system

Abstract

The system according to this embodiment aims to enhance immersion by generating a story in real time according to the user's choices. [Solution] The system according to the embodiment comprises a reception unit, a generation unit, and a creation unit. The reception unit receives user selections. The generation unit generates a story in real time based on the selections received by the reception unit. The creation unit creates new events and character reactions based on the story generated by the generation unit.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Conventional technologies do not sufficiently provide a system that generates a story in real time according to a user's selection, and there is room for improvement.

[0005] The system according to an embodiment aims to generate a story in real time according to a user's selection and enhance the sense of immersion.

Means for Solving the Problems

[0006] The system according to an embodiment includes a reception unit, a generation unit, and a creation unit. The reception unit receives a user's selection. The generation unit generates a story in real time based on the selection received by the reception unit. The creation unit creates new events and character reactions based on the story generated by the generation unit. [Effects of the Invention]

[0007] The system according to this embodiment can generate a story in real time in response to user choices, thereby enhancing immersion. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

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

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

[0014] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

[0017] As shown in FIG. 1, the 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, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are 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. Also, the reception device 38, the output device 40, and the camera 42 are connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0024] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

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

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction 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 a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also 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 processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) An interactive story generation system according to an embodiment of the present invention is a system in which the user immerses themselves in a fantasy world and carries out various quests as the protagonist. In this interactive story generation system, the user makes choices about the story, and the generation AI generates the story in real time based on the user's choices, creating new events and character reactions. This system allows the story to branch based on the user's choices and provides multiple endings. This allows the user to explore the story through their own choices and increases the value of replayability. For example, the user makes a choice about the story. At this time, the user can choose from various options. For example, they can choose the starting point of the quest, the characters who will accompany them, and the route to take. This information is input to the generation AI. Next, the generation AI analyzes the input information and generates the story in real time. The generation AI creates new events and character reactions based on the user's choices. For example, if the user chooses a particular route, events and character reactions along that route will be generated. The generated story branches based on the user's choices. For example, if the user makes a particular choice, the story will proceed in a different direction depending on that choice. This allows the user to shape the story through their own choices. Furthermore, the system provides multiple endings. For example, different endings are generated depending on the user's choices. This allows users to experience different stories by replaying the game. This mechanism improves user engagement and satisfaction. Users can explore the story through their own choices and enjoy an interactive experience. Furthermore, improved accuracy and diversity in story generation leads to increased repeat visitor rates and attracts new users. For example, the user selects a starting point for a quest, and the generation AI generates a story based on that selection. If the user chooses to accompany a specific character, that character's reactions and events are generated. If the user chooses a route to take, events and character reactions along that route are generated. This allows users to shape the story through their choices and experience different stories by replaying the game.This allows the interactive story generation system to generate narratives in real time based on user choices, creating new events and character reactions.

[0029] The interactive story generation system according to this embodiment comprises a reception unit, a generation unit, and a creation unit. The reception unit receives user selections. User selections include, but are not limited to, the starting point of a quest, accompanying characters, and the route to be taken. For example, when the user selects a starting point for a quest, the reception unit receives that selection. The reception unit can also receive the user's selection of accompanying characters. Furthermore, the reception unit can also receive the user's selection of the route to be taken. For example, when the user selects a starting point for a quest, the reception unit presents multiple options and accepts the user's selection from among them. The generation unit uses a generation AI to generate a story in real time based on the selections received by the reception unit. For example, the generation unit generates a story based on the starting point of a quest selected by the user. The generation unit can also generate a story based on the accompanying characters selected by the user. Furthermore, the generation unit can also generate a story based on the route to be taken by the user. For example, the generation unit generates a story that starts from the starting point of a quest selected by the user. The generation unit uses a generation AI to create new events and character reactions based on the user's selection. The creation unit creates new events and character reactions based on the story generated by the generation unit. For example, the creation unit creates events that occur at a starting point of a quest selected by the user. The creation unit can also create character reactions based on the accompanying character selected by the user. Furthermore, the creation unit can create events and character reactions along a route selected by the user. For example, the creation unit creates events that occur at a starting point of a quest selected by the user. As a result, the interactive story generation system according to this embodiment can generate a story in real time based on the user's selection and create new events and character reactions.

[0030] The reception desk accepts user selections. These selections include, but are not limited to, the starting point of a quest, the characters accompanying the user, and the route to take. For example, when a user selects a starting point for a quest, the reception desk accepts that selection. It can also accept the user's selection of accompanying characters. Furthermore, it can accept the user's selection of the route to take. For instance, when a user selects a starting point for a quest, the reception desk presents multiple options for the user to choose from. The reception desk is designed to allow users to make intuitive selections through its user interface. For example, it displays graphical maps and character illustrations to allow users to visually confirm the options. It also includes detailed descriptions and background information to ensure users have sufficient information when making a selection. Furthermore, the reception desk records the user's selection history and has a function to suggest new options based on past choices. This allows users to enjoy a consistent narrative experience. For example, users who have previously selected a particular character will be presented with new quests and events related to that character. Furthermore, the reception desk can dynamically update its options in response to user choices. For example, if a user selects a particular route, new options related to that route will be presented one after another. This allows users to make flexible choices as the story progresses, resulting in a more immersive experience.

