system

Abstract

An object of the system according to the embodiment is to allow an individual user to easily create an original short video.SOLUTION: A system includes an input part, a generation part, an animation creation part, and a provision part. The input unit receives a situation, characters, and lines from a user. The generation section generates an original script on the basis of the information received by the input section. The animation creating section creates a CG animation of the character based on the script generated by the generating section. The providing unit generates a short moving image based on the CG animation created by the animation creating unit, and provides the short moving image to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has had the problem that it is difficult for individual users to easily create original short videos.

[0005] The system according to the embodiment aims to enable individual users to easily create original short videos. [Means for solving the problem]

[0006] The system according to the embodiment includes an input unit, a generation unit, an animation creation unit, and a provision unit. The input unit receives a situation, characters, and lines from a user. The generation unit generates an original script based on the information received by the input unit. The animation creation unit creates CG animation of characters based on the script generated by the generation unit. The provision unit generates a short video based on the CG animation created by the animation creation unit and provides it to the user. [Effects of the Invention]

[0007] The system according to the embodiment allows individual users to easily create original short videos. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The short video production system according to an embodiment of the present invention is a system in which a generation AI automatically generates an original script based on a situation, characters, and lines input by a user, and a video generation AI creates CG animation of the characters. This allows the short video production system to allow users to easily create original short videos and provide special content.

[0029] A short video creation system according to an embodiment includes an input unit, a generation unit, an animation creation unit, and a provision unit. The input unit accepts a situation, characters, and lines from a user. For example, a user can input a situation such as "a summer beach date," characters such as "the protagonist is me and my partner," and specific lines such as "Let's enjoy this moment together." The generation unit generates an original script based on the information accepted by the input unit. For example, the generation AI automatically generates a detailed script based on the situation, characters, and lines entered by the user. The generation AI uses a text generation AI (e.g., LLM) to depict the actions and conversations of the characters based on the situation. The animation creation unit creates CG animation of the characters based on the script generated by the generation unit. For example, the video generation AI faithfully reproduces the appearance and movements of the characters specified by the user and adds backgrounds and effects appropriate to the situation. The provision unit generates a short video based on the CG animation created by the animation creation unit and provides it to the user. For example, the generated short video can be downloaded by the user or shared on social networking sites. As a result, the short video creation system according to the embodiment allows users to easily create original short videos and provide special content.

[0030] The input unit allows the generation AI to automatically complete details of the situation and characters entered by the user, generating more specific prompts. For example, if a user enters "a summer date at the beach," the generation AI automatically completes details such as the weather, time of day, and surrounding environment to generate a more specific situation. If a user enters "the main characters are me and my partner," the generation AI automatically completes the relationship between the two and past episodes, creating a deeper character setting. If a user enters "the line is 'Let's enjoy this moment together,'" the generation AI automatically completes the conversation and situation before and after the line is spoken, creating a natural flow. This allows the information entered by the user to be completed and more specific prompts to be generated.

[0031] The input unit allows the generation AI to refer to a database of similar past situations and characters based on the information entered by the user and propose the optimal scenario. For example, if the user enters "a summer date at the beach," the input unit allows the generation AI to refer to similar past situations from the database and propose the optimal scenario. Also, if the user enters "the protagonist is me and my partner," the generation AI will refer to similar past character settings from the database and propose the optimal scenario. Also, if the user enters "the line is 'Let's enjoy this moment together,'" the generation AI will refer to similar past lines from the database and propose the optimal scenario. This allows the generation AI to refer to a database of similar past situations and characters and propose the optimal scenario.

[0032] The input unit can allow users to input situations and characters using a multimodal interface, such as voice input or gesture input. For example, when a user uses voice input to say, "A summer date at the beach," the generation AI analyzes the voice and automatically sets the situation. Also, when a user uses gesture input to indicate the character's movements, the generation AI analyzes the gesture and sets the character's movements. Also, when a user uses voice input to say, "The line is 'Let's enjoy this moment together,'" the generation AI analyzes the voice and automatically sets the line. This allows users to input situations and characters using a multimodal interface, such as voice input or gesture input.

