system

Abstract

We provide the system. [Solution] Means for acquiring and storing user information, A means for analyzing the aforementioned user information and extracting individual personality traits, A means for generating a character optimized for an individual based on the aforementioned personality traits, Means for providing communication between the generated character and the user for interaction, A means for analyzing the information during the aforementioned dialogue and optimizing the generation algorithm, 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 and includes 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] Conventional idle fan activities have problems that it is difficult to have deep individual communication due to the physical distance and time constraints between users and idols. In addition, since it is impossible to provide an individually optimized experience based on the diverse hobbies of users, there is a limit to the satisfaction of fan activities. Therefore, there is a need for advanced personalized communication that meets the individual needs of users.

Means for Solving the Problems

[0005] This invention provides a means for acquiring user information and extracting individual personality traits based on that information. Furthermore, it includes real-time communication means to enable the character generated based on the personality traits to interact with the user and facilitate deeper interaction. As a result, users can enjoy an interactive experience with an individually optimized idol, thereby improving user satisfaction.

[0006] "User information" refers to data about an individual's attributes and preferences that the system collects from the user, including gender, age, region, hobbies, and educational background.

[0007] "Personality traits" refer to characteristics related to the personality and preferences of individual users, extracted by analyzing user information.

[0008] A "character" refers to a virtual personality and its behavior that is optimized for the user, generated based on the user's personality traits.

[0009] A "generative model" is an algorithm or software that generates characters based on user information and personality traits, and provides a format for interaction through these characters.

[0010] "Real-time communication" refers to an interface and communication method designed to allow users and generated characters to exchange information in real time, enabling smooth conversations. [Brief explanation of the drawing]

[0011] [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]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the 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.

[0015] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the 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.

[0017] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), and the like.

[0018] 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."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] 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.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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".

[0032] The system for implementing this invention operates between three parties: the user, the terminal, and the server. The main functions of the system are to collect user information, extract personality traits, generate individually optimized characters, and enable real-time communication with the user.

[0033] First, the user launches a dedicated application on their device and enters the necessary personal information. This information includes gender, age, place of origin, hobbies and interests, and educational background. The device then sends this data to the server.

[0034] The server stores the received information in a database and uses an analysis engine to analyze the personality traits of individual users. This extracts the user's hobbies and preferences, revealing their specific interests and concerns.

[0035] Next, the server generates a character optimized for the user based on these personality traits. This character has a personality that aligns with the user's individuality and preferences, and its speaking style and topics of interest are pre-configured.

[0036] The user restarts the conversation session via the terminal and interacts with a character provided by the server. This process involves real-time responses to user input. The server uses an AI model to appropriately answer user questions and statements.

[0037] For example, if a user enjoys movies, the generated character will engage in conversation incorporating the latest movie information, deepening the interaction with the user. If the user talks about their travel destination, the server will provide relevant tourist information and recommended spots through the character.

[0038] Thus, the system implementing the invention enables an interactive experience with a character individually optimized for the user, significantly improving user satisfaction.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] Users launch a dedicated application on their device and enter personal information such as gender, age, place of origin, hobbies and interests, and educational background. This data forms the basis of their user profile.

[0042] Step 2:

[0043] The terminal securely transmits the entered user information to the server. The server stores the received information in a database and records it as each user's profile.

[0044] Step 3:

[0045] The server processes the stored user information through an analysis engine to extract individual personality traits. These traits include the user's hobbies, preferences, and past behavioral patterns.

[0046] Step 4:

[0047] Based on the analysis results, the server generates a character optimized for the user. This character reflects the user's personality traits and possesses specific speaking styles and knowledge of certain topics.

[0048] Step 5:

[0049] The user initiates a conversation session on their device. The device sends a session start request to the server and prepares to summon the generated character.

[0050] Step 6:

[0051] The server sends the generated character to the user's terminal and begins real-time communication with the user. The server then analyzes the user's input using the character and generates an appropriate response in real time.

[0052] Step 7:

[0053] The terminal displays the response received from the server to the user and waits for further input from the user. This loop allows for smooth interaction between the user and the character.

[0054] Step 8:

[0055] The server analyzes log data and learns user interests and responses through the conversation history. Based on this data, the AI ​​model is continuously improved to provide more sophisticated communication in the future.

[0056] (Example 1)

[0057] 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."

[0058] Modern information processing systems require communication tailored to individual user needs and preferences based on the information they provide. However, existing systems suffer from insufficient customization of information to suit individual user personalities and preferences, and also struggle with flexible, real-time responses. Furthermore, there is a need for secure processing of user information and continuous optimization of dialogue content.

[0059] 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.

[0060] In this invention, the server includes means for acquiring user information and securely transmitting said user information to a processing device, means for storing said user information in a data storage device, and means for processing said user information to extract individual personality traits. This enables flexible, secure, and real-time communication that is tailored to the individuality of each user.

[0061] "User information" refers to data provided by users that includes personal identification, developmental stage, location, preferences, educational background, and other relevant information.

[0062] "Means of securely transmitting data to a processing unit" refers to methods of encrypting data to prevent unauthorized access by third parties via the network while ensuring it reaches its destination.

[0063] A "data storage device" is a storage device used to store data such as received information and analysis results for the long term.

[0064] "Methods for extracting personality traits" refer to processing methods that analyze user-provided information to identify an individual's personality and behavioral patterns.

[0065] "Personalized representation" refers to a unique, personalized format of information that is designed based on the user's characteristics and preferences.

[0066] "Information exchange communication" refers to interfaces and protocols for the bidirectional exchange of information between users and systems.

[0067] "Means for adaptively adjusting the generation method" refers to processes for dynamically changing the system's response and the parameters of the generation algorithm based on the content of the dialogue and user feedback.

[0068] This invention is implemented using an information processing system that operates between three parties: a user, a terminal, and a server. This section explains how the user utilizes the system and how the terminal and server cooperate to achieve its functions.

[0069] First, the user installs a dedicated software application on their device. This application provides an interface for collecting the user's personal information. Specific information collected includes the user's name, age, gender, preferences, and location. The user enters this information into the device. During this process, the device formats and encrypts the data and securely transmits it to a server via the internet.

[0070] The server stores the received data using database software. For example, it can use MySQL®, an open-source database management system. The server then uses data mining software to analyze the received user information. Here, it executes algorithms that utilize natural language processing techniques to identify the user's personality and preferences. This process extracts the user's individual personality traits.

[0071] Subsequently, the server uses a generative AI model to generate a virtual character optimized for the user's personality traits. This character is constructed based on the user's hobbies and interests, and possesses appropriate topics and speaking styles. Specifically, it leverages the latest natural language generation models to generate conversations with the user in real time.

[0072] When a user initiates a conversation session via their device, the server interacts with the user through a generated character. For example, if the user types "Tell me some recent movie recommendations," a character created using a generative AI model will respond, "My recent movie recommendation is 'Future World.' I recommend you watch it." This response includes the prompt, "When a user asks about recent movies, include the title of a recently released movie in your answer."

[0073] This system allows users to enjoy a personalized experience, and enables servers to respond to user needs securely and efficiently.

[0074] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0075] Step 1:

[0076] The user launches an application on their device and enters personal information. This information includes name, age, gender, hobbies, and location. The device formats and encrypts this information before securely sending it to the server. The input is personal information from the user interface, and the output is encrypted data.

[0077] Step 2:

[0078] The server receives encrypted data sent from the terminal and decrypts it. The decrypted data is then stored in a database, and storage processing is performed. The input is encrypted data, and the output is user information stored in the database. Specifically, storage is performed using a database management system.

[0079] Step 3:

[0080] The server starts data analysis using the stored user information. This analysis employs algorithms that utilize natural language processing techniques to identify the user's personality and preferences. The input is user information from the database, and the output is analysis data that shows the user's personality traits.

[0081] Step 4:

[0082] The server uses a generative AI model to generate a virtual character optimized for the user based on the analyzed data. This character will have topics of conversation and speaking style based on the user's hobbies and interests. The input is the user's personality trait data, and the output is the profile of the generated character.

[0083] Step 5:

[0084] The user initiates a conversation session using a terminal. The terminal sends a conversation request to the server, which then provides real-time interaction with the user through a generated character. The input is the conversation start request from the user, and the output is the dialogue content accompanied by the character.

[0085] Step 6:

[0086] The server uses a generative AI model during conversation to generate appropriate responses to user inquiries. For example, if a user asks, "What are some recent movie recommendations?", the character will respond, "My recent movie recommendation is 'Future World.' I recommend you watch it." The input is the user's question, and the output is the generated response. This response includes pre-configured prompts.

[0087] (Application Example 1)

[0088] 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."

[0089] Traditional in-store customer service often fails to adequately consider individual customer preferences, leading to decreased customer satisfaction and purchase intent. Furthermore, providing personalized service to each customer requires a massive amount of manpower and is inefficient. Additionally, real-time information provision is difficult, and there is a demand for rapid service delivery that keeps pace with the times. Therefore, the challenge lies in realizing a system that enables information provision and dialogue based on individual customer preferences.

[0090] 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.

[0091] In this invention, the server includes means for acquiring and storing user information, means for extracting individual personality traits, means for generating a character optimized for the individual, and means for providing a process for recommending products based on the preferences of in-store customers. This enables personalized customer service tailored to the customer's tastes and preferences in real time.

[0092] "User information" refers to information such as gender, age, region, preferences, and educational background that is collected through the device and used to extract individual personality characteristics.

[0093] "Personality traits" are analytical results that reveal a user's hobbies, preferences, and specific interests, and serve as the foundation for generating a character optimized for that individual.

[0094] A "character" is an artificial intelligence that is generated based on the user's personality traits and possesses a personality that enables interactive dialogue with the user.

[0095] "Communication" refers to the digital means provided for generated characters and users to exchange information in real time.

[0096] A "process" is a series of steps taken to provide appropriate product information within a store, based on the user's individual tastes and preferences.

[0097] A "generation algorithm" is a method for controlling character generation and product recommendation processes that are optimized based on information obtained through interaction with users.

[0098] A "system" is a collection of devices or programs that consistently perform tasks ranging from acquiring user information and generating characters to communicating and interacting, analyzing information, and optimizing generation algorithms.

[0099] The system implementing this invention operates smoothly between the user, terminal, and server. The terminal, such as smart glasses or a tablet, is used as a device for inputting user information. The user uses a dedicated application to input personal information such as gender, age, location, hobbies, and educational background into the terminal.

[0100] The servers are located in a cloud environment, specifically AWS® or Google® Cloud Platform. When the server receives user information, it stores that information in a database and uses an analysis engine to extract individual personality traits. At this time, generative AI models such as Google Cloud AI are used to generate a character that is optimal for each individual user. The generated character is constructed based on the user's personality, conversation style, and interests.

[0101] Users can initiate interactions with generated characters through their devices. The server uses an AI model to generate real-time responses to user input. In particular, within stores, a process is implemented to provide product information and promotions based on individual customer preferences.

[0102] For example, if a customer visiting a sporting goods store is interested in cycling equipment, a list of cycling-related products and promotional information will be displayed on the smart glasses screen. An example of a prompt message sent to the server in this case would be, "Show recommended products based on the customer's interests and tell me about current promotions."

[0103] In this way, the system can provide customers with a individually optimized purchasing experience, thereby improving customer satisfaction.

[0104] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0105] Step 1:

[0106] Users launch a dedicated application using smart glasses or a tablet device and enter personal information such as gender, age, address, hobbies, and educational background. This information is transmitted from the device to the server as user data. The role of the device is to collect and transmit user data.

[0107] Step 2:

[0108] The server stores the received user information data in a database. Next, it uses an analysis engine based on the collected data to extract the user's personality traits. It analyzes the input information, performs data analysis to extract characteristics related to hobbies and preferences, and stores the extraction results on the server.

[0109] Step 3:

[0110] The server uses a generative AI model to generate a character optimized for the individual, based on the extracted personality traits. The generated character is designed with a conversational style and interests based on that personality. The model takes trait data as input and generates a custom character as output.

