System

Abstract

An object of a system according to an embodiment is to efficiently generate an original image based on a desired condition and a situation of a user.SOLUTION: A system includes an input unit, an analysis unit, a generation unit, and an output unit. The input unit inputs a desired condition or situation of a user. The analysis unit analyzes the desired condition and the situation input by the input unit. The generation unit generates an original image based on the desired condition and the situation analyzed by the analysis unit. The output unit provides the user with the original image generated by the generation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional techniques have had the problem that the process of generating an original image based on the user's desired conditions and circumstances is time-consuming and difficult to carry out efficiently.

[0005] The system according to the embodiment aims to efficiently generate original images based on the desired conditions and circumstances of the user. [Means for solving the problem]

[0006] The system according to the embodiment includes an input unit, an analysis unit, a generation unit, and an output unit. The input unit inputs a user's desired conditions and circumstances. The analysis unit analyzes the desired conditions and circumstances input by the input unit. The generation unit generates an original image based on the desired conditions and circumstances analyzed by the analysis unit. The output unit provides the user with the original image generated by the generation unit. [Effects of the Invention]

[0007] The system according to the embodiment can efficiently generate original images based on the user's desired conditions and circumstances. [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 image generation system according to the embodiment of the present invention is a system in which, when a user inputs desired conditions and circumstances, the generation AI analyzes the information and automatically creates an original image. As a result, the image generation system can automatically create and provide an original image based on the user's desired conditions and circumstances.

[0029] An image generation system according to an embodiment includes an input unit, an analysis unit, a generation unit, and an output unit. The input unit inputs a user's desired conditions and circumstances. For example, the user inputs a specific situation such as "relaxing on a beach at sunset" or "a futuristic cityscape." The analysis unit analyzes the desired conditions and circumstances input by the input unit. For example, the generation AI extracts keywords such as "sunset," "beach," and "relaxation" and generates an image combining each of these elements. The generation unit generates an original image based on the desired conditions and circumstances analyzed by the analysis unit. For example, in response to a prompt for "a futuristic cityscape," an image of a futuristic city including elements such as skyscrapers, flying cars, and neon lights is generated. The output unit provides the original image generated by the generation unit to the user. For example, the user can download or share the generated image. This allows the image generation system according to an embodiment to automatically create and provide an original image based on the user's desired conditions and circumstances.

[0030] The input unit allows the generation AI to automatically suggest additional information related to the conditions and situations entered by the user, generating more specific prompts. For example, if a user enters "a beach at sunset," the generation AI suggests related information such as "people relaxing" and "seashells on the shore," resulting in a prompt that reads "people relaxing on a beach at sunset and seashells on the shore." Similarly, if a user enters "a futuristic city," the generation AI suggests elements such as "flying cars," "neon lights," and "skyscrapers," resulting in a prompt that reads "a futuristic city with flying cars and skyscrapers lit by neon lights." Similarly, if a user enters "a cabin in the woods," the generation AI suggests related information such as "a bonfire," "stars in the night sky," and "a quiet lake," resulting in a prompt that reads "people sitting around a bonfire in a cabin in the woods and a quiet lake with stars shining in the night sky." This allows the generation AI to automatically suggest additional information related to the conditions and situations entered by the user, generating more specific prompts.

[0031] The input unit can analyze a user's past input history and provide input assistance functions optimized for each individual user. For example, if a user has frequently input "seascapes" in the past, the generation AI will suggest related prompts such as "ocean sunsets" and "seaside cafes," providing input assistance tailored to the user's preferences. If a user frequently inputs "futuristic cities," the generation AI will suggest related prompts such as "futuristic city night views" and "futuristic city parks," providing input assistance tailored to the user's preferences. If a user frequently inputs "nature scenes," the generation AI will suggest related prompts such as "mountain scenery" and "river scenery," providing input assistance tailored to the user's preferences. This allows the input unit to analyze a user's past input history and provide input assistance functions optimized for each individual user.

[0032] The input unit can use voice input or gesture input to enable the user to input conditions and situations more intuitively. For example, when the user speaks "sunset beach" through voice input, the generation AI analyzes the voice, recognizes "sunset beach" as a prompt, and generates an image. Also, when the user indicates "mountain scenery" through gesture input, the generation AI analyzes the gesture, recognizes "mountain scenery" as a prompt, and generates an image. Also, when the user speaks "futuristic city" through voice input, the generation AI analyzes the voice, recognizes "futuristic city" as a prompt, and generates an image. This allows the user to input conditions and situations more intuitively through voice input or gesture input.