[0033] Based on the information entered by the user, the input unit allows the AI ​​to suggest situations and characters that reflect different cultures and historical backgrounds. For example, if a user enters "a summer beach date," the AI ​​will suggest situations that reflect different cultures and historical backgrounds, such as Edo-period Japan or modern-day Hawaii. If a user enters "the protagonists are me and my partner," the AI ​​will suggest characters that reflect different cultures and historical backgrounds, such as ancient Roman warriors or astronauts from the future. If a user enters "the line is 'Let's enjoy this moment together,'" the AI ​​will suggest lines that reflect different cultures and historical backgrounds, such as Shakespearean lines or futuristic slang. This allows the AI ​​to suggest situations and characters that reflect different cultures and historical backgrounds.

[0034] The generation unit can learn the user's past input history and preferences to generate a more personalized script. For example, the generation AI of the generation unit learns the user's past input history and generates a script that suits the user's preferences. For example, it reflects the tendencies of situations and characters entered in the past. The generation AI also learns the user's preferences and generates a script specialized for a specific genre or theme. For example, if the user likes romance dramas, it generates a script for romance dramas. The generation AI also reuses specific characters and lines based on the user's past input history. For example, it reintroduces characters that the user created in the past. This makes it possible to generate a more personalized script based on the user's past input history and preferences.

[0035] The generation unit can automatically generate scenarios that combine different genres. For example, the generation AI can automatically generate a scenario that combines comedy and drama. For example, by adding humor to moving scenes, it can create a balanced script. The generation AI can also automatically generate a scenario that combines action and romance. For example, it can incorporate romantic elements into action scenes. The generation AI can also automatically generate a scenario that combines horror and comedy. For example, it can introduce humorous characters into scary scenes. This makes it possible to automatically generate scenarios that combine different genres.

[0036] The generation unit can add a function to incorporate music and sound effects specified by the user into the scenario. For example, the generation unit allows the generation AI to incorporate music specified by the user into the scenario. For example, background music that matches a specific scene is automatically inserted. The generation AI also incorporates sound effects specified by the user into the scenario. For example, sound effects are added to action scenes. The generation AI also provides a function to incorporate music and sound effects specified by the user into the scenario. For example, a music file uploaded by the user is reflected in the scenario. This allows the music and sound effects specified by the user to be incorporated into the scenario.

[0037] The animation creation unit can generate more realistic characters based on the user's photos and videos. In the animation creation unit, for example, the image generation AI generates a realistic character based on the user's photos. For example, it creates a character that reflects the user's facial features. The image generation AI also generates a realistic character based on the user's videos. For example, it creates a character that reflects the user's movements and expressions. The image generation AI also generates a realistic character based on the user's photos and videos. For example, it creates a character that reflects the user's clothing and hairstyle. This allows more realistic characters to be generated based on the user's photos and videos.

[0038] The animation creation unit can generate realistic backgrounds and effects according to the season and time of day specified by the user. In the animation creation unit, for example, the video generation AI generates backgrounds according to the season specified by the user. For example, it recreates blue skies and oceans in summer scenes, and snowy scenery in winter scenes. The video generation AI also generates backgrounds according to the time of day specified by the user. For example, it recreates a sunrise in a morning scene, and a starry sky in a night scene. The video generation AI also generates effects according to the season and time of day specified by the user. For example, it adds an effect of falling leaves in an autumn scene, and a sunset effect in an evening scene. This makes it possible to generate realistic backgrounds and effects according to the season and time of day specified by the user.

[0039] The animation creation unit can add a function that allows different art styles to be selected. The animation creation unit, for example, provides a function that allows the image generation AI to generate anime-style characters. For example, when a user selects an anime-style style, the character is drawn in an anime style. The image generation AI also provides a function that allows the image generation AI to generate realistic-style characters. For example, when a user selects a realistic style, the character is drawn realistically. The image generation AI also provides a function that allows the image generation AI to select different art styles. For example, the user can select a cartoon style or a 3D style. This allows the addition of a function that allows different art styles to be selected.

