System

Abstract

An object of a system according to an embodiment is to make a process of generating an animation video efficient.SOLUTION: A system according to an embodiment includes a character creation unit, a layout creation unit, an original image creation unit, and a moving image creation unit. The character generation unit generates an image-set character. The layout creation unit creates a layout based on the storyboard based on the character generated by the character generation unit. The original image creation unit creates an original image based on the layout created by the layout creation unit. The moving image creation unit creates a moving image based on the original image created by the original image creation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional techniques have had the problem that the process of generating animated videos is time-consuming and labor-intensive, making it difficult to carry out efficiently.

[0005] The system according to the embodiment aims to improve the efficiency of the animation video generation process. [Means for solving the problem]

[0006] The system according to the embodiment includes a character generation unit, a layout creation unit, an original drawing creation unit, and a video creation unit. The character generation unit generates a character with an image set. The layout creation unit creates a layout based on a storyboard using the character generated by the character generation unit. The original drawing creation unit creates an original drawing based on the layout created by the layout creation unit. The video creation unit creates a video based on the original drawing created by the original drawing creation unit. [Effects of the Invention]

[0007] The system according to the embodiment can streamline the process of generating animated 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

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

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

[0028] (Example 1) The animation production system according to an embodiment of the present invention is a system that automatically creates storyboard-based layouts, original drawings, and animations based on image-set characters. This significantly improves the efficiency of animation production, and is expected to reduce production time and costs.

[0029] An animated video generation system according to an embodiment includes a character generation unit, a layout creation unit, an original drawing creation unit, and a video creation unit. The character generation unit generates a character based on an image set. For example, the generation AI generates a character's posture and facial expression based on a prompt input by a user. For example, the generation AI receives a prompt such as, "Please generate a smiling character waving," and generates a character image according to the instruction. The layout creation unit creates a layout based on a storyboard using the characters generated by the character generation unit. For example, if the storyboard includes an instruction such as, "Character A stands on the left side, and Character B sits on the right side," the generation AI creates a layout according to the instruction. The original drawing creation unit creates original drawings based on the layout created by the layout creation unit. For example, the generation AI depicts the character's posture and facial expression in detail based on the layout, and adds background scenery and objects. The video creation unit creates a video based on the original drawings created by the original drawing creation unit. For example, in a scene where a character is walking, the generation AI generates multiple frames to represent the walking motion and displays them consecutively to create a video. As a result, the animated video generation system according to the embodiment is expected to significantly improve the efficiency of animation production, shortening production time and reducing costs.

[0030] The character generation unit can reflect a specific art style specified by the user. For example, the character generation unit generates a character based on the specific art style specified by the user, with the generation AI learning the specific art style specified by the user. For example, it generates a character that reflects the style of a specific animation studio. This allows characters to be generated based on the art style specified by the user.

[0031] The character generation unit can introduce an interface that allows the user to provide feedback in real time, allowing the generation results to be instantly corrected. For example, the character generation unit introduces an interface that allows the user to provide feedback in real time when the generation AI generates a character. For example, sliders and buttons are provided that allow the user to adjust the character's facial expression and posture. This allows the user to provide feedback in real time and instantly correct the generation results.

[0032] The character generation unit can automatically generate designs for character costumes and accessories and allow the user to select from them. For example, the character generation unit provides an interface in which the generation AI automatically generates designs for character costumes and accessories and allows the user to select from them. For example, it displays multiple costume and accessory options and allows the user to select their preferred design. This allows the automatic generation of designs for character costumes and accessories and allows the user to select from them.

[0033] The character generation unit can incorporate character designs from different cultures and regions, enabling character generation from a global perspective. For example, the character generation unit allows the generation AI to learn character designs from different cultures and regions and generate characters based on those designs. For example, it can generate characters that reflect the Japanese anime style or the American comic book style. This makes it possible to incorporate character designs from different cultures and regions and generate characters from a global perspective.

[0034] The layout creation unit can reflect the camera angle and lighting conditions specified by the user. For example, the layout creation unit constructs a system that reflects the camera angle and lighting conditions specified by the user when creating a layout. For example, the layout creation unit adjusts the placement of characters based on the camera angle specified by the user. This makes it possible to reflect the camera angle and lighting conditions specified by the user.

