System

Abstract

A system according to an embodiment aims to improve the entertainment experience in aquariums.SOLUTION: A system according to an embodiment includes a photographing unit, an upload unit, and a challenge participation unit. The photographing unit takes a photograph of an exhibit or an organism. The upload unit uploads the photograph taken by the photograph taking unit through a dedicated application. The challenge participation unit may participate in a challenge or a game using the photo uploaded by the upload 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] Conventional technology has limited the entertainment experience available within aquariums, and there has been a lack of ingenuity to sustain visitor interest.

[0005] The system according to the embodiment aims to improve the entertainment experience in the aquarium. [Means for solving the problem]

[0006] The system according to the embodiment includes a photography unit, an upload unit, and a challenge participation unit. The photography unit takes photos of exhibits and living creatures. The upload unit uploads the photos taken by the photography unit through a dedicated application. The challenge participation unit participates in challenges and games using the photos uploaded by the upload unit. [Effects of the Invention]

[0007] Systems according to embodiments can enhance the entertainment experience within aquariums. [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 entertainment system according to the embodiment of the present invention allows users to participate in various challenges and games using photos taken at the aquarium, thereby enabling users to enjoy their experience at the aquarium even more.

[0029] The entertainment system according to the embodiment includes a photography unit, an upload unit, and a challenge participation unit. The photography unit takes photos of exhibits and creatures. For example, a user can use a smartphone to take photos of a dolphin show, a jellyfish exhibit, a shark tank, and the like. The upload unit uploads the photos taken by the photography unit through a dedicated application. For example, the user can upload the photos to the application and store them on a cloud server. The upload unit can also analyze the metadata of the photos and automatically record the location and date of the photo. The challenge participation unit uses the photos uploaded by the upload unit to participate in challenges and games. For example, the user can participate in a mission to photograph a specific creature, a puzzle game using the photos, or a quiz using the photos. This allows the entertainment system to enhance the user's experience at the aquarium. For example, the user can earn points using the photos they take and exchange them for specific rewards. The user can also share the photos they take and the points they earn on social media. This allows the user to compete with other users or cooperate with them to complete challenges.

[0030] The photography unit can take pictures of the dolphin show, the jellyfish exhibit, and the shark tank. For example, the photography unit allows a user to take pictures of the dolphin show using a smartphone. The photography unit can also take pictures of the jellyfish exhibit. Furthermore, the photography unit can also take pictures of the shark tank. This allows the user to take pictures of specific exhibits and creatures, enriching the experience.

[0031] The challenge participant can participate in a mission to photograph a specific creature, a puzzle game using a photo, or a quiz using a photo. The challenge participant can, for example, participate in a mission to photograph a specific creature. For example, a user can complete the mission by taking a photo of a dolphin and uploading the photo. The challenge participant can also participate in a puzzle game using a photo. For example, a user can complete a jigsaw puzzle using a photo of a jellyfish that they have taken. Furthermore, the challenge participant can also participate in a quiz using a photo. For example, a user can answer a quiz about sharks based on a photo of a shark that they have taken. This allows users to participate in various challenges and games, making the experience more enjoyable.

[0032] The uploading unit can apply art filters to photos in real time using generative AI, allowing users to create their own unique works of art. For example, the uploading unit can apply art filters to photos taken by a user inside an aquarium in real time using generative AI. For example, a user can apply a watercolor-style filter to a photo of a jellyfish to create a unique work of art. The uploading unit can also apply an oil-painting-style filter to a photo of a dolphin taken by a user. Furthermore, the uploading unit can apply a pop art-style filter to a photo of a shark. This allows users to enjoy the photos they have taken as works of art.

[0033] The uploading unit may cause the generation AI to automatically generate a 3D model of a living creature based on a photo, allowing the user to observe the creature in augmented reality (AR). For example, the uploading unit may cause the generation AI to automatically generate a 3D model based on a photo of a jellyfish taken by the user, allowing the user to observe the jellyfish in 360 degrees through the AR function. This allows the user to learn the detailed structure of the jellyfish. The uploading unit may also cause the generation AI to automatically generate a 3D model of a dolphin based on a photo of a dolphin taken by the user, allowing the user to observe the dolphin through the AR function. The uploading unit may also cause the generation AI to automatically generate a 3D model of a shark based on a photo of a shark taken by the user, allowing the user to observe the shark through the AR function. This allows the user to observe the creatures photographed in AR.

