system

Abstract

The system according to the embodiment aims to generate interactive stories based on conversations with children, allowing them to enjoy a new adventure every time. [Solution] A system according to an embodiment includes a story generation unit, an option presentation unit, a branching unit, and a story storage unit. The story generation unit analyzes conversations with a child and generates a story. The option presentation unit presents options based on the story generated by the story generation unit. The branching unit branches the story based on the options presented by the option presentation unit. The story storage unit stores the story branched by the branching unit.

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] With conventional technology, when children read picture books, the story is fixed and there is a lack of interactive experience.

[0005] The system according to the embodiment aims to generate interactive stories based on conversations with children, allowing them to enjoy a new adventure every time. [Means for solving the problem]

[0006] The system according to the embodiment includes a story generation unit, an option presentation unit, a branching unit, and a story storage unit. The story generation unit analyzes conversations with a child and generates a story. The option presentation unit presents options based on the story generated by the story generation unit. The branching unit branches the story based on the options presented by the option presentation unit. The story storage unit stores the story branched by the branching unit. [Effects of the Invention]

[0007] The system according to the embodiment generates interactive stories based on conversations with children, allowing children to enjoy a new adventure every time. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[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 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[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 AI ​​picture book system according to an embodiment of the present invention is a new type of picture book system that allows a child to adventure through a picture book. This AI picture book system analyzes conversations with the child, generates a story, and provides a picture book in which a completely new story unfolds each time the book is read. Specifically, when the child begins reading a picture book, the AI ​​analyzes the conversation with the child and generates story prompts. Next, choices are presented to the child as the story progresses, and the story branches based on the choices the child makes. Furthermore, once the story has been read, it is saved and can be reread later. This allows the child to reflect how the story unfolded based on the choices they made. For example, the AI ​​picture book system can reflect the child's name in the story by inputting it. Furthermore, by generating story prompts, it can smooth the story's progression. Furthermore, by presenting choices as the story progresses, the child can actively participate in the story. Branching the story based on the choices provides a variety of stories. The story storage unit saves stories once they have been read, allowing them to be reread later. This allows the child to look back on their adventure and enjoy it again. This allows the AI ​​storybook system to stimulate children's creativity and keep them engaged by providing new adventures with each reading. The story saving feature also allows children to look back on their adventures and relive them.

[0029] An AI picture book system according to an embodiment includes a story generation unit, an option presentation unit, a branching unit, and a story storage unit. The story generation unit analyzes conversations with a child and generates a story. For example, the story generation unit converts what the child says into text data using voice recognition technology and generates a story based on the text data. The story generation unit can also use a generation AI to generate story prompts based on the child's conversation. For example, when a child asks, "What adventure awaits me today?", the generation AI generates a prompt such as, "Today, you will have an adventure where you meet a dragon in a magical forest." The option presentation unit presents options based on the story generated by the story generation unit. For example, the option presentation unit presents options such as, "Choose the next path you want to take" as the story progresses. The option presentation unit can also use the generation AI to dynamically generate options based on the child's options. For example, when a child selects, "Choose the left path," the generation AI presents a new option such as, "What awaits on the left path?" The branching unit branches the story based on the options presented by the option presentation unit. For example, the branching unit changes the progression of the story depending on the options selected by the child. The branching unit can also dynamically generate story branches based on the options using a generation AI. For example, if a child selects "Fight the dragon," the generation AI generates a story branch such as "The battle with the dragon begins." The story storage unit stores the story branched by the branching unit. For example, the story storage unit can save a story once read as digital data so that it can be reread later. The story storage unit can also dynamically determine the format and location of the story storage using the generation AI. For example, the generation AI can highlight and save important scenes in the story. This allows the AI ​​picture book system according to the embodiment to stimulate children's creativity and provide a new adventure each time they read. Some or all of the above-described processing in the story generation unit, option presentation unit, branching unit, and story storage unit may be performed using, or without, the generation AI. For example, the story generation unit can input the child's conversation content into the generation AI and cause the generation AI to execute story prompts.The option presentation unit can cause the generation AI to generate options. The branching unit can cause the generation AI to branch the story. The story saving unit can cause the generation AI to save the story.

[0030] The AI ​​picture book system includes an input unit for inputting a child's name. The input unit provides an interface for inputting the child's name. For example, the input unit can input the child's name using a keyboard or voice input. The input unit can also input the child's name by hand using a touchscreen. For example, when a child inputs their name by hand, the input unit recognizes the handwritten characters and converts them into digital data. This allows the child's name to be reflected in the story. Furthermore, when inputting the child's name, the input unit can use a generation AI to complete or correct the input. For example, when a child inputs "Taro," the generation AI can complete the input by saying "Hello, Taro!" This allows the child's name to be reflected in the story, enhancing the sense of unity in the story. Some or all of the above-described processing in the input unit may be performed using, or without, the generation AI. For example, the input unit can input the child's name to the generation AI and have the generation AI complete or correct the name.

[0031] The AI ​​picture book system includes a prompt generation unit that generates story prompts. The prompt generation unit provides a function for generating story prompts. For example, the prompt generation unit uses a generation AI to generate story prompts based on the content of a conversation with a child. For example, when a child asks, "What adventure awaits me today?", the generation AI generates a prompt such as, "Today, an adventure where you meet a dragon in a magical forest awaits." The prompt generation unit can also dynamically generate prompts according to the progress of the story. For example, as the story progresses, the generation AI generates a prompt such as, "Please choose your next path." The prompt generation unit can also adjust the content of the prompts based on the child's age and interests. For example, the generation AI generates prompts containing simple words and a simple story for young children, and prompts containing a slightly more complex plot and character development for elementary school children. This allows the story to progress smoothly. Some or all of the above-described processing in the prompt generation unit may be performed using, or without, the generation AI. For example, the prompt generation unit can input the content of a child's conversation into the generation AI and have the generation AI generate prompts.

[0032] The choice presentation unit can present choices to the child as the story progresses. The choice presentation unit provides a function for presenting choices to the child as the story progresses. For example, the choice presentation unit presents a choice such as "Choose your next path" at the end of a particular scene or chapter in the story. The choice presentation unit can also dynamically generate choices based on the child's choices using a generation AI. For example, if the child selects "Choose the left path," the generation AI presents a new choice such as "What awaits on the left path?" The choice presentation unit can also adjust the content of the choices based on the child's emotions and interests. For example, if the child is excited, the generation AI presents choices that emphasize adventure and action elements, and if the child is relaxed, it presents calm and comfortable choices. This allows the child to actively participate in the story. Some or all of the above-described processing in the choice presentation unit may be performed using, or without, the generation AI. For example, the choice presentation unit can input the child's choices into the generation AI and have the generation AI generate choices.

[0033] The branching unit can branch the story based on choices. The branching unit provides a function for branching the story based on choices. For example, the branching unit changes the progress of the story depending on the choices selected by the child. The branching unit can also dynamically generate story branches based on choices using a generation AI. For example, if a child selects "fight the dragon," the generation AI generates a story branch such as "a battle with the dragon begins." The branching unit can also adjust the branching method of the story based on the child's emotions and interests. For example, the generation AI selects an exciting branch if the child is excited and a calm branch if the child is relaxed. This provides variety in the story. Some or all of the above-mentioned processing in the branching unit may be performed using, or without, the generation AI. For example, the branching unit can input the child's choices into the generation AI and cause the generation AI to execute the branching of the story.

