system

Abstract

We provide the system. [Solution] A means of inputting user personality information, A means for generating a user-specific avatar based on the aforementioned personality information, Methods for gathering information from knowledge bases on the internet, The means by which the aforementioned avatar generates customized suggestions and responses for the user, Means of presenting collected information to the user, 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, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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] A system that automatically provides information tailored to the personality and thinking patterns of individual users is an important factor in enhancing customer satisfaction in modern times. However, existing information systems have difficulty making proposals that fully consider the individuality of users and tend to remain at general information provision. In addition, there is a problem that it is difficult to provide specific and specialized advice because they do not have knowledge specialized for various industries. It is required to improve such a situation and realize personalized high-quality information provision to users.

Means for Solving the Problems

[0005] This invention solves the aforementioned problems by providing a system that generates individually tailored avatars based on user personality information and collects appropriate information from a broad knowledge base on the internet. This system utilizes the personality data entered by the user to generate suggestions and answers optimized for each user's needs through a personalized avatar. Furthermore, by using industry-specific information sources, it provides expert information in each field, thereby offering beneficial support to the user. This system also allows for the incorporation of user feedback to improve the accuracy of the avatars, enabling continuous improvement.

[0006] "User personality information" refers to data that indicates a user's personality traits and thinking patterns.

[0007] An "avatar" is a virtual proxy character customized based on the user's personality and characteristics.

[0008] An "online knowledge base" is a collection of databases consisting of various information sources that are accessible online.

[0009] "Means of information gathering" refers to the process of obtaining and organizing relevant information from knowledge bases on the internet.

[0010] "Means for generating suggestions and responses" refers to a function that combines collected information with user personality information to create responses that are appropriate for the user.

[0011] "Means of presenting to the user" refers to a system that displays the generated suggestions and answers in a format that is easy for the user to understand.

[0012] "Industry-specific information" refers to specialized knowledge and data specific to a particular industry or field.

[0013] "Feedback" refers to the opinions and evaluations that users give back to the information or services provided. [Brief explanation of the drawing]

[0014] [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]

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a labeled 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.

[0018] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a labeled 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, and the like.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention is a system that generates individually customized AI avatars based on the user's personality information and provides information optimized for the user. It is intended for corporate and individual users and can be used for business support, personal life planning, and learning support.

[0036] Overall flow

[0037] The user first inputs their personality assessment results and self-analysis results into an interface using their device, and this data is sent to the server. The server analyzes the received personality data and generates a user-specific avatar. This avatar has a conversational style and response logic that mimics the user's personality and behavioral patterns.

[0038] The server accesses a vast database on the internet and, for corporate clients, utilizes industry-specific information sources to collect information highly relevant to the user. Furthermore, based on this information, the avatar generates specific suggestions and solutions for the user and presents them to the user via the terminal. In this process, natural language generation technology is used to ensure that the information is presented in a way that is easy for the user to understand.

[0039] Specific example

[0040] For example, consider a scenario where a project manager at a company is facing challenges in managing a new project. The user explains the situation to an avatar on their device, and the server searches and collects industry trends and best practices for project management. The avatar then proposes strategies based on successful case studies of similar situations, listing the options and displaying them on the device. The user can then use this information to select a new approach.

[0041] Furthermore, if an individual user is considering their career path, the avatar will suggest occupational information and skill development methods that are suitable for the user's characteristics. This helps users to build their life plans more concretely.

[0042] The flexibility of this system is further enhanced by user feedback. The server continuously improves the avatars by collecting user responses. This feedback loop allows the system to provide more accurate information over time.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user accesses the device and enters their personality assessment results and personality information. The device receives this information and sends it to the server.

[0046] Step 2:

[0047] The server passes the received user personality information to the analysis engine, which then analyzes the data. This process extracts the user's personality traits and infers their behavioral patterns.

[0048] Step 3:

[0049] The server generates a user-specific AI avatar based on the analyzed data. This avatar features a conversational style and response logic tailored to the user's characteristics.

[0050] Step 4:

[0051] The server accesses the internet and industry-specific databases to collect necessary information, including the latest information and trends relevant to user needs.

[0052] Step 5:

[0053] The server integrates collected information with the user's personality data to enable the avatar to generate suggestions and responses tailored to the user. Natural language generation technology is used to ensure the responses are clear and easy to understand.

[0054] Step 6:

[0055] The server sends the generated suggestions and responses to the terminal. The terminal displays the received information on its user interface, presenting it to the user in a visually easy-to-understand manner.

[0056] Step 7:

[0057] The user makes a decision based on the displayed information and enters feedback into the device as needed. The device then sends this feedback to the server.

[0058] Step 8:

[0059] The server utilizes user feedback to improve the response accuracy of the AI ​​avatar. This will make future information delivery even more user-friendly.

[0060] (Example 1)

[0061] 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."

[0062] Conventional information provision systems have challenges in providing optimal information tailored to the individual needs and characteristics of users, and in not having a sufficient feedback loop to determine whether the information provided is beneficial to the user.

[0063] 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.

[0064] In this invention, the server includes a device for inputting user characteristic information, a device for generating a user-specific virtual agent based on the characteristic information, and a device for retrieving information from a database on a communication network. This makes it possible to dynamically provide information tailored to the user and to continuously improve the system based on feedback.

[0065] "User characteristic information" refers to data about individual characteristics of users, including their personality, preferences, and behavioral patterns.

[0066] A "virtual agent" is a digital character generated based on a user's characteristic information, possessing a conversational style and response logic specific to that user.

[0067] A "database on a communication network" is a digital storage system that stores diverse information and is accessible via the internet.

[0068] An "information retrieval device" is a system component that has the function of searching for and acquiring necessary information via a communication network.

[0069] "User response" refers to the actions and feedback that users show in response to information provided by the virtual agent.

[0070] A "device for evolution" is a system component that has the function of improving the virtual agent based on user feedback and enhancing its capabilities.

[0071] "Natural language form" refers to a form of expression based on human language that users can intuitively understand.

[0072] Embodiments of this invention will now be described. This system generates individually customized virtual agents based on the user's characteristic information and provides the user with information optimized for them. The user inputs characteristic information and self-analysis results using a terminal. This input is securely transmitted to the server through a data collection device.

[0073] The server analyzes the received characteristic information. This analysis utilizes natural language processing libraries and machine learning algorithms. Furthermore, based on the analysis results, the server generates a user-specific virtual agent. This agent possesses a conversational style that reflects the user's personality and behavioral patterns.

[0074] In information gathering, servers access databases and external APIs on the internet to retrieve highly relevant information. By utilizing scraping techniques and external APIs, new data and information tailored to user needs can be efficiently acquired. For corporate users, more specialized information is provided using specific industry information sources.

[0075] The virtual agent generates personalized suggestions for the user based on the collected information. Using natural language generation technology, complex information is transformed into a concise and easy-to-understand format, which is then displayed on the terminal screen. Users also provide feedback on the suggestions and information from the avatar, and the server continuously improves the virtual agent's performance based on this feedback.

[0076] As a concrete example, if a project manager at a company encounters a problem with a new project, they can explain the situation to a virtual agent via a terminal. The server then gathers information on project management best practices and market trends, and generates a solution strategy based on similar success stories. This makes it possible to list useful options for project progress and provide them to the project manager.

[0077] Furthermore, for individual users struggling with their career paths, a virtual agent provides personalized job information and skill development suggestions. This system can provide users with necessary advice by prompting them with phrases such as, "Please provide solutions to my project management problems," or "Please suggest a career path that suits me." Using such prompts allows users to utilize the system more intuitively.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] Users input characteristic information via their device. Specifically, they input personality assessment results and self-analysis results into an interface on the device. This input data is securely transmitted to the server. The input data can take various forms, including text data and multiple-choice options.

[0081] Step 2:

[0082] The server receives the input trait information and analyzes it using natural language processing algorithms. This analysis involves data processing such as text sentiment analysis and feature extraction to identify the user's personality and behavioral patterns. As a result of this analysis, the trait information is extracted in a more detailed data format.

[0083] Step 3:

[0084] The server uses the analysis results to generate a user-specific virtual agent. Utilizing a generative AI model, the agent is created with a conversational style and response logic that mimics the user's characteristics. In this generation process, the dialogue model is constructed through data calculations.

[0085] Step 4:

[0086] The server accesses a database on the communication network and retrieves information related to the user. Specifically, it uses external APIs and information retrieval algorithms to obtain information that matches the user's needs. The retrieved information is compiled in list format and used for subsequent processing by the virtual agent.

[0087] Step 5:

[0088] The virtual agent generates suggestions for the user based on the collected information. Using natural language generation technology, the information is formatted in a way that is easy for the user to understand. The suggestions include options and specific measures, which are sent to the device and displayed visually.

[0089] Step 6:

[0090] The user reviews suggestions from the virtual agent and then makes their own selections and takes action. The user's responses are sent from the terminal to the server as feedback. This feedback data is recorded as information indicating user satisfaction and usage trends.

[0091] Step 7:

[0092] The server analyzes user feedback to improve the virtual agent. Machine learning techniques are used for continuous adjustments to optimize future user interactions. This improvement process enhances the system's accuracy and user adaptability.

[0093] (Application Example 1)

[0094] 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."

[0095] Modern consumers seek customized experiences tailored to their personality and preferences when selecting products and obtaining information. However, traditional systems struggle to provide information optimized for users, making it difficult to deliver a highly satisfying shopping experience. Therefore, there is a need for a system that provides consumers with individually customized product information visually and effectively when they visit a physical store.

[0096] 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.

[0097] In this invention, the server includes means for inputting user personality information, means for generating a virtual character specifically for the user based on the personality information, and means for suggesting product information tailored to the user's background via an application installed on a visual information device. This enables consumers to receive real-time recommendations for products that match their preferences in physical stores.

[0098] "User personality information" refers to data related to an individual's behavioral patterns and characteristics, including personality assessment results and self-analysis results.

[0099] A "user-specific virtual character" is a digital character generated based on the user's personality information, possessing a conversational style and response logic tailored specifically to that user.

[0100] A "digital network" is a computer network used by various devices to exchange information, and encompasses a wide range of communication systems, including the internet.

[0101] A "visual information device" is a device that provides visual information to the user, and includes equipment such as smart glasses and head-mounted displays.

[0102] "Industry-specific data" refers to data that contains information related to a particular industry and is used as a specialized knowledge base.

[0103] "Opinions" refer to subjective information such as feedback and impressions obtained from users, and are data that serves as clues for improving the system.

[0104] This invention provides a system that enables customized product recommendations based on user personality information in physical stores. This system consists of a user, a visual information device, and a server.

[0105] The server analyzes the personality information entered by the user and generates a virtual character specifically for that user. This virtual character has a conversational style tailored to the user and is responsible for providing purchase recommendations and information. Visual information devices such as smart glasses and head-mounted displays are used. This allows users to visually receive real-time product and sales information when visiting physical stores.

[0106] When a user enters a store wearing a visual information device, it connects to a server via a digital network. The server extracts relevant information from industry-specific data and generates recommendations based on the user's personality. These recommendations are provided in natural language and presented in a way that is easy for the user to understand. An application installed on the visual information device presents the collected information to the user in real time.

[0107] For example, when an outdoor enthusiast visits an outdoor equipment store, a virtual character recommends tents and backpacks with new features and offers advice such as, "They are highly durable and ideal for camping."

[0108] An example of a prompt message would be something like, "Please tell me how to approach customers who are interested in outdoor equipment. Please introduce products and trends related to adventure sports, durability, and camping."

[0109] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0110] Step 1:

[0111] The user enters their personality information using a terminal. The entered data, reflecting the user's personality traits, is sent to the server.

[0112] Input: User's personality information (personality test results, self-analysis results)

[0113] Output: Personality information data sent to the server

[0114] Step 2:

[0115] The server generates a virtual character specifically for the user based on the personality information it receives. The server uses a generation AI model to create a character with a conversational style and response logic tailored to the user's characteristics.

