System

Abstract

An object of the system according to the embodiment is to generate a story from various viewpoints and provide an opportunity for role creation and co-creation.SOLUTION: A system includes a viewpoint generation part, a role making support part, and a co-creation support part. The viewpoint generation unit uses the generation AI to generate a story from the viewpoint of each character in the story. A role making support part supports an actor to make a role based on the story generated by the viewpoint generation part. The co-creation support unit provides an opportunity of co-creation based on the story generated by the viewpoint generation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has made it difficult to consider a story from various perspectives, making it difficult to effectively provide opportunities for character development and co-creation.

[0005] The system according to the embodiment aims to generate stories from various perspectives and provide opportunities for character development and co-creation. [Means for solving the problem]

[0006] The system according to the embodiment includes a viewpoint generation unit, a character creation support unit, and a co-creation support unit. The viewpoint generation unit uses a generation AI to generate a story from the viewpoint of each character in the story. The character creation support unit supports actors in creating their characters based on the story generated by the viewpoint generation unit. The co-creation support unit provides opportunities for co-creation based on the story generated by the viewpoint generation unit. [Effects of the Invention]

[0007] The system according to the embodiment can generate stories from various perspectives, providing opportunities for character development and co-creation. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

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

[0028] (Example 1) The YourSTORY system according to an embodiment of the present invention is a system that utilizes generative AI to support character creation from various perspectives in story creation, school performances, plays, etc. This system generates stories from the perspective of each character in the story, supports character creation, and provides opportunities for co-creation. This enables the YourSTORY system to generate stories from various perspectives and support character creation and co-creation based on them.

[0029] The YourSTORY system according to the embodiment includes a perspective generation unit, a character creation support unit, and a co-creation support unit. The perspective generation unit uses a generation AI to generate a story from the perspective of each character in the story. For example, the generation AI receives the basic plot and character settings of the story as input and generates stories from different perspectives. The generation AI receives prompts including a story outline and character settings, and the generation AI generates stories from different perspectives based on the prompts. The character creation support unit supports actors in creating their characters based on the stories generated by the perspective generation unit. For example, the generation AI generates stories from each character's perspective to support actors in becoming the characters. The co-creation support unit provides opportunities for co-creation based on the stories generated by the perspective generation unit. For example, the generation AI generates stories from different perspectives to provide opportunities for co-creation. This enables the YourSTORY system to generate stories from various perspectives and support character creation and co-creation based on the stories.

[0030] The perspective generation unit can generate a story that depicts in detail the inner conflicts and growth process of each character in the story. For example, the perspective generation unit uses a generation AI to generate a story that depicts in detail the inner conflicts and growth process of each character in the story. For example, by describing in detail the process by which the protagonist faces and overcomes difficulties, the reader is deeply moved. The perspective generation unit also generates a story that depicts the inner conflicts and growth process of supporting characters and antagonists. For example, by describing in detail the background and motives of why the antagonist commits evil deeds, the story becomes more profound. The perspective generation unit also sets in detail the history and cultural background of the world in which the story is set and depicts its influence from the perspective of each character. For example, by describing how the characters have survived in that world, the story becomes more realistic. In this way, the story can become more profound by depicting in detail the inner conflicts and growth process of the characters.

[0031] The perspective generation unit can set the history and cultural background of the world in which the story is set in detail and depict its impact from the perspective of the characters. The perspective generation unit, for example, uses a generation AI to set the history and cultural background of the world in which the story is set in detail and depict its impact from the perspective of each character. For example, the perspective generation unit can give the story a sense of realism by depicting how the characters have survived in that world. The perspective generation unit can also set the political and economic situation of the world in which the story is set in detail and depict its impact from the perspective of each character. For example, the perspective generation unit can give the story a sense of realism by depicting how the characters have survived in that world. The perspective generation unit can also set the natural environment and climatic situation of the world in which the story is set in detail and depict its impact from the perspective of each character. For example, the perspective generation unit can give the story a sense of realism by depicting how the characters have survived in that world. In this way, the history and cultural background of the world in which the story is set in detail can be given realism.

[0032] The perspective generation unit can reconstruct the same story in different genres and develop the story from the perspective of each genre. For example, the perspective generation unit uses a generation AI to reconstruct the same story in the fantasy genre and generate a story incorporating elements of magic and adventure. For example, it could depict a story in which the protagonist obtains magical powers and goes on an adventurous journey. The perspective generation unit could also use a generation AI to reconstruct the same story in the science fiction genre and generate a story incorporating elements of futuristic technology and space. For example, it could depict a story in which the protagonist explores an unknown planet in a spaceship. The perspective generation unit could also use a generation AI to reconstruct the same story in the mystery genre and generate a story incorporating elements of puzzle-solving and suspense. For example, it could depict a story in which the protagonist solves the mystery of a serial murder case. This makes it possible to provide diversity in stories by reconstructing stories in different genres.

