System

Abstract

A system is provided.SOLUTION: The system includes a means for a user to input his / her own information, a means for analyzing the inputted information and discriminating a marriage-seeking power, a means for providing feedback based on the discriminated marriage-seeking power, a means for executing a virtual meeting, a means for evaluating conversation and expression during the virtual meeting, a means for generating an avatar based on a behavior pattern of the user, and a means for displaying conversation between avatars.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In modern society, declining marriage rates and a declining birthrate have become serious social issues. While many people desire marriage, they lack effective ways to find a suitable partner. Traditional matchmaking services struggle to objectively evaluate users' strengths and weaknesses and provide specific feedback. Furthermore, many users experience repeated failures during their first matchmaking session, posing a major hurdle to marriage. Furthermore, self-evaluation tends to be subjective, making it difficult to find solutions. [Means for solving the problem]

[0005] To solve these problems, the present invention provides a system that objectively evaluates a user's marriage potential and suggests specific improvement measures. Specifically, the user inputs their own information, and AI determines their marriage potential based on this information. In addition, a virtual matchmaking session is conducted using the generation AI, and the conversation content and facial expressions are analyzed and evaluated. Based on this evaluation, strengths and weaknesses are clarified and specific improvement measures are suggested. Furthermore, by generating avatars based on the user's behavioral patterns and displaying conversations between avatars, the system allows users to evaluate themselves from a third-party perspective. This allows users to effectively improve themselves and take a step toward their goal of marriage.

[0006] "User" means any individual who uses this System.

[0007] "Information" refers to data entered by users, such as annual income, appearance, hobbies, and romantic history.

[0008] "Marriage Power" is an indicator used to evaluate a user's potential for marriage and likelihood of success.

[0009] "Virtual matchmaking" refers to a simulated matchmaking session using generative AI, where users interact with the AI.

[0010] "Generative AI" refers to a virtual matchmaking partner that interacts with users using artificial intelligence technology.

[0011] "Evaluation" means quantifying and analyzing the user's conversational skills and facial expressions during the virtual matchmaking session.

[0012] An "avatar" refers to a virtual character generated based on a user's behavioral patterns and characteristics.

[0013] "Feedback" refers to specific improvement measures and suggestions provided based on the user's matchmaking ability. [Brief explanation of the drawings]

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

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

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

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

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

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

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

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

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

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

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0035] The system of the present invention aims to enable users to evaluate their matchmaking ability and obtain improvement measures. This system provides specific feedback by having users input their own information and participate in a virtual matchmaking session.

[0036] Entering user information

[0037] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, love history, etc.). For example, they enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal.

[0038] Analysis of marriage potential

[0039] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[0040] Providing feedback

[0041] The server analyzes the user's strengths and weaknesses based on the determined marriage vitality score. The results are provided as feedback, including specific improvements. For example, suggestions may be made such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and displayed to the user.

[0042] Virtual matchmaking

[0043] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on weekends." All conversations in this virtual matchmaking session are recorded by the server.

[0044] Conversation and facial expression evaluation

[0045] The server analyzes the content of conversations and the user's facial expressions during the virtual matchmaking session in real time. Evaluations are made on a wide range of topics, including conversational ability, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. The analysis results are compiled on the server as an evaluation score, and specific areas for improvement are provided to the user along with the evaluation. Advice such as "be more relaxed and smile more" and "ask more questions to the other person" are included.

[0046] Create your own avatar

[0047] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "personal avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0048] This system allows users to receive objective and detailed feedback, enabling them to implement specific improvements to their search for a partner.

[0049] The processing flow will be explained below.

[0050] Step 1:

[0051] A user accesses the system and logs in by entering the required information on the login screen.

[0052] Step 2:

[0053] The device checks the user's information and displays the home screen. The user then moves to the profile setting screen and enters the necessary information (annual income, appearance, hobbies, romantic history, etc.).

[0054] Step 3:

[0055] The terminal sends the entered user information to the server, where it is stored in a database.

[0056] Step 4:

[0057] Based on the information received by the server, an AI algorithm is used to calculate a score for each element, such as annual income, appearance, hobbies, and profile text, and these are then combined to calculate an overall matchmaking ability score.

[0058] Step 5:

[0059] The server generates the calculated score and detailed feedback information. For example, if a user's annual income is highly rated but their profile text is weak, the server will suggest specific ways to improve the profile.

[0060] Step 6:

[0061] The server sends the generated feedback and score information to the device, which displays it to the user.

[0062] Step 7:

[0063] Next, the user selects a virtual matchmaking session and sets up the virtual matchmaking session. The server then starts the virtual matchmaking generation AI and generates a dialogue scenario.

[0064] Step 8:

[0065] The generative AI starts the virtual matchmaking session and makes an initial statement (e.g., "Nice to meet you. What are your hobbies?"), to which the user responds (e.g., "I like soccer and play futsal with my friends on weekends").

[0066] Step 9:

[0067] The server records the conversations and the user's facial expressions in real time, and the data is then prepared for analysis by AI.

[0068] Step 10:

[0069] The server analyzes conversation data and facial expression data to evaluate the quality of speech, the level of facial relaxation, the frequency of smiling, etc. The evaluation results are compiled as a score.

[0070] Step 11:

[0071] The server generates an evaluation score and specific feedback (e.g., "Ask people more questions more often" or "Smile more and keep a relaxed expression").

[0072] Step 12:

[0073] The server sends the evaluation score and feedback to the device, which displays it to the user.

[0074] Step 13:

[0075] Users participate in multiple virtual matchmaking sessions, and the data is stored on a server. The server then aggregates this data and generates a "personal avatar" based on the user's behavioral patterns and characteristics.

[0076] Step 14:

[0077] The server generates a conversation scenario between the generated "self avatars" and sends it to the device, which then displays it to the user.

[0078] Step 15:

[0079] Users observe conversations between avatars and self-evaluate from a third-party perspective to determine areas for improvement. Based on the information gained through this process, users can improve their behavior in actual matchmaking.

[0080] Example 1

[0081] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0082] Conventional matchmaking support systems have difficulty objectively evaluating users' matchmaking skills and providing specific improvement measures. Furthermore, it is often difficult to identify areas for improvement through self-evaluation alone, and virtual matchmaking sessions and feedback provision are insufficient. Furthermore, there is a lack of appropriate means for users to objectively understand their own behavior and conversations. This has led to issues such as users being unable to effectively improve their matchmaking skills, resulting in a lower success rate in matchmaking.

[0083] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0084] In this invention, the server includes means for a user to input his / her own information, means for analyzing and determining a marriage ability based on the input information, means for providing feedback based on the determined marriage ability score, means for conducting a virtual dialogue, means for evaluating the conversation and facial expressions during the virtual dialogue, means for generating an avatar based on the user's behavioral characteristics, and means for displaying a dialogue between the avatars. This allows a user to objectively evaluate his / her own marriage ability, understand specific areas for improvement, and effectively improve his / her actual marriage ability skills.

[0085] The "user information input means" is an interface that allows a user to provide their own individual information to the system.

[0086] "Marriage potential analysis tools" is a general term for AI algorithms and software that evaluate marriage potential based on provided user information.

[0087] The "feedback provision means" is the part of the system that has the function of presenting specific areas for improvement and strengths to users based on the analyzed marriage vitality score.

[0088] A "means for implementing virtual interaction" is software or an interface that allows a user to virtually interact within a system.

[0089] The "conversation and facial expression evaluation means" is a system function that analyzes the content of the user's conversation and facial expressions during virtual conversation in real time and evaluates the results.

[0090] "Avatar generation means" is a system function for creating an avatar, which is a virtual self-representation, based on the user's behavioral characteristics.

[0091] The "avatar dialogue display means" is an interface for displaying to the user a simulated conversation in which the generated avatars converse with each other.

[0092] The "behavior and speech recording means" is a part of the system for recording the actions and speeches made by the user during the virtual interaction and storing the data.

[0093] The "strengths and weaknesses extraction means" is a system function that extracts the strengths and weaknesses from the information input by the user and generates specific improvement measures based on that information.

[0094] The main purpose of the system of the present invention is to enable users to evaluate their marriage vitality and obtain improvement measures. The components of this system include a user information input means, a marriage vitality analysis means, a feedback providing means, a virtual dialogue implementation means, a conversation and facial expression evaluation means, an avatar generation means, and an avatar dialogue display means.

[0095] Entering user information

[0096] Users log in to the system and enter information such as annual income, appearance (height, weight, photo of face, etc.), hobbies, and romantic history into a dedicated input form. For example, they enter information such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking," and this information is sent to the server via their terminal.

[0097] Analysis of marriage potential

[0098] The server receives the information sent by the user and uses an AI algorithm to evaluate their matchmaking ability. Specifically, factors such as annual income, appearance (height and weight), and variety of hobbies are evaluated using a scoring system to calculate an overall matchmaking ability score. For example, if the annual income is 6 million yen, the score would be 8 / 10, appearance 7 / 10, hobbies 8 / 10, and profile text 6 / 10. This evaluation result, along with a detailed breakdown, is sent back to the device and displayed to the user.

[0099] Providing feedback

[0100] The server analyzes the user's strengths and weaknesses based on the evaluation results and generates feedback including specific suggestions for improvement, such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and presented to the user.

[0101] Conducting virtual conversations

[0102] The user sets up a virtual conversation on the system. The generative AI model makes the initial utterance, and the virtual conversation is simulated. For example, the generative AI model asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The contents of the virtual conversation are all recorded on the server.

[0103] Conversation and facial expression evaluation

[0104] The server analyzes the content of the conversation and the user's facial expressions during the virtual conversation in real time. Analyzed elements include conversational skills, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. For example, while understanding the context of the conversation, it evaluates whether the questions asked to the other person are appropriate and whether the user is relaxed. The analysis results are generated as an evaluation score, and specific feedback is provided, such as "be more relaxed and smile more" or "ask more questions to the other person." This evaluation score and feedback are sent to the device and displayed to the user.

[0105] Create your own avatar

[0106] The server generates an avatar that reflects the user's behavioral characteristics based on behavioral data collected from multiple virtual conversations. Users can use this avatar to evaluate themselves from a third-person perspective. A simulated conversation between the generated avatars is displayed on the device, and by observing the interaction, users can more objectively understand areas for improvement.

[0107] By integrating the above processes, users can objectively evaluate their marriage potential, understand specific improvement measures, and actually improve their conversation skills.

[0108] Example prompt sentence:

[0109] User: Nice to meet you. What hobbies should I have?

[0110] Generative AI: Nice to meet you. If you have a variety of hobbies, it's easier to have a lively conversation and make a good impression on others. Can you tell me more about your hobbies?

[0111] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0112] Step 1: Enter your user information

[0113] Users log in to the system and enter information such as annual income, appearance (height, weight, photo of face, etc.), hobbies, and romantic history into a dedicated input form. This information is sent to the server via the terminal. Input includes specific data such as "annual income of 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking." Once this data reaches the server, it is saved in a database.

[0114] Step 2: Analysis of your marriage potential

[0115] The server uses an AI algorithm to evaluate a user's matchmaking ability based on the information sent by the user. Specifically, it uses a scoring system to evaluate factors such as annual income, appearance (height and weight), and the variety of hobbies, and calculates an overall matchmaking ability score. For an annual income of 6 million yen, the server generates an evaluation result such as 8 / 10 for appearance, 7 / 10 for hobbies, 8 / 10 for hobbies, and 6 / 10 for the profile text. This evaluation result is sent back to the device and displayed to the user.

[0116] Step 3: Provide feedback

[0117] The server analyzes the user's strengths and weaknesses based on the evaluation results and generates feedback including specific recommendations for improvement. Examples of such feedback include "take a more professional profile picture" and "add detailed stories about your hobbies." This feedback is sent to the device and presented to the user. When providing feedback, the server uses a generative AI model to make more specific and personalized suggestions.

[0118] Step 4: Conducting a virtual interaction

[0119] The user sets up a virtual dialogue on the system, and the generative AI model makes the initial utterance to simulate the virtual dialogue. For example, the generative AI asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The content of this dialogue is recorded on the server. The input includes the user's answer, and the output includes the generative AI model's next question.

[0120] Step 5: Evaluate speech and facial expressions

[0121] The server analyzes the content of the conversation and the user's facial expressions during the virtual conversation in real time. Analyzed elements include conversational skills, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. For example, it understands the context of the conversation and evaluates whether the questions asked to the other person are appropriate and the level of relaxation. The analysis results are generated as an evaluation score, and specific feedback such as "be more relaxed and smile more" or "ask more questions to the other person" is provided. The evaluation score and feedback are sent to the device and displayed to the user.

[0122] Step 6: Create your own avatar

[0123] The server generates an avatar that reflects the user's behavioral characteristics based on behavioral data collected from multiple virtual conversations. Users can use this avatar to evaluate themselves from a third-party perspective. A simulated conversation between the generated avatars is displayed on the device, and by observing the interaction, users can more objectively understand areas for improvement. For example, the content of the avatar's conversation and behavioral patterns can be displayed, and by observing them, specific improvement measures can be obtained.

[0124] (Application example 1)

[0125] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0126] In conventional matchmaking support systems, users were limited to online environments in terms of the means by which they could receive feedback to evaluate and improve their matchmaking abilities, resulting in insufficient real-time support at physical stores. Additionally, virtual matchmaking experiences were only available online, resulting in a lack of feedback through physical store experiences.

[0127] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0128] In this invention, the server includes means for a user to input his / her own information, means for analyzing the input information and determining the marriage activity power, means for providing feedback based on the determined marriage activity power, means for conducting a virtual matchmaking meeting, means for evaluating the conversation and facial expressions during the virtual matchmaking meeting, means for generating an avatar based on the user's behavioral patterns, means for displaying conversations between the avatars, and means for providing real-time feedback to the user at a physical store. This enables the user to receive an evaluation of their marriage activity power and specific feedback in real time even at a physical store.

[0129] A "user" is an individual who accesses the system, enters their information, and receives a matchmaking ability rating and feedback.

[0130] The "means of inputting information" refers to the interface that allows users to input their basic information (annual income, appearance, hobbies, romantic history, etc.) into the system.

[0131] "Means of analyzing information and determining marriage potential" refers to the process of evaluating marriage potential using AI algorithms and other methods based on collected user information.

[0132] The "means of providing feedback" is a function that suggests strengths, weaknesses, and specific improvement measures to users based on their assessed matchmaking ability.

[0133] The "means for conducting a virtual matchmaking session" is a function that allows a user to simulate a matchmaking session in a virtual environment and record the results.

[0134] "Means for evaluating conversations and facial expressions" refers to the process of analyzing and evaluating the user's statements and facial expressions during virtual matchmaking.

[0135] "Means for generating avatars based on behavioral patterns" refers to a function that creates an avatar that mimics a user based on the user's behavioral data collected from multiple virtual matchmaking sessions.

[0136] "Means for displaying conversations between avatars" is a function that allows the user to visually see the generated avatars conversing with each other.

[0137] "Means for providing real-time feedback in physical stores" refers to a function that allows users to receive an on-the-spot evaluation of their matchmaking abilities at physical stores such as matchmaking cafes, and provides specific feedback in real time.

[0138] The system of the present invention aims to enable users to evaluate their matchmaking ability and obtain improvement measures. This system provides specific feedback by having users input their own information and participate in a virtual matchmaking session.

[0139] Entering user information

[0140] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, love history, etc.). For example, they enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal.

[0141] Analysis of marriage potential

[0142] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[0143] Providing feedback

[0144] The server analyzes the user's strengths and weaknesses based on the determined matchmaking power score. The results are provided as feedback, including specific improvements. For example, suggestions include "take a more professional profile picture" and "add detailed stories about your hobbies." This feedback is sent to the user's device and displayed.

[0145] Virtual matchmaking

[0146] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on the weekends." All conversations in this virtual matchmaking session are recorded by the server.

[0147] Conversation and facial expression evaluation

[0148] The server analyzes the content of conversations and the user's facial expressions during the virtual matchmaking session in real time. Evaluations are made on a wide range of topics, including conversational ability, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. The analysis results are compiled on the server as an evaluation score, and specific areas for improvement are provided to the user along with the evaluation. Advice such as "be more relaxed and smile more" and "ask more questions to the other person" are included.

[0149] Create your own avatar

[0150] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0151] Providing feedback in-store

[0152] This system can also be used in brick-and-mortar stores, such as matchmaking cafes. Users can enter their information using a tablet or smartphone in the store and conduct a virtual matchmaking session. They can then receive real-time feedback from the server. This makes it possible to evaluate a person's matchmaking ability and provide specific improvement measures even in brick-and-mortar stores.

[0153] Examples of concrete examples and prompts

[0154] A concrete example would be a system in which users can use a tablet at a matchmaking cafe to input their personal information, experience a virtual matchmaking session on the spot, and have AI provide feedback in real time. Users can then receive specific advice based on their scores.

[0155] Examples of prompts include:

[0156] User Information:

[0157] Annual income: 6 million yen

[0158] Appearance: Height 175cm, Weight 70kg

[0159] Hobbies: Soccer, cooking

[0160] Romance history: 3 relationships

[0161] Rate this user's marriage ability and provide feedback such as:

[0162] Strengths

[0163] Weakness

[0164] Improvement points

[0165] Also, provide examples of initial statements from virtual matchmaking.

[0166] This will clarify the specific steps for implementing the invention and its effects.

[0167] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0168] Step 1: Enter your user information

[0169] Users access the system via their terminal and enter their basic information (annual income, appearance, hobbies, romantic history, etc.) into a form. This input includes specific data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer, cooking." This information is sent from the terminal to the server. The input data is sent in JSON format and analyzed on the server side.

[0170] Step 2: Analysis of your marriage potential

[0171] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. This analysis scores annual income, appearance, and hobby diversity. For example, an annual income of 6 million yen would be considered high, with a score of 8 / 10, appearance 7 / 10, and hobby diversity 8 / 10. The server combines these ratings to calculate a marriage potential score and returns the result in JSON format to the device. The score returned from the server is displayed on the user's device.

[0172] Step 3: Provide feedback

[0173] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates specific feedback. For example, it suggests improvements such as "take a professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the user's device and displayed to them.

[0174] Step 4: Conduct a virtual matchmaking session

[0175] The user sets up a virtual matchmaking session through their device. The generative AI model running on the server makes the first statement, simulating the virtual matchmaking. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?" and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." All of this conversation is recorded by the server.

[0176] Step 5: Evaluate speech and facial expressions

[0177] The server analyzes the content of the conversation and the user's facial expressions during the virtual matchmaking session in real time. It evaluates conversational ability, the quality of questions, reactions to the other person, the level of facial relaxation, and the frequency of smiling, and compiles the analysis results as an evaluation score. Specific improvements are generated along with these results, and advice such as "be more relaxed and smile more" or "ask more questions to the other person" is provided to the user.

[0178] Step 6: Create your own avatar

[0179] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0180] Step 7: Providing real-time feedback in-store

[0181] In a physical store, such as a matchmaking cafe, users can access the system using a tablet or smartphone to enter the information described above, conduct a virtual matchmaking session, and receive feedback in real time. The server processes the input data from the physical store, instantly generates feedback, and sends it back to the device, allowing users to receive specific advice on the spot.

[0182] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0183] The system of the present invention aims to evaluate the user's matchmaking ability and provide more accurate feedback and improvement measures using an emotion engine. The system provides specific feedback and advice based on emotion recognition by having the user input their own information and participate in a virtual matchmaking session.

[0184] Entering user information

[0185] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, romantic history, etc.). For example, they might enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal and stored in the database.

[0186] Analysis of marriage potential

[0187] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[0188] Providing feedback

[0189] The server analyzes the user's strengths and weaknesses based on the determined marriage vitality score. The results are provided as feedback, including specific improvements. For example, suggestions may be made such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and displayed to the user.

[0190] Emotion recognition by emotion engine

[0191] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice during the virtual matchmaking session to recognize their emotions. For example, if the user is nervous, the emotion engine will recognize this from their facial expressions and tone of voice and provide an analysis result. This data is sent to the server in real time.

