System

Abstract

To provide a system for achieving highly accurate matching reflecting the characteristics or desire of a user.SOLUTION: Means for inputting basic information, means for storing the basic information in a basic information database, means for sending a request to initiate a sample chat with an artificial intelligence, means for generating a chat session with the artificial intelligence, means for providing a chat interface, means for collecting and analyzing chat content, means for generating an avatar reflecting characteristics of a user, means for setting a chat session between avatars and recording chat content, means for analyzing the recorded chat content and calculating a matching degree, means for recommending a chat log having a high matching degree to the user, and means for displaying the chat content to the user, A system comprising: means for confirming; means for selecting a match request; and means for completing a match if both users request a match.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] Currently, many matching applications exist, but users with little romantic experience have difficulty communicating and assessing compatibility at first meeting. Conventional "search-based" and "setting-based" matching methods cannot provide sufficient support for these users, making it difficult to perform effective matching. The resulting decline in marriage rates and birthrates is also a serious problem. To solve these problems, the present invention aims to provide a system that generates avatars based on users' conversational habits and desired conditions, and then allows these avatars to self-learn and recommend partners with a high degree of compatibility. [Means for solving the problem]

[0005] The present invention provides a system in which a user inputs basic information via a terminal, which is received by a server and stored in a database. Furthermore, the user engages in a sample chat with an artificial intelligence, and the server collects and analyzes the chat content. Based on the analysis results, the server generates an avatar that reflects the user's characteristics and sets up a chat session with the avatar of another user. The server records and analyzes the chat content between the avatars and calculates the degree of matching. The server then recommends chat logs with a high degree of matching to the user, and the user can review these and then select whether or not they wish to be matched. If both users wish to be matched, the server establishes a match and provides a means for notifying both users of the match.

[0006] "User" refers to a person who uses an application.

[0007] "Terminal" refers to an electronic device that a user uses to operate an application.

[0008] "Server" refers to a computer system that receives and processes information sent by users and provides various services.

[0009] "Basic information" refers to personal data such as name, age, gender, hobbies, and desired conditions that users enter when registering.

[0010] "Database" refers to a part of a computer system that systematically stores and manages user information, chat logs, etc.

[0011] "Generative AI (artificial intelligence)" refers to artificial intelligence technology used to conduct sample chats with users and analyze their characteristics.

[0012] A "sample chat" refers to a series of conversations a user has with an artificial intelligence to understand the user's conversational tendencies and desired conditions.

[0013] An "avatar" refers to a virtual representative character that is generated to reflect the characteristics and wishes of a user.

[0014] A "chat session" refers to the duration and course of a series of conversations between users or avatars.

[0015] "Analysis" refers to the process of evaluating user characteristics and chat content from acquired data and deriving insights and conclusions.

[0016] The "matching degree" is a numerical expression of compatibility obtained by analyzing the chat contents between avatars, and is an index showing the probability that users are compatible with each other.

[0017] "Recommendation" refers to the act of the server suggesting some or all of the matching chat content to the user.

[0018] "Wanting to be matched" refers to the user's intention to check the recommended chat content and select that they would like to actually be matched with that person.

[0019] "Matching established" refers to the server officially matching two people when both users agree to each other's matching.

[0020] "Notification" refers to a message sent by the server to inform the user of information or results. [Brief explanation of the drawings]

[0021] [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

[0022] 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.

[0023] First, the terms used in the following description will be explained.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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."

[0029] [First embodiment]

[0030] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0031] 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.

[0032] 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).

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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."

[0042] The system of the present invention analyzes the characteristics of a user through a chat session between the user and a generating AI (artificial intelligence) and generates an "avatar" based on the user. The system then allows the avatars to chat with each other, evaluates the degree of matching, and recommends to the user partners with high compatibility. The system of the present invention can be implemented as follows.

[0043] User Registration

[0044] The device provides an interface for users to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand what kind of match the user is looking for.

[0045] Start a sample chat

[0046] The terminal provides the user with a button to start a sample chat. When the user presses this button, the terminal sends a request to start a sample chat to the server. Based on the received request, the server sets up a chat session with the AI ​​and makes the necessary preparations.

[0047] Sample chat

[0048] The server calls the generated AI and starts a chat session between the user and the AI. The device provides the user with a chat interface and helps the user answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions.

[0049] Avatar generation

[0050] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and preferences. This avatar then converses with other avatars on the user's behalf, improving the efficiency of matching users.

[0051] Avatar-to-avatar chat

[0052] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of the avatar chat and calculates the degree of matching (compatibility score).

[0053] Matching evaluation and recommendation

[0054] The server selects chat contents with a high degree of matching and recommends them to the user. The terminal displays the recommended chat contents to the user and confirms whether the user actually wants to be matched.

[0055] Confirmation and establishment of matching requests

[0056] If a user checks the recommended chat content and wishes to be matched, the device sends that request to the server. The server then checks whether both users wish to be matched, and if both agree, the match is established. Once a match is established, the server notifies both users.

[0057] Specific examples

[0058] For example, suppose that User A and User B use this system. User A first enters basic information and sends it to the server. Next, User A participates in a sample chat with the generation AI, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates an avatar for User A.

[0059] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[0060] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[0061] This system will make it easier for users with little dating experience to find a suitable partner, making it possible to combat the declining birthrate and increase the number of marriages.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] The user inputs basic information (such as name, age, gender, hobbies, and desired partner conditions) via the terminal, which then sends this information to the server.

[0065] Step 2:

[0066] The server stores the received basic information in a database.

[0067] Step 3:

[0068] The user presses the start button for the sample chat via the terminal, and the terminal sends a request to start the sample chat to the server.

[0069] Step 4:

[0070] The server calls the generated AI and sets up the chat session. The server notifies the device that it is ready.

[0071] Step 5:

[0072] The device provides a chat interface to the user, who initiates a dialogue with the AI ​​and answers questions posed by it.

[0073] Step 6:

[0074] The server collects and analyzes chat content in real time, extracting information such as the user's personality, conversational tendencies, and desired conditions.

[0075] Step 7:

[0076] The server generates an avatar that reflects the user's characteristics based on the information extracted.

[0077] Step 8:

[0078] The server sets up chat sessions with other users' avatars, and the avatars converse with each other.

[0079] Step 9:

[0080] The server records the chat content between avatars and analyzes the match score (compatibility score) based on the records.

[0081] Step 10:

[0082] The server selects chat content with a high degree of matching and creates recommended chats.

[0083] Step 11:

[0084] The device displays the recommended chat content to the user, and the user confirms the chat content.

[0085] Step 12:

[0086] The user selects their desired match, and the device sends that preference to the server.

[0087] Step 13:

[0088] The server checks whether both users want to be matched, and if both agree, the server makes the match happen.

[0089] Step 14:

[0090] The server will notify both users that a match has been made.

[0091] Example 1

[0092] 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."

[0093] Conventional online matching systems have difficulty in matching users based on their individual characteristics and desired conditions, making it difficult to provide effective matching results. Furthermore, protecting user privacy and achieving highly accurate matching have been issues. This has made it difficult for users to find a suitable partner, resulting in reduced matching efficiency.

[0094] 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.

[0095] In this invention, the server includes: means for a user to input basic information via a terminal; means for the server to receive the basic information and store it in a storage device; means for the user to issue a request to start a sample chat with an AI; means for the terminal to send the request to the server; means for the server to generate an interactive session with the AI ​​based on the request; means for the terminal to provide an interactive interface to the user; means for the server to collect and analyze the content of the dialogue between the user and the AI; means for the server to generate a digital avatar that reflects the user's characteristics based on the analysis results; means for the server to set up an interactive session between the digital avatars and record the content of the dialogue; means for the server to analyze the recorded content of the dialogue and calculate a compatibility score; means for the server to recommend a dialogue log with a high compatibility score to the user; means for the terminal to display the recommended content of the dialogue to the user and confirm it; means for the user to select a desired match; means for the terminal to send the selected state of the desired match to the server; and means for the server to establish a match if both users desire a match. This enables highly accurate matching that reflects the characteristics and preferences of users.

[0096] "User" refers to an individual who uses the system to input basic information and is matched through dialogue with artificial intelligence.

[0097] "Terminal" refers to an electronic device that allows a user to input basic information and use an interactive interface. Examples include smartphones and computers.

[0098] "Server" refers to a central computer system that receives, stores, and processes information sent by users and terminals.

[0099] "Basic information" refers to the personal information and desired conditions that a user enters into the system, and includes, for example, name, age, gender, hobbies, and desired partner conditions.

[0100] "Artificial intelligence" is a general term for programs and systems that interact with users and analyze the information they collect. Examples include generative AI models.

[0101] A "sample chat" is an interactive session that a user has with an AI, with the purpose of gathering information about the user's characteristics and desired conditions.

[0102] "Dialogue interface" refers to the screen display and input means that allow the user to interact with artificial intelligence.

[0103] A "digital avatar" is a character with a virtual personality that reflects the characteristics and wishes of a user, and is generated to interact with other avatars.

[0104] "Dialogue content" refers to messages and conversation logs in dialogue between a user and an artificial intelligence, or between digital avatars.

[0105] The "compatibility" is a numerical value or index that indicates the compatibility between users, calculated by analyzing the content of the conversation.

[0106] "Recommendation" refers to the act of suggesting compatible partners and conversation content to the user based on the compatibility calculated by the server.

[0107] "Matching preference" refers to a user's expression of intent to actually be matched with the recommended partner or the content of the conversation.

[0108] "Notification" refers to the act of the server transmitting information to the user, and refers to a message informing the user of a match and its results.

[0109] The system of the present invention begins when a user inputs basic information via a terminal, which is then received and stored by a server. The user then engages in a sample chat with an AI, and a digital avatar that reflects the user's characteristics is generated by analyzing the content of the conversation. The system then provides a series of processes by having the avatars chat with each other, evaluating their compatibility, and recommending highly compatible partners to the user. The main processes are explained in detail below.

[0110] Enter and save basic information

[0111] The terminal provides an interface for the user to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the terminal sends the information to the server. The server stores the received information in a database and uses it for subsequent processing. In this case, a relational database management system such as MySQL (registered trademark) is used as the database.

[0112] Start a sample chat

[0113] The device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. Upon receiving the request, the server invokes a generative AI model (e.g., GPT-3 (registered trademark) from OpenAI (registered trademark)) and sets up a chat session with the user. The device then provides the user with a chat interface, allowing the user to answer questions posed by the AI.

[0114] Collection and analysis of chat content

[0115] The server collects chat content between the user and the AI ​​in real time. A natural language processing library (e.g., NLTK) is used to analyze the collected data. The analysis results are used to extract characteristics such as the user's personality, conversational tendencies, and desired conditions.

[0116] Digital avatar generation

[0117] The server then generates a digital avatar that reflects the user's characteristics and preferences based on the analysis results. This avatar then engages in simulated conversations on behalf of the user, improving the efficiency of matching users.

[0118] Avatar-to-avatar chat settings

[0119] The server sets up chat sessions between the generated digital avatars. The avatars converse with each other and record the conversations. The server analyzes the conversations and calculates the compatibility of each avatar. Machine learning algorithms are often used to calculate compatibility.

[0120] Matching result recommendations

[0121] The server selects chat content with a high degree of compatibility and recommends it to the user. The terminal displays the recommended chat content to the user and confirms whether the user actually wants to be matched. If the user confirms the recommended content and wishes to be matched, the terminal transmits the selection status to the server.

[0122] Matching is completed

[0123] The server confirms that both users are willing to match, and if both agree, the match is established. Once a match is established, the server notifies both users. Notifications can be sent via email or in-app message.

[0124] Specific examples

[0125] For example, let's consider the case where User A and User B use the system. User A first enters basic information and sends it to the server. Next, User A participates in a sample chat with the generation AI, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates a digital avatar for User A.

[0126] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B and sets up a chat session between the two avatars. The content of the conversation is recorded, and the server calculates the compatibility based on the analysis results. If the compatibility is high, it is recommended to User A and User B.

[0127] If User A and User B check the recommended chat content and agree to be compatible, the server will match them and notify them, allowing users to find compatible partners more effectively and efficiently.

[0128] Prompt Sentence Examples

[0129] By inputting questions such as "What are your hobbies?", "How do you spend your holidays?", and "What kind of person is your ideal partner?" into the generative AI model, the user's characteristics and preferences can be extracted.

[0130] Through the above process, the system can analyze the user's characteristics and preferences in detail and achieve highly accurate matching.

[0131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0132] Step 1: Enter and submit user information

[0133] The terminal provides an interface for the user to input basic information (such as name, age, sex, hobbies, and desired partner conditions).

[0134] Input: The user enters basic information into the terminal.

[0135] How it works: The user enters basic information and presses the submit button.

[0136] Output: The terminal sends the entered information to the server.

[0137] Step 2: Receiving and storing user information

[0138] The server stores the received user basic information in a database.

[0139] Input: Basic information of the user sent from the device.

[0140] Operation: The server analyzes the received information and stores it in a database, such as MySQL.

[0141] Output: User information stored in the database.

[0142] Step 3: Prepare to start a sample chat

[0143] The terminal provides the user with a button to start a sample chat.

[0144] Input: User presses the start button to begin a sample chat.

[0145] Operation: The device sends a request to the server to start a sample chat.

[0146] Output: A sample chat start request sent to the server.

[0147] Step 4: Invoke the generative AI model and set up a chat session

[0148] Based on the received request, the server invokes the generative AI model and sets up a chat session with the user.

[0149] Input: A sample chat start request.

[0150] How it works: The server invokes a generative AI model (e.g., OpenAI's GPT-3) and sets up a chat session.

[0151] Output: The configured chat session.

[0152] Step 5: Providing a chat interface

[0153] The device provides the user with a chat interface, creating an environment in which the user can interact with the AI.

[0154] Input: The configured chat session.

[0155] Behavior: The device displays and provides the user with a chat interface (text boxes, send buttons, etc.).

[0156] Output: A chat interface available to the user.

[0157] Step 6: Collecting and analyzing chat content

[0158] The server collects and analyzes chat content between the user and the generative AI model in real time.

[0159] Input: The interaction between the user and the generative AI model.

[0160] How it works: The server collects chat content and analyzes it using a natural language processing library (e.g., NLTK). Through the analysis, it extracts information about the user's personality, conversational tendencies, and desired conditions.

[0161] Output: User characteristic information as the analysis result.

[0162] Step 7: Generate a digital avatar

[0163] Based on the analysis results, the server generates a digital avatar that reflects the user's characteristics and wishes.

[0164] Input: User characteristics information.

[0165] How it works: The server generates a digital avatar based on the user's characteristics.

[0166] Output: The generated digital avatar.

[0167] Step 8: Setting up a chat session between avatars

[0168] The server sets up a chat session between the generated digital avatars.

[0169] Input: A generated digital avatar.

[0170] How it works: A server sets up chat sessions between digital avatars and records the conversations.

[0171] Output: Configured avatar chat sessions and recorded dialogue.

[0172] Step 9: Record and analyze chat content

[0173] The server records the content of the conversation between the avatars and analyzes the content.

[0174] Input: Conversation between avatars.

[0175] How it works: The server analyzes the recorded conversations and calculates the relevance using machine learning algorithms.

[0176] Output: The calculated fitness.

[0177] Step 10: Recommending matching results

[0178] The server selects dialogue content with high suitability and recommends it to the user.

[0179] Input: The calculated fitness.

[0180] Operation: The server selects the dialogue content to recommend based on the relevance result and creates a recommendation list.

[0181] Output: Recommended dialogue for the user.

[0182] Step 11: Confirm your match preference

[0183] The terminal displays the recommended dialogue content to the user and provides a means for the user to confirm it.

[0184] Input: Recommended dialogue.

[0185] Operation: The device displays the recommendations to the user and allows the user to select a match.

[0186] Output: Confirmation of user's match preference.

[0187] Step 12: Send your match request and get it done

[0188] If the user selects a match, that information is sent to the server.

[0189] Input: User's match preference selection.

[0190] Operation: The device sends the user's selection status to the server. The server confirms whether both users wish to be matched and establishes the match.

[0191] Output: Matches made and notifications.