[0040] The animation creation unit can add a function to synchronize the character's movements with music and sound effects specified by the user. For example, the animation creation unit synchronizes the character's movements with music specified by the user using a video generation AI. For example, the character dances to the rhythm of the music in a dance scene. The video generation AI also synchronizes the character's movements with sound effects specified by the user. For example, the character moves to the sound effects in an action scene. The video generation AI also provides a function to synchronize the character's movements with music and sound effects. For example, the character moves to the music file uploaded by the user. This makes it possible to add a function to synchronize the character's movements with music and sound effects specified by the user.

[0041] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0042] The input section allows the AI ​​to automatically complete the details of the situation and characters entered by the user, generating more specific prompts. For example, if a user enters "a summer date at the beach," the AI ​​automatically completes details such as the weather, time of day, and surrounding environment to generate a more specific situation. If a user enters "the main characters are me and my partner," the AI ​​automatically completes the relationship between the two and past episodes, creating a deeper characterization. If a user enters "the line is 'Let's enjoy this moment together,'" the AI ​​automatically completes the conversation and situation before and after the line, creating a natural flow. This allows the AI ​​to complete the information entered by the user and generate more specific prompts.

[0043] The input unit allows the generation AI to refer to a database of similar past situations and characters based on the information entered by the user, and propose the optimal scenario. For example, if the user enters "a summer date at the beach," the generation AI will refer to similar past situations from the database and propose the optimal scenario. Also, if the user enters "the protagonist is me and my partner," the generation AI will refer to similar past character settings from the database and propose the optimal scenario. Also, if the user enters "the line is 'Let's enjoy this moment together,'" the generation AI will refer to similar past lines from the database and propose the optimal scenario. This allows the generation AI to refer to a database of similar past situations and characters and propose the optimal scenario.

[0044] The input unit can allow users to input situations and characters using a multimodal interface, such as voice input or gesture input. For example, if a user says "A summer date at the beach" via voice input, the generation AI analyzes the voice and automatically sets the situation. Also, if the user indicates the character's movements using gesture input, the generation AI analyzes the gesture and sets the character's movements. Also, if a user says "The line is 'Let's enjoy this moment together' via voice input," the generation AI analyzes the voice and automatically sets the line. This allows users to input situations and characters using a multimodal interface, such as voice input or gesture input.

[0045] The generation unit can learn the user's past input history and preferences to generate more personalized scripts. For example, the generation AI can learn the user's past input history and generate a script that suits their preferences. For example, it can reflect the tendencies of situations and characters entered in the past. The generation AI can also learn the user's preferences and generate a script specialized for a specific genre or theme. For example, if the user likes romance dramas, it can generate a script for romance dramas. The generation AI can also reuse specific characters and lines based on the user's past input history. For example, it can reintroduce characters that the user created in the past. This makes it possible to generate a more personalized script based on the user's past input history and preferences.

[0046] The generation unit can automatically generate scenarios that combine different genres. For example, the generation AI can automatically generate a scenario that combines comedy and drama. For example, by adding humor to moving scenes, it can create a balanced script. The generation AI can also automatically generate a scenario that combines action and romance. For example, it can incorporate romantic elements into action scenes. The generation AI can also automatically generate a scenario that combines horror and comedy. For example, it can introduce humorous characters into scary scenes. This makes it possible to automatically generate scenarios that combine different genres.

[0047] The generation unit can add a function to incorporate music and sound effects specified by the user into the scenario. For example, the generation AI incorporates music specified by the user into the scenario. For example, background music that matches a specific scene is automatically inserted. The generation AI also incorporates sound effects specified by the user into the scenario. For example, sound effects are added to action scenes. The generation AI also provides a function to incorporate music and sound effects specified by the user into the scenario. For example, a music file uploaded by the user is reflected in the scenario. This allows the music and sound effects specified by the user to be incorporated into the scenario.

[0048] The processing flow of the first embodiment will be briefly explained below.