[0035] The layout creation unit can provide an interface that allows the user to preview and modify the layout in real time. For example, the layout creation unit constructs a system that provides an interface that allows the user to preview and modify the layout in real time during the layout generation process. For example, the layout creation unit provides options that allow the user to adjust the character placement and background. This allows the user to preview and modify the layout in real time.

[0036] The layout creation unit can automatically generate layouts for different animation styles. For example, the layout creation unit builds a system that automatically generates layouts for different animation styles (for example, 2D animation and 3D animation) by analyzing a storyboard. For example, it generates a layout for 3D animation based on a storyboard for 2D animation. This allows layouts for different animation styles to be automatically generated.

[0037] The layout creation unit can reflect music and sound effects specified by the user to emphasize the atmosphere of the scene. For example, the layout creation unit builds a system that reflects music and sound effects specified by the user when creating a layout to emphasize the atmosphere of the scene. For example, the atmosphere of the scene is adjusted based on music selected by the user. This allows the music and sound effects specified by the user to be reflected and the atmosphere of the scene to be emphasized.

[0038] The original drawing creation unit can reflect a specific art style designated by the user. For example, the original drawing creation unit learns the specific art style designated by the user during the process of creating the original drawing, and creates the original drawing based on that style. For example, the original drawing is created to reflect the style of a specific animation studio. This allows the original drawing to be created based on the art style designated by the user.

[0039] The original drawing creation unit can introduce an interface that allows the user to provide feedback in real time, allowing the user to instantly correct the generated results. For example, the original drawing creation unit introduces an interface that allows the user to provide feedback in real time during the original drawing generation process. For example, sliders and buttons are provided that allow the user to adjust the facial expression and posture of the character. This allows the user to provide feedback in real time and instantly correct the generated results.

[0040] The original art creation unit can incorporate art styles from different cultures and regions, enabling the generation of original art from a global perspective. For example, when creating original art, the original art creation unit learns the art styles of different cultures and regions and creates original art based on those styles. For example, original art that reflects the Japanese anime style or the American comic style is created. This makes it possible to incorporate art styles from different cultures and regions and generate original art from a global perspective.

[0041] The original image creation unit can reflect the camera angle and lighting conditions specified by the user. For example, the original image creation unit constructs a system that reflects the camera angle and lighting conditions specified by the user when creating the original image. For example, the original image creation unit adjusts the position of a character based on the camera angle specified by the user. This makes it possible to reflect the camera angle and lighting conditions specified by the user.

[0042] The video creation unit can reflect a specific animation style specified by the user. For example, the video creation unit learns the specific animation style specified by the user during the video generation process and creates a video based on that style. For example, it creates a video that reflects the style of a specific animation studio. This allows a video to be created based on the animation style specified by the user.

[0043] The video creation unit can introduce an interface that allows the user to provide feedback in real time, allowing the user to instantly correct the generated results. The video creation unit introduces an interface that allows the user to provide feedback in real time, for example, during the video generation process. For example, sliders and buttons are provided that allow the user to adjust the character's movements and facial expressions. This allows the user to provide feedback in real time and instantly correct the generated results.

[0044] The video creation unit can incorporate animation styles from different cultures and regions, enabling video generation from a global perspective. For example, when creating a video, the video creation unit learns animation styles from different cultures and regions and creates a video based on that style. For example, it creates a video that reflects the Japanese anime style or the American comic book style. This makes it possible to incorporate animation styles from different cultures and regions and generate videos from a global perspective.

[0045] The video creation unit can reflect music and sound effects specified by the user to emphasize the atmosphere of a scene. For example, when creating a video, the video creation unit builds a system that reflects music and sound effects specified by the user to emphasize the atmosphere of a scene. For example, the video creation unit adjusts the atmosphere of a scene based on music selected by the user. This allows the music and sound effects specified by the user to be reflected and the atmosphere of a scene to be emphasized.

[0046] The software can reflect a particular animation style specified by a user. For example, the software can learn a particular animation style specified by a user in providing the software and provide an interface or functionality based on that style. For example, the software can provide an interface that reflects the style of a particular animation studio. This allows the software to provide an interface or functionality based on the animation style specified by the user.

[0047] The software may incorporate an interface that allows users to provide real-time feedback and allow for immediate modifications to the software's functionality. For example, during the software delivery process, the software may incorporate an interface that allows users to provide real-time feedback. For example, the software may provide sliders or buttons that allow users to adjust the interface's design or functionality. This allows users to provide real-time feedback and allow for immediate modifications to the software's functionality.