[0033] The perspective generation unit can depict the perspective of the story from the perspective of an animal or inanimate object. For example, the perspective generation unit uses a generation AI to depict the perspective of a pet. For example, the story unfolds from the perspective of how the protagonist's pet helps the protagonist. The perspective generation unit also uses a generation AI to depict the perspective of the story from the perspective of furniture. For example, the story unfolds from the perspective of how the furniture in the protagonist's room watches over the protagonist's life. The perspective generation unit also uses a generation AI to depict the perspective of a natural element (for example, a tree or a river). For example, the story unfolds from the perspective of how the protagonist is related to nature. In this way, new perspectives can be provided by depicting the story from the perspective of an animal or inanimate object.

[0034] The character creation support unit can depict a character's past events and background in detail, allowing the actor to deeply understand the character's motivations and actions. For example, the character creation support unit uses generation AI to depict each character's past events and background in detail. For example, it may depict the protagonist's past trauma and experiences, allowing the actor to deeply understand the character's motivations and actions. The character creation support unit also uses generation AI to depict the past events and background of supporting characters and antagonists in detail. For example, it may depict the background and motivations of the antagonist, explaining why they committed evil deeds, allowing the actor to understand the character's actions. The character creation support unit also uses generation AI to set the history and cultural background of the world in which the story is set in detail, depicting its influence from each character's perspective. For example, it may depict how a character has survived in that world, allowing the actor to deeply understand the character's actions. This allows the actor to deeply understand the character's motivations and actions by depicting the character's past events and background in detail.

[0035] The character creation support unit can depict the relationships and conflict structures between characters in detail, allowing the actor to reflect those relationships in their acting. The character creation support unit, for example, uses generation AI to depict the relationships and conflict structures between characters in detail. For example, it may depict the conflict structure between a protagonist and an antagonist, allowing the actor to reflect that relationship in their acting. The character creation support unit also uses generation AI to depict the friendship and love relationships between characters in detail. For example, it may depict the friendship between the protagonist and a friend, allowing the actor to reflect that relationship in their acting. The character creation support unit also uses generation AI to depict the family relationships and master-disciple relationships between characters in detail. For example, it may depict the master-disciple relationship between the protagonist and a master, allowing the actor to reflect that relationship in their acting. In this way, by depicting the relationships and conflict structures between characters in detail, the actor can reflect that relationship in their acting.

[0036] The character creation support unit can replace the script for a school play or drama with a different cultural or historical setting, allowing actors to create their characters from different perspectives. For example, the character creation support unit uses generative AI to replace the script for a school play or drama with a different culture. For example, it can replace a modern story with medieval European culture, allowing actors to create their characters based on that culture. The character creation support unit also uses generative AI to replace the script for a school play or drama with a different historical setting. For example, it can replace a modern story with a futuristic historical setting, allowing actors to create their characters based on that historical period. The character creation support unit also uses generative AI to replace the script for a school play or drama with a different regional culture. For example, it can replace a modern story with African culture, allowing actors to create their characters based on that culture. In this way, by replacing the script with a different cultural or historical setting, actors can create their characters from different perspectives.

[0037] The character creation support unit can portray the same character at different ages and genders, allowing the actor to experience a variety of character creation experiences. The character creation support unit, for example, uses generation AI to portray the same character at different ages. For example, the main character may be portrayed as a child or an old adult, allowing the actor to experience character creation based on that age. The character creation support unit also uses generation AI to portray the same character at different genders. For example, the main character may be portrayed as a male or female, allowing the actor to experience character creation based on that gender. The character creation support unit also uses generation AI to portray the same character at different social positions. For example, the main character may be portrayed as a poor or wealthy person, allowing the actor to experience character creation based on that position. In this way, by portraying the same character at different ages and genders, the actor can experience a variety of character creation experiences.

[0038] The co-creation support unit can reconstruct each chapter and scene of the story from the perspective of a different character and provide ideas for co-creation. For example, the co-creation support unit uses a generative AI to reconstruct each chapter and scene of the story from the perspective of a different character. For example, a scene depicted from the perspective of the protagonist can be reconstructed from the perspective of a supporting character to provide ideas for co-creation. The co-creation support unit also uses a generative AI to reconstruct each chapter and scene of the story from the perspective of a different character. For example, a scene depicted from the perspective of the villain can be reconstructed from the perspective of the protagonist to provide ideas for co-creation. The co-creation support unit also uses a generative AI to reconstruct each chapter and scene of the story from the perspective of a different character. For example, a scene depicted from the perspective of a background character can be reconstructed from the perspective of a main character to provide ideas for co-creation. In this way, it is possible to provide ideas for co-creation by reconstructing each chapter and scene of the story from the perspective of a different character.

