System

Abstract

An object of a system according to an exemplary embodiment is to create an individually customized picture book based on information provided by a user.SOLUTION: A system includes a story creation part and an illustration creation part. The story creation unit creates a story of the picture book based on the information provided by the user. The illustration creation unit creates an illustration according to the story created by the story creation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional techniques have had the problem that it is difficult to create an individually customized picture book based on information provided by a user.

[0005] The system according to the embodiment aims to create an individually customized picture book based on information provided by the user. [Means for solving the problem]

[0006] The system according to the embodiment includes a story creation unit and an illustration creation unit. The story creation unit creates a story for a picture book based on information provided by a user. The illustration creation unit creates illustrations that match the story created by the story creation unit. [Effects of the Invention]

[0007] The system according to the embodiment can create an individually customized picture book based on information provided by the user. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The picture book creation system according to the embodiment of the present invention is a system in which a generation AI helps create a picture book and works with a child to create a favorite picture book. This allows parents and children to spend fun time creating an original picture book.

[0029] A picture book creation system according to an embodiment includes a story creation unit and an illustration creation unit. The story creation unit creates a story for a picture book based on information provided by a user. For example, when a user inputs information such as a child's name, favorite animal, and favorite place, the generation AI combines that information to generate an original story. The generation AI receives input from a user in the form of prompts containing instructions on what the user wants the generation AI to do, and the generation AI generates a story based on the prompts. The illustration creation unit creates illustrations that match the story. For example, the generation AI automatically draws illustrations of characters and backgrounds that appear in the story. The user can review the generated illustrations and request corrections as necessary. The generation AI receives input from a user in the form of prompts containing the content of the story and characteristics of the characters, and the generation AI generates illustrations based on the prompts. This allows the picture book creation system to create a story and illustrations for a picture book based on information provided by a user.

[0030] The story creation unit can learn the user's past story creation history and suggest stories that match the user's preferences. For example, the story creation unit uses a generation AI to analyze stories created by the user in the past and extract common themes and characters. This allows the unit to suggest new stories that reflect the user's preferences. This makes it possible to suggest stories that match the user's preferences.

[0031] The story creation unit can incorporate elements from different cultures and languages ​​to generate stories from an international perspective. For example, the generation AI can learn fairy tales and legends from different cultures and generate stories that incorporate those elements. For example, it can propose a story that combines Japanese folk tales and European fairy tales. This allows it to generate stories from an international perspective.

[0032] The story creation unit can make parts of the story interactive and introduce a format in which the story branches depending on the options the user selects. For example, the story creation unit introduces a format in which the generation AI presents options in the middle of the story and the story branches depending on the option the user selects. For example, it sets up a scene in which the character chooses where to go next. This makes it possible to introduce a format in which the story branches depending on the options the user selects.

[0033] The illustration creation unit learns the user's past illustration creation history and can suggest illustrations that match the user's preferences. For example, the illustration creation unit uses a generation AI to analyze illustrations created by the user in the past and extract common styles and themes. This allows it to suggest new illustrations that reflect the user's preferences. This makes it possible to suggest illustrations that match the user's preferences.

[0034] The illustration creation unit can incorporate different art styles and techniques to provide a variety of visual expressions. For example, the generation AI can learn different art styles and generate illustrations that incorporate them. For example, it can propose watercolor-style or comic-style illustrations. This allows for a variety of visual expressions.

[0035] The illustration creation unit can make parts of the illustration interactive and introduce a function that allows users to change the color or shape. For example, the generation AI can make parts of the illustration interactive and provide a function that allows users to change the color or shape. For example, it can make it possible to change the color of a character's clothing or the background scenery. This makes it possible to provide an interactive function that allows users to change the color or shape.

[0036] The layout creation unit can learn the user's past layout creation history and propose layouts that suit the user's preferences. For example, the layout creation unit uses a generation AI to analyze layouts created by the user in the past and extract common designs and layouts. This allows the unit to propose new layouts that reflect the user's preferences. This makes it possible to propose layouts that suit the user's preferences.

