system

Abstract

We provide the system. [Solution] A terminal means for receiving voice or text input from a user, A server that analyzes user intent using natural language processing technology, A server means that generates the optimal operating procedure for the user using a generative artificial intelligence model, A terminal device that distributes and presents the generated operating procedures to the user, A terminal means for obtaining user feedback on the results of operations, A server means that sends acquired feedback to the server to improve the generated artificial intelligence model, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a problem that the operations and settings of mobile information terminals are complex and difficult to use, especially for the elderly and technical beginners. Therefore, it is necessary to provide user-friendly support that allows anyone to easily operate a mobile information terminal. In addition, existing support systems have difficulty quickly presenting appropriate solutions corresponding to the situations of individual users and terminals, and as a result, there is a problem that the problems faced by users cannot be accurately solved.

Means for Solving the Problems

[0005] This invention receives voice or text input from a user via a terminal and analyzes the input information using natural language processing technology on a server. Based on the analyzed user requests, it generates optimal operating procedures using a generative artificial intelligence model. The generated operating procedures are delivered to the terminal and presented to the user. Furthermore, the terminal obtains feedback based on the results of the user's operations and sends it to the server. This feedback is used to improve the generative artificial intelligence model and enhance the accuracy of future support. In addition, by identifying the terminal's operating system version and generating individually customized procedures accordingly, it is possible to provide more accurate support. As a result, users can easily perform complex operations on their mobile devices without requiring technical knowledge.

[0006] "Terminal means" refers to devices or functions that receive input from users and communicate with a server.

[0007] A "server means" refers to a device or function that analyzes information from users and performs processing using a generated artificial intelligence model.

[0008] "Natural language processing technology" is a computer technology that enables computers to understand and analyze human language.

[0009] A "generative artificial intelligence model" is a machine learning model that generates optimal solutions or operating procedures based on data.

[0010] "Operating procedures" refer to the specific steps or instructions a user takes to perform a particular function on a mobile device.

[0011] "Feedback" refers to information that describes the results or reactions obtained in response to actions taken by a user. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), and the like.

[0016] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the 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.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, specific processing 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" related to the technology of this 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 processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] This invention begins with a user asking a question about operation or settings via a mobile device. For example, the user might ask the device, "How do I change the volume settings?" The device uses its voice input function to convert the user's question into text data and sends this data to the server.

[0034] The server uses natural language processing techniques to analyze the user's intent from the received text data. For example, from the user's question, the server identifies that the user wants to understand the procedure for adjusting the volume. Next, based on this analysis, the data is input into a generative artificial intelligence model to generate the optimal procedure. This procedure includes specific details such as "open the settings menu, select sound settings, and adjust the volume."

[0035] The generated operating procedure is sent back to the terminal. The terminal then presents this procedure to the user. Possible presentation methods include voice guidance using a voice assistant, or displaying it on the screen in the form of text or images. This allows the user to perform the necessary operations on the terminal by following the presented instructions.

[0036] Furthermore, after the user has finished performing this operation, the device can request feedback from the user to confirm the result. If the user reports that they were able to successfully change the volume settings, the device sends this result to the server. The server collects this feedback and uses it to improve the accuracy of the generative artificial intelligence model for future inquiries.

[0037] In this way, the system of the present invention provides accurate and personalized support so that even users without technical knowledge can easily operate their mobile information terminals. The system's flexibility and customization options to suit the user's terminal make it possible to provide operation guides tailored to various situations.

[0038] The following describes the processing flow.

[0039] Step 1:

[0040] The user inputs a question by voice into a mobile device. The device receives this voice and converts it into text data using speech recognition technology. The text data is then sent to the server. At this time, the user's inquiry is clearly transcribed into text.

[0041] Step 2:

[0042] The server analyzes the received text data using natural language processing techniques. Based on the analysis, it identifies the user's intent, for example, determining that they intend to change the volume setting. Based on this, it prepares data for creating specific operating instructions.

[0043] Step 3:

[0044] The server uses a generative artificial intelligence model to generate the optimal procedure that corresponds to the user's intent. This procedure is customized to take into account the operating system version of the user's terminal. The generated procedure includes step-by-step, specific instructions.

[0045] Step 4:

[0046] The generated operating procedures are sent from the server to the terminal. The terminal then presents the received procedures to the user. Possible presentation methods include audio guidance, text display, or diagrammatic explanations.

[0047] Step 5:

[0048] The user follows the instructions on the device and changes the device settings according to the operating procedure. For example, they open the device's settings menu, select the appropriate option, and change the volume settings.

[0049] Step 6:

[0050] After the operation is complete, the device will ask the user for feedback to confirm the results and whether the operation was successful. This feedback is expected to be entered via voice or text.

[0051] Step 7:

[0052] After the device receives feedback from the user, it sends the feedback information to the server. The server aggregates this information and uses it as data to improve the accuracy of the generated artificial intelligence model.

[0053] In this way, the system provides continuous and efficient support to the user. The seamless coordination of each step enhances the user experience and ensures smooth operation.

[0054] (Example 1)

[0055] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0056] Modern information terminals are highly functional, making it often difficult for the average user to easily operate all of their functions. This necessitates users constantly checking specific operating procedures and settings, leading to decreased operational efficiency. Furthermore, there is a need for systems that can provide precise operational assistance tailored to individual user needs. Additionally, a lack of mechanisms to utilize user feedback to continuously improve system accuracy and usability is another challenge.

[0057] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0058] In this invention, the server includes means for analyzing the user's intent using natural language processing technology and identifying related actions; means for generating the optimal operating procedure for the user using a generative artificial intelligence model and outputting that procedure as specific instructions; and means for analyzing the acquired feedback and using it to improve the accuracy of the generative artificial intelligence model. As a result, the user can easily obtain operating procedures based on their own intent, and the accuracy of the system can continuously improve through feedback.

[0059] A "terminal device" is an information processing device equipped with the function of receiving voice or text input from a user and converting it into digital data.

[0060] A "server system" is an information processing system that operates on a network, analyzes data sent by users, and generates optimal operating procedures using a generated artificial intelligence model.

[0061] "Natural language processing technology" is an information processing technology that analyzes voice or text input from users to understand their intentions and purposes.

[0062] A "generative artificial intelligence model" is a model based on machine learning and artificial intelligence technologies used to generate the optimal operating procedures for a user.

[0063] "Feedback" refers to data sent to a server regarding the results of user actions, which is used to improve the system.

[0064] "Customization" refers to the process of individually adjusting the generated operating procedures based on the user's information processing device's operating system version and individual needs.

[0065] "Visual representation" refers to supplementary information, including visual explanations and icons, that accompany the operating procedures presented to the user.

[0066] This invention provides a system that allows users to easily obtain operating procedures using an information processing terminal. The user inputs questions regarding the operation into the information processing terminal in either voice or text format. In the case of voice input, the terminal uses speech recognition software to convert this voice into text. General speech recognition technologies can be applied to this process.

[0067] The terminal sends the converted text data to the server. The server analyzes the received text data using natural language processing techniques. During the analysis, the context and structure of the text are examined to clearly understand the user's intent and purpose. For example, natural language processing libraries can be used for this technique.

[0068] Based on the analysis results, the server generates the optimal operating procedure using a generative artificial intelligence model. This model is trained using machine learning techniques and is capable of constructing appropriate procedures in response to user questions. Specifically, as a generative AI model, it utilizes, for example, a large-scale language model to understand user questions and generate appropriate prompts accordingly. An example of a prompt sentence is, "How do I change the volume settings?"

[0069] The generated operating instructions are transmitted to the terminal via a communication network. The terminal then provides the operating instructions to the user. Presentation methods include voice guidance from a voice assistant and the display of text and visual icons on the screen. This allows the user to intuitively understand the instructions and perform the terminal operations.

[0070] Furthermore, user feedback is sent from the device to the server. The server analyzes this feedback and uses it to improve the generated AI model. This allows the system to improve its accuracy over time, enabling it to better meet user needs.

[0071] This system allows users to operate their devices more easily and obtain a better user experience. This enables even tech-inexperienced users to perform necessary operations quickly and accurately.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The user inputs a question into the information processing terminal in either voice or text format. Examples of input include specific operational requests such as changing volume settings. The input voice is converted into text data using the terminal's speech recognition technology. The voice data is sent to the speech recognition engine and output as text data.

[0075] Step 2:

[0076] The terminal sends the converted text data to the server over the network. Specifically, the terminal's communication function generates data packets and uses network protocols to forward them to the specified server's IP address. Upon receiving the text data, the server can proceed to the next processing step.

[0077] Step 3:

[0078] The server analyzes the received text data using natural language processing (NLP) techniques. At this stage, the NLP engine performs syntactic analysis of the text to determine the user's intent and extract important keywords and phrases. The input is the text data before analysis, and the output is tagged data indicating the user's intent.

[0079] Step 4:

[0080] The server inputs data into a generative artificial intelligence model based on the analysis results and generates the optimal operating procedure. In this process, prompt sentences are input into the generative AI model, and specific steps for the user corresponding to those sentences are output. A list of procedures is generated, calculated based on the appropriate parameters of the model. The input is the analyzed intent data, and the output is a step-by-step explanation of the procedure.

[0081] Step 5:

[0082] The generated operating procedure is sent from the server to the terminal. The server's communication module packets the data and sends it to the terminal over the network. The terminal decodes the received procedure data and prepares it to be provided to the user.

[0083] Step 6:

[0084] The terminal presents the received instructions to the user. Specifically, this is done through voice guidance and visual representations using text and icons on the display. A speech synthesis engine generates and outputs the voice guidance to the user. Text data is sent to the display module and displayed visually on the screen.

[0085] Step 7:

[0086] After the user performs the suggested operation, the terminal requests feedback from the user based on the result of the operation. The user's response to this prompt is obtained by the terminal via the input device. The feedback data is then sent to the server.

[0087] Step 8:

[0088] The server receives feedback sent from the terminal, analyzes it, and uses it to improve the generated AI model. In this process, the database is updated based on the insights gained from the feedback to evaluate the model's performance and improve the accuracy of prompt generation in the future. Based on the statistics of the feedback data, a trigger for model retraining is output.

[0089] (Application Example 1)

[0090] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0091] Online trading via communication devices is complex for users, especially those unfamiliar with the technology. Therefore, support is needed to enable users to perform transactions quickly and accurately. Furthermore, to improve the user experience, customized guides tailored to the characteristics of individual communication devices are required.

[0092] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0093] In this invention, the server includes an information processing device that analyzes the user's intent using natural language processing technology, an information processing device that generates optimal operating procedures for the user using a generative artificial intelligence model, and a communication device that distributes the generated operating procedures to a communication device and presents them to the user. This allows the user to quickly understand how to operate online transactions and execute various operating procedures. Furthermore, individualized support based on the operating system version of each user's communication device is possible, further improving the user experience.

[0094] "Communication device means" refers to a device equipped with the function of receiving voice or text input from a user and transmitting it to a server.

[0095] An "information processing device" is a device that analyzes received information and utilizes natural language processing technology to understand the user's intent.

[0096] A "generative artificial intelligence model" refers to artificial intelligence technology that has the ability to automatically generate the optimal operating procedures for the user.

[0097] "Operating instructions" refer to information that outlines the steps necessary for a user to achieve a desired action.

[0098] An "online trading platform" is a system that provides a place for users to buy or sell goods and services via the internet.

[0099] This invention is a system that enables users to easily perform operations related to online transactions using a communication device. The server uses natural language processing technology to analyze the intent of questions and requests received from the user. This allows the server to accurately understand the user's intent and generate the optimal operation procedure based on that intent using an artificial intelligence model.

[0100] The communication device is equipped with a voice recognition function, which converts the user's voice input into text data. This text data is sent to a server, which uses an information processing device to perform analysis. The analysis results are input into a generative artificial intelligence model, which generates operating procedures for the online trading platform. The generated operating procedures are delivered to the communication device and presented to the user in visual or audio format. This allows the user to easily perform trading operations.

[0101] For example, if a user asks a voice question like, "I want to know how to buy items that are on sale," the system will immediately provide instructions on how to view a list of relevant products and the specific steps involved in the purchase process. This allows the user to complete the transaction quickly.

[0102] A concrete example of a prompt used in a generative artificial intelligence model is: "When a user says 'Tell me how to apply the coupon,' generate the latest coupon guide and application instructions. The instructions should be written concisely and explained in a way that even a beginner can understand." This example takes user convenience into maximum consideration when generating prompts and presenting operating procedures.

[0103] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0104] Step 1:

[0105] The device receives the user's voice input. The input voice data is converted into text data by the device's voice recognition software. Specifically, the microphone captures the voice, and that data is passed to the voice recognition engine. The output is the converted text data.

[0106] Step 2:

[0107] The terminal sends the generated text data to the server. The server receives this text data as input and uses a natural language processing engine to analyze the user's intent. Through analysis, the content of the text is converted into information that helps understand the steps to be taken. The output is data containing the analysis results.