[0031] The generation unit uses a generation AI to generate a story in real time based on the selections received by the reception unit. For example, the generation unit generates a story based on the starting point of a quest selected by the user. It can also generate a story based on the accompanying characters selected by the user. Furthermore, the generation unit can generate a story based on the route to be taken by the user. For example, based on the starting point of a quest selected by the user, the generation unit generates a story that begins at that point. The generation unit uses a generation AI to create new events and character reactions based on the user's selections. The generation AI utilizes natural language processing technology to generate the story's development in real time according to the user's selections. For example, based on the starting point of a quest selected by the user, it generates a detailed description of the history, background, and characters of that location. The generation AI can also adjust the tone and style of the story according to the user's selections. For example, if the character selected by the user is a brave warrior, it generates a heroic story befitting that character. On the other hand, if the character selected by the user is a mysterious wizard, it generates a mystical story befitting that character. Furthermore, the generation unit can dynamically adjust the story's progression based on the user's selections. For example, if a user selects a specific route, the system generates new events and character reactions along that route. This allows users to make flexible choices as the story progresses, resulting in a more immersive experience. The generation unit can generate diverse stories based on the user's choices, using the training data of the generation AI. For instance, by analyzing past user selection data and learning the most popular story patterns, it can generate more engaging stories. This enables the generation unit to generate stories in real time based on user choices, creating new events and character reactions.

[0032] The creation unit generates new events and character reactions based on the story generated by the generation unit. For example, the creation unit generates events that occur at a starting point of a quest selected by the user. The creation unit can also generate character reactions based on the accompanying character selected by the user. Furthermore, the creation unit can generate events and character reactions along a route selected by the user. For example, the creation unit generates events that occur at a starting point of a quest selected by the user. The creation unit dynamically generates new events and character reactions in accordance with the progression of the story generated by the generation unit. For example, when the user arrives at the starting point of a quest selected by the user, it generates events that occur at that point and character reactions in real time. This allows the user to experience new events and character reactions in accordance with the progression of the story. Based on the output of the generation AI, the creation unit can generate a variety of events and character reactions according to the user's choices. For example, based on the starting point of a quest selected by the user, it generates detailed descriptions of events that occur at that point and characters that appear. Furthermore, the creation unit can dynamically adjust events and character reactions in response to user choices. For example, if a user selects a specific route, it can create new events and character reactions that align with that route. This allows users to make flexible choices as the story progresses, resulting in a more immersive experience. In addition, the creation unit can continuously update events and character reactions based on user choices. For example, if a user interacts with a specific character, it can dynamically adjust the character's reactions based on the content of that interaction. This allows users to experience new events and character reactions as the story progresses, resulting in a more consistent narrative experience.

[0033] The generation unit can generate stories in real time based on user choices. For example, the generation unit generates a story based on the starting point of a quest selected by the user. The generation unit uses a generation AI to create new events and character reactions based on user choices. For example, the generation unit generates a story that starts from the starting point of a quest selected by the user. The generation unit uses a generation AI to create new events and character reactions based on user choices. For example, the generation unit creates events that occur at the starting point of a quest selected by the user. This allows the generation unit to generate stories in real time based on user choices.

[0034] The creation unit can generate new events and character reactions based on the generated story. For example, the creation unit generates events that occur at a starting point of a quest selected by the user. The creation unit uses a generative AI to generate new events and character reactions based on the user's choices. For example, the creation unit generates events that occur at a starting point of a quest selected by the user. The creation unit uses a generative AI to generate new events and character reactions based on the user's choices. For example, the creation unit generates events that occur at a starting point of a quest selected by the user. This allows the creation unit to generate new events and character reactions based on the generated story.

[0035] The generation unit can generate a story that branches depending on the user's choices. For example, if the user makes a specific choice, the generation unit generates the story so that it proceeds in a different direction depending on that choice. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user makes a specific choice, the generation unit generates the story so that it proceeds in a different direction depending on that choice. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user makes a specific choice, the generation unit generates the story so that it proceeds in a different direction depending on that choice. As a result, the generation unit can generate a story that branches depending on the user's choices.

[0036] The creation unit can provide multiple endings depending on the user's choices. For example, if the user makes a specific choice, the creation unit will provide a different ending depending on that choice. The creation unit uses generative AI to create new events and character reactions based on the user's choices. For example, if the user makes a specific choice, the creation unit will provide a different ending depending on that choice. The creation unit uses generative AI to create new events and character reactions based on the user's choices. For example, if the user makes a specific choice, the creation unit will provide a different ending depending on that choice. In this way, the creation unit can provide multiple endings depending on the user's choices.

[0037] The reception desk can accept selections such as the quest's starting point, accompanying characters, and route. For example, when a user selects the quest's starting point, the reception desk accepts that selection. The reception desk uses generative AI to create new events and character reactions based on the user's selections. For example, when a user selects the quest's starting point, the reception desk accepts that selection. The reception desk uses generative AI to create new events and character reactions based on the user's selections. For example, when a user selects the quest's starting point, the reception desk accepts that selection. This allows the reception desk to accept selections such as the quest's starting point, accompanying characters, and route.

[0038] The reception desk can analyze the user's past selection history and prioritize presenting the most suitable options. For example, the reception desk can prioritize presenting similar options based on the user's past choices. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, the reception desk can prioritize presenting similar options based on the user's past choices. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, the reception desk can prioritize presenting similar options based on the user's past choices. This allows the reception desk to analyze the user's past selection history and prioritize presenting the most suitable options.

[0039] The reception desk can filter the options presented based on the user's current gameplay status and progress. For example, if the user is currently in the middle of a particular quest, the reception desk will prioritize presenting options related to that quest. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, if the user is currently in the middle of a particular quest, the reception desk will prioritize presenting options related to that quest. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, if the user is currently in the middle of a particular quest, the reception desk will prioritize presenting options related to that quest. This allows the reception desk to filter the options presented based on the user's current gameplay status and progress.

[0040] The reception desk can prioritize presenting highly relevant options by considering the user's geographical location when displaying choices. For example, if the user is in a specific region, the reception desk will prioritize presenting options related to that region. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, if the user is in a specific region, the reception desk will prioritize presenting options related to that region. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, if the user is in a specific region, the reception desk will prioritize presenting options related to that region. This allows the reception desk to prioritize presenting highly relevant options by considering the user's geographical location when displaying choices.

