System

Abstract

An object of the system according to the embodiment is to efficiently integrate and support each process of animation production.SOLUTION: A system according to an embodiment includes a storyboard creation tool, a character design tool, and an animation production tool. The storyboard creation tool creates an animated storyboard. The character design tool designs an animated character. The animation production tool produces animation.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 lacks tools that efficiently integrate and support each stage of animation production, making the production process complicated.

[0005] The system according to the embodiment aims to efficiently integrate and support each step of animation production. [Means for solving the problem]

[0006] The system according to the embodiment includes a storyboard creation tool, a character design tool, and an animation production tool. The storyboard creation tool creates storyboards for animations. The character design tool designs characters for animations. The animation production tool creates animations. [Effects of the Invention]

[0007] The system according to the embodiment can efficiently integrate and support each step of animation production. [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 nonvolatile storage devices that store various programs, various parameters, etc. Examples of nonvolatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

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

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

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

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

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

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

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

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

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

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

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

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

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

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

[0028] (Example 1) A toolset according to an embodiment of the present invention is a system for supporting the production of standard animation. This system provides functions for efficiently and effectively proceeding with work at each stage of animation production. As a result, the toolset can efficiently support the entire process of animation production.

[0029] A toolset according to an embodiment includes a storyboard creation tool, a character design tool, and an animation production tool. The storyboard creation tool creates an animation storyboard. For example, a user can input sketches and notes for each scene to visually construct a storyboard. The storyboard creation tool also includes a function for changing the order of scenes by dragging and dropping. The character design tool designs animation characters. For example, a user can freely customize a character's appearance, clothing, facial expression, etc. The character design tool also includes a function for selecting a character's hairstyle and clothing and changing their color. The animation production tool creates animations. For example, a user can position characters and backgrounds and set their movement for each frame. The animation production tool also includes a function for adjusting the character's position and pose. This allows the toolset to efficiently support each stage of animation production.

[0030] The storyboard creation tool allows you to change the order of scenes by dragging and dropping. The storyboard creation tool, for example, has a function for changing the order of scenes by dragging and dropping. This allows you to change the order of scenes intuitively.

[0031] The character design tool allows the user to select a hairstyle or clothing for a character and change the color. The character design tool has a function for selecting a hairstyle or clothing for a character and changing the color, for example. This allows the user to freely customize the appearance of the character.

[0032] The animation production tool can adjust the position or pose of a character. The animation production tool has, for example, a function for adjusting the position or pose of a character. This allows for detailed settings of the character's movements.

[0033] The storyboard creation tool can automatically search for related scenes from past anime works for each scene in the storyboard and display them as reference. For example, the storyboard creation tool can automatically search for scenes from past anime works for each scene in the storyboard and display similar scenes. For example, the search can be performed based on the content or composition of the scene. This allows scenes to be created by referring to past anime works.

[0034] A storyboard creation tool can use natural language processing technology to automatically generate a summary and visually display it when a detailed description of a scene is input. A storyboard creation tool can use natural language processing technology to automatically generate a summary when a detailed description of a scene is input. For example, a long description can be summarized in a short form and visually displayed. This allows the detailed description of a scene to be displayed concisely.

[0035] A storyboard creation tool may add a voice input function and automatically convert what a user dictates into text to reflect the scene description. For example, a storyboard creation tool may add a voice input function and automatically convert what a user dictates into text. For example, the tool may use voice recognition technology to convert the dictation into text in real time. This allows scene descriptions to be created efficiently using voice input.

[0036] The storyboard creation tool can receive feedback from other users in real time. The storyboard creation tool, for example, adds a real-time feedback function and receives ratings and comments from other users. For example, a system is built that immediately reflects feedback. This allows feedback from other users to be received in real time.

[0037] The character design tool can refer to past design data and automatically display similar designs for reference. The character design tool can, for example, refer to past design data and automatically display similar designs. For example, it can search for similar designs based on design features. This allows users to design characters by referring to past design data.

[0038] The character design tool can learn the user's preferences and trends and suggest the best options.The character design tool can learn the user's preferences and trends and suggest the best options.For example, it makes suggestions based on past design history.This makes it possible to suggest the best options based on the user's preferences and trends.

[0039] Character design tools can add 3D modeling functionality, allowing characters to be designed in three dimensions. Character design tools can add 3D modeling functionality, allowing characters to be designed in three dimensions. For example, a 3D model can be created and checked from various angles. This allows characters to be designed in three dimensions.