[0034] The story storage unit can save a story once it has been read. The story storage unit provides a function for saving a story once it has been read. For example, the story storage unit can save a story as digital data so that the story can be reread later. The story storage unit can also dynamically determine the storage format and storage location of the story using the generation AI. For example, the generation AI can highlight and save important scenes of the story. Furthermore, the story storage unit can adjust the method of saving the story based on the child's emotions and interests. For example, the generation AI can highlight and save the highlight scenes of the story when the child is excited, and save the entire story in detail when the child is relaxed. This allows the story to be reread later. Some or all of the above-mentioned processing in the story storage unit may be performed using, or without, the generation AI. For example, the story storage unit can input story data into the generation AI and have the generation AI determine the storage format and storage location.

[0035] The AI ​​picture book system includes a story generation unit that analyzes a child's past conversation history and personalizes the content of the story. The story generation unit analyzes a child's past conversation history and personalizes the content of the story. For example, the story generation unit includes a favorite character that the child has talked about in the past in the story. The story generation unit can also incorporate themes and topics that the child has previously shown interest in into the story. Furthermore, the story generation unit can incorporate episodes and events that the child has talked about in the past as part of the story. This makes it possible to provide a personalized story for the child. Some or all of the above-mentioned processing in the story generation unit may be performed using, or without, a generation AI, for example. For example, the story generation unit can input the child's conversation history data into the generation AI and have the generation AI personalize the story.

[0036] The AI ​​picture book system includes a story generation unit that selects appropriate difficulty and content based on the child's age and interests when generating a story. The story generation unit selects appropriate difficulty and content based on the child's age and interests when generating a story. For example, the story generation unit selects simple words and a simple story for young children. The story generation unit can also generate stories with slightly more complex plots and character development for elementary school students. Furthermore, the story generation unit can generate stories with deeper themes and complex character relationships for junior high school students. This allows for providing stories that are appropriate for children. Some or all of the above-described processing in the story generation unit may be performed using, or without, a generation AI. For example, the story generation unit can input the child's age and interest data into the generation AI and have the generation AI select the difficulty and content of the story.

[0037] The AI ​​picture book system includes a story generation unit that incorporates elements related to the region, taking into account the child's geographical location information, when generating a story. The story generation unit incorporates elements related to the region, taking into account the child's geographical location information, when generating a story. For example, the story generation unit includes famous places and scenery in the region where the child lives in the story. Also, if the child is traveling, the story generation unit can incorporate the culture and famous places of the travel destination into the story. Furthermore, the story generation unit can reflect the history and geography of the region where the child is studying at school in the story. This makes it possible to provide a story related to the region. Some or all of the above-described processing in the story generation unit may be performed using, or without, the generation AI, for example. For example, the story generation unit can input the child's geographical location information into the generation AI and cause the generation AI to incorporate elements related to the region.

[0038] The AI ​​picture book system includes a story generation unit that analyzes a child's social media activities and reflects related topics in the story when generating a story. The story generation unit analyzes a child's social media activities and reflects related topics in the story when generating a story. For example, the story generation unit incorporates characters and themes that the child talks about on social media into the story. The story generation unit can also incorporate photos and videos that the child has shared on social media as part of the story. Furthermore, the story generation unit can also feature influencers and celebrities that the child follows on social media in the story. This allows topics related to the child to be reflected in the story. Some or all of the above-described processing in the story generation unit may be performed using, or without, a generation AI. For example, the story generation unit may input data on the child's social media activities into the generation AI and cause the generation AI to reflect related topics.

[0039] In the AI ​​picture book system, when presenting options, the option presentation unit refers to the child's past selection history to present the optimal option. When presenting options, the option presentation unit refers to the child's past selection history to present the optimal option. For example, the option presentation unit presents similar options based on options previously selected by the child. The option presentation unit can also eliminate options that the child has avoided in the past and present new options. Furthermore, the option presentation unit can present options based on the child's preferences and interests from the child's past selection history. This makes it possible to provide the optimal option for the child. Some or all of the above-described processing in the option presentation unit may be performed using, or without, a generation AI. For example, the option presentation unit can input the child's selection history data into the generation AI and cause the generation AI to present the optimal option.

[0040] In the AI ​​picture book system, when the option presentation unit presents options, it dynamically changes the number and content of options according to the progress of the story. When presenting options, the option presentation unit dynamically changes the number and content of options according to the progress of the story. For example, the option presentation unit presents a small number of important options at the climax of the story. The option presentation unit can also present a variety of options early in the story to attract children's interest. Furthermore, the option presentation unit can change the content of options according to the progress of the story to maintain the consistency of the story. In this way, the consistency of the story can be maintained by dynamically changing the options according to the progress of the story. Some or all of the above-mentioned processing in the option presentation unit may be performed using, or without, a generation AI. For example, the option presentation unit can input story progress data into the generation AI and cause the generation AI to dynamically change the number and content of options.

[0041] In the AI ​​picture book system, the option presentation unit presents options taking into consideration the child's current activity status when presenting options. The option presentation unit presents options taking into consideration the child's current activity status when presenting options. For example, if the child is playing, the option presentation unit presents options that can be selected in a short time. Also, if the child is studying, the option presentation unit can present options that include educational elements. Furthermore, if the child is taking a break, the option presentation unit can present options that allow the child to relax. This makes it possible to provide options that are suitable for the child. Some or all of the above-mentioned processing in the option presentation unit may be performed using, or without, a generation AI. For example, the option presentation unit may input child activity status data into the generation AI and cause the generation AI to present options.

[0042] In the AI ​​picture book system, when presenting options, the option presentation unit refers to the child's learning history and presents options including educational elements. When presenting options, the option presentation unit refers to the child's learning history and presents options including educational elements. For example, the option presentation unit presents options that allow the child to review content that they have previously learned. The option presentation unit can also present options related to learning topics in which the child has shown interest. Furthermore, the option presentation unit can present options of an appropriate level of difficulty depending on the child's learning progress. This makes it possible to provide options including educational elements. Some or all of the above-mentioned processing in the option presentation unit may be performed using, or without, a generation AI. For example, the option presentation unit may input the child's learning history data into the generation AI and cause the generation AI to present options including educational elements.

[0043] The AI ​​picture book system optimizes the branching pattern of the story by referring to the child's past selection history when the branching unit branches. The branching unit optimizes the branching pattern of the story by referring to the child's past selection history when branching. For example, the branching unit provides similar branches based on branches previously selected by the child. The branching unit can also eliminate branches that the child has avoided in the past and provide new branches. Furthermore, the branching unit can provide branches based on the child's preferences and interests from the child's past selection history. This makes it possible to provide the optimal branching pattern of the story for the child. Some or all of the above-described processing in the branching unit may be performed using, or without, a generation AI. For example, the branching unit can input the child's selection history data into the generation AI and cause the generation AI to optimize the branching pattern of the story.

[0044] The AI ​​picture book system provides a branch related to a region by taking into account the child's geographical location information when branching. The branching unit provides a branch related to a region by taking into account the child's geographical location information when branching. For example, the branching unit incorporates famous places and scenery in the region where the child lives into the branch. Also, if the child is traveling, the branching unit can reflect the culture and famous places of the travel destination in the branch. Furthermore, the branching unit can reflect the history and geography of the region where the child is studying at school in the branch. This makes it possible to provide a branch of the story related to the region. Some or all of the above-mentioned processing in the branching unit may be performed using, or without, a generation AI. For example, the branching unit may input the child's geographical location information into the generation AI and cause the generation AI to provide a branch related to the region.

