System

Abstract

An object of a system according to an embodiment is to enable senior generations to easily understand how to operate a smartphone.SOLUTION: A system according to an embodiment includes a screen capture acquisition unit, a generation unit, and an issuance unit. The screen capture acquisition unit acquires a screen capture. The generation unit generates a screen transition flow based on the screen capture acquired by the screen capture acquisition unit. The issuing unit issues the screen transition flow generated by the generation unit as a paper medium.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] With conventional technology, it was difficult for seniors to understand how to operate smartphones, making it difficult to provide them with appropriate support.

[0005] The system according to the embodiment aims to enable senior citizens to easily understand how to operate a smartphone. [Means for solving the problem]

[0006] A system according to an embodiment includes a screen capture acquisition unit, a generation unit, and a publishing unit. The screen capture acquisition unit acquires screen captures. The generation unit generates a screen transition flow based on the screen captures acquired by the screen capture acquisition unit. The publishing unit publishes the screen transition flow generated by the generation unit on a paper medium. [Effects of the Invention]

[0007] The system according to the embodiment can enable seniors to easily understand how to operate a smartphone. [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) A system according to an embodiment of the present invention is a system for resolving concerns about smartphone usage among seniors. This system issues a screen transition flow, along with images, necessary to resolve a situation as a paper medium, simply by taking a screen capture. This allows the system to resolve concerns about smartphone usage among seniors.

[0029] The system according to the embodiment includes a screen capture acquisition unit, a generation unit, and a publishing unit. The screen capture acquisition unit acquires screen captures. For example, a user takes a screenshot of their smartphone and sends it to the system. The screen capture acquisition unit can also record dynamic operation procedures using video capture. For example, a user may record a video of their operation procedures and send it to the system. The generation unit generates a screen transition flow based on the screen captures acquired by the screen capture acquisition unit. For example, a generation AI analyzes the transmitted screen captures and generates a screen transition flow necessary to solve a problem. The generation AI can also provide an individually customized flow by referencing the user's operation history. For example, for a user who has previously experienced the same problem, it can provide a flow based on the solution to that problem. The publishing unit publishes the screen transition flow generated by the generation unit as a paper medium. For example, the generated screen transition flow can be printed with images and provided to the user. The publishing unit can also add a QR code to the paper medium to enable access to detailed digital explanations or video tutorials. For example, the publishing unit can print a QR code that accesses a detailed video tutorial on how to use LINE. This allows the system to solve smartphone usage problems for seniors. For example, to help users understand how to use a smartphone, infographics and illustrations can be used to make it easier to understand visually, and space can be provided for users to add handwritten notes to provide additional information.

[0030] When taking a screen capture, the screen capture acquisition unit can also use voice input to explain the specific problem the user is having. For example, when a user takes a screen capture, the screen capture acquisition unit can also use voice input to explain the specific problem. For example, if a user does not know how to use LINE, the user can explain by voice, "I do not know how to add friends," while taking a screen capture. This allows the generation AI to understand the problem more accurately.

[0031] The screen capture acquisition unit can automatically record the user's operation history when taking a screen capture and send the operation procedures before and after the problem occurred to the generation AI. For example, when taking a screen capture, the screen capture acquisition unit automatically records the user's operation history and sends the operation procedures before and after the problem occurred to the generation AI. For example, if an app crashes, the operation history before and after the crash is recorded and sent. This allows the generation AI to analyze the problem more accurately.

[0032] The screen capture acquisition unit can shoot and send a short video instead of taking a screen capture, and have the generation AI analyze the dynamic operation procedures.The screen capture acquisition unit can, for example, shoot and send a short video instead of taking a screen capture, and have the generation AI analyze the dynamic operation procedures.For example, the operation procedures of an app can be filmed as a video and the video can be sent.This allows the generation AI to analyze the dynamic operation procedures and provide more detailed problem solving.