[0116] Input: User personality information data

[0117] Output: User-specific virtual character data

[0118] Step 3:

[0119] When a user enters a physical store wearing a visual information device (such as smart glasses), the terminal connects to a server and collects relevant information from an industry-specific database.

[0120] Input: Virtual character data, access to industry-specific databases

[0121] Output: User-related information data

[0122] Step 4:

[0123] Based on the collected information, the server uses an AI model generated by the user's virtual character to provide specialized recommendations and responses. It selects product information suitable for the user, referring to example prompts.

[0124] Input: Collected information data, virtual character data

[0125] Output: Recommended product information data

[0126] Step 5:

[0127] An application installed on a visual information device presents the user with generated recommended product information in real time. The user visually receives the information, which is provided in natural language.

[0128] Input: Recommended product information data

[0129] Output: Visual information presentation to the user

[0130] 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.

[0131] This invention is a system that provides more personalized and adaptive information by combining customization based on the user's personality with an emotion engine that recognizes the user's emotions. This system can be widely used, from supporting business operations in companies to providing advice on individuals' daily lives.

[0132] Overall flow

[0133] The system begins with the user using a terminal to input their personality information. The terminal sends this information to a server. The server analyzes the user's characteristics based on the received personality information and constructs an avatar accordingly. This avatar has the ability to create responses that are in line with the user's personality traits and behaviors.

[0134] Next, the server uses an emotion engine to recognize the user's emotions during user interaction. The emotion engine analyzes the user's emotional state in real time from factors such as voice tone, text expression, and changes in interaction patterns. For example, if the user is feeling stressed, the engine detects this and provides emotion data to the server.

[0135] The server takes into account the user's emotions, as recognized by the emotion engine, and adaptively adjusts the avatar's responses. These responses can include words to help the user relax and necessary guidance. It also gathers up-to-date data from a broad knowledge base, including industry-specific information, to present users with highly relevant information.

[0136] Specific example

[0137] For example, suppose a user managing a complex project at work consults an avatar about the project's progress. In this case, the server senses the user's stress level from their language and facial expressions, and the emotion engine analyzes this information. As a result, the avatar generates a response that includes words of encouragement and suggestions for changing the mood, and presents it to the user through the device.

[0138] On the other hand, if an individual user is struggling with life planning, the emotion engine accurately captures the user's hopes and anxieties, and the server provides advice and emotional support tailored to those emotions. Through this process, users can not only gather information but also receive emotional support.

[0139] This system improves the accuracy of its AI avatar and emotion engine by receiving feedback from users. As a result, the system will be able to provide increasingly user-adapted interactions over time.

[0140] The following describes the processing flow.

[0141] Step 1:

[0142] The user uses a terminal to input their personality assessment results and personality information. The terminal then formats this information into a data format and sends it to the server.

[0143] Step 2:

[0144] The server analyzes the received user personality information and extracts the user's personality traits. Based on this trait data, it generates a user-specific AI avatar. The avatar has a flexible response profile tailored to the user's characteristics.

[0145] Step 3:

[0146] The device transmits voice and text data obtained through user interaction to the emotion engine. The emotion engine evaluates the user's emotional state based on their tone, word choice, and facial expressions.

[0147] Step 4:

[0148] The emotion engine sends analysis results to the server, providing real-time data on the user's emotional state. The server analyzes this data to understand the user's emotional state.

[0149] Step 5:

[0150] The server combines the user's personality information and emotional data to customize the AI ​​avatar's responses. These responses include expressions of consideration and appropriate suggestions that reflect the user's emotions.

[0151] Step 6:

[0152] The server sends the generated avatar's response to the terminal. The terminal displays this response on its user interface and provides it to the user.

[0153] Step 7:

[0154] Users decide on actions based on suggestions and responses and provide feedback through their devices. The devices then send the collected feedback to the server.

[0155] Step 8:

[0156] The server optimizes the emotion engine and AI avatar based on user feedback data to improve system accuracy. This process is repeated regularly to continuously improve the user experience.

[0157] (Example 2)

[0158] 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".

[0159] In today's information society, providing personalized information and support to users is crucial. However, conventional systems have struggled to provide adaptive responses that adequately consider users' personalities and emotional states. As a result, users often felt dissatisfied with the system's suggestions and responses, and perceived the information as lacking relevance and usefulness. Therefore, there is a need for new systems that can provide more personalized and adaptive information based on user characteristics and emotional states.

[0160] 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.

[0161] In this invention, the server includes means for inputting user characteristics, means for generating an individualized digital person based on the characteristic information, means for collecting information from information sources on a data network, means for the digital person to generate suggestions and responses adapted to the user, means for recognizing the user's emotional state in real time, and means for adjusting the digital person's responses based on the emotional state. This enables the provision of precise information and emotional support tailored to the user's individual needs.

[0162] "User characteristics" refer to information about the user's personality and behavioral patterns that the system uses to generate personalized responses.

[0163] A "personalized digital person" is a virtual agent built based on the user's characteristics to provide appropriate responses in interactions with the user.

[0164] "Information sources on data networks" refer to knowledge bases and collections of information accessible via the internet, and serve as a medium for obtaining necessary data.

[0165] "User emotional state" refers to data that the system analyzes in real time through voice and text, indicating the user's psychological situation and emotions.

[0166] "Adjusting a digital character's responses based on emotional state" is the process of appropriately changing the content of information and advice provided by a digital character, taking into account the user's current emotions.

[0167] This invention is a system that provides personalized information and support based on the user's characteristics and emotional state. The user inputs their characteristic information using a terminal. A dedicated application or web interface is provided on the terminal, allowing the user to input information through personality tests or questionnaires.

[0168] The input information is sent from the terminal to the server. The server uses a generative AI model to process the received information. This model is pre-trained and analyzes the user's characteristics. Based on the analysis results, the server constructs an individualized digital persona. This digital persona has the ability to generate responses adapted to the user's characteristics.

[0169] Furthermore, the server operates an emotion engine to recognize the user's emotional state in real time. This engine analyzes emotions from voice tone and text to understand the user's psychological state. For example, if the user appears anxious, the engine recognizes this as "anxiety" and reflects it in the digital character's response.

[0170] The server also includes the ability to collect information from data sources on the data network. As needed, it retrieves industry-specific information and the latest data to provide users with the most relevant information. Furthermore, it receives user feedback and adjusts the parameters of the generated AI model to improve the accuracy and adaptability of the digital persona.

[0171] As a concrete example, consider a user who manages a project at work. When this user consults a digital figure through their terminal, the server considers the user's characteristics and emotional state, and provides suggestions and responses appropriate to the project's progress. For example, by using a prompt such as, "Please check my current stress level and provide appropriate solutions," the system can respond in a way that is tailored to the user's situation.

[0172] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0173] Step 1:

[0174] Users input their personal characteristics using a terminal. This input data consists of personality test results and questionnaires regarding behavioral patterns. This information is sent from the terminal to the server, where it is received by a data receiver.

[0175] Step 2:

[0176] The server processes the received characteristic information and analyzes the user's personality traits using a generative AI model. This model uses a pre-trained algorithm to create a personality profile. The input data is quantified, and the user's personality profile is output as the analysis result.

[0177] Step 3:

[0178] The server constructs an individualized digital persona based on the analysis results. This digital persona is a virtual agent designed to generate responses adapted to the user's characteristics. Here, the analyzed profile data is taken as input, and a set of behavioral rules for the digital persona is output.

[0179] Step 4:

[0180] The server activates an emotion engine to recognize the user's emotional state in real time. The user's voice or text messages are used as input, and the engine analyzes the tone and context of the voice to provide an output indicating the current emotional state. This output prompts special responses if psychological thresholds are exceeded.

[0181] Step 5:

[0182] The server uses emotional data obtained from the emotion engine to adjust the responses of the personalized digital character. Based on the emotional state and personality profile, it generates the optimal response. This response is then output directly to the terminal and presented to the user. As a result, the user receives an answer that is appropriate to their situation.

[0183] Step 6:

[0184] The server collects necessary additional information from information sources on the data network. This process identifies the most relevant information based on the user's situation and processes it through a generative AI model. If necessary, information from industry-specific databases is also retrieved and formatted for final presentation to the user.

[0185] Step 7:

[0186] The terminal presents the user with responses and information sent from the server. The user reviews the responses and provides feedback. This feedback is sent back to the server from the terminal and used to improve the generated AI model. This continuously improves the overall response accuracy and adaptability of the system.

[0187] (Application Example 2)

[0188] 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".

[0189] Conventional information systems have difficulty providing adaptive information that fully considers the user's personality and emotional state. This is particularly problematic in customer service at physical stores, where it is difficult to immediately provide services tailored to individual customer needs. Therefore, there is a need for an efficient system that accurately grasps the individual characteristics and emotions of users and provides appropriate suggestions based on that understanding.

[0190] 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.

[0191] In this invention, the server includes a device for inputting the user's individual characteristics information, a device for generating a user-specific virtual character based on the individual characteristics information, and a device for collecting information from a database on a communication network. This makes it possible to immediately provide customized suggestions that respond to the user's characteristics and emotions.

[0192] "Individual characteristic information" refers to data that shows the individual characteristics of a user, such as their personality, interests, and preferences.

[0193] A "virtual character" is a digital representation of a person generated based on the user's individual characteristics, and its role is to provide adaptive responses through interaction with the user.

[0194] A "database on a communication network" is a collection of information accessible via the internet, which stores information from various fields and provides it as needed.

[0195] "Emotional state" refers to the user's mental and emotional condition, and is data analyzed from facial expressions, tone of voice, and other factors.

[0196] A "device for displaying instructions to service providers" is a digital device that communicates appropriate responses and suggestions to service providers in real time, based on the customer's emotional state.

[0197] This invention is a system that provides personalized services based on the user's individual characteristics information. In the system, the server receives data from a terminal that inputs the user's individual characteristics information. The terminal includes a device such as smart glasses, and the user acquires information through interaction. Based on the received individual characteristics information, the server generates a specific virtual character. The virtual character has logic for generating adaptive responses according to the user's personality and emotional state.

[0198] A database on the communication network collects information highly relevant to the user, and the server passes this information to a virtual character to create customized suggestions. To analyze emotional states, voice analysis and facial recognition technologies are used. This involves facial recognition software such as OpenCV and voice libraries such as Google® Cloud Speech-to-Text. Based on the emotional state, the server displays the suggestions and information obtained from the virtual character as appropriate instructions to the service provider.

[0199] As a concrete example, in a physical store, when a user is having trouble choosing a product, smart glasses can analyze their emotional state, and a server can suggest products to the user through a virtual character, saying, "How about this product?" The service provider can then be notified, "This customer may be interested in red wine." A generative AI model can then generate prompts such as, "What do you think the details of the product the customer is looking for are?"

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] The terminal allows users to input individual characteristic information through its interface. This information includes the user's personality, hobbies, and current emotional state. This input data is converted into a digital format and sent to the server.

[0203] Step 2:

[0204] The server receives individual characteristic information sent from the terminal and generates a user-specific virtual character using a generative AI model. This model calculates the optimal attributes of the virtual character based on the user's characteristic information and stores this information in a database. The output is a personalized virtual character profile.

[0205] Step 3:

[0206] The server accesses a database on the network to collect information related to the user's needs and interests. This database query is designed to extract the most relevant data based on the profile of the generated virtual character. The retrieved information is stored for use in the virtual character's response generation process.

[0207] Step 4:

[0208] As the user interacts with the device in real time, the terminal uses voice sensors and a camera to monitor the user's emotional state. Emotional data is acquired by analyzing the user's facial expressions and tone of voice, and is quickly transmitted to the server.

[0209] Step 5:

[0210] The server processes emotional state data, and based on a generative AI model, a virtual character generates an appropriate response to the user. This response combines the input emotional information with the virtual character's profile to output content optimized for the user's state.