[0192] Through the above processing steps, the system can analyze the user's characteristics and preferences in detail and achieve highly accurate matching.

[0193] (Application example 1)

[0194] 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."

[0195] To improve production efficiency in factories, it is important to create optimal team structures based on the characteristics of each robot. However, efficient team building is difficult because there is no established method for evaluating the compatibility and collaborative effectiveness of factory robots. The present invention aims to provide a means to solve this problem.

[0196] 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.

[0197] In this invention, the server includes means for a user to input basic information via a terminal, means for the server to receive the basic information and store it in a database, means for a user to issue a request to start a sample chat with an AI, means for the terminal to send the request to the server, means for the server to generate a chat session with the AI ​​based on the request, means for the terminal to provide a chat interface to the user, means for the server to collect and analyze chat content between the user and the AI, means for the server to generate an avatar that reflects the user's characteristics based on the analysis results, and means for the server to set up a chat session between the avatars and display the chat content. The system includes a means for recording chat content, a means for the server to analyze the recorded chat content and calculate a degree of matching, a means for the server to recommend chat logs with a high degree of matching to the user, a means for the terminal to display the recommended chat content to the user and for confirmation, a means for the user to select a desired match, a means for the terminal to transmit the selected state of the desired match to the server, a means for the server to establish a match when both users desire a match, a means for inputting basic information about the factory robot, a means for generating an avatar based on the characteristics of the robot, and a means for analyzing chat sessions between the avatars and recommending an optimal team composition. This enables evaluation of the compatibility between factory robots and efficient team building.

[0198] "Users" are factory managers and operators who input information and use the system's various functions.

[0199] A "terminal" is a device used by a user to enter information or interact with a system.

[0200] "Basic information" refers to data that includes detailed information about users and robots, such as their characteristics and roles.

[0201] A "server" is a device that receives basic information about users and robots, analyzes and stores the data, and manages and processes the entire system.

[0202] A "database" is a storage device for storing various data such as basic information and analysis results.

[0203] A "request" is a request or command given by a user to a system.

[0204] "Artificial intelligence" refers to computer programs used within the system to generate chat sessions and analyze the characteristics of users and robots.

[0205] A "chat session" is a series of conversations that take place between a user or a robot and an artificial intelligence.

[0206] A "chat interface" is a screen or application that allows users and robots to conduct chat sessions.

[0207] "Chat Content" means the text and messages exchanged during a chat session.

[0208] "Analysis" is the process of analyzing collected chat content and extracting characteristics and trends.

[0209] An "avatar" is a virtual character that reflects the characteristics of a user or a robot.

[0210] "Matching degree" is a score that indicates the compatibility and cooperative effect between avatars.

[0211] "Recommendation" means that the system suggests specific avatars and team compositions to users based on analysis results and compatibility scores.

[0212] "Confirmation" refers to the process by which a user decides whether to accept a recommendation from the system.

[0213] A "factory robot" is an automated mechanical device that performs work on a production line or in a factory.

[0214] A "team composition" is a combination of multiple robot avatars working together to achieve optimal production efficiency.

[0215] This invention is a system that understands the characteristics of robots used in factories and recommends optimal team composition. The system starts operation when a user inputs basic information using a terminal and sends it to a server.

[0216] Enter and save basic information

[0217] The user inputs basic information about the factory robot (model, functions, capabilities, role, etc.) via a terminal. This information is sent to a server and stored in a database. The database is stored in a cloud environment or on a server installed in the factory, where the information is managed and accessed.

[0218] Starting and running a sample chat

[0219] When a user requests a sample chat, the device sends the request to the server. Based on the received request, the server sets up a chat session using a generative AI model. An avatar is generated based on the robot's basic information, and this avatar chats with the AI.

[0220] Collection and analysis of chat content

[0221] The terminal provides the user with a chat interface, and the server collects chat content between the robot and the AI ​​in real time. The collected data is analyzed using a generative AI model to extract information about the robot's characteristics, performance, and collaboration tendencies.

[0222] Avatar generation and matching evaluation

[0223] Based on the analysis results, the server generates avatars that reflect the characteristics of each robot. Chat sessions are set up between the generated avatars, and the chat content is recorded. The server then analyzes the recorded data again to calculate the degree of matching between the avatars, which is used to evaluate their compatibility and collaborative effectiveness.

[0224] Recommendations and Match Confirmation

[0225] The server recommends chat logs of avatars with a high degree of matching to the user. The device displays these recommendations to the user, who then checks the recommendations and selects their desired match. The user's selection is sent to the server, which then works to create the optimal team composition.

[0226] Hardware and Software Use

[0227] The system uses cloud servers, factory servers, and user devices (tablets and PCs) as hardware. It uses Python and the OpenAI API (GPT-4 (registered trademark) model) as software. It also uses a relational database management system (RDBMS) for database management.

[0228] Specific examples

[0229] For example, suppose factory robot A is an arm robot responsible for welding, and robot B is a transport robot responsible for transporting materials. The user enters basic information about these robots into a terminal and sends it to the server. The server generates avatars using a generative AI model and initiates a chat session between the avatars. Below is a specific example of a prompt sentence.

[0230] Example prompt sentence:

[0231] Start chatting as robot named Robo1, model: arm robot, ability: welding, assembly, role: welder.

[0232] A chat session is held based on this prompt, and the server analyzes the collected data and recommends the optimal team composition to the user, thereby improving the factory's production efficiency.

[0233] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0234] Step 1:

[0235] The user uses a terminal to input basic information about the factory robot. Specifically, they input detailed information such as the robot's model, functions, capabilities, and role, and then press the send button. The input information is sent from the terminal to the server. The server stores the received basic information in a database. This information is used to understand the robot's characteristics.

[0236] Step 2:

[0237] A user issues a request to start a sample chat. Specifically, the request is sent to the server by pressing the Start Sample Chat button on the device. Based on the received request, the server generates an avatar for each robot and sets up a chat session using the generative AI model. At this time, a prompt sentence is generated and input into the AI ​​model.

[0238] Step 3:

[0239] The server calls the generative AI model and initiates a chat session with each robot avatar. The device provides the user with a chat interface, and the chat session proceeds in real time. The server collects and stores the content of the conversation between the robot and the AI ​​in real time. The chat content is dynamically generated by the generative AI based on the input prompt.

[0240] Step 4:

[0241] The server analyzes the chat content collected. Using a generative AI model, it analyzes each robot's characteristics, conversational tendencies, and collaboration potential. Specifically, it extracts the robot's characteristic patterns and working behavior from the chat content and converts them into numerical data and categorical information. The results of this analysis are reflected in each robot's avatar.

[0242] Step 5:

[0243] Based on the analysis results, the server generates an avatar that reflects the characteristics of each robot. This avatar is a virtual character that corresponds to the robot's characteristics and is used to interact with other avatars. The generated avatar is displayed in a way that is easy for users and administrators to understand.

[0244] Step 6:

[0245] The server sets up a chat session between the generated avatars. The avatars converse and record the content. Specifically, a conversation between the avatars is simulated to evaluate the effectiveness of collaboration and compatibility. A scenario is generated based on the prompt text, and the conversation between the avatars progresses.

[0246] Step 7:

[0247] The server analyzes the recorded chat content and calculates the degree of matching between avatars. Specifically, it evaluates the consistency and cooperation of the chat content and outputs a numerical compatibility score. This allows the compatibility of each avatar and their suitability as a team to be evaluated.

[0248] Step 8:

[0249] The server recommends chat logs with a high degree of matching to the user. The device displays the recommended chat content to the user, who then confirms it. Specifically, avatars are recommended based on compatibility scores, and the user can view the recommended content and decide whether or not it is suitable for them.

[0250] Step 9:

[0251] The user checks the recommended chat content and selects whether they wish to be matched. The device sends the user's selection to the server. If both users wish to be matched, the server establishes the match and sends appropriate notifications. This determines the optimal team composition and reflects it on the actual production line.

[0252] 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.

[0253] The system of the present invention combines an emotion engine that recognizes the user's emotions, analyzes the user's characteristics through a chat session between the user and a generating AI (artificial intelligence), and generates an "avatar" based on the user. Furthermore, the system allows the generated avatars to chat with each other, evaluates the degree of matching, and recommends to the user partners with high compatibility. The system of the present invention can be implemented as follows.

[0254] User Registration

[0255] The device provides an interface for users to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand what kind of match the user is looking for.

[0256] Start a sample chat

[0257] The terminal provides the user with a button to start a sample chat. When the user presses this button, the terminal sends a request to start a sample chat to the server. Based on the received request, the server sets up a chat session with the AI ​​and makes the necessary preparations.

[0258] Sample chat

[0259] The server calls the generated AI and starts a chat session between the user and the AI. The device provides the user with a chat interface and helps them answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions. At this time, the emotion engine also extracts the user's emotional information and incorporates it into the analysis.

[0260] Avatar generation

[0261] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and wishes. This avatar converses with other avatars on the user's behalf, improving the efficiency of user matching. Emotional information obtained from the emotion engine is also reflected, improving the avatar's expressiveness and enabling more natural and realistic conversations.

[0262] Avatar-to-avatar chat

[0263] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of the avatar chat and calculates the degree of matching (compatibility score).

[0264] Matching evaluation and recommendation

[0265] The server selects chat contents with a high degree of matching and recommends them to the user. The terminal displays the recommended chat contents to the user and confirms whether the user actually wants to be matched.

[0266] Confirmation and establishment of matching requests

[0267] If a user checks the recommended chat content and wishes to be matched, the device sends that request to the server. The server then checks whether both users wish to be matched. If both agree, the server establishes the match and notifies both users.

[0268] Specific examples

[0269] For example, suppose that user A and user B use this system. User A first enters basic information and sends it to the server. Next, user A participates in a sample chat with the generation AI, and the server analyzes the chat content and extracts user A's characteristics. Based on the results, the server generates an avatar for user A. At this time, the emotion engine also analyzes user A's emotional information and reflects it in the avatar.

[0270] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[0271] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[0272] This system will make it easier for users with little dating experience to find a suitable partner, which will help combat the declining birthrate and increase the number of marriages.In addition, the use of an emotion engine will make avatar conversations more natural and friendly, improving the user experience.

[0273] The processing flow will be explained below.

[0274] Step 1:

[0275] The user inputs basic information (such as name, age, gender, hobbies, and desired partner conditions) via the terminal, which then sends this information to the server.

[0276] Step 2:

[0277] The server stores the received basic information in a database.

[0278] Step 3:

[0279] The user presses the start button for the sample chat via the terminal, and the terminal sends a request to start the sample chat to the server.

[0280] Step 4:

[0281] The server calls the generation AI, sets up a chat session, and initializes the emotion engine to prepare for analyzing the chat content.

[0282] Step 5:

[0283] The device provides the user with a chat interface, where the user initiates a dialogue with the generated AI and answers questions posed by the generated AI.

[0284] Step 6:

[0285] The server collects chat content in real time and extracts the user's emotional information using an emotion engine. The analysis results include information on the user's personality, conversational tendencies, desired conditions, and other emotional information.

[0286] Step 7:

[0287] Based on the information extracted by the server, an avatar is generated that reflects the user's characteristics and also includes emotional information.

[0288] Step 8:

[0289] The server sets up chat sessions with other users' avatars, and the avatars converse with each other. The server also records the emotional information that the avatars acquire through the conversation.

[0290] Step 9:

[0291] The server records the chat content and emotional information between avatars, and analyzes the degree of matching (compatibility score) based on these records.

[0292] Step 10:

[0293] The server selects chat content and emotional information with a high degree of matching and creates it as a recommended chat.

[0294] Step 11:

[0295] The device displays the recommended chat content to the user, who then checks the chat content and considers the emotional information.

[0296] Step 12:

[0297] The user selects their desired match, and the device sends that preference to the server.

[0298] Step 13:

[0299] The server checks whether both users want to be matched, and if both agree, the server makes the match happen.

[0300] Step 14:

[0301] The server will notify both users that a match has been made.

[0302] Example 2

[0303] 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."

[0304] Conventional matching systems are inefficient when handling a large number of user information and have difficulty properly reflecting user characteristics and emotional information. Furthermore, the accuracy of matching between users is low, making it difficult to find a compatible partner. Furthermore, if a user has little interaction experience, they are unable to communicate appropriately, resulting in low satisfaction. The present invention aims to solve these problems through highly accurate analysis using an emotion engine and simulation using avatars.

[0305] 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.

[0306] In this invention, the server includes a means for generating a chat session with the generative AI model, a means for collecting and analyzing chat content between the user and the generative AI model, and a means for using an emotion engine to analyze emotional information and reflect it in the avatar. This allows for highly accurate analysis of user characteristics and emotional information, thereby improving the accuracy of matching between users.

[0307] A "generative AI model" is a type of artificial intelligence that uses natural language processing and machine learning techniques to enable dialogue with users.

[0308] "Basic information" refers to personal information such as name, age, sex, hobbies, and desired partner conditions that a user enters into the system.

[0309] A "chat session" refers to a series of interactions between a user and a generative AI model, or between avatars.

[0310] "Chat interface" refers to the screen and input devices that allow users to interact with generated AI models and other avatars.

[0311] An "emotion engine" refers to software or algorithms that analyze and extract emotional information from user dialogue.

[0312] An "avatar" is a virtual conversational agent that is generated to reflect the user's characteristics and emotional information.

[0313] The "matching degree" is an index that indicates the compatibility or degree of compatibility between users, calculated by analyzing the content of chats between avatars.

[0314] "Recommendation" refers to the act of the server presenting chat logs and avatars with a high degree of matching to the user.

[0315] "Talk tendencies" is information about what topics and expressions a user likes to use in conversations.

[0316] "Desired conditions" refer to the attributes and conditions that a user desires in a partner with whom they wish to be matched.

[0317] "Analysis" refers to the process of analyzing data based on chat content and emotional information collected by the server and extracting user characteristics and emotions.

[0318] The present invention provides a system for improving the efficiency of matching between users by utilizing avatars that reflect the user's emotional information. A method for specifically implementing this system will be described below.

[0319] First, the device provides an interface for the user to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand the type of match the user is looking for.

[0320] Next, the device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. Based on the request, the server sets up a chat session with a generative AI model (e.g., GPT-4) and makes the necessary preparations.

[0321] The server calls the generative AI model and initiates a chat session between the user and the AI. The device provides the user with a chat interface and helps them answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions. At this time, the server also extracts the user's emotional information using an emotion engine and incorporates it into the analysis.

[0322] A specific example of a question would be for the generative AI model to ask, "Hello, what happened today?" and for the user to respond, "I read a new book today."

[0323] Once the analysis is complete, the server generates an avatar that reflects the user's characteristics and wishes based on the analysis results. This avatar converses with other avatars on the user's behalf, improving the efficiency of user matching. Emotional information obtained from the emotion engine is also reflected, improving the avatar's expressiveness and enabling more natural and realistic conversations.

[0324] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of these avatar chats and calculates the degree of matching (compatibility score). The server selects chat content with a high degree of matching and recommends it to the user. The device displays the recommended chat content to the user and confirms whether the user actually wishes to be matched.

[0325] Specifically, User A enters basic information and sends it to the server. Next, User A participates in a sample chat with the generative AI model, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates an avatar for User A. Meanwhile, User B also enters basic information and participates in a sample chat with the generative AI model. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[0326] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[0327] An example of a prompt is as follows:

[0328] When inputting the user's basic information: The terminal provides an interface for inputting the user's basic information.

[0329] At the start of a sample chat: When the user presses the Start Sample Chat button, the terminal sends a request to the server.

[0330] When generating an avatar: The server generates an avatar based on the analysis results, and also reflects emotional information.

[0331] Through the above steps, the system of the present invention can achieve highly accurate matching by using an avatar that reflects the user's characteristics and emotional information.

[0332] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0333] Step 1:

[0334] User registration interface provided

[0335] The terminal provides an interface for the user to input basic information (such as name, age, gender, hobbies, and desired partner conditions). The user's input becomes input to the terminal, and the terminal sends this information to the server. Specifically, the terminal displays a form, and when the user enters information and presses the send button, the data is sent to the server. The server saves this information in a database. The input is the user's basic information, and the output is the user information saved in the database.

