System

Abstract

An object of a system according to an embodiment is to provide a family quest customized based on the preference or interest of a family member.SOLUTION: A system according to an embodiment includes a preference analysis unit, a fusion design unit, and a quest generation unit. The preference analysis unit analyzes the preferences, interests, and strengths of the family. The integration design unit designs the customized family quest in which the real world and the virtual world are integrated based on the preference, the interest, and the strength of the family analyzed by the preference analysis unit. The quest generation unit generates the family quest designed by the integration design unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Previous technology has had the problem that activities designed to strengthen family bonds are not sufficiently customized and do not address the preferences and interests of individual family members.

[0005] The system according to the embodiment aims to provide a customized family quest based on the preferences and interests of the family. [Means for solving the problem]

[0006] The system according to the embodiment includes a preference analysis unit, an integration design unit, and a quest generation unit. The preference analysis unit analyzes the preferences, interests, and strengths of family members. The integration design unit designs a customized family quest that integrates the real world and the virtual world based on the preferences, interests, and strengths of family members analyzed by the preference analysis unit. The quest generation unit generates the family quest designed by the integration design unit. [Effects of the Invention]

[0007] An embodiment of the system can provide customized family quests based on family preferences and interests. [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 nonvolatile storage devices that store various programs, various parameters, etc. Examples of nonvolatile 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 Family Quest AI system according to an embodiment of the present invention analyzes family preferences, interests, and strengths to create customized family quests that blend the real and virtual worlds, providing outlandish adventures that bring families together and deepen their bonds.

[0029] The family quest AI system according to the embodiment includes a preference analysis unit, an integration design unit, and a quest generation unit. The preference analysis unit analyzes the preferences, interests, and strengths of family members. For example, the preference analysis unit collects the favorite activities, hobbies, and skills of each family member and creates a profile based on the collected information. The preference analysis unit can also analyze the history of events and activities that family members have participated in to discover hidden interests and strengths. The preference analysis unit can also collect data from apps and devices that family members use daily and analyze their behavioral patterns. For example, it can analyze exercise habits based on data from fitness apps. The integration design unit designs a customized family quest that integrates the real world and the virtual world based on the preferences, interests, and strengths analyzed by the preference analysis unit. For example, the history and culture of places that the family actually visits can be reproduced in the virtual world to strengthen the connection between the real world and the virtual world. It is also possible to introduce a mechanism that links activities in the virtual world to rewards and benefits in the real world. Furthermore, an emotion estimation function can be used to analyze whether family members feel more positive emotions in the real world or the virtual world, providing an optimal experience. The quest generation unit generates family quests designed by the integration design unit. For example, the quest generation unit customizes the difficulty and theme based on data on puzzles and challenges that family members have previously solved. It can also design specialized challenges that utilize the specific skills and knowledge of family members. Furthermore, it can use an emotion estimation function to analyze the emotions family members feel during the challenge and make adjustments to elicit positive emotions. This allows the family quest AI system according to the embodiment to provide customized family quests based on the preferences, interests, and strengths of family members. For example, by enjoying solving puzzles together or cooperating through a treasure hunt, family members can gain a sense of accomplishment and a shared experience. Furthermore, by integrating the real world and the virtual world, family members can share new experiences and strengthen their bonds.

[0030] The preference analysis unit analyzes the history of events and activities that family members have participated in in the past, and can discover hidden interests and strengths. For example, the preference analysis unit collects the history of sporting events and cultural activities that family members have participated in in the past, and analyzes what types of activities they are interested in. For example, based on data on marathons and music festivals that they have participated in in the past, it identifies what types of events family members prefer. This makes it possible to discover hidden interests and strengths of family members.

[0031] The preference analysis unit can collect data from apps and devices that family members use on a daily basis and analyze their behavioral patterns. For example, the preference analysis unit collects data from fitness apps that family members use on a daily basis and analyzes their exercise habits and preferred exercise types. For example, it identifies the types of exercise that family members prefer based on the frequency and duration of running or yoga. This makes it possible to analyze family behavioral patterns.