[0039] The co-creation support unit can generate multiple variations of a story plot, allowing co-creators to have choices as they progress through the story. The co-creation support unit generates multiple variations of a story plot, for example, using a generation AI. For example, it generates plots in which the protagonist makes different choices, allowing co-creators to have choices as they progress through the story. The co-creation support unit also uses a generation AI to generate multiple variations of a story plot. For example, it generates plots in which the story has a different ending, allowing co-creators to have choices as they progress through the story. The co-creation support unit also uses a generation AI to generate multiple variations of a story plot. For example, it generates plots in which the story is set in a different setting, allowing co-creators to have choices as they progress through the story. In this way, by generating multiple variations of a story plot, it is possible for co-creators to have choices as they progress through the story.

[0040] The co-creation support unit can generate a story in multiple languages, allowing co-creators from different cultures and languages ​​to participate. The co-creation support unit generates a story in multiple languages, for example, using a generation AI. For example, a story may be generated in multiple languages, such as English, French, and Chinese, allowing co-creators from different cultures and languages ​​to participate. The co-creation support unit also generates a story in multiple languages, using a generation AI. For example, the story plot and character settings may be generated in multiple languages, allowing co-creators from different cultures and languages ​​to participate. The co-creation support unit also generates a story in multiple languages, using a generation AI. For example, each chapter and scene of the story may be generated in multiple languages, allowing co-creators from different cultures and languages ​​to participate. In this way, generating a story in multiple languages ​​allows co-creators from different cultures and languages ​​to participate.

[0041] The co-creation support unit can generate a part of the story in an interactive format, allowing the co-creator to directly influence the progress of the story. The co-creation support unit, for example, uses a generation AI to generate a part of the story in an interactive format. For example, it generates an interactive story in which the progress of the story changes when the co-creator selects an option. The co-creation support unit also uses a generation AI to generate a part of the story in an interactive format. For example, it generates an interactive story in which the progress of the story changes when the co-creator selects the character's actions. The co-creation support unit also uses a generation AI to generate a part of the story in an interactive format. For example, it generates an interactive story in which the progress of the story changes when the co-creator selects the setting of the story. In this way, by generating a part of the story in an interactive format, the co-creator can directly influence the progress of the story.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The YourSTORY system can also be equipped with a voice generation unit that imitates the voices and speaking styles of characters. The voice generation unit uses generative AI to generate voices that imitate the voices and speaking styles of each character. For example, the voice generation unit can express the protagonist's voice with rich emotion, allowing actors to perform in sync with that voice. The voice generation unit can also generate voices for supporting and antagonist characters, allowing actors to create their characters based on those voices. Furthermore, the voice generation unit can generate background sounds and sound effects for the world in which the story takes place, enhancing the realism of the story. This allows actors to perform more realistic acting by imitating the character's voice and speaking style.

[0044] The YourSTORY system can also include a costume suggestion unit that suggests costumes and props for characters. The costume suggestion unit uses generative AI to suggest costumes and props suitable for each character. For example, it can suggest costumes for the main character that match the historical background and the character's personality, allowing the actor to create the character by wearing the costume. The costume suggestion unit can also suggest costumes and props for supporting and antagonist characters, allowing the actor to create the character based on the suggestions. Furthermore, the costume suggestion unit can suggest costumes and props based on the culture and customs of the world in which the story is set, enhancing the realism of the story. As a result, by suggesting costumes and props for characters, actors can perform more realistic acting.

[0045] The YourSTORY system can also be equipped with a motion generation unit that mimics the movements of characters. The motion generation unit uses generative AI to generate animations that mimic the movements of each character. For example, the motion generation unit can express the protagonist's movements emotionally, allowing actors to perform in sync with those movements. The motion generation unit can also generate movements for supporting and antagonist characters, allowing actors to create their characters based on those movements. Furthermore, the motion generation unit can generate movements based on the background and environment of the world in which the story is set, enhancing the realism of the story. This allows actors to perform more realistic acting by mimicking the movements of characters.

[0046] The YourSTORY system can further include a psychological state display unit that visualizes the psychological state of characters. The psychological state display unit uses generative AI to visually display each character's psychological state. For example, the protagonist's psychological state can be expressed using color and shape, allowing actors to act based on that display. The psychological state display unit can also display the psychological states of supporting characters and villains, allowing actors to create their characters based on that display. Furthermore, the psychological state display unit can display psychological states based on the background and environment of the world in which the story is set, enhancing the realism of the story. This allows actors to perform more realistically by visualizing the characters' psychological states.

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

[0048] Step 1: The viewpoint generation unit uses the generation AI to generate a story from the viewpoint of each character in the story. The generation AI receives the basic plot and character settings of the story as input and generates stories from different viewpoints. The input to the generation AI is a prompt that includes the outline of the story and character settings, and the generation AI generates stories from different viewpoints based on the prompt. Step 2: The character creation support unit supports the actor in creating their character based on the story generated by the viewpoint generation unit. The generation AI generates a story from each character's perspective, helping the actor become that character. Step 3: The co-creation support unit provides opportunities for co-creation based on the stories generated by the perspective generation unit. The generation AI generates stories from different perspectives, providing opportunities for co-creation.