[0033] The input unit can integrate inputs from different devices to provide a seamless user experience. For example, if a user inputs "sunset beach" on a smartphone and then inputs "people relaxing" on a tablet, the generation AI will integrate the inputs from both devices to generate an image. Similarly, if a user inputs "futuristic city" on a PC and then inputs "flying car" on a smartphone, the generation AI will integrate the inputs from both devices to generate an image. Similarly, if a user inputs "cabin in the woods" on a tablet and then inputs "bonfire" on a PC, the generation AI will integrate the inputs from both devices to generate an image. This allows the inputs from different devices to be integrated to provide a seamless user experience.

[0034] The analysis unit can refer to external data related to the user's input to perform more accurate analysis. For example, if a user inputs "sunset beach," the generation AI will refer to the weather information for that day and generate an image of a beach that reflects a clear sunset. If a user inputs "futuristic city," the generation AI will refer to the latest urban development trend information and generate an image that incorporates futuristic city elements. If a user inputs "cabin in the woods," the generation AI will refer to local news and generate an image that reflects forest scenery appropriate for the season and time of day. This allows the analysis unit to refer to external data related to the user's input to perform more accurate analysis.

[0035] The analysis unit can provide a user with feedback on the analysis results of conditions and situations and an interface that allows the user to confirm and modify the analysis results. For example, when a user inputs "sunset beach," the generation AI displays analysis results such as "sunset," "beach," and "relaxing," and provides an interface that allows the user to modify "relaxing" to "walk." When a user inputs "futuristic city," the generation AI displays analysis results such as "futuristic," "city," and "skyscraper," and provides an interface that allows the user to modify "skyscraper" to "park." When a user inputs "cabin in the woods," the generation AI displays analysis results such as "forest," "cabin," and "bonfire," and provides an interface that allows the user to modify "bonfire" to "lake." In this way, the analysis results of conditions and situations can be provided as feedback to the user, and an interface that allows the user to confirm and modify the analysis results can be provided.

[0036] The analysis unit can automatically translate conditions and situations entered in different languages ​​and perform multilingual analysis. For example, if a user enters "sunset beach" in English, the generation AI uses the automatic translation function to translate it as "sunset beach" and performs analysis. Also, if a user enters "ville futuriste" in French, the generation AI uses the automatic translation function to translate it as "futuristic city" and performs analysis. Also, if a user enters "a hut in the forest" in Chinese, the generation AI uses the automatic translation function to translate it as "a hut in the forest" and performs analysis. This allows the analysis unit to automatically translate conditions and situations entered in different languages ​​and perform multilingual analysis.

[0037] The analysis unit can visualize the analysis results, allowing the user to intuitively understand. For example, when a user inputs "sunset beach," the generation AI visualizes analysis results such as "sunset," "beach," and "relaxing," allowing the user to intuitively understand. Also, when a user inputs "futuristic city," the generation AI visualizes analysis results such as "futuristic," "city," and "skyscraper," allowing the user to intuitively understand. Also, when a user inputs "cabin in the woods," the generation AI visualizes analysis results such as "forest," "cabin," and "bonfire," allowing the user to intuitively understand. In this way, the analysis results can be visualized, allowing the user to intuitively understand.

[0038] The generation unit can learn the user's past preferences and style and generate individually customized images. For example, if the user has frequently requested "sunset beaches" in the past, the generation AI learns the user's preferences and generates customized images of sunset beaches. If the user frequently requests "futuristic cities," the generation AI learns the user's style and generates customized images of futuristic cities. If the user frequently requests "cabins in the woods," the generation AI learns the user's preferences and generates customized images of cabins in the woods. In this way, the generation unit can learn the user's past preferences and style and generate individually customized images.

[0039] The generation unit can provide an interactive editing function that allows the user to modify and adjust the generated images in real time. For example, the generation unit provides an interface that allows the user to adjust the color tone and composition of a generated "sunset beach" image in real time. Also, the generation unit provides an interface that allows the user to modify the building placement and lighting of a generated "futuristic city" image in real time. Also, the generation unit provides an interface that allows the user to adjust the position of background trees and the cabin in real time for a generated "cabin in the woods" image. This makes it possible to provide an interactive editing function that allows the user to modify and adjust the generated images in real time.

[0040] The generation unit can output the generated image as a 3D model or animation, enabling a wider variety of expressions. For example, when a user requests a "sunset beach," the generation AI outputs the image as a 3D model, allowing the user to observe the beach from various angles. When a user requests a "futuristic city," the generation AI outputs the image as an animation, providing a futuristic cityscape featuring flying cars and moving neon lights. When a user requests a "cabin in the woods," the generation AI outputs the image as a 3D model, allowing the user to freely explore the interior of the cabin and the surrounding scenery. This allows the generated image to be output as a 3D model or animation, enabling a wider variety of expressions.