[0336] Step 2:

[0337] Sample Chat Start Request

[0338] The device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. The server receives the request and prepares to set up a chat session with the generative AI model. The input is the user's request to start a sample chat, and the output is a state in which preparations for a chat session with the generative AI model are complete.

[0339] Step 3:

[0340] Sample chat

[0341] The server calls the generative AI model and starts a chat session between the user and the AI. The device provides the user with a chat interface and supports the user in answering questions from the AI. Specifically, the generative AI model asks, "Hello, what happened today?" and the user replies, "I read a new book today." The server collects and analyzes the entire content of this chat session in real time. The input is the chat content between the user and the AI, and the output is analyzed user characteristic information.

[0342] Step 4:

[0343] Emotional information analysis

[0344] The server uses an emotion engine to extract the user's emotional information during the chat session and incorporates it into the analysis data. Specifically, it identifies emotions such as positive, negative, and neutral from the user's comments and records them as numerical values. The input is the chat content, and the output is the analyzed emotional information.

[0345] Step 5:

[0346] Avatar generation

[0347] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and wishes. Emotional information obtained from the emotion engine is also reflected in the avatar. Specifically, the server generates an avatar with a specific profile based on data such as "User ID: 001, Personality: Curious, Hobby: Reading, Emotional Information: Happy." The input is the analysis results and emotional information, and the output is the generated avatar.

[0348] Step 6:

[0349] Avatar-to-avatar chat

[0350] The server sets up a chat session between the generated avatars. The avatars begin a conversation, and the content of that conversation is recorded. As a specific example of a conversation, avatar A might ask, "What kind of books do you like?" and avatar B might reply, "I like mystery novels." The input is the generated avatar, and the output is the recorded chat content.

[0351] Step 7:

[0352] Matching evaluation and recommendation

[0353] The server analyzes the recorded chat content and calculates the degree of matching. It selects chat content with a high compatibility score and recommends it to the user. Specifically, the server analyzes the chat content, calculates a score, and creates a ranking. The input is the chat content, and the output is the recommended chat content and its compatibility score.

[0354] Step 8:

[0355] View and review recommendations

[0356] The terminal displays the recommended chat content to the user and confirms whether the user actually wants to be matched. The input is the recommended chat content, and the output is the user's choice of desired match.

[0357] Step 9:

[0358] Confirmation and establishment of matching requests

[0359] The server checks whether both users wish to be matched. If both agree, the match is established and a notification is sent to both users. Specifically, the server checks the wishes of "User ID: 001" and "User ID: 002" and sends a notification if a match is established. The input is the user's match request, and the output is a notification that a match has been established.

[0360] (Application example 2)

[0361] 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."

[0362] Conventional food delivery systems have the problem of not being able to recommend dishes that match a user's preferences and mood. Users may also have difficulty choosing the best dish based on their emotional state. Furthermore, simple recommendation systems often do not improve the user experience, resulting in a decrease in user satisfaction.

[0363] The identification process by the identification 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 means for analyzing a user's emotions in real time using an emotion engine and providing recommendations based on the user's preferences and mood, means for recommending restaurants and dishes for food delivery to the user, and means for analyzing chat content using artificial intelligence and extracting information such as the user's conversation tendencies, desired conditions, personality, and emotional information. This makes it possible to recommend optimal dishes based on the user's emotions and preferences, enabling a food delivery service with high user satisfaction.

[0364] "User" refers to an individual who uses the Service.

[0365] A "terminal" is an electronic device that allows a user to input or receive information, and includes smartphones, computers, and the like.

[0366] "Basic information" refers to personal information about the user, such as name, age, gender, preferences, and allergies.

[0367] "Server" refers to a computer system that processes and stores information received from users and provides necessary functionality.

[0368] A "database" refers to a system for storing various information in an organized manner and making it accessible.

[0369] A "request" refers to a request by a user to initiate a particular action.

[0370] "Artificial intelligence" refers to systems or programs designed to mimic human intelligence, and in this case refers to generative AI models.

[0371] An "emotion engine" refers to a system or program for analyzing a user's emotions.

[0372] "Chat session" refers to a period of interaction or activity between a user and an artificial intelligence.

[0373] "Chat interface" refers to the screen and input means that allow users to interact with artificial intelligence.

[0374] An "avatar" refers to a virtual character created to reflect a user's characteristics and wishes.

[0375] "Matching degree" refers to a compatibility score calculated by analyzing the content of the conversation between avatars.

[0376] "Recommendation" refers to the act of a system suggesting specific information or options to a user.

[0377] "Food delivery" refers to a service that delivers food ordered by a user to a specified location.

[0378] The system of this invention combines an emotion engine that recognizes the user's emotions with a generative AI to recommend food delivery options based on the user's preferences and mood. The user inputs basic information using a terminal, and the server processes and analyzes that information.

[0379] Hardware and software used

[0380] Hardware:

[0381] Smartphone

[0382] server

[0383] software:

[0384] Emotion engine libraries (e.g., Affective Computing)

[0385] Generative AI models (e.g., GPT-4)

[0386] Database management system (e.g. MySQL)

[0387] Front-end frameworks (e.g. React Native)

[0388] System processing steps

[0389] User Registration:

[0390] Users enter basic information (such as name, age, gender, favorite foods, allergies, and desired food conditions) via a smartphone app. This basic information is sent to the server via the device and stored in a database.

[0391] Start a sample chat:

[0392] The user initiates a chat session with the emotion engine and generative AI by pressing the chat button on the device, which sends a request to the server and starts the chat session.

[0393] Sample chat execution:

[0394] The server uses a generative AI model to communicate with the user, and an emotion engine analyzes emotions in real time from the content of the user's conversation and uses this information to determine the user's preferences and mood.

[0395] Avatar Creation:

[0396] The server generates an avatar that reflects the user's characteristics and wishes based on the analysis results of the emotion engine. The generated avatar acts as a proxy character for the user and interacts with other users' avatars.

[0397] Restaurant and food recommendations:

[0398] The server analyzes the interactions between the generated avatars and recommends restaurants and dishes that go well together. It also lists food delivery options and provides optimal recommendations to users.

[0399] User presentation and confirmation:

[0400] The recommended dishes and restaurants are displayed on the device screen, and the user can review the recommended options and decide whether to actually order.

[0401] Order confirmation:

[0402] Once the order is confirmed, the server sends the order to the corresponding restaurant, and the order history is saved in the user's database.

[0403] Processing example

[0404] For example, a user logs in to the app and taps the "Recommend me today's specials!" button. At that time, the app starts an AI chat and asks, "How are you feeling today?" If the user replies, "I feel like eating something a little spicy today," the emotion engine analyzes the user's emotions and preferences and generates a list of spicy dishes. Next, the AI ​​chat suggests, "How about the Shin Ramyun from this restaurant?" If the user accepts the suggestion and confirms the order, the system sends the order to the restaurant.

[0405] Prompt Sentence Examples

[0406] "Would you like me to help you find a dish that matches your mood today? Tell me how you're feeling right now."

[0407] Using this system, recommended dishes and restaurants can be efficiently recommended based on the user's emotions and preferences, thereby improving user satisfaction.

[0408] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0409] Step 1:

[0410] The user enters basic information (such as name, age, gender, favorite foods, allergies, and desired food conditions) via a smartphone app. The entered basic information is sent to the server through the smartphone's input interface. The server stores the received information in a database. In this process, the user's input data is sent to the server and inserted into the user table in the database.

[0411] Step 2:

[0412] The user presses the "Start Chat" button on the smartphone app to start a chat session between the emotion engine and the generative AI. This causes the device to send a chat session request to the server. The server receives the request and calls the generative AI model to generate the chat session. In this process, the server creates a chat session object using the generative AI model and imports the user's basic information.

[0413] Step 3:

[0414] The server uses the generative AI model to provide a chat interface to users. Users answer questions posed by the AI ​​through the chat screen on their smartphones. The server collects chat content in real time and performs emotion analysis using an emotion engine. In this process, the user's text input is sent to the server and analyzed by the emotion engine.

[0415] Step 4:

[0416] The server generates an avatar that reflects the user's characteristics and wishes based on the analysis results of the emotion engine. This avatar is required to act as the user's representative character and to interact with other users' avatars. The generated avatar information is saved in a database. In this process, avatar data is created by combining emotion data and basic information.

[0417] Step 5:

[0418] The server sets up chat sessions between the generated avatars. The content of the avatar chats is recorded and analyzed by the server to calculate the degree of matching. In this process, the avatar conversation logs are analyzed and a compatibility score is calculated using a matching algorithm.

[0419] Step 6:

[0420] The server recommends chat logs with a high degree of matching to the user. The recommended dishes and restaurants are displayed on the smartphone screen. The user checks the options and decides whether to actually order. In this process, the recommendations are displayed on the user interface.

[0421] Step 7:

[0422] When a user confirms an order for a recommended dish or restaurant, the order confirmation information is sent from the smartphone to the server. The server then sends the order to the restaurant based on that information and saves the order history in the user's database. In this process, the order data is sent to the restaurant's system and recorded in the database.

[0423] This trend will enable food delivery recommendations based on users' emotions and preferences, making it possible to provide a service that highly satisfies users.

[0424] 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.

[0425] 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.

[0426] 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.

[0427] [Second embodiment]

[0428] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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).

[0434] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] In the smart glasses 214, 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.

[0439] 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."

[0440] The system of the present invention analyzes the characteristics of a user through a chat session between the user and a generating AI (artificial intelligence) and generates an "avatar" based on the user. The system then allows the avatars to chat with each other, evaluates the degree of matching, and recommends to the user partners with high compatibility. The system of the present invention can be implemented as follows.

[0441] User Registration

[0442] The device provides an interface for users to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand what kind of match the user is looking for.

[0443] Start a sample chat

[0444] The terminal provides the user with a button to start a sample chat. When the user presses this button, the terminal sends a request to start a sample chat to the server. Based on the received request, the server sets up a chat session with the AI ​​and makes the necessary preparations.

[0445] Sample chat

[0446] The server calls the generated AI and starts a chat session between the user and the AI. The device provides the user with a chat interface and helps the user answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions.

[0447] Avatar generation

[0448] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and preferences. This avatar then converses with other avatars on the user's behalf, improving the efficiency of matching users.

[0449] Avatar-to-avatar chat

[0450] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of the avatar chat and calculates the degree of matching (compatibility score).

[0451] Matching evaluation and recommendation

[0452] The server selects chat contents with a high degree of matching and recommends them to the user. The terminal displays the recommended chat contents to the user and confirms whether the user actually wants to be matched.

[0453] Confirmation and establishment of matching requests

[0454] If a user checks the recommended chat content and wishes to be matched, the device sends that request to the server. The server then checks whether both users wish to be matched, and if both agree, the match is established. Once a match is established, the server notifies both users.

[0455] Specific examples

[0456] For example, suppose that User A and User B use this system. User A first enters basic information and sends it to the server. Next, User A participates in a sample chat with the generation AI, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates an avatar for User A.

[0457] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[0458] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[0459] This system will make it easier for users with little dating experience to find a suitable partner, making it possible to combat the declining birthrate and increase the number of marriages.

[0460] The processing flow will be explained below.

[0461] Step 1:

[0462] The user inputs basic information (such as name, age, gender, hobbies, and desired partner conditions) via the terminal, which then sends this information to the server.

[0463] Step 2:

[0464] The server stores the received basic information in a database.

[0465] Step 3:

[0466] The user presses the start button for the sample chat via the terminal, and the terminal sends a request to start the sample chat to the server.

[0467] Step 4:

[0468] The server calls the generated AI and sets up the chat session. The server notifies the device that it is ready.

[0469] Step 5:

[0470] The device provides a chat interface to the user, who initiates a dialogue with the AI ​​and answers questions posed by it.

[0471] Step 6:

[0472] The server collects and analyzes chat content in real time, extracting information such as the user's personality, conversational tendencies, and desired conditions.

[0473] Step 7:

[0474] The server generates an avatar that reflects the user's characteristics based on the information extracted.

[0475] Step 8:

[0476] The server sets up chat sessions with other users' avatars, and the avatars converse with each other.

[0477] Step 9:

[0478] The server records the chat content between avatars and analyzes the match score (compatibility score) based on the records.

[0479] Step 10:

[0480] The server selects chat content with a high degree of matching and creates recommended chats.

[0481] Step 11:

[0482] The device displays the recommended chat content to the user, and the user confirms the chat content.

[0483] Step 12:

[0484] The user selects their desired match, and the device sends that preference to the server.

[0485] Step 13:

[0486] The server checks whether both users want to be matched, and if both agree, the server makes the match happen.

[0487] Step 14:

[0488] The server will notify both users that a match has been made.

[0489] Example 1

[0490] 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."

[0491] Conventional online matching systems have difficulty in matching users based on their individual characteristics and desired conditions, making it difficult to provide effective matching results. Furthermore, protecting user privacy and achieving highly accurate matching have been issues. This has made it difficult for users to find a suitable partner, resulting in reduced matching efficiency.

[0492] 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.

[0493] In this invention, the server includes: means for a user to input basic information via a terminal; means for the server to receive the basic information and store it in a storage device; means for the user to issue a request to start a sample chat with an AI; means for the terminal to send the request to the server; means for the server to generate an interactive session with the AI ​​based on the request; means for the terminal to provide an interactive interface to the user; means for the server to collect and analyze the content of the dialogue between the user and the AI; means for the server to generate a digital avatar that reflects the user's characteristics based on the analysis results; means for the server to set up an interactive session between the digital avatars and record the content of the dialogue; means for the server to analyze the recorded content of the dialogue and calculate a compatibility score; means for the server to recommend a dialogue log with a high compatibility score to the user; means for the terminal to display the recommended content of the dialogue to the user and confirm it; means for the user to select a desired match; means for the terminal to send the selected state of the desired match to the server; and means for the server to establish a match if both users desire a match. This enables highly accurate matching that reflects the characteristics and preferences of users.

[0494] "User" refers to an individual who uses the system to input basic information and is matched through dialogue with artificial intelligence.

[0495] "Terminal" refers to an electronic device that allows a user to input basic information and use an interactive interface. Examples include smartphones and computers.

[0496] "Server" refers to a central computer system that receives, stores, and processes information sent by users and terminals.

[0497] "Basic information" refers to the personal information and desired conditions that a user enters into the system, and includes, for example, name, age, gender, hobbies, and desired partner conditions.

[0498] "Artificial intelligence" is a general term for programs and systems that interact with users and analyze the information they collect. Examples include generative AI models.

[0499] A "sample chat" is an interactive session that a user has with an AI, with the purpose of gathering information about the user's characteristics and desired conditions.

[0500] "Dialogue interface" refers to the screen display and input means that allow the user to interact with artificial intelligence.

[0501] A "digital avatar" is a character with a virtual personality that reflects the characteristics and wishes of a user, and is generated to interact with other avatars.

[0502] "Dialogue content" refers to messages and conversation logs in dialogue between a user and an artificial intelligence, or between digital avatars.

[0503] The "compatibility" is a numerical value or index that indicates the compatibility between users, calculated by analyzing the content of the conversation.

[0504] "Recommendation" refers to the act of suggesting compatible partners and conversation content to the user based on the compatibility calculated by the server.

[0505] "Matching preference" refers to a user's expression of intent to actually be matched with the recommended partner or the content of the conversation.

[0506] "Notification" refers to the act of the server transmitting information to the user, and refers to a message informing the user of a match and its results.

[0507] The system of the present invention begins when a user inputs basic information via a terminal, which is then received and stored by a server. The user then engages in a sample chat with an AI, and a digital avatar that reflects the user's characteristics is generated by analyzing the content of the conversation. The system then provides a series of processes by having the avatars chat with each other, evaluating their compatibility, and recommending highly compatible partners to the user. The main processes are explained in detail below.

[0508] Enter and save basic information

[0509] The terminal provides an interface for the user to enter basic information (such as name, age, gender, hobbies, and desired partner criteria). When the user enters this information and presses the send button, the terminal sends the information to the server. The server stores the received information in a database and uses it for subsequent processing. In this case, a relational database management system such as MySQL is used as the database.