[0048] Software can incorporate animation styles from different cultures and regions, enabling software to be provided from a global perspective. For example, when providing software, software can learn animation styles from different cultures and regions and provide interfaces and functions based on those styles. For example, it can provide an interface that reflects the Japanese anime style or the American comic book style. This makes it possible to incorporate animation styles from different cultures and regions and provide software from a global perspective.

[0049] The software can reflect music and sound effects specified by the user to emphasize the atmosphere of a scene. For example, when the software is provided, the software builds a system that reflects music and sound effects specified by the user to emphasize the atmosphere of a scene. For example, the software adjusts the atmosphere of an interface based on music selected by the user. This allows the music and sound effects specified by the user to be reflected and the atmosphere of a scene to be emphasized.

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

[0051] The character generation unit can reflect a specific art style specified by the user. For example, the generation AI can learn a specific art style specified by the user and generate a character based on that style. It can generate characters that reflect the style of a specific animation studio. It can generate characters based on an art style specified by the user.

[0052] The character generation unit can introduce an interface that allows the user to provide feedback in real time, allowing the generation results to be immediately corrected. For example, an interface that allows the user to provide feedback in real time when the generation AI generates a character can be introduced. Sliders and buttons are provided that allow the user to adjust the character's facial expression and posture. This allows the user to provide feedback in real time and immediately correct the generation results.

[0053] The character generation unit can incorporate character designs from different cultures and regions, enabling character generation from a global perspective. For example, the generation AI can learn character designs from different cultures and regions and generate characters based on those designs. It can generate characters that reflect the Japanese anime style or the American comic book style. This makes it possible to incorporate character designs from different cultures and regions and generate characters from a global perspective.

[0054] The layout creation unit can reflect the camera angle and lighting conditions specified by the user. For example, a system can be constructed that reflects the camera angle and lighting conditions specified by the user when creating a layout. The layout of characters can be adjusted based on the camera angle specified by the user. This allows the camera angle and lighting conditions specified by the user to be reflected.

[0055] The layout creation unit can provide an interface that allows the user to preview and modify the layout in real time. For example, a system can be constructed that provides an interface that allows the user to preview and modify the layout in real time during the layout generation process. Options are provided that allow the user to adjust the placement of characters and background. This allows the user to preview and modify the layout in real time.

[0056] The processing flow of the first embodiment will be briefly explained below.

[0057] Step 1: The character generation unit generates a character based on the image set. For example, the generation AI generates the character's posture and facial expression based on a prompt entered by the user. The generation AI receives a prompt such as "I want to generate a smiling character waving," and generates an image of the character according to that instruction. Step 2: The layout creation unit creates a layout based on the storyboard and the characters generated by the character generation unit. For example, if the storyboard contains an instruction such as "Character A stands on the left and Character B sits on the right," the generation AI creates a layout according to that instruction. Step 3: The original drawing creation unit creates original drawings based on the layout created by the layout creation unit. For example, the generation AI will depict the character's posture and facial expression in detail based on the layout, and draw in the background scenery and objects. Step 4: The animation creation unit creates an animation based on the original drawings created by the original drawing creation unit. For example, in a scene where a character is walking, the generation AI generates multiple frames to represent the walking motion and displays them in succession to create an animation.

[0058] (Example 2) The animation production system according to an embodiment of the present invention is a system that automatically creates storyboard-based layouts, original drawings, and animations based on image-set characters. This significantly improves the efficiency of animation production, and is expected to reduce production time and costs.

[0059] An animated video generation system according to an embodiment includes a character generation unit, a layout creation unit, an original drawing creation unit, and a video creation unit. The character generation unit generates a character based on an image set. For example, the generation AI generates a character's posture and facial expression based on a prompt input by a user. For example, the generation AI receives a prompt such as, "Please generate a smiling character waving," and generates a character image according to the instruction. The layout creation unit creates a layout based on a storyboard using the characters generated by the character generation unit. For example, if the storyboard includes an instruction such as, "Character A stands on the left side, and Character B sits on the right side," the generation AI creates a layout according to the instruction. The original drawing creation unit creates original drawings based on the layout created by the layout creation unit. For example, the generation AI depicts the character's posture and facial expression in detail based on the layout, and adds background scenery and objects. The video creation unit creates a video based on the original drawings created by the original drawing creation unit. For example, in a scene where a character is walking, the generation AI generates multiple frames to represent the walking motion and displays them consecutively to create a video. As a result, the animated video generation system according to the embodiment is expected to significantly improve the efficiency of animation production, shortening production time and reducing costs.