[0032] The Fusion Design Department can recreate the history and culture of places that families actually visit in the virtual world, strengthening the connection between the real and virtual worlds. For example, the Fusion Design Department can recreate the history and culture of tourist destinations that families plan to visit in the virtual world and provide virtual tours before the visit. For example, virtual reality can be used to allow families to experience the historical background and culture of tourist destinations. This strengthens the connection between the real and virtual worlds.

[0033] The Fusion Design Department can introduce a system in which activities in the virtual world lead to rewards and benefits in the real world. For example, the Fusion Design Department can introduce a system in which users can earn discount coupons and benefits in the real world by completing quests and missions in the virtual world. For example, by completing a virtual quest, users can earn discount coupons that can be used at actual restaurants. This will connect activities in the virtual world to rewards and benefits in the real world.

[0034] The quest generation unit can customize the difficulty level and theme based on data of puzzles and challenges that family members have solved in the past. For example, the quest generation unit collects data on puzzles that family members have solved in the past and customizes the difficulty level and theme. For example, the quest generation unit designs new puzzles that family members can enjoy based on data on crossword puzzles and Sudoku puzzles that have been solved in the past. This allows the difficulty level and theme to be customized based on the family's past data.

[0035] The quest generation unit can design specialized challenges that utilize the specific skills and knowledge of family members. For example, the quest generation unit designs specialized challenges that utilize the specific skills and knowledge of family members. For example, the quest generation unit designs a cooking challenge that utilizes the cooking skills of family members. This makes it possible to design challenges that utilize the specific skills and knowledge of family members.

[0036] The quest generation unit can introduce puzzle-solving and treasure hunt scenarios based on different cultures and histories, and add educational elements. For example, the quest generation unit can design a puzzle-solving scenario based on different cultures and histories, and add educational elements. For example, a puzzle based on the theme of ancient Egyptian history can be designed, allowing families to have fun while learning about history. This makes it possible to provide scenarios that add educational elements based on different cultures and histories.

[0037] The quest generation unit can introduce a multiplayer mode in which family members compete against other family members in real time. The quest generation unit, for example, introduces a multiplayer mode in which family members compete against other family members in real time to add a competitive element. For example, an online puzzle-solving event can be held in which multiple family members participate simultaneously. This makes it possible to provide a multiplayer mode in which family members compete against other family members in real time.

[0038] The quest generation unit can design a special event that allows the family to share in the joy each time a stage of a quest is cleared. The quest generation unit designs a special event that allows the family to share in the joy each time a stage of a quest is cleared. For example, an online party that the family can enjoy together is held each time a stage is cleared. In this way, a special event that allows the family to share in the joy together can be designed.

[0039] The quest generation unit can record the achievements achieved by family members and create a digital album that can be looked back on later. The quest generation unit can, for example, record the achievements achieved by family members and create a digital album that can be looked back on later. For example, the quest generation unit can record the progress of quests and the achievements achieved with photos and videos. In this way, a digital album can be created that records the achievements achieved by family members and can be looked back on later.

[0040] The quest generation unit may implement a ranking system in which family members compete with other family members in real time to enhance the sense of accomplishment of a quest. For example, the quest generation unit may implement a ranking system in which family members compete with other family members in real time to enhance the sense of accomplishment of a quest. For example, a ranking may be displayed based on the progress or achievement of the quest, encouraging family members to work on the quest with a competitive spirit. This makes it possible to provide a ranking system in which family members compete with other family members in real time.

[0041] The quest generation unit can introduce a system in which family members can receive specific rewards or benefits depending on their progress in the quest. The quest generation unit introduces a system in which family members can receive specific rewards or benefits depending on their progress in the quest. For example, each time a quest stage is cleared, a special gift that the family can enjoy together is provided. This makes it possible to provide a system in which family members can receive rewards or benefits depending on their progress in the quest.

[0042] The quest generation unit can introduce a mechanism in which activities performed by family members in the virtual world affect events and activities in the real world. For example, the quest generation unit introduces a mechanism in which the progress of quests and missions in the virtual world is reflected in events and activities in the real world. For example, by completing a virtual quest, a special role can be assigned to an actual event. This makes it possible to provide a mechanism in which activities in the virtual world affect events and activities in the real world.