[0037] The layout creation unit can provide different design templates and allow the user to select one. For example, the layout creation unit may provide multiple design templates using the generation AI and allow the user to select their preferred template. For example, templates such as classic, modern, and colorful may be prepared. This allows the user to select different design templates.

[0038] The layout creation unit can make part of the layout interactive and introduce a function that allows the user to change the arrangement and design. For example, the layout creation unit provides a function where the generation AI makes part of the layout interactive and allows the user to change the arrangement of text and illustrations. For example, it allows elements to be moved by drag and drop. This makes it possible to provide an interactive function where the user can change the arrangement and design.

[0039] The customization unit learns the user's past customization history and can propose customizations that match the user's preferences. For example, the customization unit uses a generation AI to analyze the user's past customizations and extract common changes and patterns. This allows the customization unit to propose new customizations that reflect the user's preferences. This makes it possible to propose customizations that match the user's preferences.

[0040] The customization unit can provide different materials and formats and allow the user to select from them. For example, the customization unit allows the generation AI to provide multiple materials and formats and the user to select their preferred material or format. For example, the user can select the paper quality or type of binding. This allows the user to select different materials and formats.

[0041] The customization unit can make some of the customization interactive and introduce a function that allows users to check changes in real time. For example, the customization unit can make some of the customization interactive using a generation AI, providing a function that allows users to check changes to text and illustrations in real time. For example, it can make it possible to move elements by drag and drop. This makes it possible to provide an interactive function that allows users to check changes in real time.

[0042] The printing unit can learn the user's past printing history and suggest printing options that match the user's preferences. For example, the printing unit uses a generation AI to analyze the printing options the user has used in the past and extract common selections and patterns. This allows the printing unit to suggest new printing options that reflect the user's preferences. This makes it possible to suggest printing options that match the user's preferences.

[0043] The printing department can provide different paper quality and binding options to allow users to choose. For example, the generation AI can provide multiple paper quality and binding options and allow users to select their preferred option. For example, glossy paper or matte paper, hard cover or soft cover, etc. This allows users to choose different paper quality and binding options.

[0044] The printing department can make parts of the print interactive and introduce a function that allows users to preview in real time. For example, the printing department can use generative AI to make parts of the print interactive, providing a function that allows users to check the print preview of text and illustrations in real time. For example, it can allow elements to be moved by drag and drop. This allows users to provide interactive functions that allow them to preview in real time.

[0045] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0046] The picture book creation system also includes an audio narration unit. Based on the story created by the generation AI, the audio narration unit synthesizes the voice of a professional narrator to generate audio narration for each page of the picture book. For example, it can generate audio files containing character lines and narration that users can use when reading the picture book aloud. This allows the system to provide picture books that can be enjoyed both visually and aurally.

[0047] The picture book creation system also includes an educational content section. This section can add content containing educational elements based on the story created by the generative AI. For example, by weaving scientific knowledge or historical facts into the story, it can provide a picture book that children can enjoy while learning. This allows the creation of a picture book that combines entertainment and education.

[0048] The picture book creation system further includes a character customization unit. The character customization unit provides a function that allows users to freely customize the appearance and personality of characters appearing in the picture book. For example, the user can select the character's hairstyle, clothing, and personality traits. This allows users to create their own original characters and have them appear in the picture book.

[0049] The picture book creation system also includes a background music section. This section automatically selects appropriate background music based on the story created by the generation AI, and can provide music that corresponds to each page of the picture book. For example, exciting music is selected for adventure scenes, and moving music for emotional scenes. This allows the system to provide a picture book that can be enjoyed both visually and aurally.

[0050] The picture book creation system further includes an interactive game section. The interactive game section can provide mini-games in which users can participate based on the story created by the generation AI. For example, it can provide a game in which users select options to determine the progress of a character's adventure, or a game in which the story progresses by solving puzzles. This allows the system to provide a picture book in which users can become more deeply involved in the story.

[0051] The processing flow of the first embodiment will be briefly explained below.