[0049] Step 1: The input unit accepts the situation, characters, and lines from the user. For example, the user can input specific details such as a situation such as "a summer date at the beach," characters such as "the protagonist is you and your partner," and lines such as "Let's enjoy this moment together." Step 2: The generator generates an original script based on the information received by the input unit. For example, the generator AI automatically generates a detailed script based on the situation, characters, and dialogue input by the user. The generator AI uses a text generation AI (e.g., LLM) to describe the actions and conversations of characters based on the situation. Step 3: The animation creation unit creates CG animation of the characters based on the script generated by the generation unit. For example, the image generation AI faithfully reproduces the appearance and movements of the characters specified by the user, and adds backgrounds and effects that suit the situation. Step 4: The providing unit generates a short video based on the CG animation created by the animation creating unit and provides it to the user. For example, the generated short video can be downloaded by the user or shared on social media.

[0050] (Example 2) The short video production system according to an embodiment of the present invention is a system in which a generation AI automatically generates an original script based on a situation, characters, and lines input by a user, and a video generation AI creates CG animation of the characters. This allows the short video production system to allow users to easily create original short videos and provide special content.

[0051] A short video creation system according to an embodiment includes an input unit, a generation unit, an animation creation unit, and a provision unit. The input unit accepts a situation, characters, and lines from a user. For example, a user can input a situation such as "a summer beach date," characters such as "the protagonist is me and my partner," and specific lines such as "Let's enjoy this moment together." The generation unit generates an original script based on the information accepted by the input unit. For example, the generation AI automatically generates a detailed script based on the situation, characters, and lines entered by the user. The generation AI uses a text generation AI (e.g., LLM) to depict the actions and conversations of the characters based on the situation. The animation creation unit creates CG animation of the characters based on the script generated by the generation unit. For example, the video generation AI faithfully reproduces the appearance and movements of the characters specified by the user and adds backgrounds and effects appropriate to the situation. The provision unit generates a short video based on the CG animation created by the animation creation unit and provides it to the user. For example, the generated short video can be downloaded by the user or shared on social networking sites. As a result, the short video creation system according to the embodiment allows users to easily create original short videos and provide special content.

[0052] The input unit allows the generation AI to automatically complete details of the situation and characters entered by the user, generating more specific prompts. For example, if a user enters "a summer date at the beach," the generation AI automatically completes details such as the weather, time of day, and surrounding environment to generate a more specific situation. If a user enters "the main characters are me and my partner," the generation AI automatically completes the relationship between the two and past episodes, creating a deeper character setting. If a user enters "the line is 'Let's enjoy this moment together,'" the generation AI automatically completes the conversation and situation before and after the line is spoken, creating a natural flow. This allows the information entered by the user to be completed and more specific prompts to be generated.

[0053] The input unit allows the generation AI to perform emotional analysis of the lines entered by the user and suggest situations and character actions that correspond to the emotion. For example, if the user enters "The line is 'Let's enjoy this moment together,'" the input unit will analyze the emotion of the line and suggest situations and character actions that match the positive emotion. Alternatively, if the user enters "The line is 'Let's do it again,'" the generation AI will analyze the emotion of the line and suggest moving situations and character actions. Alternatively, if the user enters "The line is 'Goodbye,'" the generation AI will analyze the emotion of the line and suggest sad situations and character actions. This allows for emotional analysis based on the lines entered by the user and suggests appropriate situations and actions.

[0054] The input unit allows the generation AI to refer to a database of similar past situations and characters based on the information entered by the user and propose the optimal scenario. For example, if the user enters "a summer date at the beach," the input unit allows the generation AI to refer to similar past situations from the database and propose the optimal scenario. Also, if the user enters "the protagonist is me and my partner," the generation AI will refer to similar past character settings from the database and propose the optimal scenario. Also, if the user enters "the line is 'Let's enjoy this moment together,'" the generation AI will refer to similar past lines from the database and propose the optimal scenario. This allows the generation AI to refer to a database of similar past situations and characters and propose the optimal scenario.

[0055] The input unit can allow users to input situations and characters using a multimodal interface, such as voice input or gesture input. For example, when a user uses voice input to say, "A summer date at the beach," the generation AI analyzes the voice and automatically sets the situation. Also, when a user uses gesture input to indicate the character's movements, the generation AI analyzes the gesture and sets the character's movements. Also, when a user uses voice input to say, "The line is 'Let's enjoy this moment together,'" the generation AI analyzes the voice and automatically sets the line. This allows users to input situations and characters using a multimodal interface, such as voice input or gesture input.