[0045] In the AI ​​picture book system, the branching unit analyzes the child's social media activity and reflects related topics in the branch when branching. The branching unit analyzes the child's social media activity and reflects related topics in the branch when branching. For example, the branching unit incorporates characters and themes that the child is talking about on social media into the branch. The branching unit can also incorporate photos and videos that the child has shared on social media as part of the branch. Furthermore, the branching unit can also feature influencers and celebrities that the child follows on social media in the branch. In this way, topics related to the child can be reflected in the branch of the story. Some or all of the above-mentioned processing in the branching unit may be performed using, or without, a generation AI. For example, the branching unit may input the child's social media activity data into the generation AI and cause the generation AI to reflect related topics.

[0046] In the AI ​​picture book system, the story storage unit highlights and saves important points of the story when saving the story. The story storage unit highlights and saves important points of the story when saving the story. For example, the story storage unit highlights and saves the climax scene of the story. The story storage unit can also highlight and save important choices in the story and their outcomes. Furthermore, the story storage unit can highlight and save moving scenes in the story. This makes it easy to find important scenes later. Some or all of the above-mentioned processing in the story storage unit may be performed using, or without, the generation AI, for example. For example, the story storage unit can input story data into the generation AI and have the generation AI highlight the important points.

[0047] In the AI ​​picture book system, the story storage unit automatically adjusts the timing of saving according to the progress of the story when saving. The story storage unit automatically adjusts the timing of saving according to the progress of the story when saving. For example, the story storage unit automatically saves immediately after an important event in the story occurs. The story storage unit can also automatically save when a chapter of the story ends. Furthermore, the story storage unit can automatically save immediately after a child selects an option. This makes it possible to save important scenes without missing them. Some or all of the above-mentioned processing in the story storage unit may be performed using, or without, the generation AI, for example. For example, the story storage unit can input story progress data into the generation AI and have the generation AI adjust the timing of saving.

[0048] In the AI ​​picture book system, the story storage unit prioritizes saving related stories by taking into consideration the child's geographical location information when saving. The story storage unit prioritizes saving related stories by taking into consideration the child's geographical location information when saving. For example, the story storage unit prioritizes saving stories related to the area where the child lives. Also, if the child is traveling, the story storage unit can prioritize saving stories related to the travel destination. Furthermore, the story storage unit can prioritize saving stories related to the area where the child is studying at school. This allows stories related to the area to be saved preferentially. Some or all of the above-mentioned processing in the story storage unit may be performed using, or without, the generation AI, for example. For example, the story storage unit can input the child's geographical location information to the generation AI and cause the generation AI to save related stories.

[0049] In the AI ​​picture book system, the story storage unit analyzes the child's social media activity and stores related stories when saving. The story storage unit analyzes the child's social media activity and stores related stories when saving. For example, the story storage unit stores stories related to characters or themes that the child talks about on social media. The story storage unit can also store stories related to photos and videos that the child has shared on social media. Furthermore, the story storage unit can store stories related to influencers or celebrities that the child follows on social media. This allows stories related to the child to be stored. Some or all of the above-described processing in the story storage unit may be performed using, or without, the generation AI, for example. For example, the story storage unit can input the child's social media activity data into the generation AI and cause the generation AI to store related stories.

[0050] In the AI ​​picture book system, when an input unit inputs, the input unit refers to the child's past input history and presents the optimal input method. When inputting, the input unit refers to the child's past input history and presents the optimal input method. For example, the input unit preferentially presents input methods (voice, text, etc.) that the child has used in the past. The input unit can also present related input options based on the content the child has previously input. Furthermore, the input unit can present the most efficient input method from the child's past input history. This makes it possible to provide the optimal input method for the child. Some or all of the above-mentioned processing in the input unit may be performed using, or without, a generation AI. For example, the input unit can input the child's input history data to the generation AI and have the generation AI present the optimal input method.

[0051] In the AI ​​picture book system, when an input unit inputs, the input unit considers the child's device information and presents the optimal input method. When an input unit inputs, the input unit considers the child's device information and presents the optimal input method. For example, if a child is using a smartphone, the input unit provides an input method that matches the screen size. Also, if a child is using a tablet, the input unit can provide an input method optimized for a large screen. Furthermore, if a child is using a smartwatch, the input unit can provide an input method that is simple and highly visible. This makes it possible to provide the optimal input method for a child. Some or all of the above-described processing in the input unit may be performed using, or without, a generation AI. For example, the input unit may input the child's device information to the generation AI and have the generation AI present the optimal input method.

[0052] In the AI ​​picture book system, when generating a prompt, the prompt generation unit references the child's past conversation history to generate the optimal prompt. When generating a prompt, the prompt generation unit references the child's past conversation history to generate the optimal prompt. For example, the prompt generation unit includes a favorite character that the child has talked about in the past in the prompt. The prompt generation unit can also incorporate themes or topics in which the child has previously shown interest into the prompt. Furthermore, the prompt generation unit can incorporate episodes or events that the child has talked about in the past as part of the prompt. This makes it possible to provide the optimal prompt for the child. Some or all of the above-mentioned processing in the prompt generation unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the prompt generation unit may input the child's conversation history data into the generation AI and cause the generation AI to generate the optimal prompt.

[0053] In the AI ​​picture book system, the prompt generation unit generates a relevant prompt by taking into account the child's geographical location information when generating a prompt. The prompt generation unit generates a relevant prompt by taking into account the child's geographical location information when generating a prompt. For example, the prompt generation unit includes famous places and scenery in the area where the child lives in the prompt. Also, if the child is traveling, the prompt generation unit can incorporate the culture and famous places of the travel destination into the prompt. Furthermore, the prompt generation unit can reflect the history and geography of the area where the child is studying at school in the prompt. This makes it possible to provide prompts related to the area. Some or all of the above-mentioned processing in the prompt generation unit may be performed using, or without, a generation AI, for example. For example, the prompt generation unit can input the child's geographical location information into the generation AI and cause the generation AI to generate a relevant prompt.

[0054] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0055] The AI ​​picture book system's story generation unit can analyze a child's past selection history and personalize the story progression. For example, it can present similar options based on options the child has previously chosen. It can also eliminate options the child has avoided in the past and present new options. It can also provide a story progression based on the child's preferences and interests from their past selection history. This allows it to provide a story progression that is optimal for each child.

[0056] The story generation section of the AI ​​picture book system can reference a child's learning history and incorporate educational elements into the story. For example, it can generate a story that allows a child to review what they have learned in the past. It can also provide stories related to learning themes that interest a child. It can also generate stories of an appropriate level of difficulty depending on the child's learning progress. This makes it possible to support a child's learning through stories.

[0057] The AI ​​picture book system's story generation section can take into account the child's geographical location information and incorporate local culture and famous places into the story. For example, famous places and scenery from the area where the child lives can appear in the story. Also, if the child is traveling, the culture and famous places of the destination can be incorporated into the story. Furthermore, the history and geography of the area the child is studying at school can be reflected in the story. This allows the system to provide stories that are relevant to the area.

[0058] The AI ​​picture book system's story generation section can analyze a child's social media activity and incorporate related topics into the story. For example, it can feature characters and themes that a child talks about on social media. It can also incorporate photos and videos that a child has shared on social media as part of the story. It can also include influencers and celebrities that a child follows on social media. This allows the story to reflect topics relevant to the child.

[0059] The story generation section of the AI ​​picture book system analyzes the child's past conversation history and can incorporate episodes and events that the child has talked about into the story. For example, a favorite character that the child has talked about in the past can appear in the story. It can also incorporate themes and topics that the child has previously shown interest in into the story. It can also incorporate episodes and events that the child has talked about in the past as part of the story. This makes it possible to provide a personalized story for the child.

[0060] The processing flow of the first embodiment will be briefly explained below.