[0041] The generation unit can generate images in different styles and allow the user to select from them. For example, when a user requests a "sunset beach," the generation AI generates images in three styles, painterly, cartoon-style, and photographic, and allows the user to select from them. Also, when a user requests a "futuristic city," the generation AI generates images in three styles, painterly, cartoon-style, and photographic, and allows the user to select from them. Also, when a user requests a "cabin in the woods," the generation AI generates images in three styles, painterly, cartoon-style, and photographic, and allows the user to select from them. In this way, images can be generated in different styles and allow the user to select from them.

[0042] The output unit can output the generated image at high resolution, making it suitable for printing and large-screen display. For example, when a user requests an image of a "sunset beach," the generation AI outputs the image at high resolution so that it can be printed as a poster or calendar. Also, when a user requests an image of a "futuristic city," the generation AI outputs the image at high resolution so that it can be displayed on digital signage or a large-screen display. Also, when a user requests an image of a "cabin in the woods," the generation AI outputs the image at high resolution so that it can be used as wallpaper or an art panel. In this way, the generated image can be output at high resolution so that it can be used for printing and large-screen display.

[0043] The output unit provides a function that allows users to add comments and tags to the generated images, making it easier to manage the images. For example, when a user requests an image of a "beach at sunset," the output unit provides a function that allows the generation AI to add comments and tags to the image, allowing the user to add tags such as "relaxing" and "beautiful sunset." Furthermore, when a user requests an image of a "futuristic city," the generation AI provides a function that allows users to add comments and tags to the image, allowing the user to add tags such as "future" and "skyscraper." Furthermore, when a user requests an image of a "cabin in the woods," the generation AI provides a function that allows users to add comments and tags to the image, allowing the user to add tags such as "quiet place" and "nature." This provides a function that allows users to add comments and tags to the generated images, making it easier to manage the images.

[0044] The output unit can automatically upload the generated images to social media or cloud storage, making them easy to share. For example, when a user requests an image of a "sunset beach," the generation AI automatically uploads the image to social media so that it can be shared with friends and followers. Also, when a user requests an image of a "futuristic city," the generation AI automatically uploads the image to cloud storage so that it can be accessed from other devices. Also, when a user requests an image of a "cabin in the woods," the generation AI automatically uploads the image to social media so that it can be shared with family and friends. This allows the generated images to be automatically uploaded to social media or cloud storage, making them easy to share.

[0045] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0046] The analysis unit can suggest related music and sound effects based on the user's input. For example, if a user inputs "sunset beach," the generation AI will suggest sound effects such as the sound of waves and birds chirping. If a user inputs "futuristic city," the generation AI will suggest futuristic music and urban noises. If a user inputs "cabin in the woods," the generation AI will suggest sound effects such as the sound of wind and the sound of a campfire. This allows the system to suggest related music and sound effects based on the user's input.

[0047] The generation unit can automatically apply frames and filters to the generated images based on the theme selected by the user. For example, when a user requests a "sunset beach," the generation AI applies frames and filters that match the color tones of the sunset. Also, when a user requests a "futuristic city," the generation AI applies frames and filters with a futuristic design. Also, when a user requests a "cabin in the woods," the generation AI applies frames and filters that match the atmosphere of nature. This makes it possible to automatically apply frames and filters to the generated images based on the theme selected by the user.

[0048] The analysis unit can suggest related literary works and poems based on the user's input. For example, if a user inputs "sunset beach," the generation AI will suggest poems and literary works related to sunsets. Similarly, if a user inputs "futuristic city," the generation AI will suggest literary works with a futuristic theme. Similarly, if a user inputs "cabin in the woods," the generation AI will suggest poems and literary works with a nature theme. This allows the system to suggest related literary works and poems based on the user's input.

[0049] The analysis unit can provide relevant historical background and cultural information based on the user's input. For example, if a user inputs "sunset beach," the generation AI will provide information about the history and culture of the area. Similarly, if a user inputs "futuristic city," the generation AI will provide information about future urban planning and technology. Similarly, if a user inputs "cabin in the woods," the generation AI will provide information about the natural environment and culture of the area. This makes it possible to provide relevant historical background and cultural information based on the user's input.

[0050] The analysis unit can suggest related travel destinations and tourist attractions based on the user's input. For example, if a user inputs "sunset beaches," the generation AI will suggest travel destinations on beaches with beautiful sunsets. Also, if a user inputs "futuristic cities," the generation AI will suggest tourist destinations with futuristic architecture and advanced urban planning. Also, if a user inputs "cabins in the woods," the generation AI will suggest travel destinations with cabins in natural locations. This makes it possible to suggest related travel destinations and tourist attractions based on the user's input.