[0510] Start a sample chat

[0511] The device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. Upon receiving the request, the server invokes a generative AI model (e.g., OpenAI's GPT-3) and sets up a chat session with the user. The device then provides the user with a chat interface, allowing the user to answer questions posed by the AI.

[0512] Collection and analysis of chat content

[0513] The server collects chat content between the user and the AI ​​in real time. A natural language processing library (e.g., NLTK) is used to analyze the collected data. The analysis results are used to extract characteristics such as the user's personality, conversational tendencies, and desired conditions.

[0514] Digital avatar generation

[0515] The server then generates a digital avatar that reflects the user's characteristics and preferences based on the analysis results. This avatar then engages in simulated conversations on behalf of the user, improving the efficiency of matching users.

[0516] Avatar-to-avatar chat settings

[0517] The server sets up chat sessions between the generated digital avatars. The avatars converse with each other and record the conversations. The server analyzes the conversations and calculates the compatibility of each avatar. Machine learning algorithms are often used to calculate compatibility.

[0518] Matching result recommendations

[0519] The server selects chat content with a high degree of compatibility and recommends it to the user. The terminal displays the recommended chat content to the user and confirms whether the user actually wants to be matched. If the user confirms the recommended content and wishes to be matched, the terminal transmits the selection status to the server.

[0520] Matching is completed

[0521] The server confirms that both users are willing to match, and if both agree, the match is established. Once a match is established, the server notifies both users. Notifications can be sent via email or in-app message.

[0522] Specific examples

[0523] For example, let's consider the case where User A and User B use the system. User A first enters basic information and sends it to the server. Next, User A participates in a sample chat with the generation AI, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates a digital avatar for User A.

[0524] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B and sets up a chat session between the two avatars. The content of the conversation is recorded, and the server calculates the compatibility based on the analysis results. If the compatibility is high, it is recommended to User A and User B.

[0525] If User A and User B check the recommended chat content and agree to be compatible, the server will match them and notify them, allowing users to find compatible partners more effectively and efficiently.

[0526] Prompt Sentence Examples

[0527] By inputting questions such as "What are your hobbies?", "How do you spend your holidays?", and "What kind of person is your ideal partner?" into the generative AI model, the user's characteristics and preferences can be extracted.

[0528] Through the above process, the system can analyze the user's characteristics and preferences in detail and achieve highly accurate matching.

[0529] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0530] Step 1: Enter and submit user information

[0531] The terminal provides an interface for the user to input basic information (such as name, age, sex, hobbies, and desired partner conditions).

[0532] Input: The user enters basic information into the terminal.

[0533] How it works: The user enters basic information and presses the submit button.

[0534] Output: The terminal sends the entered information to the server.

[0535] Step 2: Receiving and storing user information

[0536] The server stores the received user basic information in a database.

[0537] Input: Basic information of the user sent from the device.

[0538] Operation: The server analyzes the received information and stores it in a database, such as MySQL.

[0539] Output: User information stored in the database.

[0540] Step 3: Prepare to start a sample chat

[0541] The terminal provides the user with a button to start a sample chat.

[0542] Input: User presses the start button to begin a sample chat.

[0543] Operation: The device sends a request to the server to start a sample chat.

[0544] Output: A sample chat start request sent to the server.

[0545] Step 4: Invoke the generative AI model and set up a chat session

[0546] Based on the received request, the server invokes the generative AI model and sets up a chat session with the user.

[0547] Input: A sample chat start request.

[0548] How it works: The server invokes a generative AI model (e.g., OpenAI's GPT-3) and sets up a chat session.

[0549] Output: The configured chat session.

[0550] Step 5: Providing a chat interface

[0551] The device provides the user with a chat interface, creating an environment in which the user can interact with the AI.

[0552] Input: The configured chat session.

[0553] Behavior: The device displays and provides the user with a chat interface (text boxes, send buttons, etc.).

[0554] Output: A chat interface available to the user.

[0555] Step 6: Collecting and analyzing chat content

[0556] The server collects and analyzes chat content between the user and the generative AI model in real time.

[0557] Input: The interaction between the user and the generative AI model.

[0558] How it works: The server collects chat content and analyzes it using a natural language processing library (e.g., NLTK). Through the analysis, it extracts information about the user's personality, conversational tendencies, and desired conditions.

[0559] Output: User characteristic information as the analysis result.

[0560] Step 7: Generate a digital avatar

[0561] Based on the analysis results, the server generates a digital avatar that reflects the user's characteristics and wishes.

[0562] Input: User characteristics information.

[0563] How it works: The server generates a digital avatar based on the user's characteristics.

[0564] Output: The generated digital avatar.

[0565] Step 8: Setting up a chat session between avatars

[0566] The server sets up a chat session between the generated digital avatars.

[0567] Input: A generated digital avatar.

[0568] How it works: A server sets up chat sessions between digital avatars and records the conversations.

[0569] Output: Configured avatar chat sessions and recorded dialogue.

[0570] Step 9: Record and analyze chat content

[0571] The server records the content of the conversation between the avatars and analyzes the content.

[0572] Input: Conversation between avatars.

[0573] How it works: The server analyzes the recorded conversations and calculates the relevance using machine learning algorithms.

[0574] Output: The calculated fitness.

[0575] Step 10: Recommending matching results

[0576] The server selects dialogue content with high suitability and recommends it to the user.

[0577] Input: The calculated fitness.

[0578] Operation: The server selects the dialogue content to recommend based on the relevance result and creates a recommendation list.

[0579] Output: Recommended dialogue for the user.

[0580] Step 11: Confirm your match preference

[0581] The terminal displays the recommended dialogue content to the user and provides a means for the user to confirm it.

[0582] Input: Recommended dialogue.

[0583] Operation: The device displays the recommendations to the user and allows the user to select a match.

[0584] Output: Confirmation of user's match preference.

[0585] Step 12: Send your match request and get it done

[0586] If the user selects a match, that information is sent to the server.

[0587] Input: User's match preference selection.

[0588] Operation: The device sends the user's selection status to the server. The server confirms whether both users wish to be matched and establishes the match.

[0589] Output: Matches made and notifications.

[0590] Through the above processing steps, the system can analyze the user's characteristics and preferences in detail and achieve highly accurate matching.

[0591] (Application example 1)

[0592] 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."

[0593] To improve production efficiency in factories, it is important to create optimal team structures based on the characteristics of each robot. However, efficient team building is difficult because there is no established method for evaluating the compatibility and collaborative effectiveness of factory robots. The present invention aims to provide a means to solve this problem.

[0594] 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.

[0595] In this invention, the server includes means for a user to input basic information via a terminal, means for the server to receive the basic information and store it in a database, means for a user to issue a request to start a sample chat with an AI, means for the terminal to send the request to the server, means for the server to generate a chat session with the AI ​​based on the request, means for the terminal to provide a chat interface to the user, means for the server to collect and analyze chat content between the user and the AI, means for the server to generate an avatar that reflects the user's characteristics based on the analysis results, and means for the server to set up a chat session between the avatars and display the chat content. The system includes a means for recording chat content, a means for the server to analyze the recorded chat content and calculate a degree of matching, a means for the server to recommend chat logs with a high degree of matching to the user, a means for the terminal to display the recommended chat content to the user and for confirmation, a means for the user to select a desired match, a means for the terminal to transmit the selected state of the desired match to the server, a means for the server to establish a match when both users desire a match, a means for inputting basic information about the factory robot, a means for generating an avatar based on the characteristics of the robot, and a means for analyzing chat sessions between the avatars and recommending an optimal team composition. This enables evaluation of the compatibility between factory robots and efficient team building.

[0596] "Users" are factory managers and operators who input information and use the system's various functions.

[0597] A "terminal" is a device used by a user to enter information or interact with a system.

[0598] "Basic information" refers to data that includes detailed information about users and robots, such as their characteristics and roles.

[0599] A "server" is a device that receives basic information about users and robots, analyzes and stores the data, and manages and processes the entire system.

[0600] A "database" is a storage device for storing various data such as basic information and analysis results.

[0601] A "request" is a request or command given by a user to a system.

[0602] "Artificial intelligence" refers to computer programs used within the system to generate chat sessions and analyze the characteristics of users and robots.

[0603] A "chat session" is a series of conversations that take place between a user or a robot and an artificial intelligence.

[0604] A "chat interface" is a screen or application that allows users and robots to conduct chat sessions.

[0605] "Chat Content" means the text and messages exchanged during a chat session.

[0606] "Analysis" is the process of analyzing collected chat content and extracting characteristics and trends.

[0607] An "avatar" is a virtual character that reflects the characteristics of a user or a robot.

[0608] "Matching degree" is a score that indicates the compatibility and cooperative effect between avatars.

[0609] "Recommendation" means that the system suggests specific avatars and team compositions to users based on analysis results and compatibility scores.

[0610] "Confirmation" refers to the process by which a user decides whether to accept a recommendation from the system.

[0611] A "factory robot" is an automated mechanical device that performs work on a production line or in a factory.

[0612] A "team composition" is a combination of multiple robot avatars working together to achieve optimal production efficiency.

[0613] This invention is a system that understands the characteristics of robots used in factories and recommends optimal team composition. The system starts operation when a user inputs basic information using a terminal and sends it to a server.

[0614] Enter and save basic information

[0615] The user inputs basic information about the factory robot (model, functions, capabilities, role, etc.) via a terminal. This information is sent to a server and stored in a database. The database is stored in a cloud environment or on a server installed in the factory, where the information is managed and accessed.

[0616] Starting and running a sample chat

[0617] When a user requests a sample chat, the device sends the request to the server. Based on the received request, the server sets up a chat session using a generative AI model. An avatar is generated based on the robot's basic information, and this avatar chats with the AI.

[0618] Collection and analysis of chat content

[0619] The terminal provides the user with a chat interface, and the server collects chat content between the robot and the AI ​​in real time. The collected data is analyzed using a generative AI model to extract information about the robot's characteristics, performance, and collaboration tendencies.

[0620] Avatar generation and matching evaluation

[0621] Based on the analysis results, the server generates avatars that reflect the characteristics of each robot. Chat sessions are set up between the generated avatars, and the chat content is recorded. The server then analyzes the recorded data again to calculate the degree of matching between the avatars, which is used to evaluate their compatibility and collaborative effectiveness.

[0622] Recommendations and Match Confirmation

[0623] The server recommends chat logs of avatars with a high degree of matching to the user. The device displays these recommendations to the user, who then checks the recommendations and selects their desired match. The user's selection is sent to the server, which then works to create the optimal team composition.

[0624] Hardware and Software Use

[0625] The system uses cloud servers, factory servers, and user devices (tablets and PCs) as hardware. Python and OpenAI API (GPT-4 model) are used as software. A relational database management system (RDBMS) is used for database management.

[0626] Specific examples

[0627] For example, suppose factory robot A is an arm robot responsible for welding, and robot B is a transport robot responsible for transporting materials. The user enters basic information about these robots into a terminal and sends it to the server. The server generates avatars using a generative AI model and initiates a chat session between the avatars. Below is a specific example of a prompt sentence.

[0628] Example prompt sentence:

[0629] Start chatting as robot named Robo1, model: arm robot, ability: welding, assembly, role: welder.

[0630] A chat session is held based on this prompt, and the server analyzes the collected data and recommends the optimal team composition to the user, thereby improving the factory's production efficiency.

[0631] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0632] Step 1:

[0633] The user uses a terminal to input basic information about the factory robot. Specifically, they input detailed information such as the robot's model, functions, capabilities, and role, and then press the send button. The input information is sent from the terminal to the server. The server stores the received basic information in a database. This information is used to understand the robot's characteristics.

[0634] Step 2:

[0635] A user issues a request to start a sample chat. Specifically, the request is sent to the server by pressing the Start Sample Chat button on the device. Based on the received request, the server generates an avatar for each robot and sets up a chat session using the generative AI model. At this time, a prompt sentence is generated and input into the AI ​​model.

[0636] Step 3:

[0637] The server calls the generative AI model and initiates a chat session with each robot avatar. The device provides the user with a chat interface, and the chat session proceeds in real time. The server collects and stores the content of the conversation between the robot and the AI ​​in real time. The chat content is dynamically generated by the generative AI based on the input prompt.

[0638] Step 4:

[0639] The server analyzes the chat content collected. Using a generative AI model, it analyzes each robot's characteristics, conversational tendencies, and collaboration potential. Specifically, it extracts the robot's characteristic patterns and working behavior from the chat content and converts them into numerical data and categorical information. The results of this analysis are reflected in each robot's avatar.

[0640] Step 5:

[0641] Based on the analysis results, the server generates an avatar that reflects the characteristics of each robot. This avatar is a virtual character that corresponds to the robot's characteristics and is used to interact with other avatars. The generated avatar is displayed in a way that is easy for users and administrators to understand.

[0642] Step 6:

[0643] The server sets up a chat session between the generated avatars. The avatars converse and record the content. Specifically, a conversation between the avatars is simulated to evaluate the effectiveness of collaboration and compatibility. A scenario is generated based on the prompt text, and the conversation between the avatars progresses.

[0644] Step 7:

[0645] The server analyzes the recorded chat content and calculates the degree of matching between avatars. Specifically, it evaluates the consistency and cooperation of the chat content and outputs a numerical compatibility score. This allows the compatibility of each avatar and their suitability as a team to be evaluated.

[0646] Step 8:

[0647] The server recommends chat logs with a high degree of matching to the user. The device displays the recommended chat content to the user, who then confirms it. Specifically, avatars are recommended based on compatibility scores, and the user can view the recommended content and decide whether or not it is suitable for them.

[0648] Step 9:

[0649] The user checks the recommended chat content and selects whether they wish to be matched. The device sends the user's selection to the server. If both users wish to be matched, the server establishes the match and sends appropriate notifications. This determines the optimal team composition and reflects it on the actual production line.

[0650] 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.

[0651] The system of the present invention combines an emotion engine that recognizes the user's emotions, analyzes the user's characteristics through a chat session between the user and a generating AI (artificial intelligence), and generates an "avatar" based on the user. Furthermore, the system allows the generated avatars to chat with each other, evaluates the degree of matching, and recommends to the user partners with high compatibility. The system of the present invention can be implemented as follows.

[0652] User Registration

[0653] The device provides an interface for users to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand what kind of match the user is looking for.

[0654] Start a sample chat

[0655] The terminal provides the user with a button to start a sample chat. When the user presses this button, the terminal sends a request to start a sample chat to the server. Based on the received request, the server sets up a chat session with the AI ​​and makes the necessary preparations.

[0656] Sample chat

[0657] The server calls the generated AI and starts a chat session between the user and the AI. The device provides the user with a chat interface and helps them answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions. At this time, the emotion engine also extracts the user's emotional information and incorporates it into the analysis.

[0658] Avatar generation

[0659] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and wishes. This avatar converses with other avatars on the user's behalf, improving the efficiency of user matching. Emotional information obtained from the emotion engine is also reflected, improving the avatar's expressiveness and enabling more natural and realistic conversations.

[0660] Avatar-to-avatar chat

[0661] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of the avatar chat and calculates the degree of matching (compatibility score).

[0662] Matching evaluation and recommendation

[0663] The server selects chat contents with a high degree of matching and recommends them to the user. The terminal displays the recommended chat contents to the user and confirms whether the user actually wants to be matched.

[0664] Confirmation and establishment of matching requests

[0665] If a user checks the recommended chat content and wishes to be matched, the device sends that request to the server. The server then checks whether both users wish to be matched. If both agree, the server establishes the match and notifies both users.

[0666] Specific examples

[0667] For example, suppose that user A and user B use this system. User A first enters basic information and sends it to the server. Next, user A participates in a sample chat with the generation AI, and the server analyzes the chat content and extracts user A's characteristics. Based on the results, the server generates an avatar for user A. At this time, the emotion engine also analyzes user A's emotional information and reflects it in the avatar.

[0668] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[0669] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[0670] This system will make it easier for users with little dating experience to find a suitable partner, which will help combat the declining birthrate and increase the number of marriages.In addition, the use of an emotion engine will make avatar conversations more natural and friendly, improving the user experience.