[0211] Step 6:

[0212] The terminal displays the virtual character's response received from the server to the user. It also notifies the service provider of the instructions via the terminal. This makes it possible to provide customized services in real time, tailored to the user's emotional state.

[0213] 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.

[0214] 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.

[0215] 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.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] 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.

[0219] 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).

[0220] 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.

[0221] 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.

[0222] 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).

[0223] 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.

[0224] 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.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] 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".

[0229] This invention is a system that generates individually customized AI avatars based on the user's personality information and provides information optimized for the user. It is intended for corporate and individual users and can be used for business support, personal life planning, and learning support.

[0230] Overall flow

[0231] The user first inputs their personality assessment results and self-analysis results into an interface using their device, and this data is sent to the server. The server analyzes the received personality data and generates a user-specific avatar. This avatar has a conversational style and response logic that mimics the user's personality and behavioral patterns.

[0232] The server accesses a vast database on the internet and, for corporate clients, utilizes industry-specific information sources to collect information highly relevant to the user. Furthermore, based on this information, the avatar generates specific suggestions and solutions for the user and presents them to the user via the terminal. In this process, natural language generation technology is used to ensure that the information is presented in a way that is easy for the user to understand.

[0233] Specific example

[0234] For example, consider a scenario where a project manager at a company is facing challenges in managing a new project. The user explains the situation to an avatar on their device, and the server searches and collects industry trends and best practices for project management. The avatar then proposes strategies based on successful case studies of similar situations, listing the options and displaying them on the device. The user can then use this information to select a new approach.

[0235] Furthermore, if an individual user is considering their career path, the avatar will suggest occupational information and skill development methods that are suitable for the user's characteristics. This helps users to build their life plans more concretely.

[0236] The flexibility of this system is further enhanced by user feedback. The server continuously improves the avatars by collecting user responses. This feedback loop allows the system to provide more accurate information over time.

[0237] The following describes the processing flow.

[0238] Step 1:

[0239] The user accesses the device and enters their personality assessment results and personality information. The device receives this information and sends it to the server.

[0240] Step 2:

[0241] The server passes the received user personality information to the analysis engine, which then analyzes the data. This process extracts the user's personality traits and infers their behavioral patterns.

[0242] Step 3:

[0243] The server generates a user-specific AI avatar based on the analyzed data. This avatar features a conversational style and response logic tailored to the user's characteristics.

[0244] Step 4:

[0245] The server accesses the internet and industry-specific databases to collect necessary information, including the latest information and trends relevant to user needs.

[0246] Step 5:

[0247] The server integrates collected information with the user's personality data to enable the avatar to generate suggestions and responses tailored to the user. Natural language generation technology is used to ensure the responses are clear and easy to understand.

[0248] Step 6:

[0249] The server sends the generated suggestions and responses to the terminal. The terminal displays the received information on its user interface, presenting it to the user in a visually easy-to-understand manner.

[0250] Step 7:

[0251] The user makes a decision based on the displayed information and enters feedback into the device as needed. The device then sends this feedback to the server.

[0252] Step 8:

[0253] The server utilizes user feedback to improve the response accuracy of the AI ​​avatar. This will make future information delivery even more user-friendly.

[0254] (Example 1)

[0255] 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."

[0256] Conventional information provision systems have challenges in providing optimal information tailored to the individual needs and characteristics of users, and in not having a sufficient feedback loop to determine whether the information provided is beneficial to the user.

[0257] 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.

[0258] In this invention, the server includes a device for inputting user characteristic information, a device for generating a user-specific virtual agent based on the characteristic information, and a device for retrieving information from a database on a communication network. This makes it possible to dynamically provide information tailored to the user and to continuously improve the system based on feedback.

[0259] "User characteristic information" refers to data about individual characteristics of users, including their personality, preferences, and behavioral patterns.

[0260] A "virtual agent" is a digital character generated based on a user's characteristic information, possessing a conversational style and response logic specific to that user.

[0261] A "database on a communication network" is a digital storage system that stores diverse information and is accessible via the internet.

[0262] An "information retrieval device" is a system component that has the function of searching for and acquiring necessary information via a communication network.

[0263] "User response" refers to the actions and feedback that users show in response to information provided by the virtual agent.

[0264] A "device for evolution" is a system component that has the function of improving the virtual agent based on user feedback and enhancing its capabilities.

[0265] "Natural language form" refers to a form of expression based on human language that users can intuitively understand.

[0266] Embodiments of this invention will now be described. This system generates individually customized virtual agents based on the user's characteristic information and provides the user with information optimized for them. The user inputs characteristic information and self-analysis results using a terminal. This input is securely transmitted to the server through a data collection device.

[0267] The server analyzes the received characteristic information. This analysis utilizes natural language processing libraries and machine learning algorithms. Furthermore, based on the analysis results, the server generates a user-specific virtual agent. This agent possesses a conversational style that reflects the user's personality and behavioral patterns.

[0268] In information gathering, servers access databases and external APIs on the internet to retrieve highly relevant information. By utilizing scraping techniques and external APIs, new data and information tailored to user needs can be efficiently acquired. For corporate users, more specialized information is provided using specific industry information sources.

[0269] The virtual agent generates personalized suggestions for the user based on the collected information. Using natural language generation technology, complex information is transformed into a concise and easy-to-understand format, which is then displayed on the terminal screen. Users also provide feedback on the suggestions and information from the avatar, and the server continuously improves the virtual agent's performance based on this feedback.

[0270] As a concrete example, if a project manager at a company encounters a problem with a new project, they can explain the situation to a virtual agent via a terminal. The server then gathers information on project management best practices and market trends, and generates a solution strategy based on similar success stories. This makes it possible to list useful options for project progress and provide them to the project manager.

[0271] Furthermore, for individual users struggling with their career paths, a virtual agent provides personalized job information and skill development suggestions. This system can provide users with necessary advice by prompting them with phrases such as, "Please provide solutions to my project management problems," or "Please suggest a career path that suits me." Using such prompts allows users to utilize the system more intuitively.

[0272] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0273] Step 1:

[0274] Users input characteristic information via their device. Specifically, they input personality assessment results and self-analysis results into an interface on the device. This input data is securely transmitted to the server. The input data can take various forms, including text data and multiple-choice options.

[0275] Step 2:

[0276] The server receives the input trait information and analyzes it using natural language processing algorithms. This analysis involves data processing such as text sentiment analysis and feature extraction to identify the user's personality and behavioral patterns. As a result of this analysis, the trait information is extracted in a more detailed data format.

[0277] Step 3:

[0278] The server uses the analysis results to generate a user-specific virtual agent. Utilizing a generative AI model, the agent is created with a conversational style and response logic that mimics the user's characteristics. In this generation process, the dialogue model is constructed through data calculations.

[0279] Step 4:

[0280] The server accesses a database on the communication network and retrieves information related to the user. Specifically, it uses external APIs and information retrieval algorithms to obtain information that matches the user's needs. The retrieved information is compiled in list format and used for subsequent processing by the virtual agent.

[0281] Step 5:

[0282] The virtual agent generates suggestions for the user based on the collected information. Using natural language generation technology, the information is formatted in a way that is easy for the user to understand. The suggestions include options and specific measures, which are sent to the device and displayed visually.

[0283] Step 6:

[0284] The user checks the proposals from the virtual agent and makes actual selections and actions. The user's reaction is sent from the terminal to the server as feedback. The feedback data is recorded as information indicating the user's satisfaction and usage tendency, etc.

[0285] Step 7:

[0286] The server analyzes the feedback from the user and uses it to improve the virtual agent. Using machine learning techniques, continuous adjustments are made to optimize future user interactions. This improvement process enhances the accuracy of the system and its adaptability to users.

[0287] (Application Example 1)

[0288] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0289] Modern consumers seek a customized experience that suits their personality and preferences in product selection and information acquisition. However, in conventional systems, it is difficult to provide information optimized for the user, and it is a challenging situation to offer a highly satisfactory shopping experience. Therefore, when consumers visit a physical store, there is a demand for a system that can visually and effectively provide individually customized product information on the spot.

[0290] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0291] In this invention, the server includes means for inputting the user's personality information, means for generating a user-specific virtual character based on the personality information, and means for proposing product information specialized for the user's background via an application installed in the visual information device. As a result, consumers can receive real-time recommendations for products that suit their preferences in a physical store.

[0292] "User personality information" refers to data related to an individual's behavioral patterns and characteristics, including personality assessment results and self-analysis results.

[0293] A "user-specific virtual character" is a digital character generated based on the user's personality information, possessing a conversational style and response logic tailored specifically to that user.

[0294] A "digital network" is a computer network used by various devices to exchange information, and encompasses a wide range of communication systems, including the internet.

[0295] A "visual information device" is a device that provides visual information to the user, and includes equipment such as smart glasses and head-mounted displays.

[0296] "Industry-specific data" refers to data that contains information related to a particular industry and is used as a specialized knowledge base.

[0297] "Opinions" refer to subjective information such as feedback and impressions obtained from users, and are data that serves as clues for improving the system.

[0298] This invention provides a system that enables customized product recommendations based on user personality information in physical stores. This system consists of a user, a visual information device, and a server.

[0299] The server analyzes the personality information entered by the user and generates a virtual character specifically for that user. This virtual character has a conversational style tailored to the user and is responsible for providing purchase recommendations and information. Visual information devices such as smart glasses and head-mounted displays are used. This allows users to visually receive real-time product and sales information when visiting physical stores.

[0300] When a user wears a visual information device and enters a store, it is connected to a server via a digital network. The server extracts relevant information from industry-specific data and generates recommendations based on the user's personality information. These recommendations are provided in natural language and presented in a form that is easy for the user to understand. An application installed on the visual information device presents the collected information to the user in real time.

[0301] As a specific example, when an outdoor-loving user visits an outdoor supplies store, the virtual character recommends tents and backpacks with new features and provides advice such as "high durability and optimal for camping."

[0302] As an example of a prompt sentence, it is assumed to be something like "Please teach me how to approach customers who are interested in outdoor supplies. I would like you to introduce products and trends related to adventure sports, durability, and camping."

[0303] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0304] Step 1:

[0305] The user inputs their personality information using a terminal. The input data reflects the user's personality characteristics and is sent to the server.

[0306] Input: User's personality information (personality diagnosis result, self-analysis result)

[0307] Output: Personality information data sent to the server

[0308] Step 2:

[0309] The server generates a virtual character dedicated to the user based on the received personality information. The server uses a generation AI model to create a character with a conversation style and response logic according to the user's characteristics.

[0310] Input: User personality information data

[0311] Output: User-specific virtual character data

[0312] Step 3:

[0313] When a user enters a physical store wearing a visual information device (such as smart glasses), the terminal connects to a server and collects relevant information from an industry-specific database.

[0314] Input: Virtual character data, access to industry-specific databases

[0315] Output: User-related information data

[0316] Step 4:

[0317] Based on the collected information, the server uses an AI model generated by the user's virtual character to provide specialized recommendations and responses. It selects product information suitable for the user, referring to example prompts.

[0318] Input: Collected information data, virtual character data

[0319] Output: Recommended product information data

[0320] Step 5:

[0321] An application installed on a visual information device presents the user with generated recommended product information in real time. The user visually receives the information, which is provided in natural language.

[0322] Input: Recommended product information data

[0323] Output: Visual information presentation to the user

[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 is a system that provides more personalized and adaptive information by combining customization based on the user's personality with an emotion engine that recognizes the user's emotions. This system can be widely used, from supporting business operations in companies to providing advice on individuals' daily lives.

[0326] Overall flow

[0327] The system begins with the user using a terminal to input their personality information. The terminal sends this information to a server. The server analyzes the user's characteristics based on the received personality information and constructs an avatar accordingly. This avatar has the ability to create responses that are in line with the user's personality traits and behaviors.

[0328] Next, the server uses an emotion engine to recognize the user's emotions during user interaction. The emotion engine analyzes the user's emotional state in real time from factors such as voice tone, text expression, and changes in interaction patterns. For example, if the user is feeling stressed, the engine detects this and provides emotion data to the server.