[0192] Virtual matchmaking

[0193] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on the weekends." The content of the virtual matchmaking session, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[0194] Conversation and facial expression evaluation

[0195] The server analyzes the content of conversations during virtual matchmaking, as well as the user's facial expressions and emotional data in real time. The evaluation takes into account conversational ability, quality of questions, reactions to the other person, facial relaxation and frequency of smiling, as well as the results of emotion recognition by the emotion engine. The analysis results are compiled as an evaluation score.

[0196] Enhanced feedback

[0197] The server uses the results of the emotion engine to provide additional feedback according to the user's emotional state. For example, it provides specific improvement suggestions such as "If you feel nervous, take a deep breath and try to relax" or "Introduce yourself calmly and with positive emotions." This feedback is sent to the device and displayed to the user.

[0198] Create your own avatar

[0199] The user's behavioral and emotional data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state. Using this avatar, the user can evaluate themselves from a third-person perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0200] This system allows users to receive objective and detailed feedback, and improve their chances of finding a partner based on highly accurate advice provided by the emotion engine.

[0201] The processing flow will be explained below.

[0202] Step 1:

[0203] A user accesses the system and logs in by entering the required information on the login screen.

[0204] Step 2:

[0205] The device checks the user's information and displays the home screen. The user then moves to the profile setting screen and enters the necessary information (annual income, appearance, hobbies, romantic history, etc.).

[0206] Step 3:

[0207] The terminal sends the entered user information to the server, where it is stored in a database.

[0208] Step 4:

[0209] Based on the information received by the server, an AI algorithm is used to calculate a score for each element, such as annual income, appearance, hobbies, and profile text, and these are then combined to calculate an overall matchmaking ability score.

[0210] Step 5:

[0211] The server generates the calculated score and detailed feedback information. For example, if a user's annual income is highly rated but their profile text is weak, the server will suggest specific ways to improve the profile.

[0212] Step 6:

[0213] The server sends the generated feedback and score information to the terminal, which displays it to the user.

[0214] Step 7:

[0215] Next, the user selects a virtual matchmaking session and sets up the virtual matchmaking session. The server then starts the virtual matchmaking generation AI and generates a dialogue scenario.

[0216] Step 8:

[0217] The generative AI starts the virtual matchmaking session and makes an initial statement (e.g., "Nice to meet you. What are your hobbies?"), to which the user responds (e.g., "I like soccer and play futsal with my friends on weekends").

[0218] Step 9:

[0219] The server records the conversation content during the virtual matchmaking session, as well as the user's facial expressions and voice in real time, and each piece of data is prepared for analysis by the emotion engine.

[0220] Step 10:

[0221] The emotion engine analyzes the user's facial expressions and voice to generate emotion data, for example, to determine whether the user is nervous.

[0222] Step 11:

[0223] The server analyzes the emotional data and conversation data, evaluating the quality of speech, the level of facial relaxation, the frequency of smiling, etc. The evaluation results are compiled as a score.

[0224] Step 12:

[0225] The server generates an evaluation score and specific feedback (e.g., "Ask people more questions more often" or "Smile more and keep a relaxed expression").

[0226] Step 13:

[0227] The server sends the evaluation score and feedback to the device, which displays it to the user.

[0228] Step 14:

[0229] Users participate in multiple virtual matchmaking sessions, and the data is stored on a server. The server then aggregates this data and generates a "personal avatar" based on the user's behavioral patterns and emotional data.

[0230] Step 15:

[0231] The server generates a conversation scenario between the generated "self avatars" and sends it to the device, which then displays it to the user.

[0232] Step 16:

[0233] Users observe conversations between avatars and self-evaluate from a third-party perspective to determine areas for improvement. Based on the information gained through this process, users can improve their behavior in actual matchmaking.

[0234] Example 2

[0235] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0236] Conventional matchmaking systems only require users to enter basic information, limiting the amount of feedback they can provide. They also lack the means for self-evaluation through detailed analysis via emotion recognition or virtual matchmaking, or avatar generation. This makes it difficult for users to receive more accurate feedback and specific improvement measures.

[0237] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0238] In this invention, the server includes means for a user to input his / her own information, means for analyzing the input information and determining the marriage activity potential, means for providing feedback based on the determined marriage activity potential, means for analyzing the facial expressions and voice of the user during the virtual matchmaking using an emotion engine and recognizing emotions, means for conducting the virtual matchmaking, means for evaluating the conversation and facial expressions during the virtual matchmaking, means for enhancing the feedback based on the evaluation results, means for generating an avatar based on the user's behavioral patterns, and means for displaying the conversation between the avatars. This allows the user to receive detailed and objective feedback and obtain specific measures for self-improvement through emotion recognition and virtual matchmaking.

[0239] "User" means an individual who accesses the system, enters their information, and receives feedback.

[0240] "Information input" refers to the act of a user providing basic information about themselves (annual income, appearance, hobbies, romantic history, etc.) to the system.

[0241] "Analysis" refers to the means of evaluating the entered user information and determining their potential for marriage.

[0242] "Marriage Ability" is a comprehensive evaluation score of a user's marriage activities, calculated based on attributes such as annual income, appearance, hobbies, and profile text.

[0243] "Feedback" refers to information that points out a user's strengths and weaknesses based on analysis results and provides specific measures for improvement.

[0244] The "emotion engine" is a technology that analyzes the user's facial expressions and voice during a virtual matchmaking session and recognizes their emotions in real time.

[0245] "Virtual matchmaking" is a feature in which a generative AI model makes the first statement and simulates a matchmaking session, which progresses through interaction with the user.

[0246] A "generative AI model" is an artificial intelligence that generates conversations with users during virtual matchmaking and feedback sessions.

[0247] "Conversation and facial expression evaluation" is a method of analyzing the content of a user's remarks and facial expression data during a virtual matchmaking session and calculating an overall evaluation score.

[0248] "Enhanced feedback" refers to a means of providing more specific feedback that has a greater effect on improvement, based on evaluation results and emotional recognition.

[0249] An "avatar" is a virtual self-image generated based on the user's behavioral patterns and emotional data, allowing for self-evaluation from a third-party perspective.

[0250] "Avatar-to-avatar conversation" is a feature that displays multiple avatars having a simulated conversation using a generative AI model.

[0251] The matchmaking support system of the present invention allows users to input their own information, evaluate their matchmaking ability through virtual matchmaking, and provides highly accurate feedback and improvement measures using an emotion engine. This system includes a terminal for users to input information, a server for analyzing the information and evaluating matchmaking ability, and various software for providing feedback.

[0252] Hardware and software used

[0253] This system uses the following hardware and software:

[0254] Device: An electronic device (computer, smartphone, tablet, etc.) where users input information and view feedback and results.

[0255] Server: A computer that manages user information, analyzes it, and generates feedback.

[0256] Emotion engine: Dedicated software for analyzing the user's facial expressions and voice in real time (e.g., Emotion API)

[0257] Generative AI model: An artificial intelligence platform for simulating virtual matchmaking conversations (e.g., GPT-3 (registered trademark))

[0258] Specific examples of processing

[0259] Input and analysis of user information

[0260] The user uses the device to input their basic information (annual income, appearance, hobbies, love history, etc.). For example, they input information such as "annual income of 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking." The device sends this information to the server, which stores it in a database.

[0261] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is rated high, while a height of 175 cm and a weight of 70 kg is rated medium. The server evaluates this information based on a scoring system and calculates an overall marriage potential score. This score is sent back to the device and displayed to the user.

[0262] Providing feedback

[0263] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates appropriate feedback, such as suggestions like "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent from the server to the user's device and displayed.

[0264] Emotion recognition by emotion engine

[0265] Once the virtual matchmaking session begins, the server's built-in emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotions. For example, if the user is nervous, the emotion engine will detect this from their facial expressions and tone of voice and send that data to the server.

[0266] Virtual matchmaking

[0267] When a user sets up a virtual matchmaking session, the generative AI model makes the first statement and simulates the matchmaking. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?", and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." The content of this conversation, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[0268] Enhanced speech and facial expression assessment and feedback

[0269] The server analyzes the conversation content during the virtual matchmaking session, as well as the user's facial expressions and emotional data, to calculate an overall evaluation score. It also strengthens feedback based on the results of the emotion engine, providing specific improvement measures such as "If you feel nervous, take a deep breath and relax" and "Introduce yourself calmly with positive emotions." This feedback is sent to the device and displayed to the user.

[0270] Create your own avatar

[0271] The server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state based on the user's behavioral and emotional data accumulated through virtual matchmaking. The user can use this avatar to evaluate themselves from a third-person perspective and observe simulated conversations between avatars.

[0272] Prompt Sentence Examples

[0273] Please rate your marriage strength based on the user information below and provide specific feedback and suggestions for improvement.

[0274] User Information:

[0275] Annual income: 6 million yen

[0276] Appearance: Height 175cm, Weight 70kg, Photo (URL)

[0277] Hobbies: Soccer, cooking

[0278] Romance history: 3 times

[0279] Matchmaking Settings:

[0280] First utterance from the generated AI: "Nice to meet you. What are your hobbies?"

[0281] User response:

[0282] "I like soccer and play futsal with my friends on the weekends."

[0283] The system of the present invention provides detailed and objective feedback to users throughout these processes and suggests specific strategies for self-improvement through emotion recognition and virtual matchmaking.

[0284] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0285] Step 1: Enter your user information

[0286] Users access the system through their terminal and enter their basic information (annual income, appearance, hobbies, love history, etc.). For example, they might enter data such as "annual income of 6 million yen," "appearance: photo of height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into a form. This input information is sent from the terminal to the server, which then stores it in a database.

[0287] Input: User information such as annual income, appearance, hobbies, and romantic history

[0288] Data processing: Save the input information as structured data

[0289] Output: Saved user information

[0290] Step 2: Analysis of your marriage potential

[0291] The server retrieves user information stored in a database and uses an AI algorithm to determine a person's marriage potential. For example, an annual income of 6 million yen is rated high, while a height of 175 cm is rated neutral. The server calculates a score for each attribute and generates an overall marriage potential score. This score is sent back to the device and displayed to the user.

[0292] Input: User information stored in the database

[0293] Data calculation: Scoring each attribute using AI algorithms

[0294] Output: Overall marriage vitality score and its breakdown

[0295] Step 3: Provide feedback

[0296] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates specific feedback, such as suggestions like "take a more professional profile picture" or "add more detailed stories about your hobbies." This feedback is sent from the server to the user's device and displayed.

[0297] Input: Marital vitality score and its breakdown

[0298] Data processing: feedback generation based on scores

[0299] Output: Analysis of strengths and weaknesses and specific feedback

[0300] Step 4: Emotion Recognition with the Emotion Engine

[0301] During the virtual matchmaking session, the server's built-in emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotions. For example, if the user is nervous, the emotion engine will detect this from their facial expressions and tone of voice, and the data will be sent to the server in real time.

[0302] Input: facial expression data and voice data of the user during the virtual matchmaking session

[0303] Data Computation: Real-time Emotion Analysis with an Emotion Engine

[0304] Output: Emotion recognition result

[0305] Step 5: Conduct a virtual matchmaking session

[0306] The user sets up a virtual matchmaking session, and the generative AI model makes the first utterance, simulating the matchmaking. For example, the generative AI asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The content of this conversation, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[0307] Input: The initial utterance of the generative AI model, and the user's response

[0308] Data processing: Recording of conversation content, facial expressions, and emotional data

[0309] Output: Recorded virtual matchmaking data

[0310] Step 6: Evaluate speech and facial expressions

[0311] The server analyzes the content of the conversation during the virtual matchmaking session, as well as the user's facial expressions and emotional data, and calculates a comprehensive evaluation score. For example, the evaluation criteria include conversational ability, quality of questions, reaction to the other person, level of facial relaxation, and frequency of smiling. The evaluation results are sent from the server to the user's device and displayed to them.

[0312] Input: Recorded virtual matchmaking data (conversation content, facial expressions, emotional data)

[0313] Data calculation: Calculation of overall evaluation score based on evaluation criteria

[0314] Output: Overall evaluation score and breakdown of evaluation results

[0315] Step 7: Reinforcing feedback

[0316] The server then provides more specific and effective feedback based on the results of the emotion engine. For example, it offers suggestions for improvement such as "If you feel nervous, take a deep breath and relax" or "Introduce yourself calmly and with positive emotions." This feedback is sent from the server to the device and displayed to the user.

[0317] Input: Overall evaluation score and emotion recognition results

[0318] Data processing: Generating feedback based on emotion recognition results

[0319] Output: Specific improvements added

[0320] Step 8: Create your own avatar

[0321] The server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state based on the user's behavioral and emotional data accumulated through virtual matchmaking. The user can use this avatar to evaluate themselves from a third-person perspective and observe simulated conversations between avatars.

[0322] Input: Accumulated behavioral and emotional data

[0323] Data Computing: Avatar Generation Based on Behavioral Characteristics and Emotional States

[0324] Output: Generated self-avatar and simulated conversation data

[0325] (Application example 2)

[0326] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0327] Conventional matchmaking support systems have difficulty not only objectively evaluating a user's matchmaking ability and providing specific improvement measures, but also analyzing their emotional state and providing real-time feedback. Furthermore, they lacked technology for generating avatars based on the user's behavioral patterns and for incorporating the results of emotional analysis during virtual matchmaking into feedback. This meant that users were unable to obtain specific guidelines for self-improvement, preventing them from effectively progressing with their matchmaking efforts.

[0328] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a user to input their own information, a means for analyzing the input information and determining their marriage ability, a means for providing feedback based on the determined marriage ability, a means for conducting a virtual matchmaking session, a means for evaluating the conversation and facial expressions during the virtual matchmaking session, a means for generating initial comments using a generative AI model, a means for analyzing the user's emotional state, a means for providing additional feedback based on the analyzed emotional state, a means for generating an avatar based on the user's behavioral patterns, and a means for displaying conversations between avatars. This not only allows users to objectively evaluate their marriage ability, but also allows them to receive real-time feedback and improvement measures based on the emotion analysis results. Furthermore, the avatar reflecting their own behavioral patterns provides specific guidelines for self-improvement, which can lead to more effective progress in their marriage search.

[0329] "User information" refers to basic information that users enter into the system, including data such as annual income, appearance, hobbies, and romantic history.

[0330] "Marriage power" is an index that evaluates the effectiveness and likelihood of success of a user's marriage search, analyzed based on user information.

[0331] "Feedback" refers to specific improvement measures and advice provided to users based on their analyzed marriage vitality and emotional state.

[0332] "Virtual matchmaking" refers to simulated interactions that users have with generative AI models and other users within the system.

[0333] "Generative AI model" refers to technology that uses artificial intelligence to generate initial utterances and simulate interactions with users.

[0334] "Emotion analysis" refers to technology that recognizes and analyzes a user's emotional state in real time from their facial expressions and voice.

[0335] An "avatar" is a virtual character that is generated based on the user's behavioral patterns and emotional state.

[0336] "Conversation evaluation" refers to a technology that evaluates the content of conversations and facial expressions of users during virtual matchmaking sessions, and provides indicators that are useful for improving their chances of finding a partner.

[0337] A "prompt sentence" refers to the initial utterance or input for a generative AI model to simulate a dialogue with a user.

[0338] "Additional feedback" refers to additional improvements or advice provided to users in real time based on sentiment analysis results and conversation evaluation.

[0339] A system for implementing the present invention uses the following hardware and software.

[0340] Hardware used

[0341] PC or smartphone

[0342] (Optional) Smart glasses, head-mounted display

[0343] Software used

[0344] Python

[0345] Libraries for AI algorithms (e.g., EmotionEngine, MatchmakingEngine)

[0346] Natural language explanation of program processing

[0347] The system begins with the user entering basic information such as annual income, appearance (specifically, height and weight), hobbies, and romantic history via smartphone or computer, which is then sent to a server. The server receives this data and uses an AI algorithm (Matchmaking Engine) to determine a person's potential for marriage.

[0348] The determined marriage ability is notified to the user as a score for each item and an overall score. Next, a feedback system extracts the user's strengths and weaknesses and suggests specific improvement measures. This feedback is displayed on the screen of a smartphone or computer.

[0349] The user sets up a virtual matchmaking session, and the generative AI model makes the first statement. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?"

[0350] When the user responds, the response is analyzed by an emotion analysis engine (Emotion Engine), and the user's emotional state is recognized in real time. For example, if the user responds, "I like soccer and play futsal with friends on the weekends," emotion analysis is performed based on the response. The analysis results are sent to the server and provided to the user as additional feedback. This feedback may include advice such as, "If you feel tense, take a deep breath and try to relax."

[0351] In addition, an avatar is generated based on the user's behavioral patterns, and conversations between these avatars are displayed to the user, providing specific guidelines for self-improvement. During this process, the server stores a series of data, allowing users to repeat the simulation multiple times.

[0352] Examples of concrete examples and prompts

[0353] A specific example would be a simulation in which a user inputs information such as "annual income of 6 million yen" and "hobbies: soccer and cooking," and the generative AI model asks, "Nice to meet you. What are your hobbies?"

[0354] Example prompt sentence:

[0355] "Calculate a marriageability score based on the user's profile information, and use an emotion engine to analyze their emotional state and provide feedback during virtual matchmaking."

[0356] In this way, the present invention provides a system that evaluates a user's marriage ability and provides feedback and specific improvement measures based on emotion analysis.

[0357] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0358] Step 1: Enter your user information

[0359] Users enter their basic information (annual income, appearance, hobbies, dating history, etc.) via their device (PC or smartphone). This information is sent from the device to the server. Input is done in form format, and is completed by filling in the required fields. The entered data is sent to the server in JSON format and saved in a database.

[0360] Step 2: Determine your marriage potential

[0361] The server analyzes the received user information using an AI algorithm (Matchmaking Engine). Specifically, each item, such as annual income, appearance, and hobbies, is scored separately, and the scores are added together to calculate an overall matchmaking score. For example, an annual income of 6 million yen would be a high score, and a diverse range of hobbies would be a higher rating. The analysis results in scores for each item and an overall score, which are then sent back to the device and displayed to the user.

[0362] Step 3: Provide feedback

[0363] The server extracts the user's strengths and weaknesses based on the determined matchmaking power score. For example, the analysis may reveal that the user has a high annual income but a narrow range of hobbies. Based on this information, the server generates specific improvement measures (e.g., "take a more professional profile picture" or "add detailed stories about your hobbies") and sends them to the device as feedback. The user can use this as a guide for self-improvement.

[0364] Step 4: Conduct a virtual matchmaking session

[0365] The user sets up a virtual matchmaking session on their device. The generative AI model makes an initial statement, and the user responds. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?", and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." This is how the virtual matchmaking session progresses, and the statements and responses are recorded.

[0366] Step 5: Analyze emotional state

[0367] The server uses an emotion analysis tool (Emotion Engine) to analyze the user's comments and facial expressions in real time during the virtual matchmaking session. This recognizes the user's emotional state from the tone of voice and facial expressions when they speak, and obtains the analysis results. For example, it can identify emotions such as tension or relaxation. This data is sent to the server, and the analysis results are returned to the device.

[0368] Step 6: Provide additional feedback

[0369] The server generates more specific feedback based on the results of the emotion analysis, such as advice like, "If you feel tense, take a deep breath and try to relax." This feedback is sent to the device and displayed to the user in real time.

[0370] Step 7: Generate and display the avatar

[0371] The server generates a "self-avatar" based on the user's behavioral patterns and emotional state. Conversations between the generated avatars are simulated and displayed on the device. By observing the avatars' interactions, users can obtain specific guidelines for self-improvement.

[0372] Through these steps, users can receive an assessment of their own matchmaking ability, obtain recommendations for improvement, and experience a virtual matchmaking experience. By combining generative AI models with sentiment analysis methods, it is possible to provide users with more accurate feedback and improve their chances of success in matchmaking.