[0061] Step 1: The story generation unit analyzes the conversation with the child and generates a story. For example, the story generation unit converts what the child says into text data using voice recognition technology, and generates a story based on that text data. The generation AI can also be used to generate story prompts based on the child's conversation. For example, if a child asks, "What adventure awaits me today?" the generation AI generates a prompt such as, "Today, you will have an adventure where you meet a dragon in a magical forest." Step 2: The option presentation unit presents options based on the story generated by the story generation unit. For example, the option presentation unit presents options such as "Choose the next path to take" as the story progresses. The generation AI can also be used to dynamically generate options based on the child's choices. For example, if the child selects "Choose the left path," the generation AI will present a new option such as "What awaits on the left path?" Step 3: The branching unit branches the story based on the options presented by the option presentation unit. For example, the branching unit changes the progress of the story depending on the option selected by the child. Alternatively, a generation AI can be used to dynamically generate branching storylines based on the options. For example, if the child selects "fight the dragon," the generation AI generates a branching story such as "the battle with the dragon begins." Step 4: The story storage unit saves the story branched by the branching unit. For example, the story storage unit can save a story that has been read once as digital data, allowing it to be read again later. The generation AI can also be used to dynamically determine the format and location of the story to be saved. For example, the generation AI can highlight and save important scenes in the story.

[0062] (Example 2) The AI ​​picture book system according to an embodiment of the present invention is a new type of picture book system that allows a child to adventure through a picture book. This AI picture book system analyzes conversations with the child, generates a story, and provides a picture book in which a completely new story unfolds each time the book is read. Specifically, when the child begins reading a picture book, the AI ​​analyzes the conversation with the child and generates story prompts. Next, choices are presented to the child as the story progresses, and the story branches based on the choices the child makes. Furthermore, once the story has been read, it is saved and can be reread later. This allows the child to reflect how the story unfolded based on the choices they made. For example, the AI ​​picture book system can reflect the child's name in the story by inputting it. Furthermore, by generating story prompts, it can smooth the story's progression. Furthermore, by presenting choices as the story progresses, the child can actively participate in the story. Branching the story based on the choices provides a variety of stories. The story storage unit saves stories once they have been read, allowing them to be reread later. This allows the child to look back on their adventure and enjoy it again. This allows the AI ​​storybook system to stimulate children's creativity and keep them engaged by providing new adventures with each reading. The story saving feature also allows children to look back on their adventures and relive them.

[0063] An AI picture book system according to an embodiment includes a story generation unit, an option presentation unit, a branching unit, and a story storage unit. The story generation unit analyzes conversations with a child and generates a story. For example, the story generation unit converts what the child says into text data using voice recognition technology and generates a story based on the text data. The story generation unit can also use a generation AI to generate story prompts based on the child's conversation. For example, when a child asks, "What adventure awaits me today?", the generation AI generates a prompt such as, "Today, you will have an adventure where you meet a dragon in a magical forest." The option presentation unit presents options based on the story generated by the story generation unit. For example, the option presentation unit presents options such as, "Choose the next path you want to take" as the story progresses. The option presentation unit can also use the generation AI to dynamically generate options based on the child's options. For example, when a child selects, "Choose the left path," the generation AI presents a new option such as, "What awaits on the left path?" The branching unit branches the story based on the options presented by the option presentation unit. For example, the branching unit changes the progression of the story depending on the options selected by the child. The branching unit can also dynamically generate story branches based on the options using a generation AI. For example, if a child selects "Fight the dragon," the generation AI generates a story branch such as "The battle with the dragon begins." The story storage unit stores the story branched by the branching unit. For example, the story storage unit can save a story once read as digital data so that it can be reread later. The story storage unit can also dynamically determine the format and location of the story storage using the generation AI. For example, the generation AI can highlight and save important scenes in the story. This allows the AI ​​picture book system according to the embodiment to stimulate children's creativity and provide a new adventure each time they read. Some or all of the above-described processing in the story generation unit, option presentation unit, branching unit, and story storage unit may be performed using, or without, the generation AI. For example, the story generation unit can input the child's conversation content into the generation AI and cause the generation AI to execute story prompts.The option presentation unit can cause the generation AI to generate options. The branching unit can cause the generation AI to branch the story. The story saving unit can cause the generation AI to save the story.

[0064] The AI ​​picture book system includes an input unit for inputting a child's name. The input unit provides an interface for inputting the child's name. For example, the input unit can input the child's name using a keyboard or voice input. The input unit can also input the child's name by hand using a touchscreen. For example, when a child inputs their name by hand, the input unit recognizes the handwritten characters and converts them into digital data. This allows the child's name to be reflected in the story. Furthermore, when inputting the child's name, the input unit can use a generation AI to complete or correct the input. For example, when a child inputs "Taro," the generation AI can complete the input by saying "Hello, Taro!" This allows the child's name to be reflected in the story, enhancing the sense of unity in the story. Some or all of the above-described processing in the input unit may be performed using, or without, the generation AI. For example, the input unit can input the child's name to the generation AI and have the generation AI complete or correct the name.

[0065] The AI ​​picture book system includes a prompt generation unit that generates story prompts. The prompt generation unit provides a function for generating story prompts. For example, the prompt generation unit uses a generation AI to generate story prompts based on the content of a conversation with a child. For example, when a child asks, "What adventure awaits me today?", the generation AI generates a prompt such as, "Today, an adventure where you meet a dragon in a magical forest awaits." The prompt generation unit can also dynamically generate prompts according to the progress of the story. For example, as the story progresses, the generation AI generates a prompt such as, "Please choose your next path." The prompt generation unit can also adjust the content of the prompts based on the child's age and interests. For example, the generation AI generates prompts containing simple words and a simple story for young children, and prompts containing a slightly more complex plot and character development for elementary school children. This allows the story to progress smoothly. Some or all of the above-described processing in the prompt generation unit may be performed using, or without, the generation AI. For example, the prompt generation unit can input the content of a child's conversation into the generation AI and have the generation AI generate prompts.

[0066] The choice presentation unit can present choices to the child as the story progresses. The choice presentation unit provides a function for presenting choices to the child as the story progresses. For example, the choice presentation unit presents a choice such as "Choose your next path" at the end of a particular scene or chapter in the story. The choice presentation unit can also dynamically generate choices based on the child's choices using a generation AI. For example, if the child selects "Choose the left path," the generation AI presents a new choice such as "What awaits on the left path?" The choice presentation unit can also adjust the content of the choices based on the child's emotions and interests. For example, if the child is excited, the generation AI presents choices that emphasize adventure and action elements, and if the child is relaxed, it presents calm and comfortable choices. This allows the child to actively participate in the story. Some or all of the above-described processing in the choice presentation unit may be performed using, or without, the generation AI. For example, the choice presentation unit can input the child's choices into the generation AI and have the generation AI generate choices.

[0067] The branching unit can branch the story based on choices. The branching unit provides a function for branching the story based on choices. For example, the branching unit changes the progress of the story depending on the choices selected by the child. The branching unit can also dynamically generate story branches based on choices using a generation AI. For example, if a child selects "fight the dragon," the generation AI generates a story branch such as "a battle with the dragon begins." The branching unit can also adjust the branching method of the story based on the child's emotions and interests. For example, the generation AI selects an exciting branch if the child is excited and a calm branch if the child is relaxed. This provides variety in the story. Some or all of the above-mentioned processing in the branching unit may be performed using, or without, the generation AI. For example, the branching unit can input the child's choices into the generation AI and cause the generation AI to execute the branching of the story.