[0329] The server takes into account the user's emotions, as recognized by the emotion engine, and adaptively adjusts the avatar's responses. These responses can include words to help the user relax and necessary guidance. It also gathers up-to-date data from a broad knowledge base, including industry-specific information, to present users with highly relevant information.

[0330] Specific example

[0331] For example, suppose a user managing a complex project at work consults an avatar about the project's progress. In this case, the server senses the user's stress level from their language and facial expressions, and the emotion engine analyzes this information. As a result, the avatar generates a response that includes words of encouragement and suggestions for changing the mood, and presents it to the user through the device.

[0332] On the other hand, if an individual user is struggling with life planning, the emotion engine accurately captures the user's hopes and anxieties, and the server provides advice and emotional support tailored to those emotions. Through this process, users can not only gather information but also receive emotional support.

[0333] This system improves the accuracy of its AI avatar and emotion engine by receiving feedback from users. As a result, the system will be able to provide increasingly user-adapted interactions over time.

[0334] The following describes the processing flow.

[0335] Step 1:

[0336] The user uses a terminal to input their personality assessment results and personality information. The terminal then formats this information into a data format and sends it to the server.

[0337] Step 2:

[0338] The server analyzes the received user personality information and extracts the user's personality traits. Based on this trait data, it generates a user-specific AI avatar. The avatar has a flexible response profile tailored to the user's characteristics.

[0339] Step 3:

[0340] The device transmits voice and text data obtained through user interaction to the emotion engine. The emotion engine evaluates the user's emotional state based on their tone, word choice, and facial expressions.

[0341] Step 4:

[0342] The emotion engine sends analysis results to the server, providing real-time data on the user's emotional state. The server analyzes this data to understand the user's emotional state.

[0343] Step 5:

[0344] The server combines the user's personality information and emotional data to customize the AI ​​avatar's responses. These responses include expressions of consideration and appropriate suggestions that reflect the user's emotions.

[0345] Step 6:

[0346] The server sends the generated avatar's response to the terminal. The terminal displays this response on its user interface and provides it to the user.

[0347] Step 7:

[0348] Users decide on actions based on suggestions and responses and provide feedback through their devices. The devices then send the collected feedback to the server.

[0349] Step 8:

[0350] The server optimizes the emotion engine and AI avatar based on user feedback data to improve system accuracy. This process is repeated regularly to continuously improve the user experience.

[0351] (Example 2)

[0352] 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".

[0353] In today's information society, providing personalized information and support to users is crucial. However, conventional systems have struggled to provide adaptive responses that adequately consider users' personalities and emotional states. As a result, users often felt dissatisfied with the system's suggestions and responses, and perceived the information as lacking relevance and usefulness. Therefore, there is a need for new systems that can provide more personalized and adaptive information based on user characteristics and emotional states.

[0354] 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.

[0355] In this invention, the server includes means for inputting user characteristics, means for generating an individualized digital person based on the characteristic information, means for collecting information from information sources on a data network, means for the digital person to generate suggestions and responses adapted to the user, means for recognizing the user's emotional state in real time, and means for adjusting the digital person's responses based on the emotional state. This enables the provision of precise information and emotional support tailored to the user's individual needs.

[0356] "User characteristics" refer to information about the user's personality and behavioral patterns that the system uses to generate personalized responses.

[0357] A "personalized digital person" is a virtual agent built based on the user's characteristics to provide appropriate responses in interactions with the user.

[0358] "Information sources on data networks" refer to knowledge bases and collections of information accessible via the internet, and serve as a medium for obtaining necessary data.

[0359] "User emotional state" refers to data that the system analyzes in real time through voice and text, indicating the user's psychological situation and emotions.

[0360] "Adjusting a digital character's responses based on emotional state" is the process of appropriately changing the content of information and advice provided by a digital character, taking into account the user's current emotions.

[0361] This invention is a system that provides personalized information and support based on the user's characteristics and emotional state. The user inputs their characteristic information using a terminal. A dedicated application or web interface is provided on the terminal, allowing the user to input information through personality tests or questionnaires.

[0362] The input information is sent from the terminal to the server. The server uses a generative AI model to process the received information. This model is pre-trained and analyzes the user's characteristics. Based on the analysis results, the server constructs an individualized digital persona. This digital persona has the ability to generate responses adapted to the user's characteristics.

[0363] Furthermore, the server operates an emotion engine to recognize the user's emotional state in real time. This engine analyzes emotions from voice tone and text to understand the user's psychological state. For example, if the user appears anxious, the engine recognizes this as "anxiety" and reflects it in the digital character's response.

[0364] The server also includes the ability to collect information from data sources on the data network. As needed, it retrieves industry-specific information and the latest data to provide users with the most relevant information. Furthermore, it receives user feedback and adjusts the parameters of the generated AI model to improve the accuracy and adaptability of the digital persona.

[0365] As a concrete example, consider a user who manages a project at work. When this user consults a digital figure through their terminal, the server considers the user's characteristics and emotional state, and provides suggestions and responses appropriate to the project's progress. For example, by using a prompt such as, "Please check my current stress level and provide appropriate solutions," the system can respond in a way that is tailored to the user's situation.

[0366] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0367] Step 1:

[0368] Users input their personal characteristics using a terminal. This input data consists of personality test results and questionnaires regarding behavioral patterns. This information is sent from the terminal to the server, where it is received by a data receiver.

[0369] Step 2:

[0370] The server processes the received characteristic information and analyzes the user's personality traits using a generative AI model. This model uses a pre-trained algorithm to create a personality profile. The input data is quantified, and the user's personality profile is output as the analysis result.

[0371] Step 3:

[0372] The server constructs an individualized digital persona based on the analysis results. This digital persona is a virtual agent designed to generate responses adapted to the user's characteristics. Here, the analyzed profile data is taken as input, and a set of behavioral rules for the digital persona is output.

[0373] Step 4:

[0374] The server activates an emotion engine to recognize the user's emotional state in real time. The user's voice or text messages are used as input, and the engine analyzes the tone and context of the voice to provide an output indicating the current emotional state. This output prompts special responses if psychological thresholds are exceeded.

[0375] Step 5:

[0376] The server uses emotional data obtained from the emotion engine to adjust the responses of the personalized digital character. Based on the emotional state and personality profile, it generates the optimal response. This response is then output directly to the terminal and presented to the user. As a result, the user receives an answer that is appropriate to their situation.

[0377] Step 6:

[0378] The server collects necessary additional information from information sources on the data network. This process identifies the most relevant information based on the user's situation and processes it through a generative AI model. If necessary, information from industry-specific databases is also retrieved and formatted for final presentation to the user.

[0379] Step 7:

[0380] The terminal presents the user with responses and information sent from the server. The user reviews the responses and provides feedback. This feedback is sent back to the server from the terminal and used to improve the generated AI model. This continuously improves the overall response accuracy and adaptability of the system.

[0381] (Application Example 2)

[0382] 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."

[0383] Conventional information systems have difficulty providing adaptive information that fully considers the user's personality and emotional state. This is particularly problematic in customer service at physical stores, where it is difficult to immediately provide services tailored to individual customer needs. Therefore, there is a need for an efficient system that accurately grasps the individual characteristics and emotions of users and provides appropriate suggestions based on that understanding.

[0384] 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.

[0385] In this invention, the server includes a device for inputting the user's individual characteristics information, a device for generating a user-specific virtual character based on the individual characteristics information, and a device for collecting information from a database on a communication network. This makes it possible to immediately provide customized suggestions that respond to the user's characteristics and emotions.

[0386] "Individual characteristic information" refers to data that shows the individual characteristics of a user, such as their personality, interests, and preferences.

[0387] A "virtual character" is a digital representation of a person generated based on the user's individual characteristics, and its role is to provide adaptive responses through interaction with the user.

[0388] A "database on a communication network" is a collection of information accessible via the internet, which stores information from various fields and provides it as needed.

[0389] "Emotional state" refers to the user's mental and emotional condition, and is data analyzed from facial expressions, tone of voice, and other factors.

[0390] A "device for displaying instructions to service providers" is a digital device that communicates appropriate responses and suggestions to service providers in real time, based on the customer's emotional state.

[0391] This invention is a system that provides personalized services based on the user's individual characteristics information. In the system, the server receives data from a terminal that inputs the user's individual characteristics information. The terminal includes a device such as smart glasses, and the user acquires information through interaction. Based on the received individual characteristics information, the server generates a specific virtual character. The virtual character has logic for generating adaptive responses according to the user's personality and emotional state.

[0392] A database on the communication network collects information highly relevant to the user, and the server passes this information to a virtual character to create customized suggestions. To analyze emotional states, voice analysis and facial recognition technologies are used. This involves facial recognition software such as OpenCV and speech libraries such as Google Cloud Speech-to-Text. Based on the emotional state, the server displays the suggestions and information obtained from the virtual character as appropriate instructions to the service provider.

[0393] As a concrete example, in a physical store, when a user is having trouble choosing a product, smart glasses can analyze their emotional state, and a server can suggest products to the user through a virtual character, saying, "How about this product?" The service provider can then be notified, "This customer may be interested in red wine." A generative AI model can then generate prompts such as, "What do you think the details of the product the customer is looking for are?"

[0394] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0395] Step 1:

[0396] The terminal allows users to input individual characteristic information through its interface. This information includes the user's personality, hobbies, and current emotional state. This input data is converted into a digital format and sent to the server.

[0397] Step 2:

[0398] The server receives individual characteristic information sent from the terminal and generates a user-specific virtual character using a generative AI model. This model calculates the optimal attributes of the virtual character based on the user's characteristic information and stores this information in a database. The output is a personalized virtual character profile.

[0399] Step 3:

[0400] The server accesses a database on the network to collect information related to the user's needs and interests. This database query is designed to extract the most relevant data based on the profile of the generated virtual character. The retrieved information is stored for use in the virtual character's response generation process.

[0401] Step 4:

[0402] As the user interacts with the device in real time, the terminal uses voice sensors and a camera to monitor the user's emotional state. Emotional data is acquired by analyzing the user's facial expressions and tone of voice, and is quickly transmitted to the server.

[0403] Step 5:

[0404] The server processes emotional state data, and based on a generative AI model, a virtual character generates an appropriate response to the user. This response combines the input emotional information with the virtual character's profile to output content optimized for the user's state.

[0405] Step 6:

[0406] The terminal displays the virtual character's response received from the server to the user. It also notifies the service provider of the instructions via the terminal. This makes it possible to provide customized services in real time, tailored to the user's emotional state.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] [Third Embodiment]

[0411] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0412] 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.

[0413] 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).

[0414] 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.

[0415] 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.

[0416] 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).

[0417] 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.

[0418] 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.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] 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".

[0423] This invention is a system that generates individually customized AI avatars based on the user's personality information and provides information optimized for the user. It is intended for corporate and individual users and can be used for business support, personal life planning, and learning support.

[0424] Overall flow

[0425] The user first inputs their personality assessment results and self-analysis results into an interface using their device, and this data is sent to the server. The server analyzes the received personality data and generates a user-specific avatar. This avatar has a conversational style and response logic that mimics the user's personality and behavioral patterns.

[0426] The server accesses a vast database on the internet and, for corporate clients, utilizes industry-specific information sources to collect information highly relevant to the user. Furthermore, based on this information, the avatar generates specific suggestions and solutions for the user and presents them to the user via the terminal. In this process, natural language generation technology is used to ensure that the information is presented in a way that is easy for the user to understand.

[0427] Specific example

[0428] For example, consider a scenario where a project manager at a company is facing challenges in managing a new project. The user explains the situation to an avatar on their device, and the server searches and collects industry trends and best practices for project management. The avatar then proposes strategies based on successful case studies of similar situations, listing the options and displaying them on the device. The user can then use this information to select a new approach.