[0040] The character design tool can add a collaboration function that allows users to share and collaborate on designs with other users. For example, the character design tool can add a collaboration function to share designs with other users. For example, the design can be edited in real time and the work can be done collaboratively. This allows users to collaborate on character designs.

[0041] The animation production tool can refer to past animation data and automatically suggest similar movements. The animation production tool, for example, refers to past animation data and automatically suggests similar movements. For example, it searches for similar movements based on movement patterns. This makes it possible to suggest similar movements by referring to past animation data.

[0042] The animation production tool can learn the user's operation history and predict and propose optimal movements. The animation production tool can, for example, learn the user's operation history and predict and propose optimal movements. For example, movements are proposed based on past operation data. This makes it possible to predict and propose optimal movements based on the user's operation history.

[0043] An animation production tool can be equipped with a motion capture function to capture actual movements and reflect them in the animation. For example, an animation production tool can be equipped with a motion capture function to capture actual movements and reflect them in the animation. For example, a motion capture device can be used to record movements. This allows actual movements to be captured and reflected in the animation.

[0044] The animation production tool can add a collaboration function that allows users to share the production process with other users in real time and work together on the production. The animation production tool can add a collaboration function, for example, that allows users to share the production process with other users in real time. For example, editing and commenting can be done in real time. This allows users to work together on the production of animation.

[0045] The voice recording and editing tool can refer to past recording data and automatically suggest similar voices. The voice recording and editing tool can, for example, refer to past recording data and automatically suggest similar voices. For example, it can search for similar voices based on voice characteristics. This makes it possible to suggest similar voices by referring to past recording data.

[0046] The audio recording and editing tool can learn the user's operation history and predict and suggest the optimal editing method. The audio recording and editing tool can, for example, learn the user's operation history and predict and suggest the optimal editing method. For example, it can make suggestions based on past editing data. This makes it possible to predict and suggest the optimal editing method based on the user's operation history.

[0047] Audio recording and editing tools can be equipped with a function for converting audio to text in real time, allowing for text-based manipulation during editing. Audio recording and editing tools can be equipped with a function for converting audio to text in real time, allowing for text-based manipulation during editing. For example, audio can be converted to text using speech recognition technology. This allows for audio to be converted to text in real time, allowing for text-based manipulation during editing.

[0048] Audio recording and editing tools allow users to collaborate with other users in real time and work together on recording. For example, audio recording and editing tools may add collaboration features, allowing users to work together on recording in real time, for example by editing or commenting on audio in real time. This allows users to work together on recording audio.

[0049] The final editing and finishing tool can refer to past editing data and automatically suggest similar editing techniques. The final editing and finishing tool can, for example, refer to past editing data and automatically suggest similar editing techniques. For example, it can search for similar edits based on the editing characteristics. This makes it possible to suggest similar editing techniques by referring to past editing data.

[0050] The final editing and finishing tool can learn the user's operation history and predict and suggest the optimal editing technique. The final editing and finishing tool can, for example, learn the user's operation history and predict and suggest the optimal editing technique. For example, it can make suggestions based on past editing data. This makes it possible to predict and suggest the optimal editing technique based on the user's operation history.

[0051] Final editing and finishing tools can add collaboration features that allow editing content to be shared with other users in real time and collaboratively progress with editing. Final editing and finishing tools can add collaboration features that allow editing content to be shared with other users in real time, for example, by editing and commenting in real time. This allows final editing and finishing to be done collaboratively with other users.

[0052] Final editing and finishing tools add the ability to preview in different formats, which can be helpful in choosing the final output format. Final editing and finishing tools, for example, add the ability to preview in different formats, which can be helpful in choosing the final output format. For example, preview in multiple formats, which can be helpful in choosing the final output format.

[0053] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0054] The storyboarding tool can automatically suggest transition effects between scenes when you change the order of scenes. For example, it suggests transition effects like fade-in, fade-out, and slide-in based on the content and mood of the scene. This helps maintain a smooth visual flow when you change the order of scenes.

[0055] Character design tools can be equipped with a function to simulate character movements. For example, you can simulate the movement of a character's joints and muscles to check realistic movements. They can also be equipped with a function to simulate the physical effects on character movements. This allows you to pursue not only the design of the character but also the realism of the movement.

[0056] When a detailed scene description is entered, the storyboarding tool can automatically generate a summary using natural language processing technology and display it visually. For example, it can summarize a long description in a short form and display it visually. This allows for a concise display of the detailed scene description.