[0051] The analysis unit can suggest related artworks and designs based on the user's input. For example, if a user inputs "sunset beach," the generation AI will suggest artworks and designs with a sunset theme. Similarly, if a user inputs "futuristic city," the generation AI will suggest artworks with a futuristic architecture and design theme. Similarly, if a user inputs "cabin in the woods," the generation AI will suggest artworks and designs with a nature theme. This makes it possible to suggest related artworks and designs based on the user's input.

[0052] The processing flow of the first embodiment will be briefly explained below.

[0053] Step 1: The input unit inputs the user's desired conditions and situation. For example, the user inputs a specific situation such as "a scene of relaxing on a beach at sunset" or "a futuristic cityscape." Step 2: The analysis unit analyzes the desired conditions and situations entered by the input unit. For example, the generation AI extracts keywords such as "sunset," "beach," and "relaxation," and performs analysis to generate an image that combines each of these elements. Step 3: The generator generates an original image based on the desired conditions and circumstances analyzed by the analyzer. For example, in response to the prompt "futuristic cityscape," it generates an image of a futuristic city including elements such as skyscrapers, flying cars, and neon lights. Step 4: The output unit provides the original image generated by the generation unit to the user. For example, the user can download or share the generated image.

[0054] (Example 2) The image generation system according to the embodiment of the present invention is a system in which, when a user inputs desired conditions and circumstances, the generation AI analyzes the information and automatically creates an original image. As a result, the image generation system can automatically create and provide an original image based on the user's desired conditions and circumstances.

[0055] An image generation system according to an embodiment includes an input unit, an analysis unit, a generation unit, and an output unit. The input unit inputs a user's desired conditions and circumstances. For example, the user inputs a specific situation such as "relaxing on a beach at sunset" or "a futuristic cityscape." The analysis unit analyzes the desired conditions and circumstances input by the input unit. For example, the generation AI extracts keywords such as "sunset," "beach," and "relaxation" and generates an image combining each of these elements. The generation unit generates an original image based on the desired conditions and circumstances analyzed by the analysis unit. For example, in response to a prompt for "a futuristic cityscape," an image of a futuristic city including elements such as skyscrapers, flying cars, and neon lights is generated. The output unit provides the original image generated by the generation unit to the user. For example, the user can download or share the generated image. This allows the image generation system according to an embodiment to automatically create and provide an original image based on the user's desired conditions and circumstances.

[0056] The input unit allows the generation AI to automatically suggest additional information related to the conditions and situations entered by the user, generating more specific prompts. For example, if a user enters "a beach at sunset," the generation AI suggests related information such as "people relaxing" and "seashells on the shore," resulting in a prompt that reads "people relaxing on a beach at sunset and seashells on the shore." Similarly, if a user enters "a futuristic city," the generation AI suggests elements such as "flying cars," "neon lights," and "skyscrapers," resulting in a prompt that reads "a futuristic city with flying cars and skyscrapers lit by neon lights." Similarly, if a user enters "a cabin in the woods," the generation AI suggests related information such as "a bonfire," "stars in the night sky," and "a quiet lake," resulting in a prompt that reads "people sitting around a bonfire in a cabin in the woods and a quiet lake with stars shining in the night sky." This allows the generation AI to automatically suggest additional information related to the conditions and situations entered by the user, generating more specific prompts.

[0057] The input unit can analyze a user's past input history and provide input assistance functions optimized for each individual user. For example, if a user has frequently input "seascapes" in the past, the generation AI will suggest related prompts such as "ocean sunsets" and "seaside cafes," providing input assistance tailored to the user's preferences. If a user frequently inputs "futuristic cities," the generation AI will suggest related prompts such as "futuristic city night views" and "futuristic city parks," providing input assistance tailored to the user's preferences. If a user frequently inputs "nature scenes," the generation AI will suggest related prompts such as "mountain scenery" and "river scenery," providing input assistance tailored to the user's preferences. This allows the input unit to analyze a user's past input history and provide input assistance functions optimized for each individual user.

[0058] The input unit uses the emotion estimation function to analyze the user's emotions when inputting text and can provide input guidance to elicit positive emotions. For example, if the user inputs "sad scenery," the generation AI uses the emotion estimation function to analyze the user's emotions and suggests positive prompts such as "beautiful sunset scenery." If the user inputs "stressful city," the generation AI uses the emotion estimation function to analyze the user's emotions and suggests positive prompts such as "relaxing park scenery." If the user inputs "lonely night," the generation AI uses the emotion estimation function to analyze the user's emotions and suggests positive prompts such as "night spent with friends under the starry sky." This makes it possible to analyze the user's emotions when inputting text and provide input guidance to elicit positive emotions.