[0671] The processing flow will be explained below.

[0672] Step 1:

[0673] The user inputs basic information (such as name, age, gender, hobbies, and desired partner conditions) via the terminal, which then sends this information to the server.

[0674] Step 2:

[0675] The server stores the received basic information in a database.

[0676] Step 3:

[0677] The user presses the start button for the sample chat via the terminal, and the terminal sends a request to start the sample chat to the server.

[0678] Step 4:

[0679] The server calls the generation AI, sets up a chat session, and initializes the emotion engine to prepare for analyzing the chat content.

[0680] Step 5:

[0681] The device provides the user with a chat interface, where the user initiates a dialogue with the generated AI and answers questions posed by the generated AI.

[0682] Step 6:

[0683] The server collects chat content in real time and extracts the user's emotional information using an emotion engine. The analysis results include information on the user's personality, conversational tendencies, desired conditions, and other emotional information.

[0684] Step 7:

[0685] Based on the information extracted by the server, an avatar is generated that reflects the user's characteristics and also includes emotional information.

[0686] Step 8:

[0687] The server sets up chat sessions with other users' avatars, and the avatars converse with each other. The server also records the emotional information that the avatars acquire through the conversation.

[0688] Step 9:

[0689] The server records the chat content and emotional information between avatars, and analyzes the degree of matching (compatibility score) based on these records.

[0690] Step 10:

[0691] The server selects chat content and emotional information with a high degree of matching and creates it as a recommended chat.

[0692] Step 11:

[0693] The device displays the recommended chat content to the user, who then checks the chat content and considers the emotional information.

[0694] Step 12:

[0695] The user selects their desired match, and the device sends that preference to the server.

[0696] Step 13:

[0697] The server checks whether both users want to be matched, and if both agree, the server makes the match happen.

[0698] Step 14:

[0699] The server will notify both users that a match has been made.

[0700] Example 2

[0701] 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."

[0702] Conventional matching systems are inefficient when handling a large number of user information and have difficulty properly reflecting user characteristics and emotional information. Furthermore, the accuracy of matching between users is low, making it difficult to find a compatible partner. Furthermore, if a user has little interaction experience, they are unable to communicate appropriately, resulting in low satisfaction. The present invention aims to solve these problems through highly accurate analysis using an emotion engine and simulation using avatars.

[0703] 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.

[0704] In this invention, the server includes a means for generating a chat session with the generative AI model, a means for collecting and analyzing chat content between the user and the generative AI model, and a means for using an emotion engine to analyze emotional information and reflect it in the avatar. This allows for highly accurate analysis of user characteristics and emotional information, thereby improving the accuracy of matching between users.

[0705] A "generative AI model" is a type of artificial intelligence that uses natural language processing and machine learning techniques to enable dialogue with users.

[0706] "Basic information" refers to personal information such as name, age, sex, hobbies, and desired partner conditions that a user enters into the system.

[0707] A "chat session" refers to a series of interactions between a user and a generative AI model, or between avatars.

[0708] "Chat interface" refers to the screen and input devices that allow users to interact with generated AI models and other avatars.

[0709] An "emotion engine" refers to software or algorithms that analyze and extract emotional information from user dialogue.

[0710] An "avatar" is a virtual conversational agent that is generated to reflect the user's characteristics and emotional information.

[0711] The "matching degree" is an index that indicates the compatibility or degree of compatibility between users, calculated by analyzing the content of chats between avatars.

[0712] "Recommendation" refers to the act of the server presenting chat logs and avatars with a high degree of matching to the user.

[0713] "Talk tendencies" is information about what topics and expressions a user likes to use in conversations.

[0714] "Desired conditions" refer to the attributes and conditions that a user desires in a partner with whom they wish to be matched.

[0715] "Analysis" refers to the process of analyzing data based on chat content and emotional information collected by the server and extracting user characteristics and emotions.

[0716] The present invention provides a system for improving the efficiency of matching between users by utilizing avatars that reflect the user's emotional information. A method for specifically implementing this system will be described below.

[0717] First, the device provides an interface for the user to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand the type of match the user is looking for.

[0718] Next, the device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. Based on the request, the server sets up a chat session with a generative AI model (e.g., GPT-4) and makes the necessary preparations.

[0719] The server calls the generative AI model and initiates a chat session between the user and the AI. The device provides the user with a chat interface and helps them answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions. At this time, the server also extracts the user's emotional information using an emotion engine and incorporates it into the analysis.

[0720] A specific example of a question would be for the generative AI model to ask, "Hello, what happened today?" and for the user to respond, "I read a new book today."

[0721] Once the analysis is complete, the server generates an avatar that reflects the user's characteristics and wishes based on the analysis results. This avatar converses with other avatars on the user's behalf, improving the efficiency of user matching. Emotional information obtained from the emotion engine is also reflected, improving the avatar's expressiveness and enabling more natural and realistic conversations.

[0722] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of these avatar chats and calculates the degree of matching (compatibility score). The server selects chat content with a high degree of matching and recommends it to the user. The device displays the recommended chat content to the user and confirms whether the user actually wishes to be matched.

[0723] Specifically, User A enters basic information and sends it to the server. Next, User A participates in a sample chat with the generative AI model, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates an avatar for User A. Meanwhile, User B also enters basic information and participates in a sample chat with the generative AI model. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[0724] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[0725] An example of a prompt is as follows:

[0726] When inputting the user's basic information: The terminal provides an interface for inputting the user's basic information.

[0727] At the start of a sample chat: When the user presses the Start Sample Chat button, the terminal sends a request to the server.

[0728] When generating an avatar: The server generates an avatar based on the analysis results, and also reflects emotional information.

[0729] Through the above steps, the system of the present invention can achieve highly accurate matching by using an avatar that reflects the user's characteristics and emotional information.

[0730] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0731] Step 1:

[0732] User registration interface provided

[0733] The terminal provides an interface for the user to input basic information (such as name, age, gender, hobbies, and desired partner conditions). The user's input becomes input to the terminal, and the terminal sends this information to the server. Specifically, the terminal displays a form, and when the user enters information and presses the send button, the data is sent to the server. The server saves this information in a database. The input is the user's basic information, and the output is the user information saved in the database.

[0734] Step 2:

[0735] Sample Chat Start Request

[0736] The device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. The server receives the request and prepares to set up a chat session with the generative AI model. The input is the user's request to start a sample chat, and the output is a state in which preparations for a chat session with the generative AI model are complete.

[0737] Step 3:

[0738] Sample chat

[0739] The server calls the generative AI model and starts a chat session between the user and the AI. The device provides the user with a chat interface and supports the user in answering questions from the AI. Specifically, the generative AI model asks, "Hello, what happened today?" and the user replies, "I read a new book today." The server collects and analyzes the entire content of this chat session in real time. The input is the chat content between the user and the AI, and the output is analyzed user characteristic information.

[0740] Step 4:

[0741] Emotional information analysis

[0742] The server uses an emotion engine to extract the user's emotional information during the chat session and incorporates it into the analysis data. Specifically, it identifies emotions such as positive, negative, and neutral from the user's comments and records them as numerical values. The input is the chat content, and the output is the analyzed emotional information.

[0743] Step 5:

[0744] Avatar generation

[0745] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and wishes. Emotional information obtained from the emotion engine is also reflected in the avatar. Specifically, the server generates an avatar with a specific profile based on data such as "User ID: 001, Personality: Curious, Hobby: Reading, Emotional Information: Happy." The input is the analysis results and emotional information, and the output is the generated avatar.

[0746] Step 6:

[0747] Avatar-to-avatar chat

[0748] The server sets up a chat session between the generated avatars. The avatars begin a conversation, and the content of that conversation is recorded. As a specific example of a conversation, avatar A might ask, "What kind of books do you like?" and avatar B might reply, "I like mystery novels." The input is the generated avatar, and the output is the recorded chat content.

[0749] Step 7:

[0750] Matching evaluation and recommendation

[0751] The server analyzes the recorded chat content and calculates the degree of matching. It selects chat content with a high compatibility score and recommends it to the user. Specifically, the server analyzes the chat content, calculates a score, and creates a ranking. The input is the chat content, and the output is the recommended chat content and its compatibility score.

[0752] Step 8:

[0753] View and review recommendations

[0754] The terminal displays the recommended chat content to the user and confirms whether the user actually wants to be matched. The input is the recommended chat content, and the output is the user's choice of desired match.

[0755] Step 9:

[0756] Confirmation and establishment of matching requests

[0757] The server checks whether both users wish to be matched. If both agree, the match is established and a notification is sent to both users. Specifically, the server checks the wishes of "User ID: 001" and "User ID: 002" and sends a notification if a match is established. The input is the user's match request, and the output is a notification that a match has been established.

[0758] (Application example 2)

[0759] 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."

[0760] Conventional food delivery systems have the problem of not being able to recommend dishes that match a user's preferences and mood. Users may also have difficulty choosing the best dish based on their emotional state. Furthermore, simple recommendation systems often do not improve the user experience, resulting in a decrease in user satisfaction.

[0761] The identification process by the identification 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 means for analyzing a user's emotions in real time using an emotion engine and providing recommendations based on the user's preferences and mood, means for recommending restaurants and dishes for food delivery to the user, and means for analyzing chat content using artificial intelligence and extracting information such as the user's conversation tendencies, desired conditions, personality, and emotional information. This makes it possible to recommend optimal dishes based on the user's emotions and preferences, enabling a food delivery service with high user satisfaction.

[0762] "User" refers to an individual who uses the Service.

[0763] A "terminal" is an electronic device that allows a user to input or receive information, and includes smartphones, computers, and the like.

[0764] "Basic information" refers to personal information about the user, such as name, age, gender, preferences, and allergies.

[0765] "Server" refers to a computer system that processes and stores information received from users and provides necessary functionality.

[0766] A "database" refers to a system for storing various information in an organized manner and making it accessible.

[0767] A "request" refers to a request by a user to initiate a particular action.

[0768] "Artificial intelligence" refers to systems or programs designed to mimic human intelligence, and in this case refers to generative AI models.

[0769] An "emotion engine" refers to a system or program for analyzing a user's emotions.

[0770] "Chat session" refers to a period of interaction or activity between a user and an artificial intelligence.

[0771] "Chat interface" refers to the screen and input means that allow users to interact with artificial intelligence.

[0772] An "avatar" refers to a virtual character created to reflect a user's characteristics and wishes.

[0773] "Matching degree" refers to a compatibility score calculated by analyzing the content of the conversation between avatars.

[0774] "Recommendation" refers to the act of a system suggesting specific information or options to a user.

[0775] "Food delivery" refers to a service that delivers food ordered by a user to a specified location.

[0776] The system of this invention combines an emotion engine that recognizes the user's emotions with a generative AI to recommend food delivery options based on the user's preferences and mood. The user inputs basic information using a terminal, and the server processes and analyzes that information.

[0777] Hardware and software used

[0778] Hardware:

[0779] Smartphone

[0780] server

[0781] software:

[0782] Emotion engine libraries (e.g., Affective Computing)

[0783] Generative AI models (e.g., GPT-4)

[0784] Database management system (e.g. MySQL)

[0785] Front-end frameworks (e.g. React Native)

[0786] System processing steps

[0787] User Registration:

[0788] Users enter basic information (such as name, age, gender, favorite foods, allergies, and desired food conditions) via a smartphone app. This basic information is sent to the server via the device and stored in a database.

[0789] Start a sample chat:

[0790] The user initiates a chat session with the emotion engine and generative AI by pressing the chat button on the device, which sends a request to the server and starts the chat session.

[0791] Sample chat execution:

[0792] The server uses a generative AI model to communicate with the user, and an emotion engine analyzes emotions in real time from the content of the user's conversation and uses this information to determine the user's preferences and mood.

[0793] Avatar Creation:

[0794] The server generates an avatar that reflects the user's characteristics and wishes based on the analysis results of the emotion engine. The generated avatar acts as a proxy character for the user and interacts with other users' avatars.

[0795] Restaurant and food recommendations:

[0796] The server analyzes the interactions between the generated avatars and recommends restaurants and dishes that go well together. It also lists food delivery options and provides optimal recommendations to users.

[0797] User presentation and confirmation:

[0798] The recommended dishes and restaurants are displayed on the device screen, and the user can review the recommended options and decide whether to actually order.

[0799] Order confirmation:

[0800] Once the order is confirmed, the server sends the order to the corresponding restaurant, and the order history is saved in the user's database.

[0801] Processing example

[0802] For example, a user logs in to the app and taps the "Recommend me today's specials!" button. At that time, the app starts an AI chat and asks, "How are you feeling today?" If the user replies, "I feel like eating something a little spicy today," the emotion engine analyzes the user's emotions and preferences and generates a list of spicy dishes. Next, the AI ​​chat suggests, "How about the Shin Ramyun from this restaurant?" If the user accepts the suggestion and confirms the order, the system sends the order to the restaurant.

[0803] Prompt Sentence Examples

[0804] "Would you like me to help you find a dish that matches your mood today? Tell me how you're feeling right now."

[0805] Using this system, recommended dishes and restaurants can be efficiently recommended based on the user's emotions and preferences, thereby improving user satisfaction.

[0806] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0807] Step 1:

[0808] The user enters basic information (such as name, age, gender, favorite foods, allergies, and desired food conditions) via a smartphone app. The entered basic information is sent to the server through the smartphone's input interface. The server stores the received information in a database. In this process, the user's input data is sent to the server and inserted into the user table in the database.

[0809] Step 2:

[0810] The user presses the "Start Chat" button on the smartphone app to start a chat session between the emotion engine and the generative AI. This causes the device to send a chat session request to the server. The server receives the request and calls the generative AI model to generate the chat session. In this process, the server creates a chat session object using the generative AI model and imports the user's basic information.

[0811] Step 3:

[0812] The server uses the generative AI model to provide a chat interface to users. Users answer questions posed by the AI ​​through the chat screen on their smartphones. The server collects chat content in real time and performs emotion analysis using an emotion engine. In this process, the user's text input is sent to the server and analyzed by the emotion engine.

[0813] Step 4:

[0814] The server generates an avatar that reflects the user's characteristics and wishes based on the analysis results of the emotion engine. This avatar is required to act as the user's representative character and to interact with other users' avatars. The generated avatar information is saved in a database. In this process, avatar data is created by combining emotion data and basic information.

[0815] Step 5:

[0816] The server sets up chat sessions between the generated avatars. The content of the avatar chats is recorded and analyzed by the server to calculate the degree of matching. In this process, the avatar conversation logs are analyzed and a compatibility score is calculated using a matching algorithm.

[0817] Step 6:

[0818] The server recommends chat logs with a high degree of matching to the user. The recommended dishes and restaurants are displayed on the smartphone screen. The user checks the options and decides whether to actually order. In this process, the recommendations are displayed on the user interface.

[0819] Step 7:

[0820] When a user confirms an order for a recommended dish or restaurant, the order confirmation information is sent from the smartphone to the server. The server then sends the order to the restaurant based on that information and saves the order history in the user's database. In this process, the order data is sent to the restaurant's system and recorded in the database.

[0821] This trend will enable food delivery recommendations based on users' emotions and preferences, making it possible to provide a service that highly satisfies users.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] [Third embodiment]

[0826] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0827] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0828] 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).

[0829] 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.

[0830] 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.

[0831] 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).

[0832] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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."

[0838] The system of the present invention analyzes the characteristics of a user through a chat session between the user and a generating AI (artificial intelligence) and generates an "avatar" based on the user. The system then allows the avatars to chat with each other, evaluates the degree of matching, and recommends to the user partners with high compatibility. The system of the present invention can be implemented as follows.

[0839] User Registration

[0840] The device provides an interface for users to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand what kind of match the user is looking for.

[0841] Start a sample chat

[0842] The terminal provides the user with a button to start a sample chat. When the user presses this button, the terminal sends a request to start a sample chat to the server. Based on the received request, the server sets up a chat session with the AI ​​and makes the necessary preparations.

[0843] Sample chat

[0844] The server calls the generated AI and starts a chat session between the user and the AI. The device provides the user with a chat interface and helps the user answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions.