[0111] Step 4:

[0112] The user initiates an interaction with a character generated via the device. The device receives the user's utterances and inputs, sends the content to the server, and receives a response in real time. The interaction process here generates immediate responses based on the input questions and conversation content.

[0113] Step 5:

[0114] The server presents store products and promotional information to the user through a character. In doing so, it utilizes prompt messages to provide information based on the user's individual tastes and preferences. It accesses the product database, processes information on the target product to generate content tailored to the user, and returns the information to the terminal.

[0115] Step 6:

[0116] In stores such as sporting goods shops, users can use smart glasses to check product information and receive recommended purchase options through interactions with characters. This allows users to have a shopping experience based on their interests.

[0117] 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.

[0118] This invention is a system that integrates user information collection, personality trait extraction, character generation, real-time communication, and user emotion recognition using an emotion engine. This system communicates with the user, terminal, and server.

[0119] Users access a dedicated application from their own devices and input information such as gender, age, region, preferences, and educational background. In addition, they can express emotions through voice and text during conversations. The device sends this information to a server, which uses an analysis engine to extract each user's personality traits based on the information stored in the database.

[0120] Next, the server generates individually optimized characters based on personality traits. These characters are designed to respond appropriately to user input during real-time conversations. Furthermore, an emotion engine can identify emotions from the nuances of the user's voice and text. The emotion engine analyzes voice tone and word choice to infer the user's emotional state.

[0121] The user initiates a conversation session. The server sends a generated character to the user's device, enabling real-time communication. During this time, the emotion engine continuously recognizes emotions, and the server adjusts the AI ​​model's responses accordingly. For example, if the user feels they are not getting the information they need, the system will try to offer more help. Conversely, if the user is satisfied, the character will continue to enjoy the conversation.

[0122] This wearable feedback allows user emotional information to be incorporated into the AI ​​model's learning process, continuously improving it to provide a better conversational experience. Through this process, users can always enjoy interactions tailored to their own emotions and interests.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The user launches a dedicated application on their device and enters personal information, including gender, age, region, preferences, and educational background. The device then prepares to send this information to the server.

[0126] Step 2:

[0127] The terminal sends the acquired user information to the server according to the security protocol. The server stores the received information in a database and generates a user profile.

[0128] Step 3:

[0129] The server processes the stored data using an analysis engine to extract the user's personality traits. These traits are related to the user's hobbies and preferences.

[0130] Step 4:

[0131] The server generates a character optimized for the user based on the extracted personality traits. This character is designed to have its own unique way of speaking and areas of interest.

[0132] Step 5:

[0133] The user initiates a conversation session using their device. The device sends this request to the server, which then prepares for the conversation.

[0134] Step 6:

[0135] The server sends the prepared character information to the terminal and begins real-time communication with the user. At this time, the emotion engine is activated and analyzes the user's emotional state in real time.

[0136] Step 7:

[0137] The terminal receives voice and text input from the user and sends it to the server. The server's emotion engine analyzes this data and recognizes the user's emotional state.

[0138] Step 8:

[0139] The server adjusts the character's responses based on the analysis results of the emotion engine. For example, if the user is unhappy, the character's responses will be changed to alleviate that dissatisfaction.

[0140] Step 9:

[0141] The terminal displays a pre-arranged response to the user and accepts the next input. This loop maintains a natural and dynamic dialogue between the user and the character.

[0142] (Example 2)

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

[0144] In modern communication, there is a need to accurately understand users' individual personality traits and real-time emotional states, and to provide digital agents optimized based on that understanding. However, conventional systems struggle to effectively analyze diverse user information and dynamically adjust responses. Therefore, there is a need to provide technologies that enable personalized conversational experiences.

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

[0146] In this invention, the server includes means for collecting user information and storing it in a data storage device, means for analyzing the user information and extracting individual personality traits, and means for generating a personalized digital agent based on the personality traits. This enables interaction with a digital agent optimized for each individual user.

[0147] "User information" refers to data including demographic information and behavioral preferences related to individual users.

[0148] A "data storage device" is an electronic storage medium for securely and efficiently storing user information.

[0149] "Analysis" is the process of thoroughly examining collected user information and extracting specific patterns and characteristics.

[0150] "Personality traits" are psychological or behavioral characteristics that represent the individuality of a user.

[0151] A "digital agent" is an interactive program that runs on a computer and is generated based on the user's personality traits.

[0152] A "communication environment" is a network infrastructure that enables digital agents and users to send and receive data to and from each other.

[0153] "Emotional data" refers to information collected from a user's voice and text that indicates their current emotional state.

[0154] A "generative computation model" is an algorithm or system that generates responses from a digital agent by utilizing user information and sentiment data.

[0155] This invention provides a system that offers users personalized digital agents and enables real-time communication. The system is realized through the cooperation of the user's terminal, a server, and a communication network.

[0156] Users access a dedicated application using devices such as smartphones or computers. Through this application, they can input demographic information such as gender, age, region, preferences, and educational background. Users can also express their emotions through voice or text, and this information is collected as user data.

[0157] The terminal is responsible for transmitting collected user information to the server. The server securely stores this information using an advanced database system. The stored data forms the basis for the analysis process.

[0158] The server utilizes an analysis engine to extract individual personality traits from stored user information. Machine learning algorithms are used for the analysis to highlight specific personality characteristics.

[0159] Next, the server uses a generative AI model to generate a digital agent based on the extracted personality traits. This digital agent incorporates natural language processing techniques to enable smooth interaction with the user.

[0160] Once a user starts a session, they can interact with a digital agent in real time through their device. The server uses an emotion engine to identify emotion data from the user's voice and text during the conversation. This allows the server to dynamically adjust its generative computation model to generate appropriate responses based on the user's emotional state.

[0161] As a concrete example, consider a scenario where a user is seeking movie recommendations. When the user inputs "I'd like to watch a funny movie recently," the server analyzes the information and generates an appropriate digital agent. The agent then provides a response such as, "A recent popular comedy movie recommendation is..."

[0162] Examples of prompts to input into a generative AI model:

[0163] "The user appears tired and is looking for relaxing music. Please recommend relaxing music and provide a calming response."

[0164] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0165] Step 1:

[0166] Users launch a dedicated application on their device and enter user information such as gender, age, region, preferences, and educational background. This input is converted into structured data by the application and temporarily stored on the device.

[0167] Step 2:

[0168] The terminal sends user information to the server. The data is encrypted and securely transferred via the HTTPS protocol. The server stores the received data in a database. The stored data is then used in subsequent analysis processes.

[0169] Step 3:

[0170] The server inputs user information stored in the database into the analysis engine and extracts individual personality traits. The analysis engine uses machine learning algorithms to identify traits based on the user's input data. As an output of this process, a user personality trait profile is generated.

[0171] Step 4:

[0172] The server generates digital agents using a generative AI model based on personality trait profiles. This generative AI model utilizes natural language processing techniques to provide appropriate conversational capabilities tailored to the user's characteristics. Information about the generated digital agents is stored on the server and prepared for user sessions.

[0173] Step 5:

[0174] The user sends a session start command to the server via their device. The server sends a digital agent to the user's device and begins real-time communication with the user. User input (text or voice) is sent from the device to the server.

[0175] Step 6:

[0176] The server inputs the user's voice and text received in real time into the emotion engine. The emotion engine analyzes the tone and language choices to infer the user's emotional state. The output from this process is the user's emotional data.

[0177] Step 7:

[0178] The server adjusts the output of the generative computation model based on emotional data. By optimizing the digital agent's response to match the user's emotions, a natural and comfortable conversation is achieved.

[0179] (Application Example 2)

[0180] 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".

[0181] When users search for information, they often face the challenge of not receiving support tailored to their individual needs and emotional states. In particular, when selecting and purchasing products in a virtual environment, the lack of information that matches the user's preferences and emotional reactions at the time can lead to problems in making effective purchasing decisions.

[0182] 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.

[0183] In this invention, the server includes means for acquiring and storing user information, means for analyzing user information to extract individual personality traits, means for generating a character optimized for the individual and dynamically adjusting the support content according to the user's emotional state, and means for providing product recommendations based on the user's emotions and past purchase history within a virtual environment. This enables the user to receive appropriate information and product suggestions that match their needs and emotions.

[0184] "User information" refers to data that indicates a user's personal characteristics, such as gender, age, region, preferences, and educational background.

[0185] "Personality traits" are characteristics of individual users' personalities and preferences that are extracted by analyzing user information.

[0186] A "character" is a virtual entity, personalized based on the user's personality traits, designed for interaction and support.

[0187] "Emotional state" refers to the emotional state a user displays during a conversation, and is identified by voice tone and chosen words.

[0188] A "virtual environment" is a digital space setting, distinct from the real world, provided via the internet or applications.

[0189] This invention constitutes a virtual store system that acquires user information, extracts personality traits, and generates characters. Specific embodiments are described below.

[0190] 1. Acquisition of user information: Users use smart glasses or head-mounted displays to input information such as gender, age, region, preferences, and educational background. This input data is transmitted from the terminal to the server.

[0191] 2. Extraction of Personality Traits and Character Generation: The server analyzes the received user information using an analysis engine and extracts individual personality traits. Furthermore, based on the extracted traits, it generates a character optimized for the user. In this process, natural language processing technology is utilized as the AI ​​model to enable real-time interaction.

[0192] 3. Identifying Emotional State and Adjusting Support: During the conversation, the server uses an emotion engine to identify the user's emotional state from their voice tone and chosen words. This allows the server to understand the user's emotions in real time and dynamically adjust the support provided by the system. This enables users to have a more personalized experience.

[0193] 4. Sales support within the virtual environment: Based on the user's emotional state and purchase history, the server recommends the most suitable products. Characters guide the user within the virtual store and support the purchase through expressive dialogue.

[0194] The server uses an AI platform in the cloud to execute generative models and sentiment recognition technologies (e.g., Amazon Web Services, Microsoft Azure, etc.). This enables advanced data processing and interactive communication with users.

[0195] As a concrete example, consider a user who is considering purchasing new running shoes. The system will recommend the most suitable shoes by taking into account their past purchase history and current emotional state. For example, it will adjust to provide detailed technical information when the user is in a calm mood, and trend information when they are in an energetic mood.

[0196] Examples of prompt statements are as follows:

[0197] "A man in his 30s, interested in sporting goods. Recently focused on running. Feeling energetic today. What running shoes would you recommend?"

[0198] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0199] Step 1:

[0200] Users enter personal information into the device using smart glasses or a head-mounted display. This information includes gender, age, region, preferences, and educational background. This information is collected as foundational data to personalize the user experience and is transmitted from the device to a server.

[0201] Step 2:

[0202] The server processes the received user information using an analysis engine. The analysis engine uses natural language processing techniques to extract individual personality traits from the user data. This process analyzes the user's characteristics by comparing them against patterns stored in a database. As a result, the user's personality traits are derived.

[0203] Step 3:

[0204] The server generates a character based on extracted personality traits. A generation AI model is used to create an interactive character optimized for the user's characteristics. The generated character is then sent to the terminal in preparation for real-time interaction with the user.

[0205] Step 4:

[0206] The user begins interacting with a character generated within the virtual store. During the interaction, the device expresses the user's emotions using voice and text. This data is sent to the server to enrich the interaction with the character.

[0207] Step 5:

[0208] The server uses an emotion engine to identify the user's emotional state from their voice tone and words. Using the input data, it analyzes the user's current emotions and dynamically adjusts the system's response based on the analysis results. The output is then determined to provide support tailored to the user's emotions.

[0209] Step 6:

[0210] The server considers the user's emotions and past purchase history within the virtual environment to recommend appropriate products. A generated character provides customized product suggestions to the user, supporting the shopping experience. Product selection and recommendations are based on input data and emotional information.

[0211] Step 7:

[0212] When a user decides to make a purchase, the device records that information and updates the user's purchase history. This improves the accuracy of future recommendations and enables the provision of better service. The updated purchase history data is saved to the server as output.

[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] The system for implementing this invention operates between three parties: the user, the terminal, and the server. The main functions of the system are to collect user information, extract personality traits, generate individually optimized characters, and enable real-time communication with the user.