[0060] The character generation unit can estimate the user's emotions and adjust the character's facial expressions and movements based on those emotions. For example, when the generation AI generates the character's movements and facial expressions, the character generation unit analyzes the user's emotions in real time and adjusts the character's facial expressions and movements based on those emotions. For example, if the user is happy, the character's facial expression will be brighter and its movements will be more active. This makes it possible to generate character expressions and movements that correspond to the user's emotions.

[0061] The character generation unit can reflect a specific art style specified by the user. For example, the character generation unit generates a character based on the specific art style specified by the user, with the generation AI learning the specific art style specified by the user. For example, it generates a character that reflects the style of a specific animation studio. This allows characters to be generated based on the art style specified by the user.

[0062] The character generation unit can introduce an interface that allows the user to provide feedback in real time, allowing the generation results to be instantly corrected. For example, the character generation unit introduces an interface that allows the user to provide feedback in real time when the generation AI generates a character. For example, sliders and buttons are provided that allow the user to adjust the character's facial expression and posture. This allows the user to provide feedback in real time and instantly correct the generation results.

[0063] The character generation unit can automatically generate designs for character costumes and accessories and allow the user to select from them. For example, the character generation unit provides an interface in which the generation AI automatically generates designs for character costumes and accessories and allows the user to select from them. For example, it displays multiple costume and accessory options and allows the user to select their preferred design. This allows the automatic generation of designs for character costumes and accessories and allows the user to select from them.

[0064] The character generation unit can incorporate character designs from different cultures and regions, enabling character generation from a global perspective. For example, the character generation unit allows the generation AI to learn character designs from different cultures and regions and generate characters based on those designs. For example, it can generate characters that reflect the Japanese anime style or the American comic book style. This makes it possible to incorporate character designs from different cultures and regions and generate characters from a global perspective.

[0065] The character generation unit can use the emotion estimation function to analyze the emotions felt by the user during the character generation process and make suggestions to elicit positive emotions. For example, the character generation unit uses the emotion estimation function to analyze the emotions felt by the user during the character generation process in real time and make suggestions to elicit positive emotions. For example, if the user is having fun, the character generation unit makes suggestions to design a character that will make the user even more enjoyable. This allows the user's emotions to be analyzed and suggestions to elicit positive emotions to be made.

[0066] The layout creation unit can estimate the atmosphere and emotion of a scene in analyzing a storyboard and adjust the layout based on that. For example, the layout creation unit can estimate the atmosphere and emotion of a scene in analyzing a storyboard and adjust the layout based on that. For example, if a scene has a sense of tension, the layout creation unit can adjust the positioning of characters and the color tone of the background. This allows the layout to be adjusted based on the atmosphere and emotion of the scene.

[0067] The layout creation unit can reflect the camera angle and lighting conditions specified by the user. For example, the layout creation unit constructs a system that reflects the camera angle and lighting conditions specified by the user when creating a layout. For example, the layout creation unit adjusts the placement of characters based on the camera angle specified by the user. This makes it possible to reflect the camera angle and lighting conditions specified by the user.

[0068] The layout creation unit can provide an interface that allows the user to preview and modify the layout in real time. For example, the layout creation unit constructs a system that provides an interface that allows the user to preview and modify the layout in real time during the layout generation process. For example, the layout creation unit provides options that allow the user to adjust the character placement and background. This allows the user to preview and modify the layout in real time.

[0069] The layout creation unit can automatically generate layouts for different animation styles. For example, the layout creation unit builds a system that automatically generates layouts for different animation styles (for example, 2D animation and 3D animation) by analyzing a storyboard. For example, it generates a layout for 3D animation based on a storyboard for 2D animation. This allows layouts for different animation styles to be automatically generated.

[0070] The layout creation unit can reflect music and sound effects specified by the user to emphasize the atmosphere of the scene. For example, the layout creation unit builds a system that reflects music and sound effects specified by the user when creating a layout to emphasize the atmosphere of the scene. For example, the atmosphere of the scene is adjusted based on music selected by the user. This allows the music and sound effects specified by the user to be reflected and the atmosphere of the scene to be emphasized.