[0052] Step 1: The story creation unit creates a picture book story based on information provided by the user. For example, when information such as a child's name, favorite animal, and favorite place is entered, the generation AI combines that information to generate an original story. The input to the generation AI is a prompt containing instructions on what the user wants the generation AI to do, and the generation AI generates a story based on that prompt. Step 2: The illustration creation unit creates illustrations that match the story. For example, the generation AI automatically draws illustrations of the characters and backgrounds that appear in the story. The user can check the generated illustrations and request corrections if necessary. The input to the generation AI is prompts that include the content of the story and the characteristics of the characters, and the generation AI generates illustrations based on those prompts.

[0053] (Example 2) The picture book creation system according to the embodiment of the present invention is a system in which a generation AI helps create a picture book and works with a child to create a favorite picture book. This allows parents and children to spend fun time creating an original picture book.

[0054] A picture book creation system according to an embodiment includes a story creation unit and an illustration creation unit. The story creation unit creates a story for a picture book based on information provided by a user. For example, when a user inputs information such as a child's name, favorite animal, and favorite place, the generation AI combines that information to generate an original story. The generation AI receives input from a user in the form of prompts containing instructions on what the user wants the generation AI to do, and the generation AI generates a story based on the prompts. The illustration creation unit creates illustrations that match the story. For example, the generation AI automatically draws illustrations of characters and backgrounds that appear in the story. The user can review the generated illustrations and request corrections as necessary. The generation AI receives input from a user in the form of prompts containing the content of the story and characteristics of the characters, and the generation AI generates illustrations based on the prompts. This allows the picture book creation system to create a story and illustrations for a picture book based on information provided by a user.

[0055] The story creation unit can learn the user's past story creation history and suggest stories that match the user's preferences. For example, the story creation unit uses a generation AI to analyze stories created by the user in the past and extract common themes and characters. This allows the unit to suggest new stories that reflect the user's preferences. This makes it possible to suggest stories that match the user's preferences.

[0056] The story creation unit analyzes the user's voice and facial expressions in real time, and can develop a story that suits the user's emotions. For example, the story creation unit uses a generation AI to analyze the user's tone of voice and facial expressions to determine whether the user is enjoying themselves. For example, if there are many smiles, the unit generates a story that includes a humorous development. This allows the story to develop in accordance with the user's emotions.

[0057] The story creation unit can use the emotion estimation function to estimate a child's emotions and generate a story that matches the child's emotions. For example, the generation AI analyzes the child's facial expressions and voice to estimate emotions. For example, if a child is excited, it will generate a story that includes many action scenes. This makes it possible to generate a story that matches the child's emotions.

[0058] The story creation unit can incorporate elements from different cultures and languages ​​to generate stories from an international perspective. For example, the generation AI can learn fairy tales and legends from different cultures and generate stories that incorporate those elements. For example, it can propose a story that combines Japanese folk tales and European fairy tales. This allows it to generate stories from an international perspective.

[0059] The story creation unit can make parts of the story interactive and introduce a format in which the story branches depending on the options the user selects. For example, the story creation unit introduces a format in which the generation AI presents options in the middle of the story and the story branches depending on the option the user selects. For example, it sets up a scene in which the character chooses where to go next. This makes it possible to introduce a format in which the story branches depending on the options the user selects.

[0060] The story creation unit uses the emotion estimation function to analyze the emotions of parents and children in real time and can suggest story branching that corresponds to their emotions. For example, the generation AI in the story creation unit analyzes the facial expressions and voices of parents and children to estimate their emotions. For example, if the parent and child are having fun, it will suggest a story branch that includes a humorous development. This makes it possible to suggest story branching that corresponds to the emotions of the parent and child.

[0061] The illustration creation unit learns the user's past illustration creation history and can suggest illustrations that match the user's preferences. For example, the illustration creation unit uses a generation AI to analyze illustrations created by the user in the past and extract common styles and themes. This allows it to suggest new illustrations that reflect the user's preferences. This makes it possible to suggest illustrations that match the user's preferences.

[0062] The illustration creation unit can analyze the user's voice and facial expressions in real time and generate illustrations that correspond to the user's emotions. For example, the illustration creation unit uses a generation AI to analyze the user's tone of voice and facial expressions to determine whether the user is enjoying themselves. For example, if there are many smiles, it generates illustrations using bright colors. This allows it to generate illustrations that correspond to the user's emotions.