[0373] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0374] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0375] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0376] [Second embodiment]

[0377] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0378] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0379] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0380] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0381] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0382] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0383] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0384] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0385] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0386] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0387] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0388] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0389] The system of the present invention aims to enable users to evaluate their matchmaking ability and obtain improvement measures. This system provides specific feedback by having users input their own information and participate in a virtual matchmaking session.

[0390] Entering user information

[0391] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, love history, etc.). For example, they enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal.

[0392] Analysis of marriage potential

[0393] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[0394] Providing feedback

[0395] The server analyzes the user's strengths and weaknesses based on the determined marriage vitality score. The results are provided as feedback, including specific improvements. For example, suggestions may be made such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and displayed to the user.

[0396] Virtual matchmaking

[0397] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on weekends." All conversations in this virtual matchmaking session are recorded by the server.

[0398] Conversation and facial expression evaluation

[0399] The server analyzes the content of conversations and the user's facial expressions during the virtual matchmaking session in real time. Evaluations are made on a wide range of topics, including conversational ability, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. The analysis results are compiled on the server as an evaluation score, and specific areas for improvement are provided to the user along with the evaluation. Advice such as "be more relaxed and smile more" and "ask more questions to the other person" are included.

[0400] Create your own avatar

[0401] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "personal avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0402] This system allows users to receive objective and detailed feedback, enabling them to implement specific improvements to their search for a partner.

[0403] The processing flow will be explained below.

[0404] Step 1:

[0405] A user accesses the system and logs in by entering the required information on the login screen.

[0406] Step 2:

[0407] The device checks the user's information and displays the home screen. The user then moves to the profile setting screen and enters the necessary information (annual income, appearance, hobbies, romantic history, etc.).

[0408] Step 3:

[0409] The terminal sends the entered user information to the server, where it is stored in a database.

[0410] Step 4:

[0411] Based on the information received by the server, an AI algorithm is used to calculate a score for each element, such as annual income, appearance, hobbies, and profile text, and these are then combined to calculate an overall matchmaking ability score.

[0412] Step 5:

[0413] The server generates the calculated score and detailed feedback information. For example, if a user's annual income is highly rated but their profile text is weak, the server will suggest specific ways to improve the profile.

[0414] Step 6:

[0415] The server sends the generated feedback and score information to the device, which displays it to the user.

[0416] Step 7:

[0417] Next, the user selects a virtual matchmaking session and sets up the virtual matchmaking session. The server then starts the virtual matchmaking generation AI and generates a dialogue scenario.

[0418] Step 8:

[0419] The generative AI starts the virtual matchmaking session and makes an initial statement (e.g., "Nice to meet you. What are your hobbies?"), to which the user responds (e.g., "I like soccer and play futsal with my friends on weekends").

[0420] Step 9:

[0421] The server records the conversations and the user's facial expressions in real time, and the data is then prepared for analysis by AI.

[0422] Step 10:

[0423] The server analyzes conversation data and facial expression data to evaluate the quality of speech, the level of facial relaxation, the frequency of smiling, etc. The evaluation results are compiled as a score.

[0424] Step 11:

[0425] The server generates an evaluation score and specific feedback (e.g., "Ask people more questions more often" or "Smile more and keep a relaxed expression").

[0426] Step 12:

[0427] The server sends the evaluation score and feedback to the device, which displays it to the user.

[0428] Step 13:

[0429] Users participate in multiple virtual matchmaking sessions, and the data is stored on a server. The server then aggregates this data and generates a "personal avatar" based on the user's behavioral patterns and characteristics.

[0430] Step 14:

[0431] The server generates a conversation scenario between the generated "self avatars" and sends it to the device, which then displays it to the user.

[0432] Step 15:

[0433] Users observe conversations between avatars and self-evaluate from a third-party perspective to determine areas for improvement. Based on the information gained through this process, users can improve their behavior in actual matchmaking.

[0434] Example 1

[0435] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0436] Conventional matchmaking support systems have difficulty objectively evaluating users' matchmaking skills and providing specific improvement measures. Furthermore, it is often difficult to identify areas for improvement through self-evaluation alone, and virtual matchmaking sessions and feedback provision are insufficient. Furthermore, there is a lack of appropriate means for users to objectively understand their own behavior and conversations. This has led to issues such as users being unable to effectively improve their matchmaking skills, resulting in a lower success rate in matchmaking.

[0437] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0438] In this invention, the server includes means for a user to input his / her own information, means for analyzing and determining a marriage ability based on the input information, means for providing feedback based on the determined marriage ability score, means for conducting a virtual dialogue, means for evaluating the conversation and facial expressions during the virtual dialogue, means for generating an avatar based on the user's behavioral characteristics, and means for displaying a dialogue between the avatars. This allows a user to objectively evaluate his / her own marriage ability, understand specific areas for improvement, and effectively improve his / her actual marriage ability skills.

[0439] The "user information input means" is an interface that allows a user to provide their own individual information to the system.

[0440] "Marriage potential analysis tools" is a general term for AI algorithms and software that evaluate marriage potential based on provided user information.

[0441] The "feedback provision means" is the part of the system that has the function of presenting specific areas for improvement and strengths to users based on the analyzed marriage vitality score.

[0442] A "means for implementing virtual interaction" is software or an interface that allows a user to virtually interact within a system.

[0443] The "conversation and facial expression evaluation means" is a system function that analyzes the content of the user's conversation and facial expressions during virtual conversation in real time and evaluates the results.

[0444] "Avatar generation means" is a system function for creating an avatar, which is a virtual self-representation, based on the user's behavioral characteristics.

[0445] The "avatar dialogue display means" is an interface for displaying to the user a simulated conversation in which the generated avatars converse with each other.

[0446] The "behavior and speech recording means" is a part of the system for recording the actions and speeches made by the user during the virtual interaction and storing the data.

[0447] The "strengths and weaknesses extraction means" is a system function that extracts the strengths and weaknesses from the information input by the user and generates specific improvement measures based on that information.

[0448] The main purpose of the system of the present invention is to enable users to evaluate their marriage vitality and obtain improvement measures. The components of this system include a user information input means, a marriage vitality analysis means, a feedback providing means, a virtual dialogue implementation means, a conversation and facial expression evaluation means, an avatar generation means, and an avatar dialogue display means.

[0449] Entering user information

[0450] Users log in to the system and enter information such as annual income, appearance (height, weight, photo of face, etc.), hobbies, and romantic history into a dedicated input form. For example, they enter information such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking," and this information is sent to the server via their terminal.

[0451] Analysis of marriage potential

[0452] The server receives the information sent by the user and uses an AI algorithm to evaluate their matchmaking ability. Specifically, factors such as annual income, appearance (height and weight), and variety of hobbies are evaluated using a scoring system to calculate an overall matchmaking ability score. For example, if the annual income is 6 million yen, the score would be 8 / 10, appearance 7 / 10, hobbies 8 / 10, and profile text 6 / 10. This evaluation result, along with a detailed breakdown, is sent back to the device and displayed to the user.

[0453] Providing feedback

[0454] The server analyzes the user's strengths and weaknesses based on the evaluation results and generates feedback including specific suggestions for improvement, such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and presented to the user.

[0455] Conducting virtual conversations

[0456] The user sets up a virtual conversation on the system. The generative AI model makes the initial utterance, and the virtual conversation is simulated. For example, the generative AI model asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The contents of the virtual conversation are all recorded on the server.

[0457] Conversation and facial expression evaluation

[0458] The server analyzes the content of the conversation and the user's facial expressions during the virtual conversation in real time. Analyzed elements include conversational skills, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. For example, while understanding the context of the conversation, it evaluates whether the questions asked to the other person are appropriate and whether the user is relaxed. The analysis results are generated as an evaluation score, and specific feedback is provided, such as "be more relaxed and smile more" or "ask more questions to the other person." This evaluation score and feedback are sent to the device and displayed to the user.

[0459] Create your own avatar

[0460] The server generates an avatar that reflects the user's behavioral characteristics based on behavioral data collected from multiple virtual conversations. Users can use this avatar to evaluate themselves from a third-person perspective. A simulated conversation between the generated avatars is displayed on the device, and by observing the interaction, users can more objectively understand areas for improvement.

[0461] By integrating the above processes, users can objectively evaluate their marriage potential, understand specific improvement measures, and actually improve their conversation skills.

[0462] Example prompt sentence:

[0463] User: Nice to meet you. What hobbies should I have?

[0464] Generative AI: Nice to meet you. If you have a variety of hobbies, it's easier to have a lively conversation and make a good impression on others. Can you tell me more about your hobbies?

[0465] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0466] Step 1: Enter your user information

[0467] Users log in to the system and enter information such as annual income, appearance (height, weight, photo of face, etc.), hobbies, and romantic history into a dedicated input form. This information is sent to the server via the terminal. Input includes specific data such as "annual income of 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking." Once this data reaches the server, it is saved in a database.

[0468] Step 2: Analysis of your marriage potential

[0469] The server uses an AI algorithm to evaluate a user's matchmaking ability based on the information sent by the user. Specifically, it uses a scoring system to evaluate factors such as annual income, appearance (height and weight), and the variety of hobbies, and calculates an overall matchmaking ability score. For an annual income of 6 million yen, the server generates an evaluation result such as 8 / 10 for appearance, 7 / 10 for hobbies, 8 / 10 for hobbies, and 6 / 10 for the profile text. This evaluation result is sent back to the device and displayed to the user.

[0470] Step 3: Provide feedback

[0471] The server analyzes the user's strengths and weaknesses based on the evaluation results and generates feedback including specific recommendations for improvement. Examples of such feedback include "take a more professional profile picture" and "add detailed stories about your hobbies." This feedback is sent to the device and presented to the user. When providing feedback, the server uses a generative AI model to make more specific and personalized suggestions.

[0472] Step 4: Conducting a virtual interaction

[0473] The user sets up a virtual dialogue on the system, and the generative AI model makes the initial utterance to simulate the virtual dialogue. For example, the generative AI asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The content of this dialogue is recorded on the server. The input includes the user's answer, and the output includes the generative AI model's next question.

[0474] Step 5: Evaluate speech and facial expressions

[0475] The server analyzes the content of the conversation and the user's facial expressions during the virtual conversation in real time. Analyzed elements include conversational skills, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. For example, it understands the context of the conversation and evaluates whether the questions asked to the other person are appropriate and the level of relaxation. The analysis results are generated as an evaluation score, and specific feedback such as "be more relaxed and smile more" or "ask more questions to the other person" is provided. The evaluation score and feedback are sent to the device and displayed to the user.

[0476] Step 6: Create your own avatar

[0477] The server generates an avatar that reflects the user's behavioral characteristics based on behavioral data collected from multiple virtual conversations. Users can use this avatar to evaluate themselves from a third-party perspective. A simulated conversation between the generated avatars is displayed on the device, and by observing the interaction, users can more objectively understand areas for improvement. For example, the content of the avatar's conversation and behavioral patterns can be displayed, and by observing them, specific improvement measures can be obtained.

[0478] (Application example 1)

[0479] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0480] In conventional matchmaking support systems, users were limited to online environments in terms of the means by which they could receive feedback to evaluate and improve their matchmaking abilities, resulting in insufficient real-time support at physical stores. Additionally, virtual matchmaking experiences were only available online, resulting in a lack of feedback through physical store experiences.

[0481] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0482] In this invention, the server includes means for a user to input his / her own information, means for analyzing the input information and determining the marriage activity power, means for providing feedback based on the determined marriage activity power, means for conducting a virtual matchmaking meeting, means for evaluating the conversation and facial expressions during the virtual matchmaking meeting, means for generating an avatar based on the user's behavioral patterns, means for displaying conversations between the avatars, and means for providing real-time feedback to the user at a physical store. This enables the user to receive an evaluation of their marriage activity power and specific feedback in real time even at a physical store.

[0483] A "user" is an individual who accesses the system, enters their information, and receives a matchmaking ability rating and feedback.

[0484] The "means of inputting information" refers to the interface that allows users to input their basic information (annual income, appearance, hobbies, romantic history, etc.) into the system.

[0485] "Means of analyzing information and determining marriage potential" refers to the process of evaluating marriage potential using AI algorithms and other methods based on collected user information.

[0486] The "means of providing feedback" is a function that suggests strengths, weaknesses, and specific improvement measures to users based on their assessed matchmaking ability.

[0487] The "means for conducting a virtual matchmaking session" is a function that allows a user to simulate a matchmaking session in a virtual environment and record the results.

[0488] "Means for evaluating conversations and facial expressions" refers to the process of analyzing and evaluating the user's statements and facial expressions during virtual matchmaking.

[0489] "Means for generating avatars based on behavioral patterns" refers to a function that creates an avatar that mimics a user based on the user's behavioral data collected from multiple virtual matchmaking sessions.

[0490] "Means for displaying conversations between avatars" is a function that allows the user to visually see the generated avatars conversing with each other.

[0491] "Means for providing real-time feedback in physical stores" refers to a function that allows users to receive an on-the-spot evaluation of their matchmaking abilities at physical stores such as matchmaking cafes, and provides specific feedback in real time.

[0492] The system of the present invention aims to enable users to evaluate their matchmaking ability and obtain improvement measures. This system provides specific feedback by having users input their own information and participate in a virtual matchmaking session.

[0493] Entering user information

[0494] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, love history, etc.). For example, they enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal.

[0495] Analysis of marriage potential

[0496] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[0497] Providing feedback

[0498] The server analyzes the user's strengths and weaknesses based on the determined matchmaking power score. The results are provided as feedback, including specific improvements. For example, suggestions include "take a more professional profile picture" and "add detailed stories about your hobbies." This feedback is sent to the user's device and displayed.

[0499] Virtual matchmaking

[0500] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on the weekends." All conversations in this virtual matchmaking session are recorded by the server.

[0501] Conversation and facial expression evaluation

[0502] The server analyzes the content of conversations and the user's facial expressions during the virtual matchmaking session in real time. Evaluations are made on a wide range of topics, including conversational ability, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. The analysis results are compiled on the server as an evaluation score, and specific areas for improvement are provided to the user along with the evaluation. Advice such as "be more relaxed and smile more" and "ask more questions to the other person" are included.

[0503] Create your own avatar

[0504] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0505] Providing feedback in-store

[0506] This system can also be used in brick-and-mortar stores, such as matchmaking cafes. Users can enter their information using a tablet or smartphone in the store and conduct a virtual matchmaking session. They can then receive real-time feedback from the server. This makes it possible to evaluate a person's matchmaking ability and provide specific improvement measures even in brick-and-mortar stores.

[0507] Examples of concrete examples and prompts

[0508] A concrete example would be a system in which users can use a tablet at a matchmaking cafe to input their personal information, experience a virtual matchmaking session on the spot, and have AI provide feedback in real time. Users can then receive specific advice based on their scores.

[0509] Examples of prompts include:

[0510] User Information:

[0511] Annual income: 6 million yen

[0512] Appearance: Height 175cm, Weight 70kg

[0513] Hobbies: Soccer, cooking

[0514] Romance history: 3 relationships

[0515] Rate this user's marriage ability and provide feedback such as:

[0516] Strengths

[0517] Weakness

[0518] Improvement points

[0519] Also, provide examples of initial statements from virtual matchmaking.

[0520] This will clarify the specific steps for implementing the invention and its effects.

[0521] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0522] Step 1: Enter your user information

[0523] Users access the system via their terminal and enter their basic information (annual income, appearance, hobbies, romantic history, etc.) into a form. This input includes specific data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer, cooking." This information is sent from the terminal to the server. The input data is sent in JSON format and analyzed on the server side.

[0524] Step 2: Analysis of your marriage potential

[0525] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. This analysis scores annual income, appearance, and hobby diversity. For example, an annual income of 6 million yen would be considered high, with a score of 8 / 10, appearance 7 / 10, and hobby diversity 8 / 10. The server combines these ratings to calculate a marriage potential score and returns the result in JSON format to the device. The score returned from the server is displayed on the user's device.

[0526] Step 3: Provide feedback

[0527] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates specific feedback. For example, it suggests improvements such as "take a professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the user's device and displayed to them.

[0528] Step 4: Conduct a virtual matchmaking session

[0529] The user sets up a virtual matchmaking session through their device. The generative AI model running on the server makes the first statement, simulating the virtual matchmaking. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?" and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." All of this conversation is recorded by the server.

[0530] Step 5: Evaluate speech and facial expressions

[0531] The server analyzes the content of the conversation and the user's facial expressions during the virtual matchmaking session in real time. It evaluates conversational ability, the quality of questions, reactions to the other person, the level of facial relaxation, and the frequency of smiling, and compiles the analysis results as an evaluation score. Specific improvements are generated along with these results, and advice such as "be more relaxed and smile more" or "ask more questions to the other person" is provided to the user.

[0532] Step 6: Create your own avatar

[0533] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0534] Step 7: Providing real-time feedback in-store

[0535] In a physical store, such as a matchmaking cafe, users can access the system using a tablet or smartphone to enter the information described above, conduct a virtual matchmaking session, and receive feedback in real time. The server processes the input data from the physical store, instantly generates feedback, and sends it back to the device, allowing users to receive specific advice on the spot.

[0536] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0537] The system of the present invention aims to evaluate the user's matchmaking ability and provide more accurate feedback and improvement measures using an emotion engine. The system provides specific feedback and advice based on emotion recognition by having the user input their own information and participate in a virtual matchmaking session.

[0538] Entering user information

[0539] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, romantic history, etc.). For example, they might enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal and stored in the database.

[0540] Analysis of marriage potential

[0541] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[0542] Providing feedback

[0543] The server analyzes the user's strengths and weaknesses based on the determined marriage vitality score. The results are provided as feedback, including specific improvements. For example, suggestions may be made such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and displayed to the user.

[0544] Emotion recognition by emotion engine

[0545] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice during the virtual matchmaking session to recognize their emotions. For example, if the user is nervous, the emotion engine will recognize this from their facial expressions and tone of voice and provide an analysis result. This data is sent to the server in real time.

[0546] Virtual matchmaking

[0547] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on the weekends." The content of the virtual matchmaking session, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[0548] Conversation and facial expression evaluation

[0549] The server analyzes the content of conversations during virtual matchmaking, as well as the user's facial expressions and emotional data in real time. The evaluation takes into account conversational ability, quality of questions, reactions to the other person, facial relaxation and frequency of smiling, as well as the results of emotion recognition by the emotion engine. The analysis results are compiled as an evaluation score.

[0550] Enhanced feedback

[0551] The server uses the results of the emotion engine to provide additional feedback according to the user's emotional state. For example, it provides specific improvement suggestions such as "If you feel nervous, take a deep breath and try to relax" or "Introduce yourself calmly and with positive emotions." This feedback is sent to the device and displayed to the user.

[0552] Create your own avatar

[0553] The user's behavioral and emotional data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state. Using this avatar, the user can evaluate themselves from a third-person perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0554] This system allows users to receive objective and detailed feedback, and improve their chances of finding a partner based on highly accurate advice provided by the emotion engine.

[0555] The processing flow will be explained below.

[0556] Step 1:

[0557] A user accesses the system and logs in by entering the required information on the login screen.

[0558] Step 2:

[0559] The device checks the user's information and displays the home screen. The user then moves to the profile setting screen and enters the necessary information (annual income, appearance, hobbies, romantic history, etc.).

[0560] Step 3:

[0561] The terminal sends the entered user information to the server, where it is stored in a database.

[0562] Step 4:

[0563] Based on the information received by the server, an AI algorithm is used to calculate a score for each element, such as annual income, appearance, hobbies, and profile text, and these are then combined to calculate an overall matchmaking ability score.

[0564] Step 5:

[0565] The server generates the calculated score and detailed feedback information. For example, if a user's annual income is highly rated but their profile text is weak, the server will suggest specific ways to improve the profile.

[0566] Step 6:

[0567] The server sends the generated feedback and score information to the terminal, which displays it to the user.