[0108] Step 3:

[0109] The server executes a generative artificial intelligence model based on the analysis results to generate the optimal operating procedure for the user. The generative AI model receives the analysis results as prompts and devises appropriate steps. Specifically, a detailed guide for the user to operate the online trading platform is generated. The output is the generated operating procedure.

[0110] Step 4:

[0111] The server sends the generated operating instructions to the terminal. The terminal receives these instructions and presents them to the user. The terminal can choose to display the instructions visually on the user's screen or provide voice guidance using a voice assistant. The output is the information presented to the user.

[0112] Step 5:

[0113] The user performs the operation according to the instructions provided. The terminal records the user's actions and collects them as feedback. Specifically, it checks the actions the user actually performed on the terminal and compiles them as feedback data. The output is feedback data regarding the operation results.

[0114] Step 6:

[0115] The terminal sends feedback data to the server. The server receives this feedback and uses it to improve the generated operating procedures. The feedback data is used as information to improve the accuracy of the generated artificial intelligence model. The output is data for model improvement.

[0116] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0117] This invention provides a more personalized user experience on mobile devices by using emotion recognition technology for user support. When a user registers questions about operation or settings via voice or text, the receiving device converts the input into text and sends it to a server.

[0118] Upon receiving user input, the server first uses an emotion engine to analyze the emotions contained in the user's input. This emotion analysis identifies the user's state, for example, "anxious" or "confused." Based on this analysis, the server determines the optimal response method appropriate to the user's emotional state.

[0119] Next, natural language processing techniques are used to analyze the user's question and identify what is being requested. This information is fed into a generative artificial intelligence model, which generates a set of operating procedures that match the user's intent. The generated procedures will reflect considerations that align with the user's emotional state.

[0120] For example, if a user asks in a panicked tone, "The volume suddenly changed, what should I do?", the server recognizes their emotion and generates quick and easy-to-understand instructions. These instructions include specific details such as "where to find the item in the settings menu" and are concisely written to address even panicked situations.

[0121] The generated operating instructions are delivered to the device, which then presents them to the user via voice and screen. The presentation method is also adjusted according to the user's emotions. For example, a confused user will be given a more detailed explanation to reassure them.

[0122] After an operation is performed, the terminal collects feedback from the user reporting the results and sends it to the server. This feedback includes emotion recognition results, which are used to improve future response generation.

[0123] In this way, the present invention can provide appropriate support to users who lack technical knowledge while also being sensitive to their emotions. Furthermore, the system aims to provide more accurate and personalized services through repeated learning.

[0124] The following describes the processing flow.

[0125] Step 1:

[0126] The user enters a problem into their mobile device via voice or text. For example, they might ask, "The screen is too dark, how can I make it brighter?" The device receives this input, converts it to text if it was voice, and sends it to the server.

[0127] Step 2:

[0128] The server passes the received text data to the emotion engine, which analyzes the user's emotions. For example, it might assess that the user is feeling "anxious." This emotion information becomes a factor that influences subsequent procedure generation.

[0129] Step 3:

[0130] The server then uses natural language processing technology to analyze the text data entered by the user. This identifies that the user is requesting "screen brightness adjustment." Based on this analysis, it collects information to resolve the issue.

[0131] Step 4:

[0132] The server uses a generative artificial intelligence model to generate operating procedures that match the user's intentions. The user's emotional state is also considered during procedure generation. For example, a user experiencing anxiety will be given a concise and reassuring procedure.

[0133] Step 5:

[0134] The generated operating procedure is sent from the server to the terminal. Based on this procedure, the terminal provides specific instructions to the user. Here, the terminal presents the procedure in the form of audio and screen display, and adds visual explanations as needed.

[0135] Step 6:

[0136] The user operates the device following the provided instructions. This might involve performing specific actions such as "opening the settings menu, going to display settings, and adjusting the brightness slider."

[0137] Step 7:

[0138] After the operation is complete, the device prompts the user for feedback. The user reports the result, for example, "The screen is brighter. Thank you." This feedback is sent from the device to the server.

[0139] Step 8:

[0140] The server records the emotional information expressed by the user, along with the feedback data received. This data is used as training data to improve the accuracy of future responses.

[0141] Therefore, this system can provide appropriate and personalized support based on the user's emotional state.

[0142] (Example 2)

[0143] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0144] Users of mobile devices sometimes experience difficulty and anxiety when inquiring about operation methods and settings. Especially for users unfamiliar with the device or in urgent situations, prompt and individually considerate responses are necessary. However, conventional technologies have not adequately considered user emotions in their responses or provided optimal operating procedures tailored to those emotions, resulting in a lack of improvement in the user experience.

[0145] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0146] In this invention, the server includes means for analyzing the user's intent using natural language processing technology, means for evaluating the user's emotional state using an emotion analysis engine, and means for generating optimal operating procedures by utilizing a generative artificial intelligence model based on the user's emotional state and intent. This makes it possible to quickly and appropriately provide personalized procedures that reflect the user's emotions.

[0147] 1. An "information processing device" is an electronic device that receives user voice or text input and manages information related to operations and settings.

[0148] 2. A "computational device" is a computer system used for analyzing and processing data, and it plays a role in analyzing the user's intentions and emotional state.

[0149] 3. An "emotion analysis engine" is software or an algorithm that identifies emotional states based on data obtained from users and provides analysis results.

[0150] 4. A "generative artificial intelligence model" is a model that uses artificial intelligence technology to generate information and procedures that meet the user's requirements.

[0151] 5. An "information presentation device" is a device that presents generated operating procedures and information to the user visually or audibly.

[0152] 6. "Feedback" refers to information about the results of actions and emotional states that a user provides through their interaction with the system.

[0153] This invention is a user support system for a mobile information terminal that combines emotion recognition technology and a generative AI model, and is implemented in the following manner.

[0154] First, the user uses a mobile device to input questions or configuration requests via voice or text. The device then uses speech recognition technology (e.g., a common speech recognition API) to convert the voice data into text. This text data is then sent to the server via a secure communication protocol.

[0155] The server analyzes the user's emotions using an emotion analysis engine based on the received text data. The analysis utilizes software employing natural language processing technology to identify the user's emotional state, such as "anxious" or "confused." Subsequently, a generative AI model is used to generate operation procedures that match the user's intentions. This generative AI model provides appropriate procedures based on the user's situation, using prompt text as a basis.

[0156] As a concrete example, consider a scenario where a user enters a question into their device such as, "The volume suddenly changed, what should I do?" After this input is sent to the server, the server, through sentiment analysis, determines that the user is panicking. Based on this result, the generative AI model creates specific instructions for a quick response.

[0157] The generated instructions are sent to the terminal and presented to the user visually or audibly. The terminal can also use speech synthesis technology to provide clear, verbal explanations of the instructions. If necessary, visual instructions can be provided to help the user feel more confident in performing the operation.

[0158] Furthermore, after the user completes an operation, the terminal collects feedback, including the results of the operation, and sends it to the server. This feedback information is used as training data for future response generation, playing a role in improving the accuracy of the system.

[0159] A concrete example of a prompt message is one that expresses the user's specific problem and situation, such as "User: The volume suddenly changed, what should I do?". This allows the generative AI model to generate an answer that aligns with the user's intent and emotions.

[0160] This system makes it possible to quickly provide personalized support that is tailored to the user's emotions.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The user enters questions and setting requests into their mobile device via voice or text.

[0164] The device converts voice input into text using speech recognition software.

[0165] Text data is obtained as the output of this input.

[0166] Step 2:

[0167] The terminal sends the converted text data to the server.

[0168] A secure communication protocol will be used for this transmission.

[0169] The input is text data, and the output is the completion of sending the data to the server.

[0170] Step 3:

[0171] The server performs sentiment analysis using the received text data.

[0172] An emotion analysis engine is used to identify the user's emotions (e.g., anxiety, confusion).

[0173] The input is text data sent to the server, and the output is the analysis results regarding the user's emotional state.

[0174] Step 4:

[0175] The server uses natural language processing techniques to analyze the user's question.

[0176] The data is processed to identify what the user is requesting.

[0177] The input is text data, and the output is the user's specific intent.

[0178] Step 5:

[0179] The server uses a generative AI model to generate operating procedures that match the user's intentions.

[0180] Based on the prompt, the model creates the optimal procedure.

[0181] The input consists of the user's intent and analyzed emotional information, while the output is a set of specific operating procedures.

[0182] Step 6:

[0183] The server sends the generated operating instructions to the terminal.

[0184] The device receives instructions and presents them to the user via voice or screen.

[0185] The input is the operating procedure, and the output is a presentation of the procedure to the user.

[0186] Step 7:

[0187] The user performs the operation according to the provided procedure.

[0188] The device collects the results of the operation.

[0189] The input is the result of the user's actions, and the output is the collected feedback.

[0190] Step 8:

[0191] The device sends the collected feedback to the server.

[0192] The server uses feedback to improve the generated AI model.

[0193] The input is feedback data, and the output is an update to the trained model.

[0194] (Application Example 2)

[0195] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0196] There is a problem in that users cannot quickly obtain appropriate information when using goods or services. Furthermore, presenting information without considering the user's emotional state can damage the user experience. Currently, there is a lack of flexible responses that respond to user emotions.

[0197] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0198] In this invention, the server includes emotion recognition means for performing emotion analysis and acquiring the user's emotional state, information processing means for analyzing the user's intentions using natural language processing technology, and means for adjusting display content that takes the user's emotional state into consideration. This enables the provision of optimal information according to the user's emotions and the presentation of quick and easy-to-understand operating procedures.

[0199] "Device means" refers to a device that receives voice or text input from a user and processes information based on that input.

[0200] An "information processing device" is a device that uses natural language processing technology to analyze the user's intentions and emotions and generate the optimal operating procedure.

[0201] "Emotion recognition means" refers to technologies and devices that analyze and acquire a user's emotional state based on their input.

[0202] A "generative artificial intelligence model" refers to artificial intelligence used to generate operating procedures that respond to the user's intentions and emotions, and to provide appropriate information based on these procedures.

[0203] "Feedback" refers to information collected from users regarding their reactions and opinions on the information they receive and the results of their actions.

[0204] The present invention begins with a device receiving voice or text input from a user and transmitting that data to an information processing device. The information processing device is equipped with a speech recognition API (e.g., Google® Speech-to-Text for converting voice data to text) and an emotion analysis engine (e.g., Microsoft® Azure® Text Analytics for analyzing the user's emotional state), thereby obtaining the user's emotional state.

[0205] Next, a natural language processing engine (e.g., Google Cloud Natural Language) is used to analyze the user's intent. The analyzed information is supplied to a generative artificial intelligence model, which generates the optimal operating procedure for the user. Depending on the user's emotional state, the information processing device adjusts the display content accordingly and presents the information to the user through the device.

[0206] For example, if a user asks about how to use a product in a store, the server recognizes the necessary emotional state from the tone of their voice and generates a quick and gentle explanation. The staff's device then displays specific product usage instructions and related visual information, enabling more personalized customer service.

[0207] In this system, user feedback regarding the results of operations is also important. The device sends the user's reactions and operation results back to the information processing device, thereby improving the accuracy of the generated artificial intelligence model and using it to improve future responses.

[0208] The following are examples of specific prompt messages.

[0209] "The customer is confused. Please gently guide them to the appropriate solution."

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] The user provides voice or text input through the device. This input is received by the terminal and converted to text using a speech recognition API. The input data is then sent to the server as the base text for processing.

[0213] Step 2:

[0214] The server processes the received text using an emotion analysis engine to determine the user's emotional state. This data processing generates emotion tags from the text content. The output is text with emotion tags.

[0215] Step 3:

[0216] The server's natural language processing engine analyzes the sentiment-tagged text to identify the user's intent. This step involves data calculations to extract the request from the text and gather the information necessary for the action. The analysis results become input to the generative AI model.

[0217] Step 4:

[0218] The generative AI model generates optimal operating procedures based on the user's intentions and emotional state. Here, the generated operating procedures are output in a clear format while taking emotions into consideration.

[0219] Step 5:

[0220] The device presents the generated operating procedures to the user. The format of the screen display and audio guidance is adjusted according to the user's emotional state. The user is provided with visual explanations and audio information to support a high level of comprehension.

[0221] Step 6:

[0222] The user inputs their operation results into the device as feedback. This feedback, along with the emotion recognition results, is sent to the server and collected as strategy information.

[0223] Step 7:

[0224] The server uses feedback to update the generated AI model, improving the accuracy of subsequent user interactions. This step involves performing data calculations to adjust the parameters of the generated artificial intelligence model based on the feedback information.