[0043] The quest generation unit can design a scenario in which a quest in the virtual world leads to a social contribution activity in the real world. For example, by completing a quest in the virtual world, the quest generation unit provides a reward that allows you to participate in volunteer activities in the real world. For example, by completing a virtual quest, you can earn a reward that allows you to participate in a local cleanup activity. This makes it possible to provide a scenario in which a quest in the virtual world leads to a social contribution activity in the real world.

[0044] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0045] The Family Quest AI system can also be equipped with a health management module. The health management module monitors the health status of family members and suggests quests to promote a healthy lifestyle. For example, it can design a walking challenge for the whole family to participate in, or a cooking quest to prepare healthy meals. The health management module can also provide exercise and dietary advice tailored to each member based on the family's health data. This allows the whole family to receive support in living a healthy lifestyle.

[0046] The Family Quest AI system can also be equipped with a learning support module. The learning support module analyzes the learning topics that family members are interested in and suggests educational quests. For example, it can design quests themed around science experiments or missions to learn about historical events. The learning support module can also provide complementary learning quests based on what family members are learning at school. This allows the whole family to learn while having fun.

[0047] The Family Quest AI system can further include an environmental protection module. The environmental protection module suggests quests for family members to participate in environmental protection activities. For example, it can design quests to participate in local cleanup activities or recycling campaigns. The environmental protection module can also provide advice for family members to take environmentally conscious actions in their daily lives. This allows the whole family to contribute to environmental protection.

[0048] The Family Quest AI system can also include a cultural exchange module, which suggests quests for family members to learn about and experience different cultures. For example, it can design a cooking quest to make foreign dishes or a mission to participate in a festival of a different culture. The cultural exchange module can also provide online events for family members to interact with people from different cultures, allowing all family members to understand and respect different cultures.

[0049] The Family Quest AI system can further include a creativity development module. The creativity development module suggests quests for family members to participate in creative activities. For example, it can design quests themed around art projects or missions for creating stories. The creativity development module can also provide support for family members to bring their ideas to life, allowing the whole family to express their creativity and have fun.

[0050] The processing flow of the first embodiment will be briefly explained below.

[0051] Step 1: The preference analysis unit analyzes the preferences, interests, and strengths of family members. For example, it collects each family member's favorite activities, hobbies, and skills and creates a profile based on that information. It can also analyze the history of events and activities that family members have participated in to discover hidden interests and strengths. It can also collect data from apps and devices that family members use on a daily basis to analyze behavioral patterns. For example, it can analyze exercise habits based on data from fitness apps. Step 2: The Integration Design Department designs a customized family quest that combines the real and virtual worlds based on the family's preferences, interests, and strengths analyzed by the Preference Analysis Department. For example, the history and culture of places the family visits can be recreated in the virtual world, strengthening the connection between the real and virtual worlds. It can also introduce a system where activities in the virtual world lead to rewards and benefits in the real world. Furthermore, the emotion estimation function can be used to analyze whether the family feels more positive emotions in the real or virtual world, providing the optimal experience. Step 3: The quest generation unit generates the family quest designed by the integration design unit. For example, the difficulty and theme can be customized based on data on puzzles and challenges that family members have previously solved. It can also design specialized challenges that utilize the specific skills and knowledge of family members. Furthermore, it can use emotion estimation to analyze the emotions family members feel during the challenge and make adjustments to elicit positive emotions.

[0052] (Example 2) The Family Quest AI system according to an embodiment of the present invention analyzes family preferences, interests, and strengths to create customized family quests that blend the real and virtual worlds, providing outlandish adventures that bring families together and deepen their bonds.