[0041] The reception desk can analyze the user's social media activity when presenting options and suggest relevant options. For example, the reception desk can suggest options related to topics the user has shown interest in on social media. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, the reception desk can suggest options related to topics the user has shown interest in on social media. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, the reception desk can suggest options related to topics the user has shown interest in on social media. This allows the reception desk to analyze the user's social media activity when presenting options and suggest relevant options.

[0042] The generation unit can adjust the level of detail in the story based on the user's selection history when generating the story. For example, if the user prefers detailed choices, the generation unit will increase the level of detail in the story. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers detailed choices, the generation unit will increase the level of detail in the story. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers detailed choices, the generation unit will increase the level of detail in the story. This allows the generation unit to adjust the level of detail in the story based on the user's selection history when generating the story.

[0043] The generation unit can apply different generation algorithms depending on the user's play style when generating a story. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. This allows the generation unit to apply different generation algorithms depending on the user's play style when generating a story.

[0044] The generation unit can determine the priority of the story based on the timing of the user's choices when generating the story. For example, if the user makes a choice early on, the generation unit will prioritize that story based on that choice. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user makes a choice early on, the generation unit will prioritize that story based on that choice. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user makes a choice early on, the generation unit will prioritize that story based on that choice. This allows the generation unit to determine the priority of the story based on the timing of the user's choices when generating the story.

[0045] The generation unit can adjust the order of stories based on user relevance when generating narratives. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating stories related to that character. The generation unit uses a generation AI to create new events and character reactions based on user choices. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating stories related to that character. The generation unit uses a generation AI to create new events and character reactions based on user choices. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating stories related to that character. This allows the generation unit to adjust the order of stories based on user relevance when generating narratives.

[0046] The generation unit can adjust the level of detail of responses based on the user's selection history when generating responses for events and characters. For example, if the user prefers detailed choices, the generation unit increases the level of detail of the responses. The generation unit uses generative AI to create new responses for events and characters based on the user's selections. For example, if the user prefers detailed choices, the generation unit increases the level of detail of the responses. The generation unit uses generative AI to create new responses for events and characters based on the user's selections. For example, if the user prefers detailed choices, the generation unit increases the level of detail of the responses. This allows the generation unit to adjust the level of detail of responses based on the user's selection history when generating responses for events and characters.

[0047] The generation unit can apply different generation algorithms depending on the user's play style when generating events and character reactions. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. This allows the generation unit to apply different generation algorithms depending on the user's play style when generating events and character reactions.

[0048] The generation unit can determine the priority of reactions based on the timing of the user's selection when generating reactions for events and characters. For example, if the user makes a selection early, the generation unit will prioritize the reaction based on that selection. The generation unit uses generative AI to create new reactions for events and characters based on the user's selection. For example, if the user makes a selection early, the generation unit will prioritize the reaction based on that selection. The generation unit uses generative AI to create new reactions for events and characters based on the user's selection. For example, if the user makes a selection early, the generation unit will prioritize the reaction based on that selection. As a result, the generation unit can determine the priority of reactions based on the timing of the user's selection when generating reactions for events and characters.

[0049] The generation unit can adjust the order of reactions based on user relevance when generating reactions for events and characters. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating reactions related to that character. The generation unit uses generative AI to create new reactions for events and characters based on user choices. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating reactions related to that character. The generation unit uses generative AI to create new reactions for events and characters based on user choices. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating reactions related to that character. This allows the generation unit to adjust the order of reactions based on user relevance when generating reactions for events and characters.

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

[0051] The interactive story generation system can dynamically change the background music of the story based on user choices. For example, different background music will play depending on the starting point of the quest selected by the user. Furthermore, if the user is accompanied by a specific character, theme music associated with that character can play. Additionally, the background music can change according to the route the user takes, enhancing the atmosphere of the story. This allows the user to have a more immersive experience.

[0052] An interactive story generation system can dynamically change the visual effects of a story based on user choices. For example, different visual effects will be displayed depending on the starting point of the quest selected by the user. Furthermore, if the user is accompanied by a specific character, visual effects related to that character can be displayed. Additionally, the visual effects can change depending on the route the user takes, emphasizing the atmosphere of the story. This allows users to have a more visually engaging experience.

[0053] An interactive story generation system can dynamically change the narration style of a story based on user choices. For example, a different narration style may be applied depending on the starting point of the quest selected by the user. Furthermore, if the user is accompanied by a specific character, a narration style associated with that character may be applied. Additionally, the narration style can change depending on the route the user takes, emphasizing the atmosphere of the story. This allows users to experience a wider variety of narratives.

[0054] An interactive story generation system can dynamically change the pace of the story based on user choices. For example, the story's pace can change depending on the starting point of the quest selected by the user. Furthermore, if the user is accompanied by a specific character, the story's pace can change to reflect that character. Additionally, the story's pace can change depending on the route the user takes, emphasizing the narrative's atmosphere. This allows users to enjoy the story at their own pace.

[0055] An interactive story generation system can dynamically change the narrative perspective based on user choices. For example, the story can unfold from different perspectives depending on the starting point of the quest selected by the user. Furthermore, if the user is accompanied by a specific character, the story can progress from that character's perspective. Additionally, the narrative perspective can change depending on the route the user takes, emphasizing the atmosphere of the story. This allows users to experience a more multifaceted narrative.

[0056] The following briefly describes the processing flow for example form 1.