[0049] (Example 2) The YourSTORY system according to an embodiment of the present invention is a system that utilizes generative AI to support character creation from various perspectives in story creation, school performances, plays, etc. This system generates stories from the perspective of each character in the story, supports character creation, and provides opportunities for co-creation. This enables the YourSTORY system to generate stories from various perspectives and support character creation and co-creation based on them.

[0050] The YourSTORY system according to the embodiment includes a perspective generation unit, a character creation support unit, and a co-creation support unit. The perspective generation unit uses a generation AI to generate a story from the perspective of each character in the story. For example, the generation AI receives the basic plot and character settings of the story as input and generates stories from different perspectives. The generation AI receives prompts including a story outline and character settings, and the generation AI generates stories from different perspectives based on the prompts. The character creation support unit supports actors in creating their characters based on the stories generated by the perspective generation unit. For example, the generation AI generates stories from each character's perspective to support actors in becoming the characters. The co-creation support unit provides opportunities for co-creation based on the stories generated by the perspective generation unit. For example, the generation AI generates stories from different perspectives to provide opportunities for co-creation. This enables the YourSTORY system to generate stories from various perspectives and support character creation and co-creation based on the stories.

[0051] The perspective generation unit can generate a story that depicts in detail the inner conflicts and growth process of each character in the story. For example, the perspective generation unit uses a generation AI to generate a story that depicts in detail the inner conflicts and growth process of each character in the story. For example, by describing in detail the process by which the protagonist faces and overcomes difficulties, the reader is deeply moved. The perspective generation unit also generates a story that depicts the inner conflicts and growth process of supporting characters and antagonists. For example, by describing in detail the background and motives of why the antagonist commits evil deeds, the story becomes more profound. The perspective generation unit also sets in detail the history and cultural background of the world in which the story is set and depicts its influence from the perspective of each character. For example, by describing how the characters have survived in that world, the story becomes more realistic. In this way, the story can become more profound by depicting in detail the inner conflicts and growth process of the characters.

[0052] The perspective generation unit can set the history and cultural background of the world in which the story is set in detail and depict its impact from the perspective of the characters. The perspective generation unit, for example, uses a generation AI to set the history and cultural background of the world in which the story is set in detail and depict its impact from the perspective of each character. For example, the perspective generation unit can give the story a sense of realism by depicting how the characters have survived in that world. The perspective generation unit can also set the political and economic situation of the world in which the story is set in detail and depict its impact from the perspective of each character. For example, the perspective generation unit can give the story a sense of realism by depicting how the characters have survived in that world. The perspective generation unit can also set the natural environment and climatic situation of the world in which the story is set in detail and depict its impact from the perspective of each character. For example, the perspective generation unit can give the story a sense of realism by depicting how the characters have survived in that world. In this way, the history and cultural background of the world in which the story is set in detail can be given realism.

[0053] The viewpoint generation unit can use the emotion estimation function to generate a story that reflects changes in the character's emotions in real time. The viewpoint generation unit, for example, uses the emotion estimation function to generate a story that reflects changes in the character's emotions in real time. For example, in a scene where a character feels joy or sadness, the change in emotion is depicted in detail. The viewpoint generation unit also uses the emotion estimation function to generate a story that reflects changes in the character's emotions in real time. For example, in a scene where a character feels anger or fear, the change in emotion is depicted in detail. The viewpoint generation unit also uses the emotion estimation function to generate a story that reflects changes in the character's emotions in real time. For example, in a scene where a character feels surprise or relief, the change in emotion is depicted in detail. In this way, by reflecting changes in the character's emotions in real time, the reader can experience the flow of emotions.

[0054] The perspective generation unit can reconstruct the same story in different genres and develop the story from the perspective of each genre. For example, the perspective generation unit uses a generation AI to reconstruct the same story in the fantasy genre and generate a story incorporating elements of magic and adventure. For example, it could depict a story in which the protagonist obtains magical powers and goes on an adventurous journey. The perspective generation unit could also use a generation AI to reconstruct the same story in the science fiction genre and generate a story incorporating elements of futuristic technology and space. For example, it could depict a story in which the protagonist explores an unknown planet in a spaceship. The perspective generation unit could also use a generation AI to reconstruct the same story in the mystery genre and generate a story incorporating elements of puzzle-solving and suspense. For example, it could depict a story in which the protagonist solves the mystery of a serial murder case. This makes it possible to provide diversity in stories by reconstructing stories in different genres.