[0429] Furthermore, if an individual user is considering their career path, the avatar will suggest occupational information and skill development methods that are suitable for the user's characteristics. This helps users to build their life plans more concretely.

[0430] The flexibility of this system is further enhanced by user feedback. The server continuously improves the avatars by collecting user responses. This feedback loop allows the system to provide more accurate information over time.

[0431] The following describes the processing flow.

[0432] Step 1:

[0433] The user accesses the device and enters their personality assessment results and personality information. The device receives this information and sends it to the server.

[0434] Step 2:

[0435] The server passes the received user personality information to the analysis engine, which then analyzes the data. This process extracts the user's personality traits and infers their behavioral patterns.

[0436] Step 3:

[0437] The server generates a user-specific AI avatar based on the analyzed data. This avatar features a conversational style and response logic tailored to the user's characteristics.

[0438] Step 4:

[0439] The server accesses the internet and industry-specific databases to collect necessary information, including the latest information and trends relevant to user needs.

[0440] Step 5:

[0441] The server integrates collected information with the user's personality data to enable the avatar to generate suggestions and responses tailored to the user. Natural language generation technology is used to ensure the responses are clear and easy to understand.

[0442] Step 6:

[0443] The server sends the generated suggestions and responses to the terminal. The terminal displays the received information on its user interface, presenting it to the user in a visually easy-to-understand manner.

[0444] Step 7:

[0445] The user makes a decision based on the displayed information and enters feedback into the device as needed. The device then sends this feedback to the server.

[0446] Step 8:

[0447] The server utilizes user feedback to improve the response accuracy of the AI ​​avatar. This will make future information delivery even more user-friendly.

[0448] (Example 1)

[0449] 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."

[0450] Conventional information provision systems have challenges in providing optimal information tailored to the individual needs and characteristics of users, and in not having a sufficient feedback loop to determine whether the information provided is beneficial to the user.

[0451] 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.

[0452] In this invention, the server includes a device for inputting user characteristic information, a device for generating a user-specific virtual agent based on the characteristic information, and a device for retrieving information from a database on a communication network. This makes it possible to dynamically provide information tailored to the user and to continuously improve the system based on feedback.

[0453] "User characteristic information" refers to data about individual characteristics of users, including their personality, preferences, and behavioral patterns.

[0454] A "virtual agent" is a digital character generated based on a user's characteristic information, possessing a conversational style and response logic specific to that user.

[0455] A "database on a communication network" is a digital storage system that stores diverse information and is accessible via the internet.

[0456] An "information retrieval device" is a system component that has the function of searching for and acquiring necessary information via a communication network.

[0457] "User response" refers to the actions and feedback that users show in response to information provided by the virtual agent.

[0458] A "device for evolution" is a system component that has the function of improving the virtual agent based on user feedback and enhancing its capabilities.

[0459] "Natural language form" refers to a form of expression based on human language that users can intuitively understand.

[0460] Embodiments of this invention will now be described. This system generates individually customized virtual agents based on the user's characteristic information and provides the user with information optimized for them. The user inputs characteristic information and self-analysis results using a terminal. This input is securely transmitted to the server through a data collection device.

[0461] The server analyzes the received characteristic information. This analysis utilizes natural language processing libraries and machine learning algorithms. Furthermore, based on the analysis results, the server generates a user-specific virtual agent. This agent possesses a conversational style that reflects the user's personality and behavioral patterns.

[0462] In information gathering, servers access databases and external APIs on the internet to retrieve highly relevant information. By utilizing scraping techniques and external APIs, new data and information tailored to user needs can be efficiently acquired. For corporate users, more specialized information is provided using specific industry information sources.

[0463] The virtual agent generates personalized suggestions for the user based on the collected information. Using natural language generation technology, complex information is transformed into a concise and easy-to-understand format, which is then displayed on the terminal screen. Users also provide feedback on the suggestions and information from the avatar, and the server continuously improves the virtual agent's performance based on this feedback.

[0464] As a concrete example, if a project manager at a company encounters a problem with a new project, they can explain the situation to a virtual agent via a terminal. The server then gathers information on project management best practices and market trends, and generates a solution strategy based on similar success stories. This makes it possible to list useful options for project progress and provide them to the project manager.

[0465] Furthermore, for individual users struggling with their career paths, a virtual agent provides personalized job information and skill development suggestions. This system can provide users with necessary advice by prompting them with phrases such as, "Please provide solutions to my project management problems," or "Please suggest a career path that suits me." Using such prompts allows users to utilize the system more intuitively.

[0466] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0467] Step 1:

[0468] Users input characteristic information via their device. Specifically, they input personality assessment results and self-analysis results into an interface on the device. This input data is securely transmitted to the server. The input data can take various forms, including text data and multiple-choice options.

[0469] Step 2:

[0470] The server receives the input trait information and analyzes it using natural language processing algorithms. This analysis involves data processing such as text sentiment analysis and feature extraction to identify the user's personality and behavioral patterns. As a result of this analysis, the trait information is extracted in a more detailed data format.

[0471] Step 3:

[0472] The server uses the analysis results to generate a user-specific virtual agent. Utilizing a generative AI model, the agent is created with a conversational style and response logic that mimics the user's characteristics. In this generation process, the dialogue model is constructed through data calculations.

[0473] Step 4:

[0474] The server accesses a database on the communication network and retrieves information related to the user. Specifically, it uses external APIs and information retrieval algorithms to obtain information that matches the user's needs. The retrieved information is compiled in list format and used for subsequent processing by the virtual agent.

[0475] Step 5:

[0476] The virtual agent generates suggestions for the user based on the collected information. Using natural language generation technology, the information is formatted in a way that is easy for the user to understand. The suggestions include options and specific measures, which are sent to the device and displayed visually.

[0477] Step 6:

[0478] The user reviews suggestions from the virtual agent and then makes their own selections and takes action. The user's responses are sent from the terminal to the server as feedback. This feedback data is recorded as information indicating user satisfaction and usage trends.

[0479] Step 7:

[0480] The server analyzes user feedback to improve the virtual agent. Machine learning techniques are used for continuous adjustments to optimize future user interactions. This improvement process enhances the system's accuracy and user adaptability.

[0481] (Application Example 1)

[0482] 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."

[0483] Modern consumers seek customized experiences tailored to their personality and preferences when selecting products and obtaining information. However, traditional systems struggle to provide information optimized for users, making it difficult to deliver a highly satisfying shopping experience. Therefore, there is a need for a system that provides consumers with individually customized product information visually and effectively when they visit a physical store.

[0484] 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.

[0485] In this invention, the server includes means for inputting user personality information, means for generating a virtual character specifically for the user based on the personality information, and means for suggesting product information tailored to the user's background via an application installed on a visual information device. This enables consumers to receive real-time recommendations for products that match their preferences in physical stores.

[0486] "User personality information" refers to data related to an individual's behavioral patterns and characteristics, including personality assessment results and self-analysis results.

[0487] A "user-specific virtual character" is a digital character generated based on the user's personality information, possessing a conversational style and response logic tailored specifically to that user.

[0488] A "digital network" is a computer network used by various devices to exchange information, and encompasses a wide range of communication systems, including the internet.

[0489] A "visual information device" is a device that provides visual information to the user, and includes equipment such as smart glasses and head-mounted displays.

[0490] "Industry-specific data" refers to data that contains information related to a particular industry and is used as a specialized knowledge base.

[0491] "Opinions" refer to subjective information such as feedback and impressions obtained from users, and are data that serves as clues for improving the system.

[0492] This invention provides a system that enables customized product recommendations based on user personality information in physical stores. This system consists of a user, a visual information device, and a server.

[0493] The server analyzes the personality information entered by the user and generates a virtual character specifically for that user. This virtual character has a conversational style tailored to the user and is responsible for providing purchase recommendations and information. Visual information devices such as smart glasses and head-mounted displays are used. This allows users to visually receive real-time product and sales information when visiting physical stores.

[0494] When a user enters a store wearing a visual information device, it connects to a server via a digital network. The server extracts relevant information from industry-specific data and generates recommendations based on the user's personality. These recommendations are provided in natural language and presented in a way that is easy for the user to understand. An application installed on the visual information device presents the collected information to the user in real time.

[0495] For example, when an outdoor enthusiast visits an outdoor equipment store, a virtual character recommends tents and backpacks with new features and offers advice such as, "They are highly durable and ideal for camping."

[0496] An example of a prompt message would be something like, "Please tell me how to approach customers who are interested in outdoor equipment. Please introduce products and trends related to adventure sports, durability, and camping."

[0497] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0498] Step 1:

[0499] The user enters their personality information using a terminal. The entered data, reflecting the user's personality traits, is sent to the server.

[0500] Input: User's personality information (personality test results, self-analysis results)

[0501] Output: Personality information data sent to the server

[0502] Step 2:

[0503] The server generates a virtual character specifically for the user based on the personality information it receives. The server uses a generation AI model to create a character with a conversational style and response logic tailored to the user's characteristics.

[0504] Input: User personality information data

[0505] Output: User-specific virtual character data

[0506] Step 3:

[0507] When a user enters a physical store wearing a visual information device (such as smart glasses), the terminal connects to a server and collects relevant information from an industry-specific database.

[0508] Input: Virtual character data, access to industry-specific databases

[0509] Output: User-related information data

[0510] Step 4:

[0511] Based on the collected information, the server uses an AI model generated by the user's virtual character to provide specialized recommendations and responses. It selects product information suitable for the user, referring to example prompts.

[0512] Input: Collected information data, virtual character data

[0513] Output: Recommended product information data

[0514] Step 5:

[0515] An application installed on a visual information device presents the user with generated recommended product information in real time. The user visually receives the information, which is provided in natural language.

[0516] Input: Recommended product information data

[0517] Output: Visual information presentation to the user

[0518] 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.

[0519] This invention is a system that provides more personalized and adaptive information by combining customization based on the user's personality with an emotion engine that recognizes the user's emotions. This system can be widely used, from supporting business operations in companies to providing advice on individuals' daily lives.

[0520] Overall flow

[0521] The system begins with the user using a terminal to input their personality information. The terminal sends this information to a server. The server analyzes the user's characteristics based on the received personality information and constructs an avatar accordingly. This avatar has the ability to create responses that are in line with the user's personality traits and behaviors.

[0522] Next, the server uses an emotion engine to recognize the user's emotions during user interaction. The emotion engine analyzes the user's emotional state in real time from factors such as voice tone, text expression, and changes in interaction patterns. For example, if the user is feeling stressed, the engine detects this and provides emotion data to the server.

[0523] The server takes into account the user's emotions, as recognized by the emotion engine, and adaptively adjusts the avatar's responses. These responses can include words to help the user relax and necessary guidance. It also gathers up-to-date data from a broad knowledge base, including industry-specific information, to present users with highly relevant information.

[0524] Specific example

[0525] For example, suppose a user managing a complex project at work consults an avatar about the project's progress. In this case, the server senses the user's stress level from their language and facial expressions, and the emotion engine analyzes this information. As a result, the avatar generates a response that includes words of encouragement and suggestions for changing the mood, and presents it to the user through the device.

[0526] On the other hand, if an individual user is struggling with life planning, the emotion engine accurately captures the user's hopes and anxieties, and the server provides advice and emotional support tailored to those emotions. Through this process, users can not only gather information but also receive emotional support.

[0527] This system improves the accuracy of its AI avatar and emotion engine by receiving feedback from users. As a result, the system will be able to provide increasingly user-adapted interactions over time.

[0528] The following describes the processing flow.

[0529] Step 1:

[0530] The user uses a terminal to input their personality assessment results and personality information. The terminal then formats this information into a data format and sends it to the server.

[0531] Step 2:

[0532] The server analyzes the received user personality information and extracts the user's personality traits. Based on this trait data, it generates a user-specific AI avatar. The avatar has a flexible response profile tailored to the user's characteristics.