[0068] The story storage unit can save a story once it has been read. The story storage unit provides a function for saving a story once it has been read. For example, the story storage unit can save a story as digital data so that the story can be reread later. The story storage unit can also dynamically determine the storage format and storage location of the story using the generation AI. For example, the generation AI can highlight and save important scenes of the story. Furthermore, the story storage unit can adjust the method of saving the story based on the child's emotions and interests. For example, the generation AI can highlight and save the highlight scenes of the story when the child is excited, and save the entire story in detail when the child is relaxed. This allows the story to be reread later. Some or all of the above-mentioned processing in the story storage unit may be performed using, or without, the generation AI. For example, the story storage unit can input story data into the generation AI and have the generation AI determine the storage format and storage location.

[0069] The AI ​​picture book system includes a story generation unit that estimates a child's emotions and adjusts the tone and theme of the story based on the estimated child's emotions. The story generation unit estimates a child's emotions and adjusts the tone and theme of the story based on the estimated child's emotions. For example, if a child is sad, the story generation unit adjusts the tone of the story to be lighter and include an encouraging message. If a child is excited, the story generation unit can also generate a story that emphasizes adventure and action elements. Furthermore, if a child is relaxed, the story generation unit can generate a story with a calm and soothing tone. This allows a story suitable for the child to be provided. Some or all of the above-described processing in the story generation unit may be performed using, or without, a generation AI. For example, the story generation unit may input child's emotion data into the generation AI and have the generation AI adjust the tone and theme of the story.

[0070] The AI ​​picture book system includes a story generation unit that analyzes a child's past conversation history and personalizes the content of the story. The story generation unit analyzes a child's past conversation history and personalizes the content of the story. For example, the story generation unit includes a favorite character that the child has talked about in the past in the story. The story generation unit can also incorporate themes and topics that the child has previously shown interest in into the story. Furthermore, the story generation unit can incorporate episodes and events that the child has talked about in the past as part of the story. This makes it possible to provide a personalized story for the child. Some or all of the above-mentioned processing in the story generation unit may be performed using, or without, a generation AI, for example. For example, the story generation unit can input the child's conversation history data into the generation AI and have the generation AI personalize the story.

[0071] The AI ​​picture book system includes a story generation unit that selects appropriate difficulty and content based on the child's age and interests when generating a story. The story generation unit selects appropriate difficulty and content based on the child's age and interests when generating a story. For example, the story generation unit selects simple words and a simple story for young children. The story generation unit can also generate stories with slightly more complex plots and character development for elementary school students. Furthermore, the story generation unit can generate stories with deeper themes and complex character relationships for junior high school students. This allows for providing stories that are appropriate for children. Some or all of the above-described processing in the story generation unit may be performed using, or without, a generation AI. For example, the story generation unit can input the child's age and interest data into the generation AI and have the generation AI select the difficulty and content of the story.

[0072] The AI ​​picture book system includes a story generation unit that estimates a child's emotions and adjusts the speed of the story based on the estimated child's emotions. The story generation unit estimates the child's emotions and adjusts the speed of the story based on the estimated child's emotions. For example, if the child is excited, the story generation unit may speed up the story to create a fast-paced development. Alternatively, if the child is relaxed, the story generation unit may slow down the story to maintain a relaxed atmosphere. Furthermore, if the child is tired, the story generation unit may adjust the speed of the story to provide shorter episodes. This allows the story to progress in a way that is appropriate for the child. Some or all of the above-described processing in the story generation unit may be performed using, or without, a generation AI. For example, the story generation unit may input child's emotion data into the generation AI and cause the generation AI to adjust the speed of the story.

[0073] The AI ​​picture book system includes a story generation unit that incorporates elements related to the region, taking into account the child's geographical location information, when generating a story. The story generation unit incorporates elements related to the region, taking into account the child's geographical location information, when generating a story. For example, the story generation unit includes famous places and scenery in the region where the child lives in the story. Also, if the child is traveling, the story generation unit can incorporate the culture and famous places of the travel destination into the story. Furthermore, the story generation unit can reflect the history and geography of the region where the child is studying at school in the story. This makes it possible to provide a story related to the region. Some or all of the above-described processing in the story generation unit may be performed using, or without, the generation AI, for example. For example, the story generation unit can input the child's geographical location information into the generation AI and cause the generation AI to incorporate elements related to the region.

[0074] The AI ​​picture book system includes a story generation unit that analyzes a child's social media activities and reflects related topics in the story when generating a story. The story generation unit analyzes a child's social media activities and reflects related topics in the story when generating a story. For example, the story generation unit incorporates characters and themes that the child talks about on social media into the story. The story generation unit can also incorporate photos and videos that the child has shared on social media as part of the story. Furthermore, the story generation unit can also feature influencers and celebrities that the child follows on social media in the story. This allows topics related to the child to be reflected in the story. Some or all of the above-described processing in the story generation unit may be performed using, or without, a generation AI. For example, the story generation unit may input data on the child's social media activities into the generation AI and cause the generation AI to reflect related topics.

[0075] In the AI ​​picture book system, the option presentation unit estimates a child's emotions and adjusts the way options are presented based on the estimated child's emotions. The option presentation unit estimates a child's emotions and adjusts the way options are presented based on the estimated child's emotions. For example, if a child is nervous, the option presentation unit presents simple and easy-to-understand options. If a child is relaxed, the option presentation unit can also present options with detailed explanations. Furthermore, if a child is excited, the option presentation unit can also present visually appealing options. This makes it possible to provide options suitable for children. Some or all of the above-described processing in the option presentation unit may be performed using, or without, a generation AI. For example, the option presentation unit may input child's emotion data into the generation AI and cause the generation AI to adjust the way options are presented.

[0076] In the AI ​​picture book system, when presenting options, the option presentation unit refers to the child's past selection history to present the optimal option. When presenting options, the option presentation unit refers to the child's past selection history to present the optimal option. For example, the option presentation unit presents similar options based on options previously selected by the child. The option presentation unit can also eliminate options that the child has avoided in the past and present new options. Furthermore, the option presentation unit can present options based on the child's preferences and interests from the child's past selection history. This makes it possible to provide the optimal option for the child. Some or all of the above-described processing in the option presentation unit may be performed using, or without, a generation AI. For example, the option presentation unit can input the child's selection history data into the generation AI and cause the generation AI to present the optimal option.

[0077] In the AI ​​picture book system, when the option presentation unit presents options, it dynamically changes the number and content of options according to the progress of the story. When presenting options, the option presentation unit dynamically changes the number and content of options according to the progress of the story. For example, the option presentation unit presents a small number of important options at the climax of the story. The option presentation unit can also present a variety of options early in the story to attract children's interest. Furthermore, the option presentation unit can change the content of options according to the progress of the story to maintain the consistency of the story. In this way, the consistency of the story can be maintained by dynamically changing the options according to the progress of the story. Some or all of the above-mentioned processing in the option presentation unit may be performed using, or without, a generation AI. For example, the option presentation unit can input story progress data into the generation AI and cause the generation AI to dynamically change the number and content of options.

[0078] In the AI ​​picture book system, the option presentation unit estimates a child's emotions and adjusts the order of options based on the estimated child's emotions. The option presentation unit estimates a child's emotions and adjusts the order of options based on the estimated child's emotions. For example, if a child is nervous, the option presentation unit presents the easiest and most reassuring option first. If a child is relaxed, the option presentation unit can also present options randomly to attract the child's interest. Furthermore, if a child is excited, the option presentation unit can present the most stimulating option first. This allows options suitable for the child to be provided. Some or all of the above-described processing in the option presentation unit may be performed using, or without, a generation AI. For example, the option presentation unit may input child's emotion data into the generation AI and have the generation AI adjust the order of options.