[0053] The family quest AI system according to the embodiment includes a preference analysis unit, an integration design unit, and a quest generation unit. The preference analysis unit analyzes the preferences, interests, and strengths of family members. For example, the preference analysis unit collects the favorite activities, hobbies, and skills of each family member and creates a profile based on the collected information. The preference analysis unit can also analyze the history of events and activities that family members have participated in to discover hidden interests and strengths. The preference analysis unit can also collect data from apps and devices that family members use daily and analyze their behavioral patterns. For example, it can analyze exercise habits based on data from fitness apps. The integration design unit designs a customized family quest that integrates the real world and the virtual world based on the preferences, interests, and strengths analyzed by the preference analysis unit. For example, the history and culture of places that the family actually visits can be reproduced in the virtual world to strengthen the connection between the real world and the virtual world. It is also possible to introduce a mechanism that links activities in the virtual world to rewards and benefits in the real world. Furthermore, an emotion estimation function can be used to analyze whether family members feel more positive emotions in the real world or the virtual world, providing an optimal experience. The quest generation unit generates family quests designed by the integration design unit. For example, the quest generation unit customizes the difficulty and theme based on data on puzzles and challenges that family members have previously solved. It can also design specialized challenges that utilize the specific skills and knowledge of family members. Furthermore, it can use an emotion estimation function to analyze the emotions family members feel during the challenge and make adjustments to elicit positive emotions. This allows the family quest AI system according to the embodiment to provide customized family quests based on the preferences, interests, and strengths of family members. For example, by enjoying solving puzzles together or cooperating through a treasure hunt, family members can gain a sense of accomplishment and a shared experience. Furthermore, by integrating the real world and the virtual world, family members can share new experiences and strengthen their bonds.

[0054] The preference analysis unit analyzes the history of events and activities that family members have participated in in the past, and can discover hidden interests and strengths. For example, the preference analysis unit collects the history of sporting events and cultural activities that family members have participated in in the past, and analyzes what types of activities they are interested in. For example, based on data on marathons and music festivals that they have participated in in the past, it identifies what types of events family members prefer. This makes it possible to discover hidden interests and strengths of family members.

[0055] The preference analysis unit can collect data from apps and devices that family members use on a daily basis and analyze their behavioral patterns. For example, the preference analysis unit collects data from fitness apps that family members use on a daily basis and analyzes their exercise habits and preferred exercise types. For example, it identifies the types of exercise that family members prefer based on the frequency and duration of running or yoga. This makes it possible to analyze family behavioral patterns.

[0056] The preference analysis unit uses the emotion estimation function to analyze how family members feel about specific activities and can suggest activities that elicit positive emotions. For example, the preference analysis unit collects emotional data from events and activities that family members have participated in in the past and identifies activities that elicit positive emotions. For example, it analyzes smiling and excited facial expressions and suggests activities that family members enjoyed. This makes it possible to suggest activities that elicit positive emotions for the family.

[0057] The Fusion Design Department can recreate the history and culture of places that families actually visit in the virtual world, strengthening the connection between the real and virtual worlds. For example, the Fusion Design Department can recreate the history and culture of tourist destinations that families plan to visit in the virtual world and provide virtual tours before the visit. For example, virtual reality can be used to allow families to experience the historical background and culture of tourist destinations. This strengthens the connection between the real and virtual worlds.

[0058] The Fusion Design Department can introduce a system in which activities in the virtual world lead to rewards and benefits in the real world. For example, the Fusion Design Department can introduce a system in which users can earn discount coupons and benefits in the real world by completing quests and missions in the virtual world. For example, by completing a virtual quest, users can earn discount coupons that can be used at actual restaurants. This will connect activities in the virtual world to rewards and benefits in the real world.

[0059] The fusion design unit uses its emotion estimation function to analyze whether family members feel more positive emotions in the real world or the virtual world, and can provide the optimal experience. For example, the fusion design unit can analyze in real time the emotions felt by family members during activities in the real world and the virtual world, and provide an experience that elicits positive emotions. For example, it can identify activities that family members enjoy and enhance those activities. This can provide an experience that evokes more positive emotions in family members.

[0060] The quest generation unit can customize the difficulty level and theme based on data of puzzles and challenges that family members have solved in the past. For example, the quest generation unit collects data on puzzles that family members have solved in the past and customizes the difficulty level and theme. For example, the quest generation unit designs new puzzles that family members can enjoy based on data on crossword puzzles and Sudoku puzzles that have been solved in the past. This allows the difficulty level and theme to be customized based on the family's past data.