[0055] The perspective generation unit can depict the perspective of the story from the perspective of an animal or inanimate object. For example, the perspective generation unit uses a generation AI to depict the perspective of a pet. For example, the story unfolds from the perspective of how the protagonist's pet helps the protagonist. The perspective generation unit also uses a generation AI to depict the perspective of the story from the perspective of furniture. For example, the story unfolds from the perspective of how the furniture in the protagonist's room watches over the protagonist's life. The perspective generation unit also uses a generation AI to depict the perspective of a natural element (for example, a tree or a river). For example, the story unfolds from the perspective of how the protagonist is related to nature. In this way, new perspectives can be provided by depicting the story from the perspective of an animal or inanimate object.

[0056] The perspective generation unit can use the emotion estimation function to dynamically change the perspective of the story based on the reader's emotional response. The perspective generation unit, for example, uses the emotion estimation function to dynamically change the perspective of the story based on the reader's emotional response. For example, if the reader feels surprise, the perspective of the story is changed in accordance with the emotion to emphasize the element of surprise. The perspective generation unit also uses the emotion estimation function to dynamically change the perspective of the story based on the reader's emotional response. For example, if the reader feels sad, the perspective of the story is changed in accordance with the emotion to emphasize the element of sadness. The perspective generation unit also uses the emotion estimation function to dynamically change the perspective of the story based on the reader's emotional response. For example, if the reader feels joy, the perspective of the story is changed in accordance with the emotion to emphasize the element of joy. In this way, by dynamically changing the perspective of the story in accordance with the reader's emotional response, it is possible to provide a story experience that is tailored to the reader.

[0057] The character creation support unit can depict a character's past events and background in detail, allowing the actor to deeply understand the character's motivations and actions. For example, the character creation support unit uses generation AI to depict each character's past events and background in detail. For example, it may depict the protagonist's past trauma and experiences, allowing the actor to deeply understand the character's motivations and actions. The character creation support unit also uses generation AI to depict the past events and background of supporting characters and antagonists in detail. For example, it may depict the background and motivations of the antagonist, explaining why they committed evil deeds, allowing the actor to understand the character's actions. The character creation support unit also uses generation AI to set the history and cultural background of the world in which the story is set in detail, depicting its influence from each character's perspective. For example, it may depict how a character has survived in that world, allowing the actor to deeply understand the character's actions. This allows the actor to deeply understand the character's motivations and actions by depicting the character's past events and background in detail.

[0058] The character creation support unit can depict the relationships and conflict structures between characters in detail, allowing the actor to reflect those relationships in their acting. The character creation support unit, for example, uses generation AI to depict the relationships and conflict structures between characters in detail. For example, it may depict the conflict structure between a protagonist and an antagonist, allowing the actor to reflect that relationship in their acting. The character creation support unit also uses generation AI to depict the friendship and love relationships between characters in detail. For example, it may depict the friendship between the protagonist and a friend, allowing the actor to reflect that relationship in their acting. The character creation support unit also uses generation AI to depict the family relationships and master-disciple relationships between characters in detail. For example, it may depict the master-disciple relationship between the protagonist and a master, allowing the actor to reflect that relationship in their acting. In this way, by depicting the relationships and conflict structures between characters in detail, the actor can reflect that relationship in their acting.

[0059] The character creation support unit can use the emotion estimation function to analyze the actor's emotions in real time and provide advice on emotional expression required for character creation. The character creation support unit, for example, uses the emotion estimation function to analyze the actor's emotions in real time and provide advice on emotional expression required for character creation. For example, specific advice is provided when the actor is expressing sadness. The character creation support unit can also use the emotion estimation function to analyze the actor's emotions in real time and provide advice on emotional expression required for character creation. For example, specific advice is provided when the actor is expressing anger. The character creation support unit can also use the emotion estimation function to analyze the actor's emotions in real time and provide advice on emotional expression required for character creation. For example, specific advice is provided when the actor is expressing joy. In this way, by analyzing the actor's emotions in real time and providing advice on emotional expression required for character creation, the actor's acting ability can be improved.

[0060] The character creation support unit can replace the script for a school play or drama with a different cultural or historical setting, allowing actors to create their characters from different perspectives. For example, the character creation support unit uses generative AI to replace the script for a school play or drama with a different culture. For example, it can replace a modern story with medieval European culture, allowing actors to create their characters based on that culture. The character creation support unit also uses generative AI to replace the script for a school play or drama with a different historical setting. For example, it can replace a modern story with a futuristic historical setting, allowing actors to create their characters based on that historical period. The character creation support unit also uses generative AI to replace the script for a school play or drama with a different regional culture. For example, it can replace a modern story with African culture, allowing actors to create their characters based on that culture. In this way, by replacing the script with a different cultural or historical setting, actors can create their characters from different perspectives.

