system

Abstract

We provide the system. [Solution] Means for collecting and storing users' personal information, A means for conducting a dialogue between the user and the artificial intelligence agent and analyzing the content of that dialogue, A means of diagnosing the user's personality traits based on analyzed dialogue data, A means of evaluating compatibility with other users based on diagnostic results and suggesting potential partners, A means of providing training programs to promote user growth, A means of evaluating user progress and providing feedback, 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] In conventional introduction and matchmaking services, matching is performed depending on the superficial information of users, but there is a problem that it is difficult to perform matching that sufficiently reflects the inner characteristics and personality. In addition, since there are insufficient specific means for further bringing out the charm possessed by the user himself / herself, the user may miss the opportunity for self-growth. Therefore, there is a need for a system that realizes matching considering personality and characteristics at a deeper level and supports the user's self-improvement.

Means for Solving the Problems

[0005] This invention provides means for collecting and storing a user's personal information, and means for analyzing the content of conversations between the user and an artificial intelligence agent. By using means to diagnose the user's personality traits based on the analyzed data and evaluate the degree of compatibility with other users based on the diagnosis results, more accurate partner candidates are presented. Furthermore, to promote the user's growth, an individually optimized training program is provided, and the user's potential is enhanced by evaluating their progress and providing feedback. This enables both appropriate matching that emphasizes inner characteristics and the user's own growth to be achieved simultaneously.

[0006] "User personal information" refers to information provided by the user, such as their background, hobbies, preferences, favorite foods, and preferred type of person.

[0007] An "artificial intelligence agent" is a computer program used to interact with users and analyze the content of those interactions.

[0008] "Means for analyzing dialogue content" refers to a system that analyzes conversations between a user and an artificial intelligence agent and has the function of evaluating language usage patterns and emotions.

[0009] "Methods for diagnosing personality traits" refers to the process of evaluating a user's internal personality traits based on analyzed conversational data.

[0010] A "means for evaluating compatibility" refers to a system that quantifies or qualitatively evaluates the compatibility between a user and other users based on the results of a user's personality trait assessment.

[0011] "Methods for presenting potential partners" refers to the process of listing and presenting suitable opposite-sex or same-sex partner candidates to the user based on evaluation results.

[0012] "Means of providing training programs" refers to a system that provides programs to promote growth in accordance with the user's diagnostic results and creates an environment that encourages users to engage in self-improvement.

[0013] "Means of evaluating user progress and providing feedback" refers to the process of evaluating users' growth and learning progress in a training program and informing them of areas for improvement and evaluation results based on that evaluation. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

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

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

[0017] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of the arithmetic unit include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

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

[0019] In the following embodiments, a storage with a reference numeral is one or more non-volatile storage devices that store various programs and various parameters and the like. Examples of the non-volatile storage device include a flash memory (SSD (Solid State Drive)), a magnetic disk (for example, a hard disk), or a magnetic tape, and the like.

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

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

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

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is implemented as a system that enables efficient user matching and supports the individual growth of users.

[0036] First, the device collects personal information from the user. The user enters their background, hobbies, preferences, and preferred type of person into an interface provided through the device. This information is sent to the server and stored as basic data used for future interactions and analysis.

[0037] Next, the terminal provides the user with a dialogue session with an artificial intelligence agent. Through this session, the user can freely converse with the AI ​​agent using voice and text. The server analyzes the dialogue in real time and evaluates the user's speech patterns and emotional developments. For example, if the user frequently uses positive expressions, they will be judged to be highly sociable.

[0038] Based on the analysis results, the server diagnoses the user's personality traits. Aspects such as the user's listening skills, conversational abilities, and tolerance are evaluated as numerical values ​​and comments. These diagnostic results are stored in a database and used when matching users with other users.

[0039] The server then uses the diagnostic results to evaluate how well a user is compatible with other registered users. Highly compatible user pairs are compiled into a candidate list and presented to the user via their device. For example, if it is confirmed that users not only share common hobbies but also have similar social skills and communication styles, they will be ranked higher in the matching list.

[0040] In addition, the device provides users with training programs for self-improvement. These programs are customized based on the user's assessment results and include content designed to promote user growth. Throughout the program, users receive progress feedback via the device. This feedback includes assessments of their learning progress and advice for the next steps.

[0041] This allows users to experience personal growth while having the opportunity to meet a suitable partner. The concrete implementation of this invention will enable matching that suits the user's personality, and is expected to foster long-term relationships.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The terminal displays an interface for the user to enter personal information. The user enters information such as their background, hobbies, preferences, favorite foods, and preferred type of person. The terminal sends the entered information to the server, which stores it in a database.

[0045] Step 2:

[0046] The device displays a screen prompting the user to begin a dialogue session with an artificial intelligence agent. Once the user starts the dialogue session, the device provides a voice or text conversation interface, enabling the user and the artificial intelligence agent to converse in real time.

[0047] Step 3:

[0048] The server collects the content of conversations between the user and the artificial intelligence agent and analyzes it in real time using natural language processing algorithms. In this process, it evaluates the user's statements to determine their emotions, interests, and response style, and diagnoses their personality traits.

[0049] Step 4:

[0050] The server uses the analysis results to perform a detailed diagnosis of the user's personality traits. The diagnosis results are quantified as indicators of the user's listening ability, sociability, etc., and stored in a database. This information is used in subsequent matching processes.

[0051] Step 5:

[0052] The server runs an algorithm that compares the diagnostic results of different users and evaluates the degree of relevance. It identifies users with high relevance and lists them as potential partners. The terminal then presents this list of candidates to the user.

[0053] Step 6:

[0054] The device presents the user with a selection of self-improvement programs. These programs are optimized for each user based on their diagnostic results. Once the user selects a program, the server tracks their progress and generates periodic feedback.

[0055] Step 7:

[0056] The device provides users with feedback on the training program. This feedback includes the user's progress, areas for improvement, and suggestions for the next steps. This allows users to feel a sense of personal growth while aiming for a better match.

[0057] (Example 1)

[0058] 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."

[0059] The goal is to address the challenge of insufficient efficient systems for users to accurately understand their own personality traits, find suitable partners, and promote individual growth.

[0060] 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.

[0061] In this invention, the server includes means for collecting and storing the user's personal information; means for conducting a dialogue between the user and the information processing device and analyzing the content of that dialogue; means for diagnosing the user's personality traits based on the analyzed dialogue data; means for evaluating the degree of compatibility with other users based on the diagnosis results and presenting candidates; means for using a generative model in the analysis of the dialogue; means for providing training means to promote the user's growth; and means for evaluating the user's progress and presenting the evaluation results. This enables the user to understand their own characteristics, find the optimal partner, and grow through individually designed training programs.

[0062] "User personal information" refers to individual information provided by the user, such as name, contact information, hobbies, and preferences.

[0063] An "information processing device" is an electronic device that processes and analyzes data in order to interact with the user.

[0064] "Dialogue content analysis" is the process of extracting and evaluating information from a user's statements during a conversation between a user and an information processing device.

[0065] "Personality trait diagnosis" is the process of evaluating a user's personality and behavioral characteristics based on analyzed conversational data.

[0066] "Compatibility assessment" involves comparing multiple users and expressing the degree of similarity in their personalities, hobbies, and other characteristics in numerical or list format.

[0067] "Presenting candidates" refers to displaying highly suitable user combinations in the form of a list or similar.

[0068] A "generative model" is a computational model based on AI technology used for data analysis and understanding user emotions.

[0069] "Training methods" refer to learning programs and training methods designed to promote user growth.

[0070] "Progress evaluation" involves checking the user's progress in the training program and providing feedback based on their level of achievement.

[0071] This invention is a system that deeply understands the user's personality and enables matching with a suitable partner. First, the user enters their personal information using a terminal. This terminal consists of common devices such as PCs and smartphones and provides an interface with the user.

[0072] The device sends the collected user personal information to a server. The server processes this data using an advanced generative AI model. This AI model plays a central role in interacting with the user, enabling natural conversation. Specifically, natural language processing libraries and AI frameworks are often used. This allows for real-time evaluation of emotions and speech patterns from the user's dialogue.

[0073] Users can freely converse with an artificial intelligence agent through their device. This can be done using either voice or text input, and the information obtained from the conversation is analyzed by a server. The server diagnoses the user's personality traits and evaluates their compatibility with other users based on the analysis results. This allows the server to display the most suitable candidates in a matching list, based on individual personality traits, hobbies, and other factors.

[0074] Furthermore, the device provides a personalized training program based on user feedback. This program is designed to promote user growth, allowing users to monitor their progress in real time and receive appropriate guidance.

[0075] As a concrete example, if a user registers information such as "I enjoy cooking and want to learn new recipes," not only will users with similar interests be displayed as candidates, but cooking-related training programs will also be suggested. An example of a prompt for the AI ​​model that generates dialogue in this system could be, "Based on User A's diagnostic results, please suggest the most suitable training program."

[0076] As described above, this invention can provide users with a means to help them efficiently find partners and grow professionally.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The terminal accepts personal information input from the user. The user enters information such as their background, hobbies, preferences, and preferred type of person through the terminal's interface. This input data undergoes basic preprocessing, including format checks and duplicate data removal, before being sent to the server.

[0080] Step 2:

[0081] The server stores user information received from the terminal in a database. During storage, database normalization and error detection are performed to improve data consistency and accuracy. This data is then used as the basis for subsequent analysis.

[0082] Step 3:

[0083] The terminal provides the user with an interactive session with an information processing device. The user converses with the agent through voice input or text input. The input data of the conversation is sent to the server in real time.

[0084] Step 4:

[0085] The server analyzes the received dialogue data using a generative AI model. Specifically, it breaks down the input text and speech using natural language processing techniques to recognize emotions and context. This analysis extracts the user's speech patterns and emotional tone.

[0086] Step 5:

[0087] The server diagnoses the user's personality traits based on the analysis of dialogue data. Using the analysis results as input, the server outputs numerical evaluations or comments on the user's listening skills, empathy, and other abilities. These diagnostic results are stored in a database.

[0088] Step 6:

[0089] The server evaluates the compatibility with other users based on the diagnostic results. Using personality traits and other user information as input, it assesses similarities and differences between the two and outputs a compatibility score. Based on these results, a candidate list is generated.

[0090] Step 7:

[0091] The terminal receives evaluation results from the server and presents the user with a list of candidates. The list is ranked based on similarities in preferences and personality traits and displayed on the terminal's screen.

[0092] Step 8:

[0093] The terminal provides a means of training for the user. A customized program is generated based on diagnostic results from the server, and the user can progress through this program via the terminal. Progress is constantly updated and feedback is provided to the user.

[0094] (Application Example 1)

[0095] 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."

[0096] Currently, users often lack access to appropriate information and personalized guidance and advice, which are crucial for their ability to make informed purchasing decisions and personal growth through online information. Furthermore, insufficient personalized product recommendations based on user attributes and preferences lead to a lack of valuable insights in purchasing decisions. There is a need for new technologies to address these challenges and improve the user experience.

[0097] 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.

[0098] In this invention, the server includes means for collecting and recording user attribute information, means for communicating between the user and an intelligent program and analyzing the content of that communication, and means for recommending items based on the user's preferences and guiding them to purchase. This makes it possible to optimize product recommendations and improve the purchasing experience based on each user's characteristics and interests.

[0099] A "user" is an individual or legal entity that utilizes this system and is the entity that receives services based on attribute information and preferences.

[0100] "Attribute information" refers to all information about an individual, such as a user's background, hobbies, and preferences, and is used as basic data for analysis and decision-making within the system.

[0101] An "intelligent program" is a program that uses artificial intelligence technology to communicate with users, analyze conversation content, evaluate user characteristics, and recommend items.

[0102] "Communication content" is a general term for information exchanged between the user and the intelligent program, and includes dialogue data expressed in voice and text.

[0103] "Analysis" is the process of analyzing communication content and evaluating and diagnosing patterns in user statements and emotions.

[0104] "Characteristics" refer to a collection of various individual characteristics of a user, such as their personality, interests, and purchasing tendencies, and are used by the system as the basis for diagnosis and recommendations.

[0105] "Preferences" refer to the things and areas of interest that users enjoy, and are a factor that determines the direction in which products and services are provided.

[0106] "Items" refer to specific products or services recommended to users, and are the objects that provide a purchasing experience within the system.

[0107] "Purchase" refers to the series of actions a user takes, from selecting an item through a system to completing the purchase process.

[0108] To implement this invention, a user-operated terminal and a server connected to it are required. The terminal can be a smartphone, tablet, smart glasses, or head-mounted display. Through these devices, the user can input attribute information and interact with an intelligent program. The server is responsible for processing the attribute information and communication content transmitted by the user.

[0109] The server is located in a cloud environment and uses natural language processing technologies such as Dialogflow and IBM Watson® to analyze user conversations and evaluate individual personality traits and preferences. The analysis data is stored in a database management system (e.g., MySQL®). Based on these analysis results, the server uses a generative AI model to recommend items suitable for the user. Machine learning frameworks such as TENSORFLOW® are used for item recommendations.

[0110] For example, when a user prompts the device with a statement like, "I want a new camera," the server analyzes the conversation and presents the most suitable camera recommendations and related information for that user. It also enhances the user's purchasing experience by providing user reviews and guiding them through the purchase process. Users can constantly receive new product information, which helps them make informed purchasing decisions.

[0111] Examples of prompts include "I'm looking for new fashion items," "Can you recommend some movies for the weekend?", and "I'd like to know about leisure events that my family can enjoy." In this way, information tailored to each user's individual needs is provided.

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] The user uses a terminal to input attribute information (e.g., hobbies, preferences, products of interest) and sends it to the server. The input here primarily consists of user prompts, and the output is stored on the server as user profile data. This information is stored in a database management system (e.g., MySQL) on the server and used as foundational data for subsequent analysis.

[0115] Step 2:

[0116] The user interacts with an intelligent program via a terminal and sends the content of the interaction to a server. The input at this time is text or voice data from the user. The server uses Dialogflow or IBM Watson to perform natural language processing and analyze the content of the interaction. The output is the intention, emotion, and areas of interest extracted from the user's statements, which are further used for evaluation and diagnosis.

[0117] Step 3:

[0118] The server evaluates the user's personality traits and preferences based on the analyzed dialogue data. This evaluation process is performed using a generative AI model, which quantifies or categorizes the data. The input is the utterance data obtained in the previous step, and the output is a detailed analysis of the user's attributes. This result provides the data necessary not only for updating the user profile but also for running the recommendation algorithm.

[0119] Step 4:

[0120] The server recommends items based on user attribute information and the results of dialogue data analysis. Machine learning frameworks such as TensorFlow support this process. The input is the user analysis results and a product database, and the output is a list of products best suited to the user's preferences. These recommendations are sent to the user's terminal and presented to the user visually or audibly.