[0225] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0226] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0227] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0228] [Second Embodiment]

[0229] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0230] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0231] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0232] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0233] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0234] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0235] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0236] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0237] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0238] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0239] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0240] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0241] This invention begins with a user asking a question about operation or settings via a mobile device. For example, the user might ask the device, "How do I change the volume settings?" The device uses its voice input function to convert the user's question into text data and sends this data to the server.

[0242] The server uses natural language processing techniques to analyze the user's intent from the received text data. For example, from the user's question, the server identifies that the user wants to understand the procedure for adjusting the volume. Next, based on this analysis, the data is input into a generative artificial intelligence model to generate the optimal procedure. This procedure includes specific details such as "open the settings menu, select sound settings, and adjust the volume."

[0243] The generated operating procedure is sent back to the terminal. The terminal then presents this procedure to the user. Possible presentation methods include voice guidance using a voice assistant, or displaying it on the screen in the form of text or images. This allows the user to perform the necessary operations on the terminal by following the presented instructions.

[0244] Furthermore, after the user has finished performing this operation, the device can request feedback from the user to confirm the result. If the user reports that they were able to successfully change the volume settings, the device sends this result to the server. The server collects this feedback and uses it to improve the accuracy of the generative artificial intelligence model for future inquiries.

[0245] In this way, the system of the present invention provides accurate and personalized support so that even users without technical knowledge can easily operate their mobile information terminals. The system's flexibility and customization options to suit the user's terminal make it possible to provide operation guides tailored to various situations.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user inputs a question by voice into a mobile device. The device receives this voice and converts it into text data using speech recognition technology. The text data is then sent to the server. At this time, the user's inquiry is clearly transcribed into text.

[0249] Step 2:

[0250] The server analyzes the received text data using natural language processing techniques. Based on the analysis, it identifies the user's intent, for example, determining that they intend to change the volume setting. Based on this, it prepares data for creating specific operating instructions.

[0251] Step 3:

[0252] The server uses a generative artificial intelligence model to generate the optimal procedure that corresponds to the user's intent. This procedure is customized to take into account the operating system version of the user's terminal. The generated procedure includes step-by-step, specific instructions.

[0253] Step 4:

[0254] The generated operating procedures are sent from the server to the terminal. The terminal then presents the received procedures to the user. Possible presentation methods include audio guidance, text display, or diagrammatic explanations.

[0255] Step 5:

[0256] The user follows the instructions on the device and changes the device settings according to the operating procedure. For example, they open the device's settings menu, select the appropriate option, and change the volume settings.

[0257] Step 6:

[0258] After the operation is complete, the device will ask the user to confirm the results and provide feedback on whether the operation was successful. This feedback is expected to be entered via voice or text.

[0259] Step 7:

[0260] After the device receives feedback from the user, it sends the feedback information to the server. The server aggregates this information and uses it as data to improve the accuracy of the generated artificial intelligence model.

[0261] In this way, the system provides continuous and efficient support to the user. The seamless coordination of each step enhances the user experience and ensures smooth operation.

[0262] (Example 1)

[0263] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0264] Modern information terminals are highly functional, making it often difficult for the average user to easily operate all of their functions. This necessitates users constantly checking specific operating procedures and settings, leading to decreased operational efficiency. Furthermore, there is a need for systems that can provide precise operational assistance tailored to individual user needs. Additionally, a lack of mechanisms to utilize user feedback to continuously improve system accuracy and usability is another challenge.

[0265] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0266] In this invention, the server includes means for analyzing the user's intent using natural language processing technology and identifying related actions; means for generating the optimal operating procedure for the user using a generative artificial intelligence model and outputting that procedure as specific instructions; and means for analyzing the acquired feedback and using it to improve the accuracy of the generative artificial intelligence model. As a result, the user can easily obtain operating procedures based on their own intent, and the accuracy of the system can continuously improve through feedback.

[0267] A "terminal device" is an information processing device equipped with the function of receiving voice or text input from a user and converting it into digital data.

[0268] A "server system" is an information processing system that operates on a network, analyzes data sent by users, and generates optimal operating procedures using a generated artificial intelligence model.

[0269] "Natural language processing technology" is an information processing technology that analyzes voice or text input from users to understand their intentions and purposes.

[0270] A "generative artificial intelligence model" is a model based on machine learning and artificial intelligence technologies used to generate the optimal operating procedures for a user.

[0271] "Feedback" refers to data sent to a server regarding the results of user actions, which is used to improve the system.

[0272] "Customization" refers to the process of individually adjusting the generated operating procedures based on the user's information processing device's operating system version and individual needs.

[0273] "Visual representation" refers to supplementary information, including visual explanations and icons, that accompany the operating procedures presented to the user.

[0274] This invention provides a system that allows users to easily obtain operating procedures using an information processing terminal. The user inputs questions regarding the operation into the information processing terminal in either voice or text format. In the case of voice input, the terminal uses speech recognition software to convert this voice into text. General speech recognition technologies can be applied to this process.

[0275] The terminal sends the converted text data to the server. The server analyzes the received text data using natural language processing techniques. During the analysis, the context and structure of the text are examined to clearly understand the user's intent and purpose. For example, natural language processing libraries can be used for this technique.

[0276] Based on the analysis results, the server generates the optimal operating procedure using a generative artificial intelligence model. This model is trained using machine learning techniques and is capable of constructing appropriate procedures in response to user questions. Specifically, as a generative AI model, it utilizes, for example, a large-scale language model to understand user questions and generate appropriate prompts accordingly. An example of a prompt sentence is, "How do I change the volume settings?"

[0277] The generated operating instructions are transmitted to the terminal via a communication network. The terminal then provides the operating instructions to the user. Presentation methods include voice guidance from a voice assistant and the display of text and visual icons on the screen. This allows the user to intuitively understand the instructions and perform the terminal operations.

[0278] Furthermore, user feedback is sent from the device to the server. The server analyzes this feedback and uses it to improve the generated AI model. This allows the system to improve its accuracy over time, enabling it to better meet user needs.

[0279] This system allows users to operate their devices more easily and obtain a better user experience. This enables even tech-inexperienced users to perform necessary operations quickly and accurately.

[0280] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0281] Step 1:

[0282] The user inputs a question in the form of voice or text towards the information processing terminal. Taking specific operation requirements such as volume setting change as an example for input. The input voice is converted into text data using the terminal's voice recognition technology. The voice data is sent to the voice recognition engine and output as text data.

[0283] Step 2:

[0284] The terminal sends the converted text data to the server via the network. Specifically, the communication function of the terminal generates data packets and uses network protocols to transfer them to the specified IP address of the server. The server can then move on to the next process by receiving the text data.

[0285] Step 3:

[0286] The server analyzes the received text data using natural language processing technology. At this stage, in order to determine the user's intention from the text data, the NLP engine performs syntactic analysis of the text and extracts important keywords and phrases. The input is the text data before analysis, and the output is the tagged data indicating the user's intention.

[0287] Step 4:

[0288] The server inputs the data into the generated artificial intelligence model based on the analysis results and generates an optimal operation procedure. In this process, a prompt sentence is input into the generated AI model, and the corresponding specific procedures for the user are output. Calculated based on the appropriate parameters of the model, a list of procedures is generated. The input is the analyzed intention data, and the output is a step-by-step explanation of the procedures.

[0289] Step 5:

[0290] The generated operating procedure is sent from the server to the terminal. The server's communication module packets the data and sends it to the terminal over the network. The terminal decodes the received procedure data and prepares it to be provided to the user.

[0291] Step 6:

[0292] The terminal presents the received instructions to the user. Specifically, this is done through voice guidance and visual representations using text and icons on the display. A speech synthesis engine generates and outputs the voice guidance to the user. Text data is sent to the display module and displayed visually on the screen.

[0293] Step 7:

[0294] After the user performs the suggested operation, the terminal requests feedback from the user based on the result of the operation. The user's response to this prompt is obtained by the terminal via the input device. The feedback data is then sent to the server.

[0295] Step 8:

[0296] The server receives feedback sent from the terminal, analyzes it, and uses it to improve the generated AI model. In this process, the database is updated based on the insights gained from the feedback to evaluate the model's performance and improve the accuracy of prompt generation in the future. Based on the statistics of the feedback data, a trigger for model retraining is output.

[0297] (Application Example 1)

[0298] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0299] Online trading via communication devices is complex for users, especially those unfamiliar with the technology. Therefore, support is needed to enable users to perform transactions quickly and accurately. Furthermore, to improve the user experience, customized guides tailored to the characteristics of individual communication devices are required.

[0300] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0301] In this invention, the server includes an information processing device that analyzes the user's intent using natural language processing technology, an information processing device that generates optimal operating procedures for the user using a generative artificial intelligence model, and a communication device that distributes the generated operating procedures to a communication device and presents them to the user. This allows the user to quickly understand how to operate online transactions and execute various operating procedures. Furthermore, individualized support based on the operating system version of each user's communication device is possible, further improving the user experience.

[0302] "Communication device means" refers to a device equipped with the function of receiving voice or text input from a user and transmitting it to a server.

[0303] An "information processing device" is a device that analyzes received information and utilizes natural language processing technology to understand the user's intent.

[0304] A "generative artificial intelligence model" refers to artificial intelligence technology that has the ability to automatically generate the optimal operating procedures for the user.

[0305] "Operating instructions" refer to information that outlines the steps necessary for a user to achieve a desired action.

[0306] An "online trading platform" is a system that provides a place for users to buy or sell goods and services via the internet.

[0307] This invention is a system that enables users to easily perform operations related to online transactions using a communication device. The server utilizes natural language processing technology to analyze the intent of questions and requests received from the user. Thereby, accurately understanding the user's operation intent and generating an optimal operation procedure based on that intent by an artificial intelligence model.

[0308] The communication device is equipped with a voice recognition function that converts the user's voice input into text data. This text data is transmitted to the server, and the server performs analysis using an information processing device. The analyzed result is input into the artificial intelligence model for generating an operation procedure on the online transaction platform. The generated operation procedure is distributed to the communication device and presented to the user in a visual or audio format. Thereby, the user can easily perform the transaction operation.

[0309] As a specific example, when the user asks in voice "I want to know how to purchase the products on sale", this system immediately presents the display method of the related product list and the specific procedures regarding the purchase process. Thereby, the user can quickly execute the transaction.

[0310] As a specific example of the prompt sentence used in the artificial intelligence model for generating, there is "When the user says in voice 'Please teach me how to apply the coupon', please generate the latest coupon guide and application procedures. Write the procedures concisely and explain them so that beginners can understand." This example maximally considers the convenience of the user when generating the prompt sentence and presenting the operation procedure.

[0311] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0312] Step 1:

[0313] The device receives the user's voice input. The input voice data is converted into text data by the device's voice recognition software. Specifically, the microphone captures the voice, and that data is passed to the voice recognition engine. The output is the converted text data.

[0314] Step 2:

[0315] The terminal sends the generated text data to the server. The server receives this text data as input and uses a natural language processing engine to analyze the user's intent. Through analysis, the content of the text is converted into information that helps understand the steps to be taken. The output is data containing the analysis results.

[0316] Step 3:

[0317] The server executes a generative artificial intelligence model based on the analysis results to generate the optimal operating procedure for the user. The generative AI model receives the analysis results as prompts and devises appropriate steps. Specifically, a detailed guide for the user to operate the online trading platform is generated. The output is the generated operating procedure.

[0318] Step 4:

[0319] The server sends the generated operating instructions to the terminal. The terminal receives these instructions and presents them to the user. The terminal can choose to display the instructions visually on the user's screen or provide voice guidance using a voice assistant. The output is the information presented to the user.

[0320] Step 5:

[0321] The user performs the operation according to the instructions provided. The terminal records the user's actions and collects them as feedback. Specifically, it checks the actions the user actually performed on the terminal and compiles them as feedback data. The output is feedback data regarding the operation results.

[0322] Step 6:

[0323] The terminal sends feedback data to the server. The server receives this feedback and uses it to improve the generated operating procedures. The feedback data is used as information to improve the accuracy of the generated artificial intelligence model. The output is data for model improvement.

[0324] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0325] This invention provides a more personalized user experience on mobile devices by using emotion recognition technology for user support. When a user registers questions about operation or settings via voice or text, the receiving device converts the input into text and sends it to a server.

[0326] Upon receiving user input, the server first uses an emotion engine to analyze the emotions contained in the user's input. This emotion analysis identifies the user's state, for example, "anxious" or "confused." Based on this analysis, the server determines the optimal response method appropriate to the user's emotional state.

[0327] Next, natural language processing techniques are used to analyze the user's question and identify what is being requested. This information is fed into a generative artificial intelligence model, which generates a set of operating procedures that match the user's intent. The generated procedures will reflect considerations that align with the user's emotional state.

[0328] For example, if a user asks in a panicked tone, "The volume suddenly changed, what should I do?", the server recognizes their emotion and generates quick and easy-to-understand instructions. These instructions include specific details such as "where to find the item in the settings menu" and are concisely written to address even panicked situations.