[0230] First, the user launches a dedicated application on their device and enters the necessary personal information. This information includes gender, age, place of origin, hobbies and interests, and educational background. The device then sends this data to the server.

[0231] The server stores the received information in a database and uses an analysis engine to analyze the personality traits of individual users. This extracts the user's hobbies and preferences, revealing their specific interests and concerns.

[0232] Next, the server generates a character optimized for the user based on these personality traits. This character has a personality that aligns with the user's individuality and preferences, and its speaking style and topics of interest are pre-configured.

[0233] The user restarts the conversation session via the terminal and interacts with a character provided by the server. This process involves real-time responses to user input. The server uses an AI model to appropriately answer user questions and statements.

[0234] For example, if a user enjoys movies, the generated character will engage in conversation incorporating the latest movie information, deepening the interaction with the user. If the user talks about their travel destination, the server will provide relevant tourist information and recommended spots through the character.

[0235] Thus, the system implementing the invention enables an interactive experience with a character individually optimized for the user, significantly improving user satisfaction.

[0236] The following describes the processing flow.

[0237] Step 1:

[0238] Users launch a dedicated application on their device and enter personal information such as gender, age, place of origin, hobbies and interests, and educational background. This data forms the basis of their user profile.

[0239] Step 2:

[0240] The terminal securely transmits the entered user information to the server. The server stores the received information in a database and records it as each user's profile.

[0241] Step 3:

[0242] The server processes the stored user information through an analysis engine to extract individual personality traits. These traits include the user's hobbies, preferences, and past behavioral patterns.

[0243] Step 4:

[0244] Based on the analysis results, the server generates a character optimized for the user. This character reflects the user's personality traits and possesses specific speaking styles and knowledge of certain topics.

[0245] Step 5:

[0246] The user initiates a conversation session on their device. The device sends a session start request to the server and prepares to summon the generated character.

[0247] Step 6:

[0248] The server sends the generated character to the user's terminal and begins real-time communication with the user. The server then analyzes the user's input using the character and generates an appropriate response in real time.

[0249] Step 7:

[0250] The terminal displays the response received from the server to the user and waits for further input from the user. This loop allows for smooth interaction between the user and the character.

[0251] Step 8:

[0252] The server analyzes log data and learns user interests and responses through the conversation history. Based on this data, the AI ​​model is continuously improved to provide more sophisticated communication in the future.

[0253] (Example 1)

[0254] 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."

[0255] Modern information processing systems require communication tailored to individual user needs and preferences based on the information they provide. However, existing systems suffer from insufficient customization of information to suit individual user personalities and preferences, and also struggle with flexible, real-time responses. Furthermore, there is a need for secure processing of user information and continuous optimization of dialogue content.

[0256] 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.

[0257] In this invention, the server includes means for acquiring user information and securely transmitting said user information to a processing device, means for storing said user information in a data storage device, and means for processing said user information to extract individual personality traits. This enables flexible, secure, and real-time communication that is tailored to the individuality of each user.

[0258] "User information" refers to data provided by users that includes personal identification, developmental stage, location, preferences, educational background, and other relevant information.

[0259] "Means of securely transmitting data to a processing unit" refers to methods of encrypting data to prevent unauthorized access by third parties via the network while ensuring it reaches its destination.

[0260] A "data storage device" is a storage device used to store data such as received information and analysis results for the long term.

[0261] "Methods for extracting personality traits" refer to processing methods that analyze user-provided information to identify an individual's personality and behavioral patterns.

[0262] "Personalized representation" refers to a unique, personalized format of information that is designed based on the user's characteristics and preferences.

[0263] "Information exchange communication" refers to interfaces and protocols for the bidirectional exchange of information between users and systems.

[0264] "Means for adaptively adjusting the generation method" refers to processes for dynamically changing the system's response and the parameters of the generation algorithm based on the content of the dialogue and user feedback.

[0265] This invention is implemented using an information processing system that operates between three parties: a user, a terminal, and a server. This section explains how the user utilizes the system and how the terminal and server cooperate to achieve its functions.

[0266] First, the user installs a dedicated software application on their device. This application provides an interface for collecting the user's personal information. Specific information collected includes the user's name, age, gender, preferences, and location. The user enters this information into the device. During this process, the device formats and encrypts the data and securely transmits it to a server via the internet.

[0267] The server stores the received data using database software. For example, it can use MySQL, an open-source database management system. The server then uses data mining software to analyze the received user information. Here, it executes algorithms that utilize natural language processing techniques to identify the user's personality and preferences. This process extracts the user's individual personality traits.

[0268] Subsequently, the server uses a generative AI model to generate a virtual character optimized for the user's personality traits. This character is constructed based on the user's hobbies and interests, and possesses appropriate topics and speaking styles. Specifically, it leverages the latest natural language generation models to generate conversations with the user in real time.

[0269] When a user initiates a conversation session via their device, the server interacts with the user through a generated character. For example, if the user types "Tell me some recent movie recommendations," a character created using a generative AI model will respond, "My recent movie recommendation is 'Future World.' I recommend you watch it." This response includes the prompt, "When a user asks about recent movies, include the title of a recently released movie in your answer."

[0270] This system allows users to enjoy a personalized experience, and enables servers to respond to user needs securely and efficiently.

[0271] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0272] Step 1:

[0273] The user launches an application on their device and enters personal information. This information includes name, age, gender, hobbies, and location. The device formats and encrypts this information before securely sending it to the server. The input is personal information from the user interface, and the output is encrypted data.

[0274] Step 2:

[0275] The server receives encrypted data sent from the terminal and decrypts it. The decrypted data is then stored in a database, and storage processing is performed. The input is encrypted data, and the output is user information stored in the database. Specifically, storage is performed using a database management system.

[0276] Step 3:

[0277] The server starts data analysis using the stored user information. This analysis employs algorithms that utilize natural language processing techniques to identify the user's personality and preferences. The input is user information from the database, and the output is analysis data that shows the user's personality traits.

[0278] Step 4:

[0279] The server uses a generative AI model to generate a virtual character optimized for the user based on the analyzed data. This character will have topics of conversation and speaking style based on the user's hobbies and interests. The input is the user's personality trait data, and the output is the profile of the generated character.

[0280] Step 5:

[0281] The user initiates a conversation session using a terminal. The terminal sends a conversation request to the server, which then provides real-time interaction with the user through a generated character. The input is the conversation start request from the user, and the output is the dialogue content accompanied by the character.

[0282] Step 6:

[0283] During the conversation, the server uses the generative AI model to generate an appropriate response to the user's query. For example, when the user asks, "Tell me some recommended movies recently," the character responds, "The recently recommended movie is 'The World of the Future'. I recommend watching it." The input is the user's question, and the output is the generated response. This response includes a pre-set prompt sentence.

[0284] (Application Example 1)

[0285] 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".

[0286] In traditional store customer service, since the individual hobbies and preferences of customers are generally not fully considered, there is a problem that customer satisfaction and purchase intention decrease. In addition, to provide personalized customer service for each customer, a huge amount of manpower is required, which is not efficient. Furthermore, it is difficult to provide real-time information, and a prompt service that keeps up with the times is required. Therefore, the realization of a system that can provide information and dialogue based on the individual preferences of customers has become an issue.

[0287] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0288] In this invention, the server includes means for acquiring and storing user information, means for extracting individual personality characteristics, means for generating a character optimized for an individual, and means for providing a process for recommending products based on the preferences of customers in the store. Thereby, it becomes possible to provide personalized customer service in real time according to the hobbies and preferences of customers.

[0289] "User information" refers to information such as gender, age, region, preferences, and educational background that is collected through the device and used to extract individual personality characteristics.

[0290] "Personality traits" are analytical results that reveal a user's hobbies, preferences, and specific interests, and serve as the foundation for generating a character optimized for that individual.

[0291] A "character" is an artificial intelligence that is generated based on the user's personality traits and possesses a personality that enables interactive dialogue with the user.

[0292] "Communication" refers to the digital means provided for generated characters and users to exchange information in real time.

[0293] A "process" is a series of steps taken to provide appropriate product information within a store, based on the user's individual tastes and preferences.

[0294] A "generation algorithm" is a method for controlling character generation and product recommendation processes that are optimized based on information obtained through interaction with users.

[0295] A "system" is a collection of devices or programs that consistently perform tasks ranging from acquiring user information and generating characters to communicating and interacting, analyzing information, and optimizing generation algorithms.

[0296] The system implementing this invention operates smoothly between the user, terminal, and server. The terminal, such as smart glasses or a tablet, is used as a device for inputting user information. The user uses a dedicated application to input personal information such as gender, age, location, hobbies, and educational background into the terminal.

[0297] The servers are located in a cloud environment, specifically AWS or Google Cloud Platform. When the server receives user information, it stores that information in a database and uses an analysis engine to extract individual personality traits. At this time, generative AI models such as Google Cloud AI are used to generate a character that is optimal for each individual user. The generated character is constructed based on the user's personality, conversation style, and interests.

[0298] Users can initiate interactions with generated characters through their devices. The server uses an AI model to generate real-time responses to user input. In particular, within stores, a process is implemented to provide product information and promotions based on individual customer preferences.

[0299] For example, if a customer visiting a sporting goods store is interested in cycling equipment, a list of cycling-related products and promotional information will be displayed on the smart glasses screen. An example of a prompt message sent to the server in this case would be, "Show recommended products based on the customer's interests and tell me about current promotions."

[0300] In this way, the system can provide customers with a individually optimized purchasing experience, thereby improving customer satisfaction.

[0301] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0302] Step 1:

[0303] Users launch a dedicated application using smart glasses or a tablet device and enter personal information such as gender, age, address, hobbies, and educational background. This information is transmitted from the device to the server as user data. The role of the device is to collect and transmit user data.

[0304] Step 2:

[0305] The server stores the received user information data in the database. Next, based on the collected data, it uses an analysis engine to extract the user's personality characteristics. It analyzes the input information, performs data analysis to extract features related to hobbies and preferences, and stores the extraction results in the server.

[0306] Step 3:

[0307] The server generates a character optimized for an individual using a generation AI model based on the extracted personality characteristics. The generated character is designed with a conversation style and interests based on that personality. The model inputs the characteristic data and generates a custom character as the output.

[0308] Step 4:

[0309] The user starts a conversation with the character generated via the terminal. The terminal that receives the user's speech or input sends the content to the server and receives a response in real time. The conversation process here generates an immediate response based on the input question or conversation content.

[0310] Step 5:

[0311] The server presents store products and promotion information to the user through the character. At this time, it utilizes prompt texts for providing information based on the user's individual hobbies and preferences. It accesses the product database, processes the information of the target product to generate content suitable for the user, and returns the information to the terminal.

[0312] Step 6:

[0313] In stores such as sporting goods shops, users can use smart glasses to check product information and receive recommended purchase options through interactions with characters. This allows users to have a shopping experience based on their interests.

[0314] 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.

[0315] This invention is a system that integrates user information collection, personality trait extraction, character generation, real-time communication, and user emotion recognition using an emotion engine. This system communicates with the user, terminal, and server.

[0316] Users access a dedicated application from their own devices and input information such as gender, age, region, preferences, and educational background. In addition, they can express emotions through voice and text during conversations. The device sends this information to a server, which uses an analysis engine to extract each user's personality traits based on the information stored in the database.

[0317] Next, the server generates individually optimized characters based on personality traits. These characters are designed to respond appropriately to user input during real-time conversations. Furthermore, an emotion engine can identify emotions from the nuances of the user's voice and text. The emotion engine analyzes voice tone and word choice to infer the user's emotional state.

[0318] The user initiates a conversation session. The server sends a generated character to the user's device, enabling real-time communication. During this time, the emotion engine continuously recognizes emotions, and the server adjusts the AI ​​model's responses accordingly. For example, if the user feels they are not getting the information they need, the system will try to offer more help. Conversely, if the user is satisfied, the character will continue to enjoy the conversation.