[0071] The layout creation unit can use the emotion estimation function to analyze the emotions felt by the user while creating a layout and make suggestions to bring out positive emotions. For example, the layout creation unit uses the emotion estimation function to analyze the emotions felt by the user while creating a layout in real time and make suggestions to bring out positive emotions. For example, if the user is having fun, the layout creation unit makes layout suggestions to make the user even more happy. In this way, the user's emotions are analyzed and suggestions to bring out positive emotions are made.

[0072] The original image creation unit can estimate the user's emotions and adjust the depiction based on the emotions in order to depict the character's actions and expressions in more detail. For example, when creating an original image, the original image creation unit analyzes the user's emotions in real time and adjusts the depiction based on the emotions in order to depict the character's actions and expressions in more detail. For example, if the user is happy, the character's expressions are made brighter and the character's movements more active. This allows the character's actions and expressions to be depicted in more detail based on the user's emotions.

[0073] The original drawing creation unit can reflect a specific art style designated by the user. For example, the original drawing creation unit learns the specific art style designated by the user during the process of creating the original drawing, and creates the original drawing based on that style. For example, the original drawing is created to reflect the style of a specific animation studio. This allows the original drawing to be created based on the art style designated by the user.

[0074] The original drawing creation unit can introduce an interface that allows the user to provide feedback in real time, allowing the user to instantly correct the generated results. For example, the original drawing creation unit introduces an interface that allows the user to provide feedback in real time during the original drawing generation process. For example, sliders and buttons are provided that allow the user to adjust the facial expression and posture of the character. This allows the user to provide feedback in real time and instantly correct the generated results.

[0075] The original art creation unit can incorporate art styles from different cultures and regions, enabling the generation of original art from a global perspective. For example, when creating original art, the original art creation unit learns the art styles of different cultures and regions and creates original art based on those styles. For example, original art that reflects the Japanese anime style or the American comic style is created. This makes it possible to incorporate art styles from different cultures and regions and generate original art from a global perspective.

[0076] The original image creation unit can reflect the camera angle and lighting conditions specified by the user. For example, the original image creation unit constructs a system that reflects the camera angle and lighting conditions specified by the user when creating the original image. For example, the original image creation unit adjusts the position of a character based on the camera angle specified by the user. This makes it possible to reflect the camera angle and lighting conditions specified by the user.

[0077] The original image creation unit can use the emotion estimation function to analyze the emotions felt by the user while creating the original image and make suggestions to bring out positive emotions. For example, the original image creation unit uses the emotion estimation function to analyze the emotions felt by the user while creating the original image in real time and make suggestions to bring out positive emotions. For example, if the user is enjoying themselves, the original image creation unit makes suggestions to make the user enjoy themselves even more. In this way, the user's emotions are analyzed and suggestions to bring out positive emotions are made.

[0078] The video creation unit can estimate the user's emotions and adjust the character's movements and expressions based on those emotions in order to make the character's movements and expressions appear more natural. For example, when creating a video, the video creation unit analyzes the user's emotions in real time and adjusts the character's movements and expressions based on those emotions in order to make the character's movements and expressions appear more natural. For example, if the user is happy, the character's expression can be made brighter and its movements more lively. This allows the character's movements and expressions to appear more natural based on the user's emotions.

[0079] The video creation unit can reflect a specific animation style specified by the user. For example, the video creation unit learns the specific animation style specified by the user during the video generation process and creates a video based on that style. For example, it creates a video that reflects the style of a specific animation studio. This allows a video to be created based on the animation style specified by the user.

[0080] The video creation unit can introduce an interface that allows the user to provide feedback in real time, allowing the user to instantly correct the generated results. The video creation unit introduces an interface that allows the user to provide feedback in real time, for example, during the video generation process. For example, sliders and buttons are provided that allow the user to adjust the character's movements and facial expressions. This allows the user to provide feedback in real time and instantly correct the generated results.

[0081] The video creation unit can incorporate animation styles from different cultures and regions, enabling video generation from a global perspective. For example, when creating a video, the video creation unit learns animation styles from different cultures and regions and creates a video based on that style. For example, it creates a video that reflects the Japanese anime style or the American comic book style. This makes it possible to incorporate animation styles from different cultures and regions and generate videos from a global perspective.