[0568] Step 7:

[0569] Next, the user selects a virtual matchmaking session and sets up the virtual matchmaking session. The server then starts the virtual matchmaking generation AI and generates a dialogue scenario.

[0570] Step 8:

[0571] The generative AI starts the virtual matchmaking session and makes an initial statement (e.g., "Nice to meet you. What are your hobbies?"), to which the user responds (e.g., "I like soccer and play futsal with my friends on weekends").

[0572] Step 9:

[0573] The server records the conversation content during the virtual matchmaking session, as well as the user's facial expressions and voice in real time, and each piece of data is prepared for analysis by the emotion engine.

[0574] Step 10:

[0575] The emotion engine analyzes the user's facial expressions and voice to generate emotion data, for example, to determine whether the user is nervous.

[0576] Step 11:

[0577] The server analyzes the emotional data and conversation data, evaluating the quality of speech, the level of facial relaxation, the frequency of smiling, etc. The evaluation results are compiled as a score.

[0578] Step 12:

[0579] The server generates an evaluation score and specific feedback (e.g., "Ask people more questions more often" or "Smile more and keep a relaxed expression").

[0580] Step 13:

[0581] The server sends the evaluation score and feedback to the device, which displays it to the user.

[0582] Step 14:

[0583] Users participate in multiple virtual matchmaking sessions, and the data is stored on a server. The server then aggregates this data and generates a "personal avatar" based on the user's behavioral patterns and emotional data.

[0584] Step 15:

[0585] The server generates a conversation scenario between the generated "self avatars" and sends it to the device, which then displays it to the user.

[0586] Step 16:

[0587] Users observe conversations between avatars and evaluate themselves from a third-party perspective to determine areas for improvement. Based on the information gained through this process, users can improve their behavior in actual matchmaking.

[0588] Example 2

[0589] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0590] Conventional matchmaking systems only require users to enter basic information, limiting the amount of feedback they can provide. They also lack the means for self-evaluation through detailed analysis via emotion recognition or virtual matchmaking, or avatar generation. This makes it difficult for users to receive more accurate feedback and specific improvement measures.

[0591] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0592] In this invention, the server includes means for a user to input his / her own information, means for analyzing the input information and determining the marriage activity potential, means for providing feedback based on the determined marriage activity potential, means for analyzing the facial expressions and voice of the user during the virtual matchmaking using an emotion engine and recognizing emotions, means for conducting the virtual matchmaking, means for evaluating the conversation and facial expressions during the virtual matchmaking, means for enhancing the feedback based on the evaluation results, means for generating an avatar based on the user's behavioral patterns, and means for displaying the conversation between the avatars. This allows the user to receive detailed and objective feedback and obtain specific measures for self-improvement through emotion recognition and virtual matchmaking.

[0593] "User" means an individual who accesses the system, enters their information, and receives feedback.

[0594] "Information input" refers to the act of a user providing basic information about themselves (annual income, appearance, hobbies, romantic history, etc.) to the system.

[0595] "Analysis" refers to the means of evaluating the entered user information and determining their potential for marriage.

[0596] "Marriage Ability" is a comprehensive evaluation score of a user's marriage activities, calculated based on attributes such as annual income, appearance, hobbies, and profile text.

[0597] "Feedback" refers to information that points out a user's strengths and weaknesses based on analysis results and provides specific measures for improvement.

[0598] The "emotion engine" is a technology that analyzes the user's facial expressions and voice during a virtual matchmaking session and recognizes their emotions in real time.

[0599] "Virtual matchmaking" is a feature in which a generative AI model makes the first statement and simulates a matchmaking session, which progresses through interaction with the user.

[0600] A "generative AI model" is an artificial intelligence that generates conversations with users during virtual matchmaking and feedback sessions.

[0601] "Conversation and facial expression evaluation" is a method of analyzing the content of a user's remarks and facial expression data during a virtual matchmaking session and calculating an overall evaluation score.

[0602] "Enhanced feedback" refers to a means of providing more specific feedback that has a greater effect on improvement, based on evaluation results and emotional recognition.

[0603] An "avatar" is a virtual self-image generated based on the user's behavioral patterns and emotional data, allowing for self-evaluation from a third-party perspective.

[0604] "Avatar-to-avatar conversation" is a feature that displays multiple avatars having a simulated conversation using a generative AI model.

[0605] The matchmaking support system of the present invention allows users to input their own information, evaluate their matchmaking ability through virtual matchmaking, and provides highly accurate feedback and improvement measures using an emotion engine. This system includes a terminal for users to input information, a server for analyzing the information and evaluating matchmaking ability, and various software for providing feedback.

[0606] Hardware and software used

[0607] This system uses the following hardware and software:

[0608] Device: An electronic device (computer, smartphone, tablet, etc.) where users input information and view feedback and results.

[0609] Server: A computer that manages user information, analyzes it, and generates feedback.

[0610] Emotion engine: Dedicated software for analyzing the user's facial expressions and voice in real time (e.g., Emotion API)

[0611] Generative AI models: artificial intelligence platforms (e.g., GPT-3) for simulating virtual matchmaking conversations

[0612] Specific examples of processing

[0613] Input and analysis of user information

[0614] The user uses the device to input their basic information (annual income, appearance, hobbies, love history, etc.). For example, they input information such as "annual income of 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking." The device sends this information to the server, which stores it in a database.

[0615] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is rated high, while a height of 175 cm and a weight of 70 kg is rated medium. The server evaluates this information based on a scoring system and calculates an overall marriage potential score. This score is sent back to the device and displayed to the user.

[0616] Providing feedback

[0617] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates appropriate feedback, such as suggestions like "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent from the server to the user's device and displayed.

[0618] Emotion recognition by emotion engine

[0619] Once the virtual matchmaking session begins, the server's built-in emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotions. For example, if the user is nervous, the emotion engine will detect this from their facial expressions and tone of voice and send that data to the server.

[0620] Virtual matchmaking

[0621] When a user sets up a virtual matchmaking session, the generative AI model makes the first statement and simulates the matchmaking. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?", and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." The content of this conversation, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[0622] Enhanced speech and facial expression assessment and feedback

[0623] The server analyzes the conversation content during the virtual matchmaking session, as well as the user's facial expressions and emotional data, to calculate an overall evaluation score. It also strengthens feedback based on the results of the emotion engine, providing specific improvement measures such as "If you feel nervous, take a deep breath and relax" and "Introduce yourself calmly with positive emotions." This feedback is sent to the device and displayed to the user.

[0624] Create your own avatar

[0625] The server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state based on the user's behavioral and emotional data accumulated through virtual matchmaking. The user can use this avatar to evaluate themselves from a third-person perspective and observe simulated conversations between avatars.

[0626] Prompt Sentence Examples

[0627] Please rate your marriage strength based on the user information below and provide specific feedback and suggestions for improvement.

[0628] User Information:

[0629] Annual income: 6 million yen

[0630] Appearance: Height 175cm, Weight 70kg, Photo (URL)

[0631] Hobbies: Soccer, cooking

[0632] Romance history: 3 times

[0633] Matchmaking Settings:

[0634] First utterance from the generated AI: "Nice to meet you. What are your hobbies?"

[0635] User response:

[0636] "I like soccer and play futsal with my friends on the weekends."

[0637] The system of the present invention provides detailed and objective feedback to users throughout these processes and suggests specific strategies for self-improvement through emotion recognition and virtual matchmaking.

[0638] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0639] Step 1: Enter your user information

[0640] Users access the system through their terminal and enter their basic information (annual income, appearance, hobbies, love history, etc.). For example, they might enter data such as "annual income of 6 million yen," "appearance: photo of height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into a form. This input information is sent from the terminal to the server, which then stores it in a database.

[0641] Input: User information such as annual income, appearance, hobbies, and romantic history

[0642] Data processing: Save the input information as structured data

[0643] Output: Saved user information

[0644] Step 2: Analysis of your marriage potential

[0645] The server retrieves user information stored in a database and uses an AI algorithm to determine a person's marriage potential. For example, an annual income of 6 million yen is rated high, while a height of 175 cm is rated neutral. The server calculates a score for each attribute and generates an overall marriage potential score. This score is sent back to the device and displayed to the user.

[0646] Input: User information stored in the database

[0647] Data calculation: Scoring each attribute using AI algorithms

[0648] Output: Overall marriage vitality score and its breakdown

[0649] Step 3: Provide feedback

[0650] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates specific feedback, such as suggestions like "take a more professional profile picture" or "add more detailed stories about your hobbies." This feedback is sent from the server to the user's device and displayed.

[0651] Input: Marital vitality score and its breakdown

[0652] Data processing: feedback generation based on scores

[0653] Output: Analysis of strengths and weaknesses and specific feedback

[0654] Step 4: Emotion Recognition with the Emotion Engine

[0655] During the virtual matchmaking session, the server's built-in emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotions. For example, if the user is nervous, the emotion engine will detect this from their facial expressions and tone of voice, and the data will be sent to the server in real time.

[0656] Input: facial expression data and voice data of the user during the virtual matchmaking session

[0657] Data Computation: Real-time Emotion Analysis with an Emotion Engine

[0658] Output: Emotion recognition result

[0659] Step 5: Conduct a virtual matchmaking session

[0660] The user sets up a virtual matchmaking session, and the generative AI model makes the first utterance, simulating the matchmaking. For example, the generative AI asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The content of this conversation, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[0661] Input: The initial utterance of the generative AI model, and the user's response

[0662] Data processing: Recording of conversation content, facial expressions, and emotional data

[0663] Output: Recorded virtual matchmaking data

[0664] Step 6: Evaluate speech and facial expressions

[0665] The server analyzes the content of the conversation during the virtual matchmaking session, as well as the user's facial expressions and emotional data, and calculates a comprehensive evaluation score. For example, the evaluation criteria include conversational ability, quality of questions, reaction to the other person, level of facial relaxation, and frequency of smiling. The evaluation results are sent from the server to the user's device and displayed to them.

[0666] Input: Recorded virtual matchmaking data (conversation content, facial expressions, emotional data)

[0667] Data calculation: Calculation of overall evaluation score based on evaluation criteria

[0668] Output: Overall evaluation score and breakdown of evaluation results

[0669] Step 7: Reinforcing feedback

[0670] The server then provides more specific and effective feedback based on the results of the emotion engine. For example, it offers suggestions for improvement such as "If you feel nervous, take a deep breath and relax" or "Introduce yourself calmly and with positive emotions." This feedback is sent from the server to the device and displayed to the user.

[0671] Input: Overall evaluation score and emotion recognition results

[0672] Data processing: Generating feedback based on emotion recognition results

[0673] Output: Specific improvements added

[0674] Step 8: Create your own avatar

[0675] The server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state based on the user's behavioral and emotional data accumulated through virtual matchmaking. The user can use this avatar to evaluate themselves from a third-person perspective and observe simulated conversations between avatars.

[0676] Input: Accumulated behavioral and emotional data

[0677] Data Computing: Avatar Generation Based on Behavioral Characteristics and Emotional States

[0678] Output: Generated self-avatar and simulated conversation data

[0679] (Application example 2)

[0680] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0681] Conventional matchmaking support systems have difficulty not only objectively evaluating a user's matchmaking ability and providing specific improvement measures, but also analyzing their emotional state and providing real-time feedback. Furthermore, they lacked technology for generating avatars based on the user's behavioral patterns and for incorporating the results of emotional analysis during virtual matchmaking into feedback. This meant that users were unable to obtain specific guidelines for self-improvement, preventing them from effectively progressing with their matchmaking efforts.

[0682] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a user to input their own information, a means for analyzing the input information and determining their marriage ability, a means for providing feedback based on the determined marriage ability, a means for conducting a virtual matchmaking session, a means for evaluating the conversation and facial expressions during the virtual matchmaking session, a means for generating initial comments using a generative AI model, a means for analyzing the user's emotional state, a means for providing additional feedback based on the analyzed emotional state, a means for generating an avatar based on the user's behavioral patterns, and a means for displaying conversations between avatars. This not only allows users to objectively evaluate their marriage ability, but also allows them to receive real-time feedback and improvement measures based on the emotion analysis results. Furthermore, the avatar reflecting their own behavioral patterns provides specific guidelines for self-improvement, which can lead to more effective progress in their marriage search.

[0683] "User information" refers to basic information that users enter into the system, including data such as annual income, appearance, hobbies, and romantic history.

[0684] "Marriage power" is an index that evaluates the effectiveness and likelihood of success of a user's marriage search, analyzed based on user information.

[0685] "Feedback" refers to specific improvement measures and advice provided to users based on their analyzed marriage vitality and emotional state.

[0686] "Virtual matchmaking" refers to simulated interactions that users have with generative AI models and other users within the system.

[0687] "Generative AI model" refers to technology that uses artificial intelligence to generate initial utterances and simulate interactions with users.

[0688] "Emotion analysis" refers to technology that recognizes and analyzes a user's emotional state in real time from their facial expressions and voice.

[0689] An "avatar" is a virtual character that is generated based on the user's behavioral patterns and emotional state.

[0690] "Conversation evaluation" refers to a technology that evaluates the content of conversations and facial expressions of users during virtual matchmaking sessions, and provides indicators that are useful for improving their chances of finding a partner.

[0691] A "prompt sentence" refers to the initial utterance or input for a generative AI model to simulate a dialogue with a user.

[0692] "Additional feedback" refers to additional improvements or advice provided to users in real time based on sentiment analysis results and conversation evaluation.

[0693] A system for implementing the present invention uses the following hardware and software.

[0694] Hardware used

[0695] PC or smartphone

[0696] (Optional) Smart glasses, head-mounted display

[0697] Software used

[0698] Python

[0699] Libraries for AI algorithms (e.g., EmotionEngine, MatchmakingEngine)

[0700] Natural language explanation of program processing

[0701] The system begins with the user entering basic information such as annual income, appearance (specifically, height and weight), hobbies, and romantic history via smartphone or computer, which is then sent to a server. The server receives this data and uses an AI algorithm (Matchmaking Engine) to determine a person's potential for marriage.

[0702] The determined marriage ability is notified to the user as a score for each item and an overall score. Next, a feedback system extracts the user's strengths and weaknesses and suggests specific improvement measures. This feedback is displayed on the screen of a smartphone or computer.

[0703] The user sets up a virtual matchmaking session, and the generative AI model makes the first statement. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?"

[0704] When the user responds, the response is analyzed by an emotion analysis engine (Emotion Engine), and the user's emotional state is recognized in real time. For example, if the user responds, "I like soccer and play futsal with friends on the weekends," emotion analysis is performed based on the response. The analysis results are sent to the server and provided to the user as additional feedback. This feedback may include advice such as, "If you feel tense, take a deep breath and try to relax."

[0705] In addition, an avatar is generated based on the user's behavioral patterns, and conversations between these avatars are displayed to the user, providing specific guidelines for self-improvement. During this process, the server stores a series of data, allowing users to repeat the simulation multiple times.

[0706] Examples of concrete examples and prompts

[0707] A specific example would be a simulation in which a user inputs information such as "annual income of 6 million yen" and "hobbies: soccer and cooking," and the generative AI model asks, "Nice to meet you. What are your hobbies?"

[0708] Example prompt sentence:

[0709] "Calculate a marriageability score based on the user's profile information, and use an emotion engine to analyze their emotional state and provide feedback during virtual matchmaking."

[0710] In this way, the present invention provides a system that evaluates a user's marriage ability and provides feedback and specific improvement measures based on emotion analysis.

[0711] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0712] Step 1: Enter your user information

[0713] Users enter their basic information (annual income, appearance, hobbies, dating history, etc.) via their device (PC or smartphone). This information is sent from the device to the server. Input is done in form format, and is completed by filling in the required fields. The entered data is sent to the server in JSON format and saved in a database.

[0714] Step 2: Determine your marriage potential

[0715] The server analyzes the received user information using an AI algorithm (Matchmaking Engine). Specifically, each item, such as annual income, appearance, and hobbies, is scored separately, and the scores are added together to calculate an overall matchmaking score. For example, an annual income of 6 million yen would be a high score, and a diverse range of hobbies would be a higher rating. The analysis results in scores for each item and an overall score, which are then sent back to the device and displayed to the user.

[0716] Step 3: Provide feedback

[0717] The server extracts the user's strengths and weaknesses based on the determined matchmaking power score. For example, the analysis may reveal that the user has a high annual income but a narrow range of hobbies. Based on this information, the server generates specific improvement measures (e.g., "take a more professional profile picture" or "add detailed stories about your hobbies") and sends them to the device as feedback. The user can use this as a guide for self-improvement.

[0718] Step 4: Conduct a virtual matchmaking session

[0719] The user sets up a virtual matchmaking session on their device. The generative AI model makes an initial statement, and the user responds. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?", and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." This is how the virtual matchmaking session progresses, and the statements and responses are recorded.

[0720] Step 5: Analyze emotional state

[0721] The server uses an emotion analysis tool (Emotion Engine) to analyze the user's comments and facial expressions in real time during the virtual matchmaking session. This recognizes the user's emotional state from the tone of voice and facial expressions when they speak, and obtains the analysis results. For example, it can identify emotions such as tension or relaxation. This data is sent to the server, and the analysis results are returned to the device.

[0722] Step 6: Provide additional feedback

[0723] The server generates more specific feedback based on the results of the emotion analysis, such as advice like, "If you feel tense, take a deep breath and try to relax." This feedback is sent to the device and displayed to the user in real time.

[0724] Step 7: Generate and display the avatar

[0725] The server generates a "self-avatar" based on the user's behavioral patterns and emotional state. Conversations between the generated avatars are simulated and displayed on the device. By observing the avatars' interactions, users can obtain specific guidelines for self-improvement.

[0726] Through these steps, users can receive an assessment of their own matchmaking ability, obtain recommendations for improvement, and experience a virtual matchmaking experience. By combining generative AI models with sentiment analysis methods, it is possible to provide users with more accurate feedback and improve their chances of success in matchmaking.

[0727] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0728] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0729] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0730] [Third embodiment]

[0731] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0732] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0733] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0734] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0735] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0736] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0737] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0738] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0739] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0740] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0741] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0742] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0743] The system of the present invention aims to enable users to evaluate their matchmaking ability and obtain improvement measures. This system provides specific feedback by having users input their own information and participate in a virtual matchmaking session.

[0744] Entering user information

[0745] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, love history, etc.). For example, they enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal.

[0746] Analysis of marriage potential

[0747] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[0748] Providing feedback

[0749] The server analyzes the user's strengths and weaknesses based on the determined marriage vitality score. The results are provided as feedback, including specific improvements. For example, suggestions may be made such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and displayed to the user.

[0750] Virtual matchmaking

[0751] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on weekends." All conversations in this virtual matchmaking session are recorded by the server.

[0752] Conversation and facial expression evaluation

[0753] The server analyzes the content of conversations and the user's facial expressions during the virtual matchmaking session in real time. Evaluations are made on a wide range of topics, including conversational ability, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. The analysis results are compiled on the server as an evaluation score, and specific areas for improvement are provided to the user along with the evaluation. Advice such as "be more relaxed and smile more" and "ask more questions to the other person" are included.

[0754] Create your own avatar

[0755] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "personal avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0756] This system allows users to receive objective and detailed feedback, enabling them to implement specific improvements to their search for a partner.

[0757] The processing flow will be explained below.

[0758] Step 1:

[0759] A user accesses the system and logs in by entering the required information on the login screen.

[0760] Step 2:

[0761] The device checks the user's information and displays the home screen. The user then moves to the profile setting screen and enters the necessary information (annual income, appearance, hobbies, romantic history, etc.).

[0762] Step 3:

[0763] The terminal sends the entered user information to the server, where it is stored in a database.

[0764] Step 4:

[0765] Based on the information received by the server, an AI algorithm is used to calculate a score for each element, such as annual income, appearance, hobbies, and profile text, and these are then combined to calculate an overall matchmaking ability score.