[0319] This wearable feedback allows user emotional information to be incorporated into the AI ​​model's learning process, continuously improving it to provide a better conversational experience. Through this process, users can always enjoy interactions tailored to their own emotions and interests.

[0320] The following describes the processing flow.

[0321] Step 1:

[0322] The user launches a dedicated application on their device and enters personal information, including gender, age, region, preferences, and educational background. The device then prepares to send this information to the server.

[0323] Step 2:

[0324] The terminal sends the acquired user information to the server according to the security protocol. The server stores the received information in a database and generates a user profile.

[0325] Step 3:

[0326] The server processes the stored data using an analysis engine to extract the user's personality traits. These traits are related to the user's hobbies and preferences.

[0327] Step 4:

[0328] The server generates a character optimized for the user based on the extracted personality traits. This character is designed to have its own unique way of speaking and areas of interest.

[0329] Step 5:

[0330] The user initiates a conversation session using their device. The device sends this request to the server, which then prepares for the conversation.

[0331] Step 6:

[0332] The server sends the prepared character information to the terminal and begins real-time communication with the user. At this time, the emotion engine is activated and analyzes the user's emotional state in real time.

[0333] Step 7:

[0334] The terminal receives voice and text input from the user and sends it to the server. The server's emotion engine analyzes this data and recognizes the user's emotional state.

[0335] Step 8:

[0336] The server adjusts the character's responses based on the analysis results of the emotion engine. For example, if the user is unhappy, the character's responses will be changed to alleviate that dissatisfaction.

[0337] Step 9:

[0338] The terminal displays a pre-arranged response to the user and accepts the next input. This loop maintains a natural and dynamic dialogue between the user and the character.

[0339] (Example 2)

[0340] 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".

[0341] In modern communication, there is a need to accurately understand users' individual personality traits and real-time emotional states, and to provide digital agents optimized based on that understanding. However, conventional systems struggle to effectively analyze diverse user information and dynamically adjust responses. Therefore, there is a need to provide technologies that enable personalized conversational experiences.

[0342] 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.

[0343] In this invention, the server includes means for collecting user information and storing it in a data storage device, means for analyzing the user information and extracting individual personality traits, and means for generating a personalized digital agent based on the personality traits. This enables interaction with a digital agent optimized for each individual user.

[0344] "User information" refers to data including demographic information and behavioral preferences related to individual users.

[0345] A "data storage device" is an electronic storage medium for securely and efficiently storing user information.

[0346] "Analysis" is the process of thoroughly examining collected user information and extracting specific patterns and characteristics.

[0347] "Personality traits" are psychological or behavioral characteristics that represent the individuality of a user.

[0348] A "digital agent" is an interactive program that runs on a computer and is generated based on the user's personality traits.

[0349] A "communication environment" is a network infrastructure that enables digital agents and users to send and receive data to and from each other.

[0350] "Emotional data" refers to information collected from a user's voice and text that indicates their current emotional state.

[0351] A "generative computation model" is an algorithm or system that generates responses from a digital agent by utilizing user information and sentiment data.

[0352] This invention provides a system that offers users personalized digital agents and enables real-time communication. The system is realized through the cooperation of the user's terminal, a server, and a communication network.

[0353] Users access a dedicated application using devices such as smartphones or computers. Through this application, they can input demographic information such as gender, age, region, preferences, and educational background. Users can also express their emotions through voice or text, and this information is collected as user data.

[0354] The terminal is responsible for transmitting collected user information to the server. The server securely stores this information using an advanced database system. The stored data forms the basis for the analysis process.

[0355] The server utilizes an analysis engine to extract individual personality traits from stored user information. Machine learning algorithms are used for the analysis to highlight specific personality characteristics.

[0356] Next, the server uses a generative AI model to generate a digital agent based on the extracted personality traits. This digital agent incorporates natural language processing techniques to enable smooth interaction with the user.

[0357] Once a user starts a session, they can interact with a digital agent in real time through their device. The server uses an emotion engine to identify emotion data from the user's voice and text during the conversation. This allows the server to dynamically adjust its generative computation model to generate appropriate responses based on the user's emotional state.

[0358] As a concrete example, consider a scenario where a user is seeking movie recommendations. When the user inputs "I'd like to watch a funny movie recently," the server analyzes the information and generates an appropriate digital agent. The agent then provides a response such as, "A recent popular comedy movie recommendation is..."

[0359] Examples of prompts to input into a generative AI model:

[0360] "The user appears tired and is looking for relaxing music. Please recommend relaxing music and provide a calming response."

[0361] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0362] Step 1:

[0363] Users launch a dedicated application on their device and enter user information such as gender, age, region, preferences, and educational background. This input is converted into structured data by the application and temporarily stored on the device.

[0364] Step 2:

[0365] The terminal sends user information to the server. The data is encrypted and securely transferred via the HTTPS protocol. The server stores the received data in a database. The stored data is then used in subsequent analysis processes.

[0366] Step 3:

[0367] The server inputs user information stored in the database into the analysis engine and extracts individual personality traits. The analysis engine uses machine learning algorithms to identify traits based on the user's input data. As an output of this process, a user personality trait profile is generated.

[0368] Step 4:

[0369] The server generates digital agents using a generative AI model based on personality trait profiles. This generative AI model utilizes natural language processing techniques to provide appropriate conversational capabilities tailored to the user's characteristics. Information about the generated digital agents is stored on the server and prepared for user sessions.

[0370] Step 5:

[0371] The user sends a session start command to the server via their device. The server sends a digital agent to the user's device and begins real-time communication with the user. User input (text or voice) is sent from the device to the server.

[0372] Step 6:

[0373] The server inputs the user's voice and text received in real time into the emotion engine. The emotion engine analyzes the tone and language choices to infer the user's emotional state. The output from this process is the user's emotional data.

[0374] Step 7:

[0375] The server adjusts the output of the generative computation model based on emotional data. By optimizing the digital agent's response to match the user's emotions, a natural and comfortable conversation is achieved.

[0376] (Application Example 2)

[0377] 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."

[0378] When users search for information, they often face the challenge of not receiving support tailored to their individual needs and emotional states. In particular, when selecting and purchasing products in a virtual environment, the lack of information that matches the user's preferences and emotional reactions at the time can lead to problems in making effective purchasing decisions.

[0379] 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.

[0380] In this invention, the server includes means for acquiring and storing user information, means for analyzing user information to extract individual personality traits, means for generating a character optimized for the individual and dynamically adjusting the support content according to the user's emotional state, and means for providing product recommendations based on the user's emotions and past purchase history within a virtual environment. This enables the user to receive appropriate information and product suggestions that match their needs and emotions.

[0381] "User information" refers to data that indicates a user's personal characteristics, such as gender, age, region, preferences, and educational background.

[0382] "Personality traits" are characteristics of individual users' personalities and preferences that are extracted by analyzing user information.

[0383] A "character" is a virtual entity, personalized based on the user's personality traits, designed for interaction and support.

[0384] "Emotional state" refers to the emotional state a user displays during a conversation, and is identified by voice tone and chosen words.

[0385] A "virtual environment" is a digital space setting, distinct from the real world, provided via the internet or applications.

[0386] This invention constitutes a virtual store system that acquires user information, extracts personality traits, and generates characters. Specific embodiments are described below.

[0387] 1. Acquisition of user information: Users use smart glasses or head-mounted displays to input information such as gender, age, region, preferences, and educational background. This input data is transmitted from the terminal to the server.

[0388] 2. Extraction of Personality Traits and Character Generation: The server analyzes the received user information using an analysis engine and extracts individual personality traits. Furthermore, based on the extracted traits, it generates a character optimized for the user. In this process, natural language processing technology is utilized as the AI ​​model to enable real-time interaction.

[0389] 3. Identifying Emotional State and Adjusting Support: During the conversation, the server uses an emotion engine to identify the user's emotional state from their voice tone and chosen words. This allows the server to understand the user's emotions in real time and dynamically adjust the support provided by the system. This enables users to have a more personalized experience.

[0390] 4. Sales support within the virtual environment: Based on the user's emotional state and purchase history, the server recommends the most suitable products. Characters guide the user within the virtual store and support the purchase through expressive dialogue.

[0391] The server uses an AI platform in the cloud to execute generative models and sentiment recognition technologies (e.g., Amazon Web Services, Microsoft Azure, etc.). This enables advanced data processing and interactive communication with users.

[0392] As a concrete example, consider a user who is considering purchasing new running shoes. The system will recommend the most suitable shoes by taking into account their past purchase history and current emotional state. For example, it will adjust to provide detailed technical information when the user is in a calm mood, and trend information when they are in an energetic mood.

[0393] Examples of prompt statements are as follows:

[0394] "A man in his 30s, interested in sporting goods. Recently focused on running. Feeling energetic today. What running shoes would you recommend?"

[0395] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0396] Step 1:

[0397] Users enter personal information into the device using smart glasses or a head-mounted display. This information includes gender, age, region, preferences, and educational background. This information is collected as foundational data to personalize the user experience and is transmitted from the device to a server.

[0398] Step 2:

[0399] The server processes the received user information using an analysis engine. The analysis engine uses natural language processing techniques to extract individual personality traits from the user data. This process analyzes the user's characteristics by comparing them against patterns stored in a database. As a result, the user's personality traits are derived.

[0400] Step 3:

[0401] The server generates a character based on extracted personality traits. A generation AI model is used to create an interactive character optimized for the user's characteristics. The generated character is then sent to the terminal in preparation for real-time interaction with the user.

[0402] Step 4:

[0403] The user begins interacting with a character generated within the virtual store. During the interaction, the device expresses the user's emotions using voice and text. This data is sent to the server to enrich the interaction with the character.

[0404] Step 5:

[0405] The server uses an emotion engine to identify the user's emotional state from their voice tone and words. Using the input data, it analyzes the user's current emotions and dynamically adjusts the system's response based on the analysis results. The output is then determined to provide support tailored to the user's emotions.

[0406] Step 6:

[0407] The server considers the user's emotions and past purchase history within the virtual environment to recommend appropriate products. A generated character provides customized product suggestions to the user, supporting the shopping experience. Product selection and recommendations are based on input data and emotional information.

[0408] Step 7:

[0409] When a user decides to make a purchase, the device records that information and updates the user's purchase history. This improves the accuracy of future recommendations and enables the provision of better service. The updated purchase history data is saved to the server as output.

[0410] 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.

[0411] 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.

[0412] 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.

[0413] [Third Embodiment]

[0414] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0415] 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.

[0416] 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).

[0417] 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.

[0418] 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.

[0419] 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).

[0420] 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.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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".

[0426] The system for implementing this invention operates between three parties: the user, the terminal, and the server. The main functions of the system are to collect user information, extract personality traits, generate individually optimized characters, and enable real-time communication with the user.

[0427] First, the user launches a dedicated application on their device and enters the necessary personal information. This information includes gender, age, place of origin, hobbies and interests, and educational background. The device then sends this data to the server.

[0428] The server stores the received information in a database and uses an analysis engine to analyze the personality traits of individual users. This extracts the user's hobbies and preferences, revealing their specific interests and concerns.

[0429] Next, the server generates a character optimized for the user based on these personality traits. This character has a personality that aligns with the user's individuality and preferences, and its speaking style and topics of interest are pre-configured.

[0430] The user restarts the conversation session via the terminal and interacts with a character provided by the server. This process involves real-time responses to user input. The server uses an AI model to appropriately answer user questions and statements.

[0431] For example, if a user enjoys movies, the generated character will engage in conversation incorporating the latest movie information, deepening the interaction with the user. If the user talks about their travel destination, the server will provide relevant tourist information and recommended spots through the character.

[0432] Thus, the system implementing the invention enables an interactive experience with a character individually optimized for the user, significantly improving user satisfaction.

[0433] The following describes the processing flow.

[0434] Step 1:

[0435] Users launch a dedicated application on their device and enter personal information such as gender, age, place of origin, hobbies and interests, and educational background. This data forms the basis of their user profile.

[0436] Step 2:

[0437] The terminal securely transmits the entered user information to the server. The server stores the received information in a database and records it as each user's profile.