[0533] Step 3:

[0534] The device transmits voice and text data obtained through user interaction to the emotion engine. The emotion engine evaluates the user's emotional state based on their tone, word choice, and facial expressions.

[0535] Step 4:

[0536] The emotion engine sends analysis results to the server, providing real-time data on the user's emotional state. The server analyzes this data to understand the user's emotional state.

[0537] Step 5:

[0538] The server combines the user's personality information and emotional data to customize the AI ​​avatar's responses. These responses include expressions of consideration and appropriate suggestions that reflect the user's emotions.

[0539] Step 6:

[0540] The server sends the generated avatar's response to the terminal. The terminal displays this response on its user interface and provides it to the user.

[0541] Step 7:

[0542] Users decide on actions based on suggestions and responses and provide feedback through their devices. The devices then send the collected feedback to the server.

[0543] Step 8:

[0544] The server optimizes the emotion engine and AI avatar based on user feedback data to improve system accuracy. This process is repeated regularly to continuously improve the user experience.

[0545] (Example 2)

[0546] 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."

[0547] In today's information society, providing personalized information and support to users is crucial. However, conventional systems have struggled to provide adaptive responses that adequately consider users' personalities and emotional states. As a result, users often felt dissatisfied with the system's suggestions and responses, and perceived the information as lacking relevance and usefulness. Therefore, there is a need for new systems that can provide more personalized and adaptive information based on user characteristics and emotional states.

[0548] 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.

[0549] In this invention, the server includes means for inputting user characteristics, means for generating an individualized digital person based on the characteristic information, means for collecting information from information sources on a data network, means for the digital person to generate suggestions and responses adapted to the user, means for recognizing the user's emotional state in real time, and means for adjusting the digital person's responses based on the emotional state. This enables the provision of precise information and emotional support tailored to the user's individual needs.

[0550] "User characteristics" refer to information about the user's personality and behavioral patterns that the system uses to generate personalized responses.

[0551] A "personalized digital person" is a virtual agent built based on the user's characteristics to provide appropriate responses in interactions with the user.

[0552] "Information sources on data networks" refer to knowledge bases and collections of information accessible via the internet, and serve as a medium for obtaining necessary data.

[0553] "User emotional state" refers to data that the system analyzes in real time through voice and text, indicating the user's psychological situation and emotions.

[0554] "Adjusting a digital character's responses based on emotional state" is the process of appropriately changing the content of information and advice provided by a digital character, taking into account the user's current emotions.

[0555] This invention is a system that provides personalized information and support based on the user's characteristics and emotional state. The user inputs their characteristic information using a terminal. A dedicated application or web interface is provided on the terminal, allowing the user to input information through personality tests or questionnaires.

[0556] The input information is sent from the terminal to the server. The server uses a generative AI model to process the received information. This model is pre-trained and analyzes the user's characteristics. Based on the analysis results, the server constructs an individualized digital persona. This digital persona has the ability to generate responses adapted to the user's characteristics.

[0557] Furthermore, the server operates an emotion engine to recognize the user's emotional state in real time. This engine analyzes emotions from voice tone and text to understand the user's psychological state. For example, if the user appears anxious, the engine recognizes this as "anxiety" and reflects it in the digital character's response.

[0558] The server also includes the ability to collect information from data sources on the data network. As needed, it retrieves industry-specific information and the latest data to provide users with the most relevant information. Furthermore, it receives user feedback and adjusts the parameters of the generated AI model to improve the accuracy and adaptability of the digital persona.

[0559] As a concrete example, consider a user who manages a project at work. When this user consults a digital figure through their terminal, the server considers the user's characteristics and emotional state, and provides suggestions and responses appropriate to the project's progress. For example, by using a prompt such as, "Please check my current stress level and provide appropriate solutions," the system can respond in a way that is tailored to the user's situation.

[0560] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0561] Step 1:

[0562] Users input their personal characteristics using a terminal. This input data consists of personality test results and questionnaires regarding behavioral patterns. This information is sent from the terminal to the server, where it is received by a data receiver.

[0563] Step 2:

[0564] The server processes the received characteristic information and analyzes the user's personality traits using a generative AI model. This model uses a pre-trained algorithm to create a personality profile. The input data is quantified, and the user's personality profile is output as the analysis result.

[0565] Step 3:

[0566] The server constructs an individualized digital persona based on the analysis results. This digital persona is a virtual agent designed to generate responses adapted to the user's characteristics. Here, the analyzed profile data is taken as input, and a set of behavioral rules for the digital persona is output.

[0567] Step 4:

[0568] The server activates an emotion engine to recognize the user's emotional state in real time. The user's voice or text messages are used as input, and the engine analyzes the tone and context of the voice to provide an output indicating the current emotional state. This output prompts special responses if psychological thresholds are exceeded.

[0569] Step 5:

[0570] The server uses emotional data obtained from the emotion engine to adjust the responses of the personalized digital character. Based on the emotional state and personality profile, it generates the optimal response. This response is then output directly to the terminal and presented to the user. As a result, the user receives an answer that is appropriate to their situation.

[0571] Step 6:

[0572] The server collects necessary additional information from information sources on the data network. This process identifies the most relevant information based on the user's situation and processes it through a generative AI model. If necessary, information from industry-specific databases is also retrieved and formatted for final presentation to the user.

[0573] Step 7:

[0574] The terminal presents the user with responses and information sent from the server. The user reviews the responses and provides feedback. This feedback is sent back to the server from the terminal and used to improve the generated AI model. This continuously improves the overall response accuracy and adaptability of the system.

[0575] (Application Example 2)

[0576] 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."

[0577] Conventional information systems have difficulty providing adaptive information that fully considers the user's personality and emotional state. This is particularly problematic in customer service at physical stores, where it is difficult to immediately provide services tailored to individual customer needs. Therefore, there is a need for an efficient system that accurately grasps the individual characteristics and emotions of users and provides appropriate suggestions based on that understanding.

[0578] 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.

[0579] In this invention, the server includes a device for inputting the user's individual characteristics information, a device for generating a user-specific virtual character based on the individual characteristics information, and a device for collecting information from a database on a communication network. This makes it possible to immediately provide customized suggestions that respond to the user's characteristics and emotions.

[0580] "Individual characteristic information" refers to data that shows the individual characteristics of a user, such as their personality, interests, and preferences.

[0581] A "virtual character" is a digital representation of a person generated based on the user's individual characteristics, and its role is to provide adaptive responses through interaction with the user.

[0582] A "database on a communication network" is a collection of information accessible via the internet, which stores information from various fields and provides it as needed.

[0583] "Emotional state" refers to the user's mental and emotional condition, and is data analyzed from facial expressions, tone of voice, and other factors.

[0584] A "device for displaying instructions to service providers" is a digital device that communicates appropriate responses and suggestions to service providers in real time, based on the customer's emotional state.

[0585] This invention is a system that provides personalized services based on the user's individual characteristics information. In the system, the server receives data from a terminal that inputs the user's individual characteristics information. The terminal includes a device such as smart glasses, and the user acquires information through interaction. Based on the received individual characteristics information, the server generates a specific virtual character. The virtual character has logic for generating adaptive responses according to the user's personality and emotional state.

[0586] A database on the communication network collects information highly relevant to the user, and the server passes this information to a virtual character to create customized suggestions. To analyze emotional states, voice analysis and facial recognition technologies are used. This involves facial recognition software such as OpenCV and speech libraries such as Google Cloud Speech-to-Text. Based on the emotional state, the server displays the suggestions and information obtained from the virtual character as appropriate instructions to the service provider.

[0587] As a concrete example, in a physical store, when a user is having trouble choosing a product, smart glasses can analyze their emotional state, and a server can suggest products to the user through a virtual character, saying, "How about this product?" The service provider can then be notified, "This customer may be interested in red wine." A generative AI model can then generate prompts such as, "What do you think the details of the product the customer is looking for are?"

[0588] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0589] Step 1:

[0590] The terminal allows users to input individual characteristic information through its interface. This information includes the user's personality, hobbies, and current emotional state. This input data is converted into a digital format and sent to the server.

[0591] Step 2:

[0592] The server receives individual characteristic information sent from the terminal and generates a user-specific virtual character using a generative AI model. This model calculates the optimal attributes of the virtual character based on the user's characteristic information and stores this information in a database. The output is a personalized virtual character profile.

[0593] Step 3:

[0594] The server accesses a database on the network to collect information related to the user's needs and interests. This database query is designed to extract the most relevant data based on the profile of the generated virtual character. The retrieved information is stored for use in the virtual character's response generation process.

[0595] Step 4:

[0596] As the user interacts with the device in real time, the terminal uses voice sensors and a camera to monitor the user's emotional state. Emotional data is acquired by analyzing the user's facial expressions and tone of voice, and is quickly transmitted to the server.

[0597] Step 5:

[0598] The server processes emotional state data, and based on a generative AI model, a virtual character generates an appropriate response to the user. This response combines the input emotional information with the virtual character's profile to output content optimized for the user's state.

[0599] Step 6:

[0600] The terminal displays the virtual character's response received from the server to the user. It also notifies the service provider of the instructions via the terminal. This makes it possible to provide customized services in real time, tailored to the user's emotional state.

[0601] 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.

[0602] 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.

[0603] 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.

[0604] [Fourth Embodiment]

[0605] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0606] 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.

[0607] 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).

[0608] 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.

[0609] 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.

[0610] 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).

[0611] 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.

[0612] 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.

[0613] 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.

[0614] 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.

[0615] 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.

[0616] 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.

[0617] 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".

[0618] This invention is a system that generates individually customized AI avatars based on the user's personality information and provides information optimized for the user. It is intended for corporate and individual users and can be used for business support, personal life planning, and learning support.

[0619] Overall flow

[0620] The user first inputs their personality assessment results and self-analysis results into an interface using their device, and this data is sent to the server. The server analyzes the received personality data and generates a user-specific avatar. This avatar has a conversational style and response logic that mimics the user's personality and behavioral patterns.

[0621] The server accesses a vast database on the internet and, for corporate clients, utilizes industry-specific information sources to collect information highly relevant to the user. Furthermore, based on this information, the avatar generates specific suggestions and solutions for the user and presents them to the user via the terminal. In this process, natural language generation technology is used to ensure that the information is presented in a way that is easy for the user to understand.

[0622] Specific example

[0623] For example, consider a scenario where a project manager at a company is facing challenges in managing a new project. The user explains the situation to an avatar on their device, and the server searches and collects industry trends and best practices for project management. The avatar then proposes strategies based on successful case studies of similar situations, listing the options and displaying them on the device. The user can then use this information to select a new approach.

[0624] Furthermore, if an individual user is considering their career path, the avatar will suggest occupational information and skill development methods that are suitable for the user's characteristics. This helps users to build their life plans more concretely.

[0625] The flexibility of this system is further enhanced by user feedback. The server continuously improves the avatars by collecting user responses. This feedback loop allows the system to provide more accurate information over time.

[0626] The following describes the processing flow.

[0627] Step 1:

[0628] The user accesses the device and enters their personality assessment results and personality information. The device receives this information and sends it to the server.

[0629] Step 2:

[0630] The server passes the received user personality information to the analysis engine, which then analyzes the data. This process extracts the user's personality traits and infers their behavioral patterns.

[0631] Step 3:

[0632] The server generates a user-specific AI avatar based on the analyzed data. This avatar features a conversational style and response logic tailored to the user's characteristics.

[0633] Step 4:

[0634] The server accesses the internet and industry-specific databases to collect necessary information, including the latest information and trends relevant to user needs.

[0635] Step 5:

[0636] The server integrates collected information with the user's personality data to enable the avatar to generate suggestions and responses tailored to the user. Natural language generation technology is used to ensure the responses are clear and easy to understand.

[0637] Step 6:

[0638] The server sends the generated suggestions and responses to the terminal. The terminal displays the received information on its user interface, presenting it to the user in a visually easy-to-understand manner.

[0639] Step 7:

[0640] The user makes a decision based on the displayed information and enters feedback into the device as needed. The device then sends this feedback to the server.