[0079] In the AI ​​picture book system, the option presentation unit presents options taking into consideration the child's current activity status when presenting options. The option presentation unit presents options taking into consideration the child's current activity status when presenting options. For example, if the child is playing, the option presentation unit presents options that can be selected in a short time. Also, if the child is studying, the option presentation unit can present options that include educational elements. Furthermore, if the child is taking a break, the option presentation unit can present options that allow the child to relax. This makes it possible to provide options that are suitable for the child. Some or all of the above-mentioned processing in the option presentation unit may be performed using, or without, a generation AI. For example, the option presentation unit may input child activity status data into the generation AI and cause the generation AI to present options.

[0080] In the AI ​​picture book system, when presenting options, the option presentation unit refers to the child's learning history and presents options including educational elements. When presenting options, the option presentation unit refers to the child's learning history and presents options including educational elements. For example, the option presentation unit presents options that allow the child to review content that they have previously learned. The option presentation unit can also present options related to learning topics in which the child has shown interest. Furthermore, the option presentation unit can present options of an appropriate level of difficulty depending on the child's learning progress. This makes it possible to provide options including educational elements. Some or all of the above-mentioned processing in the option presentation unit may be performed using, or without, a generation AI. For example, the option presentation unit may input the child's learning history data into the generation AI and cause the generation AI to present options including educational elements.

[0081] In the AI ​​picture book system, the branching unit estimates a child's emotions and adjusts the branching method of the story based on the estimated child's emotions. The branching unit estimates a child's emotions and adjusts the branching method of the story based on the estimated child's emotions. For example, if a child is nervous, the branching unit selects a reassuring branch. Also, if a child is relaxed, the branching unit can select a branch with a high degree of freedom. Furthermore, if a child is excited, the branching unit can select a stimulating branch. This makes it possible to provide a story progression that is appropriate for the child. Some or all of the above-mentioned processing in the branching unit may be performed using, or without, a generation AI. For example, the branching unit may input child's emotional data into the generation AI and have the generation AI adjust the branching method of the story.

[0082] The AI ​​picture book system optimizes the branching pattern of the story by referring to the child's past selection history when the branching unit branches. The branching unit optimizes the branching pattern of the story by referring to the child's past selection history when branching. For example, the branching unit provides similar branches based on branches previously selected by the child. The branching unit can also eliminate branches that the child has avoided in the past and provide new branches. Furthermore, the branching unit can provide branches based on the child's preferences and interests from the child's past selection history. This makes it possible to provide the optimal branching pattern of the story for the child. Some or all of the above-described processing in the branching unit may be performed using, or without, a generation AI. For example, the branching unit can input the child's selection history data into the generation AI and cause the generation AI to optimize the branching pattern of the story.

[0083] In the AI ​​picture book system, the branching unit estimates the child's emotions and adjusts the order in which branching results are displayed based on the estimated child's emotions. The branching unit estimates the child's emotions and adjusts the order in which branching results are displayed based on the estimated child's emotions. For example, if the child is nervous, the branching unit may display the most reassuring result first. If the child is relaxed, the branching unit may also randomly display results to attract the child's interest. Furthermore, if the child is excited, the branching unit may also display the most stimulating result first. This allows for a story progression that is appropriate for the child. Some or all of the above-described processing in the branching unit may be performed using, or without, a generation AI. For example, the branching unit may input the child's emotion data into the generation AI and cause the generation AI to adjust the order in which branching results are displayed.

[0084] The AI ​​picture book system provides a branch related to a region by taking into account the child's geographical location information when branching. The branching unit provides a branch related to a region by taking into account the child's geographical location information when branching. For example, the branching unit incorporates famous places and scenery in the region where the child lives into the branch. Also, if the child is traveling, the branching unit can reflect the culture and famous places of the travel destination in the branch. Furthermore, the branching unit can reflect the history and geography of the region where the child is studying at school in the branch. This makes it possible to provide a branch of the story related to the region. Some or all of the above-mentioned processing in the branching unit may be performed using, or without, a generation AI. For example, the branching unit may input the child's geographical location information into the generation AI and cause the generation AI to provide a branch related to the region.

[0085] In the AI ​​picture book system, the branching unit analyzes the child's social media activity and reflects related topics in the branch when branching. The branching unit analyzes the child's social media activity and reflects related topics in the branch when branching. For example, the branching unit incorporates characters and themes that the child is talking about on social media into the branch. The branching unit can also incorporate photos and videos that the child has shared on social media as part of the branch. Furthermore, the branching unit can also feature influencers and celebrities that the child follows on social media in the branch. In this way, topics related to the child can be reflected in the branch of the story. Some or all of the above-mentioned processing in the branching unit may be performed using, or without, a generation AI. For example, the branching unit may input the child's social media activity data into the generation AI and cause the generation AI to reflect related topics.

[0086] In the AI ​​picture book system, the story storage unit estimates a child's emotions and adjusts the story storage method based on the estimated child's emotions. The story storage unit estimates a child's emotions and adjusts the story storage method based on the estimated child's emotions. For example, if a child is excited, the story storage unit emphasizes and stores the highlight scenes of the story. If a child is relaxed, the story storage unit can also store the entire story in detail. Furthermore, if a child is tired, the story storage unit can briefly store only the important points. This allows stories to be stored that are appropriate for the child. Some or all of the above-mentioned processing in the story storage unit may be performed using, or without, a generation AI. For example, the story storage unit may input child's emotion data into the generation AI and have the generation AI adjust the story storage method.

[0087] In the AI ​​picture book system, the story storage unit highlights and saves important points of the story when saving the story. The story storage unit highlights and saves important points of the story when saving the story. For example, the story storage unit highlights and saves the climax scene of the story. The story storage unit can also highlight and save important choices in the story and their outcomes. Furthermore, the story storage unit can highlight and save moving scenes in the story. This makes it easy to find important scenes later. Some or all of the above-mentioned processing in the story storage unit may be performed using, or without, the generation AI, for example. For example, the story storage unit can input story data into the generation AI and have the generation AI highlight the important points.

[0088] In the AI ​​picture book system, the story storage unit automatically adjusts the timing of saving according to the progress of the story when saving. The story storage unit automatically adjusts the timing of saving according to the progress of the story when saving. For example, the story storage unit automatically saves immediately after an important event in the story occurs. The story storage unit can also automatically save when a chapter of the story ends. Furthermore, the story storage unit can automatically save immediately after a child selects an option. This makes it possible to save important scenes without missing them. Some or all of the above-mentioned processing in the story storage unit may be performed using, or without, the generation AI, for example. For example, the story storage unit can input story progress data into the generation AI and have the generation AI adjust the timing of saving.

[0089] In the AI ​​picture book system, a story storage unit estimates a child's emotions and determines the priority of stories to be saved based on the estimated child's emotions. The story storage unit estimates a child's emotions and determines the priority of stories to be saved based on the estimated child's emotions. For example, if a child is excited, the story storage unit may prioritize saving the most stimulating stories. Alternatively, if a child is relaxed, the story storage unit may prioritize saving calm stories. Furthermore, if a child is tired, the story storage unit may prioritize saving short and concise stories. This allows stories that are important to the child to be saved preferentially. Some or all of the above-described processing in the story storage unit may be performed using, or without, a generation AI. For example, the story storage unit may input child's emotion data into the generation AI and have the generation AI determine the priority of story saving.