[0845] Avatar generation

[0846] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and preferences. This avatar then converses with other avatars on the user's behalf, improving the efficiency of matching users.

[0847] Avatar-to-avatar chat

[0848] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of the avatar chat and calculates the degree of matching (compatibility score).

[0849] Matching evaluation and recommendation

[0850] The server selects chat contents with a high degree of matching and recommends them to the user. The terminal displays the recommended chat contents to the user and confirms whether the user actually wants to be matched.

[0851] Confirmation and establishment of matching requests

[0852] If a user checks the recommended chat content and wishes to be matched, the device sends that request to the server. The server then checks whether both users wish to be matched, and if both agree, the match is established. Once a match is established, the server notifies both users.

[0853] Specific examples

[0854] For example, suppose that User A and User B use this system. User A first enters basic information and sends it to the server. Next, User A participates in a sample chat with the generation AI, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates an avatar for User A.

[0855] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[0856] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[0857] This system will make it easier for users with little dating experience to find a suitable partner, making it possible to combat the declining birthrate and increase the number of marriages.

[0858] The processing flow will be explained below.

[0859] Step 1:

[0860] The user inputs basic information (such as name, age, gender, hobbies, and desired partner conditions) via the terminal, which then sends this information to the server.

[0861] Step 2:

[0862] The server stores the received basic information in a database.

[0863] Step 3:

[0864] The user presses the start button for the sample chat via the terminal, and the terminal sends a request to start the sample chat to the server.

[0865] Step 4:

[0866] The server calls the generated AI and sets up the chat session. The server notifies the device that it is ready.

[0867] Step 5:

[0868] The device provides a chat interface to the user, who initiates a dialogue with the AI ​​and answers questions posed by it.

[0869] Step 6:

[0870] The server collects and analyzes chat content in real time, extracting information such as the user's personality, conversational tendencies, and desired conditions.

[0871] Step 7:

[0872] The server generates an avatar that reflects the user's characteristics based on the information extracted.

[0873] Step 8:

[0874] The server sets up chat sessions with other users' avatars, and the avatars converse with each other.

[0875] Step 9:

[0876] The server records the chat content between avatars and analyzes the match score (compatibility score) based on the records.

[0877] Step 10:

[0878] The server selects chat content with a high degree of matching and creates recommended chats.

[0879] Step 11:

[0880] The device displays the recommended chat content to the user, and the user confirms the chat content.

[0881] Step 12:

[0882] The user selects their desired match, and the device sends that preference to the server.

[0883] Step 13:

[0884] The server checks whether both users want to be matched, and if both agree, the server makes the match happen.

[0885] Step 14:

[0886] The server will notify both users that a match has been made.

[0887] Example 1

[0888] 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."

[0889] Conventional online matching systems have difficulty in matching users based on their individual characteristics and desired conditions, making it difficult to provide effective matching results. Furthermore, protecting user privacy and achieving highly accurate matching have been issues. This has made it difficult for users to find a suitable partner, resulting in reduced matching efficiency.

[0890] 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.

[0891] In this invention, the server includes: means for a user to input basic information via a terminal; means for the server to receive the basic information and store it in a storage device; means for the user to issue a request to start a sample chat with an AI; means for the terminal to send the request to the server; means for the server to generate an interactive session with the AI ​​based on the request; means for the terminal to provide an interactive interface to the user; means for the server to collect and analyze the content of the dialogue between the user and the AI; means for the server to generate a digital avatar that reflects the user's characteristics based on the analysis results; means for the server to set up an interactive session between the digital avatars and record the content of the dialogue; means for the server to analyze the recorded content of the dialogue and calculate a compatibility score; means for the server to recommend a dialogue log with a high compatibility score to the user; means for the terminal to display the recommended content of the dialogue to the user and confirm it; means for the user to select a desired match; means for the terminal to send the selected state of the desired match to the server; and means for the server to establish a match if both users desire a match. This enables highly accurate matching that reflects the characteristics and preferences of users.

[0892] "User" refers to an individual who uses the system to input basic information and is matched through dialogue with artificial intelligence.

[0893] "Terminal" refers to an electronic device that allows a user to input basic information and use an interactive interface. Examples include smartphones and computers.

[0894] "Server" refers to a central computer system that receives, stores, and processes information sent by users and terminals.

[0895] "Basic information" refers to the personal information and desired conditions that a user enters into the system, and includes, for example, name, age, gender, hobbies, and desired partner conditions.

[0896] "Artificial intelligence" is a general term for programs and systems that interact with users and analyze the information they collect. Examples include generative AI models.

[0897] A "sample chat" is an interactive session that a user has with an AI, with the purpose of gathering information about the user's characteristics and desired conditions.

[0898] "Dialogue interface" refers to the screen display and input means that allow the user to interact with artificial intelligence.

[0899] A "digital avatar" is a character with a virtual personality that reflects the characteristics and wishes of a user, and is generated to interact with other avatars.

[0900] "Dialogue content" refers to messages and conversation logs in dialogue between a user and an artificial intelligence, or between digital avatars.

[0901] The "compatibility" is a numerical value or index that indicates the compatibility between users, calculated by analyzing the content of the conversation.

[0902] "Recommendation" refers to the act of suggesting compatible partners and conversation content to the user based on the compatibility calculated by the server.

[0903] "Matching preference" refers to a user's expression of intent to actually be matched with the recommended partner or the content of the conversation.

[0904] "Notification" refers to the act of the server transmitting information to the user, and refers to a message informing the user of a match and its results.

[0905] The system of the present invention begins when a user inputs basic information via a terminal, which is then received and stored by a server. The user then engages in a sample chat with an AI, and a digital avatar that reflects the user's characteristics is generated by analyzing the content of the conversation. The system then provides a series of processes by having the avatars chat with each other, evaluating their compatibility, and recommending highly compatible partners to the user. The main processes are explained in detail below.

[0906] Enter and save basic information

[0907] The terminal provides an interface for the user to enter basic information (such as name, age, gender, hobbies, and desired partner criteria). When the user enters this information and presses the send button, the terminal sends the information to the server. The server stores the received information in a database and uses it for subsequent processing. In this case, a relational database management system such as MySQL is used as the database.

[0908] Start a sample chat

[0909] The device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. Upon receiving the request, the server invokes a generative AI model (e.g., OpenAI's GPT-3) and sets up a chat session with the user. The device then provides the user with a chat interface, allowing the user to answer questions posed by the AI.

[0910] Collection and analysis of chat content

[0911] The server collects chat content between the user and the AI ​​in real time. A natural language processing library (e.g., NLTK) is used to analyze the collected data. The analysis results are used to extract characteristics such as the user's personality, conversational tendencies, and desired conditions.

[0912] Digital avatar generation

[0913] The server then generates a digital avatar that reflects the user's characteristics and preferences based on the analysis results. This avatar then engages in simulated conversations on behalf of the user, improving the efficiency of matching users.

[0914] Avatar-to-avatar chat settings

[0915] The server sets up chat sessions between the generated digital avatars. The avatars converse with each other and record the conversations. The server analyzes the conversations and calculates the compatibility of each avatar. Machine learning algorithms are often used to calculate compatibility.

[0916] Matching result recommendations

[0917] The server selects chat content with a high degree of compatibility and recommends it to the user. The terminal displays the recommended chat content to the user and confirms whether the user actually wants to be matched. If the user confirms the recommended content and wishes to be matched, the terminal transmits the selection status to the server.

[0918] Matching is completed

[0919] The server confirms that both users are willing to match, and if both agree, the match is established. Once a match is established, the server notifies both users. Notifications can be sent via email or in-app message.

[0920] Specific examples

[0921] For example, let's consider the case where User A and User B use the system. User A first enters basic information and sends it to the server. Next, User A participates in a sample chat with the generation AI, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates a digital avatar for User A.

[0922] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B and sets up a chat session between the two avatars. The content of the conversation is recorded, and the server calculates the compatibility based on the analysis results. If the compatibility is high, it is recommended to User A and User B.

[0923] If User A and User B check the recommended chat content and agree to be compatible, the server will match them and notify them, allowing users to find compatible partners more effectively and efficiently.

[0924] Prompt Sentence Examples

[0925] By inputting questions such as "What are your hobbies?", "How do you spend your holidays?", and "What kind of person is your ideal partner?" into the generative AI model, the user's characteristics and preferences can be extracted.

[0926] Through the above process, the system can analyze the user's characteristics and preferences in detail and achieve highly accurate matching.

[0927] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0928] Step 1: Enter and submit user information

[0929] The terminal provides an interface for the user to input basic information (such as name, age, sex, hobbies, and desired partner conditions).

[0930] Input: The user enters basic information into the terminal.

[0931] How it works: The user enters basic information and presses the submit button.

[0932] Output: The terminal sends the entered information to the server.

[0933] Step 2: Receiving and storing user information

[0934] The server stores the received user basic information in a database.

[0935] Input: Basic information of the user sent from the device.

[0936] Operation: The server analyzes the received information and stores it in a database, such as MySQL.

[0937] Output: User information stored in the database.

[0938] Step 3: Prepare to start a sample chat

[0939] The terminal provides the user with a button to start a sample chat.

[0940] Input: User presses the start button to begin a sample chat.

[0941] Operation: The device sends a request to the server to start a sample chat.

[0942] Output: A sample chat start request sent to the server.

[0943] Step 4: Invoke the generative AI model and set up a chat session

[0944] Based on the received request, the server invokes the generative AI model and sets up a chat session with the user.

[0945] Input: A sample chat start request.

[0946] How it works: The server invokes a generative AI model (e.g., OpenAI's GPT-3) and sets up a chat session.

[0947] Output: The configured chat session.

[0948] Step 5: Providing a chat interface

[0949] The device provides the user with a chat interface, creating an environment in which the user can interact with the AI.

[0950] Input: The configured chat session.

[0951] Behavior: The device displays and provides the user with a chat interface (text boxes, send buttons, etc.).

[0952] Output: A chat interface available to the user.

[0953] Step 6: Collecting and analyzing chat content

[0954] The server collects and analyzes chat content between the user and the generative AI model in real time.

[0955] Input: The interaction between the user and the generative AI model.

[0956] How it works: The server collects chat content and analyzes it using a natural language processing library (e.g., NLTK). Through the analysis, it extracts information about the user's personality, conversational tendencies, and desired conditions.

[0957] Output: User characteristic information as the analysis result.

[0958] Step 7: Generate a digital avatar

[0959] Based on the analysis results, the server generates a digital avatar that reflects the user's characteristics and wishes.

[0960] Input: User characteristics information.

[0961] How it works: The server generates a digital avatar based on the user's characteristics.

[0962] Output: The generated digital avatar.

[0963] Step 8: Setting up a chat session between avatars

[0964] The server sets up a chat session between the generated digital avatars.

[0965] Input: A generated digital avatar.

[0966] How it works: A server sets up chat sessions between digital avatars and records the conversations.

[0967] Output: Configured avatar chat sessions and recorded dialogue.

[0968] Step 9: Record and analyze chat content

[0969] The server records the content of the conversation between the avatars and analyzes the content.

[0970] Input: Conversation between avatars.

[0971] How it works: The server analyzes the recorded conversations and calculates the relevance using machine learning algorithms.

[0972] Output: The calculated fitness.

[0973] Step 10: Recommending matching results

[0974] The server selects dialogue content with high suitability and recommends it to the user.

[0975] Input: The calculated fitness.

[0976] Operation: The server selects the dialogue content to recommend based on the relevance result and creates a recommendation list.

[0977] Output: Recommended dialogue for the user.

[0978] Step 11: Confirm your match preference

[0979] The terminal displays the recommended dialogue content to the user and provides a means for the user to confirm it.

[0980] Input: Recommended dialogue.

[0981] Operation: The device displays the recommendations to the user and allows the user to select a match.

[0982] Output: Confirmation of user's match preference.

[0983] Step 12: Send your match request and get it done

[0984] If the user selects a match, that information is sent to the server.

[0985] Input: User's match preference selection.

[0986] Operation: The device sends the user's selection status to the server. The server confirms whether both users wish to be matched and establishes the match.

[0987] Output: Matches made and notifications.

[0988] Through the above processing steps, the system can analyze the user's characteristics and preferences in detail and achieve highly accurate matching.

[0989] (Application example 1)

[0990] 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."

[0991] To improve production efficiency in factories, it is important to create optimal team structures based on the characteristics of each robot. However, efficient team building is difficult because there is no established method for evaluating the compatibility and collaborative effectiveness of factory robots. The present invention aims to provide a means to solve this problem.

[0992] 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.

[0993] In this invention, the server includes means for a user to input basic information via a terminal, means for the server to receive the basic information and store it in a database, means for a user to issue a request to start a sample chat with an AI, means for the terminal to send the request to the server, means for the server to generate a chat session with the AI ​​based on the request, means for the terminal to provide a chat interface to the user, means for the server to collect and analyze chat content between the user and the AI, means for the server to generate an avatar that reflects the user's characteristics based on the analysis results, and means for the server to set up a chat session between the avatars and display the chat content. The system includes a means for recording chat content, a means for the server to analyze the recorded chat content and calculate a degree of matching, a means for the server to recommend chat logs with a high degree of matching to the user, a means for the terminal to display the recommended chat content to the user and for confirmation, a means for the user to select a desired match, a means for the terminal to transmit the selected state of the desired match to the server, a means for the server to establish a match when both users desire a match, a means for inputting basic information about the factory robot, a means for generating an avatar based on the characteristics of the robot, and a means for analyzing chat sessions between the avatars and recommending an optimal team composition. This enables evaluation of the compatibility between factory robots and efficient team building.

[0994] "Users" are factory managers and operators who input information and use the system's various functions.

[0995] A "terminal" is a device used by a user to enter information or interact with a system.

[0996] "Basic information" refers to data that includes detailed information about users and robots, such as their characteristics and roles.

[0997] A "server" is a device that receives basic information about users and robots, analyzes and stores the data, and manages and processes the entire system.

[0998] A "database" is a storage device for storing various data such as basic information and analysis results.

[0999] A "request" is a request or command given by a user to a system.

[1000] "Artificial intelligence" refers to computer programs used within the system to generate chat sessions and analyze the characteristics of users and robots.

[1001] A "chat session" is a series of conversations that take place between a user or a robot and an artificial intelligence.

[1002] A "chat interface" is a screen or application that allows users and robots to conduct chat sessions.

[1003] "Chat Content" means the text and messages exchanged during a chat session.

[1004] "Analysis" is the process of analyzing collected chat content and extracting characteristics and trends.

[1005] An "avatar" is a virtual character that reflects the characteristics of a user or a robot.

[1006] "Matching degree" is a score that indicates the compatibility and cooperative effect between avatars.

[1007] "Recommendation" means that the system suggests specific avatars and team compositions to users based on analysis results and compatibility scores.

[1008] "Confirmation" refers to the process by which a user decides whether to accept a recommendation from the system.

[1009] A "factory robot" is an automated mechanical device that performs work on a production line or in a factory.

[1010] A "team composition" is a combination of multiple robot avatars working together to achieve optimal production efficiency.

[1011] This invention is a system that understands the characteristics of robots used in factories and recommends optimal team composition. The system starts operation when a user inputs basic information using a terminal and sends it to a server.

[1012] Enter and save basic information

[1013] The user inputs basic information about the factory robot (model, functions, capabilities, role, etc.) via a terminal. This information is sent to a server and stored in a database. The database is stored in a cloud environment or on a server installed in the factory, where the information is managed and accessed.

[1014] Starting and running a sample chat

[1015] When a user requests a sample chat, the device sends the request to the server. Based on the received request, the server sets up a chat session using a generative AI model. An avatar is generated based on the robot's basic information, and this avatar chats with the AI.

[1016] Collection and analysis of chat content

[1017] The terminal provides the user with a chat interface, and the server collects chat content between the robot and the AI ​​in real time. The collected data is analyzed using a generative AI model to extract information about the robot's characteristics, performance, and collaboration tendencies.

[1018] Avatar generation and matching evaluation

[1019] Based on the analysis results, the server generates avatars that reflect the characteristics of each robot. Chat sessions are set up between the generated avatars, and the chat content is recorded. The server then analyzes the recorded data again to calculate the degree of matching between the avatars, which is used to evaluate their compatibility and collaborative effectiveness.