[0056] Based on the information entered by the user, the input unit allows the AI ​​to suggest situations and characters that reflect different cultures and historical backgrounds. For example, if a user enters "a summer beach date," the AI ​​will suggest situations that reflect different cultures and historical backgrounds, such as Edo-period Japan or modern-day Hawaii. If a user enters "the protagonists are me and my partner," the AI ​​will suggest characters that reflect different cultures and historical backgrounds, such as ancient Roman warriors or astronauts from the future. If a user enters "the line is 'Let's enjoy this moment together,'" the AI ​​will suggest lines that reflect different cultures and historical backgrounds, such as Shakespearean lines or futuristic slang. This allows the AI ​​to suggest situations and characters that reflect different cultures and historical backgrounds.

[0057] The input unit uses the emotion estimation function to analyze the emotions of the user when they input in real time and suggest situations and lines that will elicit positive emotions. For example, the input unit uses a camera to analyze the user's facial expressions when they input and suggest situations that will elicit positive emotions. For example, if there are a lot of smiles, it suggests fun situations. It also analyzes the tone of the voice when the user inputs and suggests lines that will elicit positive emotions. For example, if there is a bright tone, it suggests cheerful lines. It also analyzes the gestures the user makes when inputting and suggests character actions that will elicit positive emotions. For example, if there are a lot of hand waving actions, it suggests scenes where the character is waving. In this way, it is possible to analyze the user's emotions in real time and suggest situations and lines that will elicit positive emotions.

[0058] The generation unit can learn the user's past input history and preferences to generate a more personalized script. For example, the generation AI of the generation unit learns the user's past input history and generates a script that suits the user's preferences. For example, it reflects the tendencies of situations and characters entered in the past. The generation AI also learns the user's preferences and generates a script specialized for a specific genre or theme. For example, if the user likes romance dramas, it generates a script for romance dramas. The generation AI also reuses specific characters and lines based on the user's past input history. For example, it reintroduces characters that the user created in the past. This makes it possible to generate a more personalized script based on the user's past input history and preferences.

[0059] The generation unit uses the emotion estimation function to depict the emotions of the characters in detail, making it possible to create more realistic scenarios. For example, the generation unit uses the emotion estimation function to depict the emotions of the characters in detail. For example, it realistically depicts scenes in which the characters feel joy or sadness. The generation AI also uses the emotion estimation function to reflect the changes in the characters' emotions in the scenario. For example, it depicts in detail the process by which a character goes from anger to reconciliation. The generation AI also uses the emotion estimation function to reflect the behavior of the characters based on their emotions in the scenario. For example, it depicts a scene in which a character is moved to tears. This allows the emotions of the characters to be depicted in detail, making it possible to create more realistic scenarios.

[0060] The generation unit can automatically generate scenarios that combine different genres. For example, the generation AI can automatically generate a scenario that combines comedy and drama. For example, by adding humor to moving scenes, it can create a balanced script. The generation AI can also automatically generate a scenario that combines action and romance. For example, it can incorporate romantic elements into action scenes. The generation AI can also automatically generate a scenario that combines horror and comedy. For example, it can introduce humorous characters into scary scenes. This makes it possible to automatically generate scenarios that combine different genres.

[0061] The generation unit can add a function to incorporate music and sound effects specified by the user into the scenario. For example, the generation unit allows the generation AI to incorporate music specified by the user into the scenario. For example, background music that matches a specific scene is automatically inserted. The generation AI also incorporates sound effects specified by the user into the scenario. For example, sound effects are added to action scenes. The generation AI also provides a function to incorporate music and sound effects specified by the user into the scenario. For example, a music file uploaded by the user is reflected in the scenario. This allows the music and sound effects specified by the user to be incorporated into the scenario.

[0062] The generation unit can use the emotion estimation function to collect the user's emotional reactions to the generated script and reflect them in the next script generation. In the generation unit, for example, the generation AI uses the emotion estimation function to collect the user's emotional reactions to the generated script. For example, it analyzes the user's facial expressions and voice when reading the script. The generation AI also uses the emotion estimation function to reflect the user's emotional reactions in the next script generation. For example, it incorporates elements that receive many positive reactions into the next script. The generation AI also uses the emotion estimation function to collect the user's emotional reactions in real time and reflect them in the next script generation. For example, it adjusts the script based on the user's real-time feedback. In this way, the user's emotional reactions to the generated script can be collected and reflected in the next script generation.