[0090] In the AI ​​picture book system, the story storage unit prioritizes saving related stories by taking into consideration the child's geographical location information when saving. The story storage unit prioritizes saving related stories by taking into consideration the child's geographical location information when saving. For example, the story storage unit prioritizes saving stories related to the area where the child lives. Also, if the child is traveling, the story storage unit can prioritize saving stories related to the travel destination. Furthermore, the story storage unit can prioritize saving stories related to the area where the child is studying at school. This allows stories related to the area to be saved preferentially. Some or all of the above-mentioned processing in the story storage unit may be performed using, or without, the generation AI, for example. For example, the story storage unit can input the child's geographical location information to the generation AI and cause the generation AI to save related stories.

[0091] In the AI ​​picture book system, the story storage unit analyzes the child's social media activity and stores related stories when saving. The story storage unit analyzes the child's social media activity and stores related stories when saving. For example, the story storage unit stores stories related to characters or themes that the child talks about on social media. The story storage unit can also store stories related to photos and videos that the child has shared on social media. Furthermore, the story storage unit can store stories related to influencers or celebrities that the child follows on social media. This allows stories related to the child to be stored. Some or all of the above-described processing in the story storage unit may be performed using, or without, the generation AI, for example. For example, the story storage unit can input the child's social media activity data into the generation AI and cause the generation AI to store related stories.

[0092] In the AI ​​picture book system, the input unit estimates a child's emotions and adjusts the input method based on the estimated child's emotions. The input unit estimates a child's emotions and adjusts the input method based on the estimated child's emotions. For example, if the child is nervous, the input unit provides a simple and intuitive input method. If the child is relaxed, the input unit can also provide detailed input options. Furthermore, if the child is excited, the input unit can also provide a visually appealing input method. This makes it possible to provide an input method suitable for children. Some or all of the above-mentioned processing in the input unit may be performed using, or without, a generation AI. For example, the input unit may input the child's emotion data into the generation AI and have the generation AI adjust the input method.

[0093] In the AI ​​picture book system, when an input unit inputs, the input unit refers to the child's past input history and presents the optimal input method. When inputting, the input unit refers to the child's past input history and presents the optimal input method. For example, the input unit preferentially presents input methods (voice, text, etc.) that the child has used in the past. The input unit can also present related input options based on the content the child has previously input. Furthermore, the input unit can present the most efficient input method from the child's past input history. This makes it possible to provide the optimal input method for the child. Some or all of the above-mentioned processing in the input unit may be performed using, or without, a generation AI. For example, the input unit can input the child's input history data to the generation AI and have the generation AI present the optimal input method.

[0094] In the AI ​​picture book system, the input unit estimates a child's emotions and determines input priorities based on the estimated child's emotions. The input unit estimates a child's emotions and determines input priorities based on the estimated child's emotions. For example, if a child is nervous, the input unit prioritizes the simplest and most reassuring input method. The input unit can also prioritize detailed input options if a child is relaxed. Furthermore, the input unit can prioritize visually appealing input methods if a child is excited. This makes it possible to provide an input method that is suitable for children. Some or all of the above-described processing in the input unit may be performed using, or without, a generation AI. For example, the input unit can input child's emotion data into the generation AI and have the generation AI determine the input priorities.

[0095] In the AI ​​picture book system, when an input unit inputs, the input unit considers the child's device information and presents the optimal input method. When an input unit inputs, the input unit considers the child's device information and presents the optimal input method. For example, if a child is using a smartphone, the input unit provides an input method that matches the screen size. Also, if a child is using a tablet, the input unit can provide an input method optimized for a large screen. Furthermore, if a child is using a smartwatch, the input unit can provide an input method that is simple and highly visible. This makes it possible to provide the optimal input method for a child. Some or all of the above-described processing in the input unit may be performed using, or without, a generation AI. For example, the input unit may input the child's device information to the generation AI and have the generation AI present the optimal input method.

[0096] In the AI ​​picture book system, a prompt generation unit estimates a child's emotions and adjusts the way in which prompts are expressed based on the estimated child's emotions. The prompt generation unit estimates a child's emotions and adjusts the way in which prompts are expressed based on the estimated child's emotions. For example, if a child is nervous, the prompt generation unit generates a simple and easy-to-understand prompt. If a child is relaxed, the prompt generation unit can also generate a prompt that includes detailed explanations. Furthermore, if a child is excited, the prompt generation unit can also generate a visually appealing prompt. This makes it possible to provide prompts that are appropriate for the child. Some or all of the above-described processing in the prompt generation unit may be performed using, or without, a generation AI. For example, the prompt generation unit may input child's emotion data into the generation AI and cause the generation AI to adjust the way in which prompts are expressed.

[0097] In the AI ​​picture book system, when generating a prompt, the prompt generation unit references the child's past conversation history to generate the optimal prompt. When generating a prompt, the prompt generation unit references the child's past conversation history to generate the optimal prompt. For example, the prompt generation unit includes a favorite character that the child has talked about in the past in the prompt. The prompt generation unit can also incorporate themes or topics in which the child has previously shown interest into the prompt. Furthermore, the prompt generation unit can incorporate episodes or events that the child has talked about in the past as part of the prompt. This makes it possible to provide the optimal prompt for the child. Some or all of the above-mentioned processing in the prompt generation unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the prompt generation unit may input the child's conversation history data into the generation AI and cause the generation AI to generate the optimal prompt.

[0098] In the AI ​​picture book system, the prompt generation unit estimates a child's emotions and determines the priority of prompts based on the estimated child's emotions. The prompt generation unit estimates a child's emotions and determines the priority of prompts based on the estimated child's emotions. For example, if a child is nervous, the prompt generation unit prioritizes the simplest and most reassuring prompts. The prompt generation unit can also prioritize detailed prompts if a child is relaxed. Furthermore, the prompt generation unit can prioritize visually appealing prompts if a child is excited. This makes it possible to provide prompts that are appropriate for the child. Some or all of the above-described processing in the prompt generation unit may be performed using, or without, a generation AI. For example, the prompt generation unit may input child's emotion data into the generation AI and have the generation AI determine the priority of prompts.

[0099] In the AI ​​picture book system, the prompt generation unit generates a relevant prompt by taking into account the child's geographical location information when generating a prompt. The prompt generation unit generates a relevant prompt by taking into account the child's geographical location information when generating a prompt. For example, the prompt generation unit includes famous places and scenery in the area where the child lives in the prompt. Also, if the child is traveling, the prompt generation unit can incorporate the culture and famous places of the travel destination into the prompt. Furthermore, the prompt generation unit can reflect the history and geography of the area where the child is studying at school in the prompt. This makes it possible to provide prompts related to the area. Some or all of the above-mentioned processing in the prompt generation unit may be performed using, or without, a generation AI, for example. For example, the prompt generation unit can input the child's geographical location information into the generation AI and cause the generation AI to generate a relevant prompt. === Hard Collateral 1-1 === Each of the multiple elements including the story generation unit, option presentation unit, branching unit, and story storage unit described above is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the story generation unit is realized by the processor 46 of the smart device 14 and analyzes conversations with the child to generate a story. The option presentation unit presents options using the display 40A of the smart device 14. The branching unit is realized by the specific processing unit 290 of the data processing device 12 and branches the story based on the options. The story storage unit stores the story in the storage 32 of the data processing device 12. === Hard Collateral 1-2 === Each of the multiple elements including the story generation unit, choice presentation unit, branching unit, and story storage unit described above is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the story generation unit is realized by the processor 46 of the smart glasses 214 and analyzes a conversation with the child to generate a story. The choice presentation unit presents choices using the display of the smart glasses 214. The branching unit is realized by the specific processing unit 290 of the data processing device 12 and branches the story based on the choices. The story storage unit stores the story in the storage 32 of the data processing device 12. === Hard Collateral 1-3 === Each of the multiple elements including the story generation unit, choice presentation unit, branching unit, and story storage unit described above is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the story generation unit is realized by the processor 46 of the headset type terminal 314 and analyzes the conversation with the child to generate a story. The choice presentation unit presents choices using the display 343 of the headset type terminal 314. The branching unit is realized by the specific processing unit 290 of the data processing device 12 and branches the story based on the choices. The story storage unit stores the story in the storage 32 of the data processing device 12. === Hard Collateral 1-4 === Each of the multiple elements including the story generation unit, choice presentation unit, branching unit, and story storage unit described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the story generation unit is realized by the processor 46 of the robot 414 and analyzes a conversation with the child to generate a story. The choice presentation unit presents choices using the display of the robot 414. The branching unit is realized by the specific processing unit 290 of the data processing device 12 and branches the story based on the choices. The story storage unit stores the story in the storage 32 of the data processing device 12.

