For example, if a user inputs "I want to become a doctor," and the generation AI suggests, "First, you need to enroll in medical school, then complete an internship to obtain qualifications," the ad insertion unit will take the user's past purchase history into consideration and display highly relevant advertisements such as, "Here are reference books for preparing for medical school entrance exams." The generation AI analyzes the user's past purchase history and interests to identify highly relevant advertisements. For example, the generation AI can display appropriate advertisements based on the user's past purchases and search history. This can increase the effectiveness of advertising by displaying advertisements that are highly relevant to the user.

[0060] The ad insertion unit uses the emotion estimation function to analyze the emotional response of a user when viewing an advertisement and can prioritize displaying advertisements that evoke positive emotions. For example, when a user inputs "I want to become a doctor" and the generation AI displays "You must first enroll in medical school, then complete an internship to obtain a license," the ad insertion unit uses the emotion estimation function to analyze whether an advertisement such as "Click here for reference books to help you prepare for the medical school entrance exam" evokes positive emotions in the user and prioritizes displaying advertisements that evoke positive reactions. The emotion estimation function estimates the user's emotions using facial expression recognition technology and voice analysis technology. For example, the emotion estimation function analyzes changes in the user's facial expressions and tone of voice to calculate an emotion score. This allows the user to view the advertisement with positive emotions.

[0061] The ad insertion unit can display corporate advertisements not only in text format but also in image and video format, providing visually appealing advertisements. For example, when a user inputs "I want to be a doctor" and the generation AI displays "You must first enroll in medical school, then complete an internship to obtain the qualification," the ad insertion unit displays not only text advertisements but also image and video advertisements for study guides for medical school entrance exams. The generation AI displays corporate advertisements not only in text format but also in image and video format. For example, the generation AI displays advertisements using still images, animated images, streaming videos, etc. This can increase the effectiveness of advertisements by providing visually appealing advertisements.

[0062] The ad insertion unit can provide the content of the ad in the form of a story related to the user's goals and dreams, so that the ad itself can increase the user's motivation. For example, when a user inputs "I want to be a doctor" and the generation AI displays "You must first enroll in medical school, then complete an internship to obtain the qualification," the ad insertion unit can provide an advertisement for a study guide for medical school entrance exams in the form of a story about a successful doctor, thereby increasing the user's motivation. The generation AI provides the content of the ad in the form of a story related to the user's goals and dreams. For example, the generation AI can generate advertisements in the form of a story or a series of episodes. This can increase the effectiveness of the advertisement by allowing the advertisement itself to increase the user's motivation.

[0063] The ad insertion unit uses the emotion estimation function to monitor the user's emotional response in real time when viewing an advertisement, and can continuously display the most appropriate advertisement. For example, if a user inputs "I want to become a doctor," and the generation AI displays "You must first enroll in medical school, then complete an internship to obtain a qualification," the ad insertion unit uses the emotion estimation function to monitor the user's emotional response in real time when viewing an advertisement for a study guide for medical school entrance exams, and continuously displays advertisements that elicit a positive response. The emotion estimation function estimates the user's emotions using facial expression recognition technology and voice analysis technology. For example, the emotion estimation function analyzes changes in the user's facial expression and tone of voice to calculate an emotion score. This allows the system to continuously display the most appropriate advertisement by monitoring the user's emotional response in real time.

[0064] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0065] The future diary generation system can also be equipped with a health management unit that acquires the user's health data and provides health management advice to help them achieve their goals. For example, if a user inputs, "I want to complete a marathon," the health management unit will provide an appropriate training plan and dietary advice based on the user's current health condition. The health management unit will analyze the user's heart rate, number of steps, sleep data, etc., and generate specific advice to help them achieve their goals. This allows the user to receive support to achieve their goals in a healthy manner.

[0066] The future diary generation system can also include an event information section that provides event and community information related to achieving goals based on the user's hobbies and interests. For example, if a user inputs "I want to be a guitarist," the event information section will provide information on nearby guitar lessons and music events. The event information section analyzes the user's interests and past event participation history to identify highly relevant event information. This makes it easier for the user to take concrete action toward achieving their goals.

[0067] The future diary generation system can also be equipped with a progress management unit that visualizes the user's progress toward achieving their goal. For example, if a user inputs, "I want to finish writing a novel," the progress management unit will display the user's writing status in graphs and charts, allowing the user to visually check their progress toward achieving their goal. The progress management unit analyzes the user's input data and behavioral history and updates the progress status in real time. This makes it easier for the user to maintain motivation toward achieving their goal.

[0068] The future diary generation system can also be equipped with a schedule management unit that manages the user's schedule to achieve their goals. For example, if a user inputs, "I want to complete a full marathon," the schedule management unit will display training plans and dates of important events in a calendar format, supporting the user in progressing toward their goal in a planned manner. The schedule management unit will analyze the user's goals and daily schedule and propose an optimal training plan. This will allow the user to take action to achieve their goals efficiently.

[0069] The future diary generation system can also be equipped with a feedback unit that provides feedback to the user toward achieving their goal. For example, if a user inputs, "I want to be able to speak English fluently," the feedback unit will evaluate the user's learning progress and suggest specific areas for improvement and next steps. The feedback unit will analyze the user's learning data and test results and generate appropriate feedback. This will allow the user to effectively study toward achieving their goal.