[0034] The uploading unit can use a photo to enable the generation AI to automatically generate animations that reproduce the sounds and movements of living creatures. For example, the uploading unit can use a photo of a dolphin taken by a user to enable the generation AI to generate animations that reproduce the sounds and movements of a dolphin. This allows users to experience the ecology of dolphins more realistically. The uploading unit can also use a photo of a jellyfish taken by a user to enable the generation AI to generate animations that reproduce the movements of a jellyfish. Furthermore, the uploading unit can use a photo of a shark taken by a user to enable the generation AI to generate animations that reproduce the movements of a shark. This allows users to enjoy animations that reproduce the sounds and movements of living creatures they have photographed.

[0035] The uploading unit can use the photos to enable the generation AI to automatically generate an audio guide that explains the ecology and characteristics of living creatures. For example, the uploading unit can use the generation AI to generate an audio guide that explains the ecology and characteristics of jellyfish based on a photo of a jellyfish taken by a user. This allows users to deepen their knowledge about jellyfish. The uploading unit can also use the generation AI to generate an audio guide that explains the ecology and characteristics of dolphins based on a photo of a dolphin taken by a user. Furthermore, the uploading unit can also use the generation AI to generate an audio guide that explains the ecology and characteristics of sharks based on a photo of a shark taken by a user. This allows users to learn about the ecology and characteristics of the living creatures they have photographed.

[0036] The challenge participation unit can have the generation AI automatically generate quizzes about living things using photos, allowing users to take the quizzes. For example, the challenge participation unit can have the generation AI automatically generate quizzes about jellyfish based on photos of jellyfish taken by the user. This allows users to answer questions about the ecology and characteristics of jellyfish. The challenge participation unit can also have the generation AI automatically generate quizzes about dolphins based on photos of dolphins taken by the user. Furthermore, the challenge participation unit can have the generation AI automatically generate quizzes about sharks based on photos of sharks taken by the user. This allows users to deepen their knowledge by taking quizzes about living things they have photographed.

[0037] The challenge participation unit can generate a simulation game in which the generation AI automatically recreates the ecosystem of living creatures using photographs. For example, the challenge participation unit can generate a simulation game in which the generation AI recreates the ecosystem of jellyfish based on a photograph of a jellyfish taken by a user. This allows users to have fun while learning about the ecosystem of jellyfish. The challenge participation unit can also generate a simulation game in which the generation AI recreates the ecosystem of dolphins based on a photograph of a dolphin taken by a user. Furthermore, the challenge participation unit can generate a simulation game in which the generation AI recreates the ecosystem of sharks based on a photograph of a shark taken by a user. This allows users to have fun while learning about the ecosystem of the living creatures photographed.

[0038] The challenge participation unit can generate an educational game in which the generation AI automatically recreates the evolutionary process of living organisms using photographs. For example, the challenge participation unit can generate an educational game in which the generation AI recreates the evolutionary process of jellyfish based on a photograph of a jellyfish taken by a user. This allows users to have fun while learning about the evolution of jellyfish. The challenge participation unit can also generate an educational game in which the generation AI recreates the evolutionary process of dolphins based on a photograph of a dolphin taken by a user. Furthermore, the challenge participation unit can also generate an educational game in which the generation AI recreates the evolutionary process of sharks based on a photograph of a shark taken by a user. This allows users to have fun while learning about the evolutionary process of the organisms they photographed.

[0039] The challenge participation unit can use the photos to generate a virtual tour in which the generation AI automatically recreates the habitat of a living creature. For example, the challenge participation unit can generate a virtual tour in which the generation AI recreates a jellyfish habitat based on a photo of a jellyfish taken by a user. This allows the user to virtually experience the jellyfish habitat. The challenge participation unit can also generate a virtual tour in which the generation AI recreates a dolphin habitat based on a photo of a dolphin taken by a user. Furthermore, the challenge participation unit can also generate a virtual tour in which the generation AI recreates a shark habitat based on a photo of a shark taken by a user. This allows the user to virtually experience the habitat of the living creature photographed.