[0061] The character creation support unit can portray the same character at different ages and genders, allowing the actor to experience a variety of character creation experiences. The character creation support unit, for example, uses generation AI to portray the same character at different ages. For example, the main character may be portrayed as a child or an old adult, allowing the actor to experience character creation based on that age. The character creation support unit also uses generation AI to portray the same character at different genders. For example, the main character may be portrayed as a male or female, allowing the actor to experience character creation based on that gender. The character creation support unit also uses generation AI to portray the same character at different social positions. For example, the main character may be portrayed as a poor or wealthy person, allowing the actor to experience character creation based on that position. In this way, by portraying the same character at different ages and genders, the actor can experience a variety of character creation experiences.

[0062] The character creation support unit can use the emotion estimation function to analyze the emotional reactions of the audience in real time, allowing the actor to perform according to that reaction. The character creation support unit, for example, uses the emotion estimation function to analyze the emotional reactions of the audience in real time, allowing the actor to perform according to that reaction. For example, if the audience feels surprise, the performance is adjusted according to that emotion. The character creation support unit also uses the emotion estimation function to analyze the emotional reactions of the audience in real time, allowing the actor to perform according to that reaction. For example, if the audience feels sadness, the performance is adjusted according to that emotion. The character creation support unit also uses the emotion estimation function to analyze the emotional reactions of the audience in real time, allowing the actor to perform according to that reaction. For example, if the audience feels joy, the performance is adjusted according to that emotion. In this way, the emotional reactions of the audience can be analyzed in real time, allowing the actor to perform according to that reaction, thereby enhancing a sense of unity with the audience.

[0063] The co-creation support unit can reconstruct each chapter and scene of the story from the perspective of a different character and provide ideas for co-creation. For example, the co-creation support unit uses a generative AI to reconstruct each chapter and scene of the story from the perspective of a different character. For example, a scene depicted from the perspective of the protagonist can be reconstructed from the perspective of a supporting character to provide ideas for co-creation. The co-creation support unit also uses a generative AI to reconstruct each chapter and scene of the story from the perspective of a different character. For example, a scene depicted from the perspective of the villain can be reconstructed from the perspective of the protagonist to provide ideas for co-creation. The co-creation support unit also uses a generative AI to reconstruct each chapter and scene of the story from the perspective of a different character. For example, a scene depicted from the perspective of a background character can be reconstructed from the perspective of a main character to provide ideas for co-creation. In this way, it is possible to provide ideas for co-creation by reconstructing each chapter and scene of the story from the perspective of a different character.

[0064] The co-creation support unit can generate multiple variations of a story plot, allowing co-creators to have choices as they progress through the story. The co-creation support unit generates multiple variations of a story plot, for example, using a generation AI. For example, it generates plots in which the protagonist makes different choices, allowing co-creators to have choices as they progress through the story. The co-creation support unit also uses a generation AI to generate multiple variations of a story plot. For example, it generates plots in which the story has a different ending, allowing co-creators to have choices as they progress through the story. The co-creation support unit also uses a generation AI to generate multiple variations of a story plot. For example, it generates plots in which the story is set in a different setting, allowing co-creators to have choices as they progress through the story. In this way, by generating multiple variations of a story plot, it is possible for co-creators to have choices as they progress through the story.

[0065] The co-creation support unit uses the emotion estimation function to adjust the progress of the story based on the emotional reactions of the co-creators, and can generate a story that satisfies all co-creators. The co-creation support unit, for example, uses the emotion estimation function to adjust the progress of the story based on the emotional reactions of the co-creators. For example, if a co-creator feels surprise, the progress of the story is adjusted in accordance with that emotion. The co-creation support unit also uses the emotion estimation function to adjust the progress of the story based on the emotional reactions of the co-creators. For example, if a co-creator feels sad, the progress of the story is adjusted in accordance with that emotion. The co-creation support unit also uses the emotion estimation function to adjust the progress of the story based on the emotional reactions of the co-creators. For example, if a co-creator feels joy, the progress of the story is adjusted in accordance with that emotion. In this way, by adjusting the progress of the story based on the emotional reactions of the co-creators, it is possible to generate a story that satisfies all co-creators.

[0066] The co-creation support unit can generate a story in multiple languages, allowing co-creators from different cultures and languages ​​to participate. The co-creation support unit generates a story in multiple languages, for example, using a generation AI. For example, a story may be generated in multiple languages, such as English, French, and Chinese, allowing co-creators from different cultures and languages ​​to participate. The co-creation support unit also generates a story in multiple languages, using a generation AI. For example, the story plot and character settings may be generated in multiple languages, allowing co-creators from different cultures and languages ​​to participate. The co-creation support unit also generates a story in multiple languages, using a generation AI. For example, each chapter and scene of the story may be generated in multiple languages, allowing co-creators from different cultures and languages ​​to participate. In this way, generating a story in multiple languages ​​allows co-creators from different cultures and languages ​​to participate.