[0057] Step 1: The reception desk accepts user selections. User selections include the quest starting point, accompanying characters, and the route to take. For example, when the user selects the quest starting point, the reception desk accepts that selection. It can also accept the user's selections regarding accompanying characters and the route to take. Step 2: The generation unit uses a generation AI to generate a story in real time based on the selections received by the reception unit. For example, it generates a story based on the user's selected quest starting point, accompanying characters, and route. Step 3: The creation unit generates new events and character reactions based on the story generated by the generation unit. For example, based on the starting point of the quest selected by the user, it generates events that occur at that point and the reactions of the accompanying characters.

[0058] (Example of form 2) An interactive story generation system according to an embodiment of the present invention is a system in which the user immerses themselves in a fantasy world and carries out various quests as the protagonist. In this interactive story generation system, the user makes choices about the story, and the generation AI generates the story in real time based on the user's choices, creating new events and character reactions. This system allows the story to branch based on the user's choices and provides multiple endings. This allows the user to explore the story through their own choices and increases the value of replayability. For example, the user makes a choice about the story. At this time, the user can choose from various options. For example, they can choose the starting point of the quest, the characters who will accompany them, and the route to take. This information is input to the generation AI. Next, the generation AI analyzes the input information and generates the story in real time. The generation AI creates new events and character reactions based on the user's choices. For example, if the user chooses a particular route, events and character reactions along that route will be generated. The generated story branches based on the user's choices. For example, if the user makes a particular choice, the story will proceed in a different direction depending on that choice. This allows the user to shape the story through their own choices. Furthermore, the system provides multiple endings. For example, different endings are generated depending on the user's choices. This allows users to experience different stories by replaying the game. This mechanism improves user engagement and satisfaction. Users can explore the story through their own choices and enjoy an interactive experience. Furthermore, improved accuracy and diversity in story generation leads to increased repeat visitor rates and attracts new users. For example, the user selects a starting point for a quest, and the generation AI generates a story based on that selection. If the user chooses to accompany a specific character, that character's reactions and events are generated. If the user chooses a route to take, events and character reactions along that route are generated. This allows users to shape the story through their choices and experience different stories by replaying the game.This allows the interactive story generation system to generate narratives in real time based on user choices, creating new events and character reactions.

[0059] The interactive story generation system according to this embodiment comprises a reception unit, a generation unit, and a creation unit. The reception unit receives user selections. User selections include, but are not limited to, the starting point of a quest, accompanying characters, and the route to be taken. For example, when the user selects a starting point for a quest, the reception unit receives that selection. The reception unit can also receive the user's selection of accompanying characters. Furthermore, the reception unit can also receive the user's selection of the route to be taken. For example, when the user selects a starting point for a quest, the reception unit presents multiple options and accepts the user's selection from among them. The generation unit uses a generation AI to generate a story in real time based on the selections received by the reception unit. For example, the generation unit generates a story based on the starting point of a quest selected by the user. The generation unit can also generate a story based on the accompanying characters selected by the user. Furthermore, the generation unit can also generate a story based on the route to be taken by the user. For example, the generation unit generates a story that starts from the starting point of a quest selected by the user. The generation unit uses a generation AI to create new events and character reactions based on the user's selection. The creation unit creates new events and character reactions based on the story generated by the generation unit. For example, the creation unit creates events that occur at a starting point of a quest selected by the user. The creation unit can also create character reactions based on the accompanying character selected by the user. Furthermore, the creation unit can create events and character reactions along a route selected by the user. For example, the creation unit creates events that occur at a starting point of a quest selected by the user. As a result, the interactive story generation system according to this embodiment can generate a story in real time based on the user's selection and create new events and character reactions.

[0060] The reception desk accepts user selections. These selections include, but are not limited to, the starting point of a quest, the characters accompanying the user, and the route to take. For example, when a user selects a starting point for a quest, the reception desk accepts that selection. It can also accept the user's selection of accompanying characters. Furthermore, it can accept the user's selection of the route to take. For instance, when a user selects a starting point for a quest, the reception desk presents multiple options for the user to choose from. The reception desk is designed to allow users to make intuitive selections through its user interface. For example, it displays graphical maps and character illustrations to allow users to visually confirm the options. It also includes detailed descriptions and background information to ensure users have sufficient information when making a selection. Furthermore, the reception desk records the user's selection history and has a function to suggest new options based on past choices. This allows users to enjoy a consistent narrative experience. For example, users who have previously selected a particular character will be presented with new quests and events related to that character. Furthermore, the reception desk can dynamically update its options in response to user choices. For example, if a user selects a particular route, new options related to that route will be presented one after another. This allows users to make flexible choices as the story progresses, resulting in a more immersive experience.

[0061] The generation unit uses a generation AI to generate a story in real time based on the selections received by the reception unit. For example, the generation unit generates a story based on the starting point of a quest selected by the user. It can also generate a story based on the accompanying characters selected by the user. Furthermore, the generation unit can generate a story based on the route to be taken by the user. For example, based on the starting point of a quest selected by the user, the generation unit generates a story that begins at that point. The generation unit uses a generation AI to create new events and character reactions based on the user's selections. The generation AI utilizes natural language processing technology to generate the story's development in real time according to the user's selections. For example, based on the starting point of a quest selected by the user, it generates a detailed description of the history, background, and characters of that location. The generation AI can also adjust the tone and style of the story according to the user's selections. For example, if the character selected by the user is a brave warrior, it generates a heroic story befitting that character. On the other hand, if the character selected by the user is a mysterious wizard, it generates a mystical story befitting that character. Furthermore, the generation unit can dynamically adjust the story's progression based on the user's selections. For example, if a user selects a specific route, the system generates new events and character reactions along that route. This allows users to make flexible choices as the story progresses, resulting in a more immersive experience. The generation unit can generate diverse stories based on the user's choices, using the training data of the generation AI. For instance, by analyzing past user selection data and learning the most popular story patterns, it can generate more engaging stories. This enables the generation unit to generate stories in real time based on user choices, creating new events and character reactions.