[0121] Step 5:

[0122] The user reviews the recommended products displayed on the terminal and inquires for more detailed information about the products as needed. If they decide to purchase, they send a prompt to the server via the terminal. The server processes this purchase request and provides the user with payment instructions. The input is the user's selection and purchase intention, and the output is confirmation information that the purchase has been completed.

[0123] 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.

[0124] This invention is implemented as a system incorporating an emotion engine that recognizes the user's emotions. By accurately evaluating the user's emotional state using the emotion engine, it becomes possible to perform more sophisticated personality trait diagnosis, personalized matching, and self-improvement.

[0125] First, the device provides an interface for the user to input personal information. The user enters basic information such as their background, hobbies, preferences, favorite foods, and preferred type of person, and the device sends this information to the server. The server stores this information in a database and uses it for future interactions and analysis.

[0126] Next, the device displays a screen to the user to begin a dialogue session with the artificial intelligence agent. Once the user starts the session, the device engages in real-time dialogue with the artificial intelligence agent through voice and video. Here, the emotion engine is utilized to analyze the user's emotions in real time from their voice tone, facial expressions, body movements, etc., and transmit this information to the server.

[0127] The server comprehensively analyzes the received dialogue content and emotional data. For example, a user who displays a cheerful expression and frequently uses positive language is judged to be highly sociable. This allows for a detailed diagnosis of the user's personality traits. The diagnostic results are quantified and stored in the server's database.

[0128] The server then compares the results with those of other users and performs a suitability assessment that includes emotional data. This allows it to select more emotionally suitable partner candidates and present them to the user through the terminal. For example, if the analysis of facial expressions and tone indicates that the user prefers to behave cheerfully in conversations, partners with such characteristics will be recommended preferentially.

[0129] In addition, the device presents the user with a self-improvement program based on emotional data. This program is customized based on the user's emotional state and personality traits and includes, for example, tasks and sessions that promote more positive thinking. As the user progresses through the program, the server tracks their progress and provides periodic feedback.

[0130] This system allows users to achieve appropriate matching that reflects their emotional state while effectively promoting personal growth. By concretely implementing the invention, it becomes possible to build relationships that maximize the user's inner characteristics.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] The terminal displays an interface for the user to enter personal information. The user enters information such as their background, hobbies, preferences, favorite foods, and preferred type of person into a form on the screen. The terminal sends this information to the server, which stores it in a database.

[0134] Step 2:

[0135] The device displays a screen prompting the user to begin a dialogue session with an artificial intelligence agent. Once the user starts the dialogue session, the device uses its microphone and camera to capture audio and video, and prepares to send them to the server.

[0136] Step 3:

[0137] The emotion engine processes the user's video and audio, recognizing emotions from facial expressions and tone of voice. For example, if the user's face is smiling and their voice sounds cheerful, the emotion engine determines that the user is happy and adds this data to the analysis results.

[0138] Step 4:

[0139] The server integrates and analyzes the received dialogue content and emotion data. The server uses natural language processing technology to analyze the user's statements and combines them with the recognized emotion data to diagnose the user's personality traits.

[0140] Step 5:

[0141] The server compares the personality trait assessment results of other users and evaluates the degree of compatibility. This evaluation also includes emotional fit, with users having similar emotional patterns being judged to have a higher degree of compatibility. The server selects the most suitable partner candidate and presents them to the user via the device.

[0142] Step 6:

[0143] The device presents a self-improvement program optimized for the user. This program is customized based on the user's personality assessment and emotional data, and may include tasks designed to improve emotional control and communication skills, for example.

[0144] Step 7:

[0145] The server tracks the user's progress in their professional development program and performs periodic evaluations. It sends feedback to the user's device based on their progress and provides specific advice to help them move on to the next step.

[0146] This processing flow allows users to experience personalized matching that takes emotions into account, as well as personal growth.

[0147] (Example 2)

[0148] 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".

[0149] In modern society, there is a growing demand for communication and growth support environments that take into account the individuality and emotional state of users. However, technologies for accurately understanding individual personality traits and emotional states, and for appropriately forming and maintaining relationships with others, are not yet sufficiently developed. To address this challenge, there is a need for effective systems that leverage users' inner characteristics for matching and promote self-growth.

[0150] 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.

[0151] In this invention, the server includes means for collecting and storing user attribute information, means for conducting a dialogue between the user and surrogate software using artificial intelligence and analyzing the content of that dialogue, and means for diagnosing the user's personality traits based on the analyzed dialogue data and emotional data. This makes it possible to select an appropriate partner based on the user's personality and emotional state and to provide an individualized growth program.

[0152] A "user" is an individual who uses the system to input information and receives partner selection and growth support through interaction and functions.

[0153] "Attribute information" refers to basic information used to identify and characterize an individual, such as a user's background, hobbies, preferences, favorite foods, and preferred type of person.

[0154] "Agent software using artificial intelligence" refers to an interactive computer program used to perform emotional analysis and personality assessment through user interaction.

[0155] "Emotional data" refers to data that indicates the user's emotional state, analyzed from factors such as the user's voice tone, facial expressions, and posture.

[0156] "Personality traits" are the result of quantifying or classifying a user's individuality, and are characteristics that define a user's behavior and way of thinking.

[0157] "Fit" is a numerical value or evaluation that indicates the degree of commonality or compatibility between a user and other users.

[0158] "Interaction candidates" are other users suggested to the user based on their suitability, and are individuals with whom communication and relationship building can be expected.

[0159] "Personal growth" refers to changes aimed at personal development and skill improvement that users wish to achieve.

[0160] A "training program" is a series of sessions and assignments designed to improve skills and self-improvement, taking into account the user's personality traits and emotional data.

[0161] This invention is a system aimed at selecting partners and supporting self-growth, taking into account the user's personality and emotional state. The specific forms for implementing the invention are described below.

[0162] The system primarily consists of a terminal, a server, and proxy software using artificial intelligence. The terminal provides an interface for users to input personal attribute information. Users enter information such as their background and hobbies into the terminal, and this information is sent to the server. The server stores the received information in a database and makes it available for subsequent processing.

[0163] The artificial intelligence-powered proxy software analyzes emotional data in real time through interaction with the user. The device enables communication with the user through voice and video, sensing and analyzing the user's voice tone, facial expressions, posture, etc. The analyzed emotional data is sent to a server and used for personality trait diagnosis.

[0164] The server comprehensively analyzes emotional and conversational data to quantify the user's personality traits. For example, a user who frequently uses positive language is diagnosed as highly sociable. This diagnostic information is stored in a database and forms the basis for evaluating compatibility with other users.

[0165] Based on suitability assessments, the server selects potential interactions with other users and presents them to the user via the terminal. For example, sentiment analysis suggests that users who prefer cheerful behavior during conversations will be recommended interaction candidates with similar characteristics.

[0166] The device also presents users with individually tailored training programs. These programs may include tasks and sessions designed to promote positive thinking. The progress of the training program is managed by a server, and users receive regular feedback on their progress and areas for improvement.

[0167] For example, a prompt such as, "List matching candidates with personality traits suitable for highly sociable users, and propose a customized self-improvement program based on the sentiment analysis results," can be used.

[0168] Through the method described above, this invention effectively supports the selection of a partner and personal growth that takes into account the user's individuality and emotional state.

[0169] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0170] Step 1:

[0171] The terminal provides an interface for inputting user attribute information. Users input information such as their background, hobbies, and preferences, and the terminal sends this information to the server.

[0172] Input: Attribute information entered by the user.

[0173] Data processing: The terminal formats the information as structured data.

[0174] Output: Structured user information is sent to the server.

[0175] Step 2:

[0176] The server stores the received user information in a database. This information is used for subsequent interactions and analysis.

[0177] Input: Structured user information sent from the terminal.

[0178] Data processing: The server stores data in the database and creates indexes.

[0179] Output: The server records the status of information saving completion.

[0180] Step 3:

[0181] The device displays a screen to initiate a dialogue session with artificial intelligence-powered proxy software. Once the user starts the session, the device engages in dialogue through voice and video.

[0182] Input: User session start command.

[0183] Data processing: Initiating and capturing real-time streaming.

[0184] Output: Sends dialogue data (audio and video) to the server.

[0185] Step 4:

[0186] The device analyzes the user's voice tone and facial expressions in real time to analyze their emotions. The analyzed data is sent to a server.

[0187] Input: Real-time audio and video data.

[0188] Data processing: Emotional parameters are extracted through analysis using an emotion engine.

[0189] Output: The analyzed emotion data is sent to the server.

[0190] Step 5:

[0191] The server comprehensively analyzes dialogue data and emotional data to diagnose the user's personality traits.

[0192] Input: Dialogue data and sentiment data.

[0193] Data processing: Feature extraction and diagnosis based on language analysis and sentiment evaluation.

[0194] Output: The diagnostic results are saved to the database.

[0195] Step 6:

[0196] The server evaluates compatibility with other users based on the diagnostic results and selects potential interaction partners.

[0197] Input: Diagnostic result.

[0198] Data processing: Calculation of goodness of fit and candidate selection using matching algorithms.

[0199] Output: A list of highly compatible AC candidates is sent to the terminal.

[0200] Step 7:

[0201] The device presents the user with suggested interaction options. The user can browse the displayed list and select an interaction.

[0202] Input: List of potential contacts.

[0203] Data processing: Visualize candidates in the user interface.

[0204] Output: Candidate information presented to the user.

[0205] Step 8:

[0206] The device presents the user with a training program aimed at self-improvement. The program is customized based on the user's personality traits and emotional data.

[0207] Input: Personality traits and emotional data.

[0208] Data processing: Program selection and task customization.

[0209] Output: The user-facing program content is displayed.

[0210] Step 9:

[0211] The server manages the user's training program progress and provides periodic feedback.

[0212] Input: Program progress data.

[0213] Data processing: Progress analysis and feedback generation.

[0214] Output: Progress feedback is sent to the user.

[0215] (Application Example 2)

[0216] 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".

[0217] In modern consumer behavior, providing product information and service suggestions that respond to user emotions is a crucial challenge. In particular, when users experience a company's products and services in a virtual environment, traditional, uniform information provision often fails to fully capture their interest and purchasing intent. Furthermore, there are few systems that can customize the shopping experience based on the user's emotional state and suggest appropriate products, thus creating a need for new technologies to improve user satisfaction.

[0218] 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.

[0219] In this invention, the server includes means for collecting and storing the user's personal information; means for conducting a dialogue between the user and an artificial intelligence agent and analyzing the content of the dialogue; means for diagnosing the user's personality traits based on the analyzed dialogue data; means for evaluating the degree of compatibility with other users based on the diagnosis results and presenting partner candidates; means for providing training programs to promote the user's growth; means for evaluating the user's progress and providing feedback; and means for analyzing the user's emotions in real time and suggesting product information corresponding to those emotions. This enables customized purchase suggestions that are tailored to the user's emotions.

[0220] "Personal information" refers to information that identifies and characterizes individual users, such as their history, hobbies, preferences, favorite foods, and preferred types of people.

[0221] An "artificial intelligence agent" is a program that analyzes information through interaction with the user and evaluates the user's personality traits and emotions.

[0222] "Analysis of dialogue content" involves analyzing information obtained during the communication process between the user and the artificial intelligence agent to understand the user's personality traits and emotional state.

[0223] "Personality trait diagnosis" is the process of evaluating the internal personality characteristics of a user based on their conversational data and emotional data.

[0224] "Compatibility assessment" involves measuring the degree of emotional and personality match between users based on the diagnostic results, and selecting the most suitable partner candidate.

[0225] A "training program" consists of assignments and sessions designed to support user growth, and is customized to the individual user's needs.

[0226] "Progress evaluation" involves monitoring the progress of a training program and analyzing how much users are growing.

[0227] "Feedback" refers to information that provides users with progress-based evaluations and advice, thereby promoting more effective self-improvement.

[0228] "Real-time emotional analysis" involves instantly analyzing a user's emotional state at a given moment based on their voice tone, facial expressions, body movements, and other factors.

[0229] "Product information suggestion" refers to presenting appropriate product and service information based on the user's analyzed emotions, thereby encouraging purchasing behavior.

[0230] To implement this invention, a system is required that includes an application installed on a user's terminal and processing performed by a central server. Specifically, this system consists of a terminal that provides an interface for collecting the user's personal information and a server that analyzes and stores that information.

[0231] The server uses software such as TensorFlow and OpenCV to analyze user emotional data, including voice tone, facial expressions, and body movements, in real time. This allows for the evaluation of the user's personality traits and enables emotion-based purchasing suggestions. This system can present the most suitable products according to the user's emotions and can utilize generative AI models to improve the user experience.

[0232] In terms of specific operations, when a user accesses a virtual store using a device, emotional data is collected through smart glasses or a head-mounted display. The server analyzes this data, generates appropriate product information, and presents it to the user. It also proposes training programs to support the user's growth, tracks their progress, and provides feedback. This allows users to enjoy a personalized shopping experience tailored to their individual emotions.

[0233] For example, if a user experiences an emotion such as "fun" while walking around a store, the system can suggest products that correspond to that emotion, such as new products or items with unique designs.

[0234] An example of a prompt would be: "Write a prompt to analyze the facial expressions and tone of voice a user displays during their shopping experience and suggest products based on their emotional state." This serves as a guide for an AI model to generate appropriate product suggestions based on emotions.

[0235] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0236] Step 1:

[0237] The terminal displays an interface for entering the user's personal information. When the user enters their background, hobbies, and other personal information, this data is collected and sent to the server. This data is stored on the server for use in future interactions and analysis.

[0238] Step 2:

[0239] The terminal displays a screen for a dialogue session with an artificial intelligence agent, and the user initiates the session. Once the user gives the start command, the terminal performs a real-time dialogue through voice and video. It uses the user's voice and video data as input and sends it to the server as material for interpretation.

[0240] Step 3:

[0241] The server analyzes the received audio and video data and uses tools such as TensorFlow and OpenCV to evaluate the user's voice tone, facial expressions, and body movements in real time. In this step, data processing is performed and analysis results are output to obtain the user's emotional state.

[0242] Step 4:

[0243] The server integrates the analysis results of the conversation content with emotional data to diagnose the user's personality traits. The diagnosis quantifies the personality based on the entered personal information and emotional data obtained in real time, and outputs an evaluation of the user's characteristics.

[0244] Step 5:

[0245] The server compares the user's diagnostic data with that of other users and performs a suitability assessment. In this step, partner candidates are selected based on the user's personality traits and emotional data, and output is generated to present the user with the most suitable candidate.

[0246] Step 6:

[0247] The server creates individually customized training programs based on the user's emotional data and delivers them to the user via the terminal. This suggests tasks for self-improvement tailored to the user's emotions and personality. Furthermore, the server continuously tracks the program's progress.