[0766] Step 5:

[0767] The server generates the calculated score and detailed feedback information. For example, if a user's annual income is highly rated but their profile text is weak, the server will suggest specific ways to improve the profile.

[0768] Step 6:

[0769] The server sends the generated feedback and score information to the device, which displays it to the user.

[0770] Step 7:

[0771] Next, the user selects a virtual matchmaking session and sets up the virtual matchmaking session. The server then starts the virtual matchmaking generation AI and generates a dialogue scenario.

[0772] Step 8:

[0773] The generative AI starts the virtual matchmaking session and makes an initial statement (e.g., "Nice to meet you. What are your hobbies?"), to which the user responds (e.g., "I like soccer and play futsal with my friends on weekends").

[0774] Step 9:

[0775] The server records the conversations and the user's facial expressions in real time, and the data is then prepared for analysis by AI.

[0776] Step 10:

[0777] The server analyzes conversation data and facial expression data to evaluate the quality of speech, the level of facial relaxation, the frequency of smiling, etc. The evaluation results are compiled as a score.

[0778] Step 11:

[0779] The server generates an evaluation score and specific feedback (e.g., "Ask people more questions more often" or "Smile more and keep a relaxed expression").

[0780] Step 12:

[0781] The server sends the evaluation score and feedback to the device, which displays it to the user.

[0782] Step 13:

[0783] Users participate in multiple virtual matchmaking sessions, and the data is stored on a server. The server then aggregates this data and generates a "personal avatar" based on the user's behavioral patterns and characteristics.

[0784] Step 14:

[0785] The server generates a conversation scenario between the generated "self avatars" and sends it to the device, which then displays it to the user.

[0786] Step 15:

[0787] Users observe conversations between avatars and self-evaluate from a third-party perspective to determine areas for improvement. Based on the information gained through this process, users can improve their behavior in actual matchmaking.

[0788] Example 1

[0789] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0790] Conventional matchmaking support systems have difficulty objectively evaluating users' matchmaking skills and providing specific improvement measures. Furthermore, it is often difficult to identify areas for improvement through self-evaluation alone, and virtual matchmaking sessions and feedback provision are insufficient. Furthermore, there is a lack of appropriate means for users to objectively understand their own behavior and conversations. This has led to issues such as users being unable to effectively improve their matchmaking skills, resulting in a lower success rate in matchmaking.

[0791] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0792] In this invention, the server includes means for a user to input his / her own information, means for analyzing and determining a marriage ability based on the input information, means for providing feedback based on the determined marriage ability score, means for conducting a virtual dialogue, means for evaluating the conversation and facial expressions during the virtual dialogue, means for generating an avatar based on the user's behavioral characteristics, and means for displaying a dialogue between the avatars. This allows a user to objectively evaluate his / her own marriage ability, understand specific areas for improvement, and effectively improve his / her actual marriage ability skills.

[0793] The "user information input means" is an interface that allows a user to provide their own individual information to the system.

[0794] "Marriage potential analysis tools" is a general term for AI algorithms and software that evaluate marriage potential based on provided user information.

[0795] The "feedback provision means" is the part of the system that has the function of presenting specific areas for improvement and strengths to users based on the analyzed marriage vitality score.

[0796] A "means for implementing virtual interaction" is software or an interface that allows a user to virtually interact within a system.

[0797] The "conversation and facial expression evaluation means" is a system function that analyzes the content of the user's conversation and facial expressions during virtual conversation in real time and evaluates the results.

[0798] "Avatar generation means" is a system function for creating an avatar, which is a virtual self-representation, based on the user's behavioral characteristics.

[0799] The "avatar dialogue display means" is an interface for displaying to the user a simulated conversation in which the generated avatars converse with each other.

[0800] The "behavior and speech recording means" is a part of the system for recording the actions and speeches made by the user during the virtual interaction and storing the data.

[0801] The "strengths and weaknesses extraction means" is a system function that extracts the strengths and weaknesses from the information input by the user and generates specific improvement measures based on that information.

[0802] The main purpose of the system of the present invention is to enable users to evaluate their marriage vitality and obtain improvement measures. The components of this system include a user information input means, a marriage vitality analysis means, a feedback providing means, a virtual dialogue implementation means, a conversation and facial expression evaluation means, an avatar generation means, and an avatar dialogue display means.

[0803] Entering user information

[0804] Users log in to the system and enter information such as annual income, appearance (height, weight, photo of face, etc.), hobbies, and romantic history into a dedicated input form. For example, they enter information such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking," and this information is sent to the server via their terminal.

[0805] Analysis of marriage potential

[0806] The server receives the information sent by the user and uses an AI algorithm to evaluate their matchmaking ability. Specifically, factors such as annual income, appearance (height and weight), and variety of hobbies are evaluated using a scoring system to calculate an overall matchmaking ability score. For example, if the annual income is 6 million yen, the score would be 8 / 10, appearance 7 / 10, hobbies 8 / 10, and profile text 6 / 10. This evaluation result, along with a detailed breakdown, is sent back to the device and displayed to the user.

[0807] Providing feedback

[0808] The server analyzes the user's strengths and weaknesses based on the evaluation results and generates feedback including specific suggestions for improvement, such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and presented to the user.

[0809] Conducting virtual conversations

[0810] The user sets up a virtual conversation on the system. The generative AI model makes the initial utterance, and the virtual conversation is simulated. For example, the generative AI model asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The contents of the virtual conversation are all recorded on the server.

[0811] Conversation and facial expression evaluation

[0812] The server analyzes the content of the conversation and the user's facial expressions during the virtual conversation in real time. Analyzed elements include conversational skills, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. For example, while understanding the context of the conversation, it evaluates whether the questions asked to the other person are appropriate and whether the user is relaxed. The analysis results are generated as an evaluation score, and specific feedback is provided, such as "be more relaxed and smile more" or "ask more questions to the other person." This evaluation score and feedback are sent to the device and displayed to the user.

[0813] Create your own avatar

[0814] The server generates an avatar that reflects the user's behavioral characteristics based on behavioral data collected from multiple virtual conversations. Users can use this avatar to evaluate themselves from a third-person perspective. A simulated conversation between the generated avatars is displayed on the device, and by observing the interaction, users can more objectively understand areas for improvement.

[0815] By integrating the above processes, users can objectively evaluate their marriage potential, understand specific improvement measures, and actually improve their conversation skills.

[0816] Example prompt sentence:

[0817] User: Nice to meet you. What hobbies should I have?

[0818] Generative AI: Nice to meet you. If you have a variety of hobbies, it's easier to have a lively conversation and make a good impression on others. Can you tell me more about your hobbies?

[0819] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0820] Step 1: Enter your user information

[0821] Users log in to the system and enter information such as annual income, appearance (height, weight, photo of face, etc.), hobbies, and romantic history into a dedicated input form. This information is sent to the server via the terminal. Input includes specific data such as "annual income of 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking." Once this data reaches the server, it is saved in a database.

[0822] Step 2: Analysis of your marriage potential

[0823] The server uses an AI algorithm to evaluate a user's matchmaking ability based on the information sent by the user. Specifically, it uses a scoring system to evaluate factors such as annual income, appearance (height and weight), and the variety of hobbies, and calculates an overall matchmaking ability score. For an annual income of 6 million yen, the server generates an evaluation result such as 8 / 10 for appearance, 7 / 10 for hobbies, 8 / 10 for hobbies, and 6 / 10 for the profile text. This evaluation result is sent back to the device and displayed to the user.

[0824] Step 3: Provide feedback

[0825] The server analyzes the user's strengths and weaknesses based on the evaluation results and generates feedback including specific recommendations for improvement. Examples of such feedback include "take a more professional profile picture" and "add detailed stories about your hobbies." This feedback is sent to the device and presented to the user. When providing feedback, the server uses a generative AI model to make more specific and personalized suggestions.

[0826] Step 4: Conducting a virtual interaction

[0827] The user sets up a virtual dialogue on the system, and the generative AI model makes the initial utterance to simulate the virtual dialogue. For example, the generative AI asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The content of this dialogue is recorded on the server. The input includes the user's answer, and the output includes the generative AI model's next question.

[0828] Step 5: Evaluate speech and facial expressions

[0829] The server analyzes the content of the conversation and the user's facial expressions during the virtual conversation in real time. Analyzed elements include conversational skills, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. For example, it understands the context of the conversation and evaluates whether the questions asked to the other person are appropriate and the level of relaxation. The analysis results are generated as an evaluation score, and specific feedback such as "be more relaxed and smile more" or "ask more questions to the other person" is provided. The evaluation score and feedback are sent to the device and displayed to the user.

[0830] Step 6: Create your own avatar

[0831] The server generates an avatar that reflects the user's behavioral characteristics based on behavioral data collected from multiple virtual conversations. Users can use this avatar to evaluate themselves from a third-party perspective. A simulated conversation between the generated avatars is displayed on the device, and by observing the interaction, users can more objectively understand areas for improvement. For example, the content of the avatar's conversation and behavioral patterns can be displayed, and by observing them, specific improvement measures can be obtained.

[0832] (Application example 1)

[0833] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0834] In conventional matchmaking support systems, users were limited to online environments in terms of the means by which they could receive feedback to evaluate and improve their matchmaking abilities, resulting in insufficient real-time support at physical stores. Additionally, virtual matchmaking experiences were only available online, resulting in a lack of feedback through physical store experiences.

[0835] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0836] In this invention, the server includes means for a user to input his / her own information, means for analyzing the input information and determining the marriage activity power, means for providing feedback based on the determined marriage activity power, means for conducting a virtual matchmaking meeting, means for evaluating the conversation and facial expressions during the virtual matchmaking meeting, means for generating an avatar based on the user's behavioral patterns, means for displaying conversations between the avatars, and means for providing real-time feedback to the user at a physical store. This enables the user to receive an evaluation of their marriage activity power and specific feedback in real time even at a physical store.

[0837] A "user" is an individual who accesses the system, enters their information, and receives a matchmaking ability rating and feedback.

[0838] The "means of inputting information" refers to the interface that allows users to input their basic information (annual income, appearance, hobbies, romantic history, etc.) into the system.

[0839] "Means of analyzing information and determining marriage potential" refers to the process of evaluating marriage potential using AI algorithms and other methods based on collected user information.

[0840] The "means of providing feedback" is a function that suggests strengths, weaknesses, and specific improvement measures to users based on their assessed matchmaking ability.

[0841] The "means for conducting a virtual matchmaking session" is a function that allows a user to simulate a matchmaking session in a virtual environment and record the results.

[0842] "Means for evaluating conversations and facial expressions" refers to the process of analyzing and evaluating the user's statements and facial expressions during virtual matchmaking.

[0843] "Means for generating avatars based on behavioral patterns" refers to a function that creates an avatar that mimics a user based on the user's behavioral data collected from multiple virtual matchmaking sessions.

[0844] "Means for displaying conversations between avatars" is a function that allows the user to visually see the generated avatars conversing with each other.

[0845] "Means for providing real-time feedback in physical stores" refers to a function that allows users to receive an on-the-spot evaluation of their matchmaking abilities at physical stores such as matchmaking cafes, and provides specific feedback in real time.

[0846] The system of the present invention aims to enable users to evaluate their matchmaking ability and obtain improvement measures. This system provides specific feedback by having users input their own information and participate in a virtual matchmaking session.

[0847] Entering user information

[0848] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, love history, etc.). For example, they enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal.

[0849] Analysis of marriage potential

[0850] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[0851] Providing feedback

[0852] The server analyzes the user's strengths and weaknesses based on the determined matchmaking power score. The results are provided as feedback, including specific improvements. For example, suggestions include "take a more professional profile picture" and "add detailed stories about your hobbies." This feedback is sent to the user's device and displayed.

[0853] Virtual matchmaking

[0854] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on the weekends." All conversations in this virtual matchmaking session are recorded by the server.

[0855] Conversation and facial expression evaluation

[0856] The server analyzes the content of conversations and the user's facial expressions during the virtual matchmaking session in real time. Evaluations are made on a wide range of topics, including conversational ability, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. The analysis results are compiled on the server as an evaluation score, and specific areas for improvement are provided to the user along with the evaluation. Advice such as "be more relaxed and smile more" and "ask more questions to the other person" are included.

[0857] Create your own avatar

[0858] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0859] Providing feedback in-store

[0860] This system can also be used in brick-and-mortar stores, such as matchmaking cafes. Users can enter their information using a tablet or smartphone in the store and conduct a virtual matchmaking session. They can then receive real-time feedback from the server. This makes it possible to evaluate a person's matchmaking ability and provide specific improvement measures even in brick-and-mortar stores.

[0861] Examples of concrete examples and prompts

[0862] A concrete example would be a system in which users can use a tablet at a matchmaking cafe to input their personal information, experience a virtual matchmaking session on the spot, and have AI provide feedback in real time. Users can then receive specific advice based on their scores.

[0863] Examples of prompts include:

[0864] User Information:

[0865] Annual income: 6 million yen

[0866] Appearance: Height 175cm, Weight 70kg

[0867] Hobbies: Soccer, cooking

[0868] Romance history: 3 relationships

[0869] Rate this user's marriage ability and provide feedback such as:

[0870] Strengths

[0871] Weakness

[0872] Improvement points

[0873] Also, provide examples of initial statements from virtual matchmaking.

[0874] This will clarify the specific steps for implementing the invention and its effects.

[0875] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0876] Step 1: Enter your user information

[0877] Users access the system via their terminal and enter their basic information (annual income, appearance, hobbies, romantic history, etc.) into a form. This input includes specific data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer, cooking." This information is sent from the terminal to the server. The input data is sent in JSON format and analyzed on the server side.

[0878] Step 2: Analysis of your marriage potential

[0879] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. This analysis scores annual income, appearance, and hobby diversity. For example, an annual income of 6 million yen would be considered high, with a score of 8 / 10, appearance 7 / 10, and hobby diversity 8 / 10. The server combines these ratings to calculate a marriage potential score and returns the result in JSON format to the device. The score returned from the server is displayed on the user's device.

[0880] Step 3: Provide feedback

[0881] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates specific feedback. For example, it suggests improvements such as "take a professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the user's device and displayed to them.

[0882] Step 4: Conduct a virtual matchmaking session

[0883] The user sets up a virtual matchmaking session through their device. The generative AI model running on the server makes the first statement, simulating the virtual matchmaking. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?" and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." All of this conversation is recorded by the server.

[0884] Step 5: Evaluate speech and facial expressions

[0885] The server analyzes the content of the conversation and the user's facial expressions during the virtual matchmaking session in real time. It evaluates conversational ability, the quality of questions, reactions to the other person, the level of facial relaxation, and the frequency of smiling, and compiles the analysis results as an evaluation score. Specific improvements are generated along with these results, and advice such as "be more relaxed and smile more" or "ask more questions to the other person" is provided to the user.

[0886] Step 6: Create your own avatar

[0887] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0888] Step 7: Providing real-time feedback in-store

[0889] In a physical store, such as a matchmaking cafe, users can access the system using a tablet or smartphone to enter the information described above, conduct a virtual matchmaking session, and receive feedback in real time. The server processes the input data from the physical store, instantly generates feedback, and sends it back to the device, allowing users to receive specific advice on the spot.

[0890] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0891] The system of the present invention aims to evaluate the user's matchmaking ability and provide more accurate feedback and improvement measures using an emotion engine. The system provides specific feedback and advice based on emotion recognition by having the user input their own information and participate in a virtual matchmaking session.

[0892] Entering user information

[0893] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, romantic history, etc.). For example, they might enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal and stored in the database.

[0894] Analysis of marriage potential

[0895] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[0896] Providing feedback

[0897] The server analyzes the user's strengths and weaknesses based on the determined marriage vitality score. The results are provided as feedback, including specific improvements. For example, suggestions may be made such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and displayed to the user.

[0898] Emotion recognition by emotion engine

[0899] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice during the virtual matchmaking session to recognize their emotions. For example, if the user is nervous, the emotion engine will recognize this from their facial expressions and tone of voice and provide an analysis result. This data is sent to the server in real time.

[0900] Virtual matchmaking

[0901] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on the weekends." The content of the virtual matchmaking session, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[0902] Conversation and facial expression evaluation

[0903] The server analyzes the content of conversations during virtual matchmaking, as well as the user's facial expressions and emotional data in real time. The evaluation takes into account conversational ability, quality of questions, reactions to the other person, facial relaxation and frequency of smiling, as well as the results of emotion recognition by the emotion engine. The analysis results are compiled as an evaluation score.

[0904] Enhanced feedback

[0905] The server uses the results of the emotion engine to provide additional feedback according to the user's emotional state. For example, it provides specific improvement suggestions such as "If you feel nervous, take a deep breath and try to relax" or "Introduce yourself calmly and with positive emotions." This feedback is sent to the device and displayed to the user.

[0906] Create your own avatar

[0907] The user's behavioral and emotional data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state. Using this avatar, the user can evaluate themselves from a third-person perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[0908] This system allows users to receive objective and detailed feedback, and improve their chances of finding a partner based on highly accurate advice provided by the emotion engine.

[0909] The processing flow will be explained below.

[0910] Step 1:

[0911] A user accesses the system and logs in by entering the required information on the login screen.

[0912] Step 2:

[0913] The device checks the user's information and displays the home screen. The user then moves to the profile setting screen and enters the necessary information (annual income, appearance, hobbies, romantic history, etc.).

[0914] Step 3:

[0915] The terminal sends the entered user information to the server, where it is stored in a database.

[0916] Step 4:

[0917] Based on the information received by the server, an AI algorithm is used to calculate a score for each element, such as annual income, appearance, hobbies, and profile text, and these are then combined to calculate an overall matchmaking ability score.

[0918] Step 5:

[0919] The server generates the calculated score and detailed feedback information. For example, if a user's annual income is highly rated but their profile text is weak, the server will suggest specific ways to improve the profile.

[0920] Step 6:

[0921] The server sends the generated feedback and score information to the terminal, which displays it to the user.

[0922] Step 7:

[0923] Next, the user selects a virtual matchmaking session and sets up the virtual matchmaking session. The server then starts the virtual matchmaking generation AI and generates a dialogue scenario.

[0924] Step 8:

[0925] The generative AI starts the virtual matchmaking session and makes an initial statement (e.g., "Nice to meet you. What are your hobbies?"), to which the user responds (e.g., "I like soccer and play futsal with my friends on weekends").

[0926] Step 9:

[0927] The server records the conversation content during the virtual matchmaking session, as well as the user's facial expressions and voice in real time, and each piece of data is prepared for analysis by the emotion engine.

[0928] Step 10:

[0929] The emotion engine analyzes the user's facial expressions and voice to generate emotion data, for example, to determine whether the user is nervous.

[0930] Step 11:

[0931] The server analyzes the emotional data and conversation data, evaluating the quality of speech, the level of facial relaxation, the frequency of smiling, etc. The evaluation results are compiled as a score.

[0932] Step 12:

[0933] The server generates an evaluation score and specific feedback (e.g., "Ask people more questions more often" or "Smile more and keep a relaxed expression").

[0934] Step 13:

[0935] The server sends the evaluation score and feedback to the device, which displays it to the user.

[0936] Step 14:

[0937] Users participate in multiple virtual matchmaking sessions, and the data is stored on a server. The server then aggregates this data and generates a "personal avatar" based on the user's behavioral patterns and emotional data.

[0938] Step 15:

[0939] The server generates a conversation scenario between the generated "self avatars" and sends it to the device, which then displays it to the user.

[0940] Step 16:

[0941] Users observe conversations between avatars and self-evaluate from a third-party perspective to determine areas for improvement. Based on the information gained through this process, users can improve their behavior in actual matchmaking.

[0942] Example 2

[0943] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0944] Conventional matchmaking systems only require users to enter basic information, limiting the amount of feedback they can provide. They also lack the means for self-evaluation through detailed analysis via emotion recognition or virtual matchmaking, or avatar generation. This makes it difficult for users to receive more accurate feedback and specific improvement measures.

