System

Abstract

An object of the system according to the embodiment is to easily create an original story between a parent and a child and to perform narration with a voice of a friend.SOLUTION: A system according to an embodiment includes a keyword input unit, a story generation unit, a voice recording unit, and a narration generation unit. The keyword input unit receives a keyword input by a user. The story generation unit generates a story on the basis of the keyword received by the keyword input unit. The voice recording part records the voice of the mother. The narration generation unit generates narration by imitating the voice of the friend recorded by the voice recording unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has had the problem of making it difficult for parents and children to easily create original stories and have the parents narrate them in their own voices.

[0005] The system according to the embodiment aims to enable parents and children to easily create original stories and have the stories narrated in the parents' voices. [Means for solving the problem]

[0006] The system according to the embodiment includes a keyword input unit, a story generation unit, a voice recording unit, and a narration generation unit. The keyword input unit accepts keywords entered by a user. The story generation unit generates a story based on the keywords accepted by the keyword input unit. The voice recording unit records the voice of a parent. The narration generation unit generates a narration by imitating the voice of the parent recorded by the voice recording unit. [Effects of the Invention]

[0007] The system according to the embodiment allows parents and children to easily create original stories and have the stories narrated in the parents' voices. [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 AI ​​support service according to an embodiment of the present invention is a system that allows parents to easily create original animated picture books. This system uses a generation AI to instantly create an original story based on keywords entered by the user, and then generates an animated picture book by recording the parent's voice and narrating the story in a voice that mimics the parent's voice. This allows parents and children to spend creative time together and enjoy creating original animated picture books.

[0029] The AI ​​support service according to the embodiment includes a keyword input unit, a story generation unit, a voice recording unit, and a narration generation unit. The keyword input unit accepts keywords input by a user. For example, when a user inputs keywords such as "adventure," "animals," or "magic," the keyword input unit accepts these keywords. The story generation unit generates a story based on the keywords accepted by the keyword input unit. For example, the generation AI generates a story including elements of adventure, animals, and magic based on the keywords input by the user. The voice recording unit records a parent's voice. For example, when a parent records "Hello, this is my voice," the voice recording unit records that voice. The narration generation unit generates a narration by imitating the parent's voice recorded by the voice recording unit. For example, the generation AI analyzes the recorded parent's voice quality and generates a narration for the story by imitating that voice. This allows the AI ​​support service according to the embodiment to enable parents to easily create original animated picture books. For example, parents and children can choose a story theme together, and the AI ​​will generate a story based on that theme, narrated in the parent's voice, allowing parents and children to spend creative time together.

[0030] The story generation unit can generate a story based on a theme selected by parents and children. For example, if a parent and child select a theme of "sea adventure," the story generation unit generates a story based on that theme. For example, the generation AI generates a story that includes elements such as pirates, treasure hunts, and sea creatures based on keywords related to sea adventures. This can support collaborative work between parents and children. For example, by selecting a theme together and generating a story based on that theme, parents and children can spend creative time together.

[0031] The keyword input unit can refer to the user's past input history and suggest highly relevant stories. For example, the keyword input unit stores keywords previously entered by the user in a database, and when entering a new keyword, refers to that history to suggest highly relevant stories. For example, if a user who previously entered "adventure" and "pirate" now enters "treasure hunt," the generation AI will suggest a story that combines these elements. This makes it possible to suggest stories that are highly relevant to the user. For example, suggesting stories based on themes that the user has been interested in in the past can improve user satisfaction.

[0032] The keyword input unit generates a story preview in real time as keywords are input, allowing the user to check and adjust the content. For example, when a user inputs a keyword, the generation AI generates a story preview in real time and provides an interface that allows the user to add and modify keywords while checking the content. For example, if the user inputs "adventure" or "pirate," the generation AI immediately displays the beginning of the story, and if the user adds "treasure hunt," the preview is updated. This allows the user to check and adjust the content of the story in real time. For example, the user can add and modify keywords as the story progresses to create a more satisfying story.

[0033] The keyword input unit can be combined with voice recognition technology to allow parents to input keywords by voice. For example, the keyword input unit combines voice recognition technology with the generation AI to allow parents to input keywords by voice. For example, if a parent inputs "adventure" or "pirate" by voice, the generation AI converts that voice into text and generates a story. This allows parents to input keywords by voice. For example, parents can input keywords by voice without using their hands, making it easier to create stories.

[0034] The keyword input unit can automatically suggest related images and video clips when a keyword is entered, enhancing the visual elements of the story. For example, when a user enters a keyword, the generation AI automatically suggests related images and video clips, enhancing the visual elements of the story. For example, if the user enters "adventure" or "pirate," the generation AI will suggest images of a pirate ship or a treasure map. This can enhance the visual elements of the story. For example, a user can add images and video clips that match the content of the story, creating a more appealing animated picture book.