[0033] The screen capture acquisition unit provides a function that allows the user to add handwritten notes when taking a screen capture, thereby supplementing the details of the problem. The screen capture acquisition unit provides a function that allows the user to add handwritten notes when taking a screen capture, thereby supplementing the details of the problem. For example, the user can add a handwritten note on the screen saying "I don't understand this part." This allows the user to supplement the details of the problem and enable more accurate problem solving.

[0034] The generation unit can refer to the user's past operation history based on the transmitted screen capture and provide an individually customized screen transition flow. For example, when the generation AI generates a screen transition flow, the generation unit refers to the user's past operation history and provides an individually customized flow. For example, for a user who has experienced the same problem in the past, a flow based on that solution is provided. This makes it possible to provide a more appropriate solution based on the user's past operation history.

[0035] The generation unit can automatically refer to related FAQs and help articles based on the submitted screen captures and add more detailed explanations. For example, when the generation AI generates a screen transition flow, the generation unit can automatically refer to related FAQs and help articles and add more detailed explanations. For example, it can refer to an FAQ about how to use LINE and incorporate that content into the flow. This makes it possible to refer to related information and provide more detailed solutions.

[0036] The generation unit can present multiple solutions when generating a screen transition flow, allowing the user to select from them. For example, when the generation AI generates a screen transition flow, the generation unit can present multiple solutions and allow the user to select from them. For example, when using LINE, multiple ways of adding friends can be presented. This allows the user to select from multiple solutions.

[0037] When generating a screen transition flow, the generation unit can refer to success stories of other users to propose the optimal solution. For example, when the generation AI generates a screen transition flow, the generation unit refers to success stories of other users to propose the optimal solution. For example, when using LINE, the generation unit refers to the steps that other users have used successfully. This allows the generation AI to refer to success stories of other users to propose the optimal solution.

[0038] The publishing department can add a QR code when printed on paper media, allowing access to detailed explanations and video tutorials in the digital version. For example, the publishing department can add a QR code when printed on paper media, allowing access to detailed explanations and video tutorials in the digital version. For example, the publishing department can print a QR code that allows access to a detailed video tutorial on how to use LINE. This makes it possible to access detailed explanations and video tutorials in the digital version from the paper medium.

[0039] The issuing unit can provide a space where the user can add handwritten notes when printed on a paper medium, allowing the user to enter individual supplemental information. For example, when printed on a paper medium, the issuing unit can provide a space where the user can add handwritten notes, allowing the user to enter individual supplemental information. For example, a memo space can be provided next to an operating procedure. This allows the user to enter individual supplemental information.

[0040] The issuing unit can write instructions in multiple languages ​​when printed on paper media, making it possible to accommodate users who speak different languages. The issuing unit can write instructions in multiple languages ​​when printed on paper media, making it possible to accommodate users who speak different languages. For example, the issuing unit can write operating procedures in both Japanese and English. This makes it possible to accommodate users who speak different languages.

[0041] The publishing department can use a lot of infographics and illustrations when printing on paper media to make it easier to understand visually. The publishing department can use a lot of infographics and illustrations when printing on paper media to make it easier to understand visually. For example, the publishing department can use illustrations to show operating procedures. This makes it possible to provide paper media that are easy to understand visually.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The system may further include an operation procedure recording unit that records the user's operation procedures. The operation procedure recording unit records the operation procedures when the user performs them and sends them to the generation unit. For example, while the user is operating an app, the operation procedures are recorded and sent to the generation unit. This allows the generation unit to generate a more appropriate screen transition flow based on the recorded operation procedures. In addition, the operation procedure recording unit provides a function that allows the user to add handwritten notes when recording the user's operation procedures, allowing the user to supplement the details of the problem. This allows the user to supplement the details of the problem and solve the problem more accurately.