[0063] The animation creation unit can generate more realistic characters based on the user's photos and videos. In the animation creation unit, for example, the image generation AI generates a realistic character based on the user's photos. For example, it creates a character that reflects the user's facial features. The image generation AI also generates a realistic character based on the user's videos. For example, it creates a character that reflects the user's movements and expressions. The image generation AI also generates a realistic character based on the user's photos and videos. For example, it creates a character that reflects the user's clothing and hairstyle. This allows more realistic characters to be generated based on the user's photos and videos.

[0064] The animation creation unit can use the emotion estimation function to change the character's facial expression and movements according to the emotion. In the animation creation unit, for example, the video generation AI uses the emotion estimation function to change the character's facial expression according to the emotion. For example, a character feeling happy will smile. The video generation AI also uses the emotion estimation function to change the character's movements according to the emotion. For example, a character feeling angry will clench their fist. The video generation AI also uses the emotion estimation function to change the character's facial expression and movements according to the emotion. For example, a character feeling sad will shed tears. In this way, the character's facial expression and movements can be changed according to the emotion.

[0065] The animation creation unit can generate realistic backgrounds and effects according to the season and time of day specified by the user. In the animation creation unit, for example, the video generation AI generates backgrounds according to the season specified by the user. For example, it recreates blue skies and oceans in summer scenes, and snowy scenery in winter scenes. The video generation AI also generates backgrounds according to the time of day specified by the user. For example, it recreates a sunrise in a morning scene, and a starry sky in a night scene. The video generation AI also generates effects according to the season and time of day specified by the user. For example, it adds an effect of falling leaves in an autumn scene, and a sunset effect in an evening scene. This makes it possible to generate realistic backgrounds and effects according to the season and time of day specified by the user.

[0066] The animation creation unit can add a function that allows different art styles to be selected. The animation creation unit, for example, provides a function that allows the image generation AI to generate anime-style characters. For example, when a user selects an anime-style style, the character is drawn in an anime style. The image generation AI also provides a function that allows the image generation AI to generate realistic-style characters. For example, when a user selects a realistic style, the character is drawn realistically. The image generation AI also provides a function that allows the image generation AI to select different art styles. For example, the user can select a cartoon style or a 3D style. This allows the addition of a function that allows different art styles to be selected.

[0067] The animation creation unit can add a function to synchronize the character's movements with music and sound effects specified by the user. For example, the animation creation unit synchronizes the character's movements with music specified by the user using a video generation AI. For example, the character dances to the rhythm of the music in a dance scene. The video generation AI also synchronizes the character's movements with sound effects specified by the user. For example, the character moves to the sound effects in an action scene. The video generation AI also provides a function to synchronize the character's movements with music and sound effects. For example, the character moves to the music file uploaded by the user. This makes it possible to add a function to synchronize the character's movements with music and sound effects specified by the user.

[0068] The animation creation unit uses the emotion estimation function to monitor the user's emotional reactions to the generated animation in real time, and is able to continuously generate optimal animations. In the animation creation unit, for example, the video generation AI uses the emotion estimation function to monitor the user's emotional reactions to the generated animation in real time. For example, it analyzes the user's facial expressions and voice. The video generation AI also uses the emotion estimation function to continuously improve the animation based on the user's emotional reactions. For example, it emphasizes scenes with many positive reactions. The video generation AI also uses the emotion estimation function to collect the user's emotional reactions in real time and generate optimal animations. For example, it adjusts the animation based on the user's real-time feedback. This makes it possible to monitor the user's emotional reactions to the generated animation in real time and continuously generate optimal animations.