[0248] Step 7:

[0249] The server uses a generative AI model to generate product information tailored to the user's emotions and presents it to the user through the terminal. In this step, prompts generated based on emotion data are used to further personalize the content. This allows the user to receive a shopping experience optimized for their own emotional state.

[0250] 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.

[0251] 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 those described above. 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 shown 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.

[0252] 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.

[0253] [Second Embodiment]

[0254] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0255] 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.

[0256] 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).

[0257] 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.

[0258] 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.

[0259] 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).

[0260] 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.

[0261] 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.

[0262] 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.

[0263] 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.

[0264] 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.

[0265] 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".

[0266] This invention is implemented as a system that enables efficient user matching and supports the individual growth of users.

[0267] First, the device collects personal information from the user. The user enters their background, hobbies, preferences, and preferred type of person into an interface provided through the device. This information is sent to the server and stored as basic data used for future interactions and analysis.

[0268] Next, the terminal provides the user with a dialogue session with an artificial intelligence agent. Through this session, the user can freely converse with the AI ​​agent using voice and text. The server analyzes the dialogue in real time and evaluates the user's speech patterns and emotional developments. For example, if the user frequently uses positive expressions, they will be judged to be highly sociable.

[0269] Based on the analysis results, the server diagnoses the user's personality traits. Aspects such as the user's listening skills, conversational abilities, and tolerance are evaluated as numerical values ​​and comments. These diagnostic results are stored in a database and used when matching users with other users.

[0270] The server then uses the diagnostic results to evaluate how well a user is compatible with other registered users. Highly compatible user pairs are compiled into a candidate list and presented to the user via their device. For example, if it is confirmed that users not only share common hobbies but also have similar social skills and communication styles, they will be ranked higher in the matching list.

[0271] In addition, the device provides users with training programs for self-improvement. These programs are customized based on the user's assessment results and include content designed to promote user growth. Throughout the program, users receive progress feedback via the device. This feedback includes assessments of their learning progress and advice for the next steps.

[0272] This allows users to experience personal growth while having the opportunity to meet a suitable partner. The concrete implementation of this invention will enable matching that suits the user's personality, and is expected to foster long-term relationships.

[0273] The following describes the processing flow.

[0274] Step 1:

[0275] The terminal displays an interface for the user to input personal information. The user inputs information such as work experience, hobbies, preferences, favorite foods, and preferred types. The terminal sends the input information to the server, and the server saves it in the database.

[0276] Step 2:

[0277] The terminal presents the user with a screen prompting the start of a conversation session with an AI agent. When the user starts the conversation session, the terminal provides a voice or text conversation interface, enabling the user and the AI agent to converse in real time.

[0278] Step 3:

[0279] The server collects the conversation content between the user and the AI agent and analyzes it in real time using natural language processing algorithms. In this process, emotions, interests, response styles, etc. are evaluated from the user's speech, and personality traits are diagnosed.

[0280] Step 4:

[0281] Based on the analysis results, the server diagnoses the user's personality traits in detail. The diagnosis results are quantified as indicators such as the user's listening ability and sociability and saved in the database. This information is used in subsequent matching processes.

[0282] Step 5:

[0283] The server executes an algorithm to compare and evaluate the compatibility with the diagnosis results of another user. Users with a high compatibility are identified and listed as potential partners. The terminal presents this candidate list to the user.

[0284] Step 6:

[0285] The terminal presents the user with options for self-improvement programs. These programs are optimized for each user based on their diagnostic results. When the user selects a program, the server tracks the progress and generates regular feedback.

[0286] Step 7:

[0287] The terminal provides the user with feedback on the training program. The feedback includes the user's progress, areas for improvement, and suggestions for the next steps. This enables the user to aim for better matching while experiencing self-growth.

[0288] (Example 1)

[0289] Next, 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".

[0290] To solve the problem that there is a lack of an efficient system for users to accurately understand their own personality characteristics, find suitable partners, and further promote individual growth.

[0291] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0292] In this invention, the server includes means for collecting and storing the user's personal information, means for conducting a dialogue between the user and the information processing device and analyzing the content of the dialogue, means for diagnosing the user's personality characteristics based on the analyzed dialogue data, means for evaluating the compatibility with other users based on the diagnosis results and presenting candidates, means for using a generation model for the analysis of the dialogue, means for providing training means for promoting the user's growth, and means for evaluating the user's progress and presenting the evaluation results. Thereby, the user can understand their own characteristics, find the optimal partner, and achieve growth through an individually designed training program.

[0293] "User personal information" refers to individual information provided by the user, such as name, contact information, hobbies, and preferences.

[0294] An "information processing device" is an electronic device that processes and analyzes data in order to interact with the user.

[0295] "Dialogue content analysis" is the process of extracting and evaluating information from a user's statements during a conversation between a user and an information processing device.

[0296] "Personality trait diagnosis" is the process of evaluating a user's personality and behavioral characteristics based on analyzed conversational data.

[0297] "Compatibility assessment" involves comparing multiple users and expressing the degree of similarity in their personalities, hobbies, and other characteristics in numerical or list format.

[0298] "Presenting candidates" refers to displaying highly suitable user combinations in the form of a list or similar.

[0299] A "generative model" is a computational model based on AI technology used for data analysis and understanding user emotions.

[0300] "Training methods" refer to learning programs and training methods designed to promote user growth.

[0301] "Progress evaluation" involves checking the user's progress in the training program and providing feedback based on their level of achievement.

[0302] This invention is a system that deeply understands the user's personality and enables matching with a suitable partner. First, the user enters their personal information using a terminal. This terminal consists of common devices such as PCs and smartphones and provides an interface with the user.

[0303] The terminal sends the collected personal information of the user to the server. The server processes these data using an advanced generative AI model. This AI model plays a central role when interacting with the user and enables natural conversations. As specific software, natural language processing libraries and AI frameworks are often used. Thereby, it is possible to evaluate emotions and speech patterns in real time from the content of the conversation with the user.

[0304] The user can freely converse with the artificial intelligence agent through the terminal. At this time, voice input or text input can be used, and the information obtained from the conversation with the user is analyzed by the server. The server diagnoses the user's personality traits and evaluates the compatibility with other users based on the analysis results. Thereby, the optimal candidates are displayed in the matching list based on individual personalities, hobbies, etc.

[0305] Furthermore, the terminal provides an individually designed training program through feedback to the user. This program is designed to promote the growth of the user, and the user can confirm their progress in real time and receive appropriate guidance.

[0306] As a specific example, when the user registers information such as "Cooking is a hobby and I want to learn new recipes", not only users with common hobbies are displayed as candidates, but also a training program related to cooking is proposed. Examples of prompt texts for the dialogue generation AI model of this system include things like "Please propose an optimal training program based on the diagnosis result of User A".

[0307] As described above, this invention can provide the user with means to assist in efficient partner searching and growth.

[0308] The flow of the specific process in Example 1 will be described using FIG. 11.

[0309] Step 1:

[0310] The terminal accepts personal information input from the user. The user enters information such as their background, hobbies, preferences, and preferred type of person through the terminal's interface. This input data undergoes basic preprocessing, including format checks and duplicate data removal, before being sent to the server.

[0311] Step 2:

[0312] The server stores user information received from the terminal in a database. During storage, database normalization and error detection are performed to improve data consistency and accuracy. This data is then used as the basis for subsequent analysis.

[0313] Step 3:

[0314] The terminal provides the user with an interactive session with an information processing device. The user converses with the agent through voice input or text input. The input data of the conversation is sent to the server in real time.

[0315] Step 4:

[0316] The server analyzes the received dialogue data using a generative AI model. Specifically, it breaks down the input text and speech using natural language processing techniques to recognize emotions and context. This analysis extracts the user's speech patterns and emotional tone.

[0317] Step 5:

[0318] The server diagnoses the user's personality traits based on the analysis of dialogue data. Using the analysis results as input, the server outputs numerical evaluations or comments on the user's listening skills, empathy, and other abilities. These diagnostic results are stored in a database.

[0319] Step 6:

[0320] The server evaluates the compatibility with other users based on the diagnostic results. Using personality traits and other user information as input, it assesses similarities and differences between the two and outputs a compatibility score. Based on these results, a candidate list is generated.

[0321] Step 7:

[0322] The terminal receives evaluation results from the server and presents the user with a list of candidates. The list is ranked based on similarities in preferences and personality traits and displayed on the terminal's screen.

[0323] Step 8:

[0324] The terminal provides a means of training for the user. A customized program is generated based on diagnostic results from the server, and the user can progress through this program via the terminal. Progress is constantly updated and feedback is provided to the user.

[0325] (Application Example 1)

[0326] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0327] Currently, users often lack access to appropriate information and personalized guidance and advice, which are crucial for their ability to make informed purchasing decisions and personal growth through online information. Furthermore, insufficient personalized product recommendations based on user attributes and preferences lead to a lack of valuable insights in purchasing decisions. There is a need for new technologies to address these challenges and improve the user experience.

[0328] 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.

[0329] In this invention, the server includes means for collecting and recording user attribute information, means for communicating between the user and an intelligent program and analyzing the content of that communication, and means for recommending items based on the user's preferences and guiding them to purchase. This makes it possible to optimize product recommendations and improve the purchasing experience based on each user's characteristics and interests.

[0330] A "user" is an individual or legal entity that utilizes this system and is the entity that receives services based on attribute information and preferences.

[0331] "Attribute information" refers to all information about an individual, such as a user's background, hobbies, and preferences, and is used as basic data for analysis and decision-making within the system.

[0332] An "intelligent program" is a program that uses artificial intelligence technology to communicate with users, analyze conversation content, evaluate user characteristics, and recommend items.

[0333] "Communication content" is a general term for information exchanged between the user and the intelligent program, and includes dialogue data expressed in voice and text.

[0334] "Analysis" is the process of analyzing communication content and evaluating and diagnosing patterns in user statements and emotions.

[0335] "Characteristics" refer to a collection of various individual characteristics of a user, such as their personality, interests, and purchasing tendencies, and are used by the system as the basis for diagnosis and recommendations.

[0336] "Preferences" refer to the things and areas of interest that users enjoy, and are a factor that determines the direction in which products and services are provided.

[0337] "Items" refer to specific products or services recommended to users, and are the objects that provide a purchasing experience within the system.

[0338] "Purchase" refers to the series of actions a user takes, from selecting an item through a system to completing the purchase process.

[0339] To implement this invention, a user-operated terminal and a server connected to it are required. The terminal can be a smartphone, tablet, smart glasses, or head-mounted display. Through these devices, the user can input attribute information and interact with an intelligent program. The server is responsible for processing the attribute information and communication content transmitted by the user.

[0340] The server is located in a cloud environment and uses natural language processing technologies such as Dialogflow and IBM Watson to analyze user conversations and evaluate individual personality traits and preferences. The analysis data is stored in a database management system (e.g., MySQL). Based on these analysis results, the server uses a generative AI model to recommend items suitable for the user. Machine learning frameworks such as TensorFlow are used for item recommendation.

[0341] For example, when a user prompts the device with a statement like, "I want a new camera," the server analyzes the conversation and presents the most suitable camera recommendations and related information for that user. It also enhances the user's purchasing experience by providing user reviews and guiding them through the purchase process. Users can constantly receive new product information, which helps them make informed purchasing decisions.

[0342] Examples of prompts include "I'm looking for new fashion items," "Can you recommend some movies for the weekend?", and "I'd like to know about leisure events that my family can enjoy." In this way, information tailored to each user's individual needs is provided.

[0343] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0344] Step 1:

[0345] The user uses a terminal to input attribute information (e.g., hobbies, preferences, products of interest) and sends it to the server. The input here primarily consists of user prompts, and the output is stored on the server as user profile data. This information is stored in a database management system (e.g., MySQL) on the server and used as foundational data for subsequent analysis.

[0346] Step 2:

[0347] The user interacts with an intelligent program via a terminal and sends the content of the interaction to a server. The input at this time is text or voice data from the user. The server uses Dialogflow or IBM Watson to perform natural language processing and analyze the content of the interaction. The output is the intention, emotion, and areas of interest extracted from the user's statements, which are further used for evaluation and diagnosis.

[0348] Step 3:

[0349] The server evaluates the user's personality traits and preferences based on the analyzed dialogue data. This evaluation process is performed using a generative AI model, which quantifies or categorizes the data. The input is the utterance data obtained in the previous step, and the output is a detailed analysis of the user's attributes. This result provides the data necessary not only for updating the user profile but also for running the recommendation algorithm.

[0350] Step 4:

[0351] The server recommends items based on user attribute information and the results of dialogue data analysis. Machine learning frameworks such as TensorFlow support this process. The input is the user analysis results and a product database, and the output is a list of products best suited to the user's preferences. These recommendations are sent to the user's terminal and presented to the user visually or audibly.

[0352] Step 5:

[0353] The user reviews the recommended products displayed on the terminal and inquires for more detailed information about the products as needed. If they decide to purchase, they send a prompt to the server via the terminal. The server processes this purchase request and provides the user with payment instructions. The input is the user's selection and purchase intention, and the output is confirmation information that the purchase has been completed.

[0354] 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.

[0355] This invention is implemented as a system incorporating an emotion engine that recognizes the user's emotions. By accurately evaluating the user's emotional state using the emotion engine, it becomes possible to perform more sophisticated personality trait diagnosis, personalized matching, and self-improvement.

[0356] First, the device provides an interface for the user to input personal information. The user enters basic information such as their background, hobbies, preferences, favorite foods, and preferred type of person, and the device sends this information to the server. The server stores this information in a database and uses it for future interactions and analysis.

[0357] Next, the device displays a screen to the user to begin a dialogue session with the artificial intelligence agent. Once the user starts the session, the device engages in real-time dialogue with the artificial intelligence agent through voice and video. Here, the emotion engine is utilized to analyze the user's emotions in real time from their voice tone, facial expressions, body movements, etc., and transmit this information to the server.

[0358] The server comprehensively analyzes the received dialogue content and emotional data. For example, a user who displays a cheerful expression and frequently uses positive language is judged to be highly sociable. This allows for a detailed diagnosis of the user's personality traits. The diagnostic results are quantified and stored in the server's database.

[0359] The server then compares the results with those of other users and performs a suitability assessment that includes emotional data. This allows it to select more emotionally suitable partner candidates and present them to the user through the terminal. For example, if the analysis of facial expressions and tone indicates that the user prefers to behave cheerfully in conversations, partners with such characteristics will be recommended preferentially.

[0360] In addition, the device presents the user with a self-improvement program based on emotional data. This program is customized based on the user's emotional state and personality traits and includes, for example, tasks and sessions that promote more positive thinking. As the user progresses through the program, the server tracks their progress and provides periodic feedback.