[0062] The creation unit generates new events and character reactions based on the story generated by the generation unit. For example, the creation unit generates events that occur at a starting point of a quest selected by the user. The creation unit can also generate character reactions based on the accompanying character selected by the user. Furthermore, the creation unit can generate events and character reactions along a route selected by the user. For example, the creation unit generates events that occur at a starting point of a quest selected by the user. The creation unit dynamically generates new events and character reactions in accordance with the progression of the story generated by the generation unit. For example, when the user arrives at the starting point of a quest selected by the user, it generates events that occur at that point and character reactions in real time. This allows the user to experience new events and character reactions in accordance with the progression of the story. Based on the output of the generation AI, the creation unit can generate a variety of events and character reactions according to the user's choices. For example, based on the starting point of a quest selected by the user, it generates detailed descriptions of events that occur at that point and characters that appear. Furthermore, the creation unit can dynamically adjust events and character reactions in response to user choices. For example, if a user selects a specific route, it can create new events and character reactions that align with that route. This allows users to make flexible choices as the story progresses, resulting in a more immersive experience. In addition, the creation unit can continuously update events and character reactions based on user choices. For example, if a user interacts with a specific character, it can dynamically adjust the character's reactions based on the content of that interaction. This allows users to experience new events and character reactions as the story progresses, resulting in a more consistent narrative experience.

[0063] The generation unit can generate stories in real time based on user choices. For example, the generation unit generates a story based on the starting point of a quest selected by the user. The generation unit uses a generation AI to create new events and character reactions based on user choices. For example, the generation unit generates a story that starts from the starting point of a quest selected by the user. The generation unit uses a generation AI to create new events and character reactions based on user choices. For example, the generation unit creates events that occur at the starting point of a quest selected by the user. This allows the generation unit to generate stories in real time based on user choices.

[0064] The creation unit can generate new events and character reactions based on the generated story. For example, the creation unit generates events that occur at a starting point of a quest selected by the user. The creation unit uses a generative AI to generate new events and character reactions based on the user's choices. For example, the creation unit generates events that occur at a starting point of a quest selected by the user. The creation unit uses a generative AI to generate new events and character reactions based on the user's choices. For example, the creation unit generates events that occur at a starting point of a quest selected by the user. This allows the creation unit to generate new events and character reactions based on the generated story.

[0065] The generation unit can generate a story that branches depending on the user's choices. For example, if the user makes a specific choice, the generation unit generates the story so that it proceeds in a different direction depending on that choice. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user makes a specific choice, the generation unit generates the story so that it proceeds in a different direction depending on that choice. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user makes a specific choice, the generation unit generates the story so that it proceeds in a different direction depending on that choice. As a result, the generation unit can generate a story that branches depending on the user's choices.

[0066] The creation unit can provide multiple endings depending on the user's choices. For example, if the user makes a specific choice, the creation unit will provide a different ending depending on that choice. The creation unit uses generative AI to create new events and character reactions based on the user's choices. For example, if the user makes a specific choice, the creation unit will provide a different ending depending on that choice. The creation unit uses generative AI to create new events and character reactions based on the user's choices. For example, if the user makes a specific choice, the creation unit will provide a different ending depending on that choice. In this way, the creation unit can provide multiple endings depending on the user's choices.

[0067] The reception desk can accept selections such as the quest's starting point, accompanying characters, and route. For example, when a user selects the quest's starting point, the reception desk accepts that selection. The reception desk uses generative AI to create new events and character reactions based on the user's selections. For example, when a user selects the quest's starting point, the reception desk accepts that selection. The reception desk uses generative AI to create new events and character reactions based on the user's selections. For example, when a user selects the quest's starting point, the reception desk accepts that selection. This allows the reception desk to accept selections such as the quest's starting point, accompanying characters, and route.

[0068] The reception desk can estimate the user's emotions and adjust how options are presented based on the estimated emotions. For example, if the user is excited, the reception desk may visually highlight the options. The reception desk is implemented using emotion estimation functionality with an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. For example, if the user is excited, the reception desk may visually highlight the options. The reception desk may also present options in calm colors if the user is relaxed. Furthermore, if the user is stressed, the reception desk may present options in a simplified manner. For example, if the user is relaxed, the reception desk may present options in calm colors. This allows the reception desk to adjust how options are presented based on the user's emotions.

[0069] The reception desk can analyze the user's past selection history and prioritize presenting the most suitable options. For example, the reception desk can prioritize presenting similar options based on the user's past choices. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, the reception desk can prioritize presenting similar options based on the user's past choices. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, the reception desk can prioritize presenting similar options based on the user's past choices. This allows the reception desk to analyze the user's past selection history and prioritize presenting the most suitable options.

[0070] The reception desk can filter the options presented based on the user's current gameplay status and progress. For example, if the user is currently in the middle of a particular quest, the reception desk will prioritize presenting options related to that quest. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, if the user is currently in the middle of a particular quest, the reception desk will prioritize presenting options related to that quest. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, if the user is currently in the middle of a particular quest, the reception desk will prioritize presenting options related to that quest. This allows the reception desk to filter the options presented based on the user's current gameplay status and progress.

[0071] The reception desk can estimate the user's emotions and prioritize options based on those emotions. For example, if the user is excited, the reception desk will prioritize options that require action. The reception desk is implemented using emotion estimation capabilities, such as an emotion engine or generative AI. Generative AI includes, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. For example, if the user is excited, the reception desk will prioritize options that require action. The reception desk can also prioritize options that have a strong storyline if the user is relaxed. Furthermore, if the user is stressed, the reception desk can prioritize simple options. For example, if the user is relaxed, the reception desk will prioritize options that have a strong storyline. This allows the reception desk to prioritize options based on the user's emotions.