[0059] The input unit can use voice input or gesture input to enable the user to input conditions and situations more intuitively. For example, when the user speaks "sunset beach" through voice input, the generation AI analyzes the voice, recognizes "sunset beach" as a prompt, and generates an image. Also, when the user indicates "mountain scenery" through gesture input, the generation AI analyzes the gesture, recognizes "mountain scenery" as a prompt, and generates an image. Also, when the user speaks "futuristic city" through voice input, the generation AI analyzes the voice, recognizes "futuristic city" as a prompt, and generates an image. This allows the user to input conditions and situations more intuitively through voice input or gesture input.

[0060] The input unit can integrate inputs from different devices to provide a seamless user experience. For example, if a user inputs "sunset beach" on a smartphone and then inputs "people relaxing" on a tablet, the generation AI will integrate the inputs from both devices to generate an image. Similarly, if a user inputs "futuristic city" on a PC and then inputs "flying car" on a smartphone, the generation AI will integrate the inputs from both devices to generate an image. Similarly, if a user inputs "cabin in the woods" on a tablet and then inputs "bonfire" on a PC, the generation AI will integrate the inputs from both devices to generate an image. This allows the inputs from different devices to be integrated to provide a seamless user experience.

[0061] The input unit can provide input assistance based on the user's emotional state using a wearable device equipped with an emotion estimation function. For example, if the user is wearing a smartwatch equipped with an emotion estimation function, the device analyzes the user's emotional state and the generation AI suggests a prompt such as "a relaxing landscape." If the user is using a headset equipped with an emotion estimation function, the device analyzes the user's emotional state and the generation AI suggests a prompt such as "a pleasant cityscape." If the user is wearing smart glasses equipped with an emotion estimation function, the device analyzes the user's emotional state and the generation AI suggests a prompt such as "a calm lakescape." This makes it possible to provide input assistance based on the user's emotional state using a wearable device equipped with an emotion estimation function.

[0062] The analysis unit can refer to external data related to the user's input to perform more accurate analysis. For example, if a user inputs "sunset beach," the generation AI will refer to the weather information for that day and generate an image of a beach that reflects a clear sunset. If a user inputs "futuristic city," the generation AI will refer to the latest urban development trend information and generate an image that incorporates futuristic city elements. If a user inputs "cabin in the woods," the generation AI will refer to local news and generate an image that reflects forest scenery appropriate for the season and time of day. This allows the analysis unit to refer to external data related to the user's input to perform more accurate analysis.

[0063] The analysis unit can provide a user with feedback on the analysis results of conditions and situations and an interface that allows the user to confirm and modify the analysis results. For example, when a user inputs "sunset beach," the generation AI displays analysis results such as "sunset," "beach," and "relaxing," and provides an interface that allows the user to modify "relaxing" to "walk." When a user inputs "futuristic city," the generation AI displays analysis results such as "futuristic," "city," and "skyscraper," and provides an interface that allows the user to modify "skyscraper" to "park." When a user inputs "cabin in the woods," the generation AI displays analysis results such as "forest," "cabin," and "bonfire," and provides an interface that allows the user to modify "bonfire" to "lake." In this way, the analysis results of conditions and situations can be provided as feedback to the user, and an interface that allows the user to confirm and modify the analysis results can be provided.

[0064] The analysis unit uses the emotion estimation function to analyze the emotional nuances of the user's input content and generate images based on the emotions. For example, when a user inputs "sunset beach," the generation AI uses the emotion estimation function to analyze the user's emotions and generate an image of a sunset beach that reflects positive emotions. When a user inputs "futuristic city," the generation AI uses the emotion estimation function to analyze the user's emotions and generate an image of an exciting futuristic city. When a user inputs "cabin in the woods," the generation AI uses the emotion estimation function to analyze the user's emotions and generate an image of a relaxing cabin in the woods. In this way, the emotion estimation function can be used to analyze the emotional nuances of the user's input content and generate images based on emotions.

[0065] The analysis unit can automatically translate conditions and situations entered in different languages ​​and perform multilingual analysis. For example, if a user enters "sunset beach" in English, the generation AI uses the automatic translation function to translate it as "sunset beach" and performs analysis. Also, if a user enters "ville futuriste" in French, the generation AI uses the automatic translation function to translate it as "futuristic city" and performs analysis. Also, if a user enters "a hut in the forest" in Chinese, the generation AI uses the automatic translation function to translate it as "a hut in the forest" and performs analysis. This allows the analysis unit to automatically translate conditions and situations entered in different languages ​​and perform multilingual analysis.

[0066] The analysis unit can visualize the analysis results, allowing the user to intuitively understand. For example, when a user inputs "sunset beach," the generation AI visualizes analysis results such as "sunset," "beach," and "relaxing," allowing the user to intuitively understand. Also, when a user inputs "futuristic city," the generation AI visualizes analysis results such as "futuristic," "city," and "skyscraper," allowing the user to intuitively understand. Also, when a user inputs "cabin in the woods," the generation AI visualizes analysis results such as "forest," "cabin," and "bonfire," allowing the user to intuitively understand. In this way, the analysis results can be visualized, allowing the user to intuitively understand.