[0329] The generated operating instructions are delivered to the device, which then presents them to the user via voice and screen. The presentation method is also adjusted according to the user's emotions. For example, a confused user will be given a more detailed explanation to reassure them.

[0330] After an operation is performed, the terminal collects feedback from the user reporting the results and sends it to the server. This feedback includes emotion recognition results, which are used to improve future response generation.

[0331] In this way, the present invention can provide appropriate support to users who lack technical knowledge while also being sensitive to their emotions. Furthermore, the system aims to provide more accurate and personalized services through repeated learning.

[0332] The following describes the processing flow.

[0333] Step 1:

[0334] The user enters a problem into their mobile device via voice or text. For example, they might ask, "The screen is too dark, how can I make it brighter?" The device receives this input, converts it to text if it was voice, and sends it to the server.

[0335] Step 2:

[0336] The server passes the received text data to the emotion engine, which analyzes the user's emotions. For example, it might assess that the user is feeling "anxious." This emotion information becomes a factor that influences subsequent procedure generation.

[0337] Step 3:

[0338] The server then uses natural language processing technology to analyze the text data entered by the user. This identifies that the user is requesting "screen brightness adjustment." Based on this analysis, it collects information to resolve the issue.

[0339] Step 4:

[0340] The server uses a generative artificial intelligence model to generate operating procedures that match the user's intentions. The user's emotional state is also considered during procedure generation. For example, a user experiencing anxiety will be given a concise and reassuring procedure.

[0341] Step 5:

[0342] The generated operating procedure is sent from the server to the terminal. Based on this procedure, the terminal provides specific instructions to the user. Here, the terminal presents the procedure in the form of audio and screen display, and adds visual explanations as needed.

[0343] Step 6:

[0344] The user operates the device following the provided instructions. This involves performing specific actions such as "opening the settings menu, going to display settings, and adjusting the brightness slider."

[0345] Step 7:

[0346] After the operation is complete, the device prompts the user for feedback. The user reports the result, for example, "The screen is brighter. Thank you." This feedback is sent from the device to the server.

[0347] Step 8:

[0348] The server records the emotional information expressed by the user, along with the feedback data received. This data is used as training data to improve the accuracy of future responses.

[0349] Therefore, this system can provide appropriate and personalized support based on the user's emotional state.

[0350] (Example 2)

[0351] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0352] Users of mobile devices sometimes experience difficulty and anxiety when inquiring about operation methods and settings. Especially for users unfamiliar with the device or in urgent situations, prompt and individually considerate responses are necessary. However, conventional technologies have not adequately considered user emotions in their responses or provided optimal operating procedures tailored to those emotions, resulting in a lack of improvement in the user experience.

[0353] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0354] In this invention, the server includes means for analyzing the user's intent using natural language processing technology, means for evaluating the user's emotional state using an emotion analysis engine, and means for generating optimal operating procedures by utilizing a generative artificial intelligence model based on the user's emotional state and intent. This makes it possible to quickly and appropriately provide personalized procedures that reflect the user's emotions.

[0355] 1. An "information processing device" is an electronic device that receives user voice or text input and manages information related to operations and settings.

[0356] 2. A "computational device" is a computer system used for analyzing and processing data, and it plays a role in analyzing the user's intentions and emotional state.

[0357] 3. An "emotion analysis engine" is software or an algorithm that identifies emotional states based on data obtained from users and provides analysis results.

[0358] 4. A "generative artificial intelligence model" is a model that uses artificial intelligence technology to generate information and procedures that meet the user's requirements.

[0359] 5. An "information presentation device" is a device that presents generated operating procedures and information to the user visually or audibly.

[0360] 6. "Feedback" refers to information about the results of actions and emotional states that a user provides through their interaction with the system.

[0361] This invention is a user support system for a mobile information terminal that combines emotion recognition technology and a generative AI model, and is implemented in the following manner.

[0362] First, the user uses a mobile device to input questions or configuration requests via voice or text. The device then uses speech recognition technology (e.g., a common speech recognition API) to convert the voice data into text. This text data is then sent to the server via a secure communication protocol.

[0363] The server analyzes the user's emotions using an emotion analysis engine based on the received text data. The analysis utilizes software employing natural language processing technology to identify the user's emotional state, such as "anxious" or "confused." Subsequently, a generative AI model is used to generate operation procedures that match the user's intentions. This generative AI model provides appropriate procedures based on the user's situation, using prompt text as a basis.

[0364] As a concrete example, consider a scenario where a user enters a question into their device such as, "The volume suddenly changed, what should I do?" After this input is sent to the server, the server, through sentiment analysis, determines that the user is panicking. Based on this result, the generative AI model creates specific instructions for a quick response.

[0365] The generated instructions are sent to the terminal and presented to the user visually or audibly. The terminal can also use speech synthesis technology to provide clear, verbal explanations of the instructions. If necessary, visual instructions can be provided to help the user feel more confident in performing the operation.

[0366] Furthermore, after the user completes an operation, the terminal collects feedback, including the results of the operation, and sends it to the server. This feedback information is used as training data for future response generation, playing a role in improving the accuracy of the system.

[0367] A concrete example of a prompt message is one that expresses the user's specific problem and situation, such as "User: The volume suddenly changed, what should I do?". This allows the generative AI model to generate an answer that aligns with the user's intent and emotions.

[0368] This system makes it possible to quickly provide personalized support that is tailored to the user's emotions.

[0369] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0370] Step 1:

[0371] The user enters questions and setting requests into their mobile device via voice or text.

[0372] The device converts voice input into text using speech recognition software.

[0373] Text data is obtained as the output of this input.

[0374] Step 2:

[0375] The terminal sends the converted text data to the server.

[0376] A secure communication protocol will be used for this transmission.

[0377] The input is text data, and the output is the completion of sending the data to the server.

[0378] Step 3:

[0379] The server performs sentiment analysis using the received text data.

[0380] An emotion analysis engine is used to identify the user's emotions (e.g., anxiety, confusion).

[0381] The input is text data sent to the server, and the output is the analysis results regarding the user's emotional state.

[0382] Step 4:

[0383] The server uses natural language processing techniques to analyze the user's question.

[0384] The data is processed to identify what the user is requesting.

[0385] The input is text data, and the output is the user's specific intent.

[0386] Step 5:

[0387] The server uses a generative AI model to generate operating procedures that match the user's intentions.

[0388] Based on the prompt, the model creates the optimal procedure.

[0389] The input consists of the user's intent and analyzed emotional information, while the output is a set of specific operating procedures.

[0390] Step 6:

[0391] The server sends the generated operating instructions to the terminal.

[0392] The device receives instructions and presents them to the user via voice or screen.

[0393] The input is the operating procedure, and the output is a presentation of the procedure to the user.

[0394] Step 7:

[0395] The user performs the operation according to the provided procedure.

[0396] The device collects the results of the operation.

[0397] The input is the result of the user's actions, and the output is the collected feedback.

[0398] Step 8:

[0399] The device sends the collected feedback to the server.

[0400] The server uses feedback to improve the generated AI model.

[0401] The input is feedback data, and the output is an update to the trained model.

[0402] (Application Example 2)

[0403] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0404] There is a problem in that users cannot quickly obtain appropriate information when using goods or services. Furthermore, presenting information without considering the user's emotional state can damage the user experience. Currently, there is a lack of flexible responses that respond to user emotions.

[0405] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0406] In this invention, the server includes emotion recognition means for performing emotion analysis and acquiring the user's emotional state, information processing means for analyzing the user's intentions using natural language processing technology, and means for adjusting display content that takes the user's emotional state into consideration. This enables the provision of optimal information according to the user's emotions and the presentation of quick and easy-to-understand operating procedures.

[0407] "Device means" refers to a device that receives voice or text input from a user and processes information based on that input.

[0408] An "information processing device" is a device that uses natural language processing technology to analyze the user's intentions and emotions and generate the optimal operating procedure.

[0409] "Emotion recognition means" refers to technologies and devices that analyze and acquire a user's emotional state based on their input.

[0410] A "generative artificial intelligence model" refers to artificial intelligence used to generate operating procedures that respond to the user's intentions and emotions, and to provide appropriate information based on these procedures.

[0411] "Feedback" refers to information collected from users regarding their reactions and opinions on the information they receive and the results of their actions.

[0412] The present invention begins with a device receiving voice or text input from a user and transmitting that data to an information processing device. The information processing device is equipped with a speech recognition API (e.g., Google Speech-to-Text for converting voice data to text) and an emotion analysis engine (e.g., Microsoft Azure Text Analytics for analyzing the user's emotional state), thereby obtaining the user's emotional state.

[0413] Next, a natural language processing engine (e.g., Google Cloud Natural Language) is used to analyze the user's intent. The analyzed information is supplied to a generative artificial intelligence model, which generates the optimal operating procedure for the user. Depending on the user's emotional state, the information processing device adjusts the display content accordingly and presents the information to the user through the device.

[0414] For example, if a user asks about how to use a product in a store, the server recognizes the necessary emotional state from the tone of their voice and generates a quick and gentle explanation. The staff's device then displays specific product usage instructions and related visual information, enabling more personalized customer service.

[0415] In this system, user feedback regarding the results of operations is also important. The device sends the user's reactions and operation results back to the information processing device, thereby improving the accuracy of the generated artificial intelligence model and using it to improve future responses.

[0416] The following are examples of specific prompt messages.

[0417] "The customer is confused. Please gently guide them to the appropriate solution."

[0418] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0419] Step 1:

[0420] The user provides voice or text input through the device. This input is received by the terminal and converted to text using a speech recognition API. The input data is then sent to the server as the base text for processing.

[0421] Step 2:

[0422] The server processes the received text using an emotion analysis engine to determine the user's emotional state. This data processing generates emotion tags from the text content. The output is text with emotion tags.

[0423] Step 3:

[0424] The server's natural language processing engine analyzes the sentiment-tagged text to identify the user's intent. This step involves data calculations to extract the request from the text and gather the information necessary for the action. The analysis results become input to the generative AI model.

[0425] Step 4:

[0426] The generative AI model generates optimal operating procedures based on the user's intentions and emotional state. Here, the generated operating procedures are output in a clear format while taking emotions into consideration.

[0427] Step 5:

[0428] The device presents the generated operating procedures to the user. The format of the screen display and audio guidance is adjusted according to the user's emotional state. The user is provided with visual explanations and audio information to support a high level of comprehension.

[0429] Step 6:

[0430] The user inputs their operation results into the device as feedback. This feedback, along with the emotion recognition results, is sent to the server and collected as strategy information.

[0431] Step 7:

[0432] The server uses feedback to update the generated AI model, improving the accuracy of subsequent user interactions. This step involves performing data calculations to adjust the parameters of the generated artificial intelligence model based on the feedback information.

[0433] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0434] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0435] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0436] [Third Embodiment]

[0437] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0438] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0439] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0440] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0441] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0442] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0443] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0444] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0445] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0446] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0447] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0448] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0449] This invention begins with a user asking a question about operation or settings via a mobile device. For example, the user might ask the device, "How do I change the volume settings?" The device uses its voice input function to convert the user's question into text data and sends this data to the server.

[0450] The server uses natural language processing techniques to analyze the user's intent from the received text data. For example, from the user's question, the server identifies that the user wants to understand the procedure for adjusting the volume. Next, based on this analysis, the data is input into a generative artificial intelligence model to generate the optimal procedure. This procedure includes specific details such as "open the settings menu, select sound settings, and adjust the volume."

[0451] The generated operating procedure is sent back to the terminal. The terminal then presents this procedure to the user. Possible presentation methods include voice guidance using a voice assistant, or displaying it on the screen in the form of text or images. This allows the user to perform the necessary operations on the terminal by following the presented instructions.

[0452] Furthermore, after the user has finished performing this operation, the device can request feedback from the user to confirm the result. If the user reports that they were able to successfully change the volume settings, the device sends this result to the server. The server collects this feedback and uses it to improve the accuracy of the generative artificial intelligence model for future inquiries.

[0453] In this way, the system of the present invention provides accurate and personalized support so that even users without technical knowledge can easily operate their mobile information terminals. The system's flexibility and customization options to suit the user's terminal make it possible to provide operation guides tailored to various situations.

[0454] The following describes the processing flow.

[0455] Step 1:

[0456] The user inputs a question by voice into a mobile device. The device receives this voice and converts it into text data using speech recognition technology. The text data is then sent to the server. At this time, the user's inquiry is clearly transcribed into text.

[0457] Step 2:

[0458] The server analyzes the received text data using natural language processing techniques. Based on the analysis, it identifies the user's intent, for example, determining that they intend to change the volume setting. Based on this, it prepares data for creating specific operating instructions.

[0459] Step 3:

[0460] The server uses a generative artificial intelligence model to generate the optimal procedure that corresponds to the user's intent. This procedure is customized to take into account the operating system version of the user's terminal. The generated procedure includes step-by-step, specific instructions.