[0067] The co-creation support unit can generate a part of the story in an interactive format, allowing the co-creator to directly influence the progress of the story. The co-creation support unit, for example, uses a generation AI to generate a part of the story in an interactive format. For example, it generates an interactive story in which the progress of the story changes when the co-creator selects an option. The co-creation support unit also uses a generation AI to generate a part of the story in an interactive format. For example, it generates an interactive story in which the progress of the story changes when the co-creator selects the character's actions. The co-creation support unit also uses a generation AI to generate a part of the story in an interactive format. For example, it generates an interactive story in which the progress of the story changes when the co-creator selects the setting of the story. In this way, by generating a part of the story in an interactive format, the co-creator can directly influence the progress of the story.

[0068] The co-creation support unit can use the emotion estimation function to analyze the emotional responses of co-creators in real time and generate a story that promotes emotional empathy during the co-creation process. The co-creation support unit, for example, uses the emotion estimation function to analyze the emotional responses of co-creators in real time and generate a story that promotes emotional empathy during the co-creation process. For example, if a co-creator feels joy, the story is adjusted according to the emotion. The co-creation support unit also uses the emotion estimation function to analyze the emotional responses of co-creators in real time and generate a story that promotes emotional empathy during the co-creation process. For example, if a co-creator feels sad, the story is adjusted according to the emotion. The co-creation support unit also uses the emotion estimation function to analyze the emotional responses of co-creators in real time and generate a story that promotes emotional empathy during the co-creation process. For example, if a co-creator feels surprise, the story is adjusted according to the emotion. In this way, by analyzing the emotional responses of co-creators in real time and generating a story that promotes emotional empathy during the co-creation process, it is possible to enhance a sense of unity between co-creators.

[0069] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0070] The YourSTORY system can also be equipped with a voice generation unit that imitates the voices and speaking styles of characters. The voice generation unit uses generative AI to generate voices that imitate the voices and speaking styles of each character. For example, the voice generation unit can express the protagonist's voice with rich emotion, allowing actors to perform in sync with that voice. The voice generation unit can also generate voices for supporting and antagonist characters, allowing actors to create their characters based on those voices. Furthermore, the voice generation unit can generate background sounds and sound effects for the world in which the story takes place, enhancing the realism of the story. This allows actors to perform more realistic acting by imitating the character's voice and speaking style.

[0071] The YourSTORY system can also include a costume suggestion unit that suggests costumes and props for characters. The costume suggestion unit uses generative AI to suggest costumes and props suitable for each character. For example, it can suggest costumes for the main character that match the historical background and the character's personality, allowing the actor to create the character by wearing the costume. The costume suggestion unit can also suggest costumes and props for supporting and antagonist characters, allowing the actor to create the character based on the suggestions. Furthermore, the costume suggestion unit can suggest costumes and props based on the culture and customs of the world in which the story is set, enhancing the realism of the story. As a result, by suggesting costumes and props for characters, actors can perform more realistic acting.

[0072] The YourSTORY system can also be equipped with a motion generation unit that mimics the movements of characters. The motion generation unit uses generative AI to generate animations that mimic the movements of each character. For example, the motion generation unit can express the protagonist's movements emotionally, allowing actors to perform in sync with those movements. The motion generation unit can also generate movements for supporting and antagonist characters, allowing actors to create their characters based on those movements. Furthermore, the motion generation unit can generate movements based on the background and environment of the world in which the story is set, enhancing the realism of the story. This allows actors to perform more realistic acting by mimicking the movements of characters.

[0073] The YourSTORY system can further include a psychological state display unit that visualizes the psychological state of characters. The psychological state display unit uses generative AI to visually display each character's psychological state. For example, the protagonist's psychological state can be expressed using color and shape, allowing actors to act based on that display. The psychological state display unit can also display the psychological states of supporting characters and villains, allowing actors to create their characters based on that display. Furthermore, the psychological state display unit can display psychological states based on the background and environment of the world in which the story is set, enhancing the realism of the story. This allows actors to perform more realistically by visualizing the characters' psychological states.

[0074] The YourSTORY system can further include a music generation unit that expresses the emotions of characters through music. The music generation unit uses generative AI to express the emotions of each character through music. For example, it can generate music that expresses the emotions of the main character, allowing actors to act in sync with that music. The music generation unit can also generate music that expresses the emotions of supporting characters and villains, allowing actors to create their characters based on that music. Furthermore, the music generation unit can generate background music for the world in which the story takes place, enhancing the sense of realism of the story. This allows actors to perform more realistically by expressing the emotions of characters through music.

[0075] The YourSTORY system can further include a color display unit that expresses the emotions of characters with colors. The color display unit uses generative AI to express the emotions of each character with colors. For example, it can generate colors that express the emotions of the protagonist, allowing actors to act based on those colors. The color display unit can also generate colors that express the emotions of supporting characters and villains, allowing actors to create their characters based on those colors. Furthermore, the color display unit can generate background colors for the world in which the story takes place, enhancing the realism of the story. This allows actors to act more realistically by expressing the emotions of characters with colors.

