System

Abstract

A system in accordance with an embodiment is directed to generating customized stories and illustrations based on user prompts.SOLUTION: A system according to an embodiment includes a prompt input unit, a text generation unit, and an illustration generation unit. The prompt input unit receives a prompt from a user. The text generation unit generates text of a story on the basis of the prompt received by the prompt input unit. The illustration generation unit generates an illustration based on the text generated by the text generation 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 generate customized picture books in real time that meet the individual preferences and needs of users.

[0005] The system according to the embodiment aims to generate customized stories and illustrations based on user prompts. [Means for solving the problem]

[0006] A system according to an embodiment includes a prompt input unit, a text generation unit, and an illustration generation unit. The prompt input unit receives prompts from a user. The text generation unit generates story text based on the prompts received by the prompt input unit. The illustration generation unit generates illustrations based on the text generated by the text generation unit. [Effects of the Invention]

[0007] An embodiment of the system can generate customized stories and illustrations based on user prompts. [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) A customized picture book generation system according to an embodiment of the present invention uses a generation AI to automatically generate a customized picture book containing text and illustrations based on prompts (theme, characters, setting, etc.) provided by a user. This allows the customized picture book generation system to create a bespoke story in real time that matches a child's preferences and mood at the time, turning storytime into a more personalized, interactive, and enjoyable experience.

[0029] A customized picture book generation system according to an embodiment includes a prompt input unit, a text generation unit, and an illustration generation unit. The prompt input unit receives prompts from a user. For example, the user inputs prompts such as "A pirate adventure," "A brave pirate," or "Going on a journey in search of treasure." The text generation unit generates story text based on the prompts received by the prompt input unit. For example, the generation AI generates a story about a brave pirate and his companions going on a journey in search of treasure based on the prompts. The illustration generation unit generates illustrations based on the text generated by the text generation unit. For example, the generation AI generates illustrations of the brave pirate and his companions, a treasure map, a pirate ship, and the like, in accordance with the content of the story. This allows the customized picture book generation system to automatically generate a customized picture book based on the user's prompts.

[0030] The prompt input unit allows the generation AI to automatically generate related questions in response to a prompt and generate a more detailed story by providing the user with additional information. For example, after a prompt is input, the prompt input unit allows the generation AI to automatically generate related questions and request additional information from the user. For example, it may ask a question such as, "What is the pirate's name?" The prompt input unit also allows the generation AI to generate a more detailed story by providing additional information from the user. For example, if the user answers, "The pirate's name is Captain Black," the generation AI will customize the story based on that information. This allows the generation AI to generate questions relevant to the user and generate a more detailed story.

[0031] The prompt input unit can automatically suggest music or sound effects related to the theme selected by the user when the prompt is input, thereby enhancing the atmosphere of the story. For example, the prompt input unit automatically suggests music related to the theme selected by the user when the prompt is input. For example, the prompt input unit suggests the sounds of the sea or a ship for a pirate adventure. The prompt input unit can also suggest sound effects related to the theme selected by the user. For example, in a scene where a treasure map is found, the prompt input unit suggests the sound of discovery. In this way, music or sound effects related to the theme selected by the user can be suggested, enhancing the atmosphere of the story.

[0032] The prompt input unit can refer to the history of stories previously created by the user when inputting a prompt and automatically suggest related elements. For example, the prompt input unit can refer to the history of stories previously created by the user when inputting a prompt and automatically suggest related characters and settings. For example, it can reintroduce characters that appeared in previous stories. The prompt input unit can also suggest a new story plot based on the history of stories previously created by the user. For example, it can suggest a new adventure as a continuation of a previous adventure. This makes it possible to refer to the user's past story history and suggest related elements.

[0033] The text generation unit can generate a more personalized story by taking into account the user's past reading history or preferences. For example, the text generation unit uses a generation AI to analyze the user's past reading history and generate a story based on that data. For example, it can reflect the user's favorite genres and themes. The text generation unit can also adjust the content of the story by taking into account the user's preferences. For example, it can reflect the user's favorite character personalities and story developments. This allows for a more personalized story to be generated by taking into account the user's past reading history and preferences.