[0067] The analysis unit uses the emotion estimation function to collect the user's emotional reactions to the analysis results, which can be used to improve the analysis algorithm. For example, when a user inputs "sunset beach," the generation AI uses the emotion estimation function to collect the user's emotional reactions to the analysis results, which can be used to improve the analysis algorithm. Also, when a user inputs "futuristic city," the generation AI uses the emotion estimation function to collect the user's emotional reactions to the analysis results, which can be used to improve the analysis algorithm. Also, when a user inputs "cabin in the woods," the generation AI uses the emotion estimation function to collect the user's emotional reactions to the analysis results, which can be used to improve the analysis algorithm. In this way, the emotion estimation function can be used to collect the user's emotional reactions to the analysis results, which can be used to improve the analysis algorithm.

[0068] The generation unit can learn the user's past preferences and style and generate individually customized images. For example, if the user has frequently requested "sunset beaches" in the past, the generation AI learns the user's preferences and generates customized images of sunset beaches. If the user frequently requests "futuristic cities," the generation AI learns the user's style and generates customized images of futuristic cities. If the user frequently requests "cabins in the woods," the generation AI learns the user's preferences and generates customized images of cabins in the woods. In this way, the generation unit can learn the user's past preferences and style and generate individually customized images.

[0069] The generation unit can provide an interactive editing function that allows the user to modify and adjust the generated images in real time. For example, the generation unit provides an interface that allows the user to adjust the color tone and composition of a generated "sunset beach" image in real time. Also, the generation unit provides an interface that allows the user to modify the building placement and lighting of a generated "futuristic city" image in real time. Also, the generation unit provides an interface that allows the user to adjust the position of background trees and the cabin in real time for a generated "cabin in the woods" image. This makes it possible to provide an interactive editing function that allows the user to modify and adjust the generated images in real time.

[0070] The generation unit can use the emotion estimation function to automatically adjust colors and composition based on the user's emotions. For example, when a user requests a "sunset beach," the generation AI uses the emotion estimation function to analyze the user's emotions and adjusts colors and composition to elicit positive emotions. Also, when a user requests a "futuristic city," the generation AI uses the emotion estimation function to analyze the user's emotions and adjusts colors and composition to be exciting. Also, when a user requests a "cabin in the woods," the generation AI uses the emotion estimation function to analyze the user's emotions and adjusts colors and composition to be relaxing. In this way, the emotion estimation function can be used to automatically adjust colors and composition based on the user's emotions.

[0071] The generation unit can output the generated image as a 3D model or animation, enabling a wider variety of expressions. For example, when a user requests a "sunset beach," the generation AI outputs the image as a 3D model, allowing the user to observe the beach from various angles. When a user requests a "futuristic city," the generation AI outputs the image as an animation, providing a futuristic cityscape featuring flying cars and moving neon lights. When a user requests a "cabin in the woods," the generation AI outputs the image as a 3D model, allowing the user to freely explore the interior of the cabin and the surrounding scenery. This allows the generated image to be output as a 3D model or animation, enabling a wider variety of expressions.

[0072] The generation unit can generate images in different styles and allow the user to select from them. For example, when a user requests a "sunset beach," the generation AI generates images in three styles, painterly, cartoon-style, and photographic, and allows the user to select from them. Also, when a user requests a "futuristic city," the generation AI generates images in three styles, painterly, cartoon-style, and photographic, and allows the user to select from them. Also, when a user requests a "cabin in the woods," the generation AI generates images in three styles, painterly, cartoon-style, and photographic, and allows the user to select from them. In this way, images can be generated in different styles and allow the user to select from them.

[0073] The generation unit can use the emotion estimation function to collect the user's emotional response to the generated image and reflect it in the next image generation. For example, when the user requests a "sunset beach," the generation AI uses the emotion estimation function to collect the user's emotional response and reflect it in the next image generation. Also, when the user requests a "futuristic city," the generation AI uses the emotion estimation function to collect the user's emotional response and reflect it in the next image generation. Also, when the user requests a "cabin in the woods," the generation AI uses the emotion estimation function to collect the user's emotional response and reflect it in the next image generation. In this way, the emotion estimation function can be used to collect the user's emotional response to the generated image and reflect it in the next image generation.

[0074] The output unit can output the generated image at high resolution, making it suitable for printing and large-screen display. For example, when a user requests an image of a "sunset beach," the generation AI outputs the image at high resolution so that it can be printed as a poster or calendar. Also, when a user requests an image of a "futuristic city," the generation AI outputs the image at high resolution so that it can be displayed on digital signage or a large-screen display. Also, when a user requests an image of a "cabin in the woods," the generation AI outputs the image at high resolution so that it can be used as wallpaper or an art panel. In this way, the generated image can be output at high resolution so that it can be used for printing and large-screen display.