[0361] This system allows users to achieve appropriate matching that reflects their emotional state while effectively promoting personal growth. By concretely implementing the invention, it becomes possible to build relationships that maximize the user's inner characteristics.

[0362] The following describes the processing flow.

[0363] Step 1:

[0364] The terminal displays an interface for the user to enter personal information. The user enters information such as their background, hobbies, preferences, favorite foods, and preferred type of person into a form on the screen. The terminal sends this information to the server, which stores it in a database.

[0365] Step 2:

[0366] The device displays a screen prompting the user to begin a dialogue session with an artificial intelligence agent. Once the user starts the dialogue session, the device uses its microphone and camera to capture audio and video, and prepares to send them to the server.

[0367] Step 3:

[0368] The emotion engine processes the user's video and audio, recognizing emotions from facial expressions and tone of voice. For example, if the user's face is smiling and their voice sounds cheerful, the emotion engine determines that the user is happy and adds this data to the analysis results.

[0369] Step 4:

[0370] The server integrates and analyzes the received dialogue content and emotion data. The server uses natural language processing technology to analyze the user's statements and combines them with the recognized emotion data to diagnose the user's personality traits.

[0371] Step 5:

[0372] The server compares the personality trait assessment results of other users and evaluates the degree of compatibility. This evaluation also includes emotional fit, with users having similar emotional patterns being judged to have a higher degree of compatibility. The server selects the most suitable partner candidate and presents them to the user via the device.

[0373] Step 6:

[0374] The device presents a self-improvement program optimized for the user. This program is customized based on the user's personality assessment and emotional data, and may include tasks designed to improve emotional control and communication skills, for example.

[0375] Step 7:

[0376] The server tracks the user's progress in their professional development program and performs periodic evaluations. It sends feedback to the user's device based on their progress and provides specific advice to help them move on to the next step.

[0377] This processing flow allows users to experience personalized matching that takes emotions into account, as well as personal growth.

[0378] (Example 2)

[0379] 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".

[0380] In modern society, there is a growing demand for communication and growth support environments that take into account the individuality and emotional state of users. However, technologies for accurately understanding individual personality traits and emotional states, and for appropriately forming and maintaining relationships with others, are not yet sufficiently developed. To address this challenge, there is a need for effective systems that leverage users' inner characteristics for matching and promote self-growth.

[0381] 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.

[0382] In this invention, the server includes means for collecting and storing user attribute information, means for conducting a dialogue between the user and surrogate software using artificial intelligence and analyzing the content of that dialogue, and means for diagnosing the user's personality traits based on the analyzed dialogue data and emotional data. This makes it possible to select an appropriate partner based on the user's personality and emotional state and to provide an individualized growth program.

[0383] A "user" is an individual who uses the system to input information and receives partner selection and growth support through interaction and functions.

[0384] "Attribute information" refers to basic information used to identify and characterize an individual, such as a user's background, hobbies, preferences, favorite foods, and preferred type of person.

[0385] "Agent software using artificial intelligence" refers to an interactive computer program used to perform emotional analysis and personality assessment through user interaction.

[0386] "Emotional data" refers to data that indicates the user's emotional state, analyzed from factors such as the user's voice tone, facial expressions, and posture.

[0387] "Personality traits" are the result of quantifying or classifying a user's individuality, and are characteristics that define a user's behavior and way of thinking.

[0388] "Fit" is a numerical value or evaluation that indicates the degree of commonality or compatibility between a user and other users.

[0389] "Interaction candidates" are other users suggested to the user based on their suitability, and are individuals with whom communication and relationship building can be expected.

[0390] "Personal growth" refers to changes aimed at personal development and skill improvement that users wish to achieve.

[0391] A "training program" is a series of sessions and assignments designed to improve skills and self-improvement, taking into account the user's personality traits and emotional data.

[0392] This invention is a system aimed at selecting partners and supporting self-growth, taking into account the user's personality and emotional state. The specific forms for implementing the invention are described below.

[0393] The system primarily consists of a terminal, a server, and proxy software using artificial intelligence. The terminal provides an interface for users to input personal attribute information. Users enter information such as their background and hobbies into the terminal, and this information is sent to the server. The server stores the received information in a database and makes it available for subsequent processing.

[0394] The artificial intelligence-powered proxy software analyzes emotional data in real time through interaction with the user. The device enables communication with the user through voice and video, sensing and analyzing the user's voice tone, facial expressions, posture, etc. The analyzed emotional data is sent to a server and used for personality trait diagnosis.

[0395] The server comprehensively analyzes emotional and conversational data to quantify the user's personality traits. For example, a user who frequently uses positive language is diagnosed as highly sociable. This diagnostic information is stored in a database and forms the basis for evaluating compatibility with other users.

[0396] Based on suitability assessments, the server selects potential interactions with other users and presents them to the user via the terminal. For example, sentiment analysis suggests that users who prefer cheerful behavior during conversations will be recommended interaction candidates with similar characteristics.

[0397] The device also presents users with individually tailored training programs. These programs may include tasks and sessions designed to promote positive thinking. The progress of the training program is managed by a server, and users receive regular feedback on their progress and areas for improvement.

[0398] For example, a prompt such as, "List matching candidates with personality traits suitable for highly sociable users, and propose a customized self-improvement program based on the sentiment analysis results," can be used.

[0399] Through the method described above, this invention effectively supports the selection of a partner and personal growth that takes into account the user's individuality and emotional state.

[0400] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0401] Step 1:

[0402] The terminal provides an interface for inputting user attribute information. Users input information such as their background, hobbies, and preferences, and the terminal sends this information to the server.

[0403] Input: Attribute information entered by the user.

[0404] Data processing: The terminal formats the information as structured data.

[0405] Output: Structured user information is sent to the server.

[0406] Step 2:

[0407] The server stores the received user information in a database. This information is used for subsequent interactions and analysis.

[0408] Input: Structured user information sent from the terminal.

[0409] Data processing: The server stores data in the database and creates indexes.

[0410] Output: The server records the status of information saving completion.

[0411] Step 3:

[0412] The device displays a screen to initiate a dialogue session with artificial intelligence-powered proxy software. Once the user starts the session, the device engages in dialogue through voice and video.

[0413] Input: User session start command.

[0414] Data processing: Initiating and capturing real-time streaming.

[0415] Output: Sends dialogue data (audio and video) to the server.

[0416] Step 4:

[0417] The device analyzes the user's voice tone and facial expressions in real time to analyze their emotions. The analyzed data is sent to a server.

[0418] Input: Real-time audio and video data.

[0419] Data processing: Emotional parameters are extracted through analysis using an emotion engine.

[0420] Output: The analyzed emotion data is sent to the server.

[0421] Step 5:

[0422] The server comprehensively analyzes dialogue data and emotional data to diagnose the user's personality traits.

[0423] Input: Dialogue data and sentiment data.

[0424] Data processing: Feature extraction and diagnosis based on language analysis and sentiment evaluation.

[0425] Output: The diagnostic results are saved to the database.

[0426] Step 6:

[0427] The server evaluates compatibility with other users based on the diagnostic results and selects potential interaction partners.

[0428] Input: Diagnostic result.

[0429] Data processing: Calculation of goodness of fit and candidate selection using matching algorithms.

[0430] Output: A list of highly compatible AC candidates is sent to the terminal.

[0431] Step 7:

[0432] The device presents the user with suggested interaction options. The user can browse the displayed list and select an interaction.

[0433] Input: List of potential contacts.

[0434] Data processing: Visualize candidates in the user interface.

[0435] Output: Candidate information presented to the user.

[0436] Step 8:

[0437] The device presents the user with a training program aimed at self-improvement. The program is customized based on the user's personality traits and emotional data.

[0438] Input: Personality traits and emotional data.

[0439] Data processing: Program selection and task customization.

[0440] Output: The user-facing program content is displayed.

[0441] Step 9:

[0442] The server manages the user's training program progress and provides periodic feedback.

[0443] Input: Program progress data.

[0444] Data processing: Progress analysis and feedback generation.

[0445] Output: Progress feedback is sent to the user.

[0446] (Application Example 2)

[0447] 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."

[0448] In modern consumer behavior, providing product information and service suggestions that respond to user emotions is a crucial challenge. In particular, when users experience a company's products and services in a virtual environment, traditional, uniform information provision often fails to fully capture their interest and purchasing intent. Furthermore, there are few systems that can customize the shopping experience based on the user's emotional state and suggest appropriate products, thus creating a need for new technologies to improve user satisfaction.

[0449] 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.

[0450] In this invention, the server includes means for collecting and storing the user's personal information; means for conducting a dialogue between the user and an artificial intelligence agent and analyzing the content of the dialogue; means for diagnosing the user's personality traits based on the analyzed dialogue data; means for evaluating the degree of compatibility with other users based on the diagnosis results and presenting partner candidates; means for providing training programs to promote the user's growth; means for evaluating the user's progress and providing feedback; and means for analyzing the user's emotions in real time and suggesting product information corresponding to those emotions. This enables customized purchase suggestions that are tailored to the user's emotions.

[0451] "Personal information" refers to information that identifies and characterizes individual users, such as their history, hobbies, preferences, favorite foods, and preferred types of people.

[0452] An "artificial intelligence agent" is a program that analyzes information through interaction with the user and evaluates the user's personality traits and emotions.

[0453] "Analysis of dialogue content" involves analyzing information obtained during the communication process between the user and the artificial intelligence agent to understand the user's personality traits and emotional state.

[0454] "Personality trait diagnosis" is the process of evaluating the internal personality characteristics of a user based on their conversational data and emotional data.

[0455] "Compatibility assessment" involves measuring the degree of emotional and personality match between users based on the diagnostic results, and selecting the most suitable partner candidate.

[0456] A "training program" consists of assignments and sessions designed to support user growth, and is customized to the individual user's needs.

[0457] "Progress evaluation" involves monitoring the progress of a training program and analyzing how much users are growing.

[0458] "Feedback" refers to information that provides users with progress-based evaluations and advice, thereby promoting more effective self-improvement.

[0459] "Real-time emotional analysis" involves instantly analyzing a user's emotional state at a given moment based on their voice tone, facial expressions, body movements, and other factors.

[0460] "Product information suggestion" refers to presenting appropriate product and service information based on the user's analyzed emotions, thereby encouraging purchasing behavior.

[0461] To implement this invention, a system is required that includes an application installed on a user's terminal and processing performed by a central server. Specifically, this system consists of a terminal that provides an interface for collecting the user's personal information and a server that analyzes and stores that information.

[0462] The server uses software such as TensorFlow and OpenCV to analyze user emotional data, including voice tone, facial expressions, and body movements, in real time. This allows for the evaluation of the user's personality traits and enables emotion-based purchasing suggestions. This system can present the most suitable products according to the user's emotions and can utilize generative AI models to improve the user experience.

[0463] In terms of specific operations, when a user accesses a virtual store using a device, emotional data is collected through smart glasses or a head-mounted display. The server analyzes this data, generates appropriate product information, and presents it to the user. It also proposes training programs to support the user's growth, tracks their progress, and provides feedback. This allows users to enjoy a personalized shopping experience tailored to their individual emotions.

[0464] For example, if a user experiences an emotion such as "fun" while walking around a store, the system can suggest products that correspond to that emotion, such as new products or items with unique designs.

[0465] An example of a prompt would be: "Write a prompt to analyze the facial expressions and tone of voice a user displays during their shopping experience and suggest products based on their emotional state." This serves as a guide for an AI model to generate appropriate product suggestions based on emotions.

[0466] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0467] Step 1:

[0468] The terminal displays an interface for entering the user's personal information. When the user enters their background, hobbies, and other personal information, this data is collected and sent to the server. This data is stored on the server for use in future interactions and analysis.

[0469] Step 2:

[0470] The terminal displays a screen for a dialogue session with an artificial intelligence agent, and the user initiates the session. Once the user gives the start command, the terminal performs a real-time dialogue through voice and video. It uses the user's voice and video data as input and sends it to the server as material for interpretation.

[0471] Step 3:

[0472] The server analyzes the received audio and video data and uses tools such as TensorFlow and OpenCV to evaluate the user's voice tone, facial expressions, and body movements in real time. In this step, data processing is performed and analysis results are output to obtain the user's emotional state.

[0473] Step 4:

[0474] The server integrates the analysis results of the conversation content with emotional data to diagnose the user's personality traits. The diagnosis quantifies the personality based on the entered personal information and emotional data obtained in real time, and outputs an evaluation of the user's characteristics.

[0475] Step 5:

[0476] The server compares the user's diagnostic data with that of other users and performs a suitability assessment. In this step, partner candidates are selected based on the user's personality traits and emotional data, and output is generated to present the user with the most suitable candidate.

[0477] Step 6:

[0478] The server creates individually customized training programs based on the user's emotional data and delivers them to the user via the terminal. This suggests tasks for self-improvement tailored to the user's emotions and personality. Furthermore, the server continuously tracks the program's progress.

[0479] Step 7:

[0480] The server uses a generative AI model to generate product information tailored to the user's emotions and presents it to the user through the terminal. In this step, prompts generated based on emotion data are used to further personalize the content. This allows the user to receive a shopping experience optimized for their own emotional state.

[0481] 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.

[0482] 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 those described above. 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 shown 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.

[0483] 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.

[0484] [Third Embodiment]

[0485] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0486] 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.

[0487] 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).

[0488] 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.

[0489] 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.

[0490] 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).

[0491] 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.

[0492] 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.

[0493] 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.

[0494] 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.

[0495] 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.

[0496] 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".

[0497] This invention is implemented as a system that enables efficient user matching and supports the individual growth of users.

[0498] First, the device collects personal information from the user. The user enters their background, hobbies, preferences, and preferred type of person into an interface provided through the device. This information is sent to the server and stored as basic data used for future interactions and analysis.

[0499] Next, the terminal provides the user with a dialogue session with an artificial intelligence agent. Through this session, the user can freely converse with the AI ​​agent using voice and text. The server analyzes the dialogue in real time and evaluates the user's speech patterns and emotional developments. For example, if the user frequently uses positive expressions, they will be judged to be highly sociable.

[0500] Based on the analysis results, the server diagnoses the user's personality traits. Aspects such as the user's listening skills, conversational abilities, and tolerance are evaluated as numerical values ​​and comments. These diagnostic results are stored in a database and used when matching users with other users.

[0501] The server then uses the diagnostic results to evaluate how well a user is compatible with other registered users. Highly compatible user pairs are compiled into a candidate list and presented to the user via their device. For example, if it is confirmed that users not only share common hobbies but also have similar social skills and communication styles, they will be ranked higher in the matching list.

[0502] In addition, the device provides users with training programs for self-improvement. These programs are customized based on the user's assessment results and include content designed to promote user growth. Throughout the program, users receive progress feedback via the device. This feedback includes assessments of their learning progress and advice for the next steps.