[0044] The system may further include an operation procedure analysis unit that analyzes the user's operation procedures. When the user performs an operation procedure, the operation procedure analysis unit analyzes the procedure and sends it to the generation unit. For example, when the user is operating an app, the operation procedure analysis unit analyzes the procedure and sends it to the generation unit. This allows the generation unit to generate a more appropriate screen transition flow based on the analyzed operation procedure. In addition, when analyzing the user's operation procedure, the operation procedure analysis unit can automatically refer to related FAQs and help articles and add more detailed explanations. This makes it possible to refer to related information and provide more detailed solutions.

[0045] The system can further include a solution presentation unit that presents multiple solutions when recording the user's operation procedures. The solution presentation unit presents multiple solutions when the user performs the operation procedures, allowing the user to select one. For example, when using LINE, multiple ways of adding friends can be presented. This allows the user to select from multiple solutions. Furthermore, when recording the user's operation procedures, the solution presentation unit can also refer to success stories of other users to suggest the optimal solution. This makes it possible to refer to success stories of other users to suggest the optimal solution.

[0046] The system may further include a visualization unit that makes extensive use of infographics and illustrations to make the user's operation procedures easier to understand visually when recording them. The visualization unit makes extensive use of infographics and illustrations to make the user's operation procedures easier to understand visually when performing them. For example, the operation procedures may be shown using illustrations. This makes it possible to provide operation procedures that are visually easy to understand. The visualization unit may also provide a space for adding handwritten notes when recording the user's operation procedures, allowing the user to enter individual supplemental information. This makes it possible for the user to enter individual supplemental information.

[0047] The system can further include a multilingual support unit that, when recording a user's operating procedures, provides explanations in multiple languages. The multilingual support unit provides explanations in multiple languages ​​when the user performs the operating procedures, making it possible to accommodate users who speak different languages. For example, the operating procedures can be provided in both Japanese and English. This makes it possible to accommodate users who speak different languages. Furthermore, when recording a user's operating procedures, the multilingual support unit can make extensive use of infographics and illustrations to make them visually easy to understand. This makes it possible to provide operating procedures that are visually easy to understand.

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

[0049] Step 1: The screen capture acquisition unit acquires a screen capture. For example, a user takes a screenshot of a smartphone and sends it to the system. The screen capture acquisition unit can also record dynamic operation procedures using video capture. For example, a user records a video of the operation procedures and sends it to the system. Step 2: The generation unit generates a screen transition flow based on the screen captures acquired by the screen capture acquisition unit. For example, the generation AI analyzes the transmitted screen captures and generates the screen transition flow required to solve the problem. The generation AI can also refer to the user's operation history and provide an individually customized flow. For example, if a user has experienced the same problem in the past, it will provide a flow based on that solution. Step 3: The publishing unit publishes the screen transition flow generated by the generating unit as a paper medium. For example, the publishing unit prints out the generated screen transition flow with images and provides it to the user. The publishing unit can also add a QR code to the paper medium to enable access to detailed digital explanations or video tutorials. For example, the publishing unit prints a QR code that enables access to a detailed video tutorial on how to use LINE.

[0050] (Example 2) A system according to an embodiment of the present invention is a system for resolving concerns about smartphone usage among seniors. This system issues a screen transition flow, along with images, necessary to resolve a situation as a paper medium, simply by taking a screen capture. This allows the system to resolve concerns about smartphone usage among seniors.

[0051] The system according to the embodiment includes a screen capture acquisition unit, a generation unit, and a publishing unit. The screen capture acquisition unit acquires screen captures. For example, a user takes a screenshot of their smartphone and sends it to the system. The screen capture acquisition unit can also record dynamic operation procedures using video capture. For example, a user may record a video of their operation procedures and send it to the system. The generation unit generates a screen transition flow based on the screen captures acquired by the screen capture acquisition unit. For example, a generation AI analyzes the transmitted screen captures and generates a screen transition flow necessary to solve a problem. The generation AI can also provide an individually customized flow by referencing the user's operation history. For example, for a user who has previously experienced the same problem, it can provide a flow based on the solution to that problem. The publishing unit publishes the screen transition flow generated by the generation unit as a paper medium. For example, the generated screen transition flow can be printed with images and provided to the user. The publishing unit can also add a QR code to the paper medium to enable access to detailed digital explanations or video tutorials. For example, the publishing unit can print a QR code that accesses a detailed video tutorial on how to use LINE. This allows the system to solve smartphone usage problems for seniors. For example, to help users understand how to use a smartphone, infographics and illustrations can be used to make it easier to understand visually, and space can be provided for users to add handwritten notes to provide additional information.