[0061] The quest generation unit can design specialized challenges that utilize the specific skills and knowledge of family members. For example, the quest generation unit designs specialized challenges that utilize the specific skills and knowledge of family members. For example, the quest generation unit designs a cooking challenge that utilizes the cooking skills of family members. This makes it possible to design challenges that utilize the specific skills and knowledge of family members.

[0062] The quest generation unit can use the emotion estimation function to analyze what emotions family members are feeling during the challenge and make adjustments to bring out positive emotions. For example, the quest generation unit can monitor the emotions of family members in real time during the challenge and make adjustments to bring out positive emotions. For example, the quest generation unit can strengthen challenges that the family members enjoy and reduce challenges that cause stress. In this way, adjustments can be made to bring out positive emotions in the family.

[0063] The quest generation unit can introduce puzzle-solving and treasure hunt scenarios based on different cultures and histories, and add educational elements. For example, the quest generation unit can design a puzzle-solving scenario based on different cultures and histories, and add educational elements. For example, a puzzle based on the theme of ancient Egyptian history can be designed, allowing families to have fun while learning about history. This makes it possible to provide scenarios that add educational elements based on different cultures and histories.

[0064] The quest generation unit can introduce a multiplayer mode in which family members compete against other family members in real time. The quest generation unit, for example, introduces a multiplayer mode in which family members compete against other family members in real time to add a competitive element. For example, an online puzzle-solving event can be held in which multiple family members participate simultaneously. This makes it possible to provide a multiplayer mode in which family members compete against other family members in real time.

[0065] The quest generation unit can use the emotion estimation function to monitor in real time what emotions family members are feeling during the challenge and make adjustments to bring out positive emotions. For example, the quest generation unit can monitor in real time the emotions of family members during the challenge and make adjustments to bring out positive emotions. For example, the quest generation unit can strengthen challenges that the family members enjoy and reduce challenges that cause stress. In this way, adjustments can be made to bring out positive emotions in the family.

[0066] The quest generation unit can design a special event that allows the family to share in the joy each time a stage of a quest is cleared. The quest generation unit designs a special event that allows the family to share in the joy each time a stage of a quest is cleared. For example, an online party that the family can enjoy together is held each time a stage is cleared. In this way, a special event that allows the family to share in the joy together can be designed.

[0067] The quest generation unit can record the achievements achieved by family members and create a digital album that can be looked back on later. The quest generation unit can, for example, record the achievements achieved by family members and create a digital album that can be looked back on later. For example, the quest generation unit can record the progress of quests and the achievements achieved with photos and videos. In this way, a digital album can be created that records the achievements achieved by family members and can be looked back on later.

[0068] The quest generation unit can use the emotion estimation function to analyze what emotions family members are feeling through the quest and provide feedback that elicits positive emotions. For example, the quest generation unit can monitor the emotions of family members in real time during the quest and provide feedback to elicit positive emotions. For example, the quest generation unit can reinforce activities that the family members enjoy and reduce activities that cause stress. This makes it possible to provide feedback that elicits positive emotions in the family.

[0069] The quest generation unit may implement a ranking system in which family members compete with other family members in real time to enhance the sense of accomplishment of a quest. For example, the quest generation unit may implement a ranking system in which family members compete with other family members in real time to enhance the sense of accomplishment of a quest. For example, a ranking may be displayed based on the progress or achievement of the quest, encouraging family members to work on the quest with a competitive spirit. This makes it possible to provide a ranking system in which family members compete with other family members in real time.

[0070] The quest generation unit can introduce a system in which family members can receive specific rewards or benefits depending on their progress in the quest. The quest generation unit introduces a system in which family members can receive specific rewards or benefits depending on their progress in the quest. For example, each time a quest stage is cleared, a special gift that the family can enjoy together is provided. This makes it possible to provide a system in which family members can receive rewards or benefits depending on their progress in the quest.