[0461] Step 4:

[0462] The generated operating procedures are sent from the server to the terminal. The terminal then presents the received procedures to the user. Possible presentation methods include audio guidance, text display, or diagrammatic explanations.

[0463] Step 5:

[0464] The user follows the instructions on the device and changes the device settings according to the operating procedure. For example, they open the device's settings menu, select the appropriate option, and change the volume settings.

[0465] Step 6:

[0466] After the operation is complete, the device will ask the user for feedback to confirm the results and whether the operation was successful. This feedback is expected to be entered via voice or text.

[0467] Step 7:

[0468] After the device receives feedback from the user, it sends the feedback information to the server. The server aggregates this information and uses it as data to improve the accuracy of the generated artificial intelligence model.

[0469] In this way, the system provides continuous and efficient support to the user. The seamless coordination of each step enhances the user experience and ensures smooth operation.

[0470] (Example 1)

[0471] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0472] Modern information terminals are highly functional, making it often difficult for the average user to easily operate all of their functions. This necessitates users constantly checking specific operating procedures and settings, leading to decreased operational efficiency. Furthermore, there is a need for systems that can provide precise operational assistance tailored to individual user needs. Additionally, a lack of mechanisms to utilize user feedback to continuously improve system accuracy and usability is another challenge.

[0473] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0474] In this invention, the server includes means for analyzing the user's intent using natural language processing technology and identifying related actions; means for generating the optimal operating procedure for the user using a generative artificial intelligence model and outputting that procedure as specific instructions; and means for analyzing the acquired feedback and using it to improve the accuracy of the generative artificial intelligence model. As a result, the user can easily obtain operating procedures based on their own intent, and the accuracy of the system can continuously improve through feedback.

[0475] A "terminal device" is an information processing device equipped with the function of receiving voice or text input from a user and converting it into digital data.

[0476] A "server system" is an information processing system that operates on a network, analyzes data sent by users, and generates optimal operating procedures using a generated artificial intelligence model.

[0477] "Natural language processing technology" is an information processing technology that analyzes voice or text input from users to understand their intentions and purposes.

[0478] A "generative artificial intelligence model" is a model based on machine learning and artificial intelligence technologies used to generate the optimal operating procedures for a user.

[0479] "Feedback" refers to data sent to a server regarding the results of user actions, which is used to improve the system.

[0480] "Customization" refers to the process of individually adjusting the generated operating procedures based on the user's information processing device's operating system version and individual needs.

[0481] "Visual representation" refers to supplementary information, including visual explanations and icons, that accompany the operating procedures presented to the user.

[0482] This invention provides a system that allows users to easily obtain operating procedures using an information processing terminal. The user inputs questions regarding the operation into the information processing terminal in either voice or text format. In the case of voice input, the terminal uses speech recognition software to convert this voice into text. General speech recognition technologies can be applied to this process.

[0483] The terminal sends the converted text data to the server. The server analyzes the received text data using natural language processing techniques. During the analysis, the context and structure of the text are examined to clearly understand the user's intent and purpose. For example, natural language processing libraries can be used for this technique.

[0484] Based on the analysis results, the server generates the optimal operating procedure using a generative artificial intelligence model. This model is trained using machine learning techniques and is capable of constructing appropriate procedures in response to user questions. Specifically, as a generative AI model, it utilizes, for example, a large-scale language model to understand user questions and generate appropriate prompts accordingly. An example of a prompt sentence is, "How do I change the volume settings?"

[0485] The generated operating instructions are transmitted to the terminal via a communication network. The terminal then provides the operating instructions to the user. Presentation methods include voice guidance from a voice assistant and the display of text and visual icons on the screen. This allows the user to intuitively understand the instructions and perform the terminal operations.

[0486] Furthermore, user feedback is sent from the device to the server. The server analyzes this feedback and uses it to improve the generated AI model. This allows the system to improve its accuracy over time, enabling it to better meet user needs.

[0487] This system allows users to operate their devices more easily and obtain a better user experience. This enables even tech-inexperienced users to perform necessary operations quickly and accurately.

[0488] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0489] Step 1:

[0490] The user inputs a question into the information processing terminal in either voice or text format. Examples of input include specific operational requests such as changing volume settings. The input voice is converted into text data using the terminal's speech recognition technology. The voice data is sent to the speech recognition engine and output as text data.

[0491] Step 2:

[0492] The terminal sends the converted text data to the server over the network. Specifically, the terminal's communication function generates data packets and uses network protocols to forward them to the specified server's IP address. Upon receiving the text data, the server can proceed to the next processing step.

[0493] Step 3:

[0494] The server analyzes the received text data using natural language processing (NLP) techniques. At this stage, the NLP engine performs syntactic analysis of the text to determine the user's intent and extract important keywords and phrases. The input is the text data before analysis, and the output is tagged data indicating the user's intent.

[0495] Step 4:

[0496] The server inputs data into a generative artificial intelligence model based on the analysis results and generates the optimal operating procedure. In this process, prompt sentences are input into the generative AI model, and specific steps for the user corresponding to those sentences are output. A list of procedures is generated, calculated based on the appropriate parameters of the model. The input is the analyzed intent data, and the output is a step-by-step explanation of the procedure.

[0497] Step 5:

[0498] The generated operating procedure is sent from the server to the terminal. The server's communication module packets the data and sends it to the terminal over the network. The terminal decodes the received procedure data and prepares it to be provided to the user.

[0499] Step 6:

[0500] The terminal presents the received instructions to the user. Specifically, this is done through voice guidance and visual representations using text and icons on the display. A speech synthesis engine generates and outputs the voice guidance to the user. Text data is sent to the display module and displayed visually on the screen.

[0501] Step 7:

[0502] After the user performs the suggested operation, the terminal requests feedback from the user based on the result of the operation. The user's response to this prompt is obtained by the terminal via the input device. The feedback data is then sent to the server.

[0503] Step 8:

[0504] The server receives feedback sent from the terminal, analyzes it, and uses it to improve the generated AI model. In this process, the database is updated based on the insights gained from the feedback to evaluate the model's performance and improve the accuracy of prompt generation in the future. Based on the statistics of the feedback data, a trigger for model retraining is output.

[0505] (Application Example 1)

[0506] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0507] Online trading via communication devices is complex for users, especially those unfamiliar with the technology. Therefore, support is needed to enable users to perform transactions quickly and accurately. Furthermore, to improve the user experience, customized guides tailored to the characteristics of individual communication devices are required.

[0508] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0509] In this invention, the server includes an information processing device that analyzes the user's intent using natural language processing technology, an information processing device that generates optimal operating procedures for the user using a generative artificial intelligence model, and a communication device that distributes the generated operating procedures to a communication device and presents them to the user. This allows the user to quickly understand how to operate online transactions and execute various operating procedures. Furthermore, individualized support based on the operating system version of each user's communication device is possible, further improving the user experience.

[0510] "Communication device means" refers to a device equipped with the function of receiving voice or text input from a user and transmitting it to a server.

[0511] An "information processing device" is a device that analyzes received information and utilizes natural language processing technology to understand the user's intent.

[0512] A "generative artificial intelligence model" refers to artificial intelligence technology that has the ability to automatically generate the optimal operating procedures for the user.

[0513] "Operating instructions" refer to information that outlines the steps necessary for a user to achieve a desired action.

[0514] An "online trading platform" is a system that provides a place for users to buy or sell goods and services via the internet.

[0515] This invention is a system that enables users to easily perform operations related to online transactions using a communication device. The server uses natural language processing technology to analyze the intent of questions and requests received from the user. This allows the server to accurately understand the user's intent and generate the optimal operation procedure based on that intent using an artificial intelligence model.

[0516] The communication device is equipped with a voice recognition function, which converts the user's voice input into text data. This text data is sent to a server, which uses an information processing device to perform analysis. The analysis results are input into a generative artificial intelligence model, which generates operating procedures for the online trading platform. The generated operating procedures are delivered to the communication device and presented to the user in visual or audio format. This allows the user to easily perform trading operations.

[0517] For example, if a user asks a voice question like, "I want to know how to buy items that are on sale," the system will immediately provide instructions on how to view a list of relevant products and the specific steps involved in the purchase process. This allows the user to complete the transaction quickly.

[0518] A concrete example of a prompt used in a generative artificial intelligence model is: "When a user says 'Tell me how to apply the coupon,' generate the latest coupon guide and application instructions. The instructions should be written concisely and explained in a way that even a beginner can understand." This example takes user convenience into maximum consideration when generating prompts and presenting operating procedures.

[0519] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0520] Step 1:

[0521] The device receives the user's voice input. The input voice data is converted into text data by the device's voice recognition software. Specifically, the microphone captures the voice, and that data is passed to the voice recognition engine. The output is the converted text data.

[0522] Step 2:

[0523] The terminal sends the generated text data to the server. The server receives this text data as input and uses a natural language processing engine to analyze the user's intent. Through analysis, the content of the text is converted into information that helps understand the steps to be taken. The output is data containing the analysis results.

[0524] Step 3:

[0525] The server executes a generative artificial intelligence model based on the analysis results to generate the optimal operating procedure for the user. The generative AI model receives the analysis results as prompts and devises appropriate steps. Specifically, a detailed guide for the user to operate the online trading platform is generated. The output is the generated operating procedure.

[0526] Step 4:

[0527] The server sends the generated operating instructions to the terminal. The terminal receives these instructions and presents them to the user. The terminal can choose to display the instructions visually on the user's screen or provide voice guidance using a voice assistant. The output is the information presented to the user.

[0528] Step 5:

[0529] The user performs the operation according to the instructions provided. The terminal records the user's actions and collects them as feedback. Specifically, it checks the actions the user actually performed on the terminal and compiles them as feedback data. The output is feedback data regarding the operation results.

[0530] Step 6:

[0531] The terminal sends feedback data to the server. The server receives this feedback and uses it to improve the generated operating procedures. The feedback data is used as information to improve the accuracy of the generated artificial intelligence model. The output is data for model improvement.

[0532] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0533] This invention provides a more personalized user experience on mobile devices by using emotion recognition technology for user support. When a user registers questions about operation or settings via voice or text, the receiving device converts the input into text and sends it to a server.

[0534] Upon receiving user input, the server first uses an emotion engine to analyze the emotions contained in the user's input. This emotion analysis identifies the user's state, for example, "anxious" or "confused." Based on this analysis, the server determines the optimal response method appropriate to the user's emotional state.

[0535] Next, natural language processing techniques are used to analyze the user's question and identify what is being requested. This information is fed into a generative artificial intelligence model, which generates a set of operating procedures that match the user's intent. The generated procedures will reflect considerations that align with the user's emotional state.

[0536] For example, if a user asks in a panicked tone, "The volume suddenly changed, what should I do?", the server recognizes their emotion and generates quick and easy-to-understand instructions. These instructions include specific details such as "where to find the item in the settings menu" and are concisely written to address even panicked situations.

[0537] The generated operating instructions are delivered to the device, which then presents them to the user via voice and screen. The presentation method is also adjusted according to the user's emotions. For example, a confused user will be given a more detailed explanation to reassure them.

[0538] After an operation is performed, the terminal collects feedback from the user reporting the results and sends it to the server. This feedback includes emotion recognition results, which are used to improve future response generation.

[0539] In this way, the present invention can provide appropriate support to users who lack technical knowledge while also being sensitive to their emotions. Furthermore, the system aims to provide more accurate and personalized services through repeated learning.

[0540] The following describes the processing flow.

[0541] Step 1:

[0542] The user enters a problem into their mobile device via voice or text. For example, they might ask, "The screen is too dark, how can I make it brighter?" The device receives this input, converts it to text if it was voice, and sends it to the server.

[0543] Step 2:

[0544] The server passes the received text data to the emotion engine, which analyzes the user's emotions. For example, it might assess that the user is feeling "anxious." This emotion information becomes a factor that influences subsequent procedure generation.

[0545] Step 3:

[0546] The server then uses natural language processing technology to analyze the text data entered by the user. This identifies that the user is requesting "screen brightness adjustment." Based on this analysis, it collects information to resolve the issue.

[0547] Step 4:

[0548] The server uses a generative artificial intelligence model to generate operating procedures that match the user's intentions. The user's emotional state is also considered during procedure generation. For example, a user experiencing anxiety will be given a concise and reassuring procedure.

[0549] Step 5:

[0550] The generated operating procedure is sent from the server to the terminal. Based on this procedure, the terminal provides specific instructions to the user. Here, the terminal presents the procedure in the form of audio and screen display, and adds visual explanations as needed.

[0551] Step 6:

[0552] The user operates the device following the provided instructions. This might involve performing specific actions such as "opening the settings menu, going to display settings, and adjusting the brightness slider."