[0052] When taking a screen capture, the screen capture acquisition unit can also use voice input to explain the specific problem the user is having. For example, when a user takes a screen capture, the screen capture acquisition unit can also use voice input to explain the specific problem. For example, if a user does not know how to use LINE, the user can explain by voice, "I do not know how to add friends," while taking a screen capture. This allows the generation AI to understand the problem more accurately.

[0053] The screen capture acquisition unit can automatically record the user's operation history when taking a screen capture and send the operation procedures before and after the problem occurred to the generation AI. For example, when taking a screen capture, the screen capture acquisition unit automatically records the user's operation history and sends the operation procedures before and after the problem occurred to the generation AI. For example, if an app crashes, the operation history before and after the crash is recorded and sent. This allows the generation AI to analyze the problem more accurately.

[0054] The screen capture acquisition unit can use the emotion estimation function to analyze the emotion of the user when taking a screen capture, and can emphasize and analyze parts that are particularly stressful. For example, the screen capture acquisition unit can use the emotion estimation function to analyze the emotion of the user when taking a screen capture, and can emphasize and analyze parts that are particularly stressful. For example, if the user is irritated, the screen capture acquisition unit can focus on analyzing those parts. This can reduce the user's stress and enable quick problem resolution.

[0055] The screen capture acquisition unit can shoot and send a short video instead of taking a screen capture, and have the generation AI analyze the dynamic operation procedures.The screen capture acquisition unit can, for example, shoot and send a short video instead of taking a screen capture, and have the generation AI analyze the dynamic operation procedures.For example, the operation procedures of an app can be filmed as a video and the video can be sent.This allows the generation AI to analyze the dynamic operation procedures and provide more detailed problem solving.

[0056] The screen capture acquisition unit provides a function that allows the user to add handwritten notes when taking a screen capture, thereby supplementing the details of the problem. The screen capture acquisition unit provides a function that allows the user to add handwritten notes when taking a screen capture, thereby supplementing the details of the problem. For example, the user can add a handwritten note on the screen saying "I don't understand this part." This allows the user to supplement the details of the problem and enable more accurate problem solving.

[0057] The screen capture acquisition unit can use the emotion estimation function to analyze the emotion of the user when taking a screen capture in real time and provide positive feedback. For example, the screen capture acquisition unit can use the emotion estimation function to analyze the emotion of the user when taking a screen capture in real time and provide positive feedback. For example, if the user is feeling stressed, the screen capture acquisition unit can provide feedback such as "It's okay, we'll solve it right away." This makes it possible to provide feedback according to the user's emotion and support problem solving.

[0058] The generation unit can refer to the user's past operation history based on the transmitted screen capture and provide an individually customized screen transition flow. For example, when the generation AI generates a screen transition flow, the generation unit refers to the user's past operation history and provides an individually customized flow. For example, for a user who has experienced the same problem in the past, a flow based on that solution is provided. This makes it possible to provide a more appropriate solution based on the user's past operation history.

[0059] The generation unit can automatically refer to related FAQs and help articles based on the submitted screen captures and add more detailed explanations. For example, when the generation AI generates a screen transition flow, the generation unit can automatically refer to related FAQs and help articles and add more detailed explanations. For example, it can refer to an FAQ about how to use LINE and incorporate that content into the flow. This makes it possible to refer to related information and provide more detailed solutions.