[0057] Storyboarding tools can add voice input functionality, automatically converting dictation into text and incorporating it into scene descriptions. For example, they can use voice recognition technology to convert dictation into text in real time. This allows for efficient creation of scene descriptions using voice input.

[0058] The character design tool can learn the user's preferences and trends and suggest optimal options. For example, it can make suggestions based on past design history. This allows it to suggest optimal options based on the user's preferences and trends.

[0059] Animation production tools can add motion capture functionality, allowing you to capture real-world movements and incorporate them into your animation. For example, you can record your movements using a motion capture device. This allows you to capture real-world movements and incorporate them into your animation.

[0060] The processing flow of the first embodiment will be briefly explained below.

[0061] Step 1: The storyboard creation tool creates an animated storyboard. Users can input sketches and notes for each scene and visually build the storyboard. It also has the ability to change the order of scenes with drag and drop. Step 2: The character design tool allows users to design their anime characters. Users can freely customize the character's appearance, clothing, and facial expressions. It also has the ability to select the character's hairstyle and clothing, and change the color. Step 3: The animation production tool creates the animation. Users can place characters and backgrounds and set frame-by-frame movements. It also has the ability to adjust the character's position and pose.

[0062] (Example 2) A toolset according to an embodiment of the present invention is a system for supporting the production of standard animation. This system provides functions for efficiently and effectively proceeding with work at each stage of animation production. As a result, the toolset can efficiently support the entire process of animation production.

[0063] A toolset according to an embodiment includes a storyboard creation tool, a character design tool, and an animation production tool. The storyboard creation tool creates an animation storyboard. For example, a user can input sketches and notes for each scene to visually construct a storyboard. The storyboard creation tool also includes a function for changing the order of scenes by dragging and dropping. The character design tool designs animation characters. For example, a user can freely customize a character's appearance, clothing, facial expression, etc. The character design tool also includes a function for selecting a character's hairstyle and clothing and changing their color. The animation production tool creates animations. For example, a user can position characters and backgrounds and set their movement for each frame. The animation production tool also includes a function for adjusting the character's position and pose. This allows the toolset to efficiently support each stage of animation production.

[0064] The storyboard creation tool allows you to change the order of scenes by dragging and dropping. The storyboard creation tool, for example, has a function for changing the order of scenes by dragging and dropping. This allows you to change the order of scenes intuitively.

[0065] The character design tool allows the user to select a hairstyle or clothing for a character and change the color. The character design tool has a function for selecting a hairstyle or clothing for a character and changing the color, for example. This allows the user to freely customize the appearance of the character.

[0066] The animation production tool can adjust the position or pose of a character. The animation production tool has, for example, a function for adjusting the position or pose of a character. This allows for detailed settings of the character's movements.

[0067] A storyboard creation tool can use generative AI to estimate the emotion of each scene and automatically suggest the order of scenes based on the flow of emotions. For example, a storyboard creation tool can use generative AI to analyze the emotion of each scene and quantify the intensity and type of emotion. For example, it can calculate an emotion score for each scene and automatically suggest the order of scenes based on the flow of emotions. This makes it possible to optimize the order of scenes based on the flow of emotions.

[0068] The storyboard creation tool can automatically search for related scenes from past anime works for each scene in the storyboard and display them as reference. For example, the storyboard creation tool can automatically search for scenes from past anime works for each scene in the storyboard and display similar scenes. For example, the search can be performed based on the content or composition of the scene. This allows scenes to be created by referring to past anime works.

[0069] A storyboard creation tool can use natural language processing technology to automatically generate a summary and visually display it when a detailed description of a scene is input. A storyboard creation tool can use natural language processing technology to automatically generate a summary when a detailed description of a scene is input. For example, a long description can be summarized in a short form and visually displayed. This allows the detailed description of a scene to be displayed concisely.

[0070] A storyboard creation tool may add a voice input function and automatically convert what a user dictates into text to reflect the scene description. For example, a storyboard creation tool may add a voice input function and automatically convert what a user dictates into text. For example, the tool may use voice recognition technology to convert the dictation into text in real time. This allows scene descriptions to be created efficiently using voice input.

[0071] The storyboard creation tool can receive feedback from other users in real time. The storyboard creation tool, for example, adds a real-time feedback function and receives ratings and comments from other users. For example, a system is built that immediately reflects feedback. This allows feedback from other users to be received in real time.