[0034] The text generator can provide different writing style or word choice options for the user to select from. For example, the generation AI can provide different writing style or word choice options for the user to select from. For example, the text generator can select a formal or casual writing style. The text generator can also generate a story based on the writing style and word choice selected by the user. For example, the tone and tempo of the story can be adjusted to match the writing style selected by the user. This allows different writing style and word choice options to be provided for the user to select from.

[0035] The text generation unit can incorporate elements from different cultures or regions to provide a story from a global perspective. For example, the generation AI can incorporate elements from different cultures and regions to generate a story from a global perspective. For example, it can reflect the traditions and customs of different countries. The text generation unit can also customize the story based on the culture or region selected by the user. For example, it can generate a story that incorporates Japanese culture or a story that reflects Western traditions. This allows it to incorporate elements from different cultures and regions to provide a story from a global perspective.

[0036] The text generator can incorporate historical facts or scientific knowledge related to the theme selected by the user. For example, the generation AI can incorporate historical facts related to the theme selected by the user. For example, a pirate adventure story can reflect the actual history of pirates. The text generator can also incorporate scientific knowledge related to the theme selected by the user. For example, a space exploration story can reflect the latest scientific discoveries. This makes it possible to incorporate historical facts or scientific knowledge related to the theme selected by the user.

[0037] The illustration generation unit can provide options for different art styles or techniques and allow the user to select from them. For example, the generation AI can provide options for different art styles and techniques and allow the user to select from them. For example, the illustration generation unit can select a watercolor or anime style. The illustration generation unit can also generate an illustration based on the art style or technique selected by the user. For example, the color and details of the illustration can be adjusted to match the style selected by the user. This allows options for different art styles and techniques to be provided and allowed the user to select from them.

[0038] The illustration generation unit can refer to artwork or photographs related to the theme selected by the user. For example, the generation AI of the illustration generation unit refers to artwork related to the theme selected by the user and generates an illustration that reflects that style. For example, for a pirate adventure, marine paintings are used as reference. The illustration generation unit can also refer to photographs related to the theme selected by the user. For example, a photograph of a pirate ship is used as reference to generate an illustration. This allows artwork or photographs related to the theme selected by the user to be used as reference.

[0039] The illustration generation unit can generate a 3D model or animation related to a theme selected by the user. For example, the illustration generation unit generates a 3D model related to the theme selected by the user using a generation AI, and creates an illustration based on that model. For example, the illustration generation unit generates a 3D model of a pirate ship. The illustration generation unit can also generate animation related to the theme selected by the user. For example, it animates a scene of a pirate adventure. This makes it possible to generate a 3D model or animation related to the theme selected by the user.

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

[0041] The prompt input unit can automatically suggest related educational elements based on the prompt entered by the user. For example, if the user enters "dinosaur adventure," the prompt input unit can suggest scientific facts and historical background about dinosaurs. Alternatively, if the user enters "space exploration," the prompt input unit can suggest the latest scientific discoveries and astronomical knowledge about space. This allows the system to automatically suggest educational elements related to the theme selected by the user, adding depth to the story.

[0042] The prompt input unit can suggest related social or ethical themes based on the prompt entered by the user. For example, if the user enters "a story of friendship," the prompt input unit can suggest themes about the importance of friendship and the value of trust. Alternatively, if the user enters "an environmental protection adventure," the prompt input unit can suggest themes about the importance of environmental protection and sustainable living. This allows the system to suggest social or ethical themes related to the theme selected by the user and add depth to the story.

[0043] The prompt input unit can automatically suggest related cultural elements based on the prompt entered by the user. For example, if the user enters "Japanese legends," the prompt input unit can suggest Japanese traditions, customs, and historical background. Also, if the user enters "African adventures," the prompt input unit can suggest African culture, customs, and historical background. This allows the system to automatically suggest cultural elements related to the theme selected by the user, adding depth to the story.

[0044] The prompt input unit can automatically suggest related psychological elements based on the prompt entered by the user. For example, if the user enters "horror story," the prompt input unit can suggest elements about the psychology of fear and how to overcome it. Also, if the user enters "self-growth story," the prompt input unit can suggest psychological elements about self-growth and self-development. This automatically suggests psychological elements related to the theme selected by the user, making it possible to add depth to the story.