[0063] The illustration creation unit uses an emotion estimation function to estimate a child's emotions and generate illustrations that match the child's emotions. For example, the generation AI analyzes the child's facial expressions and voice to estimate emotions. For example, if a child is excited, it generates illustrations that include many action scenes. This makes it possible to generate illustrations that match the child's emotions.

[0064] The illustration creation unit can incorporate different art styles and techniques to provide a variety of visual expressions. For example, the generation AI can learn different art styles and generate illustrations that incorporate them. For example, it can propose watercolor-style or comic-style illustrations. This allows for a variety of visual expressions.

[0065] The illustration creation unit can make parts of the illustration interactive and introduce a function that allows users to change the color or shape. For example, the generation AI can make parts of the illustration interactive and provide a function that allows users to change the color or shape. For example, it can make it possible to change the color of a character's clothing or the background scenery. This makes it possible to provide an interactive function that allows users to change the color or shape.

[0066] The illustration creation unit uses an emotion estimation function to analyze the emotions of parents and children in real time and suggest changes to the illustration based on their emotions. For example, the generation AI in the illustration creation unit analyzes the facial expressions and voices of the parent and child to estimate their emotions. For example, if the parent and child are having fun, it suggests changing the illustration to use bright colors. This makes it possible to suggest changes to the illustration based on the emotions of the parent and child.

[0067] The layout creation unit can learn the user's past layout creation history and propose layouts that suit the user's preferences. For example, the layout creation unit uses a generation AI to analyze layouts created by the user in the past and extract common designs and layouts. This allows the unit to propose new layouts that reflect the user's preferences. This makes it possible to propose layouts that suit the user's preferences.

[0068] The layout creation unit can analyze the user's voice and facial expressions in real time and generate a layout that corresponds to the user's emotions. For example, the layout creation unit uses a generation AI to analyze the user's tone of voice and facial expressions to determine whether the user is enjoying themselves. For example, if there are many smiles, a layout using bright colors is generated. This allows the creation of a layout that corresponds to the user's emotions.

[0069] The layout creation unit can use the emotion estimation function to estimate a child's emotions and generate a layout that matches the child's emotions. For example, the layout creation unit uses a generation AI to analyze a child's facial expressions and voice to estimate their emotions. For example, if a child is excited, it will generate a layout that includes many action scenes. This makes it possible to generate a layout that matches the child's emotions.

[0070] The layout creation unit can provide different design templates and allow the user to select one. For example, the layout creation unit may provide multiple design templates using the generation AI and allow the user to select their preferred template. For example, templates such as classic, modern, and colorful may be prepared. This allows the user to select different design templates.

[0071] The layout creation unit can make part of the layout interactive and introduce a function that allows the user to change the arrangement and design. For example, the layout creation unit provides a function where the generation AI makes part of the layout interactive and allows the user to change the arrangement of text and illustrations. For example, it allows elements to be moved by drag and drop. This makes it possible to provide an interactive function where the user can change the arrangement and design.

[0072] The layout creation unit uses an emotion estimation function to analyze the emotions of parents and children in real time and propose layout changes according to their emotions. For example, the layout creation unit uses a generation AI to analyze the facial expressions and voices of parents and children and predict their emotions. For example, if the parent and child are having fun, it proposes a layout change using bright colors. This makes it possible to propose layout changes according to the emotions of the parent and child.

[0073] The customization unit learns the user's past customization history and can propose customizations that match the user's preferences. For example, the customization unit uses a generation AI to analyze the user's past customizations and extract common changes and patterns. This allows the customization unit to propose new customizations that reflect the user's preferences. This makes it possible to propose customizations that match the user's preferences.

[0074] The customization unit analyzes the user's voice and facial expressions in real time and can customize the app according to the user's emotions. For example, the customization unit uses a generation AI to analyze the user's tone of voice and facial expressions to determine whether the user is enjoying themselves. For example, if the user smiles a lot, the customization will use bright colors. This allows customization according to the user's emotions.

[0075] The customization unit uses the emotion estimation function to estimate a child's emotions and propose customizations that match the child's emotions. For example, the generation AI analyzes the child's facial expressions and voice to estimate emotions. For example, if a child is excited, the customization unit proposes customizations that include many action scenes. This makes it possible to propose customizations that match the child's emotions.