[0438] Step 3:

[0439] The server processes the stored user information through an analysis engine to extract individual personality traits. These traits include the user's hobbies, preferences, and past behavioral patterns.

[0440] Step 4:

[0441] Based on the analysis results, the server generates a character optimized for the user. This character reflects the user's personality traits and possesses specific speaking styles and knowledge of certain topics.

[0442] Step 5:

[0443] The user initiates a conversation session on their device. The device sends a session start request to the server and prepares to summon the generated character.

[0444] Step 6:

[0445] The server sends the generated character to the user's terminal and begins real-time communication with the user. The server then analyzes the user's input using the character and generates an appropriate response in real time.

[0446] Step 7:

[0447] The terminal displays the response received from the server to the user and waits for further input from the user. This loop allows for smooth interaction between the user and the character.

[0448] Step 8:

[0449] The server analyzes log data and learns user interests and responses through the conversation history. Based on this data, the AI ​​model is continuously improved to provide more sophisticated communication in the future.

[0450] (Example 1)

[0451] 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."

[0452] Modern information processing systems require communication tailored to individual user needs and preferences based on the information they provide. However, existing systems suffer from insufficient customization of information to suit individual user personalities and preferences, and also struggle with flexible, real-time responses. Furthermore, there is a need for secure processing of user information and continuous optimization of dialogue content.

[0453] 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.

[0454] In this invention, the server includes means for acquiring user information and securely transmitting said user information to a processing device, means for storing said user information in a data storage device, and means for processing said user information to extract individual personality traits. This enables flexible, secure, and real-time communication that is tailored to the individuality of each user.

[0455] "User information" refers to data provided by users that includes personal identification, developmental stage, location, preferences, educational background, and other relevant information.

[0456] "Means of securely transmitting data to a processing unit" refers to methods of encrypting data to prevent unauthorized access by third parties via the network while ensuring it reaches its destination.

[0457] A "data storage device" is a storage device used to store data such as received information and analysis results for the long term.

[0458] "Methods for extracting personality traits" refer to processing methods that analyze user-provided information to identify an individual's personality and behavioral patterns.

[0459] "Personalized representation" refers to a unique, personalized format of information that is designed based on the user's characteristics and preferences.

[0460] "Information exchange communication" refers to interfaces and protocols for the bidirectional exchange of information between users and systems.

[0461] "Means for adaptively adjusting the generation method" refers to processes for dynamically changing the system's response and the parameters of the generation algorithm based on the content of the dialogue and user feedback.

[0462] This invention is implemented using an information processing system that operates between three parties: a user, a terminal, and a server. This section explains how the user utilizes the system and how the terminal and server cooperate to achieve its functions.

[0463] First, the user installs a dedicated software application on their device. This application provides an interface for collecting the user's personal information. Specific information collected includes the user's name, age, gender, preferences, and location. The user enters this information into the device. During this process, the device formats and encrypts the data and securely transmits it to a server via the internet.

[0464] The server stores the received data using database software. For example, it can use MySQL, an open-source database management system. The server then uses data mining software to analyze the received user information. Here, it executes algorithms that utilize natural language processing techniques to identify the user's personality and preferences. This process extracts the user's individual personality traits.

[0465] Subsequently, the server uses a generative AI model to generate a virtual character optimized for the user's personality traits. This character is constructed based on the user's hobbies and interests, and possesses appropriate topics and speaking styles. Specifically, it leverages the latest natural language generation models to generate conversations with the user in real time.

[0466] When a user initiates a conversation session via their device, the server interacts with the user through a generated character. For example, if the user types "Tell me some recent movie recommendations," a character created using a generative AI model will respond, "My recent movie recommendation is 'Future World.' I recommend you watch it." This response includes the prompt, "When a user asks about recent movies, include the title of a recently released movie in your answer."

[0467] This system allows users to enjoy a personalized experience, and enables servers to respond to user needs securely and efficiently.

[0468] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0469] Step 1:

[0470] The user launches an application on their device and enters personal information. This information includes name, age, gender, hobbies, and location. The device formats and encrypts this information before securely sending it to the server. The input is personal information from the user interface, and the output is encrypted data.

[0471] Step 2:

[0472] The server receives encrypted data sent from the terminal and decrypts it. The decrypted data is then stored in a database, and storage processing is performed. The input is encrypted data, and the output is user information stored in the database. Specifically, storage is performed using a database management system.

[0473] Step 3:

[0474] The server starts data analysis using the stored user information. This analysis employs algorithms that utilize natural language processing techniques to identify the user's personality and preferences. The input is user information from the database, and the output is analysis data that shows the user's personality traits.

[0475] Step 4:

[0476] The server uses a generative AI model to generate a virtual character optimized for the user based on the analyzed data. This character will have topics of conversation and speaking style based on the user's hobbies and interests. The input is the user's personality trait data, and the output is the profile of the generated character.

[0477] Step 5:

[0478] The user initiates a conversation session using a terminal. The terminal sends a conversation request to the server, which then provides real-time interaction with the user through a generated character. The input is the conversation start request from the user, and the output is the dialogue content accompanied by the character.

[0479] Step 6:

[0480] The server uses a generative AI model during conversation to generate appropriate responses to user inquiries. For example, if a user asks, "What are some recent movie recommendations?", the character will respond, "My recent movie recommendation is 'Future World.' I recommend you watch it." The input is the user's question, and the output is the generated response. This response includes pre-configured prompts.

[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] Traditional in-store customer service often fails to adequately consider individual customer preferences, leading to decreased customer satisfaction and purchase intent. Furthermore, providing personalized service to each customer requires a massive amount of manpower and is inefficient. Additionally, real-time information provision is difficult, and there is a demand for rapid service delivery that keeps pace with the times. Therefore, the challenge lies in realizing a system that enables information provision and dialogue based on individual customer preferences.

[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 acquiring and storing user information, means for extracting individual personality traits, means for generating a character optimized for the individual, and means for providing a process for recommending products based on the preferences of in-store customers. This enables personalized customer service tailored to the customer's tastes and preferences in real time.

[0486] "User information" refers to information such as gender, age, region, preferences, and educational background that is collected through the device and used to extract individual personality characteristics.

[0487] "Personality traits" are analytical results that reveal a user's hobbies, preferences, and specific interests, and serve as the foundation for generating a character optimized for that individual.

[0488] A "character" is an artificial intelligence that is generated based on the user's personality traits and possesses a personality that enables interactive dialogue with the user.

[0489] "Communication" refers to the digital means provided for generated characters and users to exchange information in real time.

[0490] A "process" is a series of steps taken to provide appropriate product information within a store, based on the user's individual tastes and preferences.

[0491] A "generation algorithm" is a method for controlling character generation and product recommendation processes that are optimized based on information obtained through interaction with users.

[0492] A "system" is a collection of devices or programs that consistently perform tasks ranging from acquiring user information and generating characters to communicating and interacting, analyzing information, and optimizing generation algorithms.

[0493] The system implementing this invention operates smoothly between the user, terminal, and server. The terminal, such as smart glasses or a tablet, is used as a device for inputting user information. The user uses a dedicated application to input personal information such as gender, age, location, hobbies, and educational background into the terminal.

[0494] The servers are located in a cloud environment, specifically AWS or Google Cloud Platform. When the server receives user information, it stores that information in a database and uses an analysis engine to extract individual personality traits. At this time, generative AI models such as Google Cloud AI are used to generate a character that is optimal for each individual user. The generated character is constructed based on the user's personality, conversation style, and interests.

[0495] Users can initiate interactions with generated characters through their devices. The server uses an AI model to generate real-time responses to user input. In particular, within stores, a process is implemented to provide product information and promotions based on individual customer preferences.

[0496] For example, if a customer visiting a sporting goods store is interested in cycling equipment, a list of cycling-related products and promotional information will be displayed on the smart glasses screen. An example of a prompt message sent to the server in this case would be, "Show recommended products based on the customer's interests and tell me about current promotions."

[0497] In this way, the system can provide customers with a individually optimized purchasing experience, thereby improving customer satisfaction.

[0498] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0499] Step 1:

[0500] Users launch a dedicated application using smart glasses or a tablet device and enter personal information such as gender, age, address, hobbies, and educational background. This information is transmitted from the device to the server as user data. The role of the device is to collect and transmit user data.

[0501] Step 2:

[0502] The server stores the received user information data in a database. Next, it uses an analysis engine based on the collected data to extract the user's personality traits. It analyzes the input information, performs data analysis to extract characteristics related to hobbies and preferences, and stores the extraction results on the server.

[0503] Step 3:

[0504] The server uses a generative AI model to generate a character optimized for the individual, based on the extracted personality traits. The generated character is designed with a conversational style and interests based on that personality. The model takes trait data as input and generates a custom character as output.

[0505] Step 4:

[0506] The user initiates an interaction with a character generated via the device. The device receives the user's utterances and inputs, sends the content to the server, and receives a response in real time. The interaction process here generates immediate responses based on the input questions and conversation content.

[0507] Step 5:

[0508] The server presents store products and promotional information to the user through a character. In doing so, it utilizes prompt messages to provide information based on the user's individual tastes and preferences. It accesses the product database, processes information on the target product to generate content tailored to the user, and returns the information to the terminal.

[0509] Step 6:

[0510] In stores such as sporting goods shops, users can use smart glasses to check product information and receive recommended purchase options through interactions with characters. This allows users to have a shopping experience based on their interests.

[0511] 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.

[0512] This invention is a system that integrates user information collection, personality trait extraction, character generation, real-time communication, and user emotion recognition using an emotion engine. This system communicates with the user, terminal, and server.

[0513] Users access a dedicated application from their own devices and input information such as gender, age, region, preferences, and educational background. In addition, they can express emotions through voice and text during conversations. The device sends this information to a server, which uses an analysis engine to extract each user's personality traits based on the information stored in the database.

[0514] Next, the server generates individually optimized characters based on personality traits. These characters are designed to respond appropriately to user input during real-time conversations. Furthermore, an emotion engine can identify emotions from the nuances of the user's voice and text. The emotion engine analyzes voice tone and word choice to infer the user's emotional state.

[0515] The user initiates a conversation session. The server sends a generated character to the user's device, enabling real-time communication. During this time, the emotion engine continuously recognizes emotions, and the server adjusts the AI ​​model's responses accordingly. For example, if the user feels they are not getting the information they need, the system will try to offer more help. Conversely, if the user is satisfied, the character will continue to enjoy the conversation.

[0516] This wearable feedback allows user emotional information to be incorporated into the AI ​​model's learning process, continuously improving it to provide a better conversational experience. Through this process, users can always enjoy interactions tailored to their own emotions and interests.

[0517] The following describes the processing flow.

[0518] Step 1:

[0519] The user launches a dedicated application on their device and enters personal information, including gender, age, region, preferences, and educational background. The device then prepares to send this information to the server.

[0520] Step 2:

[0521] The terminal sends the acquired user information to the server according to the security protocol. The server stores the received information in a database and generates a user profile.

[0522] Step 3:

[0523] The server processes the stored data using an analysis engine to extract the user's personality traits. These traits are related to the user's hobbies and preferences.

[0524] Step 4:

[0525] The server generates a character optimized for the user based on the extracted personality traits. This character is designed to have its own unique way of speaking and areas of interest.

[0526] Step 5:

[0527] The user initiates a conversation session using their device. The device sends this request to the server, which then prepares for the conversation.

[0528] Step 6:

[0529] The server sends the prepared character information to the terminal and begins real-time communication with the user. At this time, the emotion engine is activated and analyzes the user's emotional state in real time.

[0530] Step 7:

[0531] The terminal receives voice and text input from the user and sends it to the server. The server's emotion engine analyzes this data and recognizes the user's emotional state.

[0532] Step 8:

[0533] The server adjusts the character's responses based on the analysis results of the emotion engine. For example, if the user is unhappy, the character's responses will be changed to alleviate that dissatisfaction.

[0534] Step 9:

[0535] The terminal displays a pre-arranged response to the user and accepts the next input. This loop maintains a natural and dynamic dialogue between the user and the character.