[0045] The prompt input unit can automatically suggest related philosophical elements based on the prompt entered by the user. For example, if the user enters "a story about searching for the meaning of life," the prompt input unit can suggest philosophical elements about the meaning of life and the significance of existence. Also, if the user enters "a story about freedom and destiny," the prompt input unit can suggest philosophical elements about free will and destiny. This allows philosophical elements related to the theme selected by the user to be automatically suggested, adding depth to the story.

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

[0047] Step 1: The prompt input unit receives a prompt from the user. For example, the user inputs a prompt such as "A pirate adventure," "A brave pirate," or "Go on a journey in search of treasure." Step 2: The text generator generates story text based on the prompts received by the prompt input unit. For example, the generator generates a story about a brave pirate and his companions going on a journey in search of treasure based on the prompts. Step 3: The illustration generation unit generates illustrations based on the text generated by the text generation unit. For example, the AI ​​generates illustrations of brave pirates and their companions, treasure maps, pirate ships, and other elements to fit the story.

[0048] (Example 2) A customized picture book generation system according to an embodiment of the present invention uses a generation AI to automatically generate a customized picture book containing text and illustrations based on prompts (theme, characters, setting, etc.) provided by a user. This allows the customized picture book generation system to create a bespoke story in real time that matches a child's preferences and mood at the time, turning storytime into a more personalized, interactive, and enjoyable experience.

[0049] A customized picture book generation system according to an embodiment includes a prompt input unit, a text generation unit, and an illustration generation unit. The prompt input unit receives prompts from a user. For example, the user inputs prompts such as "A pirate adventure," "A brave pirate," or "Going on a journey in search of treasure." The text generation unit generates story text based on the prompts received by the prompt input unit. For example, the generation AI generates a story about a brave pirate and his companions going on a journey in search of treasure based on the prompts. The illustration generation unit generates illustrations based on the text generated by the text generation unit. For example, the generation AI generates illustrations of the brave pirate and his companions, a treasure map, a pirate ship, and the like, in accordance with the content of the story. This allows the customized picture book generation system to automatically generate a customized picture book based on the user's prompts.

[0050] The prompt input unit can analyze the tone or speed of the user's voice and adjust the tone and tempo of the story based on the user's emotional state. For example, the prompt input unit analyzes the tone and speed of the voice through a microphone when the user inputs a prompt. For example, if the user is excited, the prompt input unit can speed up the tempo of the story to increase tension. Also, if the user is calm, the prompt input unit can calm the tone of the story to create a relaxed atmosphere. This makes it possible to adjust the tone and tempo of the story based on the user's emotional state.

[0051] The prompt input unit allows the generation AI to automatically generate related questions in response to a prompt and generate a more detailed story by providing the user with additional information. For example, after a prompt is input, the prompt input unit allows the generation AI to automatically generate related questions and request additional information from the user. For example, it may ask a question such as, "What is the pirate's name?" The prompt input unit also allows the generation AI to generate a more detailed story by providing additional information from the user. For example, if the user answers, "The pirate's name is Captain Black," the generation AI will customize the story based on that information. This allows the generation AI to generate questions relevant to the user and generate a more detailed story.

[0052] The prompt input unit can use the emotion estimation function to analyze the emotion the user is feeling when inputting a prompt and adjust the story theme and character personality based on that emotion. For example, the prompt input unit analyzes the user's emotion when inputting a prompt and adjusts the story theme based on that emotion. For example, if the user is sad, it selects an encouraging theme. The prompt input unit can also adjust the character personality based on the user's emotion. For example, if the user is happy, it sets the character to have a cheerful and fun personality. This makes it possible to adjust the story theme and character personality based on the user's emotion.