[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 entertainment system may further include a behavior analysis unit that tracks user behavior. The behavior analysis unit may analyze which exhibits a user viewed in an aquarium and for how long. For example, if a user viewed a dolphin show for a long time, the behavior analysis unit may provide additional information or quizzes about dolphins based on that information. If a user shows interest in a particular exhibit, the behavior analysis unit may recommend other exhibits or activities related to that exhibit. Furthermore, the behavior analysis unit may generate personalized content based on user behavior data to provide an optimal experience for each individual user. This may provide a more fulfilling experience based on the user's interests and behavior.

[0042] The entertainment system may further include a health management unit that monitors the user's health. The health management unit may monitor the user's heart rate and number of steps while the user is active in the aquarium and prompt the user to take a break at an appropriate time. For example, if the user's heart rate becomes high, the health management unit may notify the user to take a break. The health management unit may also provide a specific reward when the user achieves a certain number of steps. Furthermore, the health management unit may recommend healthy activities based on the user's health data. This allows the user to enjoy the aquarium in a healthy manner.

[0043] The entertainment system may further include an interest analysis unit that analyzes the user's interests and recommends specific exhibits based on the interests. The interest analysis unit can analyze the interests the user shows during their experience at the aquarium and recommend exhibits that match those interests. For example, if the user shows an interest in jellyfish, it can recommend other jellyfish-related exhibits. If the user shows an interest in dolphins, the interest analysis unit can also recommend dolphin-related exhibits and activities. If the user shows an interest in sharks, it can also recommend shark-related exhibits. This allows specific exhibits to be recommended based on the user's interests, providing a more fulfilling experience.

[0044] The entertainment system may further include an action suggestion unit that analyzes the user's behavior and suggests a specific activity based on the behavior. The action suggestion unit may analyze the behavior exhibited by the user during their experience in the aquarium and suggest an activity that matches that behavior. For example, if the user has been walking for a long time, the action suggestion unit may suggest that the user take a break. Furthermore, if the user has been staying at a particular exhibit for a long time, the action suggestion unit may suggest an activity related to that exhibit. Furthermore, if the user frequently visits a particular area, the action suggestion unit may suggest an activity related to that area. This makes it possible to suggest specific activities based on the user's behavior and provide a more fulfilling experience.

[0045] The entertainment system may further include a health suggestion unit that analyzes the user's health condition and suggests a specific activity based on the health condition. The health suggestion unit may analyze the health condition the user exhibits during their experience at the aquarium and suggest an activity that suits the user's health condition. For example, if the user's heart rate is high, a relaxing activity may be suggested. The health suggestion unit may also suggest an active activity if the user has achieved a certain number of steps. Furthermore, the health suggestion unit may suggest that the user take a break if the user is tired. This allows the system to suggest a specific activity based on the user's health condition, providing a healthier experience.

[0046] The entertainment system may further include an information providing unit that analyzes the user's interests and provides specific information based on the interests. The information providing unit may analyze the interests the user has shown during their experience at the aquarium and provide information that matches the interests. For example, if the user is interested in jellyfish, the information providing unit may provide detailed information about jellyfish. If the user is interested in dolphins, the information providing unit may provide information and stories about dolphins. If the user is interested in sharks, the information providing unit may provide information about sharks. This may provide specific information based on the user's interests, providing a more fulfilling experience.

[0047] The processing flow of the first embodiment will be briefly explained below.

[0048] Step 1: The photography unit takes photos of exhibits and creatures. For example, a user can use a smartphone to take photos of a dolphin show, a jellyfish exhibit, or a shark tank. Step 2: The uploading unit uploads the photos taken by the photography unit through a dedicated application. For example, a user can upload the photos they have taken to the application and store them on a cloud server. The uploading unit can also analyze the metadata of the photos and automatically record the location and date of the photo. Step 3: The challenge participation unit uses the photos uploaded by the upload unit to participate in challenges and games. For example, users can participate in missions to photograph specific creatures, puzzle games using the photos they have taken, or quizzes using photos. This allows users to earn points using the photos they have taken and exchange them for specific rewards. Users can also share the photos they have taken and the points they have earned on social media.

[0049] (Example 2) The entertainment system according to the embodiment of the present invention allows users to participate in various challenges and games using photos taken at the aquarium, thereby enabling users to enjoy their experience at the aquarium even more.