[0075] The output unit provides a function that allows users to add comments and tags to the generated images, making it easier to manage the images. For example, when a user requests an image of a "beach at sunset," the output unit provides a function that allows the generation AI to add comments and tags to the image, allowing the user to add tags such as "relaxing" and "beautiful sunset." Furthermore, when a user requests an image of a "futuristic city," the generation AI provides a function that allows users to add comments and tags to the image, allowing the user to add tags such as "future" and "skyscraper." Furthermore, when a user requests an image of a "cabin in the woods," the generation AI provides a function that allows users to add comments and tags to the image, allowing the user to add tags such as "quiet place" and "nature." This provides a function that allows users to add comments and tags to the generated images, making it easier to manage the images.

[0076] The output unit can use the emotion estimation function to analyze the emotion the user feels when viewing the generated image and provide the result as feedback. For example, when a user views an image of a "sunset beach," the generation AI uses the emotion estimation function to analyze the user's emotion and provides feedback such as "I felt relaxed." When a user views an image of a "futuristic city," the generation AI uses the emotion estimation function to analyze the user's emotion and provides feedback such as "I felt excited." When a user views an image of a "cabin in the woods," the generation AI uses the emotion estimation function to analyze the user's emotion and provides feedback such as "I felt calm." In this way, the emotion estimation function can be used to analyze the emotion the user feels when viewing the generated image and provide the result as feedback.

[0077] The output unit can automatically upload the generated images to social media or cloud storage, making them easy to share. For example, when a user requests an image of a "sunset beach," the generation AI automatically uploads the image to social media so that it can be shared with friends and followers. Also, when a user requests an image of a "futuristic city," the generation AI automatically uploads the image to cloud storage so that it can be accessed from other devices. Also, when a user requests an image of a "cabin in the woods," the generation AI automatically uploads the image to social media so that it can be shared with family and friends. This allows the generated images to be automatically uploaded to social media or cloud storage, making them easy to share.

[0078] The output unit can use the emotion estimation function to collect other users' emotional reactions to the generated images and display popular images in a ranking order. For example, when a user requests an image of a "sunset beach," the generation AI collects other users' emotional reactions and displays images with a high number of positive reactions in a ranking order. Also, when a user requests an image of a "futuristic city," the generation AI collects other users' emotional reactions and displays images with a high number of exciting reactions in a ranking order. Also, when a user requests an image of a "cabin in the woods," the generation AI collects other users' emotional reactions and displays images with a high number of relaxing reactions in a ranking order. In this way, the emotion estimation function can be used to collect other users' emotional reactions to the generated images and display popular images in a ranking order.

[0079] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0080] The analysis unit can suggest related music and sound effects based on the user's input. For example, if a user inputs "sunset beach," the generation AI will suggest sound effects such as the sound of waves and birds chirping. If a user inputs "futuristic city," the generation AI will suggest futuristic music and urban noises. If a user inputs "cabin in the woods," the generation AI will suggest sound effects such as the sound of wind and the sound of a campfire. This allows the system to suggest related music and sound effects based on the user's input.

[0081] The generation unit can automatically apply frames and filters to the generated images based on the theme selected by the user. For example, when a user requests a "sunset beach," the generation AI applies frames and filters that match the color tones of the sunset. Also, when a user requests a "futuristic city," the generation AI applies frames and filters with a futuristic design. Also, when a user requests a "cabin in the woods," the generation AI applies frames and filters that match the atmosphere of nature. This makes it possible to automatically apply frames and filters to the generated images based on the theme selected by the user.

[0082] The analysis unit can suggest related literary works and poems based on the user's input. For example, if a user inputs "sunset beach," the generation AI will suggest poems and literary works related to sunsets. Similarly, if a user inputs "futuristic city," the generation AI will suggest literary works with a futuristic theme. Similarly, if a user inputs "cabin in the woods," the generation AI will suggest poems and literary works with a nature theme. This allows the system to suggest related literary works and poems based on the user's input.

[0083] The generation unit can apply effects to the generated image based on the emotion selected by the user. For example, when a user requests a "sunset beach," the generation AI applies a soft light effect to reflect a relaxed emotion. When a user requests a "futuristic city," the generation AI applies a vibrant color effect to reflect an excited emotion. When a user requests a "cabin in the woods," the generation AI applies a calm color effect to reflect a calm emotion. This allows effects based on the emotion selected by the user to be applied to the generated image.