[0070] The future diary generation system can also be equipped with a motivation maintenance unit that estimates the user's emotions and provides encouraging messages to maintain motivation toward achieving goals. For example, if a user inputs "I want to become a doctor" and the emotion estimation function determines that the user's motivation is declining, the motivation maintenance unit will display an encouraging message such as "You can definitely become a doctor!" The emotion estimation function analyzes the user's facial expressions and voice and calculates an emotion score. This allows the user to continue taking action toward achieving their goals while maintaining positive emotions.

[0071] The future diary generation system can also be equipped with an advice unit that estimates the user's emotions and provides advice toward achieving their goals. For example, if a user inputs "I want to be a writer" and the emotion estimation function determines that the user is feeling anxious, the advice unit will provide specific advice such as "Let's start by writing a short story." The emotion estimation function analyzes the user's facial expressions and voice and calculates an emotion score. This allows the user to take action toward achieving their goals with peace of mind.

[0072] The future diary generation system can also be equipped with a reminder module that estimates the user's emotions and provides reminders to help them achieve their goals. For example, if a user inputs "I want to succeed in my diet," and the emotion estimation function determines that the user's motivation is declining, the reminder module will display a reminder such as "Don't forget to exercise today!" The emotion estimation function analyzes the user's facial expressions and voice and calculates an emotion score. This allows the user to continue taking action toward achieving their goals while maintaining positive emotions.

[0073] The future diary generation system can also be equipped with a reward unit that estimates the user's emotions and provides rewards for achieving goals. For example, if a user inputs "I want to pass the qualification exam" and the emotion estimation function evaluates the user's efforts, the reward unit will display a reward message such as "Give yourself a reward today!" The emotion estimation function analyzes the user's facial expressions and voice and calculates an emotion score. This allows the user to continue taking action toward achieving their goals while maintaining positive emotions.

[0074] The future diary generation system can also be equipped with a relaxation module that estimates the user's emotions and suggests relaxation methods to help them achieve their goals. For example, if a user inputs "I want to reduce stress" and the emotion estimation function determines that the user's stress level is high, the relaxation module will suggest relaxation methods such as "Take a deep breath and relax." The emotion estimation function analyzes the user's facial expressions and voice and calculates an emotion score. This allows the user to take action to achieve their goals in a relaxed state.

[0075] The processing flow of the second embodiment will be briefly explained below.

[0076] Step 1: The goal input unit inputs the user's goals and dreams. For example, the user inputs "I want to be a doctor." Step 2: The diary generation unit generates a future diary based on the goals and dreams entered by the goal input unit. For example, the generation AI might generate a diary entry such as, "In 2025, I have finally become a doctor. I see many patients every day and live a fulfilling life." Step 3: The communication unit enables communication between the user and their future self through the future diary created by the diary generation unit. For example, if the user asks, "How did you become a doctor?", the generation AI generates an answer to that question. Step 4: The ad insertion unit inserts corporate advertisements into the goal achievement process. For example, it displays advertisements for related companies in the form of "Click here for preparatory schools for entering medical school."

[0077] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0078] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0079] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0080] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0081] 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.

[0082] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0083] 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.

[0084] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0085] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0086] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0087] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0088] 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.

[0089] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0090] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0091] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0092] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0093] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0094] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0095] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0096] 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.

[0097] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0098] 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.

[0099] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0100] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0101] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0102] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0103] 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.

[0104] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0105] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0106] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0107] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0108] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0109] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0110] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0111] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0112] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0113] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0114] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0115] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0116] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0117] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0118] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0119] 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.

[0120] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0121] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0122] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0123] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0124] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0125] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0126] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0127] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0128] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0129] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0130] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0131] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0132] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0133] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0134] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0135] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0136] 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.

[0137] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0138] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0139] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0140] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0141] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0142] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0143] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0144] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a goal input section for inputting the user's goals and dreams; a diary creation unit that creates a future diary based on the goals and dreams input by the goal input unit; a communication unit that realizes communication between the user and his / her future self through the future diary created by the diary creation unit; and an advertisement insertion unit that inserts corporate advertisements into the goal achievement process. A system characterized by:

2. The goal input unit As users input their goals and dreams, the generative AI provides real-time feedback and advice to make their goals more specific and achievable.

2. The system of claim 1.

3. The diary creation unit Reflecting the user's past behavioral data and history, it generates a more realistic and specific future diary.

2. The system of claim 1.

4. The communication unit When the generative AI answers as its future self, it references the user's past question history to provide consistent answers.

2. The system of claim 1.

5. The advertisement insertion unit The goal-achievement process presented by the generative AI is reflected in the user's past purchase history and interests, allowing for highly relevant ads to be displayed.

2. The system of claim 1.

6. The goal input unit Analyzes emotions when users enter their goals and displays encouraging messages to elicit positive emotions.

2. The system of claim 1.

7. The diary creation unit Adjust the contents of future diary entries to evoke positive emotions in users.

2. The system of claim 1.

8. The communication unit Tailor the answers to questions the user asks their future self to evoke positive emotions in the user.

2. The system of claim 1.

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