[0053] The prompt input unit can automatically suggest music or sound effects related to the theme selected by the user when the prompt is input, thereby enhancing the atmosphere of the story. For example, the prompt input unit automatically suggests music related to the theme selected by the user when the prompt is input. For example, the prompt input unit suggests the sounds of the sea or a ship for a pirate adventure. The prompt input unit can also suggest sound effects related to the theme selected by the user. For example, in a scene where a treasure map is found, the prompt input unit suggests the sound of discovery. In this way, music or sound effects related to the theme selected by the user can be suggested, enhancing the atmosphere of the story.

[0054] The prompt input unit can refer to the history of stories previously created by the user when inputting a prompt and automatically suggest related elements. For example, the prompt input unit can refer to the history of stories previously created by the user when inputting a prompt and automatically suggest related characters and settings. For example, it can reintroduce characters that appeared in previous stories. The prompt input unit can also suggest a new story plot based on the history of stories previously created by the user. For example, it can suggest a new adventure as a continuation of a previous adventure. This makes it possible to refer to the user's past story history and suggest related elements.

[0055] The prompt input unit can use the emotion estimation function to analyze the user's emotions in real time when inputting a prompt and make suggestions to elicit positive emotions. For example, the prompt input unit can analyze the user's emotions in real time when inputting a prompt and make suggestions to elicit positive emotions. For example, it can display an encouraging message. Furthermore, if the user is feeling emotionally down, the prompt input unit can also suggest a story theme to cheer them up. For example, it can suggest an encouraging story. In this way, the user's emotions can be analyzed in real time and suggestions to elicit positive emotions can be made.

[0056] The text generation unit can generate a more personalized story by taking into account the user's past reading history or preferences. For example, the text generation unit uses a generation AI to analyze the user's past reading history and generate a story based on that data. For example, it can reflect the user's favorite genres and themes. The text generation unit can also adjust the content of the story by taking into account the user's preferences. For example, it can reflect the user's favorite character personalities and story developments. This allows for a more personalized story to be generated by taking into account the user's past reading history and preferences.

[0057] The text generator can provide different writing style or word choice options for the user to select from. For example, the generation AI can provide different writing style or word choice options for the user to select from. For example, the text generator can select a formal or casual writing style. The text generator can also generate a story based on the writing style and word choice selected by the user. For example, the tone and tempo of the story can be adjusted to match the writing style selected by the user. This allows different writing style and word choice options to be provided for the user to select from.

[0058] The text generation unit can use the emotion estimation function to analyze the user's emotional response to each scene in the generated story and adjust the development of the story. For example, the text generation unit analyzes the user's emotional response to each scene in the generated story and adjusts the development of the story based on that data. For example, scenes with low emotion scores are modified. The text generation unit can also change the development of the story based on the user's emotional response. For example, if the user is moved by a particular scene, an additional scene is generated to enhance that emotion. This makes it possible to analyze the user's emotional response and adjust the development of the story.

[0059] The text generation unit can incorporate elements from different cultures or regions to provide a story from a global perspective. For example, the generation AI can incorporate elements from different cultures and regions to generate a story from a global perspective. For example, it can reflect the traditions and customs of different countries. The text generation unit can also customize the story based on the culture or region selected by the user. For example, it can generate a story that incorporates Japanese culture or a story that reflects Western traditions. This allows it to incorporate elements from different cultures and regions to provide a story from a global perspective.

[0060] The text generator can incorporate historical facts or scientific knowledge related to the theme selected by the user. For example, the generation AI can incorporate historical facts related to the theme selected by the user. For example, a pirate adventure story can reflect the actual history of pirates. The text generator can also incorporate scientific knowledge related to the theme selected by the user. For example, a space exploration story can reflect the latest scientific discoveries. This makes it possible to incorporate historical facts or scientific knowledge related to the theme selected by the user.

[0061] The text generation unit can use the emotion estimation function to analyze the user's emotional response to each scene of the generated story in real time and adjust the development of the story. For example, the text generation unit analyzes the user's emotional response to each scene of the generated story in real time and adjusts the development of the story based on the data. For example, it modifies scenes with low emotion scores. The text generation unit can also change the development of the story based on the user's emotional response. For example, if the user is moved by a particular scene, it generates an additional scene to enhance that emotion. This makes it possible to analyze the user's emotional response in real time and adjust the development of the story.