[0503] This allows users to experience personal growth while having the opportunity to meet a suitable partner. The concrete implementation of this invention will enable matching that suits the user's personality, and is expected to foster long-term relationships.

[0504] The following describes the processing flow.

[0505] Step 1:

[0506] The terminal displays an interface for the user to enter personal information. The user enters information such as their background, hobbies, preferences, favorite foods, and preferred type of person. The terminal sends the entered information to the server, which stores it in a database.

[0507] Step 2:

[0508] The device displays a screen prompting the user to begin a dialogue session with an artificial intelligence agent. Once the user starts the dialogue session, the device provides a voice or text conversation interface, enabling the user and the artificial intelligence agent to converse in real time.

[0509] Step 3:

[0510] The server collects the content of conversations between the user and the artificial intelligence agent and analyzes it in real time using natural language processing algorithms. In this process, it evaluates the user's statements to determine their emotions, interests, and response style, and diagnoses their personality traits.

[0511] Step 4:

[0512] The server uses the analysis results to perform a detailed diagnosis of the user's personality traits. The diagnosis results are quantified as indicators of the user's listening ability, sociability, etc., and stored in a database. This information is used in subsequent matching processes.

[0513] Step 5:

[0514] The server runs an algorithm that compares the diagnostic results of different users and evaluates the degree of relevance. It identifies users with high relevance and lists them as potential partners. The terminal then presents this list of candidates to the user.

[0515] Step 6:

[0516] The device presents the user with a selection of self-improvement programs. These programs are optimized for each user based on their diagnostic results. Once the user selects a program, the server tracks their progress and generates periodic feedback.

[0517] Step 7:

[0518] The device provides users with feedback on the training program. This feedback includes the user's progress, areas for improvement, and suggestions for the next steps. This allows users to feel a sense of personal growth while aiming for a better match.

[0519] (Example 1)

[0520] 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."

[0521] The goal is to address the challenge of insufficient efficient systems for users to accurately understand their own personality traits, find suitable partners, and promote individual growth.

[0522] 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.

[0523] In this invention, the server includes means for collecting and storing the user's personal information; means for conducting a dialogue between the user and the information processing device and analyzing the content of that dialogue; means for diagnosing the user's personality traits based on the analyzed dialogue data; means for evaluating the degree of compatibility with other users based on the diagnosis results and presenting candidates; means for using a generative model in the analysis of the dialogue; means for providing training means to promote the user's growth; and means for evaluating the user's progress and presenting the evaluation results. This enables the user to understand their own characteristics, find the optimal partner, and grow through individually designed training programs.

[0524] "User personal information" refers to individual information provided by the user, such as name, contact information, hobbies, and preferences.

[0525] An "information processing device" is an electronic device that processes and analyzes data in order to interact with the user.

[0526] "Dialogue content analysis" is the process of extracting and evaluating information from a user's statements during a conversation between a user and an information processing device.

[0527] "Personality trait diagnosis" is the process of evaluating a user's personality and behavioral characteristics based on analyzed conversational data.

[0528] "Compatibility assessment" involves comparing multiple users and expressing the degree of similarity in their personalities, hobbies, and other characteristics in numerical or list format.

[0529] "Presenting candidates" refers to displaying highly suitable user combinations in the form of a list or similar.

[0530] A "generative model" is a computational model based on AI technology used for data analysis and understanding user emotions.

[0531] "Training methods" refer to learning programs and training methods designed to promote user growth.

[0532] "Progress evaluation" involves checking the user's progress in the training program and providing feedback based on their level of achievement.

[0533] This invention is a system that deeply understands the user's personality and enables matching with a suitable partner. First, the user enters their personal information using a terminal. This terminal consists of common devices such as PCs and smartphones and provides an interface with the user.

[0534] The device sends the collected user personal information to a server. The server processes this data using an advanced generative AI model. This AI model plays a central role in interacting with the user, enabling natural conversation. Specifically, natural language processing libraries and AI frameworks are often used. This allows for real-time evaluation of emotions and speech patterns from the user's dialogue.

[0535] Users can freely converse with an artificial intelligence agent through their device. This can be done using either voice or text input, and the information obtained from the conversation is analyzed by a server. The server diagnoses the user's personality traits and evaluates their compatibility with other users based on the analysis results. This allows the server to display the most suitable candidates in a matching list, based on individual personality traits, hobbies, and other factors.

[0536] Furthermore, the device provides a personalized training program based on user feedback. This program is designed to promote user growth, allowing users to monitor their progress in real time and receive appropriate guidance.

[0537] As a concrete example, if a user registers information such as "I enjoy cooking and want to learn new recipes," not only will users with similar interests be displayed as candidates, but cooking-related training programs will also be suggested. An example of a prompt for the AI ​​model that generates dialogue in this system could be, "Based on User A's diagnostic results, please suggest the most suitable training program."

[0538] As described above, this invention can provide users with a means to help them efficiently find partners and grow professionally.

[0539] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0540] Step 1:

[0541] The terminal accepts personal information input from the user. The user enters information such as their background, hobbies, preferences, and preferred type of person through the terminal's interface. This input data undergoes basic preprocessing, including format checks and duplicate data removal, before being sent to the server.

[0542] Step 2:

[0543] The server stores user information received from the terminal in a database. During storage, database normalization and error detection are performed to improve data consistency and accuracy. This data is then used as the basis for subsequent analysis.

[0544] Step 3:

[0545] The terminal provides the user with an interactive session with an information processing device. The user converses with the agent through voice input or text input. The input data of the conversation is sent to the server in real time.

[0546] Step 4:

[0547] The server analyzes the received dialogue data using a generative AI model. Specifically, it breaks down the input text and speech using natural language processing techniques to recognize emotions and context. This analysis extracts the user's speech patterns and emotional tone.

[0548] Step 5:

[0549] The server diagnoses the user's personality traits based on the analysis of dialogue data. Using the analysis results as input, the server outputs numerical evaluations or comments on the user's listening skills, empathy, and other abilities. These diagnostic results are stored in a database.

[0550] Step 6:

[0551] The server evaluates the compatibility with other users based on the diagnostic results. Using personality traits and other user information as input, it assesses similarities and differences between the two and outputs a compatibility score. Based on these results, a candidate list is generated.

[0552] Step 7:

[0553] The terminal receives evaluation results from the server and presents the user with a list of candidates. The list is ranked based on similarities in preferences and personality traits and displayed on the terminal's screen.

[0554] Step 8:

[0555] The terminal provides a means of training for the user. A customized program is generated based on diagnostic results from the server, and the user can progress through this program via the terminal. Progress is constantly updated and feedback is provided to the user.

[0556] (Application Example 1)

[0557] 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."

[0558] Currently, users often lack access to appropriate information and personalized guidance and advice, which are crucial for their ability to make informed purchasing decisions and personal growth through online information. Furthermore, insufficient personalized product recommendations based on user attributes and preferences lead to a lack of valuable insights in purchasing decisions. There is a need for new technologies to address these challenges and improve the user experience.

[0559] 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.

[0560] In this invention, the server includes means for collecting and recording user attribute information, means for communicating between the user and an intelligent program and analyzing the content of that communication, and means for recommending items based on the user's preferences and guiding them to purchase. This makes it possible to optimize product recommendations and improve the purchasing experience based on each user's characteristics and interests.

[0561] A "user" is an individual or legal entity that utilizes this system and is the entity that receives services based on attribute information and preferences.

[0562] "Attribute information" refers to all information about an individual, such as a user's background, hobbies, and preferences, and is used as basic data for analysis and decision-making within the system.

[0563] An "intelligent program" is a program that uses artificial intelligence technology to communicate with users, analyze conversation content, evaluate user characteristics, and recommend items.

[0564] "Communication content" is a general term for information exchanged between the user and the intelligent program, and includes dialogue data expressed in voice and text.

[0565] "Analysis" is the process of analyzing communication content and evaluating and diagnosing patterns in user statements and emotions.

[0566] "Characteristics" refer to a collection of various individual characteristics of a user, such as their personality, interests, and purchasing tendencies, and are used by the system as the basis for diagnosis and recommendations.

[0567] "Preferences" refer to the things and areas of interest that users enjoy, and are a factor that determines the direction in which products and services are provided.

[0568] "Items" refer to specific products or services recommended to users, and are the objects that provide a purchasing experience within the system.

[0569] "Purchase" refers to the series of actions a user takes, from selecting an item through a system to completing the purchase process.

[0570] To implement this invention, a user-operated terminal and a server connected to it are required. The terminal can be a smartphone, tablet, smart glasses, or head-mounted display. Through these devices, the user can input attribute information and interact with an intelligent program. The server is responsible for processing the attribute information and communication content transmitted by the user.

[0571] The server is located in a cloud environment and uses natural language processing technologies such as Dialogflow and IBM Watson to analyze user conversations and evaluate individual personality traits and preferences. The analysis data is stored in a database management system (e.g., MySQL). Based on these analysis results, the server uses a generative AI model to recommend items suitable for the user. Machine learning frameworks such as TensorFlow are used for item recommendation.

[0572] For example, when a user prompts the device with a statement like, "I want a new camera," the server analyzes the conversation and presents the most suitable camera recommendations and related information for that user. It also enhances the user's purchasing experience by providing user reviews and guiding them through the purchase process. Users can constantly receive new product information, which helps them make informed purchasing decisions.

[0573] Examples of prompts include "I'm looking for new fashion items," "Can you recommend some movies for the weekend?", and "I'd like to know about leisure events that my family can enjoy." In this way, information tailored to each user's individual needs is provided.

[0574] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0575] Step 1:

[0576] The user uses a terminal to input attribute information (e.g., hobbies, preferences, products of interest) and sends it to the server. The input here primarily consists of user prompts, and the output is stored on the server as user profile data. This information is stored in a database management system (e.g., MySQL) on the server and used as foundational data for subsequent analysis.

[0577] Step 2:

[0578] The user interacts with an intelligent program via a terminal and sends the content of the interaction to a server. The input at this time is text or voice data from the user. The server uses Dialogflow or IBM Watson to perform natural language processing and analyze the content of the interaction. The output is the intention, emotion, and areas of interest extracted from the user's statements, which are further used for evaluation and diagnosis.

[0579] Step 3:

[0580] The server evaluates the user's personality traits and preferences based on the analyzed dialogue data. This evaluation process is performed using a generative AI model, which quantifies or categorizes the data. The input is the utterance data obtained in the previous step, and the output is a detailed analysis of the user's attributes. This result provides the data necessary not only for updating the user profile but also for running the recommendation algorithm.

[0581] Step 4:

[0582] The server recommends items based on user attribute information and the results of dialogue data analysis. Machine learning frameworks such as TensorFlow support this process. The input is the user analysis results and a product database, and the output is a list of products best suited to the user's preferences. These recommendations are sent to the user's terminal and presented to the user visually or audibly.

[0583] Step 5:

[0584] The user reviews the recommended products displayed on the terminal and inquires for more detailed information about the products as needed. If they decide to purchase, they send a prompt to the server via the terminal. The server processes this purchase request and provides the user with payment instructions. The input is the user's selection and purchase intention, and the output is confirmation information that the purchase has been completed.

[0585] 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.

[0586] This invention is implemented as a system incorporating an emotion engine that recognizes the user's emotions. By accurately evaluating the user's emotional state using the emotion engine, it becomes possible to perform more sophisticated personality trait diagnosis, personalized matching, and self-improvement.

[0587] First, the device provides an interface for the user to input personal information. The user enters basic information such as their background, hobbies, preferences, favorite foods, and preferred type of person, and the device sends this information to the server. The server stores this information in a database and uses it for future interactions and analysis.

[0588] Next, the device displays a screen to the user to begin a dialogue session with the artificial intelligence agent. Once the user starts the session, the device engages in real-time dialogue with the artificial intelligence agent through voice and video. Here, the emotion engine is utilized to analyze the user's emotions in real time from their voice tone, facial expressions, body movements, etc., and transmit this information to the server.

[0589] The server comprehensively analyzes the received dialogue content and emotional data. For example, a user who displays a cheerful expression and frequently uses positive language is judged to be highly sociable. This allows for a detailed diagnosis of the user's personality traits. The diagnostic results are quantified and stored in the server's database.

[0590] The server then compares the results with those of other users and performs a suitability assessment that includes emotional data. This allows it to select more emotionally suitable partner candidates and present them to the user through the terminal. For example, if the analysis of facial expressions and tone indicates that the user prefers to behave cheerfully in conversations, partners with such characteristics will be recommended preferentially.

[0591] In addition, the device presents the user with a self-improvement program based on emotional data. This program is customized based on the user's emotional state and personality traits and includes, for example, tasks and sessions that promote more positive thinking. As the user progresses through the program, the server tracks their progress and provides periodic feedback.

[0592] This system allows users to achieve appropriate matching that reflects their emotional state while effectively promoting personal growth. By concretely implementing the invention, it becomes possible to build relationships that maximize the user's inner characteristics.

[0593] The following describes the processing flow.

[0594] Step 1:

[0595] The terminal displays an interface for the user to enter personal information. The user enters information such as their background, hobbies, preferences, favorite foods, and preferred type of person into a form on the screen. The terminal sends this information to the server, which stores it in a database.

[0596] Step 2:

[0597] The device displays a screen prompting the user to begin a dialogue session with an artificial intelligence agent. Once the user starts the dialogue session, the device uses its microphone and camera to capture audio and video, and prepares to send them to the server.

[0598] Step 3:

[0599] The emotion engine processes the user's video and audio, recognizing emotions from facial expressions and tone of voice. For example, if the user's face is smiling and their voice sounds cheerful, the emotion engine determines that the user is happy and adds this data to the analysis results.

[0600] Step 4:

[0601] The server integrates and analyzes the received dialogue content and emotion data. The server uses natural language processing technology to analyze the user's statements and combines them with the recognized emotion data to diagnose the user's personality traits.

[0602] Step 5:

[0603] The server compares the personality trait assessment results of other users and evaluates the degree of compatibility. This evaluation also includes emotional fit, with users having similar emotional patterns being judged to have a higher degree of compatibility. The server selects the most suitable partner candidate and presents them to the user via the device.

[0604] Step 6:

[0605] The device presents a self-improvement program optimized for the user. This program is customized based on the user's personality assessment and emotional data, and may include tasks designed to improve emotional control and communication skills, for example.

[0606] Step 7:

[0607] The server tracks the user's progress in their professional development program and performs periodic evaluations. It sends feedback to the user's device based on their progress and provides specific advice to help them move on to the next step.

[0608] This processing flow allows users to experience personalized matching that takes emotions into account, as well as personal growth.

[0609] (Example 2)

[0610] 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."