[0553] Step 7:

[0554] After the operation is complete, the device prompts the user for feedback. The user reports the result, for example, "The screen is brighter. Thank you." This feedback is sent from the device to the server.

[0555] Step 8:

[0556] The server records the emotional information expressed by the user, along with the feedback data received. This data is used as training data to improve the accuracy of future responses.

[0557] Therefore, this system can provide appropriate and personalized support based on the user's emotional state.

[0558] (Example 2)

[0559] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0560] Users of mobile devices sometimes experience difficulty and anxiety when inquiring about operation methods and settings. Especially for users unfamiliar with the device or in urgent situations, prompt and individually considerate responses are necessary. However, conventional technologies have not adequately considered user emotions in their responses or provided optimal operating procedures tailored to those emotions, resulting in a lack of improvement in the user experience.

[0561] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0562] In this invention, the server includes means for analyzing the user's intent using natural language processing technology, means for evaluating the user's emotional state using an emotion analysis engine, and means for generating optimal operating procedures by utilizing a generative artificial intelligence model based on the user's emotional state and intent. This makes it possible to quickly and appropriately provide personalized procedures that reflect the user's emotions.

[0563] 1. An "information processing device" is an electronic device that receives user voice or text input and manages information related to operations and settings.

[0564] 2. A "computational device" is a computer system used for analyzing and processing data, and it plays a role in analyzing the user's intentions and emotional state.

[0565] 3. An "emotion analysis engine" is software or an algorithm that identifies emotional states based on data obtained from users and provides analysis results.

[0566] 4. A "generative artificial intelligence model" is a model that uses artificial intelligence technology to generate information and procedures that meet the user's requirements.

[0567] 5. An "information presentation device" is a device that presents generated operating procedures and information to the user visually or audibly.

[0568] 6. "Feedback" refers to information about the results of actions and emotional states that a user provides through their interaction with the system.

[0569] This invention is a user support system for a mobile information terminal that combines emotion recognition technology and a generative AI model, and is implemented in the following manner.

[0570] First, the user uses a mobile device to input questions or configuration requests via voice or text. The device then uses speech recognition technology (e.g., a common speech recognition API) to convert the voice data into text. This text data is then sent to the server via a secure communication protocol.

[0571] The server analyzes the user's emotions using an emotion analysis engine based on the received text data. The analysis utilizes software employing natural language processing technology to identify the user's emotional state, such as "anxious" or "confused." Subsequently, a generative AI model is used to generate operation procedures that match the user's intentions. This generative AI model provides appropriate procedures based on the user's situation, using prompt text as a basis.

[0572] As a concrete example, consider a scenario where a user enters a question into their device such as, "The volume suddenly changed, what should I do?" After this input is sent to the server, the server, through sentiment analysis, determines that the user is panicking. Based on this result, the generative AI model creates specific instructions for a quick response.

[0573] The generated instructions are sent to the terminal and presented to the user visually or audibly. The terminal can also use speech synthesis technology to provide clear, verbal explanations of the instructions. If necessary, visual instructions can be provided to help the user feel more confident in performing the operation.

[0574] Furthermore, after the user completes an operation, the terminal collects feedback, including the results of the operation, and sends it to the server. This feedback information is used as training data for future response generation, playing a role in improving the accuracy of the system.

[0575] A concrete example of a prompt message is one that expresses the user's specific problem and situation, such as "User: The volume suddenly changed, what should I do?". This allows the generative AI model to generate an answer that aligns with the user's intent and emotions.

[0576] This system makes it possible to quickly provide personalized support that is tailored to the user's emotions.

[0577] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0578] Step 1:

[0579] The user enters questions and setting requests into their mobile device via voice or text.

[0580] The device converts voice input into text using speech recognition software.

[0581] Text data is obtained as the output of this input.

[0582] Step 2:

[0583] The terminal sends the converted text data to the server.

[0584] A secure communication protocol will be used for this transmission.

[0585] The input is text data, and the output is the completion of sending the data to the server.

[0586] Step 3:

[0587] The server performs sentiment analysis using the received text data.

[0588] An emotion analysis engine is used to identify the user's emotions (e.g., anxiety, confusion).

[0589] The input is text data sent to the server, and the output is the analysis results regarding the user's emotional state.

[0590] Step 4:

[0591] The server uses natural language processing techniques to analyze the user's question.

[0592] The data is processed to identify what the user is requesting.

[0593] The input is text data, and the output is the user's specific intent.

[0594] Step 5:

[0595] The server uses a generative AI model to generate operating procedures that match the user's intentions.

[0596] Based on the prompt, the model creates the optimal procedure.

[0597] The input consists of the user's intent and analyzed emotional information, while the output is a set of specific operating procedures.

[0598] Step 6:

[0599] The server sends the generated operating instructions to the terminal.

[0600] The device receives instructions and presents them to the user via voice or screen.

[0601] The input is the operating procedure, and the output is a presentation of the procedure to the user.

[0602] Step 7:

[0603] The user performs the operation according to the provided procedure.

[0604] The device collects the results of the operation.

[0605] The input is the result of the user's actions, and the output is the collected feedback.

[0606] Step 8:

[0607] The device sends the collected feedback to the server.

[0608] The server uses feedback to improve the generated AI model.

[0609] The input is feedback data, and the output is an update to the trained model.

[0610] (Application Example 2)

[0611] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0612] There is a problem in that users cannot quickly obtain appropriate information when using goods or services. Furthermore, presenting information without considering the user's emotional state can damage the user experience. Currently, there is a lack of flexible responses that respond to user emotions.

[0613] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0614] In this invention, the server includes emotion recognition means for performing emotion analysis and acquiring the user's emotional state, information processing means for analyzing the user's intentions using natural language processing technology, and means for adjusting display content that takes the user's emotional state into consideration. This enables the provision of optimal information according to the user's emotions and the presentation of quick and easy-to-understand operating procedures.

[0615] "Device means" refers to a device that receives voice or text input from a user and processes information based on that input.

[0616] An "information processing device" is a device that uses natural language processing technology to analyze the user's intentions and emotions and generate the optimal operating procedure.

[0617] "Emotion recognition means" refers to technologies and devices that analyze and acquire a user's emotional state based on their input.

[0618] A "generative artificial intelligence model" refers to artificial intelligence used to generate operating procedures that respond to the user's intentions and emotions, and to provide appropriate information based on these procedures.

[0619] "Feedback" refers to information collected from users regarding their reactions and opinions on the information they receive and the results of their actions.

[0620] The present invention begins with a device receiving voice or text input from a user and transmitting that data to an information processing device. The information processing device is equipped with a speech recognition API (e.g., Google Speech-to-Text for converting voice data to text) and an emotion analysis engine (e.g., Microsoft Azure Text Analytics for analyzing the user's emotional state), thereby obtaining the user's emotional state.

[0621] Next, a natural language processing engine (e.g., Google Cloud Natural Language) is used to analyze the user's intent. The analyzed information is supplied to a generative artificial intelligence model, which generates the optimal operating procedure for the user. Depending on the user's emotional state, the information processing device adjusts the display content accordingly and presents the information to the user through the device.

[0622] For example, if a user asks about how to use a product in a store, the server recognizes the necessary emotional state from the tone of their voice and generates a quick and gentle explanation. The staff's device then displays specific product usage instructions and related visual information, enabling more personalized customer service.

[0623] In this system, user feedback regarding the results of operations is also important. The device sends the user's reactions and operation results back to the information processing device, thereby improving the accuracy of the generated artificial intelligence model and using it to improve future responses.

[0624] The following are examples of specific prompt messages.

[0625] "The customer is confused. Please gently guide them to the appropriate solution."

[0626] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0627] Step 1:

[0628] The user provides voice or text input through the device. This input is received by the terminal and converted to text using a speech recognition API. The input data is then sent to the server as the base text for processing.

[0629] Step 2:

[0630] The server processes the received text using an emotion analysis engine to determine the user's emotional state. This data processing generates emotion tags from the text content. The output is text with emotion tags.

[0631] Step 3:

[0632] The server's natural language processing engine analyzes the sentiment-tagged text to identify the user's intent. This step involves data calculations to extract the request from the text and gather the information necessary for the action. The analysis results become input to the generative AI model.

[0633] Step 4:

[0634] The generative AI model generates optimal operating procedures based on the user's intentions and emotional state. Here, the generated operating procedures are output in a clear format while taking emotions into consideration.

[0635] Step 5:

[0636] The device presents the generated operating procedures to the user. The format of the screen display and audio guidance is adjusted according to the user's emotional state. The user is provided with visual explanations and audio information to support a high level of comprehension.

[0637] Step 6:

[0638] The user inputs their operation results into the device as feedback. This feedback, along with the emotion recognition results, is sent to the server and collected as strategy information.

[0639] Step 7:

[0640] The server uses feedback to update the generated AI model, improving the accuracy of subsequent user interactions. This step involves performing data calculations to adjust the parameters of the generated artificial intelligence model based on the feedback information.

[0641] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0642] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0643] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0644] [Fourth Embodiment]

[0645] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0646] As shown in Figure 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.

[0647] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0648] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0649] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0650] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0651] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0652] The controlled 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0653] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0654] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0655] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0656] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0657] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0658] This invention begins with a user asking a question about operation or settings via a mobile device. For example, the user might ask the device, "How do I change the volume settings?" The device uses its voice input function to convert the user's question into text data and sends this data to the server.

[0659] The server uses natural language processing techniques to analyze the user's intent from the received text data. For example, from the user's question, the server identifies that the user wants to understand the procedure for adjusting the volume. Next, based on this analysis, the data is input into a generative artificial intelligence model to generate the optimal procedure. This procedure includes specific details such as "open the settings menu, select sound settings, and adjust the volume."

[0660] The generated operating procedure is sent back to the terminal. The terminal then presents this procedure to the user. Possible presentation methods include voice guidance using a voice assistant, or displaying it on the screen in the form of text or images. This allows the user to perform the necessary operations on the terminal by following the presented instructions.

[0661] Furthermore, after the user has finished performing this operation, the device can request feedback from the user to confirm the result. If the user reports that they were able to successfully change the volume settings, the device sends this result to the server. The server collects this feedback and uses it to improve the accuracy of the generative artificial intelligence model for future inquiries.

[0662] In this way, the system of the present invention provides accurate and personalized support so that even users without technical knowledge can easily operate their mobile information terminals. The system's flexibility and customization options to suit the user's terminal make it possible to provide operation guides tailored to various situations.

[0663] The following describes the processing flow.

[0664] Step 1:

[0665] The user inputs a question by voice into a mobile device. The device receives this voice and converts it into text data using speech recognition technology. The text data is then sent to the server. At this time, the user's inquiry is clearly transcribed into text.

[0666] Step 2:

[0667] The server analyzes the received text data using natural language processing techniques. Based on the analysis, it identifies the user's intent, for example, determining that they intend to change the volume setting. Based on this, it prepares data for creating specific operating instructions.

[0668] Step 3:

[0669] The server uses a generative artificial intelligence model to generate the optimal procedure that corresponds to the user's intent. This procedure is customized to take into account the operating system version of the user's terminal. The generated procedure includes step-by-step, specific instructions.

[0670] Step 4:

[0671] The generated operating procedures are sent from the server to the terminal. The terminal then presents the received procedures to the user. Possible presentation methods include audio guidance, text display, or diagrammatic explanations.

[0672] Step 5:

[0673] The user follows the instructions on the device and changes the device settings according to the operating procedure. For example, they open the device's settings menu, select the appropriate option, and change the volume settings.

[0674] Step 6:

[0675] After the operation is complete, the device will ask the user for feedback to confirm the results and whether the operation was successful. This feedback is expected to be entered via voice or text.

[0676] Step 7:

[0677] After the device receives feedback from the user, it sends the feedback information to the server. The server aggregates this information and uses it as data to improve the accuracy of the generated artificial intelligence model.

[0678] In this way, the system provides continuous and efficient support to the user. The seamless coordination of each step enhances the user experience and ensures smooth operation.

[0679] (Example 1)

[0680] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0681] Modern information terminals are highly functional, making it often difficult for the average user to easily operate all of their functions. This necessitates users constantly checking specific operating procedures and settings, leading to decreased operational efficiency. Furthermore, there is a need for systems that can provide precise operational assistance tailored to individual user needs. Additionally, a lack of mechanisms to utilize user feedback to continuously improve system accuracy and usability is another challenge.

[0682] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0683] In this invention, the server includes means for analyzing the user's intent using natural language processing technology and identifying related actions; means for generating the optimal operating procedure for the user using a generative artificial intelligence model and outputting that procedure as specific instructions; and means for analyzing the acquired feedback and using it to improve the accuracy of the generative artificial intelligence model. As a result, the user can easily obtain operating procedures based on their own intent, and the accuracy of the system can continuously improve through feedback.

[0684] A "terminal device" is an information processing device equipped with the function of receiving voice or text input from a user and converting it into digital data.