[0072] The storyboard creation tool uses an emotion estimation function to analyze the emotions of a user when creating a scene in real time and make suggestions to elicit positive emotions. The storyboard creation tool uses, for example, an emotion estimation function to analyze the emotions of a user when creating a scene in real time. For example, the tool analyzes the user's facial expressions and voice and calculates an emotion score. This allows the tool to analyze the user's emotions and make suggestions to elicit positive emotions.

[0073] Character design tools can use generative AI to automatically suggest facial expressions and poses based on a character's emotions. Character design tools can use generative AI to automatically suggest facial expressions and poses based on a character's emotions. For example, they can generate optimal facial expressions and poses based on emotion scores. This makes it possible to automatically suggest facial expressions and poses based on a character's emotions.

[0074] The character design tool can refer to past design data and automatically display similar designs for reference. The character design tool can, for example, refer to past design data and automatically display similar designs. For example, it can search for similar designs based on design features. This allows users to design characters by referring to past design data.

[0075] The character design tool can learn the user's preferences and trends and suggest the best options.The character design tool can learn the user's preferences and trends and suggest the best options.For example, it makes suggestions based on past design history.This makes it possible to suggest the best options based on the user's preferences and trends.

[0076] Character design tools can add 3D modeling functionality, allowing characters to be designed in three dimensions. Character design tools can add 3D modeling functionality, allowing characters to be designed in three dimensions. For example, a 3D model can be created and checked from various angles. This allows characters to be designed in three dimensions.

[0077] The character design tool can add a collaboration function that allows users to share and collaborate on designs with other users. For example, the character design tool can add a collaboration function to share designs with other users. For example, the design can be edited in real time and the work can be done collaboratively. This allows users to collaborate on character designs.

[0078] The character design tool uses an emotion estimation function to analyze the emotions of a user when designing a character and can suggest design directions. The character design tool, for example, uses the emotion estimation function to analyze the emotions of a user when designing a character. For example, the tool analyzes the user's facial expressions and voice and calculates an emotion score. This makes it possible to suggest design directions based on the user's emotions.

[0079] The animation production tool can use a generative AI to estimate emotions associated with a character's movements and automatically interpolate movements based on the emotions. The animation production tool can, for example, use a generative AI to estimate emotions associated with a character's movements and automatically interpolate movements based on the emotions. For example, the tool can optimize movements based on emotion scores. This allows the tool to estimate emotions associated with a character's movements and automatically interpolate movements based on the emotions.

[0080] The animation production tool can refer to past animation data and automatically suggest similar movements. The animation production tool, for example, refers to past animation data and automatically suggests similar movements. For example, it searches for similar movements based on movement patterns. This makes it possible to suggest similar movements by referring to past animation data.

[0081] The animation production tool can learn the user's operation history and predict and propose optimal movements. The animation production tool can, for example, learn the user's operation history and predict and propose optimal movements. For example, movements are proposed based on past operation data. This makes it possible to predict and propose optimal movements based on the user's operation history.

[0082] An animation production tool can be equipped with a motion capture function to capture actual movements and reflect them in the animation. For example, an animation production tool can be equipped with a motion capture function to capture actual movements and reflect them in the animation. For example, a motion capture device can be used to record movements. This allows actual movements to be captured and reflected in the animation.

[0083] The animation production tool can add a collaboration function that allows users to share the production process with other users in real time and work together on the production. The animation production tool can add a collaboration function, for example, that allows users to share the production process with other users in real time. For example, editing and commenting can be done in real time. This allows users to work together on the production of animation.

[0084] The animation production tool uses the emotion estimation function to analyze the emotions of the user when creating animation and can make suggestions to elicit positive emotions. The animation production tool, for example, uses the emotion estimation function to analyze the emotions of the user when creating animation. For example, the tool analyzes the user's facial expressions and voice and calculates an emotion score. This allows the tool to analyze the user's emotions and make suggestions to elicit positive emotions.

[0085] The voice recording and editing tool uses generative AI to estimate the emotion of a character's lines and automatically perform voice filtering based on the emotion. The voice recording and editing tool, for example, uses generative AI to estimate the emotion of a character's lines and automatically perform voice filtering based on the emotion. For example, it adjusts the tone and pitch of the voice based on the emotion score. This makes it possible to estimate the emotion of a character's lines and automatically perform voice filtering based on the emotion.