[0641] Step 8:

[0642] The server utilizes user feedback to improve the response accuracy of the AI ​​avatar. This will make future information delivery even more user-friendly.

[0643] (Example 1)

[0644] 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".

[0645] Conventional information provision systems have challenges in providing optimal information tailored to the individual needs and characteristics of users, and in not having a sufficient feedback loop to determine whether the information provided is beneficial to the user.

[0646] 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.

[0647] In this invention, the server includes a device for inputting user characteristic information, a device for generating a user-specific virtual agent based on the characteristic information, and a device for retrieving information from a database on a communication network. This makes it possible to dynamically provide information tailored to the user and to continuously improve the system based on feedback.

[0648] "User characteristic information" refers to data about individual characteristics of users, including their personality, preferences, and behavioral patterns.

[0649] A "virtual agent" is a digital character generated based on a user's characteristic information, possessing a conversational style and response logic specific to that user.

[0650] A "database on a communication network" is a digital storage system that stores diverse information and is accessible via the internet.

[0651] An "information retrieval device" is a system component that has the function of searching for and acquiring necessary information via a communication network.

[0652] "User response" refers to the actions and feedback that users show in response to information provided by the virtual agent.

[0653] A "device for evolution" is a system component that has the function of improving the virtual agent based on user feedback and enhancing its capabilities.

[0654] "Natural language form" refers to a form of expression based on human language that users can intuitively understand.

[0655] Embodiments of this invention will now be described. This system generates individually customized virtual agents based on the user's characteristic information and provides the user with information optimized for them. The user inputs characteristic information and self-analysis results using a terminal. This input is securely transmitted to the server through a data collection device.

[0656] The server analyzes the received characteristic information. This analysis utilizes natural language processing libraries and machine learning algorithms. Furthermore, based on the analysis results, the server generates a user-specific virtual agent. This agent possesses a conversational style that reflects the user's personality and behavioral patterns.

[0657] In information gathering, servers access databases and external APIs on the internet to retrieve highly relevant information. By utilizing scraping techniques and external APIs, new data and information tailored to user needs can be efficiently acquired. For corporate users, more specialized information is provided using specific industry information sources.

[0658] The virtual agent generates personalized suggestions for the user based on the collected information. Using natural language generation technology, complex information is transformed into a concise and easy-to-understand format, which is then displayed on the terminal screen. Users also provide feedback on the suggestions and information from the avatar, and the server continuously improves the virtual agent's performance based on this feedback.

[0659] As a concrete example, if a project manager at a company encounters a problem with a new project, they can explain the situation to a virtual agent via a terminal. The server then gathers information on project management best practices and market trends, and generates a solution strategy based on similar success stories. This makes it possible to list useful options for project progress and provide them to the project manager.

[0660] Furthermore, for individual users struggling with their career paths, a virtual agent provides personalized job information and skill development suggestions. This system can provide users with necessary advice by prompting them with phrases such as, "Please provide solutions to my project management problems," or "Please suggest a career path that suits me." Using such prompts allows users to utilize the system more intuitively.

[0661] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0662] Step 1:

[0663] Users input characteristic information via their device. Specifically, they input personality assessment results and self-analysis results into an interface on the device. This input data is securely transmitted to the server. The input data can take various forms, including text data and multiple-choice options.

[0664] Step 2:

[0665] The server receives the input trait information and analyzes it using natural language processing algorithms. This analysis involves data processing such as text sentiment analysis and feature extraction to identify the user's personality and behavioral patterns. As a result of this analysis, the trait information is extracted in a more detailed data format.

[0666] Step 3:

[0667] The server uses the analysis results to generate a user-specific virtual agent. Utilizing a generative AI model, the agent is created with a conversational style and response logic that mimics the user's characteristics. In this generation process, the dialogue model is constructed through data calculations.

[0668] Step 4:

[0669] The server accesses a database on the communication network and retrieves information related to the user. Specifically, it uses external APIs and information retrieval algorithms to obtain information that matches the user's needs. The retrieved information is compiled in list format and used for subsequent processing by the virtual agent.

[0670] Step 5:

[0671] The virtual agent generates suggestions for the user based on the collected information. Using natural language generation technology, the information is formatted in a way that is easy for the user to understand. The suggestions include options and specific measures, which are sent to the device and displayed visually.

[0672] Step 6:

[0673] The user reviews suggestions from the virtual agent and then makes their own selections and takes action. The user's responses are sent from the terminal to the server as feedback. This feedback data is recorded as information indicating user satisfaction and usage trends.

[0674] Step 7:

[0675] The server analyzes user feedback to improve the virtual agent. Machine learning techniques are used for continuous adjustments to optimize future user interactions. This improvement process enhances the system's accuracy and user adaptability.

[0676] (Application Example 1)

[0677] 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".

[0678] Modern consumers seek customized experiences tailored to their personality and preferences when selecting products and obtaining information. However, traditional systems struggle to provide information optimized for users, making it difficult to deliver a highly satisfying shopping experience. Therefore, there is a need for a system that provides consumers with individually customized product information visually and effectively when they visit a physical store.

[0679] 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.

[0680] In this invention, the server includes means for inputting user personality information, means for generating a virtual character specifically for the user based on the personality information, and means for suggesting product information tailored to the user's background via an application installed on a visual information device. This enables consumers to receive real-time recommendations for products that match their preferences in physical stores.

[0681] "User personality information" refers to data related to an individual's behavioral patterns and characteristics, including personality assessment results and self-analysis results.

[0682] A "user-specific virtual character" is a digital character generated based on the user's personality information, possessing a conversational style and response logic tailored specifically to that user.

[0683] A "digital network" is a computer network used by various devices to exchange information, and encompasses a wide range of communication systems, including the internet.

[0684] A "visual information device" is a device that provides visual information to the user, and includes equipment such as smart glasses and head-mounted displays.

[0685] "Industry-specific data" refers to data that contains information related to a particular industry and is used as a specialized knowledge base.

[0686] "Opinions" refer to subjective information such as feedback and impressions obtained from users, and are data that serves as clues for improving the system.

[0687] This invention provides a system that enables customized product recommendations based on user personality information in physical stores. This system consists of a user, a visual information device, and a server.

[0688] The server analyzes the personality information entered by the user and generates a virtual character specifically for that user. This virtual character has a conversational style tailored to the user and is responsible for providing purchase recommendations and information. Visual information devices such as smart glasses and head-mounted displays are used. This allows users to visually receive real-time product and sales information when visiting physical stores.

[0689] When a user enters a store wearing a visual information device, it connects to a server via a digital network. The server extracts relevant information from industry-specific data and generates recommendations based on the user's personality. These recommendations are provided in natural language and presented in a way that is easy for the user to understand. An application installed on the visual information device presents the collected information to the user in real time.

[0690] For example, when an outdoor enthusiast visits an outdoor equipment store, a virtual character recommends tents and backpacks with new features and offers advice such as, "They are highly durable and ideal for camping."

[0691] An example of a prompt message would be something like, "Please tell me how to approach customers who are interested in outdoor equipment. Please introduce products and trends related to adventure sports, durability, and camping."

[0692] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0693] Step 1:

[0694] The user enters their personality information using a terminal. The entered data, reflecting the user's personality traits, is sent to the server.

[0695] Input: User's personality information (personality test results, self-analysis results)

[0696] Output: Personality information data sent to the server

[0697] Step 2:

[0698] The server generates a virtual character specifically for the user based on the personality information it receives. The server uses a generation AI model to create a character with a conversational style and response logic tailored to the user's characteristics.

[0699] Input: User personality information data

[0700] Output: User-specific virtual character data

[0701] Step 3:

[0702] When a user enters a physical store wearing a visual information device (such as smart glasses), the terminal connects to a server and collects relevant information from an industry-specific database.

[0703] Input: Virtual character data, access to industry-specific databases

[0704] Output: User-related information data

[0705] Step 4:

[0706] Based on the collected information, the server uses an AI model generated by the user's virtual character to provide specialized recommendations and responses. It selects product information suitable for the user, referring to example prompts.

[0707] Input: Collected information data, virtual character data

[0708] Output: Recommended product information data

[0709] Step 5:

[0710] An application installed on a visual information device presents the user with generated recommended product information in real time. The user visually receives the information, which is provided in natural language.

[0711] Input: Recommended product information data

[0712] Output: Visual information presentation to the user

[0713] 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.

[0714] This invention is a system that provides more personalized and adaptive information by combining customization based on the user's personality with an emotion engine that recognizes the user's emotions. This system can be widely used, from supporting business operations in companies to providing advice on individuals' daily lives.

[0715] Overall flow

[0716] The system begins with the user using a terminal to input their personality information. The terminal sends this information to a server. The server analyzes the user's characteristics based on the received personality information and constructs an avatar accordingly. This avatar has the ability to create responses that are in line with the user's personality traits and behaviors.

[0717] Next, the server uses an emotion engine to recognize the user's emotions during user interaction. The emotion engine analyzes the user's emotional state in real time from factors such as voice tone, text expression, and changes in interaction patterns. For example, if the user is feeling stressed, the engine detects this and provides emotion data to the server.

[0718] The server takes into account the user's emotions, as recognized by the emotion engine, and adaptively adjusts the avatar's responses. These responses can include words to help the user relax and necessary guidance. It also gathers up-to-date data from a broad knowledge base, including industry-specific information, to present users with highly relevant information.

[0719] Specific example

[0720] For example, suppose a user managing a complex project at work consults an avatar about the project's progress. In this case, the server senses the user's stress level from their language and facial expressions, and the emotion engine analyzes this information. As a result, the avatar generates a response that includes words of encouragement and suggestions for changing the mood, and presents it to the user through the device.

[0721] On the other hand, if an individual user is struggling with life planning, the emotion engine accurately captures the user's hopes and anxieties, and the server provides advice and emotional support tailored to those emotions. Through this process, users can not only gather information but also receive emotional support.

[0722] This system improves the accuracy of its AI avatar and emotion engine by receiving feedback from users. As a result, the system will be able to provide increasingly user-adapted interactions over time.

[0723] The following describes the processing flow.

[0724] Step 1:

[0725] The user uses a terminal to input their personality assessment results and personality information. The terminal then formats this information into a data format and sends it to the server.

[0726] Step 2:

[0727] The server analyzes the received user personality information and extracts the user's personality traits. Based on this trait data, it generates a user-specific AI avatar. The avatar has a flexible response profile tailored to the user's characteristics.

[0728] Step 3:

[0729] The device transmits voice and text data obtained through user interaction to the emotion engine. The emotion engine evaluates the user's emotional state based on their tone, word choice, and facial expressions.

[0730] Step 4:

[0731] The emotion engine sends analysis results to the server, providing real-time data on the user's emotional state. The server analyzes this data to understand the user's emotional state.

[0732] Step 5:

[0733] The server combines the user's personality information and emotional data to customize the AI ​​avatar's responses. These responses include expressions of consideration and appropriate suggestions that reflect the user's emotions.

[0734] Step 6:

[0735] The server sends the generated avatar's response to the terminal. The terminal displays this response on its user interface and provides it to the user.

[0736] Step 7:

[0737] Users decide on actions based on suggestions and responses and provide feedback through their devices. The devices then send the collected feedback to the server.

[0738] Step 8:

[0739] The server optimizes the emotion engine and AI avatar based on user feedback data to improve system accuracy. This process is repeated regularly to continuously improve the user experience.

[0740] (Example 2)

[0741] 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".

[0742] In today's information society, providing personalized information and support to users is crucial. However, conventional systems have struggled to provide adaptive responses that adequately consider users' personalities and emotional states. As a result, users often felt dissatisfied with the system's suggestions and responses, and perceived the information as lacking relevance and usefulness. Therefore, there is a need for new systems that can provide more personalized and adaptive information based on user characteristics and emotional states.

[0743] 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.