[0536] (Example 2)

[0537] 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."

[0538] In modern communication, there is a need to accurately understand users' individual personality traits and real-time emotional states, and to provide digital agents optimized based on that understanding. However, conventional systems struggle to effectively analyze diverse user information and dynamically adjust responses. Therefore, there is a need to provide technologies that enable personalized conversational experiences.

[0539] 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.

[0540] In this invention, the server includes means for collecting user information and storing it in a data storage device, means for analyzing the user information and extracting individual personality traits, and means for generating a personalized digital agent based on the personality traits. This enables interaction with a digital agent optimized for each individual user.

[0541] "User information" refers to data including demographic information and behavioral preferences related to individual users.

[0542] A "data storage device" is an electronic storage medium for securely and efficiently storing user information.

[0543] "Analysis" is the process of thoroughly examining collected user information and extracting specific patterns and characteristics.

[0544] "Personality traits" are psychological or behavioral characteristics that represent the individuality of a user.

[0545] A "digital agent" is an interactive program that runs on a computer and is generated based on the user's personality traits.

[0546] A "communication environment" is a network infrastructure that enables digital agents and users to send and receive data to and from each other.

[0547] "Emotional data" refers to information collected from a user's voice and text that indicates their current emotional state.

[0548] A "generative computation model" is an algorithm or system that generates responses from a digital agent by utilizing user information and sentiment data.

[0549] This invention provides a system that offers users personalized digital agents and enables real-time communication. The system is realized through the cooperation of the user's terminal, a server, and a communication network.

[0550] Users access a dedicated application using devices such as smartphones or computers. Through this application, they can input demographic information such as gender, age, region, preferences, and educational background. Users can also express their emotions through voice or text, and this information is collected as user data.

[0551] The terminal is responsible for transmitting collected user information to the server. The server securely stores this information using an advanced database system. The stored data forms the basis for the analysis process.

[0552] The server utilizes an analysis engine to extract individual personality traits from stored user information. Machine learning algorithms are used for the analysis to highlight specific personality characteristics.

[0553] Next, the server uses a generative AI model to generate a digital agent based on the extracted personality traits. This digital agent incorporates natural language processing techniques to enable smooth interaction with the user.

[0554] Once a user starts a session, they can interact with a digital agent in real time through their device. The server uses an emotion engine to identify emotion data from the user's voice and text during the conversation. This allows the server to dynamically adjust its generative computation model to generate appropriate responses based on the user's emotional state.

[0555] As a concrete example, consider a scenario where a user is seeking movie recommendations. When the user inputs "I'd like to watch a funny movie recently," the server analyzes the information and generates an appropriate digital agent. The agent then provides a response such as, "A recent popular comedy movie recommendation is..."

[0556] Examples of prompts to input into a generative AI model:

[0557] "The user appears tired and is looking for relaxing music. Please recommend relaxing music and provide a calming response."

[0558] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0559] Step 1:

[0560] Users launch a dedicated application on their device and enter user information such as gender, age, region, preferences, and educational background. This input is converted into structured data by the application and temporarily stored on the device.

[0561] Step 2:

[0562] The terminal sends user information to the server. The data is encrypted and securely transferred via the HTTPS protocol. The server stores the received data in a database. The stored data is then used in subsequent analysis processes.

[0563] Step 3:

[0564] The server inputs user information stored in the database into the analysis engine and extracts individual personality traits. The analysis engine uses machine learning algorithms to identify traits based on the user's input data. As an output of this process, a user personality trait profile is generated.

[0565] Step 4:

[0566] The server generates digital agents using a generative AI model based on personality trait profiles. This generative AI model utilizes natural language processing techniques to provide appropriate conversational capabilities tailored to the user's characteristics. Information about the generated digital agents is stored on the server and prepared for user sessions.

[0567] Step 5:

[0568] The user sends a session start command to the server via their device. The server sends a digital agent to the user's device and begins real-time communication with the user. User input (text or voice) is sent from the device to the server.

[0569] Step 6:

[0570] The server inputs the user's voice and text received in real time into the emotion engine. The emotion engine analyzes the tone and language choices to infer the user's emotional state. The output from this process is the user's emotional data.

[0571] Step 7:

[0572] The server adjusts the output of the generative computation model based on emotional data. By optimizing the digital agent's response to match the user's emotions, a natural and comfortable conversation is achieved.

[0573] (Application Example 2)

[0574] 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."

[0575] When users search for information, they often face the challenge of not receiving support tailored to their individual needs and emotional states. In particular, when selecting and purchasing products in a virtual environment, the lack of information that matches the user's preferences and emotional reactions at the time can lead to problems in making effective purchasing decisions.

[0576] 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.

[0577] In this invention, the server includes means for acquiring and storing user information, means for analyzing user information to extract individual personality traits, means for generating a character optimized for the individual and dynamically adjusting the support content according to the user's emotional state, and means for providing product recommendations based on the user's emotions and past purchase history within a virtual environment. This enables the user to receive appropriate information and product suggestions that match their needs and emotions.

[0578] "User information" refers to data that indicates a user's personal characteristics, such as gender, age, region, preferences, and educational background.

[0579] "Personality traits" are characteristics of individual users' personalities and preferences that are extracted by analyzing user information.

[0580] A "character" is a virtual entity, personalized based on the user's personality traits, designed for interaction and support.

[0581] "Emotional state" refers to the emotional state a user displays during a conversation, and is identified by voice tone and chosen words.

[0582] A "virtual environment" is a digital space setting, distinct from the real world, provided via the internet or applications.

[0583] This invention constitutes a virtual store system that acquires user information, extracts personality traits, and generates characters. Specific embodiments are described below.

[0584] 1. Acquisition of user information: Users use smart glasses or head-mounted displays to input information such as gender, age, region, preferences, and educational background. This input data is transmitted from the terminal to the server.

[0585] 2. Extraction of Personality Traits and Character Generation: The server analyzes the received user information using an analysis engine and extracts individual personality traits. Furthermore, based on the extracted traits, it generates a character optimized for the user. In this process, natural language processing technology is utilized as the AI ​​model to enable real-time interaction.

[0586] 3. Identifying Emotional State and Adjusting Support: During the conversation, the server uses an emotion engine to identify the user's emotional state from their voice tone and chosen words. This allows the server to understand the user's emotions in real time and dynamically adjust the support provided by the system. This enables users to have a more personalized experience.

[0587] 4. Sales support within the virtual environment: Based on the user's emotional state and purchase history, the server recommends the most suitable products. Characters guide the user within the virtual store and support the purchase through expressive dialogue.

[0588] The server uses an AI platform in the cloud to execute generative models and sentiment recognition technologies (e.g., Amazon Web Services, Microsoft Azure, etc.). This enables advanced data processing and interactive communication with users.

[0589] As a concrete example, consider a user who is considering purchasing new running shoes. The system will recommend the most suitable shoes by taking into account their past purchase history and current emotional state. For example, it will adjust to provide detailed technical information when the user is in a calm mood, and trend information when they are in an energetic mood.

[0590] Examples of prompt statements are as follows:

[0591] "A man in his 30s, interested in sporting goods. Recently focused on running. Feeling energetic today. What running shoes would you recommend?"

[0592] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0593] Step 1:

[0594] Users enter personal information into the device using smart glasses or a head-mounted display. This information includes gender, age, region, preferences, and educational background. This information is collected as foundational data to personalize the user experience and is transmitted from the device to a server.

[0595] Step 2:

[0596] The server processes the received user information using an analysis engine. The analysis engine uses natural language processing techniques to extract individual personality traits from the user data. This process analyzes the user's characteristics by comparing them against patterns stored in a database. As a result, the user's personality traits are derived.

[0597] Step 3:

[0598] The server generates a character based on extracted personality traits. A generation AI model is used to create an interactive character optimized for the user's characteristics. The generated character is then sent to the terminal in preparation for real-time interaction with the user.

[0599] Step 4:

[0600] The user begins interacting with a character generated within the virtual store. During the interaction, the device expresses the user's emotions using voice and text. This data is sent to the server to enrich the interaction with the character.

[0601] Step 5:

[0602] The server uses an emotion engine to identify the user's emotional state from their voice tone and words. Using the input data, it analyzes the user's current emotions and dynamically adjusts the system's response based on the analysis results. The output is then determined to provide support tailored to the user's emotions.

[0603] Step 6:

[0604] The server considers the user's emotions and past purchase history within the virtual environment to recommend appropriate products. A generated character provides customized product suggestions to the user, supporting the shopping experience. Product selection and recommendations are based on input data and emotional information.

[0605] Step 7:

[0606] When a user decides to make a purchase, the device records that information and updates the user's purchase history. This improves the accuracy of future recommendations and enables the provision of better service. The updated purchase history data is saved to the server as output.

[0607] 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.

[0608] 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.

[0609] 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.

[0610] [Fourth Embodiment]

[0611] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0612] 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.

[0613] 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).

[0614] 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.

[0615] 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.

[0616] 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).

[0617] 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.

[0618] 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.

[0619] 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.

[0620] 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.

[0621] 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.

[0622] 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.

[0623] 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".

[0624] The system for implementing this invention operates between three parties: the user, the terminal, and the server. The main functions of the system are to collect user information, extract personality traits, generate individually optimized characters, and enable real-time communication with the user.

[0625] First, the user launches a dedicated application on their device and enters the necessary personal information. This information includes gender, age, place of origin, hobbies and interests, and educational background. The device then sends this data to the server.

[0626] The server stores the received information in a database and uses an analysis engine to analyze the personality traits of individual users. This extracts the user's hobbies and preferences, revealing their specific interests and concerns.

[0627] Next, the server generates a character optimized for the user based on these personality traits. This character has a personality that aligns with the user's individuality and preferences, and its speaking style and topics of interest are pre-configured.

[0628] The user restarts the conversation session via the terminal and interacts with a character provided by the server. This process involves real-time responses to user input. The server uses an AI model to appropriately answer user questions and statements.

[0629] For example, if a user enjoys movies, the generated character will engage in conversation incorporating the latest movie information, deepening the interaction with the user. If the user talks about their travel destination, the server will provide relevant tourist information and recommended spots through the character.

[0630] Thus, the system implementing the invention enables an interactive experience with a character individually optimized for the user, significantly improving user satisfaction.

[0631] The following describes the processing flow.

[0632] Step 1:

[0633] Users launch a dedicated application on their device and enter personal information such as gender, age, place of origin, hobbies and interests, and educational background. This data forms the basis of their user profile.

[0634] Step 2:

[0635] The terminal securely transmits the entered user information to the server. The server stores the received information in a database and records it as each user's profile.

[0636] Step 3:

[0637] The server processes the stored user information through an analysis engine to extract individual personality traits. These traits include the user's hobbies, preferences, and past behavioral patterns.

[0638] Step 4:

[0639] Based on the analysis results, the server generates a character optimized for the user. This character reflects the user's personality traits and possesses specific speaking styles and knowledge of certain topics.

[0640] Step 5:

[0641] The user initiates a conversation session on their device. The device sends a session start request to the server and prepares to summon the generated character.

[0642] Step 6:

[0643] The server sends the generated character to the user's terminal and begins real-time communication with the user. The server then analyzes the user's input using the character and generates an appropriate response in real time.

[0644] Step 7:

[0645] The terminal displays the response received from the server to the user and waits for further input from the user. This loop allows for smooth interaction between the user and the character.

[0646] Step 8:

[0647] The server analyzes log data and learns user interests and responses through the conversation history. Based on this data, the AI ​​model is continuously improved to provide more sophisticated communication in the future.

[0648] (Example 1)

[0649] 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".

[0650] Modern information processing systems require communication tailored to individual user needs and preferences based on the information they provide. However, existing systems suffer from insufficient customization of information to suit individual user personalities and preferences, and also struggle with flexible, real-time responses. Furthermore, there is a need for secure processing of user information and continuous optimization of dialogue content.

[0651] 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.