[0084] The analysis unit can provide relevant historical background and cultural information based on the user's input. For example, if a user inputs "sunset beach," the generation AI will provide information about the history and culture of the area. Similarly, if a user inputs "futuristic city," the generation AI will provide information about future urban planning and technology. Similarly, if a user inputs "cabin in the woods," the generation AI will provide information about the natural environment and culture of the area. This makes it possible to provide relevant historical background and cultural information based on the user's input.

[0085] The generation unit can automatically play music based on the emotion selected by the user for the generated image. For example, when a user requests a "sunset beach," the generation AI plays calm music to reflect a relaxed emotion. When a user requests a "futuristic city," the generation AI plays energetic music to reflect an excited emotion. When a user requests a "cabin in the woods," the generation AI plays quiet music to reflect a calm emotion. This allows music based on the emotion selected by the user to be automatically played for the generated image.

[0086] The analysis unit can suggest related travel destinations and tourist attractions based on the user's input. For example, if a user inputs "sunset beaches," the generation AI will suggest travel destinations on beaches with beautiful sunsets. Also, if a user inputs "futuristic cities," the generation AI will suggest tourist destinations with futuristic architecture and advanced urban planning. Also, if a user inputs "cabins in the woods," the generation AI will suggest travel destinations with cabins in natural locations. This makes it possible to suggest related travel destinations and tourist attractions based on the user's input.

[0087] The generation unit can apply animation effects to the generated images based on the emotions selected by the user. For example, when a user requests a "sunset beach," the generation AI applies animations of moving waves and a setting sun to reflect a relaxed emotion. When a user requests a "futuristic city," the generation AI applies animations of flashing neon lights and flying cars to reflect an excited emotion. When a user requests a "cabin in the woods," the generation AI applies animations of trees swaying in the wind and a bonfire to reflect a calm emotion. This allows animation effects to be applied to the generated images based on the emotions selected by the user.

[0088] The analysis unit can suggest related artworks and designs based on the user's input. For example, if a user inputs "sunset beach," the generation AI will suggest artworks and designs with a sunset theme. Similarly, if a user inputs "futuristic city," the generation AI will suggest artworks with a futuristic architecture and design theme. Similarly, if a user inputs "cabin in the woods," the generation AI will suggest artworks and designs with a nature theme. This makes it possible to suggest related artworks and designs based on the user's input.

[0089] The generation unit can automatically add text and captions to generated images based on the emotions selected by the user. For example, when a user requests a "sunset beach," the generation AI adds text such as "Relaxing on a beautiful sunset beach" to reflect a relaxed emotion. When a user requests a "futuristic city," the generation AI adds text such as "Adventure in a futuristic city" to reflect an exciting emotion. When a user requests a "cabin in the woods," the generation AI adds text such as "A quiet moment in a cabin in the woods" to reflect a calm emotion. This makes it possible to automatically add text and captions to generated images based on the emotions selected by the user.

[0090] The processing flow of the second embodiment will be briefly explained below.

[0091] Step 1: The input unit inputs the user's desired conditions and situation. For example, the user inputs a specific situation such as "a scene of relaxing on a beach at sunset" or "a futuristic cityscape." Step 2: The analysis unit analyzes the desired conditions and situations entered by the input unit. For example, the generation AI extracts keywords such as "sunset," "beach," and "relaxation," and performs analysis to generate an image that combines each of these elements. Step 3: The generator generates an original image based on the desired conditions and circumstances analyzed by the analyzer. For example, in response to the prompt "futuristic cityscape," it generates an image of a futuristic city including elements such as skyscrapers, flying cars, and neon lights. Step 4: The output unit provides the original image generated by the generation unit to the user. For example, the user can download or share the generated image.

[0092] 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.

[0093] 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.

[0094] 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.

[0095] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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).

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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).

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0126] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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).

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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).

[0145] 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.

[0146] 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."

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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, in order to avoid confusion and to 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.

[0158] 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]

[0159] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. an input section for inputting the user's desired conditions and circumstances; an analysis unit that analyzes the desired conditions and situations input by the input unit; a generation unit that generates an original image based on the desired conditions and circumstances analyzed by the analysis unit; an output unit that provides the original image generated by the generation unit to a user; A system characterized by:

2. The input unit Using voice input or gesture input, the user can input conditions and the situation more intuitively.

2. The system of claim 1.

3. The analysis unit Refer to external data related to the user's input to perform more accurate analysis 2. The system of claim 1.

4. The generation unit Learn the user's past preferences and styles and generate individually customized images 2. The system of claim 1.

5. The output unit The generated images are output in high resolution, allowing them to be printed or displayed on a large screen.

2. The system of claim 1.

6. The input unit Analyzing the emotions of the user when inputting information and providing an input guide to elicit positive emotions.

2. The system of claim 1.

Images