[0050] The entertainment system according to the embodiment includes a photography unit, an upload unit, and a challenge participation unit. The photography unit takes photos of exhibits and creatures. For example, a user can use a smartphone to take photos of a dolphin show, a jellyfish exhibit, a shark tank, and the like. The upload unit uploads the photos taken by the photography unit through a dedicated application. For example, the user can upload the photos to the application and store them on a cloud server. The upload unit can also analyze the metadata of the photos and automatically record the location and date of the photo. The challenge participation unit uses the photos uploaded by the upload unit to participate in challenges and games. For example, the user can participate in a mission to photograph a specific creature, a puzzle game using the photos, or a quiz using the photos. This allows the entertainment system to enhance the user's experience at the aquarium. For example, the user can earn points using the photos they take and exchange them for specific rewards. The user can also share the photos they take and the points they earn on social media. This allows the user to compete with other users or cooperate with them to complete challenges.

[0051] The photography unit can take pictures of the dolphin show, the jellyfish exhibit, and the shark tank. For example, the photography unit allows a user to take pictures of the dolphin show using a smartphone. The photography unit can also take pictures of the jellyfish exhibit. Furthermore, the photography unit can also take pictures of the shark tank. This allows the user to take pictures of specific exhibits and creatures, enriching the experience.

[0052] The challenge participant can participate in a mission to photograph a specific creature, a puzzle game using a photo, or a quiz using a photo. The challenge participant can, for example, participate in a mission to photograph a specific creature. For example, a user can complete the mission by taking a photo of a dolphin and uploading the photo. The challenge participant can also participate in a puzzle game using a photo. For example, a user can complete a jigsaw puzzle using a photo of a jellyfish that they have taken. Furthermore, the challenge participant can also participate in a quiz using a photo. For example, a user can answer a quiz about sharks based on a photo of a shark that they have taken. This allows users to participate in various challenges and games, making the experience more enjoyable.

[0053] The uploading unit can apply art filters to photos in real time using generative AI, allowing users to create their own unique works of art. For example, the uploading unit can apply art filters to photos taken by a user inside an aquarium in real time using generative AI. For example, a user can apply a watercolor-style filter to a photo of a jellyfish to create a unique work of art. The uploading unit can also apply an oil-painting-style filter to a photo of a dolphin taken by a user. Furthermore, the uploading unit can apply a pop art-style filter to a photo of a shark. This allows users to enjoy the photos they have taken as works of art.

[0054] The uploading unit may cause the generation AI to automatically generate a 3D model of a living creature based on a photo, allowing the user to observe the creature in augmented reality (AR). For example, the uploading unit may cause the generation AI to automatically generate a 3D model based on a photo of a jellyfish taken by the user, allowing the user to observe the jellyfish in 360 degrees through the AR function. This allows the user to learn the detailed structure of the jellyfish. The uploading unit may also cause the generation AI to automatically generate a 3D model of a dolphin based on a photo of a dolphin taken by the user, allowing the user to observe the dolphin through the AR function. The uploading unit may also cause the generation AI to automatically generate a 3D model of a shark based on a photo of a shark taken by the user, allowing the user to observe the shark through the AR function. This allows the user to observe the creatures photographed in AR.

[0055] The uploading unit can use the emotion estimation function to analyze the emotion felt by the user when taking a photo and automatically apply specific effects and filters based on the emotion. For example, the uploading unit can use the emotion estimation function to analyze the emotion felt by the user when taking a photo, and apply a bright effect if a positive emotion is detected. For example, if the emotion of joy is strong, a bright filter can be applied to the photo. Furthermore, the uploading unit can apply a calming effect if the emotion estimation function is used to detect a negative emotion in the photo taken by the user. For example, if the emotion of sadness is strong, a monochrome filter can be applied to the photo. Furthermore, the uploading unit can apply a vivid effect if the emotion estimation function is used to detect a surprise emotion in the photo taken by the user. For example, if the emotion of surprise is strong, a vivid filter can be applied to the photo. In this way, effects and filters can be applied to photos based on the user's emotions.