[0086] The voice recording and editing tool can refer to past recording data and automatically suggest similar voices. The voice recording and editing tool can, for example, refer to past recording data and automatically suggest similar voices. For example, it can search for similar voices based on voice characteristics. This makes it possible to suggest similar voices by referring to past recording data.

[0087] The audio recording and editing tool can learn the user's operation history and predict and suggest the optimal editing method. The audio recording and editing tool can, for example, learn the user's operation history and predict and suggest the optimal editing method. For example, it can make suggestions based on past editing data. This makes it possible to predict and suggest the optimal editing method based on the user's operation history.

[0088] Audio recording and editing tools can be equipped with a function for converting audio to text in real time, allowing for text-based manipulation during editing. Audio recording and editing tools can be equipped with a function for converting audio to text in real time, allowing for text-based manipulation during editing. For example, audio can be converted to text using speech recognition technology. This allows for audio to be converted to text in real time, allowing for text-based manipulation during editing.

[0089] Audio recording and editing tools allow users to collaborate with other users in real time and work together on recording. For example, audio recording and editing tools may add collaboration features, allowing users to work together on recording in real time, for example by editing or commenting on audio in real time. This allows users to work together on recording audio.

[0090] The voice recording and editing tool uses an emotion estimation function to analyze the emotions expressed by the user when recording and editing voice, and can make suggestions that elicit positive emotions. The voice recording and editing tool, for example, uses an emotion estimation function to analyze the emotions expressed by the user when recording and editing voice. For example, it can analyze the user's facial expressions and voice and calculate an emotion score. This allows it to analyze the user's emotions and make suggestions that elicit positive emotions.

[0091] Final editing and finishing tools can use generative AI to estimate emotions for transitions between scenes and automatically suggest transitions based on emotions. Final editing and finishing tools can, for example, use generative AI to estimate emotions for transitions between scenes and automatically suggest transitions based on emotions. For example, they can adjust the type and speed of transitions based on emotion scores. This makes it possible to estimate emotions for transitions between scenes and automatically suggest transitions based on emotions.

[0092] The final editing and finishing tool can refer to past editing data and automatically suggest similar editing techniques. The final editing and finishing tool can, for example, refer to past editing data and automatically suggest similar editing techniques. For example, it can search for similar edits based on the editing characteristics. This makes it possible to suggest similar editing techniques by referring to past editing data.

[0093] The final editing and finishing tool can learn the user's operation history and predict and suggest the optimal editing technique. The final editing and finishing tool can, for example, learn the user's operation history and predict and suggest the optimal editing technique. For example, it can make suggestions based on past editing data. This makes it possible to predict and suggest the optimal editing technique based on the user's operation history.

[0094] Final editing and finishing tools can add collaboration features that allow editing content to be shared with other users in real time and collaboratively progress with editing. Final editing and finishing tools can add collaboration features that allow editing content to be shared with other users in real time, for example, by editing and commenting in real time. This allows final editing and finishing to be done collaboratively with other users.

[0095] Final editing and finishing tools add the ability to preview in different formats, which can be helpful in choosing the final output format. Final editing and finishing tools, for example, add the ability to preview in different formats, which can be helpful in choosing the final output format. For example, preview in multiple formats, which can be helpful in choosing the final output format.

[0096] The final editing and finishing tool uses an emotion estimation function to analyze the emotions of the user when performing final editing and finishing, and can make suggestions that will elicit positive emotions. The final editing and finishing tool, for example, uses an emotion estimation function to analyze the emotions of the user when performing final editing and finishing. For example, it can analyze the user's facial expressions and voice and calculate an emotion score. This makes it possible to analyze the user's emotions and make suggestions that will elicit positive emotions.

[0097] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0098] The toolset may further include a music production tool. The music production tool provides a function for creating music that matches an anime scene. For example, a user can select instruments and tempo to match the atmosphere of a scene and create music. The music production tool may also include a function for automatically generating music based on the emotion of the scene. This allows for efficient creation of music that is optimal for an anime scene.

[0099] The storyboarding tool can automatically suggest transition effects between scenes when you change the order of scenes. For example, it suggests transition effects like fade-in, fade-out, and slide-in based on the content and mood of the scene. This helps maintain a smooth visual flow when you change the order of scenes.

[0100] Character design tools can be equipped with a function to simulate character movements. For example, you can simulate the movement of a character's joints and muscles to check realistic movements. They can also be equipped with a function to simulate the physical effects on character movements. This allows you to pursue not only the design of the character but also the realism of the movement.