[0082] The video creation unit can reflect music and sound effects specified by the user to emphasize the atmosphere of a scene. For example, when creating a video, the video creation unit builds a system that reflects music and sound effects specified by the user to emphasize the atmosphere of a scene. For example, the video creation unit adjusts the atmosphere of a scene based on music selected by the user. This allows the music and sound effects specified by the user to be reflected and the atmosphere of a scene to be emphasized.

[0083] The video creation unit can use the emotion estimation function to analyze the emotions felt by the user while creating a video and make suggestions to bring out positive emotions. For example, the video creation unit uses the emotion estimation function to analyze the emotions felt by the user while creating a video in real time and make suggestions to bring out positive emotions. For example, if the user is enjoying themselves, the video creation unit makes suggestions to make the user even more enjoyable. In this way, the video creation unit analyzes the user's emotions and makes suggestions to bring out positive emotions.

[0084] The software can estimate a user's emotions and customize the interface and functions based on the emotions. For example, the software can estimate a user's emotions in real time and customize the interface and functions based on the emotions. For example, if the user is relaxed, the color tone of the interface can be made calm. This allows the interface and functions to be customized based on the user's emotions.

[0085] The software can reflect a particular animation style specified by a user. For example, the software can learn a particular animation style specified by a user in providing the software and provide an interface or functionality based on that style. For example, the software can provide an interface that reflects the style of a particular animation studio. This allows the software to provide an interface or functionality based on the animation style specified by the user.

[0086] The software may incorporate an interface that allows users to provide real-time feedback and allow for immediate modifications to the software's functionality. For example, during the software delivery process, the software may incorporate an interface that allows users to provide real-time feedback. For example, the software may provide sliders or buttons that allow users to adjust the interface's design or functionality. This allows users to provide real-time feedback and allow for immediate modifications to the software's functionality.

[0087] Software can incorporate animation styles from different cultures and regions, enabling software to be provided from a global perspective. For example, when providing software, software can learn animation styles from different cultures and regions and provide interfaces and functions based on those styles. For example, it can provide an interface that reflects the Japanese anime style or the American comic book style. This makes it possible to incorporate animation styles from different cultures and regions and provide software from a global perspective.

[0088] The software can reflect music and sound effects specified by the user to emphasize the atmosphere of a scene. For example, when the software is provided, the software builds a system that reflects music and sound effects specified by the user to emphasize the atmosphere of a scene. For example, the software adjusts the atmosphere of an interface based on music selected by the user. This allows the music and sound effects specified by the user to be reflected and the atmosphere of a scene to be emphasized.

[0089] The software can use the emotion estimation function to analyze the emotions felt by the user while using the software and make suggestions to elicit positive emotions. For example, the software can use the emotion estimation function to analyze the emotions felt by the user while using the software in real time and make suggestions to elicit positive emotions. For example, if the user is enjoying the software, the software can make interface suggestions to further increase the enjoyment. This allows the software to analyze the user's emotions and make suggestions to elicit positive emotions.

[0090] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0091] The character generation unit can estimate the user's emotions and adjust the character's facial expressions and movements based on those emotions. For example, if the user is happy, the character's facial expression will be brighter and its movements will be more active. If the user is sad, the character's facial expression will be calmer and its movements will be slower. If the user is surprised, the character's facial expression will be surprised and its movements will be more abrupt. In this way, the character's facial expressions and movements can be generated according to the user's emotions.

[0092] The character generation unit can reflect a specific art style specified by the user. For example, the generation AI can learn a specific art style specified by the user and generate a character based on that style. It can generate characters that reflect the style of a specific animation studio. It can generate characters based on an art style specified by the user.

[0093] The character generation unit can introduce an interface that allows the user to provide feedback in real time, allowing the generation results to be immediately corrected. For example, an interface that allows the user to provide feedback in real time when the generation AI generates a character can be introduced. Sliders and buttons are provided that allow the user to adjust the character's facial expression and posture. This allows the user to provide feedback in real time and immediately correct the generation results.

[0094] The character generation unit can incorporate character designs from different cultures and regions, enabling character generation from a global perspective. For example, the generation AI can learn character designs from different cultures and regions and generate characters based on those designs. It can generate characters that reflect the Japanese anime style or the American comic book style. This makes it possible to incorporate character designs from different cultures and regions and generate characters from a global perspective.