[0100] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0101] The AI ​​picture book system's story generation unit can estimate a child's emotions and adjust the behavior and dialogue of the story characters based on the estimated emotions. For example, if a child is sad, the character will offer comforting words. If the child is excited, the character will act as if they are enjoying an adventure together. Furthermore, if the child is relaxed, the character will engage in calming dialogue. This allows the story characters to act in a way that is in tune with the child's emotions.

[0102] The AI ​​picture book system's story generation unit can analyze a child's past selection history and personalize the story progression. For example, it can present similar options based on options the child has previously chosen. It can also eliminate options the child has avoided in the past and present new options. It can also provide a story progression based on the child's preferences and interests from their past selection history. This allows it to provide a story progression that is optimal for each child.

[0103] The AI ​​picture book system's story generation unit can estimate a child's emotions and adjust the background music and sound effects of the story based on the estimated emotions. For example, if a child is excited, fast-paced music can be played. If a child is relaxed, calm music can be played. Furthermore, if a child is sad, comforting music can be played. This allows the atmosphere of the story to be adjusted to match the child's emotions.

[0104] The story generation section of the AI ​​picture book system can reference a child's learning history and incorporate educational elements into the story. For example, it can generate a story that allows a child to review what they have learned in the past. It can also provide stories related to learning themes that interest a child. It can also generate stories of an appropriate level of difficulty depending on the child's learning progress. This makes it possible to support a child's learning through stories.

[0105] The AI ​​picture book system's story generator can estimate a child's emotions and adjust the visual effects of the story based on the estimated emotions. For example, if a child is excited, vivid colors and dynamic effects can be used. If a child is relaxed, calm colors and quiet effects can be used. Furthermore, if a child is sad, calm colors and comforting effects can be used. This allows the visual effects of the story to be adjusted to match the child's emotions.

[0106] The AI ​​picture book system's story generation section can take into account the child's geographical location information and incorporate local culture and famous places into the story. For example, famous places and scenery from the area where the child lives can appear in the story. Also, if the child is traveling, the culture and famous places of the destination can be incorporated into the story. Furthermore, the history and geography of the area the child is studying at school can be reflected in the story. This allows the system to provide stories that are relevant to the area.

[0107] The AI ​​picture book system's story generation unit can estimate a child's emotions and adjust the facial expressions and movements of the story characters based on the estimated emotions. For example, if a child is sad, the character will make a comforting expression. If the child is excited, the character will move more actively. Furthermore, if the child is relaxed, the character can move more calmly. This allows the story characters to make expressions and movements that are in line with the child's emotions.

[0108] The AI ​​picture book system's story generation section can analyze a child's social media activity and incorporate related topics into the story. For example, it can feature characters and themes that a child talks about on social media. It can also incorporate photos and videos that a child has shared on social media as part of the story. It can also include influencers and celebrities that a child follows on social media. This allows the story to reflect topics relevant to the child.

[0109] The AI ​​picture book system's story generation unit can estimate a child's emotions and adjust the story's pace based on the estimated emotions. For example, if a child is excited, the story can be sped up to create a fast-paced story. Alternatively, if a child is relaxed, the story can be slowed down to maintain a relaxed atmosphere. Furthermore, if a child is tired, the story's pace can be adjusted to provide shorter episodes. This allows the system to provide a story progression that is appropriate for each child.

[0110] The story generation section of the AI ​​picture book system analyzes the child's past conversation history and can incorporate episodes and events that the child has talked about into the story. For example, a favorite character that the child has talked about in the past can appear in the story. It can also incorporate themes and topics that the child has previously shown interest in into the story. It can also incorporate episodes and events that the child has talked about in the past as part of the story. This makes it possible to provide a personalized story for the child.

[0111] The processing flow of the second embodiment will be briefly explained below.

[0112] Step 1: The story generation unit analyzes the conversation with the child and generates a story. For example, the story generation unit converts what the child says into text data using voice recognition technology, and generates a story based on that text data. The generation AI can also be used to generate story prompts based on the child's conversation. For example, if a child asks, "What adventure awaits me today?" the generation AI generates a prompt such as, "Today, you will have an adventure where you meet a dragon in a magical forest." Step 2: The option presentation unit presents options based on the story generated by the story generation unit. For example, the option presentation unit presents options such as "Choose the next path to take" as the story progresses. The generation AI can also be used to dynamically generate options based on the child's choices. For example, if the child selects "Choose the left path," the generation AI will present a new option such as "What awaits on the left path?" Step 3: The branching unit branches the story based on the options presented by the option presentation unit. For example, the branching unit changes the progress of the story depending on the option selected by the child. Alternatively, a generation AI can be used to dynamically generate branching storylines based on the options. For example, if the child selects "fight the dragon," the generation AI generates a branching story such as "the battle with the dragon begins." Step 4: The story storage unit saves the story branched by the branching unit. For example, the story storage unit can save a story that has been read once as digital data, allowing it to be read again later. The generation AI can also be used to dynamically determine the format and location of the story to be saved. For example, the generation AI can highlight and save important scenes in the story.

[0113] 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.

[0114] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of the generative AI include a neural network (NN) and a neural network (NN). 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 (e.g., still image data or video data). 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 one or more data formats of voice data, text data, image data, etc. 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 may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0115] 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.

[0116] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0117] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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).

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0127] 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. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0128] 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.

[0129] 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.

[0130] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0131] 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.

[0132] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0133] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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).

[0139] 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.

[0140] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0141] 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.

[0142] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0143] 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 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0144] 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.

[0145] 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.

[0146] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0147] 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.

[0148] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0149] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0150] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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).

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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 a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0160] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. 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 the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0161] 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.

[0162] 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.

[0163] 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 including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as audio data, text data, and image 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0164] 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.

[0165] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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).

[0170] 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.

[0171] 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."

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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.

[0182] 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.

[0183] 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.

[0184] [Explanation of symbols]

[0185] 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 story generation unit that analyzes conversations with children and generates stories; an option presentation unit that presents options based on the story generated by the story generation unit; a branching unit that branches the story based on the options presented by the option presenting unit; a story storage unit that stores the story branched by the branching unit; A system characterized by:

2. Equipped with an input section for entering the child's name The system of claim 1 .

3. A prompt generator is provided to generate story prompts. The system of claim 1 .

4. The option presentation unit Present your child with choices as the story unfolds The system of claim 1 .

5. The branch portion is Branching story based on choices The system of claim 1 .

6. The story storage unit Save a story once you've read it The system of claim 1 .

7. The story generation unit Estimate the child's emotions and adjust the tone and theme of the story based on those emotions. The system of claim 1 .

8. The story generation unit Analyze your child's conversation history to personalize the story The system of claim 1 .

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