[0035] The narration generation unit can record a parent's voice multiple times and combine them to generate a more natural narration. For example, the narration generation unit can record a parent's voice multiple times, and the generation AI can combine them to generate a more natural narration. For example, if a parent records "hello" and "good night," the generation AI can combine those sounds to generate a narration. This allows for the generation of a more natural narration. For example, by combining multiple recordings depending on the scene in the story, a more natural and engaging narration can be provided.

[0036] The narration generation unit can not only imitate the parent's voice, but also record the voices of all family members and narrate using multiple voices. For example, the narration generation unit provides a function that records the voices of not only the parent but all family members, and the generation AI combines those voices to narrate. For example, the voices of the parent and child can be recorded, and the generation AI can combine those voices to narrate the story. This allows the narration to be performed using the voices of all family members. For example, by using different family members' voices for each character in the story, a more appealing animated picture book can be created.

[0037] The narration generation unit can automatically add background sounds and sound effects when imitating a parent's voice, generating a more realistic narration. For example, when imitating a parent's voice, the generation AI can automatically add background sounds and sound effects to generate a more realistic narration. For example, if a parent records "Hello, this is my voice," the generation AI can add birdsong and wind sounds to match the voice. This allows for the generation of a more realistic narration. For example, adding background sounds and sound effects according to the story scene can provide a more appealing narration for children.

[0038] The system can prompt interactive questions as the story progresses, encouraging dialogue between parents and children. For example, when a parent and child are creating a story together, the generative AI prompts interactive questions as the story progresses, encouraging dialogue between the parent and child. For example, the system prompts questions such as "What do you think will happen next?" midway through the story, allowing the parent and child to discuss as the story progresses. This encourages dialogue between parents and children and supports collaborative work. For example, parents and children can spend creative time discussing the progress of the story.

[0039] The system can add a timeline function that records collaborative work between parents and children and allows them to look back on it later. The system provides a timeline function that records collaborative work between parents and children, for example, when creating a story, and allows them to look back on it later. For example, the process of creating a story can be recorded on a timeline, and parents and children can look back on that process later. This allows parents and children to record collaborative work and look back on it later. For example, parents and children can think of ideas for the next story while looking back on the process of creating a story.

[0040] The system enables parents and children to collaborate online, and can add a function that allows them to create stories together with family members who are in remote locations. For example, the system provides a function that allows parents and children to collaborate online when creating a story, allowing them to create a story together with family members who are in remote locations. For example, a story can be created together with family members who are in remote locations via a video call. This makes it possible to create a story together with family members who are in remote locations. For example, a parent and child can create a story at home while collaborating with grandparents who are in remote locations via a video call, allowing the whole family to spend creative time together.

[0041] The system gamifies collaborative work between parents and children, introducing a mechanism that allows points to be earned as the story progresses. For example, when parents and children create a story together, the system gamifies collaborative work by introducing a mechanism that allows the generation AI to earn points as the story progresses. For example, points can be earned each time a scene in the story is completed. This allows parents and children to create stories while having fun. For example, parents and children can earn points as the story progresses, and spend creative time competing with each other.

[0042] The system can add a function to adjust the speed and pitch of the voice in customized narration. For example, the system provides an interface that allows the generation AI to adjust the speed and pitch of the voice in customized narration. For example, when a parent records "Hello, this is my voice," the generation AI adjusts the speed and pitch of that voice to generate narration. This allows the speed and pitch of the narration to be adjusted. For example, by adjusting the speed and pitch of the voice depending on the scene in the story, it is possible to provide narration that is more appealing to children.

[0043] The system can add a function to automatically generate narration in different languages ​​for customized narration. For example, the system provides a function for the generation AI to automatically generate narration in different languages ​​for customized narration. For example, if a parent records "Hello, this is my voice," the generation AI can generate narration in different languages, such as English or French, based on that voice. This allows for automatic generation of narration in different languages. For example, children can listen to stories in different languages ​​and use it as part of their language learning.

[0044] The system can automatically generate voices for different characters and narrate each character in a story in a different voice. For example, in customized narration, the system provides a function in which the generation AI automatically generates voices for different characters and narrates each character in a story in a different voice. For example, if a parent records "Hello, this is my voice," the generation AI can generate different character voices based on that voice and narrate the story. This allows narration in a different voice for each character in a story. For example, by using different character voices depending on the scene in the story, it is possible to create an animated picture book that is more appealing to children.

[0045] The system can automatically add background music and sound effects to generate more realistic narration. For example, in a customized narration, the generation AI automatically adds background music and sound effects to generate more realistic narration. For example, when a parent records "Hello, this is my voice," the generation AI adds background music and sound effects to match the voice. This allows for the generation of more realistic narration. For example, adding background music and sound effects according to the story scene can provide a more appealing narration for children.