[0072] The reception desk can prioritize presenting highly relevant options by considering the user's geographical location when displaying choices. For example, if the user is in a specific region, the reception desk will prioritize presenting options related to that region. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, if the user is in a specific region, the reception desk will prioritize presenting options related to that region. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, if the user is in a specific region, the reception desk will prioritize presenting options related to that region. This allows the reception desk to prioritize presenting highly relevant options by considering the user's geographical location when displaying choices.

[0073] The reception desk can analyze the user's social media activity when presenting options and suggest relevant options. For example, the reception desk can suggest options related to topics the user has shown interest in on social media. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, the reception desk can suggest options related to topics the user has shown interest in on social media. The reception desk uses generative AI to create new events and character reactions based on the user's choices. For example, the reception desk can suggest options related to topics the user has shown interest in on social media. This allows the reception desk to analyze the user's social media activity when presenting options and suggest relevant options.

[0074] The generation unit can estimate the user's emotions and adjust the narrative development based on those emotions. For example, if the user is excited, the generation unit will speed up the narrative development. The generation unit is implemented using emotion estimation capabilities, such as an emotion engine or generative AI. Generative AI can be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. For example, if the user is excited, the generation unit will speed up the narrative development. The generation unit can also develop the narrative at a leisurely pace if the user is relaxed. Furthermore, if the user is stressed, the generation unit can simplify the narrative development. For example, if the user is relaxed, the generation unit will develop the narrative at a leisurely pace. In this way, the generation unit can adjust the narrative development based on the user's emotions.

[0075] The generation unit can adjust the level of detail in the story based on the user's selection history when generating the story. For example, if the user prefers detailed choices, the generation unit will increase the level of detail in the story. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers detailed choices, the generation unit will increase the level of detail in the story. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers detailed choices, the generation unit will increase the level of detail in the story. This allows the generation unit to adjust the level of detail in the story based on the user's selection history when generating the story.

[0076] The generation unit can apply different generation algorithms depending on the user's play style when generating a story. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. This allows the generation unit to apply different generation algorithms depending on the user's play style when generating a story.

[0077] The generation unit can estimate the user's emotions and adjust the length of the story based on those emotions. For example, if the user is in a hurry, the generation unit will shorten the story. The generation unit is implemented using emotion estimation capabilities, such as an emotion engine or generative AI. Generative AI can be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. For example, if the user is in a hurry, the generation unit will shorten the story. The generation unit can also lengthen the story if the user is relaxed. Furthermore, if the user is excited, the generation unit can adjust the story length appropriately. For example, if the user is relaxed, the generation unit will lengthen the story. In this way, the generation unit can adjust the length of the story based on the user's emotions.

[0078] The generation unit can determine the priority of the story based on the timing of the user's choices when generating the story. For example, if the user makes a choice early on, the generation unit will prioritize that story based on that choice. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user makes a choice early on, the generation unit will prioritize that story based on that choice. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user makes a choice early on, the generation unit will prioritize that story based on that choice. This allows the generation unit to determine the priority of the story based on the timing of the user's choices when generating the story.

[0079] The generation unit can adjust the order of stories based on user relevance when generating narratives. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating stories related to that character. The generation unit uses a generation AI to create new events and character reactions based on user choices. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating stories related to that character. The generation unit uses a generation AI to create new events and character reactions based on user choices. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating stories related to that character. This allows the generation unit to adjust the order of stories based on user relevance when generating narratives.

[0080] The creation unit can estimate the user's emotions and adjust events and character reactions based on the estimated emotions. For example, if the user is excited, the creation unit will make character reactions more active. The creation unit is implemented using emotion estimation capabilities with an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. For example, if the user is excited, the creation unit will make character reactions more active. The creation unit can also make character reactions calmer if the user is relaxed. Furthermore, if the user is stressed, the creation unit can simplify events. For example, if the user is relaxed, the creation unit will make character reactions calmer. In this way, the creation unit can adjust events and character reactions based on the user's emotions.

[0081] The generation unit can adjust the level of detail of responses based on the user's selection history when generating responses for events and characters. For example, if the user prefers detailed choices, the generation unit increases the level of detail of the responses. The generation unit uses generative AI to create new responses for events and characters based on the user's selections. For example, if the user prefers detailed choices, the generation unit increases the level of detail of the responses. The generation unit uses generative AI to create new responses for events and characters based on the user's selections. For example, if the user prefers detailed choices, the generation unit increases the level of detail of the responses. This allows the generation unit to adjust the level of detail of responses based on the user's selection history when generating responses for events and characters.

[0082] The generation unit can apply different generation algorithms depending on the user's play style when generating events and character reactions. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. The generation unit uses a generation AI to create new events and character reactions based on the user's choices. For example, if the user prefers action, the generation unit will apply an action-oriented generation algorithm. This allows the generation unit to apply different generation algorithms depending on the user's play style when generating events and character reactions.

[0083] The creation unit can estimate the user's emotions and determine the priority of events and character reactions based on the estimated emotions. For example, if the user is excited, the creation unit will prioritize generating events with high action. The creation unit is implemented using emotion estimation capabilities with an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. For example, if the user is excited, the creation unit will prioritize generating events with high action. The creation unit can also prioritize generating events with high storytelling if the user is relaxed. Furthermore, if the user is stressed, the creation unit can also prioritize generating simple events. For example, if the user is relaxed, the creation unit will prioritize generating events with high storytelling. This allows the creation unit to determine the priority of events and character reactions based on the user's emotions.