[0062] The illustration generation unit can provide options for different art styles or techniques and allow the user to select from them. For example, the generation AI can provide options for different art styles and techniques and allow the user to select from them. For example, the illustration generation unit can select a watercolor or anime style. The illustration generation unit can also generate an illustration based on the art style or technique selected by the user. For example, the color and details of the illustration can be adjusted to match the style selected by the user. This allows options for different art styles and techniques to be provided and allowed the user to select from them.

[0063] The illustration generation unit can use the emotion estimation function to analyze the user's emotional response to the generated illustration and adjust the details of the illustration. For example, the illustration generation unit analyzes the user's emotional response to the generated illustration and adjusts the details of the illustration based on that data. For example, it corrects parts with low emotion scores. The illustration generation unit can also change the color and details of the illustration based on the user's emotional response. For example, if the user likes a particular color, it can emphasize that color. This allows the user's emotional response to be analyzed and the details of the illustration to be adjusted.

[0064] The illustration generation unit can refer to artwork or photographs related to the theme selected by the user. For example, the generation AI of the illustration generation unit refers to artwork related to the theme selected by the user and generates an illustration that reflects that style. For example, for a pirate adventure, marine paintings are used as reference. The illustration generation unit can also refer to photographs related to the theme selected by the user. For example, a photograph of a pirate ship is used as reference to generate an illustration. This allows artwork or photographs related to the theme selected by the user to be used as reference.

[0065] The illustration generation unit can generate a 3D model or animation related to a theme selected by the user. For example, the illustration generation unit generates a 3D model related to the theme selected by the user using a generation AI, and creates an illustration based on that model. For example, the illustration generation unit generates a 3D model of a pirate ship. The illustration generation unit can also generate animation related to the theme selected by the user. For example, it animates a scene of a pirate adventure. This makes it possible to generate a 3D model or animation related to the theme selected by the user.

[0066] The illustration generation unit can use the emotion estimation function to analyze the user's emotional response to the generated illustration in real time and adjust the details of the illustration. For example, the illustration generation unit analyzes the user's emotional response to the generated illustration in real time and adjusts the details of the illustration based on the data. For example, it corrects parts with low emotion scores. The illustration generation unit can also change the color and details of the illustration based on the user's emotional response. For example, if the user likes a particular color, it can emphasize that color. This allows the user's emotional response to be analyzed in real time and the details of the illustration to be adjusted.

[0067] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0068] The prompt input unit can automatically suggest related educational elements based on the prompt entered by the user. For example, if the user enters "dinosaur adventure," the prompt input unit can suggest scientific facts and historical background about dinosaurs. Alternatively, if the user enters "space exploration," the prompt input unit can suggest the latest scientific discoveries and astronomical knowledge about space. This allows the system to automatically suggest educational elements related to the theme selected by the user, adding depth to the story.

[0069] The prompt input unit can suggest related social or ethical themes based on the prompt entered by the user. For example, if the user enters "a story of friendship," the prompt input unit can suggest themes about the importance of friendship and the value of trust. Alternatively, if the user enters "an environmental protection adventure," the prompt input unit can suggest themes about the importance of environmental protection and sustainable living. This allows the system to suggest social or ethical themes related to the theme selected by the user and add depth to the story.

[0070] The prompt input unit can automatically suggest related cultural elements based on the prompt entered by the user. For example, if the user enters "Japanese legends," the prompt input unit can suggest Japanese traditions, customs, and historical background. Also, if the user enters "African adventures," the prompt input unit can suggest African culture, customs, and historical background. This allows the system to automatically suggest cultural elements related to the theme selected by the user, adding depth to the story.

[0071] The prompt input unit can automatically suggest related psychological elements based on the prompt entered by the user. For example, if the user enters "horror story," the prompt input unit can suggest elements about the psychology of fear and how to overcome it. Also, if the user enters "self-growth story," the prompt input unit can suggest psychological elements about self-growth and self-development. This automatically suggests psychological elements related to the theme selected by the user, making it possible to add depth to the story.