[0056] The uploading unit can use a photo to enable the generation AI to automatically generate animations that reproduce the sounds and movements of living creatures. For example, the uploading unit can use a photo of a dolphin taken by a user to enable the generation AI to generate animations that reproduce the sounds and movements of a dolphin. This allows users to experience the ecology of dolphins more realistically. The uploading unit can also use a photo of a jellyfish taken by a user to enable the generation AI to generate animations that reproduce the movements of a jellyfish. Furthermore, the uploading unit can use a photo of a shark taken by a user to enable the generation AI to generate animations that reproduce the movements of a shark. This allows users to enjoy animations that reproduce the sounds and movements of living creatures they have photographed.

[0057] The uploading unit can use the photos to enable the generation AI to automatically generate an audio guide that explains the ecology and characteristics of living creatures. For example, the uploading unit can use the generation AI to generate an audio guide that explains the ecology and characteristics of jellyfish based on a photo of a jellyfish taken by a user. This allows users to deepen their knowledge about jellyfish. The uploading unit can also use the generation AI to generate an audio guide that explains the ecology and characteristics of dolphins based on a photo of a dolphin taken by a user. Furthermore, the uploading unit can also use the generation AI to generate an audio guide that explains the ecology and characteristics of sharks based on a photo of a shark taken by a user. This allows users to learn about the ecology and characteristics of the living creatures they have photographed.

[0058] The uploading unit can use the emotion estimation function to display other users' emotional reactions to photos taken by the user in real time, thereby promoting empathy. The uploading unit can, for example, build a system that displays other users' emotional reactions to photos taken by the user in real time. For example, a heart mark or a smiley face icon can be displayed for photos with many positive emotional reactions. The uploading unit can also display a sad icon for photos with many negative emotional reactions to the user's photos. Furthermore, the uploading unit can display a surprise icon for photos with many surprised emotional reactions to the user's photos. This allows the user to check other users' emotional reactions in real time, promoting empathy.

[0059] The challenge participation unit can have the generation AI automatically generate quizzes about living things using photos, allowing users to take the quizzes. For example, the challenge participation unit can have the generation AI automatically generate quizzes about jellyfish based on photos of jellyfish taken by the user. This allows users to answer questions about the ecology and characteristics of jellyfish. The challenge participation unit can also have the generation AI automatically generate quizzes about dolphins based on photos of dolphins taken by the user. Furthermore, the challenge participation unit can have the generation AI automatically generate quizzes about sharks based on photos of sharks taken by the user. This allows users to deepen their knowledge by taking quizzes about living things they have photographed.

[0060] The challenge participation unit can generate a simulation game in which the generation AI automatically recreates the ecosystem of living creatures using photographs. For example, the challenge participation unit can generate a simulation game in which the generation AI recreates the ecosystem of jellyfish based on a photograph of a jellyfish taken by a user. This allows users to have fun while learning about the ecosystem of jellyfish. The challenge participation unit can also generate a simulation game in which the generation AI recreates the ecosystem of dolphins based on a photograph of a dolphin taken by a user. Furthermore, the challenge participation unit can generate a simulation game in which the generation AI recreates the ecosystem of sharks based on a photograph of a shark taken by a user. This allows users to have fun while learning about the ecosystem of the living creatures photographed.

[0061] The challenge participation unit can generate an educational game in which the generation AI automatically recreates the evolutionary process of living organisms using photographs. For example, the challenge participation unit can generate an educational game in which the generation AI recreates the evolutionary process of jellyfish based on a photograph of a jellyfish taken by a user. This allows users to have fun while learning about the evolution of jellyfish. The challenge participation unit can also generate an educational game in which the generation AI recreates the evolutionary process of dolphins based on a photograph of a dolphin taken by a user. Furthermore, the challenge participation unit can also generate an educational game in which the generation AI recreates the evolutionary process of sharks based on a photograph of a shark taken by a user. This allows users to have fun while learning about the evolutionary process of the organisms they photographed.

[0062] The challenge participation unit can use the photos to generate a virtual tour in which the generation AI automatically recreates the habitat of a living creature. For example, the challenge participation unit can generate a virtual tour in which the generation AI recreates a jellyfish habitat based on a photo of a jellyfish taken by a user. This allows the user to virtually experience the jellyfish habitat. The challenge participation unit can also generate a virtual tour in which the generation AI recreates a dolphin habitat based on a photo of a dolphin taken by a user. Furthermore, the challenge participation unit can also generate a virtual tour in which the generation AI recreates a shark habitat based on a photo of a shark taken by a user. This allows the user to virtually experience the habitat of the living creature photographed.