[0046] The system can add a function that allows created animated picture books to be saved in the cloud and accessed synchronously from multiple devices. The system provides, for example, a function that allows created animated picture books to be saved in the cloud and accessed synchronously from multiple devices. For example, a parent can save an animated picture book created at home in the cloud and access it from a smartphone while on the go. This allows synchronous access from multiple devices. For example, a parent can save an animated picture book created at home in the cloud and access it from a smartphone while on the go, allowing the child to enjoy the animated picture book anytime, anywhere.

[0047] The system can add a function to download the created animated picture book to a device so that it can be played offline. The system provides, for example, a function to download the created animated picture book to a device so that it can be played offline. For example, a parent can download an animated picture book created at home to a smartphone and play it offline while on the go. This allows the animated picture book to be played offline. For example, a parent can download an animated picture book created at home to a smartphone and play it offline while on the go, so that the animated picture book can be enjoyed even in places without an internet connection.

[0048] The system can add a function that allows users to share the animated picture book they have created, so that they can enjoy it with family and friends. The system, for example, provides a function that allows users to share the animated picture book they have created, so that they can enjoy it with family and friends. For example, a parent can upload the animated picture book they have created to the cloud and send a sharing link to their family and friends. This allows the created animated picture book to be shared with family and friends. For example, a parent can upload the animated picture book they have created to the cloud and send a sharing link to their family and friends, so that they can enjoy the animated picture book together with family and friends who are far away.

[0049] The system can add a function that allows users to cast the animated picture book they created to a projector or smart TV and enjoy it on a large screen. The system provides a function that allows users to cast the animated picture book they created to a projector or smart TV and enjoy it on a large screen. For example, a parent can cast the animated picture book they created to a smart TV so that the whole family can enjoy it on a large screen. This allows users to enjoy the animated picture book they created on a large screen. For example, a parent can cast the animated picture book they created to a projector or smart TV so that the whole family can enjoy it on a large screen, providing a more immersive visual experience.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The system can add a timeline function that records the collaborative work between parents and children and allows them to look back on it later. For example, a timeline function is provided that allows parents and children to record the collaborative work of creating a story and look back on it later. For example, the process of creating a story can be recorded on a timeline, allowing parents and children to look back on the process later. This allows parents and children to record the collaborative work and look back on it later. For example, parents and children can think of ideas for the next story while looking back on the process of creating a story.

[0052] The system enables parents and children to collaborate online, and can add a function that allows them to create stories together with family members who are in remote locations. For example, when creating a story together, a function that allows parents and children to collaborate online can be provided, allowing them to create a story together with family members who are in remote locations. For example, a story can be created together with family members who are in remote locations via a video call. This makes it possible to create a story together with family members who are in remote locations. For example, a parent and child can create a story at home while collaborating with grandparents who are in remote locations via a video call, allowing the whole family to spend creative time together.

[0053] The system can gamify collaborative work between parents and children, introducing a mechanism that allows points to be earned as the story progresses. For example, when parents and children create a story together, a mechanism can be introduced that allows the generation AI to earn points as the story progresses, gamifying the collaborative work. For example, points can be earned as each scene in the story is completed. This allows parents and children to create stories while having fun. For example, parents and children can earn points as the story progresses, and spend creative time competing with each other.

[0054] The system can add a function that allows created animated picture books to be saved in the cloud and accessed synchronously from multiple devices. For example, a function is provided that allows created animated picture books to be saved in the cloud and accessed synchronously from multiple devices. For example, a parent can save an animated picture book created at home in the cloud and access it from a smartphone while on the go. This allows synchronous access from multiple devices. For example, a parent can save an animated picture book created at home in the cloud and access it from a smartphone while on the go, allowing the child to enjoy the animated picture book anytime, anywhere.

[0055] The system can add a function that allows users to cast the animated picture books they create onto a projector or smart TV to enjoy them on a large screen. For example, the system can provide a function that allows users to cast the animated picture books they create onto a projector or smart TV to enjoy them on a large screen. For example, parents can cast the animated picture books they create onto a smart TV so that the whole family can enjoy them on a large screen. This allows users to enjoy the animated picture books they create on a large screen. For example, parents can cast the animated picture books they create onto a projector or smart TV so that the whole family can enjoy them on a large screen, providing a more immersive visual experience.

[0056] The system can add a function to enable sharing of created animated picture books so that they can be enjoyed with family and friends. For example, a function to share created animated picture books can be provided so that they can be enjoyed with family and friends. For example, a parent can upload the animated picture book they created to the cloud and send a sharing link to their family and friends. This allows the created animated picture book to be shared with family and friends. For example, a parent can upload the animated picture book they created to the cloud and send a sharing link to their family and friends so that they can enjoy the animated picture book together, even with family and friends who are far away.