[0945] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0946] In this invention, the server includes means for a user to input his / her own information, means for analyzing the input information and determining the marriage activity potential, means for providing feedback based on the determined marriage activity potential, means for analyzing the facial expressions and voice of the user during the virtual matchmaking using an emotion engine and recognizing emotions, means for conducting the virtual matchmaking, means for evaluating the conversation and facial expressions during the virtual matchmaking, means for enhancing the feedback based on the evaluation results, means for generating an avatar based on the user's behavioral patterns, and means for displaying the conversation between the avatars. This allows the user to receive detailed and objective feedback and obtain specific measures for self-improvement through emotion recognition and virtual matchmaking.

[0947] "User" means an individual who accesses the system, enters their information, and receives feedback.

[0948] "Information input" refers to the act of a user providing basic information about themselves (annual income, appearance, hobbies, romantic history, etc.) to the system.

[0949] "Analysis" refers to the means of evaluating the entered user information and determining their potential for marriage.

[0950] "Marriage Ability" is a comprehensive evaluation score of a user's marriage activities, calculated based on attributes such as annual income, appearance, hobbies, and profile text.

[0951] "Feedback" refers to information that points out a user's strengths and weaknesses based on analysis results and provides specific measures for improvement.

[0952] The "emotion engine" is a technology that analyzes the user's facial expressions and voice during a virtual matchmaking session and recognizes their emotions in real time.

[0953] "Virtual matchmaking" is a feature in which a generative AI model makes the first statement and simulates a matchmaking session, which progresses through interaction with the user.

[0954] A "generative AI model" is an artificial intelligence that generates conversations with users during virtual matchmaking and feedback sessions.

[0955] "Conversation and facial expression evaluation" is a method of analyzing the content of a user's remarks and facial expression data during a virtual matchmaking session and calculating an overall evaluation score.

[0956] "Enhanced feedback" refers to a means of providing more specific feedback that has a greater effect on improvement, based on evaluation results and emotional recognition.

[0957] An "avatar" is a virtual self-image generated based on the user's behavioral patterns and emotional data, allowing for self-evaluation from a third-party perspective.

[0958] "Avatar-to-avatar conversation" is a feature that displays multiple avatars having a simulated conversation using a generative AI model.

[0959] The matchmaking support system of the present invention allows users to input their own information, evaluate their matchmaking ability through virtual matchmaking, and provides highly accurate feedback and improvement measures using an emotion engine. This system includes a terminal for users to input information, a server for analyzing the information and evaluating matchmaking ability, and various software for providing feedback.

[0960] Hardware and software used

[0961] This system uses the following hardware and software:

[0962] Device: An electronic device (computer, smartphone, tablet, etc.) where users input information and view feedback and results.

[0963] Server: A computer that manages user information, analyzes it, and generates feedback.

[0964] Emotion engine: Dedicated software for analyzing the user's facial expressions and voice in real time (e.g., Emotion API)

[0965] Generative AI models: artificial intelligence platforms (e.g., GPT-3) for simulating virtual matchmaking conversations

[0966] Specific examples of processing

[0967] Input and analysis of user information

[0968] The user uses the device to input their basic information (annual income, appearance, hobbies, love history, etc.). For example, they input information such as "annual income of 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking." The device sends this information to the server, which stores it in a database.

[0969] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is rated high, while a height of 175 cm and a weight of 70 kg is rated medium. The server evaluates this information based on a scoring system and calculates an overall marriage potential score. This score is sent back to the device and displayed to the user.

[0970] Providing feedback

[0971] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates appropriate feedback, such as suggestions like "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent from the server to the user's device and displayed.

[0972] Emotion recognition by emotion engine

[0973] Once the virtual matchmaking session begins, the server's built-in emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotions. For example, if the user is nervous, the emotion engine will detect this from their facial expressions and tone of voice and send that data to the server.

[0974] Virtual matchmaking

[0975] When a user sets up a virtual matchmaking session, the generative AI model makes the first statement and simulates the matchmaking. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?", and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." The content of this conversation, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[0976] Enhanced speech and facial expression assessment and feedback

[0977] The server analyzes the conversation content during the virtual matchmaking session, as well as the user's facial expressions and emotional data, to calculate an overall evaluation score. It also strengthens feedback based on the results of the emotion engine, providing specific improvement measures such as "If you feel nervous, take a deep breath and relax" and "Introduce yourself calmly with positive emotions." This feedback is sent to the device and displayed to the user.

[0978] Create your own avatar

[0979] The server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state based on the user's behavioral and emotional data accumulated through virtual matchmaking. The user can use this avatar to evaluate themselves from a third-person perspective and observe simulated conversations between avatars.

[0980] Prompt Sentence Examples

[0981] Please rate your marriage strength based on the user information below and provide specific feedback and suggestions for improvement.

[0982] User Information:

[0983] Annual income: 6 million yen

[0984] Appearance: Height 175cm, Weight 70kg, Photo (URL)

[0985] Hobbies: Soccer, cooking

[0986] Romance history: 3 times

[0987] Matchmaking Settings:

[0988] First utterance from the generated AI: "Nice to meet you. What are your hobbies?"

[0989] User response:

[0990] "I like soccer and play futsal with my friends on the weekends."

[0991] The system of the present invention provides detailed and objective feedback to users throughout these processes and suggests specific strategies for self-improvement through emotion recognition and virtual matchmaking.

[0992] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0993] Step 1: Enter your user information

[0994] Users access the system through their terminal and enter their basic information (annual income, appearance, hobbies, love history, etc.). For example, they might enter data such as "annual income of 6 million yen," "appearance: photo of height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into a form. This input information is sent from the terminal to the server, which then stores it in a database.

[0995] Input: User information such as annual income, appearance, hobbies, and romantic history

[0996] Data processing: Save the input information as structured data

[0997] Output: Saved user information

[0998] Step 2: Analysis of your marriage potential

[0999] The server retrieves user information stored in a database and uses an AI algorithm to determine a person's marriage potential. For example, an annual income of 6 million yen is rated high, while a height of 175 cm is rated neutral. The server calculates a score for each attribute and generates an overall marriage potential score. This score is sent back to the device and displayed to the user.

[1000] Input: User information stored in the database

[1001] Data calculation: Scoring each attribute using AI algorithms

[1002] Output: Overall marriage vitality score and its breakdown

[1003] Step 3: Provide feedback

[1004] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates specific feedback, such as suggestions like "take a more professional profile picture" or "add more detailed stories about your hobbies." This feedback is sent from the server to the user's device and displayed.

[1005] Input: Marital vitality score and its breakdown

[1006] Data processing: feedback generation based on scores

[1007] Output: Analysis of strengths and weaknesses and specific feedback

[1008] Step 4: Emotion Recognition with the Emotion Engine

[1009] During the virtual matchmaking session, the server's built-in emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotions. For example, if the user is nervous, the emotion engine will detect this from their facial expressions and tone of voice, and the data will be sent to the server in real time.

[1010] Input: facial expression data and voice data of the user during the virtual matchmaking session

[1011] Data Computation: Real-time Emotion Analysis with an Emotion Engine

[1012] Output: Emotion recognition result

[1013] Step 5: Conduct a virtual matchmaking session

[1014] The user sets up a virtual matchmaking session, and the generative AI model makes the first utterance, simulating the matchmaking. For example, the generative AI asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The content of this conversation, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[1015] Input: The initial utterance of the generative AI model, and the user's response

[1016] Data processing: Recording of conversation content, facial expressions, and emotional data

[1017] Output: Recorded virtual matchmaking data

[1018] Step 6: Evaluate speech and facial expressions

[1019] The server analyzes the content of the conversation during the virtual matchmaking session, as well as the user's facial expressions and emotional data, and calculates a comprehensive evaluation score. For example, the evaluation criteria include conversational ability, quality of questions, reaction to the other person, level of facial relaxation, and frequency of smiling. The evaluation results are sent from the server to the user's device and displayed to them.

[1020] Input: Recorded virtual matchmaking data (conversation content, facial expressions, emotional data)

[1021] Data calculation: Calculation of overall evaluation score based on evaluation criteria

[1022] Output: Overall evaluation score and breakdown of evaluation results

[1023] Step 7: Reinforcing feedback

[1024] The server then provides more specific and effective feedback based on the results of the emotion engine. For example, it offers suggestions for improvement such as "If you feel nervous, take a deep breath and relax" or "Introduce yourself calmly and with positive emotions." This feedback is sent from the server to the device and displayed to the user.

[1025] Input: Overall evaluation score and emotion recognition results

[1026] Data processing: Generating feedback based on emotion recognition results

[1027] Output: Specific improvements added

[1028] Step 8: Create your own avatar

[1029] The server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state based on the user's behavioral and emotional data accumulated through virtual matchmaking. The user can use this avatar to evaluate themselves from a third-person perspective and observe simulated conversations between avatars.

[1030] Input: Accumulated behavioral and emotional data

[1031] Data Computing: Avatar Generation Based on Behavioral Characteristics and Emotional States

[1032] Output: Generated self-avatar and simulated conversation data

[1033] (Application example 2)

[1034] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1035] Conventional matchmaking support systems have difficulty not only objectively evaluating a user's matchmaking ability and providing specific improvement measures, but also analyzing their emotional state and providing real-time feedback. Furthermore, they lacked technology for generating avatars based on the user's behavioral patterns and for incorporating the results of emotional analysis during virtual matchmaking into feedback. This meant that users were unable to obtain specific guidelines for self-improvement, preventing them from effectively progressing with their matchmaking efforts.

[1036] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a user to input their own information, a means for analyzing the input information and determining their marriage ability, a means for providing feedback based on the determined marriage ability, a means for conducting a virtual matchmaking session, a means for evaluating the conversation and facial expressions during the virtual matchmaking session, a means for generating initial comments using a generative AI model, a means for analyzing the user's emotional state, a means for providing additional feedback based on the analyzed emotional state, a means for generating an avatar based on the user's behavioral patterns, and a means for displaying conversations between avatars. This not only allows users to objectively evaluate their marriage ability, but also allows them to receive real-time feedback and improvement measures based on the emotion analysis results. Furthermore, the avatar reflecting their own behavioral patterns provides specific guidelines for self-improvement, which can lead to more effective progress in their marriage search.

[1037] "User information" refers to basic information that users enter into the system, including data such as annual income, appearance, hobbies, and romantic history.

[1038] "Marriage power" is an index that evaluates the effectiveness and likelihood of success of a user's marriage search, analyzed based on user information.

[1039] "Feedback" refers to specific improvement measures and advice provided to users based on their analyzed marriage vitality and emotional state.

[1040] "Virtual matchmaking" refers to simulated interactions that users have with generative AI models and other users within the system.

[1041] "Generative AI model" refers to technology that uses artificial intelligence to generate initial utterances and simulate interactions with users.

[1042] "Emotion analysis" refers to technology that recognizes and analyzes a user's emotional state in real time from their facial expressions and voice.

[1043] An "avatar" is a virtual character that is generated based on the user's behavioral patterns and emotional state.

[1044] "Conversation evaluation" refers to a technology that evaluates the content of conversations and facial expressions of users during virtual matchmaking sessions, and provides indicators that are useful for improving their chances of finding a partner.

[1045] A "prompt sentence" refers to the initial utterance or input for a generative AI model to simulate a dialogue with a user.

[1046] "Additional feedback" refers to additional improvements or advice provided to users in real time based on sentiment analysis results and conversation evaluation.

[1047] A system for implementing the present invention uses the following hardware and software.

[1048] Hardware used

[1049] PC or smartphone

[1050] (Optional) Smart glasses, head-mounted display

[1051] Software used

[1052] Python

[1053] Libraries for AI algorithms (e.g., EmotionEngine, MatchmakingEngine)

[1054] Natural language explanation of program processing

[1055] The system begins with the user entering basic information such as annual income, appearance (specifically, height and weight), hobbies, and romantic history via smartphone or computer, which is then sent to a server. The server receives this data and uses an AI algorithm (Matchmaking Engine) to determine a person's potential for marriage.

[1056] The determined marriage ability is notified to the user as a score for each item and an overall score. Next, a feedback system extracts the user's strengths and weaknesses and suggests specific improvement measures. This feedback is displayed on the screen of a smartphone or computer.

[1057] The user sets up a virtual matchmaking session, and the generative AI model makes the first statement. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?"

[1058] When the user responds, the response is analyzed by an emotion analysis engine (Emotion Engine), and the user's emotional state is recognized in real time. For example, if the user responds, "I like soccer and play futsal with friends on the weekends," emotion analysis is performed based on the response. The analysis results are sent to the server and provided to the user as additional feedback. This feedback may include advice such as, "If you feel tense, take a deep breath and try to relax."

[1059] In addition, an avatar is generated based on the user's behavioral patterns, and conversations between these avatars are displayed to the user, providing specific guidelines for self-improvement. During this process, the server stores a series of data, allowing users to repeat the simulation multiple times.

[1060] Examples of concrete examples and prompts

[1061] A specific example would be a simulation in which a user inputs information such as "annual income of 6 million yen" and "hobbies: soccer and cooking," and the generative AI model asks, "Nice to meet you. What are your hobbies?"

[1062] Example prompt sentence:

[1063] "Calculate a marriageability score based on the user's profile information, and use an emotion engine to analyze their emotional state and provide feedback during virtual matchmaking."

[1064] In this way, the present invention provides a system that evaluates a user's marriage ability and provides feedback and specific improvement measures based on emotion analysis.

[1065] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1066] Step 1: Enter your user information

[1067] Users enter their basic information (annual income, appearance, hobbies, dating history, etc.) via their device (PC or smartphone). This information is sent from the device to the server. Input is done in form format, and is completed by filling in the required fields. The entered data is sent to the server in JSON format and saved in a database.

[1068] Step 2: Determine your marriage potential

[1069] The server analyzes the received user information using an AI algorithm (Matchmaking Engine). Specifically, each item, such as annual income, appearance, and hobbies, is scored separately, and the scores are added together to calculate an overall matchmaking score. For example, an annual income of 6 million yen would be a high score, and a diverse range of hobbies would be a higher rating. The analysis results in scores for each item and an overall score, which are then sent back to the device and displayed to the user.

[1070] Step 3: Provide feedback

[1071] The server extracts the user's strengths and weaknesses based on the determined matchmaking power score. For example, the analysis may reveal that the user has a high annual income but a narrow range of hobbies. Based on this information, the server generates specific improvement measures (e.g., "take a more professional profile picture" or "add detailed stories about your hobbies") and sends them to the device as feedback. The user can use this as a guide for self-improvement.

[1072] Step 4: Conduct a virtual matchmaking session

[1073] The user sets up a virtual matchmaking session on their device. The generative AI model makes an initial statement, and the user responds. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?", and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." This is how the virtual matchmaking session progresses, and the statements and responses are recorded.

[1074] Step 5: Analyze emotional state

[1075] The server uses an emotion analysis tool (Emotion Engine) to analyze the user's comments and facial expressions in real time during the virtual matchmaking session. This recognizes the user's emotional state from the tone of voice and facial expressions when they speak, and obtains the analysis results. For example, it can identify emotions such as tension or relaxation. This data is sent to the server, and the analysis results are returned to the device.

[1076] Step 6: Provide additional feedback

[1077] The server generates more specific feedback based on the results of the emotion analysis, such as advice like, "If you feel tense, take a deep breath and try to relax." This feedback is sent to the device and displayed to the user in real time.

[1078] Step 7: Generate and display the avatar

[1079] The server generates a "self-avatar" based on the user's behavioral patterns and emotional state. Conversations between the generated avatars are simulated and displayed on the device. By observing the avatars' interactions, users can obtain specific guidelines for self-improvement.

[1080] Through these steps, users can receive an assessment of their own matchmaking ability, obtain recommendations for improvement, and experience a virtual matchmaking experience. By combining generative AI models with sentiment analysis methods, it is possible to provide users with more accurate feedback and improve their chances of success in matchmaking.

[1081] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1082] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1083] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1084] [Fourth embodiment]

[1085] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1086] 7, a 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.

[1087] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1088] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1089] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1090] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1091] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1092] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1093] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1094] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1095] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1096] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1097] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1098] The system of the present invention aims to enable users to evaluate their matchmaking ability and obtain improvement measures. This system provides specific feedback by having users input their own information and participate in a virtual matchmaking session.

[1099] Entering user information

[1100] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, love history, etc.). For example, they enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal.

[1101] Analysis of marriage potential

[1102] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[1103] Providing feedback

[1104] The server analyzes the user's strengths and weaknesses based on the determined marriage vitality score. The results are provided as feedback, including specific improvements. For example, suggestions may be made such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and displayed to the user.

[1105] Virtual matchmaking

[1106] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on weekends." All conversations in this virtual matchmaking session are recorded by the server.

[1107] Conversation and facial expression evaluation

[1108] The server analyzes the content of conversations and the user's facial expressions during the virtual matchmaking session in real time. Evaluations are made on a wide range of topics, including conversational ability, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. The analysis results are compiled on the server as an evaluation score, and specific areas for improvement are provided to the user along with the evaluation. Advice such as "be more relaxed and smile more" and "ask more questions to the other person" are included.

[1109] Create your own avatar

[1110] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "personal avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[1111] This system allows users to receive objective and detailed feedback, enabling them to implement specific improvements to their search for a partner.

[1112] The processing flow will be explained below.

[1113] Step 1:

[1114] A user accesses the system and logs in by entering the required information on the login screen.

[1115] Step 2:

[1116] The device checks the user's information and displays the home screen. The user then moves to the profile setting screen and enters the necessary information (annual income, appearance, hobbies, romantic history, etc.).

[1117] Step 3:

[1118] The terminal sends the entered user information to the server, where it is stored in a database.

[1119] Step 4:

[1120] Based on the information received by the server, an AI algorithm is used to calculate a score for each element, such as annual income, appearance, hobbies, and profile text, and these are then combined to calculate an overall matchmaking ability score.

[1121] Step 5:

[1122] The server generates the calculated score and detailed feedback information. For example, if a user's annual income is highly rated but their profile text is weak, the server will suggest specific ways to improve the profile.

[1123] Step 6:

[1124] The server sends the generated feedback and score information to the device, which displays it to the user.

[1125] Step 7:

[1126] Next, the user selects a virtual matchmaking session and sets up the virtual matchmaking session. The server then starts the virtual matchmaking generation AI and generates a dialogue scenario.

[1127] Step 8:

[1128] The generative AI starts the virtual matchmaking session and makes an initial statement (e.g., "Nice to meet you. What are your hobbies?"), to which the user responds (e.g., "I like soccer and play futsal with my friends on weekends").

[1129] Step 9:

[1130] The server records the conversations and the user's facial expressions in real time, and the data is then prepared for analysis by AI.

[1131] Step 10:

[1132] The server analyzes conversation data and facial expression data to evaluate the quality of speech, the level of facial relaxation, the frequency of smiling, etc. The evaluation results are compiled as a score.

[1133] Step 11:

[1134] The server generates an evaluation score and specific feedback (e.g., "Ask people more questions more often" or "Smile more and keep a relaxed expression").

[1135] Step 12:

[1136] The server sends the evaluation score and feedback to the device, which displays it to the user.

[1137] Step 13:

[1138] Users participate in multiple virtual matchmaking sessions, and the data is stored on a server. The server then aggregates this data and generates a "personal avatar" based on the user's behavioral patterns and characteristics.

[1139] Step 14:

[1140] The server generates a conversation scenario between the generated "self avatars" and sends it to the device, which then displays it to the user.

[1141] Step 15:

[1142] Users observe conversations between avatars and self-evaluate from a third-party perspective to determine areas for improvement. Based on the information gained through this process, users can improve their behavior in actual matchmaking.

[1143] Example 1

[1144] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1145] Conventional matchmaking support systems have difficulty objectively evaluating users' matchmaking skills and providing specific improvement measures. Furthermore, it is often difficult to identify areas for improvement through self-evaluation alone, and virtual matchmaking sessions and feedback provision are insufficient. Furthermore, there is a lack of appropriate means for users to objectively understand their own behavior and conversations. This has led to issues such as users being unable to effectively improve their matchmaking skills, resulting in a lower success rate in matchmaking.