[0652] In this invention, the server includes means for acquiring user information and securely transmitting said user information to a processing device, means for storing said user information in a data storage device, and means for processing said user information to extract individual personality traits. This enables flexible, secure, and real-time communication that is tailored to the individuality of each user.

[0653] "User information" refers to data provided by users that includes personal identification, developmental stage, location, preferences, educational background, and other relevant information.

[0654] "Means of securely transmitting data to a processing unit" refers to methods of encrypting data to prevent unauthorized access by third parties via the network while ensuring it reaches its destination.

[0655] A "data storage device" is a storage device used to store data such as received information and analysis results for the long term.

[0656] "Methods for extracting personality traits" refer to processing methods that analyze user-provided information to identify an individual's personality and behavioral patterns.

[0657] "Personalized representation" refers to a unique, personalized format of information that is designed based on the user's characteristics and preferences.

[0658] "Information exchange communication" refers to interfaces and protocols for the bidirectional exchange of information between users and systems.

[0659] "Means for adaptively adjusting the generation method" refers to processes for dynamically changing the system's response and the parameters of the generation algorithm based on the content of the dialogue and user feedback.

[0660] This invention is implemented using an information processing system that operates between three parties: a user, a terminal, and a server. This section explains how the user utilizes the system and how the terminal and server cooperate to achieve its functions.

[0661] First, the user installs a dedicated software application on their device. This application provides an interface for collecting the user's personal information. Specific information collected includes the user's name, age, gender, preferences, and location. The user enters this information into the device. During this process, the device formats and encrypts the data and securely transmits it to a server via the internet.

[0662] The server stores the received data using database software. For example, it can use MySQL, an open-source database management system. The server then uses data mining software to analyze the received user information. Here, it executes algorithms that utilize natural language processing techniques to identify the user's personality and preferences. This process extracts the user's individual personality traits.

[0663] Subsequently, the server uses a generative AI model to generate a virtual character optimized for the user's personality traits. This character is constructed based on the user's hobbies and interests, and possesses appropriate topics and speaking styles. Specifically, it leverages the latest natural language generation models to generate conversations with the user in real time.

[0664] When a user initiates a conversation session via their device, the server interacts with the user through a generated character. For example, if the user types "Tell me some recent movie recommendations," a character created using a generative AI model will respond, "My recent movie recommendation is 'Future World.' I recommend you watch it." This response includes the prompt, "When a user asks about recent movies, include the title of a recently released movie in your answer."

[0665] This system allows users to enjoy a personalized experience, and enables servers to respond to user needs securely and efficiently.

[0666] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0667] Step 1:

[0668] The user launches an application on their device and enters personal information. This information includes name, age, gender, hobbies, and location. The device formats and encrypts this information before securely sending it to the server. The input is personal information from the user interface, and the output is encrypted data.

[0669] Step 2:

[0670] The server receives encrypted data sent from the terminal and decrypts it. The decrypted data is then stored in a database, and storage processing is performed. The input is encrypted data, and the output is user information stored in the database. Specifically, storage is performed using a database management system.

[0671] Step 3:

[0672] The server starts data analysis using the stored user information. This analysis employs algorithms that utilize natural language processing techniques to identify the user's personality and preferences. The input is user information from the database, and the output is analysis data that shows the user's personality traits.

[0673] Step 4:

[0674] The server uses a generative AI model to generate a virtual character optimized for the user based on the analyzed data. This character will have topics of conversation and speaking style based on the user's hobbies and interests. The input is the user's personality trait data, and the output is the profile of the generated character.

[0675] Step 5:

[0676] The user initiates a conversation session using a terminal. The terminal sends a conversation request to the server, which then provides real-time interaction with the user through a generated character. The input is the conversation start request from the user, and the output is the dialogue content accompanied by the character.

[0677] Step 6:

[0678] The server uses a generative AI model during conversation to generate appropriate responses to user inquiries. For example, if a user asks, "What are some recent movie recommendations?", the character will respond, "My recent movie recommendation is 'Future World.' I recommend you watch it." The input is the user's question, and the output is the generated response. This response includes pre-configured prompts.

[0679] (Application Example 1)

[0680] 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".

[0681] Traditional in-store customer service often fails to adequately consider individual customer preferences, leading to decreased customer satisfaction and purchase intent. Furthermore, providing personalized service to each customer requires a massive amount of manpower and is inefficient. Additionally, real-time information provision is difficult, and there is a demand for rapid service delivery that keeps pace with the times. Therefore, the challenge lies in realizing a system that enables information provision and dialogue based on individual customer preferences.

[0682] 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.

[0683] In this invention, the server includes means for acquiring and storing user information, means for extracting individual personality traits, means for generating a character optimized for the individual, and means for providing a process for recommending products based on the preferences of in-store customers. This enables personalized customer service tailored to the customer's tastes and preferences in real time.

[0684] "User information" refers to information such as gender, age, region, preferences, and educational background that is collected through the device and used to extract individual personality characteristics.

[0685] "Personality traits" are analytical results that reveal a user's hobbies, preferences, and specific interests, and serve as the foundation for generating a character optimized for that individual.

[0686] A "character" is an artificial intelligence that is generated based on the user's personality traits and possesses a personality that enables interactive dialogue with the user.

[0687] "Communication" refers to the digital means provided for generated characters and users to exchange information in real time.

[0688] A "process" is a series of steps taken to provide appropriate product information within a store, based on the user's individual tastes and preferences.

[0689] A "generation algorithm" is a method for controlling character generation and product recommendation processes that are optimized based on information obtained through interaction with users.

[0690] A "system" is a collection of devices or programs that consistently perform tasks ranging from acquiring user information and generating characters to communicating and interacting, analyzing information, and optimizing generation algorithms.

[0691] The system implementing this invention operates smoothly between the user, terminal, and server. The terminal, such as smart glasses or a tablet, is used as a device for inputting user information. The user uses a dedicated application to input personal information such as gender, age, location, hobbies, and educational background into the terminal.

[0692] The servers are located in a cloud environment, specifically AWS or Google Cloud Platform. When the server receives user information, it stores that information in a database and uses an analysis engine to extract individual personality traits. At this time, generative AI models such as Google Cloud AI are used to generate a character that is optimal for each individual user. The generated character is constructed based on the user's personality, conversation style, and interests.

[0693] Users can initiate interactions with generated characters through their devices. The server uses an AI model to generate real-time responses to user input. In particular, within stores, a process is implemented to provide product information and promotions based on individual customer preferences.

[0694] For example, if a customer visiting a sporting goods store is interested in cycling equipment, a list of cycling-related products and promotional information will be displayed on the smart glasses screen. An example of a prompt message sent to the server in this case would be, "Show recommended products based on the customer's interests and tell me about current promotions."

[0695] In this way, the system can provide customers with a individually optimized purchasing experience, thereby improving customer satisfaction.

[0696] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0697] Step 1:

[0698] Users launch a dedicated application using smart glasses or a tablet device and enter personal information such as gender, age, address, hobbies, and educational background. This information is transmitted from the device to the server as user data. The role of the device is to collect and transmit user data.

[0699] Step 2:

[0700] The server stores the received user information data in a database. Next, it uses an analysis engine based on the collected data to extract the user's personality traits. It analyzes the input information, performs data analysis to extract characteristics related to hobbies and preferences, and stores the extraction results on the server.

[0701] Step 3:

[0702] The server uses a generative AI model to generate a character optimized for the individual, based on the extracted personality traits. The generated character is designed with a conversational style and interests based on that personality. The model takes trait data as input and generates a custom character as output.

[0703] Step 4:

[0704] The user initiates an interaction with a character generated via the device. The device receives the user's utterances and inputs, sends the content to the server, and receives a response in real time. The interaction process here generates immediate responses based on the input questions and conversation content.

[0705] Step 5:

[0706] The server presents store products and promotional information to the user through a character. In doing so, it utilizes prompt messages to provide information based on the user's individual tastes and preferences. It accesses the product database, processes information on the target product to generate content tailored to the user, and returns the information to the terminal.

[0707] Step 6:

[0708] In stores such as sporting goods shops, users can use smart glasses to check product information and receive recommended purchase options through interactions with characters. This allows users to have a shopping experience based on their interests.

[0709] 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.

[0710] This invention is a system that integrates user information collection, personality trait extraction, character generation, real-time communication, and user emotion recognition using an emotion engine. This system communicates with the user, terminal, and server.

[0711] Users access a dedicated application from their own devices and input information such as gender, age, region, preferences, and educational background. In addition, they can express emotions through voice and text during conversations. The device sends this information to a server, which uses an analysis engine to extract each user's personality traits based on the information stored in the database.

[0712] Next, the server generates individually optimized characters based on personality traits. These characters are designed to respond appropriately to user input during real-time conversations. Furthermore, an emotion engine can identify emotions from the nuances of the user's voice and text. The emotion engine analyzes voice tone and word choice to infer the user's emotional state.

[0713] The user initiates a conversation session. The server sends a generated character to the user's device, enabling real-time communication. During this time, the emotion engine continuously recognizes emotions, and the server adjusts the AI ​​model's responses accordingly. For example, if the user feels they are not getting the information they need, the system will try to offer more help. Conversely, if the user is satisfied, the character will continue to enjoy the conversation.

[0714] This wearable feedback allows user emotional information to be incorporated into the AI ​​model's learning process, continuously improving it to provide a better conversational experience. Through this process, users can always enjoy interactions tailored to their own emotions and interests.

[0715] The following describes the processing flow.

[0716] Step 1:

[0717] The user launches a dedicated application on their device and enters personal information, including gender, age, region, preferences, and educational background. The device then prepares to send this information to the server.

[0718] Step 2:

[0719] The terminal sends the acquired user information to the server according to the security protocol. The server stores the received information in a database and generates a user profile.

[0720] Step 3:

[0721] The server processes the stored data using an analysis engine to extract the user's personality traits. These traits are related to the user's hobbies and preferences.

[0722] Step 4:

[0723] The server generates a character optimized for the user based on the extracted personality traits. This character is designed to have its own unique way of speaking and areas of interest.

[0724] Step 5:

[0725] The user initiates a conversation session using their device. The device sends this request to the server, which then prepares for the conversation.

[0726] Step 6:

[0727] The server sends the prepared character information to the terminal and begins real-time communication with the user. At this time, the emotion engine is activated and analyzes the user's emotional state in real time.

[0728] Step 7:

[0729] The terminal receives voice and text input from the user and sends it to the server. The server's emotion engine analyzes this data and recognizes the user's emotional state.

[0730] Step 8:

[0731] The server adjusts the character's responses based on the analysis results of the emotion engine. For example, if the user is unhappy, the character's responses will be changed to alleviate that dissatisfaction.

[0732] Step 9:

[0733] The terminal displays a pre-arranged response to the user and accepts the next input. This loop maintains a natural and dynamic dialogue between the user and the character.

[0734] (Example 2)

[0735] 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".

[0736] In modern communication, there is a need to accurately understand users' individual personality traits and real-time emotional states, and to provide digital agents optimized based on that understanding. However, conventional systems struggle to effectively analyze diverse user information and dynamically adjust responses. Therefore, there is a need to provide technologies that enable personalized conversational experiences.

[0737] 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.

[0738] In this invention, the server includes means for collecting user information and storing it in a data storage device, means for analyzing the user information and extracting individual personality traits, and means for generating a personalized digital agent based on the personality traits. This enables interaction with a digital agent optimized for each individual user.

[0739] "User information" refers to data including demographic information and behavioral preferences related to individual users.

[0740] A "data storage device" is an electronic storage medium for securely and efficiently storing user information.

[0741] "Analysis" is the process of thoroughly examining collected user information and extracting specific patterns and characteristics.

[0742] "Personality traits" are psychological or behavioral characteristics that represent the individuality of a user.

[0743] A "digital agent" is an interactive program that runs on a computer and is generated based on the user's personality traits.

[0744] A "communication environment" is a network infrastructure that enables digital agents and users to send and receive data to and from each other.

[0745] "Emotional data" refers to information collected from a user's voice and text that indicates their current emotional state.