[0611] In modern society, there is a growing demand for communication and growth support environments that take into account the individuality and emotional state of users. However, technologies for accurately understanding individual personality traits and emotional states, and for appropriately forming and maintaining relationships with others, are not yet sufficiently developed. To address this challenge, there is a need for effective systems that leverage users' inner characteristics for matching and promote self-growth.

[0612] 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.

[0613] In this invention, the server includes means for collecting and storing user attribute information, means for conducting a dialogue between the user and surrogate software using artificial intelligence and analyzing the content of that dialogue, and means for diagnosing the user's personality traits based on the analyzed dialogue data and emotional data. This makes it possible to select an appropriate partner based on the user's personality and emotional state and to provide an individualized growth program.

[0614] A "user" is an individual who uses the system to input information and receives partner selection and growth support through interaction and functions.

[0615] "Attribute information" refers to basic information used to identify and characterize an individual, such as a user's background, hobbies, preferences, favorite foods, and preferred type of person.

[0616] "Agent software using artificial intelligence" refers to an interactive computer program used to perform emotional analysis and personality assessment through user interaction.

[0617] "Emotional data" refers to data that indicates the user's emotional state, analyzed from factors such as the user's voice tone, facial expressions, and posture.

[0618] "Personality traits" are the result of quantifying or classifying a user's individuality, and are characteristics that define a user's behavior and way of thinking.

[0619] "Fit" is a numerical value or evaluation that indicates the degree of commonality or compatibility between a user and other users.

[0620] "Interaction candidates" are other users suggested to the user based on their suitability, and are individuals with whom communication and relationship building can be expected.

[0621] "Personal growth" refers to changes aimed at personal development and skill improvement that users wish to achieve.

[0622] A "training program" is a series of sessions and assignments designed to improve skills and self-improvement, taking into account the user's personality traits and emotional data.

[0623] This invention is a system aimed at selecting partners and supporting self-growth, taking into account the user's personality and emotional state. The specific forms for implementing the invention are described below.

[0624] The system primarily consists of a terminal, a server, and proxy software using artificial intelligence. The terminal provides an interface for users to input personal attribute information. Users enter information such as their background and hobbies into the terminal, and this information is sent to the server. The server stores the received information in a database and makes it available for subsequent processing.

[0625] The artificial intelligence-powered proxy software analyzes emotional data in real time through interaction with the user. The device enables communication with the user through voice and video, sensing and analyzing the user's voice tone, facial expressions, posture, etc. The analyzed emotional data is sent to a server and used for personality trait diagnosis.

[0626] The server comprehensively analyzes emotional and conversational data to quantify the user's personality traits. For example, a user who frequently uses positive language is diagnosed as highly sociable. This diagnostic information is stored in a database and forms the basis for evaluating compatibility with other users.

[0627] Based on suitability assessments, the server selects potential interactions with other users and presents them to the user via the terminal. For example, sentiment analysis suggests that users who prefer cheerful behavior during conversations will be recommended interaction candidates with similar characteristics.

[0628] The device also presents users with individually tailored training programs. These programs may include tasks and sessions designed to promote positive thinking. The progress of the training program is managed by a server, and users receive regular feedback on their progress and areas for improvement.

[0629] For example, a prompt such as, "List matching candidates with personality traits suitable for highly sociable users, and propose a customized self-improvement program based on the sentiment analysis results," can be used.

[0630] Through the method described above, this invention effectively supports the selection of a partner and personal growth that takes into account the user's individuality and emotional state.

[0631] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0632] Step 1:

[0633] The terminal provides an interface for inputting user attribute information. Users input information such as their background, hobbies, and preferences, and the terminal sends this information to the server.

[0634] Input: Attribute information entered by the user.

[0635] Data processing: The terminal formats the information as structured data.

[0636] Output: Structured user information is sent to the server.

[0637] Step 2:

[0638] The server stores the received user information in a database. This information is used for subsequent interactions and analysis.

[0639] Input: Structured user information sent from the terminal.

[0640] Data processing: The server stores data in the database and creates indexes.

[0641] Output: The server records the status of information saving completion.

[0642] Step 3:

[0643] The device displays a screen to initiate a dialogue session with artificial intelligence-powered proxy software. Once the user starts the session, the device engages in dialogue through voice and video.

[0644] Input: User session start command.

[0645] Data processing: Initiating and capturing real-time streaming.

[0646] Output: Sends dialogue data (audio and video) to the server.

[0647] Step 4:

[0648] The device analyzes the user's voice tone and facial expressions in real time to analyze their emotions. The analyzed data is sent to a server.

[0649] Input: Real-time audio and video data.

[0650] Data processing: Emotional parameters are extracted through analysis using an emotion engine.

[0651] Output: The analyzed emotion data is sent to the server.

[0652] Step 5:

[0653] The server comprehensively analyzes dialogue data and emotional data to diagnose the user's personality traits.

[0654] Input: Dialogue data and sentiment data.

[0655] Data processing: Feature extraction and diagnosis based on language analysis and sentiment evaluation.

[0656] Output: The diagnostic results are saved to the database.

[0657] Step 6:

[0658] The server evaluates compatibility with other users based on the diagnostic results and selects potential interaction partners.

[0659] Input: Diagnostic result.

[0660] Data processing: Calculation of goodness of fit and candidate selection using matching algorithms.

[0661] Output: A list of highly compatible AC candidates is sent to the terminal.

[0662] Step 7:

[0663] The device presents the user with suggested interaction options. The user can browse the displayed list and select an interaction.

[0664] Input: List of potential contacts.

[0665] Data processing: Visualize candidates in the user interface.

[0666] Output: Candidate information presented to the user.

[0667] Step 8:

[0668] The device presents the user with a training program aimed at self-improvement. The program is customized based on the user's personality traits and emotional data.

[0669] Input: Personality traits and emotional data.

[0670] Data processing: Program selection and task customization.

[0671] Output: The user-facing program content is displayed.

[0672] Step 9:

[0673] The server manages the user's training program progress and provides periodic feedback.

[0674] Input: Program progress data.

[0675] Data processing: Progress analysis and feedback generation.

[0676] Output: Progress feedback is sent to the user.

[0677] (Application Example 2)

[0678] 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."

[0679] In modern consumer behavior, providing product information and service suggestions that respond to user emotions is a crucial challenge. In particular, when users experience a company's products and services in a virtual environment, traditional, uniform information provision often fails to fully capture their interest and purchasing intent. Furthermore, there are few systems that can customize the shopping experience based on the user's emotional state and suggest appropriate products, thus creating a need for new technologies to improve user satisfaction.

[0680] 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.

[0681] In this invention, the server includes means for collecting and storing the user's personal information; means for conducting a dialogue between the user and an artificial intelligence agent and analyzing the content of the dialogue; means for diagnosing the user's personality traits based on the analyzed dialogue data; means for evaluating the degree of compatibility with other users based on the diagnosis results and presenting partner candidates; means for providing training programs to promote the user's growth; means for evaluating the user's progress and providing feedback; and means for analyzing the user's emotions in real time and suggesting product information corresponding to those emotions. This enables customized purchase suggestions that are tailored to the user's emotions.

[0682] "Personal information" refers to information that identifies and characterizes individual users, such as their history, hobbies, preferences, favorite foods, and preferred types of people.

[0683] An "artificial intelligence agent" is a program that analyzes information through interaction with the user and evaluates the user's personality traits and emotions.

[0684] "Analysis of dialogue content" involves analyzing information obtained during the communication process between the user and the artificial intelligence agent to understand the user's personality traits and emotional state.

[0685] "Personality trait diagnosis" is the process of evaluating the internal personality characteristics of a user based on their conversational data and emotional data.

[0686] "Compatibility assessment" involves measuring the degree of emotional and personality match between users based on the diagnostic results, and selecting the most suitable partner candidate.

[0687] A "training program" consists of assignments and sessions designed to support user growth, and is customized to the individual user's needs.

[0688] "Progress evaluation" involves monitoring the progress of a training program and analyzing how much users are growing.

[0689] "Feedback" refers to information that provides users with progress-based evaluations and advice, thereby promoting more effective self-improvement.

[0690] "Real-time emotional analysis" involves instantly analyzing a user's emotional state at a given moment based on their voice tone, facial expressions, body movements, and other factors.

[0691] "Product information suggestion" refers to presenting appropriate product and service information based on the user's analyzed emotions, thereby encouraging purchasing behavior.

[0692] To implement this invention, a system is required that includes an application installed on a user's terminal and processing performed by a central server. Specifically, this system consists of a terminal that provides an interface for collecting the user's personal information and a server that analyzes and stores that information.

[0693] The server uses software such as TensorFlow and OpenCV to analyze user emotional data, including voice tone, facial expressions, and body movements, in real time. This allows for the evaluation of the user's personality traits and enables emotion-based purchasing suggestions. This system can present the most suitable products according to the user's emotions and can utilize generative AI models to improve the user experience.

[0694] In terms of specific operations, when a user accesses a virtual store using a device, emotional data is collected through smart glasses or a head-mounted display. The server analyzes this data, generates appropriate product information, and presents it to the user. It also proposes training programs to support the user's growth, tracks their progress, and provides feedback. This allows users to enjoy a personalized shopping experience tailored to their individual emotions.

[0695] For example, if a user experiences an emotion such as "fun" while walking around a store, the system can suggest products that correspond to that emotion, such as new products or items with unique designs.

[0696] An example of a prompt would be: "Write a prompt to analyze the facial expressions and tone of voice a user displays during their shopping experience and suggest products based on their emotional state." This serves as a guide for an AI model to generate appropriate product suggestions based on emotions.

[0697] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0698] Step 1:

[0699] The terminal displays an interface for entering the user's personal information. When the user enters their background, hobbies, and other personal information, this data is collected and sent to the server. This data is stored on the server for use in future interactions and analysis.

[0700] Step 2:

[0701] The terminal displays a screen for a dialogue session with an artificial intelligence agent, and the user initiates the session. Once the user gives the start command, the terminal performs a real-time dialogue through voice and video. It uses the user's voice and video data as input and sends it to the server as material for interpretation.

[0702] Step 3:

[0703] The server analyzes the received audio and video data and uses tools such as TensorFlow and OpenCV to evaluate the user's voice tone, facial expressions, and body movements in real time. In this step, data processing is performed and analysis results are output to obtain the user's emotional state.

[0704] Step 4:

[0705] The server integrates the analysis results of the conversation content with emotional data to diagnose the user's personality traits. The diagnosis quantifies the personality based on the entered personal information and emotional data obtained in real time, and outputs an evaluation of the user's characteristics.

[0706] Step 5:

[0707] The server compares the user's diagnostic data with that of other users and performs a suitability assessment. In this step, partner candidates are selected based on the user's personality traits and emotional data, and output is generated to present the user with the most suitable candidate.

[0708] Step 6:

[0709] The server creates individually customized training programs based on the user's emotional data and delivers them to the user via the terminal. This suggests tasks for self-improvement tailored to the user's emotions and personality. Furthermore, the server continuously tracks the program's progress.

[0710] Step 7:

[0711] The server uses a generative AI model to generate product information tailored to the user's emotions and presents it to the user through the terminal. In this step, prompts generated based on emotion data are used to further personalize the content. This allows the user to receive a shopping experience optimized for their own emotional state.

[0712] 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.

[0713] 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 those described above. 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 shown 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.

[0714] 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.

[0715] [Fourth Embodiment]

[0716] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0717] 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.

[0718] 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).

[0719] 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.

[0720] 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.

[0721] 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).

[0722] 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.

[0723] 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.

[0724] 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.

[0725] 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.

[0726] 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.

[0727] 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.

[0728] 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".

[0729] This invention is implemented as a system that enables efficient user matching and supports the individual growth of users.

[0730] First, the device collects personal information from the user. The user enters their background, hobbies, preferences, and preferred type of person into an interface provided through the device. This information is sent to the server and stored as basic data used for future interactions and analysis.

[0731] Next, the terminal provides the user with a dialogue session with an artificial intelligence agent. Through this session, the user can freely converse with the AI ​​agent using voice and text. The server analyzes the dialogue in real time and evaluates the user's speech patterns and emotional developments. For example, if the user frequently uses positive expressions, they will be judged to be highly sociable.

[0732] Based on the analysis results, the server diagnoses the user's personality traits. Aspects such as the user's listening skills, conversational abilities, and tolerance are evaluated as numerical values ​​and comments. These diagnostic results are stored in a database and used when matching users with other users.

[0733] The server then uses the diagnostic results to evaluate how well a user is compatible with other registered users. Highly compatible user pairs are compiled into a candidate list and presented to the user via their device. For example, if it is confirmed that users not only share common hobbies but also have similar social skills and communication styles, they will be ranked higher in the matching list.

[0734] In addition, the device provides users with training programs for self-improvement. These programs are customized based on the user's assessment results and include content designed to promote user growth. Throughout the program, users receive progress feedback via the device. This feedback includes assessments of their learning progress and advice for the next steps.

[0735] This allows users to experience personal growth while having the opportunity to meet a suitable partner. The concrete implementation of this invention will enable matching that suits the user's personality, and is expected to foster long-term relationships.

[0736] The following describes the processing flow.

[0737] Step 1:

[0738] The terminal displays an interface for the user to enter personal information. The user enters information such as their background, hobbies, preferences, favorite foods, and preferred type of person. The terminal sends the entered information to the server, which stores it in a database.

[0739] Step 2:

[0740] The device displays a screen prompting the user to begin a dialogue session with an artificial intelligence agent. Once the user starts the dialogue session, the device provides a voice or text conversation interface, enabling the user and the artificial intelligence agent to converse in real time.

[0741] Step 3:

[0742] The server collects the content of conversations between the user and the artificial intelligence agent and analyzes it in real time using natural language processing algorithms. In this process, it evaluates the user's statements to determine their emotions, interests, and response style, and diagnoses their personality traits.

[0743] Step 4:

[0744] The server uses the analysis results to perform a detailed diagnosis of the user's personality traits. The diagnosis results are quantified as indicators of the user's listening ability, sociability, etc., and stored in a database. This information is used in subsequent matching processes.

[0745] Step 5:

[0746] The server runs an algorithm that compares the diagnostic results of different users and evaluates the degree of relevance. It identifies users with high relevance and lists them as potential partners. The terminal then presents this list of candidates to the user.

[0747] Step 6:

[0748] The device presents the user with a selection of self-improvement programs. These programs are optimized for each user based on their diagnostic results. Once the user selects a program, the server tracks their progress and generates periodic feedback.

[0749] Step 7:

[0750] The device provides users with feedback on the training program. This feedback includes the user's progress, areas for improvement, and suggestions for the next steps. This allows users to feel a sense of personal growth while aiming for a better match.

[0751] (Example 1)

[0752] 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".

[0753] The goal is to address the challenge of insufficient efficient systems for users to accurately understand their own personality traits, find suitable partners, and promote individual growth.