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

[0070] The input section allows the AI ​​to automatically complete the details of the situation and characters entered by the user, generating more specific prompts. For example, if a user enters "a summer date at the beach," the AI ​​automatically completes details such as the weather, time of day, and surrounding environment to generate a more specific situation. If a user enters "the main characters are me and my partner," the AI ​​automatically completes the relationship between the two and past episodes, creating a deeper characterization. If a user enters "the line is 'Let's enjoy this moment together,'" the AI ​​automatically completes the conversation and situation before and after the line, creating a natural flow. This allows the AI ​​to complete the information entered by the user and generate more specific prompts.

[0071] The input unit allows the generation AI to perform emotional analysis of the lines entered by the user and suggest situations and character actions that correspond to the emotion. For example, if the user enters "The line is 'Let's enjoy this moment together,'" the generation AI will analyze the emotion of the line and suggest situations and character actions that match the positive emotion. Alternatively, if the user enters "The line is 'Let's do it again,'" the generation AI will analyze the emotion of the line and suggest moving situations and character actions. Alternatively, if the user enters "The line is 'Goodbye,'" the generation AI will analyze the emotion of the line and suggest sad situations and character actions. This allows emotion analysis to be performed based on the lines entered by the user and suggest appropriate situations and actions.

[0072] The input unit allows the generation AI to refer to a database of similar past situations and characters based on the information entered by the user, and propose the optimal scenario. For example, if the user enters "a summer date at the beach," the generation AI will refer to similar past situations from the database and propose the optimal scenario. Also, if the user enters "the protagonist is me and my partner," the generation AI will refer to similar past character settings from the database and propose the optimal scenario. Also, if the user enters "the line is 'Let's enjoy this moment together,'" the generation AI will refer to similar past lines from the database and propose the optimal scenario. This allows the generation AI to refer to a database of similar past situations and characters and propose the optimal scenario.

[0073] The input unit can allow users to input situations and characters using a multimodal interface, such as voice input or gesture input. For example, if a user says "A summer date at the beach" via voice input, the generation AI analyzes the voice and automatically sets the situation. Also, if the user indicates the character's movements using gesture input, the generation AI analyzes the gesture and sets the character's movements. Also, if a user says "The line is 'Let's enjoy this moment together' via voice input," the generation AI analyzes the voice and automatically sets the line. This allows users to input situations and characters using a multimodal interface, such as voice input or gesture input.

[0074] The input unit uses an emotion estimation function to analyze the emotions of the user when they input in real time and suggest situations and lines that will elicit positive emotions. For example, a camera can analyze the user's facial expressions when they input and suggest situations that will elicit positive emotions. For example, if there are a lot of smiles, fun situations can be suggested. The tone of the voice when the user inputs can also be analyzed and lines that will elicit positive emotions can be suggested. For example, if there is a bright tone, cheerful lines can be suggested. The gestures the user makes when inputting can also be analyzed and characters' actions that will elicit positive emotions can be suggested. For example, if there are a lot of hand waving actions, scenes in which characters are waving their hands can be suggested. This allows the system to analyze the user's emotions in real time and suggest situations and lines that will elicit positive emotions.

[0075] The generation unit can learn the user's past input history and preferences to generate more personalized scripts. For example, the generation AI can learn the user's past input history and generate a script that suits their preferences. For example, it can reflect the tendencies of situations and characters entered in the past. The generation AI can also learn the user's preferences and generate a script specialized for a specific genre or theme. For example, if the user likes romance dramas, it can generate a script for romance dramas. The generation AI can also reuse specific characters and lines based on the user's past input history. For example, it can reintroduce characters that the user created in the past. This makes it possible to generate a more personalized script based on the user's past input history and preferences.

[0076] The generation unit uses the emotion estimation function to depict the emotions of characters in detail, allowing for the creation of more realistic scenarios. For example, the generation AI uses the emotion estimation function to depict the emotions of characters in detail. For example, it realistically depicts scenes in which characters feel joy or sadness. The generation AI also uses the emotion estimation function to reflect the changes in the characters' emotions in the scenario. For example, it depicts in detail the process by which a character goes from anger to reconciliation. The generation AI also uses the emotion estimation function to reflect the behavior of characters based on their emotions in the scenario. For example, it depicts a scene in which a character is moved to tears. This allows for the emotions of characters to be depicted in detail, allowing for the creation of more realistic scenarios.