[1020] Recommendations and Match Confirmation

[1021] The server recommends chat logs of avatars with a high degree of matching to the user. The device displays these recommendations to the user, who then checks the recommendations and selects their desired match. The user's selection is sent to the server, which then works to create the optimal team composition.

[1022] Hardware and Software Use

[1023] The system uses cloud servers, factory servers, and user devices (tablets and PCs) as hardware. Python and OpenAI API (GPT-4 model) are used as software. A relational database management system (RDBMS) is used for database management.

[1024] Specific examples

[1025] For example, suppose factory robot A is an arm robot responsible for welding, and robot B is a transport robot responsible for transporting materials. The user enters basic information about these robots into a terminal and sends it to the server. The server generates avatars using a generative AI model and initiates a chat session between the avatars. Below is a specific example of a prompt sentence.

[1026] Example prompt sentence:

[1027] Start chatting as robot named Robo1, model: arm robot, ability: welding, assembly, role: welder.

[1028] A chat session is held based on this prompt, and the server analyzes the collected data and recommends the optimal team composition to the user, thereby improving the factory's production efficiency.

[1029] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1030] Step 1:

[1031] The user uses a terminal to input basic information about the factory robot. Specifically, they input detailed information such as the robot's model, functions, capabilities, and role, and then press the send button. The input information is sent from the terminal to the server. The server stores the received basic information in a database. This information is used to understand the robot's characteristics.

[1032] Step 2:

[1033] A user issues a request to start a sample chat. Specifically, the request is sent to the server by pressing the Start Sample Chat button on the device. Based on the received request, the server generates an avatar for each robot and sets up a chat session using the generative AI model. At this time, a prompt sentence is generated and input into the AI ​​model.

[1034] Step 3:

[1035] The server calls the generative AI model and initiates a chat session with each robot avatar. The device provides the user with a chat interface, and the chat session proceeds in real time. The server collects and stores the content of the conversation between the robot and the AI ​​in real time. The chat content is dynamically generated by the generative AI based on the input prompt.

[1036] Step 4:

[1037] The server analyzes the chat content collected. Using a generative AI model, it analyzes each robot's characteristics, conversational tendencies, and collaboration potential. Specifically, it extracts the robot's characteristic patterns and working behavior from the chat content and converts them into numerical data and categorical information. The results of this analysis are reflected in each robot's avatar.

[1038] Step 5:

[1039] Based on the analysis results, the server generates an avatar that reflects the characteristics of each robot. This avatar is a virtual character that corresponds to the robot's characteristics and is used to interact with other avatars. The generated avatar is displayed in a way that is easy for users and administrators to understand.

[1040] Step 6:

[1041] The server sets up a chat session between the generated avatars. The avatars converse and record the content. Specifically, a conversation between the avatars is simulated to evaluate the effectiveness of collaboration and compatibility. A scenario is generated based on the prompt text, and the conversation between the avatars progresses.

[1042] Step 7:

[1043] The server analyzes the recorded chat content and calculates the degree of matching between avatars. Specifically, it evaluates the consistency and cooperation of the chat content and outputs a numerical compatibility score. This allows the compatibility of each avatar and their suitability as a team to be evaluated.

[1044] Step 8:

[1045] The server recommends chat logs with a high degree of matching to the user. The device displays the recommended chat content to the user, who then confirms it. Specifically, avatars are recommended based on compatibility scores, and the user can view the recommended content and decide whether or not it is suitable for them.

[1046] Step 9:

[1047] The user checks the recommended chat content and selects whether they wish to be matched. The device sends the user's selection to the server. If both users wish to be matched, the server establishes the match and sends appropriate notifications. This determines the optimal team composition and reflects it on the actual production line.

[1048] 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.

[1049] The system of the present invention combines an emotion engine that recognizes the user's emotions, analyzes the user's characteristics through a chat session between the user and a generating AI (artificial intelligence), and generates an "avatar" based on the user. Furthermore, the system allows the generated avatars to chat with each other, evaluates the degree of matching, and recommends to the user partners with high compatibility. The system of the present invention can be implemented as follows.

[1050] User Registration

[1051] The device provides an interface for users to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand what kind of match the user is looking for.

[1052] Start a sample chat

[1053] The terminal provides the user with a button to start a sample chat. When the user presses this button, the terminal sends a request to start a sample chat to the server. Based on the received request, the server sets up a chat session with the AI ​​and makes the necessary preparations.

[1054] Sample chat

[1055] The server calls the generated AI and starts a chat session between the user and the AI. The device provides the user with a chat interface and helps them answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions. At this time, the emotion engine also extracts the user's emotional information and incorporates it into the analysis.

[1056] Avatar generation

[1057] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and wishes. This avatar converses with other avatars on the user's behalf, improving the efficiency of user matching. Emotional information obtained from the emotion engine is also reflected, improving the avatar's expressiveness and enabling more natural and realistic conversations.

[1058] Avatar-to-avatar chat

[1059] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of the avatar chat and calculates the degree of matching (compatibility score).

[1060] Matching evaluation and recommendation

[1061] The server selects chat contents with a high degree of matching and recommends them to the user. The terminal displays the recommended chat contents to the user and confirms whether the user actually wants to be matched.

[1062] Confirmation and establishment of matching requests

[1063] If a user checks the recommended chat content and wishes to be matched, the device sends that request to the server. The server then checks whether both users wish to be matched. If both agree, the server establishes the match and notifies both users.

[1064] Specific examples

[1065] For example, suppose that user A and user B use this system. User A first enters basic information and sends it to the server. Next, user A participates in a sample chat with the generation AI, and the server analyzes the chat content and extracts user A's characteristics. Based on the results, the server generates an avatar for user A. At this time, the emotion engine also analyzes user A's emotional information and reflects it in the avatar.

[1066] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[1067] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[1068] This system will make it easier for users with little dating experience to find a suitable partner, which will help combat the declining birthrate and increase the number of marriages.In addition, the use of an emotion engine will make avatar conversations more natural and friendly, improving the user experience.

[1069] The processing flow will be explained below.

[1070] Step 1:

[1071] The user inputs basic information (such as name, age, gender, hobbies, and desired partner conditions) via the terminal, which then sends this information to the server.

[1072] Step 2:

[1073] The server stores the received basic information in a database.

[1074] Step 3:

[1075] The user presses the start button for the sample chat via the terminal, and the terminal sends a request to start the sample chat to the server.

[1076] Step 4:

[1077] The server calls the generation AI, sets up a chat session, and initializes the emotion engine to prepare for analyzing the chat content.

[1078] Step 5:

[1079] The device provides the user with a chat interface, where the user initiates a dialogue with the generated AI and answers questions posed by the generated AI.

[1080] Step 6:

[1081] The server collects chat content in real time and extracts the user's emotional information using an emotion engine. The analysis results include information on the user's personality, conversational tendencies, desired conditions, and other emotional information.

[1082] Step 7:

[1083] Based on the information extracted by the server, an avatar is generated that reflects the user's characteristics and also includes emotional information.

[1084] Step 8:

[1085] The server sets up chat sessions with other users' avatars, and the avatars converse with each other. The server also records the emotional information that the avatars acquire through the conversation.

[1086] Step 9:

[1087] The server records the chat content and emotional information between avatars, and analyzes the degree of matching (compatibility score) based on these records.

[1088] Step 10:

[1089] The server selects chat content and emotional information with a high degree of matching and creates it as a recommended chat.

[1090] Step 11:

[1091] The device displays the recommended chat content to the user, who then checks the chat content and considers the emotional information.

[1092] Step 12:

[1093] The user selects their desired match, and the device sends that preference to the server.

[1094] Step 13:

[1095] The server checks whether both users want to be matched, and if both agree, the server makes the match happen.

[1096] Step 14:

[1097] The server will notify both users that a match has been made.

[1098] Example 2

[1099] 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."

[1100] Conventional matching systems are inefficient when handling a large number of user information and have difficulty properly reflecting user characteristics and emotional information. Furthermore, the accuracy of matching between users is low, making it difficult to find a compatible partner. Furthermore, if a user has little interaction experience, they are unable to communicate appropriately, resulting in low satisfaction. The present invention aims to solve these problems through highly accurate analysis using an emotion engine and simulation using avatars.

[1101] 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.

[1102] In this invention, the server includes a means for generating a chat session with the generative AI model, a means for collecting and analyzing chat content between the user and the generative AI model, and a means for using an emotion engine to analyze emotional information and reflect it in the avatar. This allows for highly accurate analysis of user characteristics and emotional information, thereby improving the accuracy of matching between users.

[1103] A "generative AI model" is a type of artificial intelligence that uses natural language processing and machine learning techniques to enable dialogue with users.

[1104] "Basic information" refers to personal information such as name, age, sex, hobbies, and desired partner conditions that a user enters into the system.

[1105] A "chat session" refers to a series of interactions between a user and a generative AI model, or between avatars.

[1106] "Chat interface" refers to the screen and input devices that allow users to interact with generated AI models and other avatars.

[1107] An "emotion engine" refers to software or algorithms that analyze and extract emotional information from user dialogue.

[1108] An "avatar" is a virtual conversational agent that is generated to reflect the user's characteristics and emotional information.

[1109] The "matching degree" is an index that indicates the compatibility or degree of compatibility between users, calculated by analyzing the content of chats between avatars.

[1110] "Recommendation" refers to the act of the server presenting chat logs and avatars with a high degree of matching to the user.

[1111] "Talk tendencies" is information about what topics and expressions a user likes to use in conversations.

[1112] "Desired conditions" refer to the attributes and conditions that a user desires in a partner with whom they wish to be matched.

[1113] "Analysis" refers to the process of analyzing data based on chat content and emotional information collected by the server and extracting user characteristics and emotions.

[1114] The present invention provides a system for improving the efficiency of matching between users by utilizing avatars that reflect the user's emotional information. A method for specifically implementing this system will be described below.

[1115] First, the device provides an interface for the user to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand the type of match the user is looking for.

[1116] Next, the device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. Based on the request, the server sets up a chat session with a generative AI model (e.g., GPT-4) and makes the necessary preparations.

[1117] The server calls the generative AI model and initiates a chat session between the user and the AI. The device provides the user with a chat interface and helps them answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions. At this time, the server also extracts the user's emotional information using an emotion engine and incorporates it into the analysis.

[1118] A specific example of a question would be for the generative AI model to ask, "Hello, what happened today?" and for the user to respond, "I read a new book today."

[1119] Once the analysis is complete, the server generates an avatar that reflects the user's characteristics and wishes based on the analysis results. This avatar converses with other avatars on the user's behalf, improving the efficiency of user matching. Emotional information obtained from the emotion engine is also reflected, improving the avatar's expressiveness and enabling more natural and realistic conversations.

[1120] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of these avatar chats and calculates the degree of matching (compatibility score). The server selects chat content with a high degree of matching and recommends it to the user. The device displays the recommended chat content to the user and confirms whether the user actually wishes to be matched.

[1121] Specifically, User A enters basic information and sends it to the server. Next, User A participates in a sample chat with the generative AI model, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates an avatar for User A. Meanwhile, User B also enters basic information and participates in a sample chat with the generative AI model. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[1122] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[1123] An example of a prompt is as follows:

[1124] When inputting the user's basic information: The terminal provides an interface for inputting the user's basic information.

[1125] At the start of a sample chat: When the user presses the Start Sample Chat button, the terminal sends a request to the server.

[1126] When generating an avatar: The server generates an avatar based on the analysis results, and also reflects emotional information.

[1127] Through the above steps, the system of the present invention can achieve highly accurate matching by using an avatar that reflects the user's characteristics and emotional information.

[1128] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1129] Step 1:

[1130] User registration interface provided

[1131] The terminal provides an interface for the user to input basic information (such as name, age, gender, hobbies, and desired partner conditions). The user's input becomes input to the terminal, and the terminal sends this information to the server. Specifically, the terminal displays a form, and when the user enters information and presses the send button, the data is sent to the server. The server saves this information in a database. The input is the user's basic information, and the output is the user information saved in the database.

[1132] Step 2:

[1133] Sample Chat Start Request

[1134] The device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. The server receives the request and prepares to set up a chat session with the generative AI model. The input is the user's request to start a sample chat, and the output is a state in which preparations for a chat session with the generative AI model are complete.

[1135] Step 3:

[1136] Sample chat

[1137] The server calls the generative AI model and starts a chat session between the user and the AI. The device provides the user with a chat interface and supports the user in answering questions from the AI. Specifically, the generative AI model asks, "Hello, what happened today?" and the user replies, "I read a new book today." The server collects and analyzes the entire content of this chat session in real time. The input is the chat content between the user and the AI, and the output is analyzed user characteristic information.

[1138] Step 4:

[1139] Emotional information analysis

[1140] The server uses an emotion engine to extract the user's emotional information during the chat session and incorporates it into the analysis data. Specifically, it identifies emotions such as positive, negative, and neutral from the user's comments and records them as numerical values. The input is the chat content, and the output is the analyzed emotional information.

[1141] Step 5:

[1142] Avatar generation

[1143] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and wishes. Emotional information obtained from the emotion engine is also reflected in the avatar. Specifically, the server generates an avatar with a specific profile based on data such as "User ID: 001, Personality: Curious, Hobby: Reading, Emotional Information: Happy." The input is the analysis results and emotional information, and the output is the generated avatar.

[1144] Step 6:

[1145] Avatar-to-avatar chat

[1146] The server sets up a chat session between the generated avatars. The avatars begin a conversation, and the content of that conversation is recorded. As a specific example of a conversation, avatar A might ask, "What kind of books do you like?" and avatar B might reply, "I like mystery novels." The input is the generated avatar, and the output is the recorded chat content.

[1147] Step 7:

[1148] Matching evaluation and recommendation

[1149] The server analyzes the recorded chat content and calculates the degree of matching. It selects chat content with a high compatibility score and recommends it to the user. Specifically, the server analyzes the chat content, calculates a score, and creates a ranking. The input is the chat content, and the output is the recommended chat content and its compatibility score.

[1150] Step 8:

[1151] View and review recommendations

[1152] The terminal displays the recommended chat content to the user and confirms whether the user actually wants to be matched. The input is the recommended chat content, and the output is the user's choice of desired match.

[1153] Step 9:

[1154] Confirmation and establishment of matching requests

[1155] The server checks whether both users wish to be matched. If both agree, the match is established and a notification is sent to both users. Specifically, the server checks the wishes of "User ID: 001" and "User ID: 002" and sends a notification if a match is established. The input is the user's match request, and the output is a notification that a match has been established.

[1156] (Application example 2)

[1157] 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."

[1158] Conventional food delivery systems have the problem of not being able to recommend dishes that match a user's preferences and mood. Users may also have difficulty choosing the best dish based on their emotional state. Furthermore, simple recommendation systems often do not improve the user experience, resulting in a decrease in user satisfaction.

[1159] The identification process by the identification 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 means for analyzing a user's emotions in real time using an emotion engine and providing recommendations based on the user's preferences and mood, means for recommending restaurants and dishes for food delivery to the user, and means for analyzing chat content using artificial intelligence and extracting information such as the user's conversation tendencies, desired conditions, personality, and emotional information. This makes it possible to recommend optimal dishes based on the user's emotions and preferences, enabling a food delivery service with high user satisfaction.

[1160] "User" refers to an individual who uses the Service.

[1161] A "terminal" is an electronic device that allows a user to input or receive information, and includes smartphones, computers, and the like.

[1162] "Basic information" refers to personal information about the user, such as name, age, gender, preferences, and allergies.

[1163] "Server" refers to a computer system that processes and stores information received from users and provides necessary functionality.

[1164] A "database" refers to a system for storing various information in an organized manner and making it accessible.

[1165] A "request" refers to a request by a user to initiate a particular action.

[1166] "Artificial intelligence" refers to systems or programs designed to mimic human intelligence, and in this case refers to generative AI models.

[1167] An "emotion engine" refers to a system or program for analyzing a user's emotions.

[1168] "Chat session" refers to a period of interaction or activity between a user and an artificial intelligence.