[0057] The processing flow of the first embodiment will be briefly explained below.

[0058] Step 1: The keyword input unit accepts keywords entered by the user. For example, if the user enters keywords such as "adventure," "animal," or "magic," the keyword input unit accepts these keywords. Step 2: The story generation unit generates a story based on the keywords received by the keyword input unit. For example, the AI ​​may generate a story that includes elements of adventure, animals, and magic based on keywords entered by the user. Step 3: The voice recording unit records the parent's voice. For example, the parent records "Hello, this is my voice," and the voice recording unit records that voice. Step 4: The narration generation unit generates narration by imitating the parent's voice recorded by the voice recording unit. For example, the generation AI analyzes the parent's voice quality in the recording and generates the story narration by imitating that voice.

[0059] (Example 2) The AI ​​support service according to an embodiment of the present invention is a system that allows parents to easily create original animated picture books. This system uses a generation AI to instantly create an original story based on keywords entered by the user, and then generates an animated picture book by recording the parent's voice and narrating the story in a voice that mimics the parent's voice. This allows parents and children to spend creative time together and enjoy creating original animated picture books.

[0060] The AI ​​support service according to the embodiment includes a keyword input unit, a story generation unit, a voice recording unit, and a narration generation unit. The keyword input unit accepts keywords input by a user. For example, when a user inputs keywords such as "adventure," "animals," or "magic," the keyword input unit accepts these keywords. The story generation unit generates a story based on the keywords accepted by the keyword input unit. For example, the generation AI generates a story including elements of adventure, animals, and magic based on the keywords input by the user. The voice recording unit records a parent's voice. For example, when a parent records "Hello, this is my voice," the voice recording unit records that voice. The narration generation unit generates a narration by imitating the parent's voice recorded by the voice recording unit. For example, the generation AI analyzes the recorded parent's voice quality and generates a narration for the story by imitating that voice. This allows the AI ​​support service according to the embodiment to enable parents to easily create original animated picture books. For example, parents and children can choose a story theme together, and the AI ​​will generate a story based on that theme, narrated in the parent's voice, allowing parents and children to spend creative time together.

[0061] The story generation unit can generate a story based on a theme selected by parents and children. For example, if a parent and child select a theme of "sea adventure," the story generation unit generates a story based on that theme. For example, the generation AI generates a story that includes elements such as pirates, treasure hunts, and sea creatures based on keywords related to sea adventures. This can support collaborative work between parents and children. For example, by selecting a theme together and generating a story based on that theme, parents and children can spend creative time together.

[0062] The narration generation unit can finely adjust the tone and emotional expression when imitating a parent's voice. The narration generation unit provides an interface that allows the generation AI to finely adjust the tone and emotional expression of the voice when imitating a parent's voice. For example, if a parent records "Hello, this is my voice," the generation AI adjusts the tone and emotion of that voice to generate narration. This allows for the generation of more natural and emotional narration. For example, by adjusting the tone and emotion of the voice depending on the scene in the story, it is possible to provide a narration that is more appealing to children.

[0063] The keyword input unit can refer to the user's past input history and suggest highly relevant stories. For example, the keyword input unit stores keywords previously entered by the user in a database, and when entering a new keyword, refers to that history to suggest highly relevant stories. For example, if a user who previously entered "adventure" and "pirate" now enters "treasure hunt," the generation AI will suggest a story that combines these elements. This makes it possible to suggest stories that are highly relevant to the user. For example, suggesting stories based on themes that the user has been interested in in the past can improve user satisfaction.

[0064] The keyword input unit generates a story preview in real time as keywords are input, allowing the user to check and adjust the content. For example, when a user inputs a keyword, the generation AI generates a story preview in real time and provides an interface that allows the user to add and modify keywords while checking the content. For example, if the user inputs "adventure" or "pirate," the generation AI immediately displays the beginning of the story, and if the user adds "treasure hunt," the preview is updated. This allows the user to check and adjust the content of the story in real time. For example, the user can add and modify keywords as the story progresses to create a more satisfying story.

[0065] The keyword input unit can use the emotion estimation function to generate a story that is easy to empathize with emotionally based on keywords entered by the user. For example, the keyword input unit uses the emotion estimation function to generate a story that is easy to empathize with emotionally based on keywords entered by the user. For example, if "adventure" or "friendship" is entered, the generation AI generates a story with emotional intensity. This makes it possible to generate a story that is easy to empathize with emotionally. For example, by generating a story based on a theme that is easy for the user to empathize with emotionally, user satisfaction can be improved.