[0060] The generation unit can use the emotion estimation function to generate explanatory text in a tone that corresponds to the user's emotion, making it easier for the user to understand. For example, the generation unit uses the emotion estimation function to generate explanatory text in a tone that corresponds to the user's emotion, making it easier for the user to understand. For example, if the user is feeling anxious, the generation unit generates explanatory text in a gentle tone. This allows explanatory text to be generated in a tone that corresponds to the user's emotion, making it easier for the user to understand.

[0061] The generation unit can present multiple solutions when generating a screen transition flow, allowing the user to select from them. For example, when the generation AI generates a screen transition flow, the generation unit can present multiple solutions and allow the user to select from them. For example, when using LINE, multiple ways of adding friends can be presented. This allows the user to select from multiple solutions.

[0062] When generating a screen transition flow, the generation unit can refer to success stories of other users to propose the optimal solution. For example, when the generation AI generates a screen transition flow, the generation unit refers to success stories of other users to propose the optimal solution. For example, when using LINE, the generation unit refers to the steps that other users have used successfully. This allows the generation AI to refer to success stories of other users to propose the optimal solution.

[0063] The generation unit can use the emotion estimation function to identify the explanation style that is easiest for the user to understand and generate a screen transition flow in that style. For example, the generation unit uses the emotion estimation function to identify the explanation style that is easiest for the user to understand and generates a screen transition flow in that style. For example, if the user prefers visual explanations, it makes extensive use of diagrams and illustrations. This makes it possible to provide a screen transition flow in an explanation style that is easiest for the user to understand.

[0064] The publishing department can add a QR code when printed on paper media, allowing access to detailed explanations and video tutorials in the digital version. For example, the publishing department can add a QR code when printed on paper media, allowing access to detailed explanations and video tutorials in the digital version. For example, the publishing department can print a QR code that allows access to a detailed video tutorial on how to use LINE. This makes it possible to access detailed explanations and video tutorials in the digital version from the paper medium.

[0065] The issuing unit can provide a space where the user can add handwritten notes when printed on a paper medium, allowing the user to enter individual supplemental information. For example, when printed on a paper medium, the issuing unit can provide a space where the user can add handwritten notes, allowing the user to enter individual supplemental information. For example, a memo space can be provided next to an operating procedure. This allows the user to enter individual supplemental information.

[0066] The publishing unit can use the emotion estimation function to provide feedback on the emotions felt by the user when they received the paper medium, and use this feedback to improve the process next time. The publishing unit can, for example, use the emotion estimation function to provide feedback on the emotions felt by the user when they received the paper medium, and use this feedback to improve the process next time. For example, the publishing unit can analyze whether the user is satisfied and reflect this in the generation of the next flow. This allows the publishing unit to provide feedback on the user's emotions, and use this feedback to improve the process next time.

[0067] The issuing unit can write instructions in multiple languages ​​when printed on paper media, making it possible to accommodate users who speak different languages. The issuing unit can write instructions in multiple languages ​​when printed on paper media, making it possible to accommodate users who speak different languages. For example, the issuing unit can write operating procedures in both Japanese and English. This makes it possible to accommodate users who speak different languages.

[0068] The publishing department can use a lot of infographics and illustrations when printing on paper media to make it easier to understand visually. The publishing department can use a lot of infographics and illustrations when printing on paper media to make it easier to understand visually. For example, the publishing department can use illustrations to show operating procedures. This makes it possible to provide paper media that are easy to understand visually.

[0069] The publishing unit can use the emotion estimation function to analyze the emotions of the user when they receive the paper medium in real time and provide positive feedback. For example, the publishing unit can use the emotion estimation function to analyze the emotions of the user when they receive the paper medium in real time and provide positive feedback. For example, if the user is satisfied, the publishing unit can provide feedback such as "I'm glad I could be of help to you." This allows the publishing unit to provide feedback according to the user's emotions and improve satisfaction.