[0077] The generation unit can automatically generate scenarios that combine different genres. For example, the generation AI can automatically generate a scenario that combines comedy and drama. For example, by adding humor to moving scenes, it can create a balanced script. The generation AI can also automatically generate a scenario that combines action and romance. For example, it can incorporate romantic elements into action scenes. The generation AI can also automatically generate a scenario that combines horror and comedy. For example, it can introduce humorous characters into scary scenes. This makes it possible to automatically generate scenarios that combine different genres.

[0078] The generation unit can add a function to incorporate music and sound effects specified by the user into the scenario. For example, the generation AI incorporates music specified by the user into the scenario. For example, background music that matches a specific scene is automatically inserted. The generation AI also incorporates sound effects specified by the user into the scenario. For example, sound effects are added to action scenes. The generation AI also provides a function to incorporate music and sound effects specified by the user into the scenario. For example, a music file uploaded by the user is reflected in the scenario. This allows the music and sound effects specified by the user to be incorporated into the scenario.

[0079] The generation unit can use the emotion estimation function to collect the user's emotional reactions to the generated script and reflect them in the next script generation. For example, the generation AI uses the emotion estimation function to collect the user's emotional reactions to the generated script. For example, it analyzes the user's facial expressions and voice when reading the script. The generation AI also uses the emotion estimation function to reflect the user's emotional reactions in the next script generation. For example, it incorporates elements that receive a lot of positive reactions into the next script. The generation AI also uses the emotion estimation function to collect the user's emotional reactions in real time and reflect them in the next script generation. For example, it adjusts the script based on the user's real-time feedback. In this way, the user's emotional reactions to the generated script can be collected and reflected in the next script generation.

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

[0081] Step 1: The input unit accepts the situation, characters, and lines from the user. For example, the user can input specific details such as a situation such as "a summer date at the beach," characters such as "the protagonist is you and your partner," and lines such as "Let's enjoy this moment together." Step 2: The generator generates an original script based on the information received by the input unit. For example, the generator AI automatically generates a detailed script based on the situation, characters, and dialogue input by the user. The generator AI uses a text generation AI (e.g., LLM) to describe the actions and conversations of characters based on the situation. Step 3: The animation creation unit creates CG animation of the characters based on the script generated by the generation unit. For example, the image generation AI faithfully reproduces the appearance and movements of the characters specified by the user, and adds backgrounds and effects that suit the situation. Step 4: The providing unit generates a short video based on the CG animation created by the animation creating unit and provides it to the user. For example, the generated short video can be downloaded by the user or shared on social media.

[0082] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0083] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0084] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

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

[0086] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0087] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0088] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0089] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0090] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0091] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0092] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0093] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

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

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

[0096] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0097] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0098] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0099] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

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

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

[0102] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0103] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0104] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0105] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0106] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0107] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0108] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

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

[0110] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0111] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0112] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0113] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0114] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

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

[0116] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0117] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0118] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0119] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0120] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0121] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0122] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0123] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

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

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

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

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

[0128] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

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

[0130] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0131] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0132] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0133] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0134] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0135] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0136] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0137] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0138] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0139] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0140] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0141] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0142] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0143] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0144] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0145] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0146] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0147] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0148] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0149] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. an input unit that receives a situation, characters, and lines from a user; a generation unit that generates an original script based on the information received by the input unit; an animation creation unit that creates CG animation of characters based on the script generated by the generation unit; a providing unit that generates a short video based on the CG animation created by the animation creating unit and provides the short video to a user. A system characterized by:

2. The input unit The AI ​​automatically completes the details of the situation and characters entered by the user, generating more specific prompts.

2. The system of claim 1.

3. The input unit The generation AI performs emotional analysis on the lines entered by the user and suggests the situation and the actions of the characters according to the emotions.

2. The system of claim 1.

4. The input unit Based on the information entered by the user, the AI ​​will refer to a database of similar situations from the past and the characters mentioned above to propose the optimal scenario.

2. The system of claim 1.

5. The input unit The situation and the characters that the user inputs can be input using a multimodal interface such as voice input and gesture input.

2. The system of claim 1.

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