[0071] The quest generation unit can use the emotion estimation function to monitor in real time what emotions family members are feeling through the quest and make adjustments to bring out positive emotions. For example, the quest generation unit can monitor in real time the emotions of family members during the quest and make adjustments to bring out positive emotions. For example, the quest generation unit can strengthen activities that the family members enjoy and reduce activities that cause stress. In this way, adjustments can be made to bring out positive emotions in the family.

[0072] The quest generation unit can introduce a mechanism in which activities performed by family members in the virtual world affect events and activities in the real world. For example, the quest generation unit introduces a mechanism in which the progress of quests and missions in the virtual world is reflected in events and activities in the real world. For example, by completing a virtual quest, a special role can be assigned to an actual event. This makes it possible to provide a mechanism in which activities in the virtual world affect events and activities in the real world.

[0073] The quest generation unit can design a scenario in which a quest in the virtual world leads to a social contribution activity in the real world. For example, by completing a quest in the virtual world, the quest generation unit provides a reward that allows you to participate in volunteer activities in the real world. For example, by completing a virtual quest, you can earn a reward that allows you to participate in a local cleanup activity. This makes it possible to provide a scenario in which a quest in the virtual world leads to a social contribution activity in the real world.

[0074] The quest generation unit can use the emotion estimation function to monitor in real time what emotions family members are feeling while they are engaged in activities in the virtual world and make adjustments to bring out positive emotions. For example, the quest generation unit can monitor in real time the emotions of family members while they are engaged in activities in the virtual world and make adjustments to bring out positive emotions. For example, the quest generation unit can strengthen activities that the family enjoys and reduce activities that cause stress. In this way, adjustments can be made to bring out positive emotions in the family.

[0075] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0076] The Family Quest AI system can also be equipped with a health management module. The health management module monitors the health status of family members and suggests quests to promote a healthy lifestyle. For example, it can design a walking challenge for the whole family to participate in, or a cooking quest to prepare healthy meals. The health management module can also provide exercise and dietary advice tailored to each member based on the family's health data. This allows the whole family to receive support in living a healthy lifestyle.

[0077] The Family Quest AI system can also be equipped with a learning support module. The learning support module analyzes the learning topics that family members are interested in and suggests educational quests. For example, it can design quests themed around science experiments or missions to learn about historical events. The learning support module can also provide complementary learning quests based on what family members are learning at school. This allows the whole family to learn while having fun.

[0078] The Family Quest AI system can further include an environmental protection module. The environmental protection module suggests quests for family members to participate in environmental protection activities. For example, it can design quests to participate in local cleanup activities or recycling campaigns. The environmental protection module can also provide advice for family members to take environmentally conscious actions in their daily lives. This allows the whole family to contribute to environmental protection.

[0079] The Family Quest AI system can also include a cultural exchange module, which suggests quests for family members to learn about and experience different cultures. For example, it can design a cooking quest to make foreign dishes or a mission to participate in a festival of a different culture. The cultural exchange module can also provide online events for family members to interact with people from different cultures, allowing all family members to understand and respect different cultures.

[0080] The Family Quest AI system can further include a creativity development module. The creativity development module suggests quests for family members to participate in creative activities. For example, it can design quests themed around art projects or missions for creating stories. The creativity development module can also provide support for family members to bring their ideas to life, allowing the whole family to express their creativity and have fun.

[0081] The Family Quest AI system also uses emotion estimation to monitor whether family members are feeling stressed and suggest relaxation quests. For example, it can suggest a yoga session or a walk in nature that will help the whole family relax. It can also use emotion estimation to provide relaxing music and videos for family members, helping everyone in the family reduce stress and relax.

[0082] The Family Quest AI system can also use emotion estimation to identify activities that family members enjoy and suggest quests that enhance those activities. For example, it can design new challenges based on the sports and games that family members enjoy. It can also use emotion estimation to identify the time of day and place where family members are having fun and provide the most appropriate quests based on that information. This allows it to suggest activities that are more enjoyable for the whole family.

[0083] The Family Quest AI system also uses emotion estimation to monitor whether family members are feeling anxious and suggest quests that provide comfort. For example, it could suggest a relaxing meditation session for the whole family or reassuring storytelling. It can also use emotion estimation to identify environments in which family members feel safe and suggest the most appropriate quests based on that information, helping the whole family feel safe.