[0084] The generation unit can determine the priority of reactions based on the timing of the user's selection when generating reactions for events and characters. For example, if the user makes a selection early, the generation unit will prioritize the reaction based on that selection. The generation unit uses generative AI to create new reactions for events and characters based on the user's selection. For example, if the user makes a selection early, the generation unit will prioritize the reaction based on that selection. The generation unit uses generative AI to create new reactions for events and characters based on the user's selection. For example, if the user makes a selection early, the generation unit will prioritize the reaction based on that selection. As a result, the generation unit can determine the priority of reactions based on the timing of the user's selection when generating reactions for events and characters.

[0085] The generation unit can adjust the order of reactions based on user relevance when generating reactions for events and characters. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating reactions related to that character. The generation unit uses generative AI to create new reactions for events and characters based on user choices. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating reactions related to that character. The generation unit uses generative AI to create new reactions for events and characters based on user choices. For example, if the user makes a choice related to a specific character, the generation unit will prioritize generating reactions related to that character. This allows the generation unit to adjust the order of reactions based on user relevance when generating reactions for events and characters.

[0086] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0087] The interactive story generation system can dynamically change the background music of the story based on user choices. For example, different background music will play depending on the starting point of the quest selected by the user. Furthermore, if the user is accompanied by a specific character, theme music associated with that character can play. Additionally, the background music can change according to the route the user takes, enhancing the atmosphere of the story. This allows the user to have a more immersive experience.

[0088] An interactive story generation system can dynamically change the visual effects of a story based on user choices. For example, different visual effects will be displayed depending on the starting point of the quest selected by the user. Furthermore, if the user is accompanied by a specific character, visual effects related to that character can be displayed. Additionally, the visual effects can change depending on the route the user takes, emphasizing the atmosphere of the story. This allows users to have a more visually engaging experience.

[0089] An interactive story generation system can dynamically change the narration style of a story based on user choices. For example, a different narration style may be applied depending on the starting point of the quest selected by the user. Furthermore, if the user is accompanied by a specific character, a narration style associated with that character may be applied. Additionally, the narration style can change depending on the route the user takes, emphasizing the atmosphere of the story. This allows users to experience a wider variety of narratives.

[0090] An interactive story generation system can dynamically change the pace of the story based on user choices. For example, the story's pace can change depending on the starting point of the quest selected by the user. Furthermore, if the user is accompanied by a specific character, the story's pace can change to reflect that character. Additionally, the story's pace can change depending on the route the user takes, emphasizing the narrative's atmosphere. This allows users to enjoy the story at their own pace.

[0091] An interactive story generation system can dynamically change the narrative perspective based on user choices. For example, the story can unfold from different perspectives depending on the starting point of the quest selected by the user. Furthermore, if the user is accompanied by a specific character, the story can progress from that character's perspective. Additionally, the narrative perspective can change depending on the route the user takes, emphasizing the atmosphere of the story. This allows users to experience a more multifaceted narrative.

[0092] An interactive story generation system can estimate the user's emotions and dynamically adjust the difficulty of the story based on those emotions. For example, if the user is excited, the difficulty of the story can be increased. Conversely, if the user is relaxed, the difficulty can be decreased. Furthermore, if the user is stressed, the difficulty can be appropriately adjusted. This allows users to enjoy the story at an optimal difficulty level that suits their emotions.

[0093] An interactive story generation system can estimate the user's emotions and dynamically adjust the number of story choices based on those emotions. For example, if the user is excited, the number of choices can be increased. If the user is relaxed, the number of choices can be decreased. Furthermore, if the user is stressed, the number of choices can be appropriately adjusted. This allows the user to enjoy the story with the optimal number of choices that suits their emotions.

[0094] An interactive story generation system can estimate the user's emotions and dynamically adjust the behavior of the story's characters based on those emotions. For example, if the user is excited, the characters' behavior can be made more energetic. If the user is relaxed, the characters' behavior can be made calmer. Furthermore, if the user is stressed, the characters' behavior can be simplified. This allows users to enjoy the story with characters behaving in a way that best suits their emotions.

[0095] An interactive story generation system can estimate the user's emotions and dynamically adjust the type of story ending based on those emotions. For example, if the user is excited, it can provide an action-packed ending. If the user is relaxed, it can provide a more story-driven ending. Furthermore, if the user is stressed, it can provide a simple ending. This allows users to enjoy the story with the ending that best suits their emotions.

[0096] An interactive story generation system can estimate the user's emotions and dynamically adjust the pace of the story based on those emotions. For example, if the user is excited, the story's pace can be sped up. If the user is relaxed, the pace can be slowed down. Furthermore, if the user is stressed, the pace can be adjusted appropriately. This allows users to enjoy the story at an optimal pace that suits their emotions.

[0097] The following briefly describes the processing flow for example form 2.

[0098] Step 1: The reception desk accepts user selections. User selections include the quest starting point, accompanying characters, and the route to take. For example, when the user selects the quest starting point, the reception desk accepts that selection. It can also accept the user's selections regarding accompanying characters and the route to take. Step 2: The generation unit uses a generation AI to generate a story in real time based on the selections received by the reception unit. For example, it generates a story based on the user's selected quest starting point, accompanying characters, and route. Step 3: The creation unit generates new events and character reactions based on the story generated by the generation unit. For example, based on the starting point of the quest selected by the user, it generates events that occur at that point and the reactions of the accompanying characters.

[0099] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0100] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0101] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, 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.