[0754] 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.

[0755] In this invention, the server includes means for collecting and storing the user's personal information; means for conducting a dialogue between the user and the information processing device and analyzing the content of that dialogue; means for diagnosing the user's personality traits based on the analyzed dialogue data; means for evaluating the degree of compatibility with other users based on the diagnosis results and presenting candidates; means for using a generative model in the analysis of the dialogue; means for providing training means to promote the user's growth; and means for evaluating the user's progress and presenting the evaluation results. This enables the user to understand their own characteristics, find the optimal partner, and grow through individually designed training programs.

[0756] "User personal information" refers to individual information provided by the user, such as name, contact information, hobbies, and preferences.

[0757] An "information processing device" is an electronic device that processes and analyzes data in order to interact with the user.

[0758] "Dialogue content analysis" is the process of extracting and evaluating information from a user's statements during a conversation between a user and an information processing device.

[0759] "Personality trait diagnosis" is the process of evaluating a user's personality and behavioral characteristics based on analyzed conversational data.

[0760] "Compatibility assessment" involves comparing multiple users and expressing the degree of similarity in their personalities, hobbies, and other characteristics in numerical or list format.

[0761] "Presenting candidates" refers to displaying highly suitable user combinations in the form of a list or similar.

[0762] A "generative model" is a computational model based on AI technology used for data analysis and understanding user emotions.

[0763] "Training methods" refer to learning programs and training methods designed to promote user growth.

[0764] "Progress evaluation" involves checking the user's progress in the training program and providing feedback based on their level of achievement.

[0765] This invention is a system that deeply understands the user's personality and enables matching with a suitable partner. First, the user enters their personal information using a terminal. This terminal consists of common devices such as PCs and smartphones and provides an interface with the user.

[0766] The device sends the collected user personal information to a server. The server processes this data using an advanced generative AI model. This AI model plays a central role in interacting with the user, enabling natural conversation. Specifically, natural language processing libraries and AI frameworks are often used. This allows for real-time evaluation of emotions and speech patterns from the user's dialogue.

[0767] Users can freely converse with an artificial intelligence agent through their device. This can be done using either voice or text input, and the information obtained from the conversation is analyzed by a server. The server diagnoses the user's personality traits and evaluates their compatibility with other users based on the analysis results. This allows the server to display the most suitable candidates in a matching list, based on individual personality traits, hobbies, and other factors.

[0768] Furthermore, the device provides a personalized training program based on user feedback. This program is designed to promote user growth, allowing users to monitor their progress in real time and receive appropriate guidance.

[0769] As a concrete example, if a user registers information such as "I enjoy cooking and want to learn new recipes," not only will users with similar interests be displayed as candidates, but cooking-related training programs will also be suggested. An example of a prompt for the AI ​​model that generates dialogue in this system could be, "Based on User A's diagnostic results, please suggest the most suitable training program."

[0770] As described above, this invention can provide users with a means to help them efficiently find partners and grow professionally.

[0771] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0772] Step 1:

[0773] The terminal accepts personal information input from the user. The user enters information such as their background, hobbies, preferences, and preferred type of person through the terminal's interface. This input data undergoes basic preprocessing, including format checks and duplicate data removal, before being sent to the server.

[0774] Step 2:

[0775] The server stores user information received from the terminal in a database. During storage, database normalization and error detection are performed to improve data consistency and accuracy. This data is then used as the basis for subsequent analysis.

[0776] Step 3:

[0777] The terminal provides the user with an interactive session with an information processing device. The user converses with the agent through voice input or text input. The input data of the conversation is sent to the server in real time.

[0778] Step 4:

[0779] The server analyzes the received dialogue data using a generative AI model. Specifically, it breaks down the input text and speech using natural language processing techniques to recognize emotions and context. This analysis extracts the user's speech patterns and emotional tone.

[0780] Step 5:

[0781] The server diagnoses the user's personality traits based on the analysis of dialogue data. Using the analysis results as input, the server outputs numerical evaluations or comments on the user's listening skills, empathy, and other abilities. These diagnostic results are stored in a database.

[0782] Step 6:

[0783] The server evaluates the compatibility with other users based on the diagnostic results. Using personality traits and other user information as input, it assesses similarities and differences between the two and outputs a compatibility score. Based on these results, a candidate list is generated.

[0784] Step 7:

[0785] The terminal receives evaluation results from the server and presents the user with a list of candidates. The list is ranked based on similarities in preferences and personality traits and displayed on the terminal's screen.

[0786] Step 8:

[0787] The terminal provides a means of training for the user. A customized program is generated based on diagnostic results from the server, and the user can progress through this program via the terminal. Progress is constantly updated and feedback is provided to the user.

[0788] (Application Example 1)

[0789] 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".

[0790] Currently, users often lack access to appropriate information and personalized guidance and advice, which are crucial for their ability to make informed purchasing decisions and personal growth through online information. Furthermore, insufficient personalized product recommendations based on user attributes and preferences lead to a lack of valuable insights in purchasing decisions. There is a need for new technologies to address these challenges and improve the user experience.

[0791] 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.

[0792] In this invention, the server includes means for collecting and recording user attribute information, means for communicating between the user and an intelligent program and analyzing the content of that communication, and means for recommending items based on the user's preferences and guiding them to purchase. This makes it possible to optimize product recommendations and improve the purchasing experience based on each user's characteristics and interests.

[0793] A "user" is an individual or legal entity that utilizes this system and is the entity that receives services based on attribute information and preferences.

[0794] "Attribute information" refers to all information about an individual, such as a user's background, hobbies, and preferences, and is used as basic data for analysis and decision-making within the system.

[0795] An "intelligent program" is a program that uses artificial intelligence technology to communicate with users, analyze conversation content, evaluate user characteristics, and recommend items.

[0796] "Communication content" is a general term for information exchanged between the user and the intelligent program, and includes dialogue data expressed in voice and text.

[0797] "Analysis" is the process of analyzing communication content and evaluating and diagnosing patterns in user statements and emotions.

[0798] "Characteristics" refer to a collection of various individual characteristics of a user, such as their personality, interests, and purchasing tendencies, and are used by the system as the basis for diagnosis and recommendations.

[0799] "Preferences" refer to the things and areas of interest that users enjoy, and are a factor that determines the direction in which products and services are provided.

[0800] "Items" refer to specific products or services recommended to users, and are the objects that provide a purchasing experience within the system.

[0801] "Purchase" refers to the series of actions a user takes, from selecting an item through a system to completing the purchase process.

[0802] To implement this invention, a user-operated terminal and a server connected to it are required. The terminal can be a smartphone, tablet, smart glasses, or head-mounted display. Through these devices, the user can input attribute information and interact with an intelligent program. The server is responsible for processing the attribute information and communication content transmitted by the user.

[0803] The server is located in a cloud environment and uses natural language processing technologies such as Dialogflow and IBM Watson to analyze user conversations and evaluate individual personality traits and preferences. The analysis data is stored in a database management system (e.g., MySQL). Based on these analysis results, the server uses a generative AI model to recommend items suitable for the user. Machine learning frameworks such as TensorFlow are used for item recommendation.

[0804] For example, when a user prompts the device with a statement like, "I want a new camera," the server analyzes the conversation and presents the most suitable camera recommendations and related information for that user. It also enhances the user's purchasing experience by providing user reviews and guiding them through the purchase process. Users can constantly receive new product information, which helps them make informed purchasing decisions.

[0805] Examples of prompts include "I'm looking for new fashion items," "Can you recommend some movies for the weekend?", and "I'd like to know about leisure events that my family can enjoy." In this way, information tailored to each user's individual needs is provided.

[0806] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0807] Step 1:

[0808] The user uses a terminal to input attribute information (e.g., hobbies, preferences, products of interest) and sends it to the server. The input here primarily consists of user prompts, and the output is stored on the server as user profile data. This information is stored in a database management system (e.g., MySQL) on the server and used as foundational data for subsequent analysis.

[0809] Step 2:

[0810] The user interacts with an intelligent program via a terminal and sends the content of the interaction to a server. The input at this time is text or voice data from the user. The server uses Dialogflow or IBM Watson to perform natural language processing and analyze the content of the interaction. The output is the intention, emotion, and areas of interest extracted from the user's statements, which are further used for evaluation and diagnosis.

[0811] Step 3:

[0812] The server evaluates the user's personality traits and preferences based on the analyzed dialogue data. This evaluation process is performed using a generative AI model, which quantifies or categorizes the data. The input is the utterance data obtained in the previous step, and the output is a detailed analysis of the user's attributes. This result provides the data necessary not only for updating the user profile but also for running the recommendation algorithm.

[0813] Step 4:

[0814] The server recommends items based on user attribute information and the results of dialogue data analysis. Machine learning frameworks such as TensorFlow support this process. The input is the user analysis results and a product database, and the output is a list of products best suited to the user's preferences. These recommendations are sent to the user's terminal and presented to the user visually or audibly.

[0815] Step 5:

[0816] The user reviews the recommended products displayed on the terminal and inquires for more detailed information about the products as needed. If they decide to purchase, they send a prompt to the server via the terminal. The server processes this purchase request and provides the user with payment instructions. The input is the user's selection and purchase intention, and the output is confirmation information that the purchase has been completed.

[0817] 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.

[0818] This invention is implemented as a system incorporating an emotion engine that recognizes the user's emotions. By accurately evaluating the user's emotional state using the emotion engine, it becomes possible to perform more sophisticated personality trait diagnosis, personalized matching, and self-improvement.

[0819] First, the device provides an interface for the user to input personal information. The user enters basic information such as their background, hobbies, preferences, favorite foods, and preferred type of person, and the device sends this information to the server. The server stores this information in a database and uses it for future interactions and analysis.

[0820] Next, the device displays a screen to the user to begin a dialogue session with the artificial intelligence agent. Once the user starts the session, the device engages in real-time dialogue with the artificial intelligence agent through voice and video. Here, the emotion engine is utilized to analyze the user's emotions in real time from their voice tone, facial expressions, body movements, etc., and transmit this information to the server.

[0821] The server comprehensively analyzes the received dialogue content and emotional data. For example, a user who displays a cheerful expression and frequently uses positive language is judged to be highly sociable. This allows for a detailed diagnosis of the user's personality traits. The diagnostic results are quantified and stored in the server's database.

[0822] The server then compares the results with those of other users and performs a suitability assessment that includes emotional data. This allows it to select more emotionally suitable partner candidates and present them to the user through the terminal. For example, if the analysis of facial expressions and tone indicates that the user prefers to behave cheerfully in conversations, partners with such characteristics will be recommended preferentially.

[0823] In addition, the device presents the user with a self-improvement program based on emotional data. This program is customized based on the user's emotional state and personality traits and includes, for example, tasks and sessions that promote more positive thinking. As the user progresses through the program, the server tracks their progress and provides periodic feedback.

[0824] This system allows users to achieve appropriate matching that reflects their emotional state while effectively promoting personal growth. By concretely implementing the invention, it becomes possible to build relationships that maximize the user's inner characteristics.

[0825] The following describes the processing flow.

[0826] Step 1:

[0827] The terminal displays an interface for the user to enter personal information. The user enters information such as their background, hobbies, preferences, favorite foods, and preferred type of person into a form on the screen. The terminal sends this information to the server, which stores it in a database.

[0828] Step 2:

[0829] The device displays a screen prompting the user to begin a dialogue session with an artificial intelligence agent. Once the user starts the dialogue session, the device uses its microphone and camera to capture audio and video, and prepares to send them to the server.

[0830] Step 3:

[0831] The emotion engine processes the user's video and audio, recognizing emotions from facial expressions and tone of voice. For example, if the user's face is smiling and their voice sounds cheerful, the emotion engine determines that the user is happy and adds this data to the analysis results.

[0832] Step 4:

[0833] The server integrates and analyzes the received dialogue content and emotion data. The server uses natural language processing technology to analyze the user's statements and combines them with the recognized emotion data to diagnose the user's personality traits.

[0834] Step 5:

[0835] The server compares the personality trait assessment results of other users and evaluates the degree of compatibility. This evaluation also includes emotional fit, with users having similar emotional patterns being judged to have a higher degree of compatibility. The server selects the most suitable partner candidate and presents them to the user via the device.

[0836] Step 6:

[0837] The device presents a self-improvement program optimized for the user. This program is customized based on the user's personality assessment and emotional data, and may include tasks designed to improve emotional control and communication skills, for example.

[0838] Step 7:

[0839] The server tracks the user's progress in their professional development program and performs periodic evaluations. It sends feedback to the user's device based on their progress and provides specific advice to help them move on to the next step.

[0840] This processing flow allows users to experience personalized matching that takes emotions into account, as well as personal growth.

[0841] (Example 2)

[0842] 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".

[0843] In modern society, there is a growing demand for communication and growth support environments that take into account the individuality and emotional state of users. However, technologies for accurately understanding individual personality traits and emotional states, and for appropriately forming and maintaining relationships with others, are not yet sufficiently developed. To address this challenge, there is a need for effective systems that leverage users' inner characteristics for matching and promote self-growth.

[0844] 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.

[0845] In this invention, the server includes means for collecting and storing user attribute information, means for conducting a dialogue between the user and surrogate software using artificial intelligence and analyzing the content of that dialogue, and means for diagnosing the user's personality traits based on the analyzed dialogue data and emotional data. This makes it possible to select an appropriate partner based on the user's personality and emotional state and to provide an individualized growth program.

[0846] A "user" is an individual who uses the system to input information and receives partner selection and growth support through interaction and functions.

[0847] "Attribute information" refers to basic information used to identify and characterize an individual, such as a user's background, hobbies, preferences, favorite foods, and preferred type of person.

[0848] "Agent software using artificial intelligence" refers to an interactive computer program used to perform emotional analysis and personality assessment through user interaction.

[0849] "Emotional data" refers to data that indicates the user's emotional state, analyzed from factors such as the user's voice tone, facial expressions, and posture.

[0850] "Personality traits" are the result of quantifying or classifying a user's individuality, and are characteristics that define a user's behavior and way of thinking.

[0851] "Fit" is a numerical value or evaluation that indicates the degree of commonality or compatibility between a user and other users.

[0852] "Interaction candidates" are other users suggested to the user based on their suitability, and are individuals with whom communication and relationship building can be expected.

[0853] "Personal growth" refers to changes aimed at personal development and skill improvement that users wish to achieve.

[0854] A "training program" is a series of sessions and assignments designed to improve skills and self-improvement, taking into account the user's personality traits and emotional data.

[0855] This invention is a system aimed at selecting partners and supporting self-growth, taking into account the user's personality and emotional state. The specific forms for implementing the invention are described below.

[0856] The system primarily consists of a terminal, a server, and proxy software using artificial intelligence. The terminal provides an interface for users to input personal attribute information. Users enter information such as their background and hobbies into the terminal, and this information is sent to the server. The server stores the received information in a database and makes it available for subsequent processing.