[0063] The challenge participation unit can use the emotion estimation function to monitor the emotions of the user when participating in a challenge or game in real time, and provide feedback to elicit positive emotions. The challenge participation unit can, for example, use the emotion estimation function to monitor the emotions of the user when participating in a challenge or game in real time, and provide feedback to elicit positive emotions. For example, if the user is enjoying themselves, an encouraging message can be displayed. The challenge participation unit can also provide advice or hints if the user is confused. Furthermore, the challenge participation unit can provide praise or a reward if the user feels a sense of accomplishment. In this way, the user's emotions can be monitored in real time, and feedback to elicit positive emotions can be provided.

[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 entertainment system may further include a behavior analysis unit that tracks user behavior. The behavior analysis unit may analyze which exhibits a user viewed in an aquarium and for how long. For example, if a user viewed a dolphin show for a long time, the behavior analysis unit may provide additional information or quizzes about dolphins based on that information. If a user shows interest in a particular exhibit, the behavior analysis unit may recommend other exhibits or activities related to that exhibit. Furthermore, the behavior analysis unit may generate personalized content based on user behavior data to provide an optimal experience for each individual user. This may provide a more fulfilling experience based on the user's interests and behavior.

[0066] The entertainment system may further include a health management unit that monitors the user's health. The health management unit may monitor the user's heart rate and number of steps while the user is active in the aquarium and prompt the user to take a break at an appropriate time. For example, if the user's heart rate becomes high, the health management unit may notify the user to take a break. The health management unit may also provide a specific reward when the user achieves a certain number of steps. Furthermore, the health management unit may recommend healthy activities based on the user's health data. This allows the user to enjoy the aquarium in a healthy manner.

[0067] The entertainment system may further include an explanation unit that estimates the user's emotions and customizes the explanation of the exhibits based on the estimated emotions. The explanation unit estimates the user's emotions while viewing the exhibits and can provide a detailed explanation if the user is interested. For example, if the user is enjoying a dolphin show, the explanation unit can provide a detailed explanation about the dolphin's ecology and training methods. Furthermore, if the user expresses surprise at a particular exhibit, the explanation unit can provide surprising facts or stories about the exhibit. Furthermore, if the user expresses negative emotions toward an exhibit, the explanation unit can provide positive information to alleviate those emotions. This allows the explanation of the exhibits to be customized based on the user's emotions.

[0068] The entertainment system may further include a music providing unit that estimates the user's emotions and selects music based on the estimated emotions. The music providing unit may estimate the emotions felt by the user during their experience in the aquarium and provide music that matches those emotions. For example, if the user is relaxed, it may play calm music. If the user is excited, the music providing unit may provide upbeat music. If the user is moved, the music providing unit may provide moving music. This allows music to be selected based on the user's emotions, providing a richer experience.

[0069] The entertainment system may further include a recommendation unit that estimates the user's emotions and recommends specific exhibits based on the estimated emotions. The recommendation unit can estimate the emotions felt by the user during their experience in the aquarium and recommend exhibits that match those emotions. For example, if the user is having fun, it can recommend other enjoyable exhibits. If the user is surprised, the recommendation unit can also recommend surprising exhibits. Furthermore, if the user is relaxed, the recommendation unit can also recommend relaxing exhibits. This makes it possible to recommend specific exhibits based on the user's emotions and provide a more fulfilling experience.

[0070] The entertainment system may further include a suggestion unit that estimates the user's emotions and suggests a specific activity based on the estimated emotions. The suggestion unit can estimate the emotions felt by the user during their experience in the aquarium and suggest an activity that matches the emotions. For example, if the user is excited, an active activity can be suggested. Furthermore, if the user is relaxed, the suggestion unit can suggest a relaxing activity. Furthermore, if the user is moved, the suggestion unit can suggest an emotional activity. In this way, a specific activity can be suggested based on the user's emotions, providing a richer experience.