[0685] A "server system" is an information processing system that operates on a network, analyzes data sent by users, and generates optimal operating procedures using a generated artificial intelligence model.

[0686] "Natural language processing technology" is an information processing technology that analyzes voice or text input from users to understand their intentions and purposes.

[0687] A "generative artificial intelligence model" is a model based on machine learning and artificial intelligence technologies that is used to generate the optimal operating procedures for a user.

[0688] "Feedback" refers to data sent to a server regarding the results of user actions, which is used to improve the system.

[0689] "Customization" refers to the process of individually adjusting the generated operating procedures based on the user's information processing device's operating system version and individual needs.

[0690] "Visual representation" refers to supplementary information, including visual explanations and icons, that accompany the operating procedures presented to the user.

[0691] This invention provides a system that allows users to easily obtain operating procedures using an information processing terminal. The user inputs questions regarding the operation into the information processing terminal in either voice or text format. In the case of voice input, the terminal uses speech recognition software to convert this voice into text. General speech recognition technologies can be applied to this process.

[0692] The terminal sends the converted text data to the server. The server analyzes the received text data using natural language processing techniques. During the analysis, the context and structure of the text are examined to clearly understand the user's intent and purpose. For example, natural language processing libraries can be used for this technique.

[0693] Based on the analysis results, the server generates the optimal operating procedure using a generative artificial intelligence model. This model is trained using machine learning techniques and is capable of constructing appropriate procedures in response to user questions. Specifically, as a generative AI model, it utilizes, for example, a large-scale language model to understand user questions and generate appropriate prompts accordingly. An example of a prompt sentence is, "How do I change the volume settings?"

[0694] The generated operating instructions are transmitted to the terminal via a communication network. The terminal then provides the operating instructions to the user. Presentation methods include voice guidance from a voice assistant and the display of text and visual icons on the screen. This allows the user to intuitively understand the instructions and perform the terminal operations.

[0695] Furthermore, user feedback is sent from the device to the server. The server analyzes this feedback and uses it to improve the generated AI model. This allows the system to improve its accuracy over time, enabling it to better meet user needs.

[0696] This system allows users to operate their devices more easily and obtain a better user experience. This enables even tech-inexperienced users to perform necessary operations quickly and accurately.

[0697] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0698] Step 1:

[0699] The user inputs a question into the information processing terminal in either voice or text format. Examples of input include specific operational requests such as changing volume settings. The input voice is converted into text data using the terminal's speech recognition technology. The voice data is sent to the speech recognition engine and output as text data.

[0700] Step 2:

[0701] The terminal sends the converted text data to the server over the network. Specifically, the terminal's communication function generates data packets and uses network protocols to forward them to the specified server's IP address. Upon receiving the text data, the server can proceed to the next processing step.

[0702] Step 3:

[0703] The server analyzes the received text data using natural language processing (NLP) techniques. At this stage, the NLP engine performs syntactic analysis of the text to determine the user's intent and extract important keywords and phrases. The input is the text data before analysis, and the output is tagged data indicating the user's intent.

[0704] Step 4:

[0705] The server inputs data into a generative artificial intelligence model based on the analysis results and generates the optimal operating procedure. In this process, prompt sentences are input into the generative AI model, and specific steps for the user corresponding to those sentences are output. A list of procedures is generated, calculated based on the appropriate parameters of the model. The input is the analyzed intent data, and the output is a step-by-step explanation of the procedure.

[0706] Step 5:

[0707] The generated operating procedure is sent from the server to the terminal. The server's communication module packets the data and sends it to the terminal over the network. The terminal decodes the received procedure data and prepares it to be provided to the user.

[0708] Step 6:

[0709] The terminal presents the received instructions to the user. Specifically, this is done through voice guidance and visual representations using text and icons on the display. A speech synthesis engine generates and outputs the voice guidance to the user. Text data is sent to the display module and displayed visually on the screen.

[0710] Step 7:

[0711] After the user performs the suggested operation, the terminal requests feedback from the user based on the result of the operation. The user's response to this prompt is obtained by the terminal via the input device. The feedback data is then sent to the server.

[0712] Step 8:

[0713] The server receives feedback sent from the terminal, analyzes it, and uses it to improve the generated AI model. In this process, the database is updated based on the insights gained from the feedback to evaluate the model's performance and improve the accuracy of prompt generation in the future. Based on the statistics of the feedback data, a trigger for model retraining is output.

[0714] (Application Example 1)

[0715] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0716] Online trading via communication devices is complex for users, especially those unfamiliar with the technology. Therefore, support is needed to enable users to perform transactions quickly and accurately. Furthermore, to improve the user experience, customized guides tailored to the characteristics of individual communication devices are required.

[0717] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0718] In this invention, the server includes an information processing device that analyzes the user's intent using natural language processing technology, an information processing device that generates optimal operating procedures for the user using a generative artificial intelligence model, and a communication device that distributes the generated operating procedures to a communication device and presents them to the user. This allows the user to quickly understand how to operate online transactions and execute various operating procedures. Furthermore, individualized support based on the operating system version of each user's communication device is possible, further improving the user experience.

[0719] "Communication device means" refers to a device equipped with the function of receiving voice or text input from a user and transmitting it to a server.

[0720] An "information processing device" is a device that analyzes received information and utilizes natural language processing technology to understand the user's intent.

[0721] A "generative artificial intelligence model" refers to artificial intelligence technology that has the ability to automatically generate the optimal operating procedures for the user.

[0722] "Operating instructions" refer to information that outlines the steps necessary for a user to achieve a desired action.

[0723] An "online trading platform" is a system that provides a place for users to buy or sell goods and services via the internet.

[0724] This invention is a system that enables users to easily perform operations related to online transactions using a communication device. The server uses natural language processing technology to analyze the intent of questions and requests received from the user. This allows the server to accurately understand the user's intent and generate the optimal operation procedure based on that intent using an artificial intelligence model.

[0725] The communication device is equipped with a voice recognition function, which converts the user's voice input into text data. This text data is sent to a server, which uses an information processing device to perform analysis. The analysis results are input into a generative artificial intelligence model, which generates operating procedures for the online trading platform. The generated operating procedures are delivered to the communication device and presented to the user in visual or audio format. This allows the user to easily perform trading operations.

[0726] For example, if a user asks a voice question like, "I want to know how to buy items that are on sale," the system will immediately provide instructions on how to view a list of relevant products and the specific steps involved in the purchase process. This allows the user to complete the transaction quickly.

[0727] A concrete example of a prompt used in a generative artificial intelligence model is: "When a user says 'Tell me how to apply the coupon,' generate the latest coupon guide and application instructions. The instructions should be written concisely and explained in a way that even a beginner can understand." This example takes user convenience into maximum consideration when generating prompts and presenting operating procedures.

[0728] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0729] Step 1:

[0730] The device receives the user's voice input. The input voice data is converted into text data by the device's voice recognition software. Specifically, the microphone captures the voice, and that data is passed to the voice recognition engine. The output is the converted text data.

[0731] Step 2:

[0732] The terminal sends the generated text data to the server. The server receives this text data as input and uses a natural language processing engine to analyze the user's intent. Through analysis, the content of the text is converted into information that helps understand the steps to be taken. The output is data containing the analysis results.

[0733] Step 3:

[0734] The server executes a generative artificial intelligence model based on the analysis results to generate the optimal operating procedure for the user. The generative AI model receives the analysis results as prompts and devises appropriate steps. Specifically, a detailed guide for the user to operate the online trading platform is generated. The output is the generated operating procedure.

[0735] Step 4:

[0736] The server sends the generated operating instructions to the terminal. The terminal receives these instructions and presents them to the user. The terminal can choose to display the instructions visually on the user's screen or provide voice guidance using a voice assistant. The output is the information presented to the user.

[0737] Step 5:

[0738] The user performs the operation according to the instructions provided. The terminal records the user's actions and collects them as feedback. Specifically, it checks the actions the user actually performed on the terminal and compiles them as feedback data. The output is feedback data regarding the operation results.

[0739] Step 6:

[0740] The terminal sends feedback data to the server. The server receives this feedback and uses it to improve the generated operating procedures. The feedback data is used as information to improve the accuracy of the generated artificial intelligence model. The output is data for model improvement.

[0741] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0742] This invention provides a more personalized user experience on mobile devices by using emotion recognition technology for user support. When a user registers questions about operation or settings via voice or text, the receiving device converts the input into text and sends it to a server.

[0743] Upon receiving user input, the server first uses an emotion engine to analyze the emotions contained in the user's input. This emotion analysis identifies the user's state, for example, "anxious" or "confused." Based on this analysis, the server determines the optimal response method appropriate to the user's emotional state.

[0744] Next, natural language processing techniques are used to analyze the user's question and identify what is being requested. This information is fed into a generative artificial intelligence model, which generates a set of operating procedures that match the user's intent. The generated procedures will reflect considerations that align with the user's emotional state.

[0745] For example, if a user asks in a panicked tone, "The volume suddenly changed, what should I do?", the server recognizes their emotion and generates quick and easy-to-understand instructions. These instructions include specific details such as "where to find the item in the settings menu" and are concisely written to address even panicked situations.

[0746] The generated operating instructions are delivered to the device, which then presents them to the user via voice and screen. The presentation method is also adjusted according to the user's emotions. For example, a confused user will be given a more detailed explanation to reassure them.

[0747] After an operation is performed, the terminal collects feedback from the user reporting the results and sends it to the server. This feedback includes emotion recognition results, which are used to improve future response generation.

[0748] In this way, the present invention can provide appropriate support to users who lack technical knowledge while also being sensitive to their emotions. Furthermore, the system aims to provide more accurate and personalized services through repeated learning.

[0749] The following describes the processing flow.

[0750] Step 1:

[0751] The user enters a problem into their mobile device via voice or text. For example, they might ask, "The screen is too dark, how can I make it brighter?" The device receives this input, converts it to text if it was voice, and sends it to the server.

[0752] Step 2:

[0753] The server passes the received text data to the emotion engine, which analyzes the user's emotions. For example, it might assess that the user is feeling "anxious." This emotion information becomes a factor that influences subsequent procedure generation.

[0754] Step 3:

[0755] The server then uses natural language processing technology to analyze the text data entered by the user. This identifies that the user is requesting "screen brightness adjustment." Based on this analysis, it collects information to resolve the issue.

[0756] Step 4:

[0757] The server uses a generative artificial intelligence model to generate operating procedures that match the user's intentions. The user's emotional state is also considered during procedure generation. For example, a user experiencing anxiety will be given a concise and reassuring procedure.

[0758] Step 5:

[0759] The generated operating procedure is sent from the server to the terminal. Based on this procedure, the terminal provides specific instructions to the user. Here, the terminal presents the procedure in the form of audio and screen display, and adds visual explanations as needed.

[0760] Step 6:

[0761] The user operates the device following the provided instructions. This involves performing specific actions such as "opening the settings menu, going to display settings, and adjusting the brightness slider."

[0762] Step 7:

[0763] After the operation is complete, the device prompts the user for feedback. The user reports the result, for example, "The screen is brighter. Thank you." This feedback is sent from the device to the server.

[0764] Step 8:

[0765] The server records the emotional information expressed by the user, along with the feedback data received. This data is used as training data to improve the accuracy of future responses.

[0766] Therefore, this system can provide appropriate and personalized support based on the user's emotional state.

[0767] (Example 2)

[0768] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0769] Users of mobile devices sometimes experience difficulty and anxiety when inquiring about operation methods and settings. Especially for users unfamiliar with the device or in urgent situations, prompt and individually considerate responses are necessary. However, conventional technologies have not adequately considered user emotions or provided optimal operating procedures tailored to those emotions, resulting in a lack of improvement in the user experience.

[0770] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0771] In this invention, the server includes means for analyzing the user's intent using natural language processing technology, means for evaluating the user's emotional state using an emotion analysis engine, and means for generating optimal operating procedures by utilizing a generative artificial intelligence model based on the user's emotional state and intent. This makes it possible to quickly and appropriately provide personalized procedures that reflect the user's emotions.

[0772] 1. An "information processing device" is an electronic device that receives user voice or text input and manages information related to operations and settings.

[0773] 2. A "computational device" is a computer system used for analyzing and processing data, and it plays a role in analyzing the user's intentions and emotional state.

[0774] 3. An "emotion analysis engine" is software or an algorithm that identifies emotional states based on data obtained from users and provides analysis results.

[0775] 4. A "generative artificial intelligence model" is a model that uses artificial intelligence technology to generate information and procedures that meet the user's requirements.

[0776] 5. An "information presentation device" is a device that presents generated operating procedures and information to the user visually or audibly.

[0777] 6. "Feedback" refers to information about the results of actions and emotional states that a user provides through their interaction with the system.

[0778] This invention is a user support system for a mobile information terminal that combines emotion recognition technology and a generative AI model, and is implemented in the following manner.