[0857] The artificial intelligence-powered proxy software analyzes emotional data in real time through interaction with the user. The device enables communication with the user through voice and video, sensing and analyzing the user's voice tone, facial expressions, posture, etc. The analyzed emotional data is sent to a server and used for personality trait diagnosis.

[0858] The server comprehensively analyzes emotional and conversational data to quantify the user's personality traits. For example, a user who frequently uses positive language is diagnosed as highly sociable. This diagnostic information is stored in a database and forms the basis for evaluating compatibility with other users.

[0859] Based on suitability assessments, the server selects potential interactions with other users and presents them to the user via the terminal. For example, sentiment analysis suggests that users who prefer cheerful behavior during conversations will be recommended interaction candidates with similar characteristics.

[0860] The device also presents users with individually tailored training programs. These programs may include tasks and sessions designed to promote positive thinking. The progress of the training program is managed by a server, and users receive regular feedback on their progress and areas for improvement.

[0861] For example, a prompt such as, "List matching candidates with personality traits suitable for highly sociable users, and propose a customized self-improvement program based on the sentiment analysis results," can be used.

[0862] Through the method described above, this invention effectively supports the selection of a partner and personal growth that takes into account the user's individuality and emotional state.

[0863] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0864] Step 1:

[0865] The terminal provides an interface for inputting user attribute information. Users input information such as their background, hobbies, and preferences, and the terminal sends this information to the server.

[0866] Input: Attribute information entered by the user.

[0867] Data processing: The terminal formats the information as structured data.

[0868] Output: Structured user information is sent to the server.

[0869] Step 2:

[0870] The server stores the received user information in a database. This information is used for subsequent interactions and analysis.

[0871] Input: Structured user information sent from the terminal.

[0872] Data processing: The server stores data in the database and creates indexes.

[0873] Output: The server records the status of information saving completion.

[0874] Step 3:

[0875] The device displays a screen to initiate a dialogue session with artificial intelligence-powered proxy software. Once the user starts the session, the device engages in dialogue through voice and video.

[0876] Input: User session start command.

[0877] Data processing: Initiating and capturing real-time streaming.

[0878] Output: Sends dialogue data (audio and video) to the server.

[0879] Step 4:

[0880] The device analyzes the user's voice tone and facial expressions in real time to analyze their emotions. The analyzed data is sent to a server.

[0881] Input: Real-time audio and video data.

[0882] Data processing: Emotional parameters are extracted through analysis using an emotion engine.

[0883] Output: The analyzed emotion data is sent to the server.

[0884] Step 5:

[0885] The server comprehensively analyzes dialogue data and emotional data to diagnose the user's personality traits.

[0886] Input: Dialogue data and sentiment data.

[0887] Data processing: Feature extraction and diagnosis based on language analysis and sentiment evaluation.

[0888] Output: The diagnostic results are saved to the database.

[0889] Step 6:

[0890] The server evaluates compatibility with other users based on the diagnostic results and selects potential interaction partners.

[0891] Input: Diagnostic result.

[0892] Data processing: Calculation of goodness of fit and candidate selection using matching algorithms.

[0893] Output: A list of highly compatible AC candidates is sent to the terminal.

[0894] Step 7:

[0895] The device presents the user with suggested interaction options. The user can browse the displayed list and select an interaction.

[0896] Input: List of potential contacts.

[0897] Data processing: Visualize candidates in the user interface.

[0898] Output: Candidate information presented to the user.

[0899] Step 8:

[0900] The device presents the user with a training program aimed at self-improvement. The program is customized based on the user's personality traits and emotional data.

[0901] Input: Personality traits and emotional data.

[0902] Data processing: Program selection and task customization.

[0903] Output: The user-facing program content is displayed.

[0904] Step 9:

[0905] The server manages the user's training program progress and provides periodic feedback.

[0906] Input: Program progress data.

[0907] Data processing: Progress analysis and feedback generation.

[0908] Output: Progress feedback is sent to the user.

[0909] (Application Example 2)

[0910] 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".

[0911] In modern consumer behavior, providing product information and service suggestions that respond to user emotions is a crucial challenge. In particular, when users experience a company's products and services in a virtual environment, traditional, uniform information provision often fails to fully capture their interest and purchasing intent. Furthermore, there are few systems that can customize the shopping experience based on the user's emotional state and suggest appropriate products, thus creating a need for new technologies to improve user satisfaction.

[0912] 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.

[0913] In this invention, the server includes means for collecting and storing the user's personal information; means for conducting a dialogue between the user and an artificial intelligence agent and analyzing the content of the dialogue; means for diagnosing the user's personality traits based on the analyzed dialogue data; means for evaluating the degree of compatibility with other users based on the diagnosis results and presenting partner candidates; means for providing training programs to promote the user's growth; means for evaluating the user's progress and providing feedback; and means for analyzing the user's emotions in real time and suggesting product information corresponding to those emotions. This enables customized purchase suggestions that are tailored to the user's emotions.

[0914] "Personal information" refers to information that identifies and characterizes individual users, such as their history, hobbies, preferences, favorite foods, and preferred types of people.

[0915] An "artificial intelligence agent" is a program that analyzes information through interaction with the user and evaluates the user's personality traits and emotions.

[0916] "Analysis of dialogue content" involves analyzing information obtained during the communication process between the user and the artificial intelligence agent to understand the user's personality traits and emotional state.

[0917] "Personality trait diagnosis" is the process of evaluating the internal personality characteristics of a user based on their conversational data and emotional data.

[0918] "Compatibility assessment" involves measuring the degree of emotional and personality match between users based on the diagnostic results, and selecting the most suitable partner candidate.

[0919] A "training program" consists of assignments and sessions designed to support user growth, and is customized to the individual user's needs.

[0920] "Progress evaluation" involves monitoring the progress of a training program and analyzing how much users are growing.

[0921] "Feedback" refers to information that provides users with progress-based evaluations and advice, thereby promoting more effective self-improvement.

[0922] "Real-time emotional analysis" involves instantly analyzing a user's emotional state at a given moment based on their voice tone, facial expressions, body movements, and other factors.

[0923] "Product information suggestion" refers to presenting appropriate product and service information based on the user's analyzed emotions, thereby encouraging purchasing behavior.

[0924] To implement this invention, a system is required that includes an application installed on a user's terminal and processing performed by a central server. Specifically, this system consists of a terminal that provides an interface for collecting the user's personal information and a server that analyzes and stores that information.

[0925] The server uses software such as TensorFlow and OpenCV to analyze user emotional data, including voice tone, facial expressions, and body movements, in real time. This allows for the evaluation of the user's personality traits and enables emotion-based purchasing suggestions. This system can present the most suitable products according to the user's emotions and can utilize generative AI models to improve the user experience.

[0926] In terms of specific operations, when a user accesses a virtual store using a device, emotional data is collected through smart glasses or a head-mounted display. The server analyzes this data, generates appropriate product information, and presents it to the user. It also proposes training programs to support the user's growth, tracks their progress, and provides feedback. This allows users to enjoy a personalized shopping experience tailored to their individual emotions.

[0927] For example, if a user experiences an emotion such as "fun" while walking around a store, the system can suggest products that correspond to that emotion, such as new products or items with unique designs.

[0928] An example of a prompt would be: "Write a prompt to analyze the facial expressions and tone of voice a user displays during their shopping experience and suggest products based on their emotional state." This serves as a guide for an AI model to generate appropriate product suggestions based on emotions.

[0929] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0930] Step 1:

[0931] The terminal displays an interface for entering the user's personal information. When the user enters their background, hobbies, and other personal information, this data is collected and sent to the server. This data is stored on the server for use in future interactions and analysis.

[0932] Step 2:

[0933] The terminal displays a screen for a dialogue session with an artificial intelligence agent, and the user initiates the session. Once the user gives the start command, the terminal performs a real-time dialogue through voice and video. It uses the user's voice and video data as input and sends it to the server as material for interpretation.

[0934] Step 3:

[0935] The server analyzes the received audio and video data and uses tools such as TensorFlow and OpenCV to evaluate the user's voice tone, facial expressions, and body movements in real time. In this step, data processing is performed and analysis results are output to obtain the user's emotional state.

[0936] Step 4:

[0937] The server integrates the analysis results of the conversation content with emotional data to diagnose the user's personality traits. The diagnosis quantifies the personality based on the entered personal information and emotional data obtained in real time, and outputs an evaluation of the user's characteristics.

[0938] Step 5:

[0939] The server compares the user's diagnostic data with that of other users and performs a suitability assessment. In this step, partner candidates are selected based on the user's personality traits and emotional data, and output is generated to present the user with the most suitable candidate.

[0940] Step 6:

[0941] The server creates individually customized training programs based on the user's emotional data and delivers them to the user via the terminal. This suggests tasks for self-improvement tailored to the user's emotions and personality. Furthermore, the server continuously tracks the program's progress.

[0942] Step 7:

[0943] The server uses a generative AI model to generate product information tailored to the user's emotions and presents it to the user through the terminal. In this step, prompts generated based on emotion data are used to further personalize the content. This allows the user to receive a shopping experience optimized for their own emotional state.

[0944] 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.

[0945] 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 those described above. 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 shown 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.

[0946] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0947] 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.

[0948] 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.

[0949] 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.

[0950] 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.

[0951] 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.

[0952] 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."

[0953] 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.

[0954] 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.

[0955] 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.

[0956] 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.

[0957] 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.

[0958] 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.

[0959] 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.

[0960] 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.

[0961] 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.

[0962] 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.

[0963] 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.

[0964] 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.

[0965] The following is further disclosed regarding the embodiments described above.

[0966] (Claim 1)

[0967] Means for collecting and storing users' personal information,

[0968] A means for conducting a dialogue between the user and the artificial intelligence agent and analyzing the content of that dialogue,

[0969] A means of diagnosing the user's personality traits based on analyzed dialogue data,

[0970] A means of evaluating compatibility with other users based on diagnostic results and suggesting potential partners,

[0971] A means of providing training programs to promote user growth,

[0972] A means of evaluating user progress and providing feedback,

[0973] A system that includes this.

[0974] (Claim 2)

[0975] The system according to claim 1, further comprising means for evaluating the user's emotions and speech patterns in real time during interaction with the artificial intelligence agent.

[0976] (Claim 3)

[0977] The system according to claim 1, further comprising means for the training program that promotes the growth of the user to be individually customized based on the user's diagnostic results.

[0978] "Example 1"

[0979] (Claim 1)

[0980] Means for collecting and storing users' personal information,

[0981] A means for conducting a dialogue between the user and the information processing device and analyzing the content of that dialogue,

[0982] A means of diagnosing the user's personality traits based on analyzed dialogue data,

[0983] A means of evaluating the degree of compatibility with other users based on the diagnostic results and presenting candidates,

[0984] A means of providing training methods to promote user growth,

[0985] A means of evaluating user progress and presenting the evaluation results,

[0986] Methods for using generative models in the analysis of dialogue,

[0987] A system that includes this.

[0988] (Claim 2)

[0989] The system according to claim 1, further comprising means for evaluating the user's emotions and speech patterns in real time during interaction with the information processing device.

[0990] (Claim 3)

[0991] The system according to claim 1, wherein the training means for promoting the growth of the user further includes means for which the training means are individually designed based on the user's diagnostic results.

[0992] "Application Example 1"

[0993] (Claim 1)

[0994] A means of collecting and recording user attribute information,

[0995] A means for communicating between the user and the intelligent program and analyzing the content of that communication,

[0996] A means for evaluating user characteristics based on analyzed communication data,

[0997] A means of measuring compatibility with other users based on evaluation results and suggesting mutual candidates,

[0998] A means of providing educational programs to support user improvement,

[0999] A means of measuring user progress and providing responses,

[1000] A means of recommending and guiding the purchase of items based on user preferences,

[1001] A system that includes this.

[1002] (Claim 2)

[1003] The system according to claim 1, further comprising means for instantaneously evaluating the user's emotions and expression patterns in communication with the intelligent program.

[1004] (Claim 3)

[1005] The system according to claim 1, further comprising means for individually optimizing the educational program that supports the improvement of the user based on the user's evaluation results.

[1006] "Example 2 of combining an emotion engine"

[1007] (Claim 1)

[1008] A means of collecting and storing user attribute information,

[1009] A means for conducting a dialogue between the user and the surrogate software using artificial intelligence, and for analyzing the content of that dialogue,

[1010] A means for diagnosing a user's personality traits based on analyzed dialogue data and emotional data,

[1011] A means for evaluating compatibility with other users based on diagnostic results and sentiment evaluation data, and for suggesting potential interaction candidates.

[1012] A means of providing training programs to promote user self-growth,

[1013] A means of evaluating user progress and providing information,

[1014] A system that includes this.

[1015] (Claim 2)

[1016] The system according to claim 1, further comprising means for evaluating the user's emotional state and speech patterns in real time during interaction with the aforementioned surrogate software using artificial intelligence.

[1017] (Claim 3)

[1018] The system according to claim 1, further comprising means for individually adjusting the training program for promoting the user's self-growth based on the user's diagnostic results and emotional data.

[1019] "Application example 2 when combining with an emotional engine"

[1020] (Claim 1)

[1021] Means for collecting and storing users' personal information,

[1022] A means for conducting a dialogue between the user and the artificial intelligence agent and analyzing the content of that dialogue,

[1023] A means of diagnosing the user's personality traits based on analyzed dialogue data,

[1024] A means of evaluating compatibility with other users based on diagnostic results and suggesting potential partners,

[1025] A means of providing training programs to promote user growth,

[1026] A means of evaluating user progress and providing feedback,

[1027] A method for analyzing user emotions in real time and suggesting product information that corresponds to those emotions,

[1028] A system that includes this.

[1029] (Claim 2)

[1030] The system according to claim 1, further comprising means for evaluating the user's emotions and speech patterns in real time during interaction with the artificial intelligence agent.

[1031] (Claim 3)

[1032] The system according to claim 1, further comprising means for the training program that promotes the growth of the user to be individually customized based on the user's diagnostic results. [Explanation of Symbols]

[1033] 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 collecting and storing users' personal information, A means for conducting a dialogue between the user and the artificial intelligence agent and analyzing the content of that dialogue, A means of diagnosing the user's personality traits based on analyzed dialogue data, A means of evaluating compatibility with other users based on diagnostic results and suggesting potential partners, A means of providing training programs to promote user growth, A means of evaluating user progress and providing feedback, A system that includes this.

2. The system according to claim 1, further comprising means for evaluating the user's emotions and speech patterns in real time during interaction with the artificial intelligence agent.

3. The system according to claim 1, further comprising means for the training program that promotes the growth of the user to be individually customized based on the user's diagnostic results.

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