[0095] The character generation unit can use the emotion estimation function to analyze the emotions felt by the user during the character generation process and make suggestions to bring out positive emotions. For example, the emotion estimation function can be used to analyze the emotions felt by the user during the character generation process in real time and make suggestions to bring out positive emotions. If the user is enjoying themselves, character design suggestions to further increase enjoyment are made. This analyzes the user's emotions and makes suggestions to bring out positive emotions.

[0096] The layout creation unit can estimate the atmosphere and emotion of a scene in analyzing the storyboard and adjust the layout based on that. For example, in analyzing the storyboard, the layout creation unit estimates the atmosphere and emotion of a scene and adjusts the layout based on that. If the scene is tense, the character placement and background color tone are adjusted. If the scene is fun, the character placement and background color tone are brightened. In this way, the layout can be adjusted based on the atmosphere and emotion of the scene.

[0097] The layout creation unit can reflect the camera angle and lighting conditions specified by the user. For example, a system can be constructed that reflects the camera angle and lighting conditions specified by the user when creating a layout. The layout of characters can be adjusted based on the camera angle specified by the user. This allows the camera angle and lighting conditions specified by the user to be reflected.

[0098] The layout creation unit can provide an interface that allows the user to preview and modify the layout in real time. For example, a system can be constructed that provides an interface that allows the user to preview and modify the layout in real time during the layout generation process. Options are provided that allow the user to adjust the placement of characters and background. This allows the user to preview and modify the layout in real time.

[0099] The layout creation unit can use the emotion estimation function to analyze the emotions felt by the user while creating a layout and make suggestions to bring out positive emotions. For example, the emotion estimation function can be used to analyze the emotions felt by the user while creating a layout in real time and make suggestions to bring out positive emotions. If the user is enjoying themselves, layout suggestions to further increase their enjoyment are made. In this way, the user's emotions are analyzed and suggestions to bring out positive emotions are made.

[0100] The original drawing creation unit can estimate the user's emotions and adjust the depiction based on the emotions in order to depict the character's actions and expressions in more detail. For example, when creating an original drawing, the unit analyzes the user's emotions in real time and adjusts the depiction based on the emotions in order to depict the character's actions and expressions in more detail. If the user is happy, the character's expression is made brighter and its movements more active. This allows the character's actions and expressions to be depicted in more detail based on the user's emotions.

[0101] The processing flow of the second embodiment will be briefly explained below.

[0102] Step 1: The character generation unit generates a character based on the image set. For example, the generation AI generates the character's posture and facial expression based on a prompt entered by the user. The generation AI receives a prompt such as "I want to generate a smiling character waving," and generates an image of the character according to that instruction. Step 2: The layout creation unit creates a layout based on the storyboard and the characters generated by the character generation unit. For example, if the storyboard contains an instruction such as "Character A stands on the left and Character B sits on the right," the generation AI creates a layout according to that instruction. Step 3: The original drawing creation unit creates original drawings based on the layout created by the layout creation unit. For example, the generation AI will depict the character's posture and facial expression in detail based on the layout, and draw in the background scenery and objects. Step 4: The animation creation unit creates an animation based on the original drawings created by the original drawing creation unit. For example, in a scene where a character is walking, the generation AI generates multiple frames to represent the walking motion and displays them in succession to create an animation.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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).

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0137] 7, a 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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).

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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).

[0156] 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.

[0157] 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."

[0158] 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.

[0159] 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.

[0160] 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.

[0161] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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]

[0170] 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 character generation unit that generates a character according to an image set; a layout creation unit that creates a layout based on a storyboard using the characters generated by the character generation unit; an original image creating unit that creates an original image based on the layout created by the layout creating unit; a moving image creating unit that creates a moving image based on the original image created by the original image creating unit; A system characterized by:

2. The layout creation unit In analyzing the storyboard, the mood and emotion of the scene are estimated and the layout is adjusted accordingly.

2. The system of claim 1.

3. The original image creation unit In order to depict the character's movements and expressions in more detail, the user's emotions are estimated and the depictions are adjusted based on the emotions.

2. The system of claim 1.

4. The video creation unit In order to make the character's movements and expressions appear more natural, the user's emotions are estimated and the movements and expressions are adjusted based on the emotions.

2. The system of claim 1.

5. The character generation unit The user's emotions are estimated, and the character's facial expressions and movements are adjusted based on the emotions.

2. The system of claim 1.

Images