[0070] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0071] The system may further include a voice analysis unit that analyzes the user's voice input. When the user takes a screen capture, the voice analysis unit analyzes the specific problem described in the voice and sends it to the generation unit. For example, if the user describes in voice that "the app keeps crashing," the content of that analysis is analyzed and sent to the generation unit. This allows the generation unit to more accurately understand the problem and generate an appropriate screen transition flow. The voice analysis unit can also estimate emotions from the user's voice and, if the user is feeling stressed, can focus analysis on that part in particular. This reduces the user's stress and enables the problem to be resolved more quickly.

[0072] The system may further include an operation history analysis unit that analyzes the user's operation history. The operation history analysis unit analyzes the user's past operation history and sends it to the generation unit. For example, if the user has experienced the same problem in the past, the operation history is referenced and sent to the generation unit. This allows the generation unit to generate a more appropriate screen transition flow based on the past operation history. The operation history analysis unit can also infer the user's emotions from the user's operation history and focus analysis on areas that cause particular stress. This reduces the user's stress and enables problems to be solved quickly.

[0073] The system may further include a real-time analysis unit that analyzes a user's operation procedures in real time. The real-time analysis unit analyzes the operation procedures in real time as the user performs them and sends them to the generation unit. For example, while the user is operating an app, the operation procedures are analyzed in real time and sent to the generation unit. This allows the generation unit to generate a more appropriate screen transition flow based on the operation procedures analyzed in real time. The real-time analysis unit can also infer emotions from the user's operation procedures and focus analysis on areas that cause particular stress. This reduces the user's stress and enables problems to be solved quickly.

[0074] The system may further include a feedback unit that estimates the user's emotions and provides feedback according to the emotions. The feedback unit estimates the user's emotions and provides feedback according to the emotions. For example, if the user is feeling stressed, the feedback unit may provide feedback such as "It's okay, we'll solve it right away." This provides feedback according to the user's emotions and supports problem solving. The feedback unit may also analyze the user's emotions in real time and provide positive feedback. This provides feedback according to the user's emotions and improves satisfaction.

[0075] The system may further include an explanatory sentence generation unit that estimates the user's emotions and generates explanatory sentences in a tone that corresponds to the emotions. The explanatory sentence generation unit estimates the user's emotions and generates explanatory sentences in a tone that corresponds to the emotions. For example, if the user is feeling anxious, the explanatory sentences are generated in a gentle tone. This allows explanatory sentences to be generated in a tone that corresponds to the user's emotions and makes them easier to understand. The explanatory sentence generation unit may also analyze the user's emotions in real time and generate explanatory sentences in a tone that corresponds to the emotions. This allows explanatory sentences to be generated in a tone that corresponds to the user's emotions and makes them easier to understand.

[0076] The system may further include an operation procedure recording unit that records the user's operation procedures. The operation procedure recording unit records the operation procedures when the user performs them and sends them to the generation unit. For example, while the user is operating an app, the operation procedures are recorded and sent to the generation unit. This allows the generation unit to generate a more appropriate screen transition flow based on the recorded operation procedures. In addition, the operation procedure recording unit provides a function that allows the user to add handwritten notes when recording the user's operation procedures, allowing the user to supplement the details of the problem. This allows the user to supplement the details of the problem and solve the problem more accurately.

[0077] The system may further include an operation procedure analysis unit that analyzes the user's operation procedures. When the user performs an operation procedure, the operation procedure analysis unit analyzes the procedure and sends it to the generation unit. For example, when the user is operating an app, the operation procedure analysis unit analyzes the procedure and sends it to the generation unit. This allows the generation unit to generate a more appropriate screen transition flow based on the analyzed operation procedure. In addition, when analyzing the user's operation procedure, the operation procedure analysis unit can automatically refer to related FAQs and help articles and add more detailed explanations. This makes it possible to refer to related information and provide more detailed solutions.