[0746] A "generative computation model" is an algorithm or system that generates responses from a digital agent by utilizing user information and sentiment data.

[0747] This invention provides a system that offers users personalized digital agents and enables real-time communication. The system is realized through the cooperation of the user's terminal, a server, and a communication network.

[0748] Users access a dedicated application using devices such as smartphones or computers. Through this application, they can input demographic information such as gender, age, region, preferences, and educational background. Users can also express their emotions through voice or text, and this information is collected as user data.

[0749] The terminal is responsible for transmitting collected user information to the server. The server securely stores this information using an advanced database system. The stored data forms the basis for the analysis process.

[0750] The server utilizes an analysis engine to extract individual personality traits from stored user information. Machine learning algorithms are used for the analysis to highlight specific personality characteristics.

[0751] Next, the server uses a generative AI model to generate a digital agent based on the extracted personality traits. This digital agent incorporates natural language processing techniques to enable smooth interaction with the user.

[0752] Once a user starts a session, they can interact with a digital agent in real time through their device. The server uses an emotion engine to identify emotion data from the user's voice and text during the conversation. This allows the server to dynamically adjust its generative computation model to generate appropriate responses based on the user's emotional state.

[0753] As a concrete example, consider a scenario where a user is seeking movie recommendations. When the user inputs "I'd like to watch a funny movie recently," the server analyzes the information and generates an appropriate digital agent. The agent then provides a response such as, "A recent popular comedy movie recommendation is..."

[0754] Examples of prompts to input into a generative AI model:

[0755] "The user appears tired and is looking for relaxing music. Please recommend relaxing music and provide a calming response."

[0756] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0757] Step 1:

[0758] Users launch a dedicated application on their device and enter user information such as gender, age, region, preferences, and educational background. This input is converted into structured data by the application and temporarily stored on the device.

[0759] Step 2:

[0760] The terminal sends user information to the server. The data is encrypted and securely transferred via the HTTPS protocol. The server stores the received data in a database. The stored data is then used in subsequent analysis processes.

[0761] Step 3:

[0762] The server inputs user information stored in the database into the analysis engine and extracts individual personality traits. The analysis engine uses machine learning algorithms to identify traits based on the user's input data. As an output of this process, a user personality trait profile is generated.

[0763] Step 4:

[0764] The server generates digital agents using a generative AI model based on personality trait profiles. This generative AI model utilizes natural language processing techniques to provide appropriate conversational capabilities tailored to the user's characteristics. Information about the generated digital agents is stored on the server and prepared for user sessions.

[0765] Step 5:

[0766] The user sends a session start command to the server via their device. The server sends a digital agent to the user's device and begins real-time communication with the user. User input (text or voice) is sent from the device to the server.

[0767] Step 6:

[0768] The server inputs the user's voice and text received in real time into the emotion engine. The emotion engine analyzes the tone and language choices to infer the user's emotional state. The output from this process is the user's emotional data.

[0769] Step 7:

[0770] The server adjusts the output of the generative computation model based on emotional data. By optimizing the digital agent's response to match the user's emotions, a natural and comfortable conversation is achieved.

[0771] (Application Example 2)

[0772] 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".

[0773] When users search for information, they often face the challenge of not receiving support tailored to their individual needs and emotional states. In particular, when selecting and purchasing products in a virtual environment, the lack of information that matches the user's preferences and emotional reactions at the time can lead to problems in making effective purchasing decisions.

[0774] 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.

[0775] In this invention, the server includes means for acquiring and storing user information, means for analyzing user information to extract individual personality traits, means for generating a character optimized for the individual and dynamically adjusting the support content according to the user's emotional state, and means for providing product recommendations based on the user's emotions and past purchase history within a virtual environment. This enables the user to receive appropriate information and product suggestions that match their needs and emotions.

[0776] "User information" refers to data that indicates a user's personal characteristics, such as gender, age, region, preferences, and educational background.

[0777] "Personality traits" are characteristics of individual users' personalities and preferences that are extracted by analyzing user information.

[0778] A "character" is a virtual entity, personalized based on the user's personality traits, designed for interaction and support.

[0779] "Emotional state" refers to the emotional state a user displays during a conversation, and is identified by voice tone and chosen words.

[0780] A "virtual environment" is a digital space setting, distinct from the real world, provided via the internet or applications.

[0781] This invention constitutes a virtual store system that acquires user information, extracts personality traits, and generates characters. Specific embodiments are described below.

[0782] 1. Acquisition of user information: Users use smart glasses or head-mounted displays to input information such as gender, age, region, preferences, and educational background. This input data is transmitted from the terminal to the server.

[0783] 2. Extraction of Personality Traits and Character Generation: The server analyzes the received user information using an analysis engine and extracts individual personality traits. Furthermore, based on the extracted traits, it generates a character optimized for the user. In this process, natural language processing technology is utilized as the AI ​​model to enable real-time interaction.

[0784] 3. Identifying Emotional State and Adjusting Support: During the conversation, the server uses an emotion engine to identify the user's emotional state from their voice tone and chosen words. This allows the server to understand the user's emotions in real time and dynamically adjust the support provided by the system. This enables users to have a more personalized experience.

[0785] 4. Sales support within the virtual environment: Based on the user's emotional state and purchase history, the server recommends the most suitable products. Characters guide the user within the virtual store and support the purchase through expressive dialogue.

[0786] The server uses an AI platform in the cloud to execute generative models and sentiment recognition technologies (e.g., Amazon Web Services, Microsoft Azure, etc.). This enables advanced data processing and interactive communication with users.

[0787] As a concrete example, consider a user who is considering purchasing new running shoes. The system will recommend the most suitable shoes by taking into account their past purchase history and current emotional state. For example, it will adjust to provide detailed technical information when the user is in a calm mood, and trend information when they are in an energetic mood.

[0788] Examples of prompt statements are as follows:

[0789] "A man in his 30s, interested in sporting goods. Recently focused on running. Feeling energetic today. What running shoes would you recommend?"

[0790] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0791] Step 1:

[0792] Users enter personal information into the device using smart glasses or a head-mounted display. This information includes gender, age, region, preferences, and educational background. This information is collected as foundational data to personalize the user experience and is transmitted from the device to a server.

[0793] Step 2:

[0794] The server processes the received user information using an analysis engine. The analysis engine uses natural language processing techniques to extract individual personality traits from the user data. This process analyzes the user's characteristics by comparing them against patterns stored in a database. As a result, the user's personality traits are derived.

[0795] Step 3:

[0796] The server generates a character based on extracted personality traits. A generation AI model is used to create an interactive character optimized for the user's characteristics. The generated character is then sent to the terminal in preparation for real-time interaction with the user.

[0797] Step 4:

[0798] The user begins interacting with a character generated within the virtual store. During the interaction, the device expresses the user's emotions using voice and text. This data is sent to the server to enrich the interaction with the character.

[0799] Step 5:

[0800] The server uses an emotion engine to identify the user's emotional state from their voice tone and words. Using the input data, it analyzes the user's current emotions and dynamically adjusts the system's response based on the analysis results. The output is then determined to provide support tailored to the user's emotions.

[0801] Step 6:

[0802] The server considers the user's emotions and past purchase history within the virtual environment to recommend appropriate products. A generated character provides customized product suggestions to the user, supporting the shopping experience. Product selection and recommendations are based on input data and emotional information.

[0803] Step 7:

[0804] When a user decides to make a purchase, the device records that information and updates the user's purchase history. This improves the accuracy of future recommendations and enables the provision of better service. The updated purchase history data is saved to the server as output.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] 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.

[0809] 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.

[0810] 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.

[0811] 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.

[0812] 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.

[0813] 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."

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] 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.

[0826] The following is further disclosed regarding the embodiments described above.

[0827] (Claim 1)

[0828] Means for acquiring and storing user information,

[0829] A means for analyzing the aforementioned user information and extracting individual personality traits,

[0830] A means for generating a character optimized for an individual based on the aforementioned personality traits,

[0831] Means for providing communication between the generated character and the user for interaction,

[0832] A means for analyzing the information during the aforementioned dialogue and optimizing the generation algorithm,

[0833] A system that includes this.

[0834] (Claim 2)

[0835] The system according to claim 1, wherein the acquisition of user information includes elements such as gender, age, region, preferences, and educational background.

[0836] (Claim 3)

[0837] The system according to claim 1, wherein the generated character interacts with the user in real time using a generative model.

[0838] "Example 1"

[0839] (Claim 1)

[0840] A means for acquiring user information and securely transmitting said user information to a processing device,

[0841] Means for storing the user information in a data storage device,

[0842] A means for processing the stored user information and extracting individual personality traits,

[0843] Means for generating individualized expressions based on the aforementioned personality traits,

[0844] A means of providing communication that exchanges information with the user through the generated representation,

[0845] Means for analyzing the exchanged information and adaptively adjusting the generation method,

[0846] A system that includes this.

[0847] (Claim 2)

[0848] The system according to claim 1, which includes elements such as personal identification, developmental stage, location, preferences, and educational background for obtaining the user information.

[0849] (Claim 3)

[0850] The system according to claim 1, which uses a generation algorithm to exchange information with the user in real time with the generated expression.

[0851] "Application Example 1"

[0852] (Claim 1)

[0853] Means for acquiring and storing user information,

[0854] A means for analyzing the aforementioned user information and extracting individual personality traits,

[0855] A means for generating a character optimized for an individual based on the aforementioned personality traits,

[0856] Means for providing communication between the generated character and the user for interaction,

[0857] A means of providing a process for recommending products based on customer preferences within a store,

[0858] A means for analyzing the information during the aforementioned dialogue and optimizing the generation algorithm,

[0859] A system that includes this.

[0860] (Claim 2)

[0861] The system according to claim 1, wherein the acquisition of user information includes elements such as gender, age, region, preferences, and educational background.

[0862] (Claim 3)

[0863] The system according to claim 1, wherein the generated character interacts with the user in real time using a generative model.

[0864] "Example 2 of combining an emotion engine"

[0865] (Claim 1)

[0866] A means for collecting user information and storing it in a data storage device,

[0867] A means for analyzing the user information and extracting individual personality traits,

[0868] A means for generating a personalized digital agent based on the aforementioned personality traits,

[0869] Means for providing a communication environment for the digital agent and the user to interact,

[0870] A means of analyzing user emotion data and dynamically adjusting the generative computation model,

[0871] A system that includes this.

[0872] (Claim 2)

[0873] The system according to claim 1, which includes demographic information and behavioral preferences for acquiring the user information.

[0874] (Claim 3)

[0875] The system according to claim 1, wherein the digital agent performs real-time interaction with the user by utilizing a generative artificial intelligence model.

[0876] "Application example 2 when combining with an emotional engine"

[0877] (Claim 1)

[0878] Means for acquiring and storing user information,

[0879] A means for analyzing the aforementioned user information and extracting individual personality traits,

[0880] A means for generating a character optimized for an individual based on the aforementioned personality traits,

[0881] Means for providing communication between the generated character and the user for interaction,

[0882] A means for analyzing the information during the aforementioned dialogue and optimizing the generation algorithm,

[0883] A means for identifying the user's emotional state during a conversation and dynamically adjusting support based on that data,

[0884] A means of using the aforementioned character as a purchasing supporter in a virtual environment and recommending products based on the user's purchase history and emotions,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, wherein the acquisition of user information includes elements such as gender, age, region, preferences, and educational background.

[0888] (Claim 3)

[0889] The system according to claim 1, wherein the generated character interacts with the user in real time using a generation model and provides purchasing support services within a virtual environment. [Explanation of Symbols]

[0890] 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. Means for acquiring and storing user information, A means for analyzing the aforementioned user information and extracting individual personality traits, A means for generating a character optimized for an individual based on the aforementioned personality traits, Means for providing communication between the generated character and the user for interaction, A means for analyzing the information during the aforementioned dialogue and optimizing the generation algorithm, A system that includes this.

2. The system according to claim 1, wherein the acquisition of user information includes elements such as gender, age, region, preferences, and educational background.

3. The system according to claim 1, wherein the generated character interacts with the user in real time using a generative model.

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