[0076] The YourSTORY system can further include a scent generation unit that expresses the emotions of characters through scent. The scent generation unit uses generation AI to express the emotions of each character through scent. For example, it can generate a scent that expresses the emotions of the main character, allowing actors to act based on that scent. The scent generation unit can also generate scents that express the emotions of supporting characters and villains, allowing actors to create their characters based on that scent. Furthermore, the scent generation unit can generate background scents for the world in which the story takes place, enhancing the realism of the story. This allows actors to act more realistically by expressing the emotions of characters through scent.

[0077] The YourSTORY system can further include a haptic generation unit that expresses the emotions of characters through touch. The haptic generation unit uses generative AI to express the emotions of each character through touch. For example, it can generate haptics that express the emotions of the protagonist, allowing the actor to act based on those haptics. The haptic generation unit can also generate haptics that express the emotions of supporting characters and villains, allowing the actor to create their character based on those haptics. Furthermore, the haptic generation unit can generate haptics of the background of the world in which the story takes place, enhancing the sense of realism of the story. This allows the actor to perform more realistic acting by expressing the emotions of the characters through touch.

[0078] The YourSTORY system can further include a temperature generation unit that expresses a character's emotions with temperature. The temperature generation unit uses generation AI to express each character's emotions with temperature. For example, it generates a temperature that expresses the protagonist's emotions, allowing the actor to act based on that temperature. The temperature generation unit can also generate temperatures that express the emotions of supporting characters and villains, allowing the actor to create their character based on that temperature. Furthermore, the temperature generation unit can generate the background temperature of the world in which the story takes place, enhancing the realism of the story. This allows the actor to perform more realistically by expressing the character's emotions with temperature.

[0079] The YourSTORY system can further include a vibration generation unit that expresses the emotions of characters through vibrations. The vibration generation unit uses generation AI to express the emotions of each character through vibrations. For example, it can generate vibrations that express the emotions of the main character, allowing actors to act based on those vibrations. The vibration generation unit can also generate vibrations that express the emotions of supporting characters and villains, allowing actors to create their characters based on those vibrations. Furthermore, the vibration generation unit can generate vibrations of the background of the world in which the story takes place, enhancing the sense of realism of the story. This allows actors to act more realistically by expressing the emotions of characters through vibrations.

[0080] The processing flow of the second embodiment will be briefly explained below.

[0081] Step 1: The viewpoint generation unit uses the generation AI to generate a story from the viewpoint of each character in the story. The generation AI receives the basic plot and character settings of the story as input and generates stories from different viewpoints. The input to the generation AI is a prompt that includes the outline of the story and character settings, and the generation AI generates stories from different viewpoints based on the prompt. Step 2: The character creation support unit supports the actor in creating their character based on the story generated by the viewpoint generation unit. The generation AI generates a story from each character's perspective, helping the actor become that character. Step 3: The co-creation support unit provides opportunities for co-creation based on the stories generated by the perspective generation unit. The generation AI generates stories from different perspectives, providing opportunities for co-creation.

[0082] 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.

[0083] 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.

[0084] 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.

[0085] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0086] 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.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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).

[0091] 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.

[0092] 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.

[0093] 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.

[0094] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0095] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0101] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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).

[0106] 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.

[0107] 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.

[0108] 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.

[0109] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0110] In the headset type terminal 314, 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 headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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).

[0121] 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.

[0122] 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.

[0123] 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.

[0124] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0125] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0126] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0127] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0128] The specific processing unit 290 transmits the result of the specific processing to the 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.

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

[0130] The data processing system 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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).

[0135] 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.

[0136] 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."

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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]

[0149] 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 viewpoint generation unit that uses a generation AI to generate a story from the viewpoint of each character in the story; a character creation support unit that supports an actor in creating a character based on the story generated by the viewpoint generation unit; a co-creation support unit that provides opportunities for co-creation based on the story generated by the viewpoint generation unit. A system characterized by:

2. The viewpoint generation unit Generate a story that details the inner conflicts and growth of each character in the story 2. The system of claim 1.

3. The viewpoint generation unit Establish a detailed historical and cultural background for the world in which the story is set, and portray its influence from the perspective of the character.

2. The system of claim 1.

4. The viewpoint generation unit Generate a story that reflects the character's emotional changes in real time 2. The system of claim 1.

5. The viewpoint generation unit Reconstruct the same story in different genres and develop the story from the perspective of each genre.

2. The system of claim 1.

6. The viewpoint generation unit The point of view of the story is depicted from the point of view of an animal or inanimate object.

2. The system of claim 1.

7. The viewpoint generation unit Dynamically change the perspective of the story based on the reader's emotional response 2. The system of claim 1.

8. The character creation support section Describe the character's past events and background in detail, allowing for a deeper understanding of the character's motivations and actions.

2. The system of claim 1.

Images