[0078] The system can further include a solution presentation unit that presents multiple solutions when recording the user's operation procedures. The solution presentation unit presents multiple solutions when the user performs the operation procedures, allowing the user to select one. For example, when using LINE, multiple ways of adding friends can be presented. This allows the user to select from multiple solutions. Furthermore, when recording the user's operation procedures, the solution presentation unit can also refer to success stories of other users to suggest the optimal solution. This makes it possible to refer to success stories of other users to suggest the optimal solution.

[0079] The system may further include a visualization unit that makes extensive use of infographics and illustrations to make the user's operation procedures easier to understand visually when recording them. The visualization unit makes extensive use of infographics and illustrations to make the user's operation procedures easier to understand visually when performing them. For example, the operation procedures may be shown using illustrations. This makes it possible to provide operation procedures that are visually easy to understand. The visualization unit may also provide a space for adding handwritten notes when recording the user's operation procedures, allowing the user to enter individual supplemental information. This makes it possible for the user to enter individual supplemental information.

[0080] The system can further include a multilingual support unit that, when recording a user's operating procedures, provides explanations in multiple languages. The multilingual support unit provides explanations in multiple languages ​​when the user performs the operating procedures, making it possible to accommodate users who speak different languages. For example, the operating procedures can be provided in both Japanese and English. This makes it possible to accommodate users who speak different languages. Furthermore, when recording a user's operating procedures, the multilingual support unit can make extensive use of infographics and illustrations to make them visually easy to understand. This makes it possible to provide operating procedures that are visually easy to understand.

[0081] The processing flow of the second embodiment will be briefly explained below.

[0082] Step 1: The screen capture acquisition unit acquires a screen capture. For example, a user takes a screenshot of a smartphone and sends it to the system. The screen capture acquisition unit can also record dynamic operation procedures using video capture. For example, a user records a video of the operation procedures and sends it to the system. Step 2: The generation unit generates a screen transition flow based on the screen captures acquired by the screen capture acquisition unit. For example, the generation AI analyzes the transmitted screen captures and generates the screen transition flow required to solve the problem. The generation AI can also refer to the user's operation history and provide an individually customized flow. For example, if a user has experienced the same problem in the past, it will provide a flow based on that solution. Step 3: The publishing unit publishes the screen transition flow generated by the generating unit as a paper medium. For example, the publishing unit prints out the generated screen transition flow with images and provides it to the user. The publishing unit can also add a QR code to the paper medium to enable access to detailed digital explanations or video tutorials. For example, the publishing unit prints a QR code that enables access to a detailed video tutorial on how to use LINE.

[0083] 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.

[0084] 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.

[0085] 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.

[0086] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0087] 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.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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).

[0092] 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.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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).

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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. Note that 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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).

[0136] 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.

[0137] 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."

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0149] 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]

[0150] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a screen capture acquisition unit that acquires a screen capture; a generation unit that generates a screen transition flow based on the screen captures acquired by the screen capture acquisition unit; a publishing unit that publishes the screen transition flow generated by the generating unit as a paper medium. A system characterized by:

2. The screen capture acquisition unit When taking a screen capture, the user's operation history is automatically recorded and the operation procedures before and after the problem occurred are sent to the generation AI.

2. The system of claim 1.

3. The screen capture acquisition unit Instead of taking a screen capture, a short video is shot and sent to the AI ​​to analyze the dynamic operation steps.

2. The system of claim 1.

4. The generation unit Based on the screen captures sent, the system references the user's past operation history and provides an individually customized screen transition flow.

2. The system of claim 1.

5. The issuing department: When printed, the QR code will be added to the paper copy, providing access to a detailed digital version and video tutorials.

2. The system of claim 1.

6. The screen capture acquisition unit Analyze the emotions of users when taking screen captures and highlight areas where they feel particularly stressed.

2. The system of claim 1.

7. The generation unit The explanation is generated in a tone that corresponds to the user's emotions, making it easy for the user to understand.

2. The system of claim 1.

8. The issuing department: Feedback on the user's feelings when receiving the paper media will be used to improve the next time.

2. The system of claim 1.

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