[0066] The keyword input unit can be combined with voice recognition technology to allow parents to input keywords by voice. For example, the keyword input unit combines voice recognition technology with the generation AI to allow parents to input keywords by voice. For example, if a parent inputs "adventure" or "pirate" by voice, the generation AI converts that voice into text and generates a story. This allows parents to input keywords by voice. For example, parents can input keywords by voice without using their hands, making it easier to create stories.

[0067] The keyword input unit can automatically suggest related images and video clips when a keyword is entered, enhancing the visual elements of the story. For example, when a user enters a keyword, the generation AI automatically suggests related images and video clips, enhancing the visual elements of the story. For example, if the user enters "adventure" or "pirate," the generation AI will suggest images of a pirate ship or a treasure map. This can enhance the visual elements of the story. For example, a user can add images and video clips that match the content of the story, creating a more appealing animated picture book.

[0068] The keyword input unit uses the emotion estimation function to analyze the emotional response to keywords entered by the user in real time and can suggest the most suitable story. For example, when a user enters a keyword, the generation AI uses the emotion estimation function to analyze the emotional response to the keyword in real time and suggests the most suitable story. For example, if "adventure" or "friendship" is entered, the generation AI will suggest a story that is likely to resonate emotionally. This makes it possible to suggest the most suitable story based on the user's emotions. For example, by suggesting stories based on themes that users can easily empathize with emotionally, user satisfaction can be improved.

[0069] The narration generation unit can record a parent's voice multiple times and combine them to generate a more natural narration. For example, the narration generation unit can record a parent's voice multiple times, and the generation AI can combine them to generate a more natural narration. For example, if a parent records "hello" and "good night," the generation AI can combine those sounds to generate a narration. This allows for the generation of a more natural narration. For example, by combining multiple recordings depending on the scene in the story, a more natural and engaging narration can be provided.

[0070] The narration generation unit can use the emotion estimation function to analyze the emotional expressions in the parent's voice and generate an emotionally rich narration that matches the content of the story. For example, the narration generation unit records the parent's voice, and the generation AI uses the emotion estimation function to analyze the emotional expressions in the voice and generate an emotionally rich narration that matches the content of the story. For example, if the parent records "Hello, this is my voice," the generation AI analyzes the emotion in the voice and generates a narration that matches the emotion of the story. This makes it possible to generate an emotionally rich narration that matches the content of the story. For example, by adjusting the emotional expressions according to the scene in the story, it is possible to provide a narration that is more appealing to children.

[0071] The narration generation unit can not only imitate the parent's voice, but also record the voices of all family members and narrate using multiple voices. For example, the narration generation unit provides a function that records the voices of not only the parent but all family members, and the generation AI combines those voices to narrate. For example, the voices of the parent and child can be recorded, and the generation AI can combine those voices to narrate the story. This allows the narration to be performed using the voices of all family members. For example, by using different family members' voices for each character in the story, a more appealing animated picture book can be created.

[0072] The narration generation unit can automatically add background sounds and sound effects when imitating a parent's voice, generating a more realistic narration. For example, when imitating a parent's voice, the generation AI can automatically add background sounds and sound effects to generate a more realistic narration. For example, if a parent records "Hello, this is my voice," the generation AI can add birdsong and wind sounds to match the voice. This allows for the generation of a more realistic narration. For example, adding background sounds and sound effects according to the story scene can provide a more appealing narration for children.

[0073] The narration generation unit can analyze the emotional expressions in the parent's voice in real time using the emotion estimation function and generate the optimal narration. For example, the narration generation unit records the parent's voice, and the generation AI analyzes the emotional expressions in the voice in real time using the emotion estimation function to generate the optimal narration according to the content of the story. For example, if the parent records "Hello, this is my voice," the generation AI analyzes the emotion in the voice in real time and generates narration that matches the emotion of the story. This allows the optimal narration to be generated in real time. For example, by adjusting the emotional expressions in real time according to the scene in the story, it is possible to provide a narration that is more appealing to children.

[0074] The system can prompt interactive questions as the story progresses, encouraging dialogue between parents and children. For example, when a parent and child are creating a story together, the generative AI prompts interactive questions as the story progresses, encouraging dialogue between the parent and child. For example, the system prompts questions such as "What do you think will happen next?" midway through the story, allowing the parent and child to discuss as the story progresses. This encourages dialogue between parents and children and supports collaborative work. For example, parents and children can spend creative time discussing the progress of the story.

[0075] The system can add a timeline function that records collaborative work between parents and children and allows them to look back on it later. The system provides a timeline function that records collaborative work between parents and children, for example, when creating a story, and allows them to look back on it later. For example, the process of creating a story can be recorded on a timeline, and parents and children can look back on that process later. This allows parents and children to record collaborative work and look back on it later. For example, parents and children can think of ideas for the next story while looking back on the process of creating a story.