[0084] The Family Quest AI system also uses emotion estimation to monitor whether family members feel a sense of accomplishment and suggest quests that enhance that sense of accomplishment. For example, it can design projects that give the whole family a sense of accomplishment, or challenges that give each member a sense of accomplishment. It can also use emotion estimation to identify activities that give family members a sense of accomplishment and suggest the most appropriate quests based on that information, allowing everyone in the family to feel a sense of accomplishment.

[0085] The Family Quest AI system also uses its emotion estimation function to monitor whether family members are feeling happy and suggest quests that will increase their happiness. For example, it can design events that allow the whole family to share a sense of happiness, or activities that make each member feel happy. It can also use emotion estimation to identify moments when family members feel happy and provide optimal quests based on that information, allowing the whole family to feel happy.

[0086] The processing flow of the second embodiment will be briefly explained below.

[0087] Step 1: The preference analysis unit analyzes the preferences, interests, and strengths of family members. For example, it collects each family member's favorite activities, hobbies, and skills and creates a profile based on that information. It can also analyze the history of events and activities that family members have participated in to discover hidden interests and strengths. It can also collect data from apps and devices that family members use on a daily basis to analyze behavioral patterns. For example, it can analyze exercise habits based on data from fitness apps. Step 2: The Integration Design Department designs a customized family quest that combines the real and virtual worlds based on the family's preferences, interests, and strengths analyzed by the Preference Analysis Department. For example, the history and culture of places the family visits can be recreated in the virtual world, strengthening the connection between the real and virtual worlds. It can also introduce a system where activities in the virtual world lead to rewards and benefits in the real world. Furthermore, the emotion estimation function can be used to analyze whether the family feels more positive emotions in the real or virtual world, providing the optimal experience. Step 3: The quest generation unit generates the family quest designed by the integration design unit. For example, the difficulty and theme can be customized based on data on puzzles and challenges that family members have previously solved. It can also design specialized challenges that utilize the specific skills and knowledge of family members. Furthermore, it can use emotion estimation to analyze the emotions family members feel during the challenge and make adjustments to elicit positive emotions.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0092] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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).

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0107] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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).

[0112] 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.

[0113] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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).

[0141] 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.

[0142] 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."

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] The hardware resource for executing a specific process can be any of the following processors: A CPU is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A dedicated electrical circuit, such as a field-programmable gate array (FPGA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC), is a processor with a circuit configuration specifically designed to execute a specific process. Each processor has built-in or connected memory, and uses the memory to execute the specific process.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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]

[0155] 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 preference analysis section that analyzes family preferences, interests, and strengths; a fusion design unit that designs a customized family quest that fuses the real world and the virtual world based on the preferences, interests, and strengths of the family analyzed by the preference analysis unit; a quest generation unit that generates the family quest designed by the integrated design unit. A system characterized by:

2. The preference analysis unit Analyzing the history of events and activities that the family members have participated in in the past to discover their hidden interests and strengths 2. The system of claim 1.

3. The fusion design unit Recreate the history and culture of the places the family actually visits in the virtual world, strengthening the connection between the real and virtual worlds.

2. The system of claim 1.

4. The quest generation unit Customize the difficulty and theme based on the puzzles and challenges the family member has previously solved 2. The system of claim 1.

5. The preference analysis unit Using emotion estimation, analyze how the family members feel about specific activities and suggest activities that elicit positive emotions.

2. The system of claim 1.

6. The fusion design unit Using emotion estimation, the system analyzes whether the family member feels more positive emotions in the real world or the virtual world, providing an optimal experience.

2. The system of claim 1.

7. The quest generation unit Using the emotion estimation function, the system analyzes the emotions the family members are feeling during the challenge and makes adjustments to bring out positive emotions.

2. The system of claim 1.

8. The quest generation unit Using emotion estimation, the system analyzes the emotions the family members feel during the quest and provides feedback that elicits positive emotions.

2. The system of claim 1.

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