[0102] Each of the multiple elements, including the reception unit, generation unit, and creation unit described above, is implemented in at least one of the smart device 14 and the data processing device 12. For example, the reception unit is implemented by the control unit 46A of the smart device 14 and accepts user selections. The generation unit is implemented by the specific processing unit 290 of the data processing device 12 and generates a story in real time using a generation AI. The creation unit is implemented by the specific processing unit 290 of the data processing device 12 and creates new events and character reactions based on the generated story. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0103] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0104] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0105] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0106] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0107] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0108] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0109] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0110] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0111] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0112] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0113] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. 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 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0114] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0115] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0116] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0117] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0118] Each of the multiple elements, including the reception unit, generation unit, and creation unit described above, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the smart glasses 214 and accepts the user's selection. The generation unit is implemented by the specific processing unit 290 of the data processing unit 12 and generates a story in real time using a generation AI. The creation unit is implemented by the specific processing unit 290 of the data processing unit 12 and creates new events and character reactions based on the generated story. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0119] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0120] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0121] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0122] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0123] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0124] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0125] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0126] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0127] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0128] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0129] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0130] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0131] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0132] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0133] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0134] Each of the multiple elements, including the reception unit, generation unit, and creation unit described above, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the headset terminal 314 and accepts user selections. The generation unit is implemented by the specific processing unit 290 of the data processing unit 12 and generates a story in real time using a generation AI. The creation unit is implemented by the specific processing unit 290 of the data processing unit 12 and creates new events and character reactions based on the generated story. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0135] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0136] As shown in Figure 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.

[0137] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0138] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0139] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0140] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0141] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0142] The controlled 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 robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0143] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0144] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0145] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0146] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0147] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0148] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0149] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0150] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0151] Each of the multiple elements, including the reception unit, generation unit, and creation unit described above, is implemented in at least one of the robot 414 and the data processing unit 12. For example, the reception unit is implemented by the control unit 46A of the robot 414 and accepts user selections. The generation unit is implemented by the specific processing unit 290 of the data processing unit 12 and generates a story in real time using a generation AI. The creation unit is implemented by the specific processing unit 290 of the data processing unit 12 and creates new events and character reactions based on the generated story. The correspondence between each unit and the device or control unit is not limited to the example described above and can be modified in various ways.

[0152] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0153] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0154] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0155] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0156] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0157] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0158] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0159] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0160] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0161] 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.

[0162] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0163] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0164] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0165] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0166] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0167] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0168] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0169] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0170] (Note 1) A reception desk that accepts user selections, A generation unit generates a story in real time based on the selection received by the reception unit, The system comprises a creation unit that creates new events and character reactions based on the story generated by the generation unit. A system characterized by the following features. (Note 2) The generating unit is Generate stories in real time based on user choices. The system described in Appendix 1, characterized by the features described herein. (Note 3) The creation unit is, Create new events and character reactions based on the generated story. The system described in Appendix 1, characterized by the features described herein. (Note 4) The generating unit is The story is generated in a way that branches based on the user's choices. The system described in Appendix 1, characterized by the features described herein. (Note 5) The creation unit is, Provides multiple endings depending on the user's choice. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned reception unit is The game allows you to choose the starting point of the quest, the characters who will accompany you, and the route you will take. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned reception unit is It estimates the user's emotions and adjusts how choices are presented based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned reception unit is Analyze the user's past selection history and prioritize presenting the most suitable options. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned reception unit is When presenting options, filtering is performed based on the user's current gameplay status and progress. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned reception unit is It estimates the user's emotions and determines the priority of choices based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned reception unit is When presenting options, the system prioritizes showing the most relevant options by considering the user's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned reception unit is When presenting options, analyze the user's social media activity and suggest relevant options. The system described in Appendix 1, characterized by the features described herein. (Note 13) The generating unit is It estimates the user's emotions and adjusts the story's progression based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 14) The generating unit is When generating a story, adjust the level of detail in the story based on the user's selection history. The system described in Appendix 1, characterized by the features described herein. (Note 15) The generating unit is When generating a story, different generation algorithms are applied depending on the user's play style. The system described in Appendix 1, characterized by the features described herein. (Note 16) The generating unit is It estimates the user's emotions and adjusts the length of the story based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 17) The generating unit is During story generation, the priority of the story is determined based on the timing of the user's selection. The system described in Appendix 1, characterized by the features described herein. (Note 18) The generating unit is During story generation, the order of stories is adjusted based on user relevance. The system described in Appendix 1, characterized by the features described herein. (Note 19) The creation unit is, It estimates the user's emotions and adjusts the reactions of events and characters based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 20) The creation unit is, When generating reactions for events and characters, adjust the level of detail of the reactions based on the user's selection history. The system described in Appendix 1, characterized by the features described herein. (Note 21) The creation unit is, When generating events and character reactions, different generation algorithms are applied depending on the user's play style. The system described in Appendix 1, characterized by the features described herein. (Note 22) The creation unit is, It estimates the user's emotions and determines the priority of events and character reactions based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 23) The creation unit is, When generating reactions for events and characters, the priority of these reactions is determined based on the timing of the user's selection. The system described in Appendix 1, characterized by the features described herein. (Note 24) The creation unit is, When generating reactions from events and characters, the order of reactions is adjusted based on user relevance. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0171] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. A reception desk that accepts user selections, A generation unit generates a story in real time based on the selection received by the reception unit, The system comprises a creation unit that creates new events and character reactions based on the story generated by the generation unit. A system characterized by the following features.

2. The generating unit is Generate stories in real time based on user choices. The system according to feature 1.

3. The creation unit is, Create new events and character reactions based on the generated story. The system according to feature 1.

4. The generating unit is The story is generated in a way that branches based on the user's choices. The system according to feature 1.

5. The creation unit is, Provides multiple endings depending on the user's choice. The system according to feature 1.

6. The aforementioned reception unit is The game allows you to choose the starting point of the quest, the characters who will accompany you, and the route you will take. The system according to feature 1.

7. The aforementioned reception unit is It estimates the user's emotions and adjusts how choices are presented based on those estimated emotions. The system according to feature 1.

8. The aforementioned reception unit is Analyze the user's past selection history and prioritize presenting the most suitable options. The system according to feature 1.

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