[0076] The system uses the emotion estimation function to analyze the emotional state of parents and children and suggests the optimal timing for progressing the story. For example, when a parent and child are creating a story together, the generation AI uses the emotion estimation function to analyze the emotional state of the parent and child and suggests the optimal timing for progressing the story. For example, when the parent and child are tired, the generation AI suggests taking a break. This allows the system to suggest the optimal timing for progressing the story based on the emotional state of the parent and child. For example, when the parent and child are having fun, the generation AI can suggest the next scene, making it possible to make the most of the creative time between parent and child.

[0077] The system enables parents and children to collaborate online, and can add a function that allows them to create stories together with family members who are in remote locations. For example, the system provides a function that allows parents and children to collaborate online when creating a story, allowing them to create a story together with family members who are in remote locations. For example, a story can be created together with family members who are in remote locations via a video call. This makes it possible to create a story together with family members who are in remote locations. For example, a parent and child can create a story at home while collaborating with grandparents who are in remote locations via a video call, allowing the whole family to spend creative time together.

[0078] The system gamifies collaborative work between parents and children, introducing a mechanism that allows points to be earned as the story progresses. For example, when parents and children create a story together, the system gamifies collaborative work by introducing a mechanism that allows the generation AI to earn points as the story progresses. For example, points can be earned each time a scene in the story is completed. This allows parents and children to create stories while having fun. For example, parents and children can earn points as the story progresses, and spend creative time competing with each other.

[0079] The system uses the emotion estimation function to analyze the emotional state of parents and children in real time and suggests the optimal story progression. For example, when a parent and child are creating a story together, the generation AI uses the emotion estimation function to analyze the emotional state of the parent and child in real time and suggests the optimal story progression. For example, when the parent and child are having fun, the generation AI suggests the next scene. This makes it possible to suggest the optimal story progression based on the emotional state of the parent and child. For example, when the parent and child are tired, the generation AI can suggest taking a break, allowing parents and children to make the most of their creative time.

[0080] The system can add a function to adjust the speed and pitch of the voice in customized narration. For example, the system provides an interface that allows the generation AI to adjust the speed and pitch of the voice in customized narration. For example, when a parent records "Hello, this is my voice," the generation AI adjusts the speed and pitch of that voice to generate narration. This allows the speed and pitch of the narration to be adjusted. For example, by adjusting the speed and pitch of the voice depending on the scene in the story, it is possible to provide narration that is more appealing to children.

[0081] The system can add a function to automatically generate narration in different languages ​​for customized narration. For example, the system provides a function for the generation AI to automatically generate narration in different languages ​​for customized narration. For example, if a parent records "Hello, this is my voice," the generation AI can generate narration in different languages, such as English or French, based on that voice. This allows for automatic generation of narration in different languages. For example, children can listen to stories in different languages ​​and use it as part of their language learning.

[0082] The system can analyze a child's emotional state using its emotion estimation function and generate optimal narration. For example, the system analyzes a child's emotional state and the generation AI generates narration that best suits that emotion. For example, when a child is having fun, the generation AI generates a bright and cheerful narration. This allows the system to generate optimal narration based on the child's emotional state. For example, when a child is tired, the generation AI generates a calm narration, providing a more relaxing listening experience for the child.

[0083] The system can automatically generate voices for different characters and narrate each character in a story in a different voice. For example, in customized narration, the system provides a function in which the generation AI automatically generates voices for different characters and narrates each character in a story in a different voice. For example, if a parent records "Hello, this is my voice," the generation AI can generate different character voices based on that voice and narrate the story. This allows narration in a different voice for each character in a story. For example, by using different character voices depending on the scene in the story, it is possible to create an animated picture book that is more appealing to children.

[0084] The system can automatically add background music and sound effects to generate more realistic narration. For example, in a customized narration, the generation AI automatically adds background music and sound effects to generate more realistic narration. For example, when a parent records "Hello, this is my voice," the generation AI adds background music and sound effects to match the voice. This allows for the generation of more realistic narration. For example, adding background music and sound effects according to the story scene can provide a more appealing narration for children.

[0085] The system can use its emotion estimation function to analyze a child's emotional state in real time and generate optimal narration. For example, the system can analyze a child's emotional state in real time and have the generation AI generate narration that best suits that emotion. For example, when a child is having fun, the generation AI generates a bright and cheerful narration. This allows the system to generate optimal narration based on the child's emotional state. For example, when a child is tired, the generation AI can generate a calm narration, providing a more relaxing listening experience for the child.