[0071] The entertainment system may further include an interest analysis unit that analyzes the user's interests and recommends specific exhibits based on the interests. The interest analysis unit can analyze the interests the user shows during their experience at the aquarium and recommend exhibits that match those interests. For example, if the user shows an interest in jellyfish, it can recommend other jellyfish-related exhibits. If the user shows an interest in dolphins, the interest analysis unit can also recommend dolphin-related exhibits and activities. If the user shows an interest in sharks, it can also recommend shark-related exhibits. This allows specific exhibits to be recommended based on the user's interests, providing a more fulfilling experience.

[0072] The entertainment system may further include an action suggestion unit that analyzes the user's behavior and suggests a specific activity based on the behavior. The action suggestion unit may analyze the behavior exhibited by the user during their experience in the aquarium and suggest an activity that matches that behavior. For example, if the user has been walking for a long time, the action suggestion unit may suggest that the user take a break. Furthermore, if the user has been staying at a particular exhibit for a long time, the action suggestion unit may suggest an activity related to that exhibit. Furthermore, if the user frequently visits a particular area, the action suggestion unit may suggest an activity related to that area. This makes it possible to suggest specific activities based on the user's behavior and provide a more fulfilling experience.

[0073] The entertainment system may further include a health suggestion unit that analyzes the user's health condition and suggests a specific activity based on the health condition. The health suggestion unit may analyze the health condition the user exhibits during their experience at the aquarium and suggest an activity that suits the user's health condition. For example, if the user's heart rate is high, a relaxing activity may be suggested. The health suggestion unit may also suggest an active activity if the user has achieved a certain number of steps. Furthermore, the health suggestion unit may suggest that the user take a break if the user is tired. This allows the system to suggest a specific activity based on the user's health condition, providing a healthier experience.

[0074] The entertainment system may further include an information providing unit that analyzes the user's interests and provides specific information based on the interests. The information providing unit may analyze the interests the user has shown during their experience at the aquarium and provide information that matches the interests. For example, if the user is interested in jellyfish, the information providing unit may provide detailed information about jellyfish. If the user is interested in dolphins, the information providing unit may provide information and stories about dolphins. If the user is interested in sharks, the information providing unit may provide information about sharks. This may provide specific information based on the user's interests, providing a more fulfilling experience.

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

[0076] Step 1: The photography unit takes photos of exhibits and creatures. For example, a user can use a smartphone to take photos of a dolphin show, a jellyfish exhibit, or a shark tank. Step 2: The uploading unit uploads the photos taken by the photography unit through a dedicated application. For example, a user can upload the photos they have taken to the application and store them on a cloud server. The uploading unit can also analyze the metadata of the photos and automatically record the location and date of the photo. Step 3: The challenge participation unit uses the photos uploaded by the upload unit to participate in challenges and games. For example, users can participate in missions to photograph specific creatures, puzzle games using the photos they have taken, or quizzes using photos. This allows users to earn points using the photos they have taken and exchange them for specific rewards. Users can also share the photos they have taken and the points they have earned on social media.

[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 a 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 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 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 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.

[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 photography club takes photos of exhibits and animals. an upload unit that uploads the photographs taken by the photographing unit through a dedicated application; a challenge participation unit that participates in a challenge or game by utilizing the photo uploaded by the upload unit. A system characterized by:

2. The photography unit is Photograph the dolphin show, jellyfish exhibit, and shark tank 2. The system of claim 1.

3. The upload unit Based on the photo, the AI ​​automatically generates a 3D model of the creature, allowing the user to observe the creature in augmented reality (AR).

2. The system of claim 1.

4. The upload unit Using the photo, the AI ​​automatically generates an animation that reproduces the sounds and movements of the creature.

2. The system of claim 1.

5. The challenge participant is A generation AI automatically generates a quiz about the living thing using the photo, and the user can take the quiz.

2. The system of claim 1.

6. The upload unit Emotion estimation function analyzes the emotions felt by the user when taking a photo and automatically applies specific effects and filters based on those emotions.

2. The system of claim 1.

7. The challenge participant is An emotion estimation function is used to analyze the emotions felt by the user during challenges and the game, and the difficulty and content of the game are dynamically adjusted based on the emotions.

2. The system of claim 1.

8. The challenge participant is Emotion estimation function monitors users' emotions in real time as they participate in challenges and games, and provides feedback to elicit positive emotions.

2. The system of claim 1.

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