[0072] The prompt input unit can automatically suggest related philosophical elements based on the prompt entered by the user. For example, if the user enters "a story about searching for the meaning of life," the prompt input unit can suggest philosophical elements about the meaning of life and the significance of existence. Also, if the user enters "a story about freedom and destiny," the prompt input unit can suggest philosophical elements about free will and destiny. This allows philosophical elements related to the theme selected by the user to be automatically suggested, adding depth to the story.

[0073] The text generator can estimate the user's emotions and adjust the ending of the story based on the emotions. For example, if the user is sad, the text generator can suggest a happy ending. Alternatively, if the user is excited, the text generator can suggest a thrilling ending. This allows the ending of the story to be adjusted based on the user's emotions, providing a more emotional story.

[0074] The text generator can estimate the user's emotions and adjust the behavior of the story character based on the emotions. For example, if the user is feeling anxious, the text generator can adjust the character's behavior to give a sense of security. Also, if the user is happy, the text generator can adjust the character's behavior to be more joyful. This allows the character's behavior to be adjusted based on the user's emotions, providing a more emotionally appealing story.

[0075] The text generator can estimate the user's emotions and adjust the story setting based on the emotions. For example, if the user wants to relax, the text generator can suggest a calm setting. Alternatively, if the user wants to be adventurous, the text generator can suggest an exciting setting. This allows the story setting to be adjusted based on the user's emotions, providing a more emotionally appealing story.

[0076] The text generator can estimate the user's emotions and adjust the story theme based on the emotions. For example, if the user is depressed, the text generator can suggest an encouraging theme. If the user is excited, the text generator can suggest an adventure theme. This allows the story theme to be adjusted based on the user's emotions, providing a more emotional story.

[0077] The text generator can estimate the user's emotions and adjust the tone of the story based on the emotions. For example, if the user is sad, the text generator can suggest a cheerful tone. If the user is happy, the text generator can suggest a happy tone. This allows the tone of the story to be adjusted based on the user's emotions, providing a more emotional story.

[0078] The processing flow of the second embodiment will be briefly explained below.

[0079] Step 1: The prompt input unit receives a prompt from the user. For example, the user inputs a prompt such as "A pirate adventure," "A brave pirate," or "Go on a journey in search of treasure." Step 2: The text generator generates story text based on the prompts received by the prompt input unit. For example, the generator generates a story about a brave pirate and his companions going on a journey in search of treasure based on the prompts. Step 3: The illustration generation unit generates illustrations based on the text generated by the text generation unit. For example, the AI ​​generates illustrations of brave pirates and their companions, treasure maps, pirate ships, and other elements to fit the story.

[0080] 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.

[0081] 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.

[0082] 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.

[0083] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0084] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0085] 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.

[0086] 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.

[0087] 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.

[0088] 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).

[0089] 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.

[0090] 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.

[0091] 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.

[0092] 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.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0099] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0100] 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.

[0101] 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.

[0102] 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.

[0103] 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).

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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).

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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).

[0133] 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.

[0134] 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."

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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]

[0147] 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 prompt input unit that accepts a prompt from a user; a text generation unit that generates a story text based on the prompt received by the prompt input unit; an illustration generation unit that generates an illustration based on the text generated by the text generation unit; A system characterized by:

2. The prompt input unit Analyzing the tone or rate of the user's voice and adjusting the tone or tempo of the story based on the user's emotional state.

2. The system of claim 1.

3. The prompt input unit Automatically suggesting music or sound effects related to the user's selected theme upon prompt entry to enhance the atmosphere of the story 2. The system of claim 1.

4. The text generation unit Taking into account the user's past reading history or preferences to generate a more personalized version of the story 2. The system of claim 1.

5. The text generation unit Analyzing the user's emotional response to each scene of the generated story and adjusting the development of the story.

2. The system of claim 1.

6. The illustration generation unit Generate a more personalized illustration by taking into account the preferences or style of the user's past illustrations.

2. The system of claim 1.

7. The illustration generation unit Analyzing the user's emotional response to the generated illustration and adjusting the details of the illustration.

2. The system of claim 1.

8. The illustration generation unit Analyzing the user's emotional response to the generated illustration in real time and adjusting the details of the illustration 2. The system of claim 1.

Images