[0086] The system can add a function that allows created animated picture books to be saved in the cloud and accessed synchronously from multiple devices. The system provides, for example, a function that allows created animated picture books to be saved in the cloud and accessed synchronously from multiple devices. For example, a parent can save an animated picture book created at home in the cloud and access it from a smartphone while on the go. This allows synchronous access from multiple devices. For example, a parent can save an animated picture book created at home in the cloud and access it from a smartphone while on the go, allowing the child to enjoy the animated picture book anytime, anywhere.

[0087] The system can add a function to download the created animated picture book to a device so that it can be played offline. The system provides, for example, a function to download the created animated picture book to a device so that it can be played offline. For example, a parent can download an animated picture book created at home to a smartphone and play it offline while on the go. This allows the animated picture book to be played offline. For example, a parent can download an animated picture book created at home to a smartphone and play it offline while on the go, so that the animated picture book can be enjoyed even in places without an internet connection.

[0088] The system can analyze a child's emotional state using an emotion estimation function and make suggestions to play an animated picture book at the optimal timing. For example, the system analyzes a child's emotional state and the generation AI makes suggestions to play an animated picture book at the optimal timing for that emotion. For example, the generation AI suggests playing an animated picture book when a child is having fun. This makes it possible to make suggestions to play an animated picture book at the optimal timing based on a child's emotional state. For example, the generation AI can suggest playing an animated picture book when a child is relaxed, providing a more effective auditory experience for the child.

[0089] The system can add a function that allows users to share the animated picture book they have created, so that they can enjoy it with family and friends. The system, for example, provides a function that allows users to share the animated picture book they have created, so that they can enjoy it with family and friends. For example, a parent can upload the animated picture book they have created to the cloud and send a sharing link to their family and friends. This allows the created animated picture book to be shared with family and friends. For example, a parent can upload the animated picture book they have created to the cloud and send a sharing link to their family and friends, so that they can enjoy the animated picture book together with family and friends who are far away.

[0090] The system can add a function that allows users to cast the animated picture book they created to a projector or smart TV and enjoy it on a large screen. The system provides a function that allows users to cast the animated picture book they created to a projector or smart TV and enjoy it on a large screen. For example, a parent can cast the animated picture book they created to a smart TV so that the whole family can enjoy it on a large screen. This allows users to enjoy the animated picture book they created on a large screen. For example, a parent can cast the animated picture book they created to a projector or smart TV so that the whole family can enjoy it on a large screen, providing a more immersive visual experience.

[0091] The system can use its emotion estimation function to analyze a child's emotional state in real time and make suggestions to play an animated picture book at the optimal timing. For example, the system can analyze a child's emotional state in real time and make suggestions to play an animated picture book at the optimal timing for that emotion using the generation AI. For example, the generation AI can suggest playing an animated picture book when a child is having fun. This makes it possible to make suggestions to play an animated picture book at the optimal timing based on a child's emotional state. For example, the generation AI can suggest playing an animated picture book when a child is relaxed, providing a more effective auditory experience for the child.

[0092] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0093] The system can add a timeline function that records the collaborative work between parents and children and allows them to look back on it later. For example, a timeline function is provided that allows parents and children to record the collaborative work of creating a story and look back on it later. For example, the process of creating a story can be recorded on a timeline, allowing parents and children to look back on the process later. This allows parents and children to record the collaborative work and look back on it later. For example, parents and children can think of ideas for the next story while looking back on the process of creating a story.

[0094] The system uses the emotion estimation function to analyze the emotional state of parents and children and suggests the optimal timing for progressing through the story. For example, when parents and children are creating a story together, the generation AI uses the emotion estimation function to analyze the emotional state of the parent and child and suggests the optimal timing for progressing through the story. For example, if the parent and child are tired, the generation AI will suggest taking a break. This allows the system to suggest the optimal timing for progressing through the story based on the emotional state of the parent and child. For example, if the generation AI suggests the next scene when the parent and child are having fun, it can make the most of the creative time between parent and child.

[0095] The system enables parents and children to collaborate online, and can add a function that allows them to create stories together with family members who are in remote locations. For example, when creating a story together, a function that allows parents and children to collaborate online can be provided, allowing them to create a story together with family members who are in remote locations. For example, a story can be created together with family members who are in remote locations via a video call. This makes it possible to create a story together with family members who are in remote locations. For example, a parent and child can create a story at home while collaborating with grandparents who are in remote locations via a video call, allowing the whole family to spend creative time together.

[0096] The system can gamify collaborative work between parents and children, introducing a mechanism that allows points to be earned as the story progresses. For example, when parents and children create a story together, a mechanism can be introduced that allows the generation AI to earn points as the story progresses, gamifying the collaborative work. For example, points can be earned as each scene in the story is completed. This allows parents and children to create stories while having fun. For example, parents and children can earn points as the story progresses, and spend creative time competing with each other.