[1146] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1147] In this invention, the server includes means for a user to input his / her own information, means for analyzing and determining a marriage ability based on the input information, means for providing feedback based on the determined marriage ability score, means for conducting a virtual dialogue, means for evaluating the conversation and facial expressions during the virtual dialogue, means for generating an avatar based on the user's behavioral characteristics, and means for displaying a dialogue between the avatars. This allows a user to objectively evaluate his / her own marriage ability, understand specific areas for improvement, and effectively improve his / her actual marriage ability skills.

[1148] The "user information input means" is an interface that allows a user to provide their own individual information to the system.

[1149] "Marriage potential analysis tools" is a general term for AI algorithms and software that evaluate marriage potential based on provided user information.

[1150] The "feedback provision means" is the part of the system that has the function of presenting specific areas for improvement and strengths to users based on the analyzed marriage vitality score.

[1151] A "means for implementing virtual interaction" is software or an interface that allows a user to virtually interact within a system.

[1152] The "conversation and facial expression evaluation means" is a system function that analyzes the content of the user's conversation and facial expressions during virtual conversation in real time and evaluates the results.

[1153] "Avatar generation means" is a system function for creating an avatar, which is a virtual self-representation, based on the user's behavioral characteristics.

[1154] The "avatar dialogue display means" is an interface for displaying to the user a simulated conversation in which the generated avatars converse with each other.

[1155] The "behavior and speech recording means" is a part of the system for recording the actions and speeches made by the user during the virtual interaction and storing the data.

[1156] The "strengths and weaknesses extraction means" is a system function that extracts the strengths and weaknesses from the information input by the user and generates specific improvement measures based on that information.

[1157] The main purpose of the system of the present invention is to enable users to evaluate their marriage vitality and obtain improvement measures. The components of this system include a user information input means, a marriage vitality analysis means, a feedback providing means, a virtual dialogue implementation means, a conversation and facial expression evaluation means, an avatar generation means, and an avatar dialogue display means.

[1158] Entering user information

[1159] Users log in to the system and enter information such as annual income, appearance (height, weight, photo of face, etc.), hobbies, and romantic history into a dedicated input form. For example, they enter information such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking," and this information is sent to the server via their terminal.

[1160] Analysis of marriage potential

[1161] The server receives the information sent by the user and uses an AI algorithm to evaluate their matchmaking ability. Specifically, factors such as annual income, appearance (height and weight), and variety of hobbies are evaluated using a scoring system to calculate an overall matchmaking ability score. For example, if the annual income is 6 million yen, the score would be 8 / 10, appearance 7 / 10, hobbies 8 / 10, and profile text 6 / 10. This evaluation result, along with a detailed breakdown, is sent back to the device and displayed to the user.

[1162] Providing feedback

[1163] The server analyzes the user's strengths and weaknesses based on the evaluation results and generates feedback including specific suggestions for improvement, such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and presented to the user.

[1164] Conducting virtual conversations

[1165] The user sets up a virtual conversation on the system. The generative AI model makes the initial utterance, and the virtual conversation is simulated. For example, the generative AI model asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The contents of the virtual conversation are all recorded on the server.

[1166] Conversation and facial expression evaluation

[1167] The server analyzes the content of the conversation and the user's facial expressions during the virtual conversation in real time. Analyzed elements include conversational skills, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. For example, while understanding the context of the conversation, it evaluates whether the questions asked to the other person are appropriate and whether the user is relaxed. The analysis results are generated as an evaluation score, and specific feedback is provided, such as "be more relaxed and smile more" or "ask more questions to the other person." This evaluation score and feedback are sent to the device and displayed to the user.

[1168] Create your own avatar

[1169] The server generates an avatar that reflects the user's behavioral characteristics based on behavioral data collected from multiple virtual conversations. Users can use this avatar to evaluate themselves from a third-person perspective. A simulated conversation between the generated avatars is displayed on the device, and by observing the interaction, users can more objectively understand areas for improvement.

[1170] By integrating the above processes, users can objectively evaluate their marriage potential, understand specific improvement measures, and actually improve their conversation skills.

[1171] Example prompt sentence:

[1172] User: Nice to meet you. What hobbies should I have?

[1173] Generative AI: Nice to meet you. If you have a variety of hobbies, it's easier to have a lively conversation and make a good impression on others. Can you tell me more about your hobbies?

[1174] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1175] Step 1: Enter your user information

[1176] Users log in to the system and enter information such as annual income, appearance (height, weight, photo of face, etc.), hobbies, and romantic history into a dedicated input form. This information is sent to the server via the terminal. Input includes specific data such as "annual income of 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking." Once this data reaches the server, it is saved in a database.

[1177] Step 2: Analysis of your marriage potential

[1178] The server uses an AI algorithm to evaluate a user's matchmaking ability based on the information sent by the user. Specifically, it uses a scoring system to evaluate factors such as annual income, appearance (height and weight), and the variety of hobbies, and calculates an overall matchmaking ability score. For an annual income of 6 million yen, the server generates an evaluation result such as 8 / 10 for appearance, 7 / 10 for hobbies, 8 / 10 for hobbies, and 6 / 10 for the profile text. This evaluation result is sent back to the device and displayed to the user.

[1179] Step 3: Provide feedback

[1180] The server analyzes the user's strengths and weaknesses based on the evaluation results and generates feedback including specific recommendations for improvement. Examples of such feedback include "take a more professional profile picture" and "add detailed stories about your hobbies." This feedback is sent to the device and presented to the user. When providing feedback, the server uses a generative AI model to make more specific and personalized suggestions.

[1181] Step 4: Conducting a virtual interaction

[1182] The user sets up a virtual dialogue on the system, and the generative AI model makes the initial utterance to simulate the virtual dialogue. For example, the generative AI asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The content of this dialogue is recorded on the server. The input includes the user's answer, and the output includes the generative AI model's next question.

[1183] Step 5: Evaluate speech and facial expressions

[1184] The server analyzes the content of the conversation and the user's facial expressions during the virtual conversation in real time. Analyzed elements include conversational skills, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. For example, it understands the context of the conversation and evaluates whether the questions asked to the other person are appropriate and the level of relaxation. The analysis results are generated as an evaluation score, and specific feedback such as "be more relaxed and smile more" or "ask more questions to the other person" is provided. The evaluation score and feedback are sent to the device and displayed to the user.

[1185] Step 6: Create your own avatar

[1186] The server generates an avatar that reflects the user's behavioral characteristics based on behavioral data collected from multiple virtual conversations. Users can use this avatar to evaluate themselves from a third-party perspective. A simulated conversation between the generated avatars is displayed on the device, and by observing the interaction, users can more objectively understand areas for improvement. For example, the content of the avatar's conversation and behavioral patterns can be displayed, and by observing them, specific improvement measures can be obtained.

[1187] (Application example 1)

[1188] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1189] In conventional matchmaking support systems, users were limited to online environments in terms of the means by which they could receive feedback to evaluate and improve their matchmaking abilities, resulting in insufficient real-time support at physical stores. Additionally, virtual matchmaking experiences were only available online, resulting in a lack of feedback through physical store experiences.

[1190] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1191] In this invention, the server includes means for a user to input his / her own information, means for analyzing the input information and determining the marriage activity power, means for providing feedback based on the determined marriage activity power, means for conducting a virtual matchmaking meeting, means for evaluating the conversation and facial expressions during the virtual matchmaking meeting, means for generating an avatar based on the user's behavioral patterns, means for displaying conversations between the avatars, and means for providing real-time feedback to the user at a physical store. This enables the user to receive an evaluation of their marriage activity power and specific feedback in real time even at a physical store.

[1192] A "user" is an individual who accesses the system, enters their information, and receives a matchmaking ability rating and feedback.

[1193] The "means of inputting information" refers to the interface that allows users to input their basic information (annual income, appearance, hobbies, romantic history, etc.) into the system.

[1194] "Means of analyzing information and determining marriage potential" refers to the process of evaluating marriage potential using AI algorithms and other methods based on collected user information.

[1195] The "means of providing feedback" is a function that suggests strengths, weaknesses, and specific improvement measures to users based on their assessed matchmaking ability.

[1196] The "means for conducting a virtual matchmaking session" is a function that allows a user to simulate a matchmaking session in a virtual environment and record the results.

[1197] "Means for evaluating conversations and facial expressions" refers to the process of analyzing and evaluating the user's statements and facial expressions during virtual matchmaking.

[1198] "Means for generating avatars based on behavioral patterns" refers to a function that creates an avatar that mimics a user based on the user's behavioral data collected from multiple virtual matchmaking sessions.

[1199] "Means for displaying conversations between avatars" is a function that allows the user to visually see the generated avatars conversing with each other.

[1200] "Means for providing real-time feedback in physical stores" refers to a function that allows users to receive an on-the-spot evaluation of their matchmaking abilities at physical stores such as matchmaking cafes, and provides specific feedback in real time.

[1201] The system of the present invention aims to enable users to evaluate their matchmaking ability and obtain improvement measures. This system provides specific feedback by having users input their own information and participate in a virtual matchmaking session.

[1202] Entering user information

[1203] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, love history, etc.). For example, they enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal.

[1204] Analysis of marriage potential

[1205] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[1206] Providing feedback

[1207] The server analyzes the user's strengths and weaknesses based on the determined matchmaking power score. The results are provided as feedback, including specific improvements. For example, suggestions include "take a more professional profile picture" and "add detailed stories about your hobbies." This feedback is sent to the user's device and displayed.

[1208] Virtual matchmaking

[1209] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on the weekends." All conversations in this virtual matchmaking session are recorded by the server.

[1210] Conversation and facial expression evaluation

[1211] The server analyzes the content of conversations and the user's facial expressions during the virtual matchmaking session in real time. Evaluations are made on a wide range of topics, including conversational ability, quality of questions, reactions to the other person, facial relaxation, and frequency of smiling. The analysis results are compiled on the server as an evaluation score, and specific areas for improvement are provided to the user along with the evaluation. Advice such as "be more relaxed and smile more" and "ask more questions to the other person" are included.

[1212] Create your own avatar

[1213] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[1214] Providing feedback in-store

[1215] This system can also be used in brick-and-mortar stores, such as matchmaking cafes. Users can enter their information using a tablet or smartphone in the store and conduct a virtual matchmaking session. They can then receive real-time feedback from the server. This makes it possible to evaluate a person's matchmaking ability and provide specific improvement measures even in brick-and-mortar stores.

[1216] Examples of concrete examples and prompts

[1217] A concrete example would be a system in which users can use a tablet at a matchmaking cafe to input their personal information, experience a virtual matchmaking session on the spot, and have AI provide feedback in real time. Users can then receive specific advice based on their scores.

[1218] Examples of prompts include:

[1219] User Information:

[1220] Annual income: 6 million yen

[1221] Appearance: Height 175cm, Weight 70kg

[1222] Hobbies: Soccer, cooking

[1223] Romance history: 3 relationships

[1224] Rate this user's marriage ability and provide feedback such as:

[1225] Strengths

[1226] Weakness

[1227] Improvement points

[1228] Also, provide examples of initial statements from virtual matchmaking.

[1229] This will clarify the specific steps for implementing the invention and its effects.

[1230] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1231] Step 1: Enter your user information

[1232] Users access the system via their terminal and enter their basic information (annual income, appearance, hobbies, romantic history, etc.) into a form. This input includes specific data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer, cooking." This information is sent from the terminal to the server. The input data is sent in JSON format and analyzed on the server side.

[1233] Step 2: Analysis of your marriage potential

[1234] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. This analysis scores annual income, appearance, and hobby diversity. For example, an annual income of 6 million yen would be considered high, with a score of 8 / 10, appearance 7 / 10, and hobby diversity 8 / 10. The server combines these ratings to calculate a marriage potential score and returns the result in JSON format to the device. The score returned from the server is displayed on the user's device.

[1235] Step 3: Provide feedback

[1236] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates specific feedback. For example, it suggests improvements such as "take a professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the user's device and displayed to them.

[1237] Step 4: Conduct a virtual matchmaking session

[1238] The user sets up a virtual matchmaking session through their device. The generative AI model running on the server makes the first statement, simulating the virtual matchmaking. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?" and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." All of this conversation is recorded by the server.

[1239] Step 5: Evaluate speech and facial expressions

[1240] The server analyzes the content of the conversation and the user's facial expressions during the virtual matchmaking session in real time. It evaluates conversational ability, the quality of questions, reactions to the other person, the level of facial relaxation, and the frequency of smiling, and compiles the analysis results as an evaluation score. Specific improvements are generated along with these results, and advice such as "be more relaxed and smile more" or "ask more questions to the other person" is provided to the user.

[1241] Step 6: Create your own avatar

[1242] The user's behavioral data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics. Using this avatar, the user can evaluate themselves from a third-party perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[1243] Step 7: Providing real-time feedback in-store

[1244] In a physical store, such as a matchmaking cafe, users can access the system using a tablet or smartphone to enter the information described above, conduct a virtual matchmaking session, and receive feedback in real time. The server processes the input data from the physical store, instantly generates feedback, and sends it back to the device, allowing users to receive specific advice on the spot.

[1245] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1246] The system of the present invention aims to evaluate the user's matchmaking ability and provide more accurate feedback and improvement measures using an emotion engine. The system provides specific feedback and advice based on emotion recognition by having the user input their own information and participate in a virtual matchmaking session.

[1247] Entering user information

[1248] First, the user accesses the system and enters their basic information (annual income, appearance, hobbies, romantic history, etc.). For example, they might enter data such as "annual income 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into the form. This information is sent to the server via the terminal and stored in the database.

[1249] Analysis of marriage potential

[1250] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is given a high rating, while factors such as height, weight, and the variety of hobbies are evaluated using a unique scoring system. This calculates an overall marriage potential score. The breakdown of the score (for example, annual income 8 / 10, appearance 7 / 10, hobbies 8 / 10, profile text 6 / 10, etc.) and the overall score are sent back from the server to the device and displayed to the user.

[1251] Providing feedback

[1252] The server analyzes the user's strengths and weaknesses based on the determined marriage vitality score. The results are provided as feedback, including specific improvements. For example, suggestions may be made such as "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent to the device and displayed to the user.

[1253] Emotion recognition by emotion engine

[1254] The server is equipped with an emotion engine that analyzes the user's facial expressions and voice during the virtual matchmaking session to recognize their emotions. For example, if the user is nervous, the emotion engine will recognize this from their facial expressions and tone of voice and provide an analysis result. This data is sent to the server in real time.

[1255] Virtual matchmaking

[1256] Next, the user sets up a virtual matchmaking session. Here, the generation AI makes the first statement, simulating a matchmaking session. For example, the generation AI might ask, "Nice to meet you. What are your hobbies?" The user might respond, for example, by saying, "I like soccer, and I play futsal with my friends on the weekends." The content of the virtual matchmaking session, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[1257] Conversation and facial expression evaluation

[1258] The server analyzes the content of conversations during virtual matchmaking, as well as the user's facial expressions and emotional data in real time. The evaluation takes into account conversational ability, quality of questions, reactions to the other person, facial relaxation and frequency of smiling, as well as the results of emotion recognition by the emotion engine. The analysis results are compiled as an evaluation score.

[1259] Enhanced feedback

[1260] The server uses the results of the emotion engine to provide additional feedback according to the user's emotional state. For example, it provides specific improvement suggestions such as "If you feel nervous, take a deep breath and try to relax" or "Introduce yourself calmly and with positive emotions." This feedback is sent to the device and displayed to the user.

[1261] Create your own avatar

[1262] The user's behavioral and emotional data acquired through multiple virtual matchmaking sessions is stored on a server. Based on this data, the server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state. Using this avatar, the user can evaluate themselves from a third-person perspective. A mock conversation between avatars is displayed on the device, and by observing the interactions between the avatars, users can more objectively identify areas for improvement.

[1263] This system allows users to receive objective and detailed feedback, and improve their chances of finding a partner based on highly accurate advice provided by the emotion engine.

[1264] The processing flow will be explained below.

[1265] Step 1:

[1266] A user accesses the system and logs in by entering the required information on the login screen.

[1267] Step 2:

[1268] The device checks the user's information and displays the home screen. The user then moves to the profile setting screen and enters the necessary information (annual income, appearance, hobbies, romantic history, etc.).

[1269] Step 3:

[1270] The terminal sends the entered user information to the server, where it is stored in a database.

[1271] Step 4:

[1272] Based on the information received by the server, an AI algorithm is used to calculate a score for each element, such as annual income, appearance, hobbies, and profile text, and these are then combined to calculate an overall matchmaking ability score.

[1273] Step 5:

[1274] The server generates the calculated score and detailed feedback information. For example, if a user's annual income is highly rated but their profile text is weak, the server will suggest specific ways to improve the profile.

[1275] Step 6:

[1276] The server sends the generated feedback and score information to the terminal, which displays it to the user.

[1277] Step 7:

[1278] Next, the user selects a virtual matchmaking session and sets up the virtual matchmaking session. The server then starts the virtual matchmaking generation AI and generates a dialogue scenario.

[1279] Step 8:

[1280] The generative AI starts the virtual matchmaking session and makes an initial statement (e.g., "Nice to meet you. What are your hobbies?"), to which the user responds (e.g., "I like soccer and play futsal with my friends on weekends").

[1281] Step 9:

[1282] The server records the conversation content during the virtual matchmaking session, as well as the user's facial expressions and voice in real time, and each piece of data is prepared for analysis by the emotion engine.

[1283] Step 10:

[1284] The emotion engine analyzes the user's facial expressions and voice to generate emotion data, for example, to determine whether the user is nervous.

[1285] Step 11:

[1286] The server analyzes the emotional data and conversation data, evaluating the quality of speech, the level of facial relaxation, the frequency of smiling, etc. The evaluation results are compiled as a score.

[1287] Step 12:

[1288] The server generates an evaluation score and specific feedback (e.g., "Ask people more questions more often" or "Smile more and keep a relaxed expression").

[1289] Step 13:

[1290] The server sends the evaluation score and feedback to the device, which displays it to the user.

[1291] Step 14:

[1292] Users participate in multiple virtual matchmaking sessions, and the data is stored on a server. The server then aggregates this data and generates a "personal avatar" based on the user's behavioral patterns and emotional data.

[1293] Step 15:

[1294] The server generates a conversation scenario between the generated "self avatars" and sends it to the device, which then displays it to the user.

[1295] Step 16:

[1296] Users observe conversations between avatars and self-evaluate from a third-party perspective to determine areas for improvement. Based on the information gained through this process, users can improve their behavior in actual matchmaking.

[1297] Example 2

[1298] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1299] Conventional matchmaking systems only require users to enter basic information, limiting the amount of feedback they can provide. They also lack the means for self-evaluation through detailed analysis via emotion recognition or virtual matchmaking, or avatar generation. This makes it difficult for users to receive more accurate feedback and specific improvement measures.

[1300] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1301] In this invention, the server includes means for a user to input his / her own information, means for analyzing the input information and determining the marriage activity potential, means for providing feedback based on the determined marriage activity potential, means for analyzing the facial expressions and voice of the user during the virtual matchmaking using an emotion engine and recognizing emotions, means for conducting the virtual matchmaking, means for evaluating the conversation and facial expressions during the virtual matchmaking, means for enhancing the feedback based on the evaluation results, means for generating an avatar based on the user's behavioral patterns, and means for displaying the conversation between the avatars. This allows the user to receive detailed and objective feedback and obtain specific measures for self-improvement through emotion recognition and virtual matchmaking.

[1302] "User" means an individual who accesses the system, enters their information, and receives feedback.

[1303] "Information input" refers to the act of a user providing basic information about themselves (annual income, appearance, hobbies, romantic history, etc.) to the system.

[1304] "Analysis" refers to the means of evaluating the entered user information and determining their potential for marriage.