[0101] The animation production tool can estimate the emotion of a character's movements and automatically interpolate movements based on the emotion. For example, if a character has a sad expression, the movement will be slowed down based on that emotion. On the other hand, if the character is happy, the movement will be speeded up based on that emotion. This makes it possible to achieve natural movements based on the character's emotions.

[0102] When a detailed scene description is entered, the storyboarding tool can automatically generate a summary using natural language processing technology and display it visually. For example, it can summarize a long description in a short form and display it visually. This allows for a concise display of the detailed scene description.

[0103] Storyboarding tools can add voice input functionality, automatically converting dictation into text and incorporating it into scene descriptions. For example, they can use voice recognition technology to convert dictation into text in real time. This allows for efficient creation of scene descriptions using voice input.

[0104] Character design tools can use generative AI to automatically suggest facial expressions and poses based on a character's emotions. For example, they can generate optimal facial expressions and poses based on emotion scores. This allows them to automatically suggest facial expressions and poses based on a character's emotions.

[0105] The character design tool can learn the user's preferences and trends and suggest optimal options. For example, it can make suggestions based on past design history. This allows it to suggest optimal options based on the user's preferences and trends.

[0106] Animation production tools can add motion capture functionality, allowing you to capture real-world movements and incorporate them into your animation. For example, you can record your movements using a motion capture device. This allows you to capture real-world movements and incorporate them into your animation.

[0107] The animation production tool uses an emotion estimation function to analyze the emotions of users when creating animations and make suggestions to elicit positive emotions. For example, it analyzes the user's facial expressions and voice and calculates an emotion score. This allows it to analyze the user's emotions and make suggestions to elicit positive emotions.

[0108] The processing flow of the second embodiment will be briefly explained below.

[0109] Step 1: The storyboard creation tool creates an animated storyboard. Users can input sketches and notes for each scene and visually build the storyboard. It also has the ability to change the order of scenes with drag and drop. Step 2: The character design tool allows users to design their anime characters. Users can freely customize the character's appearance, clothing, and facial expressions. It also has the ability to select the character's hairstyle and clothing, and change the color. Step 3: The animation production tool creates the animation. Users can place characters and backgrounds and set frame-by-frame movements. It also has the ability to adjust the character's position and pose.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0114] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0115] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0116] The 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.

[0117] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (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).

[0119] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0120] 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.

[0121] 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.

[0122] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0123] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0124] 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.

[0125] 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.

[0126] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0127] 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.

[0128] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0129] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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).

[0134] 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.

[0135] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset 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.

[0136] 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.

[0137] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0138] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0139] 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.

[0140] 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.

[0141] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0142] 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.

[0143] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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).

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0154] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0155] 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.

[0156] 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.

[0157] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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).

[0163] 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.

[0164] 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."

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] The hardware resource for executing a specific process can be any of the following processors: A CPU is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A dedicated electrical circuit, such as a field-programmable gate array (FPGA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC), is a processor with a circuit configuration specifically designed to execute a specific process. Each processor has built-in or connected memory, and uses the memory to execute the specific process.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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]

[0177] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A storyboard creation tool for creating anime storyboards, A character design tool for designing anime characters, an animation production tool for producing animations; A system characterized by:

2. The storyboard creation tool includes: Using generative AI, emotions are estimated for each scene, and the order of the scenes is automatically suggested based on the flow of emotions.

2. The system of claim 1.

3. The character design tool includes: Using generative AI, expressions and poses based on the character's emotions are automatically suggested.

2. The system of claim 1.

4. The animation production tool includes: Using a generation AI, the emotion of the character for the movement is estimated, and the movement based on the emotion is automatically interpolated.

2. The system of claim 1.

5. Audio recording and editing tools Using generative AI, the emotions of the characters in response to their lines are estimated, and voice filtering is automatically performed based on those emotions.

2. The system of claim 1.

6. Final editing and finishing tools are Using generative AI to estimate emotions associated with transitions between scenes and automatically suggest transitions based on those emotions.

2. The system of claim 1.

7. The storyboard creation tool includes: Using emotion estimation, the system analyzes the emotions of users as they create scenes in real time and makes suggestions to elicit positive emotions.

2. The system of claim 1.

8. The character design tool includes: Using an emotion estimation function, the emotion felt by the user when designing the character is analyzed, and the direction of the design is proposed.

2. The system of claim 1.

Images