[0097] The system can use its emotion estimation function to analyze a child's emotional state and generate the optimal narration. For example, the system analyzes a child's emotional state and generates the narration that best suits that emotion. For example, when a child is having fun, the system generates a bright and cheerful narration. This allows the system to generate the optimal narration based on the child's emotional state. For example, when a child is tired, the system generates a calm narration, providing a more relaxing listening experience for the child.

[0098] The system can add a function that allows created animated picture books to be saved in the cloud and accessed synchronously from multiple devices. For example, a function is provided that allows created animated picture books to be saved in the cloud and accessed synchronously from multiple devices. For example, a parent can save an animated picture book created at home in the cloud and access it from a smartphone while on the go. This allows synchronous access from multiple devices. For example, a parent can save an animated picture book created at home in the cloud and access it from a smartphone while on the go, allowing the child to enjoy the animated picture book anytime, anywhere.

[0099] The system uses its emotion estimation function to analyze a child's emotional state in real time and make suggestions to play an animated picture book at the optimal timing. For example, a child's emotional state can be analyzed in real time, and the generation AI can make suggestions to play an animated picture book at the optimal timing for that emotion. For example, the generation AI can suggest playing an animated picture book when a child is having fun. This makes it possible to make suggestions to play an animated picture book at the optimal timing based on a child's emotional state. For example, the generation AI can suggest playing an animated picture book when a child is relaxed, providing a more effective auditory experience for the child.

[0100] The system can add a function that allows users to cast the animated picture books they create onto a projector or smart TV to enjoy them on a large screen. For example, the system can provide a function that allows users to cast the animated picture books they create onto a projector or smart TV to enjoy them on a large screen. For example, parents can cast the animated picture books they create onto a smart TV so that the whole family can enjoy them on a large screen. This allows users to enjoy the animated picture books they create on a large screen. For example, parents can cast the animated picture books they create onto a projector or smart TV so that the whole family can enjoy them on a large screen, providing a more immersive visual experience.

[0101] The system uses the emotion estimation function to analyze the emotional state of parents and children in real time and suggests the optimal story progression. For example, when parents and children are creating a story together, the generation AI uses the emotion estimation function to analyze the emotional state of parents and children in real time and suggests the optimal story progression. For example, when parents and children are having fun, the generation AI suggests the next scene. This makes it possible to suggest the optimal story progression based on the emotional state of parents and children. For example, when parents and children are tired, the generation AI can suggest taking a break, allowing parents and children to make the most of their creative time.

[0102] The system can add a function to enable sharing of created animated picture books so that they can be enjoyed with family and friends. For example, a function to share created animated picture books can be provided so that they can be enjoyed with family and friends. For example, a parent can upload the animated picture book they created to the cloud and send a sharing link to their family and friends. This allows the created animated picture book to be shared with family and friends. For example, a parent can upload the animated picture book they created to the cloud and send a sharing link to their family and friends so that they can enjoy the animated picture book together, even with family and friends who are far away.

[0103] The processing flow of the second embodiment will be briefly explained below.

[0104] Step 1: The keyword input unit accepts keywords entered by the user. For example, if the user enters keywords such as "adventure," "animal," or "magic," the keyword input unit accepts these keywords. Step 2: The story generation unit generates a story based on the keywords received by the keyword input unit. For example, the AI ​​may generate a story that includes elements of adventure, animals, and magic based on keywords entered by the user. Step 3: The voice recording unit records the parent's voice. For example, the parent records "Hello, this is my voice," and the voice recording unit records that voice. Step 4: The narration generation unit generates narration by imitating the parent's voice recorded by the voice recording unit. For example, the generation AI analyzes the parent's voice quality in the recording and generates the story narration by imitating that voice.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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).

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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).

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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).

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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).

[0158] 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.

[0159] 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."

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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]

[0172] 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 keyword input unit that accepts keywords input by a user; a story generation unit that generates a story based on the keywords received by the keyword input unit; A voice recording section for recording parents' voices, a narration generating unit that generates a narration by imitating the voice of the parent recorded by the voice recording unit. A system characterized by:

2. The keyword input unit A preview of the story is generated in real time in response to keyword input, allowing the user to check and adjust the content.

2. The system of claim 1.

3. The narration generation unit Record the parent's voice multiple times and combine them to create a more natural-sounding narration 2. The system of claim 1.

4. The system comprises: Interactive questions are presented as the story progresses, encouraging dialogue between parents and children.

2. The system of claim 1.

5. The system comprises: Analyzes a child's emotional state using emotion estimation functionality and suggests optimal timing for playing animated picture books.

2. The system of claim 1.

Images