[0076] The customization unit can provide different materials and formats and allow the user to select from them. For example, the customization unit allows the generation AI to provide multiple materials and formats and the user to select their preferred material or format. For example, the user can select the paper quality or type of binding. This allows the user to select different materials and formats.

[0077] The customization unit can make some of the customization interactive and introduce a function that allows users to check changes in real time. For example, the customization unit can make some of the customization interactive using a generation AI, providing a function that allows users to check changes to text and illustrations in real time. For example, it can make it possible to move elements by drag and drop. This makes it possible to provide an interactive function that allows users to check changes in real time.

[0078] The customization unit uses an emotion estimation function to analyze the emotions of parents and children in real time and suggest customization changes based on their emotions. For example, the customization unit uses a generation AI to analyze the facial expressions and voices of parents and children to estimate their emotions. For example, if a parent and child are having fun, it suggests a customization change to use bright colors. This makes it possible to suggest customization changes based on the emotions of parents and children.

[0079] The printing unit can learn the user's past printing history and suggest printing options that match the user's preferences. For example, the printing unit uses a generation AI to analyze the printing options the user has used in the past and extract common selections and patterns. This allows the printing unit to suggest new printing options that reflect the user's preferences. This makes it possible to suggest printing options that match the user's preferences.

[0080] The printing unit can analyze the user's voice and facial expressions in real time and suggest printing options that correspond to the user's emotions. For example, the printing unit's generation AI can analyze the user's tone of voice and facial expressions to determine whether the user is enjoying themselves. For example, if the user smiles a lot, it can suggest printing options that use bright colors. This makes it possible to suggest printing options that correspond to the user's emotions.

[0081] The printing department can use the emotion estimation function to estimate a child's emotions and suggest printing options that match the child's emotions. For example, the generation AI analyzes a child's facial expressions and voice to estimate emotions. For example, if a child is excited, the printing department will suggest printing options that include many action scenes. This allows the printing department to suggest printing options that match the child's emotions.

[0082] The printing department can provide different paper quality and binding options to allow users to choose. For example, the generation AI can provide multiple paper quality and binding options and allow users to select their preferred option. For example, glossy paper or matte paper, hard cover or soft cover, etc. This allows users to choose different paper quality and binding options.

[0083] The printing department can make parts of the print interactive and introduce a function that allows users to preview in real time. For example, the printing department can use generative AI to make parts of the print interactive, providing a function that allows users to check the print preview of text and illustrations in real time. For example, it can allow elements to be moved by drag and drop. This allows users to provide interactive functions that allow them to preview in real time.

[0084] The printing department can use the emotion estimation function to analyze the emotions of parents and children in real time and suggest changes to printing options based on their emotions. For example, the generation AI in the printing department can analyze the facial expressions and voices of parents and children to estimate their emotions. For example, if the parent and child are having fun, it can suggest changing the printing options to use bright colors. This makes it possible to suggest changes to printing options based on the emotions of the parent and child.

[0085] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0086] The picture book creation system also includes an audio narration unit. Based on the story created by the generation AI, the audio narration unit synthesizes the voice of a professional narrator to generate audio narration for each page of the picture book. For example, it can generate audio files containing character lines and narration that users can use when reading the picture book aloud. This allows the system to provide picture books that can be enjoyed both visually and aurally.

[0087] The picture book creation system also includes an educational content section. This section can add content containing educational elements based on the story created by the generative AI. For example, by weaving scientific knowledge or historical facts into the story, it can provide a picture book that children can enjoy while learning. This allows the creation of a picture book that combines entertainment and education.

[0088] The picture book creation system can further use the emotion estimation function to adjust the difficulty of the story based on the user's emotions. For example, if the user is relaxed, a story including a difficult problem-solving scene is generated, and if the user is tired, an easy, relaxing story is generated. In this way, the difficulty of the story can be adjusted according to the user's emotions.

[0089] The picture book creation system can also use the emotion estimation function to change the genre of the story based on the user's emotions. For example, if the user is excited, a story with many action and adventure elements can be generated, and if the user is calm, a heartwarming family story can be generated. This allows the story genre to be changed according to the user's emotions.