[0744] In this invention, the server includes means for inputting user characteristics, means for generating an individualized digital person based on the characteristic information, means for collecting information from information sources on a data network, means for the digital person to generate suggestions and responses adapted to the user, means for recognizing the user's emotional state in real time, and means for adjusting the digital person's responses based on the emotional state. This enables the provision of precise information and emotional support tailored to the user's individual needs.

[0745] "User characteristics" refer to information about the user's personality and behavioral patterns that the system uses to generate personalized responses.

[0746] A "personalized digital person" is a virtual agent built based on the user's characteristics to provide appropriate responses in interactions with the user.

[0747] "Information sources on data networks" refer to knowledge bases and collections of information accessible via the internet, and serve as a medium for obtaining necessary data.

[0748] "User emotional state" refers to data that the system analyzes in real time through voice and text, indicating the user's psychological situation and emotions.

[0749] "Adjusting a digital character's responses based on emotional state" is the process of appropriately changing the content of information and advice provided by a digital character, taking into account the user's current emotions.

[0750] This invention is a system that provides personalized information and support based on the user's characteristics and emotional state. The user inputs their characteristic information using a terminal. A dedicated application or web interface is provided on the terminal, allowing the user to input information through personality tests or questionnaires.

[0751] The input information is sent from the terminal to the server. The server uses a generative AI model to process the received information. This model is pre-trained and analyzes the user's characteristics. Based on the analysis results, the server constructs an individualized digital persona. This digital persona has the ability to generate responses adapted to the user's characteristics.

[0752] Furthermore, the server operates an emotion engine to recognize the user's emotional state in real time. This engine analyzes emotions from voice tone and text to understand the user's psychological state. For example, if the user appears anxious, the engine recognizes this as "anxiety" and reflects it in the digital character's response.

[0753] The server also includes the ability to collect information from data sources on the data network. As needed, it retrieves industry-specific information and the latest data to provide users with the most relevant information. Furthermore, it receives user feedback and adjusts the parameters of the generated AI model to improve the accuracy and adaptability of the digital persona.

[0754] As a concrete example, consider a user who manages a project at work. When this user consults a digital figure through their terminal, the server considers the user's characteristics and emotional state, and provides suggestions and responses appropriate to the project's progress. For example, by using a prompt such as, "Please check my current stress level and provide appropriate solutions," the system can respond in a way that is tailored to the user's situation.

[0755] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0756] Step 1:

[0757] Users input their personal characteristics using a terminal. This input data consists of personality test results and questionnaires regarding behavioral patterns. This information is sent from the terminal to the server, where it is received by a data receiver.

[0758] Step 2:

[0759] The server processes the received characteristic information and analyzes the user's personality traits using a generative AI model. This model uses a pre-trained algorithm to create a personality profile. The input data is quantified, and the user's personality profile is output as the analysis result.

[0760] Step 3:

[0761] The server constructs an individualized digital persona based on the analysis results. This digital persona is a virtual agent designed to generate responses adapted to the user's characteristics. Here, the analyzed profile data is taken as input, and a set of behavioral rules for the digital persona is output.

[0762] Step 4:

[0763] The server activates an emotion engine to recognize the user's emotional state in real time. The user's voice or text messages are used as input, and the engine analyzes the tone and context of the voice to provide an output indicating the current emotional state. This output prompts special responses if psychological thresholds are exceeded.

[0764] Step 5:

[0765] The server uses emotional data obtained from the emotion engine to adjust the responses of the personalized digital character. Based on the emotional state and personality profile, it generates the optimal response. This response is then output directly to the terminal and presented to the user. As a result, the user receives an answer that is appropriate to their situation.

[0766] Step 6:

[0767] The server collects necessary additional information from information sources on the data network. This process identifies the most relevant information based on the user's situation and processes it through a generative AI model. If necessary, information from industry-specific databases is also retrieved and formatted for final presentation to the user.

[0768] Step 7:

[0769] The terminal presents the user with responses and information sent from the server. The user reviews the responses and provides feedback. This feedback is sent back to the server from the terminal and used to improve the generated AI model. This continuously improves the overall response accuracy and adaptability of the system.

[0770] (Application Example 2)

[0771] 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".

[0772] Conventional information systems have difficulty providing adaptive information that fully considers the user's personality and emotional state. This is particularly problematic in customer service at physical stores, where it is difficult to immediately provide services tailored to individual customer needs. Therefore, there is a need for an efficient system that accurately grasps the individual characteristics and emotions of users and provides appropriate suggestions based on that understanding.

[0773] 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.

[0774] In this invention, the server includes a device for inputting the user's individual characteristics information, a device for generating a user-specific virtual character based on the individual characteristics information, and a device for collecting information from a database on a communication network. This makes it possible to immediately provide customized suggestions that respond to the user's characteristics and emotions.

[0775] "Individual characteristic information" refers to data that shows the individual characteristics of a user, such as their personality, interests, and preferences.

[0776] A "virtual character" is a digital representation of a person generated based on the user's individual characteristics, and its role is to provide adaptive responses through interaction with the user.

[0777] A "database on a communication network" is a collection of information accessible via the internet, which stores information from various fields and provides it as needed.

[0778] "Emotional state" refers to the user's mental and emotional condition, and is data analyzed from facial expressions, tone of voice, and other factors.

[0779] A "device for displaying instructions to service providers" is a digital device that communicates appropriate responses and suggestions to service providers in real time, based on the customer's emotional state.

[0780] This invention is a system that provides personalized services based on the user's individual characteristics information. In the system, the server receives data from a terminal that inputs the user's individual characteristics information. The terminal includes a device such as smart glasses, and the user acquires information through interaction. Based on the received individual characteristics information, the server generates a specific virtual character. The virtual character has logic for generating adaptive responses according to the user's personality and emotional state.

[0781] A database on the communication network collects information highly relevant to the user, and the server passes this information to a virtual character to create customized suggestions. To analyze emotional states, voice analysis and facial recognition technologies are used. This involves facial recognition software such as OpenCV and speech libraries such as Google Cloud Speech-to-Text. Based on the emotional state, the server displays the suggestions and information obtained from the virtual character as appropriate instructions to the service provider.

[0782] As a concrete example, in a physical store, when a user is having trouble choosing a product, smart glasses can analyze their emotional state, and a server can suggest products to the user through a virtual character, saying, "How about this product?" The service provider can then be notified, "This customer may be interested in red wine." A generative AI model can then generate prompts such as, "What do you think the details of the product the customer is looking for are?"

[0783] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0784] Step 1:

[0785] The terminal allows users to input individual characteristic information through its interface. This information includes the user's personality, hobbies, and current emotional state. This input data is converted into a digital format and sent to the server.

[0786] Step 2:

[0787] The server receives individual characteristic information sent from the terminal and generates a user-specific virtual character using a generative AI model. This model calculates the optimal attributes of the virtual character based on the user's characteristic information and stores this information in a database. The output is a personalized virtual character profile.

[0788] Step 3:

[0789] The server accesses a database on the network to collect information related to the user's needs and interests. This database query is designed to extract the most relevant data based on the profile of the generated virtual character. The retrieved information is stored for use in the virtual character's response generation process.

[0790] Step 4:

[0791] As the user interacts with the device in real time, the terminal uses voice sensors and a camera to monitor the user's emotional state. Emotional data is acquired by analyzing the user's facial expressions and tone of voice, and is quickly transmitted to the server.

[0792] Step 5:

[0793] The server processes emotional state data, and based on a generative AI model, a virtual character generates an appropriate response to the user. This response combines the input emotional information with the virtual character's profile to output content optimized for the user's state.

[0794] Step 6:

[0795] The terminal displays the virtual character's response received from the server to the user. It also notifies the service provider of the instructions via the terminal. This makes it possible to provide customized services in real time, tailored to the user's emotional state.

[0796] 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.

[0797] 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.

[0798] 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 robot 414.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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."

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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.

[0814] 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.

[0815] 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.

[0816] 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 to be incorporated by reference.

[0817] The following is further disclosed regarding the embodiments described above.

[0818] (Claim 1)

[0819] A means of inputting user personality information,

[0820] A means for generating a user-specific avatar based on the aforementioned personality information,

[0821] Methods for gathering information from knowledge bases on the internet,

[0822] The means by which the aforementioned avatar generates customized suggestions and responses for the user,

[0823] Means of presenting collected information to the user,

[0824] A system that includes this.

[0825] (Claim 2)

[0826] The system according to claim 1, characterized by including means for using industry-specific information as a knowledge base.

[0827] (Claim 3)

[0828] The system according to claim 1, characterized by including means for improving the avatar based on user feedback.

[0829] "Example 1"

[0830] (Claim 1)

[0831] A device for inputting user characteristic information,

[0832] A device that generates a user-specific virtual agent based on the aforementioned characteristic information,

[0833] A device for retrieving information from a database on a communication network,

[0834] The aforementioned virtual agent is a device that generates suggestions and responses adapted to the user,

[0835] A device that presents the collected information to the user,

[0836] A device for collecting user responses,

[0837] A device for evolving the virtual agent based on the above reaction,

[0838] A system that includes this.

[0839] (Claim 2)

[0840] The system according to claim 1, comprising a device that uses field-specific information as a database.

[0841] (Claim 3)

[0842] The system according to claim 1, comprising a device that provides the generated response in natural language format.

[0843] "Application Example 1"

[0844] (Claim 1)

[0845] A means of inputting user personality information,

[0846] Means for generating a user-specific virtual character based on the aforementioned personality information,

[0847] Means of collecting information from databases on digital networks,

[0848] The aforementioned virtual character provides a means for generating user-specific recommendations and responses,

[0849] The means of presenting the collected information to the user,

[0850] A means of suggesting product information tailored to the user's background via an application installed on a visual information device,

[0851] A system that includes this.

[0852] (Claim 2)

[0853] The system according to claim 1, characterized by including means for using industry-specific data as a knowledge base.

[0854] (Claim 3)

[0855] The system according to claim 1, characterized by including means for improving a virtual character based on user feedback.

[0856] "Example 2 of combining an emotion engine"

[0857] (Claim 1)

[0858] A means of inputting user characteristics,

[0859] Means for generating an individualized digital person based on the aforementioned characteristic information,

[0860] Means for collecting information from information sources on a data network,

[0861] The means by which the aforementioned digital person generates suggestions and responses adapted to the user,

[0862] Means of presenting collected information to the user,

[0863] A means of recognizing the user's emotional state in real time,

[0864] Means for adjusting the response of a digital character based on the aforementioned emotional state,

[0865] A system that includes this.

[0866] (Claim 2)

[0867] The system according to claim 1, characterized in that it uses industry-specific information as a source of information.

[0868] (Claim 3)

[0869] The system according to claim 1, characterized in that it improves the digital character based on user feedback.

[0870] "Application example 2 when combining with an emotional engine"

[0871] (Claim 1)

[0872] A device for inputting individual user characteristics information,

[0873] A device that generates a user-specific virtual character based on the aforementioned individual characteristic information,

[0874] A device that collects information from a database on a communication network,

[0875] The aforementioned virtual character generates suggestions and answers adapted to the user,

[0876] A device that displays the collected information to the user,

[0877] A device that analyzes the emotional state of customers,

[0878] A device that displays instructions to the service provider based on the customer's emotional state,

[0879] A system that includes this.

[0880] (Claim 2)

[0881] The system according to claim 1, characterized in that it uses industry-specific information as a database.

[0882] (Claim 3)

[0883] The system according to claim 1, characterized in that it adjusts the virtual character based on user evaluations. [Explanation of symbols]

[0884] 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 means of inputting user personality information, A means for generating a user-specific avatar based on the aforementioned personality information, Methods for gathering information from knowledge bases on the internet, The means by which the aforementioned avatar generates customized suggestions and responses for the user, Means of presenting collected information to the user, A system that includes this.

2. The system according to claim 1, characterized by including means for using industry-specific information as a knowledge base.

3. The system according to claim 1, characterized by including means for improving the avatar based on user feedback.

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