[0779] First, the user uses a mobile device to input questions or configuration requests via voice or text. The device then uses speech recognition technology (e.g., a common speech recognition API) to convert the voice data into text. This text data is then sent to the server via a secure communication protocol.

[0780] The server analyzes the user's emotions using an emotion analysis engine based on the received text data. The analysis utilizes software employing natural language processing technology to identify the user's emotional state, such as "anxious" or "confused." Subsequently, a generative AI model is used to generate operation procedures that match the user's intentions. This generative AI model provides appropriate procedures based on the user's situation, using prompt text as a basis.

[0781] As a concrete example, consider a scenario where a user enters a question into their device such as, "The volume suddenly changed, what should I do?" After this input is sent to the server, the server, through sentiment analysis, determines that the user is panicking. Based on this result, the generative AI model creates specific instructions for a quick response.

[0782] The generated instructions are sent to the terminal and presented to the user visually or audibly. The terminal can also use speech synthesis technology to provide clear, verbal explanations of the instructions. If necessary, visual instructions can be provided to help the user feel more confident in performing the operation.

[0783] Furthermore, after the user completes an operation, the terminal collects feedback, including the results of the operation, and sends it to the server. This feedback information is used as training data for future response generation, playing a role in improving the accuracy of the system.

[0784] A concrete example of a prompt message is one that expresses the user's specific problem and situation, such as "User: The volume suddenly changed, what should I do?". This allows the generative AI model to generate an answer that aligns with the user's intent and emotions.

[0785] This system makes it possible to quickly provide personalized support that is tailored to the user's emotions.

[0786] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0787] Step 1:

[0788] The user enters questions and setting requests into their mobile device via voice or text.

[0789] The device converts voice input into text using speech recognition software.

[0790] Text data is obtained as the output of this input.

[0791] Step 2:

[0792] The terminal sends the converted text data to the server.

[0793] A secure communication protocol will be used for this transmission.

[0794] The input is text data, and the output is the completion of sending the data to the server.

[0795] Step 3:

[0796] The server performs sentiment analysis using the received text data.

[0797] An emotion analysis engine is used to identify the user's emotions (e.g., anxiety, confusion).

[0798] The input is text data sent to the server, and the output is the analysis results regarding the user's emotional state.

[0799] Step 4:

[0800] The server uses natural language processing techniques to analyze the user's question.

[0801] The data is processed to identify what the user is requesting.

[0802] The input is text data, and the output is the user's specific intent.

[0803] Step 5:

[0804] The server uses a generative AI model to generate operating procedures that match the user's intentions.

[0805] Based on the prompt, the model creates the optimal procedure.

[0806] The input consists of the user's intent and analyzed emotional information, while the output is a set of specific operating procedures.

[0807] Step 6:

[0808] The server sends the generated operating instructions to the terminal.

[0809] The device receives instructions and presents them to the user via voice or screen.

[0810] The input is the operating procedure, and the output is a presentation of the procedure to the user.

[0811] Step 7:

[0812] The user performs the operation according to the provided procedure.

[0813] The device collects the results of the operation.

[0814] The input is the result of the user's actions, and the output is the collected feedback.

[0815] Step 8:

[0816] The device sends the collected feedback to the server.

[0817] The server uses feedback to improve the generated AI model.

[0818] The input is feedback data, and the output is an update to the trained model.

[0819] (Application Example 2)

[0820] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0821] There is a problem in that users cannot quickly obtain appropriate information when using goods or services. Furthermore, presenting information without considering the user's emotional state can damage the user experience. Currently, there is a lack of flexible responses that respond to user emotions.

[0822] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0823] In this invention, the server includes emotion recognition means for performing emotion analysis and acquiring the user's emotional state, information processing means for analyzing the user's intentions using natural language processing technology, and means for adjusting display content that takes the user's emotional state into consideration. This enables the provision of optimal information according to the user's emotions and the presentation of quick and easy-to-understand operating procedures.

[0824] "Device means" refers to a device that receives voice or text input from a user and processes information based on that input.

[0825] An "information processing device" is a device that uses natural language processing technology to analyze the user's intentions and emotions and generate the optimal operating procedure.

[0826] "Emotion recognition means" refers to technologies and devices that analyze and acquire a user's emotional state based on their input.

[0827] A "generative artificial intelligence model" refers to artificial intelligence used to generate operating procedures that respond to the user's intentions and emotions, and to provide appropriate information based on these procedures.

[0828] "Feedback" refers to information collected from users regarding their reactions and opinions on the information they receive and the results of their actions.

[0829] The present invention begins with a device receiving voice or text input from a user and transmitting that data to an information processing device. The information processing device is equipped with a speech recognition API (e.g., Google Speech-to-Text for converting voice data to text) and an emotion analysis engine (e.g., Microsoft Azure Text Analytics for analyzing the user's emotional state), thereby obtaining the user's emotional state.

[0830] Next, a natural language processing engine (e.g., Google Cloud Natural Language) is used to analyze the user's intent. The analyzed information is supplied to a generative artificial intelligence model, which generates the optimal operating procedure for the user. Depending on the user's emotional state, the information processing device adjusts the display content accordingly and presents the information to the user through the device.

[0831] For example, if a user asks about how to use a product in a store, the server recognizes the necessary emotional state from the tone of their voice and generates a quick and gentle explanation. The staff's device then displays specific product usage instructions and related visual information, enabling more personalized customer service.

[0832] In this system, user feedback regarding the results of operations is also important. The device sends the user's reactions and operation results back to the information processing device, thereby improving the accuracy of the generated artificial intelligence model and using it to improve future responses.

[0833] The following are examples of specific prompt messages.

[0834] "The customer is confused. Please gently guide them to the appropriate solution."

[0835] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0836] Step 1:

[0837] The user provides voice or text input through the device. This input is received by the terminal and converted to text using a speech recognition API. The input data is then sent to the server as the base text for processing.

[0838] Step 2:

[0839] The server processes the received text using an emotion analysis engine to determine the user's emotional state. This data processing generates emotion tags from the text content. The output is text with emotion tags.

[0840] Step 3:

[0841] The server's natural language processing engine analyzes the sentiment-tagged text to identify the user's intent. This step involves data calculations to extract the request from the text and gather the information necessary for the action. The analysis results become input to the generative AI model.

[0842] Step 4:

[0843] The generative AI model generates optimal operating procedures based on the user's intentions and emotional state. Here, the generated operating procedures are output in a clear format while taking emotions into consideration.

[0844] Step 5:

[0845] The device presents the generated operating procedures to the user. The format of the screen display and audio guidance is adjusted according to the user's emotional state. The user is provided with visual explanations and audio information to support a high level of comprehension.

[0846] Step 6:

[0847] The user inputs their operation results into the device as feedback. This feedback, along with the emotion recognition results, is sent to the server and collected as strategy information.

[0848] Step 7:

[0849] The server uses feedback to update the generated AI model, improving the accuracy of subsequent user interactions. This step involves performing data calculations to adjust the parameters of the generated artificial intelligence model based on the feedback information.

[0850] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0851] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0852] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0853] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0854] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0855] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0856] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0857] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0858] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0859] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0860] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0861] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0862] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0863] 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.

[0864] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0865] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0866] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0867] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0868] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0869] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0870] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0871] The following is further disclosed regarding the embodiments described above.

[0872] (Claim 1)

[0873] A terminal means for receiving voice or text input from a user,

[0874] A server that analyzes user intent using natural language processing technology,

[0875] A server means that generates the optimal operating procedure for the user using a generative artificial intelligence model,

[0876] A terminal device that distributes and presents the generated operating procedures to the user,

[0877] A terminal means for obtaining user feedback on the results of operations,

[0878] A server means that sends acquired feedback to the server to improve the generated artificial intelligence model,

[0879] A system that includes this.

[0880] (Claim 2)

[0881] The system according to claim 1, comprising server means for individually customizing the generated operating procedures based on the operating system version of the user's terminal.

[0882] (Claim 3)

[0883] The system according to claim 1, further comprising terminal means for delivering information including visual explanations in conjunction with the operating procedures presented to the user.

[0884] "Example 1"

[0885] (Claim 1)

[0886] A terminal means that receives voice or text input from a user and converts that input into digital data,

[0887] A server means that analyzes user intent using natural language processing technology and identifies related actions,

[0888] A server that uses a generative artificial intelligence model to generate the optimal operating procedure for the user and outputs that procedure as specific instructions,

[0889] A terminal means that distributes the generated operating procedure to the terminal via a communication network and presents it to the user through voice or visual display,

[0890] A terminal means that obtains feedback from the user regarding the results of the operation and sends that feedback to a server,

[0891] A server that analyzes the acquired feedback and uses it to improve the accuracy of the generated artificial intelligence model,

[0892] A system that includes this.

[0893] (Claim 2)

[0894] The system according to claim 1, comprising a server means for individually customizing generated operating procedures based on the operating system version of the user's information processing device and transmitting the customization results to a terminal.

[0895] (Claim 3)

[0896] The system according to claim 1, comprising terminal means for distributing auxiliary information, including visual representations and icons, in conjunction with the operating procedures presented to the user.

[0897] "Application Example 1"

[0898] (Claim 1)

[0899] A communication device means for receiving voice or text input from a user,

[0900] Information processing device means for analyzing user intent using natural language processing technology,

[0901] Information processing device means that generates the optimal operating procedure for the user using a generative artificial intelligence model,

[0902] A communication device means that distributes the operating procedures generated by the communication device and presents them to the user,

[0903] A communication device means for obtaining feedback from the user regarding the results of operations,

[0904] Information processing device means for transmitting acquired feedback to an information processing device to improve the generated artificial intelligence model,

[0905] A communication device means that provides procedures for operating an online trading platform based on questions from users,

[0906] A system that includes this.

[0907] (Claim 2)

[0908] The system according to claim 1, comprising information processing means for individually customizing generated operating procedures based on the operating system version of the user's communication device.

[0909] (Claim 3)

[0910] The system according to claim 1, further comprising a communication device means for delivering information including visual explanations in conjunction with the operating procedures presented to the user.

[0911] "Example 2 of combining an emotion engine"

[0912] (Claim 1)

[0913] An information processing device that receives voice or text input from a user,

[0914] A computing device that analyzes user intent using natural language processing technology,

[0915] A computing device that evaluates the user's emotional state using an emotion analysis engine,

[0916] A computing device that generates optimal operating procedures by utilizing an artificial intelligence model based on the user's emotional state and intentions,

[0917] An information display device that distributes the generated operating procedures to an information processing device and presents them to the user,

[0918] An information display device that customizes the operating procedure in a format suitable for the user's emotional state,

[0919] An information processing device that acquires feedback regarding the user's operation results,

[0920] A computing device that transmits acquired feedback to another computing device to improve the generated artificial intelligence model,

[0921] A system that includes this.

[0922] (Claim 2)

[0923] The system according to claim 1, comprising a computing device that individually customizes the generated operating procedures based on the program execution environment in the user's information processing device.

[0924] (Claim 3)

[0925] The system according to claim 1, comprising an information display device that delivers visual information accompanying the operating procedures presented to the user.

[0926] "Application example 2 when combining with an emotional engine"

[0927] (Claim 1)

[0928] A device means for receiving voice or text input from a user,

[0929] An information processing device that analyzes user intent using natural language processing technology,

[0930] An emotion recognition means that performs emotion analysis to obtain the user's emotional state,

[0931] Information processing device means that generates the optimal operating procedure for the user using a generative artificial intelligence model,

[0932] A device that distributes and presents to the user the operating procedures generated on the terminal,

[0933] A means of adjusting the displayed content to be considerate based on the user's emotional state,

[0934] A device means for obtaining feedback from the user regarding the results of operations,

[0935] Information processing device means for transmitting acquired feedback to an information processing device to improve the generated artificial intelligence model,

[0936] A system that includes this.

[0937] (Claim 2)

[0938] The system according to claim 1, comprising information processing means for individually customizing generated operating procedures based on the type of operating system of the user's device.

[0939] (Claim 3)

[0940] The system according to claim 1, comprising a device means for delivering information including visual explanations in conjunction with the operating procedures presented to the user, and making adjustments according to the user's emotional state. [Explanation of Symbols]

[0941] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A terminal means for receiving voice or text input from a user, A server that analyzes user intent using natural language processing technology, A server means that generates the optimal operating procedure for the user using a generative artificial intelligence model, A terminal device that distributes and presents the generated operating procedures to the user, A terminal means for obtaining user feedback on the results of operations, A server means that sends acquired feedback to the server to improve the generated artificial intelligence model, A system that includes this.

2. The system according to claim 1, further comprising server means for individually customizing the generated operating procedures based on the operating system version of the user's terminal.

3. The system according to claim 1, further comprising terminal means for delivering information including visual explanations in conjunction with the operating procedures presented to the user.

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