[0090] The picture book creation system can further use the emotion estimation function to adjust the pace of the story based on the user's emotions. For example, if the user is in a hurry, a short, fast-paced story can be generated, and if the user wants to enjoy it at a leisurely pace, a detailed, slow-paced story can be generated. This allows the pace of the story to be adjusted according to the user's emotions.

[0091] The picture book creation system can further use the emotion estimation function to change the ending of the story based on the user's emotions. For example, if the user is sad, a story with a happy ending is generated, and if the user is having fun, a story with a surprise ending is generated. This allows the ending of the story to be changed according to the user's emotions.

[0092] The picture book creation system further includes a character customization unit. The character customization unit provides a function that allows users to freely customize the appearance and personality of characters appearing in the picture book. For example, the user can select the character's hairstyle, clothing, and personality traits. This allows users to create their own original characters and have them appear in the picture book.

[0093] The picture book creation system also includes a background music section. This section automatically selects appropriate background music based on the story created by the generation AI, and can provide music that corresponds to each page of the picture book. For example, exciting music is selected for adventure scenes, and moving music for emotional scenes. This allows the system to provide a picture book that can be enjoyed both visually and aurally.

[0094] The picture book creation system further includes an interactive game section. The interactive game section can provide mini-games in which users can participate based on the story created by the generation AI. For example, it can provide a game in which users select options to determine the progress of a character's adventure, or a game in which the story progresses by solving puzzles. This allows the system to provide a picture book in which users can become more deeply involved in the story.

[0095] The picture book creation system can further use the emotion estimation function to change the style of illustrations based on the user's emotions. For example, if the user is relaxed, it generates illustrations using soft colors, and if the user is excited, it generates illustrations using vivid colors. This allows the style of illustrations to be changed according to the user's emotions.

[0096] The processing flow of the second embodiment will be briefly explained below.

[0097] Step 1: The story creation unit creates a picture book story based on information provided by the user. For example, when information such as a child's name, favorite animal, and favorite place is entered, the generation AI combines that information to generate an original story. The input to the generation AI is a prompt containing instructions on what the user wants the generation AI to do, and the generation AI generates a story based on that prompt. Step 2: The illustration creation unit creates illustrations that match the story. For example, the generation AI automatically draws illustrations of the characters and backgrounds that appear in the story. The user can check the generated illustrations and request corrections if necessary. The input to the generation AI is prompts that include the content of the story and the characteristics of the characters, and the generation AI generates illustrations based on those prompts.

[0098] 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.

[0099] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0100] 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.

[0101] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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).

[0107] 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.

[0108] 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.

[0109] 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.

[0110] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0111] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0112] 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.

[0113] 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.

[0114] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0115] 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.

[0116] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] 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.

[0124] 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.

[0125] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0126] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0127] 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.

[0128] 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.

[0129] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0130] 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.

[0131] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0132] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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).

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0142] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0143] 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.

[0144] 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.

[0145] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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).

[0151] 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.

[0152] 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."

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0165] 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 creation unit that creates a story for a picture book based on information provided by a user; an illustration creation unit that creates illustrations that match the story created by the story creation unit; A system characterized by:

2. The story creation unit Incorporating elements from different cultures and languages ​​to create stories with an international perspective The system of claim 1 .

3. The illustration creation unit The system learns the user's past illustration creation history and proposes illustrations that match the user's preferences. The system of claim 1 .

4. The layout creation section Learn the user's past layout creation history and propose layouts that match the user's preferences The system of claim 1 .

5. The customization section is Learn the user's past customization history and suggest customizations that match the user's preferences The system of claim 1 .

6. The printing department Analyzing the user's voice and facial expressions in real time and suggesting printing options according to the user's emotions The system of claim 1 .

7. The story creation unit The voice and facial expression of the user are analyzed in real time, and a story is developed according to the emotions of the user. The system of claim 1 .

8. The illustration creation unit The voice and facial expression of the user are analyzed in real time, and the illustration is generated according to the emotion of the user. The system of claim 1 .

Images