[1305] "Marriage Ability" is a comprehensive evaluation score of a user's marriage activities, calculated based on attributes such as annual income, appearance, hobbies, and profile text.

[1306] "Feedback" refers to information that points out a user's strengths and weaknesses based on analysis results and provides specific measures for improvement.

[1307] The "emotion engine" is a technology that analyzes the user's facial expressions and voice during a virtual matchmaking session and recognizes their emotions in real time.

[1308] "Virtual matchmaking" is a feature in which a generative AI model makes the first statement and simulates a matchmaking session, which progresses through interaction with the user.

[1309] A "generative AI model" is an artificial intelligence that generates conversations with users during virtual matchmaking and feedback sessions.

[1310] "Conversation and facial expression evaluation" is a method of analyzing the content of a user's remarks and facial expression data during a virtual matchmaking session and calculating an overall evaluation score.

[1311] "Enhanced feedback" refers to a means of providing more specific feedback that has a greater effect on improvement, based on evaluation results and emotional recognition.

[1312] An "avatar" is a virtual self-image generated based on the user's behavioral patterns and emotional data, allowing for self-evaluation from a third-party perspective.

[1313] "Avatar-to-avatar conversation" is a feature that displays multiple avatars having a simulated conversation using a generative AI model.

[1314] The matchmaking support system of the present invention allows users to input their own information, evaluate their matchmaking ability through virtual matchmaking, and provides highly accurate feedback and improvement measures using an emotion engine. This system includes a terminal for users to input information, a server for analyzing the information and evaluating matchmaking ability, and various software for providing feedback.

[1315] Hardware and software used

[1316] This system uses the following hardware and software:

[1317] Device: An electronic device (computer, smartphone, tablet, etc.) where users input information and view feedback and results.

[1318] Server: A computer that manages user information, analyzes it, and generates feedback.

[1319] Emotion engine: Dedicated software for analyzing the user's facial expressions and voice in real time (e.g., Emotion API)

[1320] Generative AI models: artificial intelligence platforms (e.g., GPT-3) for simulating virtual matchmaking conversations

[1321] Specific examples of processing

[1322] Input and analysis of user information

[1323] The user uses the device to input their basic information (annual income, appearance, hobbies, love history, etc.). For example, they input information such as "annual income of 6 million yen," "appearance: height 175 cm, weight 70 kg," and "hobbies: soccer and cooking." The device sends this information to the server, which stores it in a database.

[1324] The server uses an AI algorithm to determine a person's marriage potential based on the received user information. For example, an annual income of 6 million yen is rated high, while a height of 175 cm and a weight of 70 kg is rated medium. The server evaluates this information based on a scoring system and calculates an overall marriage potential score. This score is sent back to the device and displayed to the user.

[1325] Providing feedback

[1326] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates appropriate feedback, such as suggestions like "take a more professional profile picture" or "add detailed stories about your hobbies." This feedback is sent from the server to the user's device and displayed.

[1327] Emotion recognition by emotion engine

[1328] Once the virtual matchmaking session begins, the server's built-in emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotions. For example, if the user is nervous, the emotion engine will detect this from their facial expressions and tone of voice and send that data to the server.

[1329] Virtual matchmaking

[1330] When a user sets up a virtual matchmaking session, the generative AI model makes the first statement and simulates the matchmaking. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?", and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." The content of this conversation, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[1331] Enhanced speech and facial expression assessment and feedback

[1332] The server analyzes the conversation content during the virtual matchmaking session, as well as the user's facial expressions and emotional data, to calculate an overall evaluation score. It also strengthens feedback based on the results of the emotion engine, providing specific improvement measures such as "If you feel nervous, take a deep breath and relax" and "Introduce yourself calmly with positive emotions." This feedback is sent to the device and displayed to the user.

[1333] Create your own avatar

[1334] The server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state based on the user's behavioral and emotional data accumulated through virtual matchmaking. The user can use this avatar to evaluate themselves from a third-person perspective and observe simulated conversations between avatars.

[1335] Prompt Sentence Examples

[1336] Please rate your marriage strength based on the user information below and provide specific feedback and suggestions for improvement.

[1337] User Information:

[1338] Annual income: 6 million yen

[1339] Appearance: Height 175cm, Weight 70kg, Photo (URL)

[1340] Hobbies: Soccer, cooking

[1341] Romance history: 3 times

[1342] Matchmaking Settings:

[1343] First utterance from the generated AI: "Nice to meet you. What are your hobbies?"

[1344] User response:

[1345] "I like soccer and play futsal with my friends on the weekends."

[1346] The system of the present invention provides detailed and objective feedback to users throughout these processes and suggests specific strategies for self-improvement through emotion recognition and virtual matchmaking.

[1347] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1348] Step 1: Enter your user information

[1349] Users access the system through their terminal and enter their basic information (annual income, appearance, hobbies, love history, etc.). For example, they might enter data such as "annual income of 6 million yen," "appearance: photo of height 175 cm, weight 70 kg," and "hobbies: soccer and cooking" into a form. This input information is sent from the terminal to the server, which then stores it in a database.

[1350] Input: User information such as annual income, appearance, hobbies, and romantic history

[1351] Data processing: Save the input information as structured data

[1352] Output: Saved user information

[1353] Step 2: Analysis of your marriage potential

[1354] The server retrieves user information stored in a database and uses an AI algorithm to determine a person's marriage potential. For example, an annual income of 6 million yen is rated high, while a height of 175 cm is rated neutral. The server calculates a score for each attribute and generates an overall marriage potential score. This score is sent back to the device and displayed to the user.

[1355] Input: User information stored in the database

[1356] Data calculation: Scoring each attribute using AI algorithms

[1357] Output: Overall marriage vitality score and its breakdown

[1358] Step 3: Provide feedback

[1359] The server analyzes the user's strengths and weaknesses based on their matchmaking score and generates specific feedback, such as suggestions like "take a more professional profile picture" or "add more detailed stories about your hobbies." This feedback is sent from the server to the user's device and displayed.

[1360] Input: Marital vitality score and its breakdown

[1361] Data processing: feedback generation based on scores

[1362] Output: Analysis of strengths and weaknesses and specific feedback

[1363] Step 4: Emotion Recognition with the Emotion Engine

[1364] During the virtual matchmaking session, the server's built-in emotion engine analyzes the user's facial expressions and voice in real time to recognize their emotions. For example, if the user is nervous, the emotion engine will detect this from their facial expressions and tone of voice, and the data will be sent to the server in real time.

[1365] Input: facial expression data and voice data of the user during the virtual matchmaking session

[1366] Data Computation: Real-time Emotion Analysis with an Emotion Engine

[1367] Output: Emotion recognition result

[1368] Step 5: Conduct a virtual matchmaking session

[1369] The user sets up a virtual matchmaking session, and the generative AI model makes the first utterance, simulating the matchmaking. For example, the generative AI asks, "Nice to meet you. What are your hobbies?", and the user responds, "I like soccer, and I play futsal with my friends on the weekends." The content of this conversation, the user's facial expressions, and the emotion recognition results are all recorded by the server.

[1370] Input: The initial utterance of the generative AI model, and the user's response

[1371] Data processing: Recording of conversation content, facial expressions, and emotional data

[1372] Output: Recorded virtual matchmaking data

[1373] Step 6: Evaluate speech and facial expressions

[1374] The server analyzes the content of the conversation during the virtual matchmaking session, as well as the user's facial expressions and emotional data, and calculates a comprehensive evaluation score. For example, the evaluation criteria include conversational ability, quality of questions, reaction to the other person, level of facial relaxation, and frequency of smiling. The evaluation results are sent from the server to the user's device and displayed to them.

[1375] Input: Recorded virtual matchmaking data (conversation content, facial expressions, emotional data)

[1376] Data calculation: Calculation of overall evaluation score based on evaluation criteria

[1377] Output: Overall evaluation score and breakdown of evaluation results

[1378] Step 7: Reinforcing feedback

[1379] The server then provides more specific and effective feedback based on the results of the emotion engine. For example, it offers suggestions for improvement such as "If you feel nervous, take a deep breath and relax" or "Introduce yourself calmly and with positive emotions." This feedback is sent from the server to the device and displayed to the user.

[1380] Input: Overall evaluation score and emotion recognition results

[1381] Data processing: Generating feedback based on emotion recognition results

[1382] Output: Specific improvements added

[1383] Step 8: Create your own avatar

[1384] The server generates a "self-avatar" that reflects the user's behavioral characteristics and emotional state based on the user's behavioral and emotional data accumulated through virtual matchmaking. The user can use this avatar to evaluate themselves from a third-person perspective and observe simulated conversations between avatars.

[1385] Input: Accumulated behavioral and emotional data

[1386] Data Computing: Avatar Generation Based on Behavioral Characteristics and Emotional States

[1387] Output: Generated self-avatar and simulated conversation data

[1388] (Application example 2)

[1389] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1390] Conventional matchmaking support systems have difficulty not only objectively evaluating a user's matchmaking ability and providing specific improvement measures, but also analyzing their emotional state and providing real-time feedback. Furthermore, they lacked technology for generating avatars based on the user's behavioral patterns and for incorporating the results of emotional analysis during virtual matchmaking into feedback. This meant that users were unable to obtain specific guidelines for self-improvement, preventing them from effectively progressing with their matchmaking efforts.

[1391] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for a user to input their own information, a means for analyzing the input information and determining their marriage ability, a means for providing feedback based on the determined marriage ability, a means for conducting a virtual matchmaking session, a means for evaluating the conversation and facial expressions during the virtual matchmaking session, a means for generating initial comments using a generative AI model, a means for analyzing the user's emotional state, a means for providing additional feedback based on the analyzed emotional state, a means for generating an avatar based on the user's behavioral patterns, and a means for displaying conversations between avatars. This not only allows users to objectively evaluate their marriage ability, but also allows them to receive real-time feedback and improvement measures based on the emotion analysis results. Furthermore, the avatar reflecting their own behavioral patterns provides specific guidelines for self-improvement, which can lead to more effective progress in their marriage search.

[1392] "User information" refers to basic information that users enter into the system, including data such as annual income, appearance, hobbies, and romantic history.

[1393] "Marriage power" is an index that evaluates the effectiveness and likelihood of success of a user's marriage search, analyzed based on user information.

[1394] "Feedback" refers to specific improvement measures and advice provided to users based on their analyzed marriage vitality and emotional state.

[1395] "Virtual matchmaking" refers to simulated interactions that users have with generative AI models and other users within the system.

[1396] "Generative AI model" refers to technology that uses artificial intelligence to generate initial utterances and simulate interactions with users.

[1397] "Emotion analysis" refers to technology that recognizes and analyzes a user's emotional state in real time from their facial expressions and voice.

[1398] An "avatar" is a virtual character that is generated based on the user's behavioral patterns and emotional state.

[1399] "Conversation evaluation" refers to a technology that evaluates the content of conversations and facial expressions of users during virtual matchmaking sessions, and provides indicators that are useful for improving their chances of finding a partner.

[1400] A "prompt sentence" refers to the initial utterance or input for a generative AI model to simulate a dialogue with a user.

[1401] "Additional feedback" refers to additional improvements or advice provided to users in real time based on sentiment analysis results and conversation evaluation.

[1402] A system for implementing the present invention uses the following hardware and software.

[1403] Hardware used

[1404] PC or smartphone

[1405] (Optional) Smart glasses, head-mounted display

[1406] Software used

[1407] Python

[1408] Libraries for AI algorithms (e.g., EmotionEngine, MatchmakingEngine)

[1409] Natural language explanation of program processing

[1410] The system begins with the user entering basic information such as annual income, appearance (specifically, height and weight), hobbies, and romantic history via smartphone or computer, which is then sent to a server. The server receives this data and uses an AI algorithm (Matchmaking Engine) to determine a person's potential for marriage.

[1411] The determined marriage ability is notified to the user as a score for each item and an overall score. Next, a feedback system extracts the user's strengths and weaknesses and suggests specific improvement measures. This feedback is displayed on the screen of a smartphone or computer.

[1412] The user sets up a virtual matchmaking session, and the generative AI model makes the first statement. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?"

[1413] When the user responds, the response is analyzed by an emotion analysis engine (Emotion Engine), and the user's emotional state is recognized in real time. For example, if the user responds, "I like soccer and play futsal with friends on the weekends," emotion analysis is performed based on the response. The analysis results are sent to the server and provided to the user as additional feedback. This feedback may include advice such as, "If you feel tense, take a deep breath and try to relax."

[1414] In addition, an avatar is generated based on the user's behavioral patterns, and conversations between these avatars are displayed to the user, providing specific guidelines for self-improvement. During this process, the server stores a series of data, allowing users to repeat the simulation multiple times.

[1415] Examples of concrete examples and prompts

[1416] A specific example would be a simulation in which a user inputs information such as "annual income of 6 million yen" and "hobbies: soccer and cooking," and the generative AI model asks, "Nice to meet you. What are your hobbies?"

[1417] Example prompt sentence:

[1418] "Calculate a marriageability score based on the user's profile information, and use an emotion engine to analyze their emotional state and provide feedback during virtual matchmaking."

[1419] In this way, the present invention provides a system that evaluates a user's marriage ability and provides feedback and specific improvement measures based on emotion analysis.

[1420] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1421] Step 1: Enter your user information

[1422] Users enter their basic information (annual income, appearance, hobbies, dating history, etc.) via their device (PC or smartphone). This information is sent from the device to the server. Input is done in form format, and is completed by filling in the required fields. The entered data is sent to the server in JSON format and saved in a database.

[1423] Step 2: Determine your marriage potential

[1424] The server analyzes the received user information using an AI algorithm (Matchmaking Engine). Specifically, each item, such as annual income, appearance, and hobbies, is scored separately, and the scores are added together to calculate an overall matchmaking score. For example, an annual income of 6 million yen would be a high score, and a diverse range of hobbies would be a higher rating. The analysis results in scores for each item and an overall score, which are then sent back to the device and displayed to the user.

[1425] Step 3: Provide feedback

[1426] The server extracts the user's strengths and weaknesses based on the determined matchmaking power score. For example, the analysis may reveal that the user has a high annual income but a narrow range of hobbies. Based on this information, the server generates specific improvement measures (e.g., "take a more professional profile picture" or "add detailed stories about your hobbies") and sends them to the device as feedback. The user can use this as a guide for self-improvement.

[1427] Step 4: Conduct a virtual matchmaking session

[1428] The user sets up a virtual matchmaking session on their device. The generative AI model makes an initial statement, and the user responds. For example, the generative AI might ask, "Nice to meet you. What are your hobbies?", and the user might reply, "I like soccer, and I play futsal with my friends on the weekends." This is how the virtual matchmaking session progresses, and the statements and responses are recorded.

[1429] Step 5: Analyze emotional state

[1430] The server uses an emotion analysis tool (Emotion Engine) to analyze the user's comments and facial expressions in real time during the virtual matchmaking session. This recognizes the user's emotional state from the tone of voice and facial expressions when they speak, and obtains the analysis results. For example, it can identify emotions such as tension or relaxation. This data is sent to the server, and the analysis results are returned to the device.

[1431] Step 6: Provide additional feedback

[1432] The server generates more specific feedback based on the results of the emotion analysis, such as advice like, "If you feel tense, take a deep breath and try to relax." This feedback is sent to the device and displayed to the user in real time.

[1433] Step 7: Generate and display the avatar

[1434] The server generates a "self-avatar" based on the user's behavioral patterns and emotional state. Conversations between the generated avatars are simulated and displayed on the device. By observing the avatars' interactions, users can obtain specific guidelines for self-improvement.

[1435] Through these steps, users can receive an assessment of their own matchmaking ability, obtain recommendations for improvement, and experience a virtual matchmaking experience. By combining generative AI models with sentiment analysis methods, it is possible to provide users with more accurate feedback and improve their chances of success in matchmaking.

[1436] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1437] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1438] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1439] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1440] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1441] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1442] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1443] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1444] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1445] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1446] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1447] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1448] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1449] 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.

[1450] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1451] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1452] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1453] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1454] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1455] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1456] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1457] The following is further disclosed regarding the above embodiment.

[1458] (Claim 1)

[1459] a means for users to enter their information;

[1460] A means of analyzing the input information and determining the marriage potential,

[1461] a means for providing feedback based on the determined marital strength;

[1462] A means for conducting a virtual matchmaking session;

[1463] A means for evaluating conversations and facial expressions during virtual matchmaking;

[1464] means for generating an avatar based on a user's behavioral patterns;

[1465] a means for displaying conversations between avatars;

[1466] A system including:

[1467] (Claim 2)

[1468] 2. The system according to claim 1, further comprising means for allowing a user to record his or her own actions and statements during the virtual matchmaking session and to make an evaluation based on the recording.

[1469] (Claim 3)

[1470] 2. The system according to claim 1, wherein the feedback providing means extracts strengths and weaknesses from the information input by the user and presents specific improvement measures based on the strengths and weaknesses.

[1471] "Example 1"

[1472] (Claim 1)

[1473] a means for users to enter their information;

[1474] A means of analyzing and determining your marriage potential based on the information you enter,

[1475] a means for providing feedback based on the determined marital vitality score;

[1476] a means for conducting a virtual interaction;

[1477] a means for assessing speech and facial expressions during virtual interactions;

[1478] A means for generating an avatar based on a user's behavioral characteristics;

[1479] a means for displaying interactions between avatars;

[1480] A system including:

[1481] (Claim 2)

[1482] 10. The system of claim 1, further comprising means for allowing a user to record his or her actions and statements during the virtual interaction and to make an evaluation based on the recording.

[1483] (Claim 3)

[1484] 2. The system according to claim 1, wherein the feedback providing means extracts strengths and weaknesses from the information input by the user and presents specific improvement measures based on the strengths and weaknesses.

[1485] "Application Example 1"

[1486] (Claim 1)

[1487] a means for users to enter their information;

[1488] A means of analyzing the input information and determining the marriage potential,

[1489] a means for providing feedback based on the determined marital strength;

[1490] A means for conducting a virtual matchmaking session;

[1491] A means for evaluating conversations and facial expressions during virtual matchmaking;

[1492] means for generating an avatar based on a user's behavioral patterns;

[1493] a means for displaying conversations between avatars;

[1494] A means of providing real-time user feedback in physical stores;

[1495] A system including:

[1496] (Claim 2)

[1497] 2. The system according to claim 1, further comprising means for allowing a user to record his or her own actions and statements during the virtual matchmaking session and to make an evaluation based on the recording.

[1498] (Claim 3)

[1499] 2. The system according to claim 1, wherein the feedback providing means extracts strengths and weaknesses from the information input by the user and presents specific improvement measures based on the strengths and weaknesses.

[1500] "Example 2: Combining Emotion Engines"

[1501] (Claim 1)

[1502] a means for users to enter their information;

[1503] A means of analyzing the input information and determining the marriage potential,

[1504] a means for providing feedback based on the determined marital strength;

[1505] A means for analyzing the facial expressions and voice of a user during a virtual matchmaking session using an emotion engine to recognize emotions;

[1506] A means for conducting a virtual matchmaking session;

[1507] A means for evaluating conversations and facial expressions during virtual matchmaking;

[1508] a means of enhancing feedback based on the assessment results;

[1509] means for generating an avatar based on a user's behavioral patterns;

[1510] ...

Claims

1. a means for users to enter their information; A means of analyzing the input information and determining the marriage potential, a means for providing feedback based on the determined marital strength; A means for conducting a virtual matchmaking session; A means for evaluating conversations and facial expressions during virtual matchmaking; means for generating an avatar based on a user's behavioral patterns; a means for displaying conversations between avatars; A system including:

2. 2. The system according to claim 1, further comprising means for allowing a user to record his or her own actions and statements during the virtual matchmaking session and to make an evaluation based on the record.

3. 2. The system according to claim 1, wherein the feedback providing means extracts strengths and weaknesses from the information input by the user and presents specific improvement measures based on the strengths and weaknesses.

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