[1169] "Chat interface" refers to the screen and input means that allow users to interact with artificial intelligence.

[1170] An "avatar" refers to a virtual character created to reflect a user's characteristics and wishes.

[1171] "Matching degree" refers to a compatibility score calculated by analyzing the content of the conversation between avatars.

[1172] "Recommendation" refers to the act of a system suggesting specific information or options to a user.

[1173] "Food delivery" refers to a service that delivers food ordered by a user to a specified location.

[1174] The system of this invention combines an emotion engine that recognizes the user's emotions with a generative AI to recommend food delivery options based on the user's preferences and mood. The user inputs basic information using a terminal, and the server processes and analyzes that information.

[1175] Hardware and software used

[1176] Hardware:

[1177] Smartphone

[1178] server

[1179] software:

[1180] Emotion engine libraries (e.g., Affective Computing)

[1181] Generative AI models (e.g., GPT-4)

[1182] Database management system (e.g. MySQL)

[1183] Front-end frameworks (e.g. React Native)

[1184] System processing steps

[1185] User Registration:

[1186] Users enter basic information (such as name, age, gender, favorite foods, allergies, and desired food conditions) via a smartphone app. This basic information is sent to the server via the device and stored in a database.

[1187] Start a sample chat:

[1188] The user initiates a chat session with the emotion engine and generative AI by pressing the chat button on the device, which sends a request to the server and starts the chat session.

[1189] Sample chat execution:

[1190] The server uses a generative AI model to communicate with the user, and an emotion engine analyzes emotions in real time from the content of the user's conversation and uses this information to determine the user's preferences and mood.

[1191] Avatar Creation:

[1192] The server generates an avatar that reflects the user's characteristics and wishes based on the analysis results of the emotion engine. The generated avatar acts as a proxy character for the user and interacts with other users' avatars.

[1193] Restaurant and food recommendations:

[1194] The server analyzes the interactions between the generated avatars and recommends restaurants and dishes that go well together. It also lists food delivery options and provides optimal recommendations to users.

[1195] User presentation and confirmation:

[1196] The recommended dishes and restaurants are displayed on the device screen, and the user can review the recommended options and decide whether to actually order.

[1197] Order confirmation:

[1198] Once the order is confirmed, the server sends the order to the corresponding restaurant, and the order history is saved in the user's database.

[1199] Processing example

[1200] For example, a user logs in to the app and taps the "Recommend me today's specials!" button. At that time, the app starts an AI chat and asks, "How are you feeling today?" If the user replies, "I feel like eating something a little spicy today," the emotion engine analyzes the user's emotions and preferences and generates a list of spicy dishes. Next, the AI ​​chat suggests, "How about the Shin Ramyun from this restaurant?" If the user accepts the suggestion and confirms the order, the system sends the order to the restaurant.

[1201] Prompt Sentence Examples

[1202] "Would you like me to help you find a dish that matches your mood today? Tell me how you're feeling right now."

[1203] Using this system, recommended dishes and restaurants can be efficiently recommended based on the user's emotions and preferences, thereby improving user satisfaction.

[1204] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1205] Step 1:

[1206] The user enters basic information (such as name, age, gender, favorite foods, allergies, and desired food conditions) via a smartphone app. The entered basic information is sent to the server through the smartphone's input interface. The server stores the received information in a database. In this process, the user's input data is sent to the server and inserted into the user table in the database.

[1207] Step 2:

[1208] The user presses the "Start Chat" button on the smartphone app to start a chat session between the emotion engine and the generative AI. This causes the device to send a chat session request to the server. The server receives the request and calls the generative AI model to generate the chat session. In this process, the server creates a chat session object using the generative AI model and imports the user's basic information.

[1209] Step 3:

[1210] The server uses the generative AI model to provide a chat interface to users. Users answer questions posed by the AI ​​through the chat screen on their smartphones. The server collects chat content in real time and performs emotion analysis using an emotion engine. In this process, the user's text input is sent to the server and analyzed by the emotion engine.

[1211] Step 4:

[1212] The server generates an avatar that reflects the user's characteristics and wishes based on the analysis results of the emotion engine. This avatar is required to act as the user's representative character and to interact with other users' avatars. The generated avatar information is saved in a database. In this process, avatar data is created by combining emotion data and basic information.

[1213] Step 5:

[1214] The server sets up chat sessions between the generated avatars. The content of the avatar chats is recorded and analyzed by the server to calculate the degree of matching. In this process, the avatar conversation logs are analyzed and a compatibility score is calculated using a matching algorithm.

[1215] Step 6:

[1216] The server recommends chat logs with a high degree of matching to the user. The recommended dishes and restaurants are displayed on the smartphone screen. The user checks the options and decides whether to actually order. In this process, the recommendations are displayed on the user interface.

[1217] Step 7:

[1218] When a user confirms an order for a recommended dish or restaurant, the order confirmation information is sent from the smartphone to the server. The server then sends the order to the restaurant based on that information and saves the order history in the user's database. In this process, the order data is sent to the restaurant's system and recorded in the database.

[1219] This trend will enable food delivery recommendations based on users' emotions and preferences, making it possible to provide a service that highly satisfies users.

[1220] 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.

[1221] 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.

[1222] 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.

[1223] [Fourth embodiment]

[1224] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1225] 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.

[1226] 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).

[1227] 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.

[1228] 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.

[1229] 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).

[1230] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[1231] 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.

[1232] 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.

[1233] 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.

[1234] 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.

[1235] 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.

[1236] 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."

[1237] The system of the present invention analyzes the characteristics of a user through a chat session between the user and a generating AI (artificial intelligence) and generates an "avatar" based on the user. The system then allows the avatars to chat with each other, evaluates the degree of matching, and recommends to the user partners with high compatibility. The system of the present invention can be implemented as follows.

[1238] User Registration

[1239] The device provides an interface for users to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand what kind of match the user is looking for.

[1240] Start a sample chat

[1241] The terminal provides the user with a button to start a sample chat. When the user presses this button, the terminal sends a request to start a sample chat to the server. Based on the received request, the server sets up a chat session with the AI ​​and makes the necessary preparations.

[1242] Sample chat

[1243] The server calls the generated AI and starts a chat session between the user and the AI. The device provides the user with a chat interface and helps the user answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions.

[1244] Avatar generation

[1245] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and preferences. This avatar then converses with other avatars on the user's behalf, improving the efficiency of matching users.

[1246] Avatar-to-avatar chat

[1247] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of the avatar chat and calculates the degree of matching (compatibility score).

[1248] Matching evaluation and recommendation

[1249] The server selects chat contents with a high degree of matching and recommends them to the user. The terminal displays the recommended chat contents to the user and confirms whether the user actually wants to be matched.

[1250] Confirmation and establishment of matching requests

[1251] If a user checks the recommended chat content and wishes to be matched, the device sends that request to the server. The server then checks whether both users wish to be matched, and if both agree, the match is established. Once a match is established, the server notifies both users.

[1252] Specific examples

[1253] For example, suppose that User A and User B use this system. User A first enters basic information and sends it to the server. Next, User A participates in a sample chat with the generation AI, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates an avatar for User A.

[1254] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[1255] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[1256] This system will make it easier for users with little dating experience to find a suitable partner, making it possible to combat the declining birthrate and increase the number of marriages.

[1257] The processing flow will be explained below.

[1258] Step 1:

[1259] The user inputs basic information (such as name, age, gender, hobbies, and desired partner conditions) via the terminal, which then sends this information to the server.

[1260] Step 2:

[1261] The server stores the received basic information in a database.

[1262] Step 3:

[1263] The user presses the start button for the sample chat via the terminal, and the terminal sends a request to start the sample chat to the server.

[1264] Step 4:

[1265] The server calls the generated AI and sets up the chat session. The server notifies the device that it is ready.

[1266] Step 5:

[1267] The device provides a chat interface to the user, who initiates a dialogue with the AI ​​and answers questions posed by it.

[1268] Step 6:

[1269] The server collects and analyzes chat content in real time, extracting information such as the user's personality, conversational tendencies, and desired conditions.

[1270] Step 7:

[1271] The server generates an avatar that reflects the user's characteristics based on the information extracted.

[1272] Step 8:

[1273] The server sets up chat sessions with other users' avatars, and the avatars converse with each other.

[1274] Step 9:

[1275] The server records the chat content between avatars and analyzes the match score (compatibility score) based on the records.

[1276] Step 10:

[1277] The server selects chat content with a high degree of matching and creates recommended chats.

[1278] Step 11:

[1279] The device displays the recommended chat content to the user, and the user confirms the chat content.

[1280] Step 12:

[1281] The user selects their desired match, and the device sends that preference to the server.

[1282] Step 13:

[1283] The server checks whether both users want to be matched, and if both agree, the server makes the match happen.

[1284] Step 14:

[1285] The server will notify both users that a match has been made.

[1286] Example 1

[1287] 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."

[1288] Conventional online matching systems have difficulty in matching users based on their individual characteristics and desired conditions, making it difficult to provide effective matching results. Furthermore, protecting user privacy and achieving highly accurate matching have been issues. This has made it difficult for users to find a suitable partner, resulting in reduced matching efficiency.

[1289] 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.

[1290] In this invention, the server includes: means for a user to input basic information via a terminal; means for the server to receive the basic information and store it in a storage device; means for the user to issue a request to start a sample chat with an AI; means for the terminal to send the request to the server; means for the server to generate an interactive session with the AI ​​based on the request; means for the terminal to provide an interactive interface to the user; means for the server to collect and analyze the content of the dialogue between the user and the AI; means for the server to generate a digital avatar that reflects the user's characteristics based on the analysis results; means for the server to set up an interactive session between the digital avatars and record the content of the dialogue; means for the server to analyze the recorded content of the dialogue and calculate a compatibility score; means for the server to recommend a dialogue log with a high compatibility score to the user; means for the terminal to display the recommended content of the dialogue to the user and confirm it; means for the user to select a desired match; means for the terminal to send the selected state of the desired match to the server; and means for the server to establish a match if both users desire a match. This enables highly accurate matching that reflects the characteristics and preferences of users.

[1291] "User" refers to an individual who uses the system to input basic information and is matched through dialogue with artificial intelligence.

[1292] "Terminal" refers to an electronic device that allows a user to input basic information and use an interactive interface. Examples include smartphones and computers.

[1293] "Server" refers to a central computer system that receives, stores, and processes information sent by users and terminals.

[1294] "Basic information" refers to the personal information and desired conditions that a user enters into the system, and includes, for example, name, age, gender, hobbies, and desired partner conditions.

[1295] "Artificial intelligence" is a general term for programs and systems that interact with users and analyze the information they collect. Examples include generative AI models.

[1296] A "sample chat" is an interactive session that a user has with an AI, with the purpose of gathering information about the user's characteristics and desired conditions.

[1297] "Dialogue interface" refers to the screen display and input means that allow the user to interact with artificial intelligence.

[1298] A "digital avatar" is a character with a virtual personality that reflects the characteristics and wishes of a user, and is generated to interact with other avatars.

[1299] "Dialogue content" refers to messages and conversation logs in dialogue between a user and an artificial intelligence, or between digital avatars.

[1300] The "compatibility" is a numerical value or index that indicates the compatibility between users, calculated by analyzing the content of the conversation.

[1301] "Recommendation" refers to the act of suggesting compatible partners and conversation content to the user based on the compatibility calculated by the server.

[1302] "Matching preference" refers to a user's expression of intent to actually be matched with the recommended partner or the content of the conversation.

[1303] "Notification" refers to the act of the server transmitting information to the user, and refers to a message informing the user of a match and its results.

[1304] The system of the present invention begins when a user inputs basic information via a terminal, which is then received and stored by a server. The user then engages in a sample chat with an AI, and a digital avatar that reflects the user's characteristics is generated by analyzing the content of the conversation. The system then provides a series of processes by having the avatars chat with each other, evaluating their compatibility, and recommending highly compatible partners to the user. The main processes are explained in detail below.

[1305] Enter and save basic information

[1306] The terminal provides an interface for the user to enter basic information (such as name, age, gender, hobbies, and desired partner criteria). When the user enters this information and presses the send button, the terminal sends the information to the server. The server stores the received information in a database and uses it for subsequent processing. In this case, a relational database management system such as MySQL is used as the database.

[1307] Start a sample chat

[1308] The device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. Upon receiving the request, the server invokes a generative AI model (e.g., OpenAI's GPT-3) and sets up a chat session with the user. The device then provides the user with a chat interface, allowing the user to answer questions posed by the AI.

[1309] Collection and analysis of chat content

[1310] The server collects chat content between the user and the AI ​​in real time. A natural language processing library (e.g., NLTK) is used to analyze the collected data. The analysis results are used to extract characteristics such as the user's personality, conversational tendencies, and desired conditions.

[1311] Digital avatar generation

[1312] The server then generates a digital avatar that reflects the user's characteristics and preferences based on the analysis results. This avatar then engages in simulated conversations on behalf of the user, improving the efficiency of matching users.

[1313] Avatar-to-avatar chat settings

[1314] The server sets up chat sessions between the generated digital avatars. The avatars converse with each other and record the conversations. The server analyzes the conversations and calculates the compatibility of each avatar. Machine learning algorithms are often used to calculate compatibility.

[1315] Matching result recommendations

[1316] The server selects chat content with a high degree of compatibility and recommends it to the user. The terminal displays the recommended chat content to the user and confirms whether the user actually wants to be matched. If the user confirms the recommended content and wishes to be matched, the terminal transmits the selection status to the server.

[1317] Matching is completed

[1318] The server confirms that both users are willing to match, and if both agree, the match is established. Once a match is established, the server notifies both users. Notifications can be sent via email or in-app message.

[1319] Specific examples

[1320] For example, let's consider the case where User A and User B use the system. User A first enters basic information and sends it to the server. Next, User A participates in a sample chat with the generation AI, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates a digital avatar for User A.

[1321] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B and sets up a chat session between the two avatars. The content of the conversation is recorded, and the server calculates the compatibility based on the analysis results. If the compatibility is high, it is recommended to User A and User B.

[1322] If User A and User B check the recommended chat content and agree to be compatible, the server will match them and notify them, allowing users to find compatible partners more effectively and efficiently.

[1323] Prompt Sentence Examples

[1324] By inputting questions such as "What are your hobbies?", "How do you spend your holidays?", and "What kind of person is your ideal partner?" into the generative AI model, the user's characteristics and preferences can be extracted.

[1325] Through the above process, the system can analyze the user's characteristics and preferences in detail and achieve highly accurate matching.

[1326] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1327] Step 1: Enter and submit user information

[1328] The terminal provides an interface for the user to input basic information (such as name, age, sex, hobbies, and desired partner conditions).

[1329] Input: The user enters basic information into the terminal.

[1330] How it works: The user enters basic information and presses the submit button.

[1331] Output: The terminal sends the entered information to the server.

[1332] Step 2: Receiving and storing user information

[1333] The server stores the received user basic information in a database.

[1334] Input: Basic information of the user sent from the device.

[1335] Operation: The server analyzes the received information and stores it in a database, such as MySQL.

[1336] Output: User information stored in the database.

[1337] Step 3: Prepare to start a sample chat

[1338] The terminal provides the user with a button to start a sample chat.

[1339] Input: User presses the start button to begin a sample chat.

[1340] Operation: The device sends a request to the server to start a sample chat.

[1341] Output: A sample chat start request sent to the server.

[1342] Step 4: Invoke the generative AI model and set up a chat session

[1343] Based on the received request, the server invokes the generative AI model and sets up a chat session with the user.

[1344] Input: A sample chat start request.

[1345] How it works: The server invokes a generative AI model (e.g., OpenAI's GPT-3) and sets up a chat session.

[1346] Output: The configured chat session.

[1347] Step 5: Providing a chat interface

[1348] The device provides the user with a chat interface, creating an environment in which the user can interact with the AI.

[1349] Input: The configured chat session.

[1350] Behavior: The device displays and provides the user with a chat interface (text boxes, send buttons, etc.).

[1351] Output: A chat interface available to the user.

[1352] Step 6: Collecting and analyzing chat content

[1353] The server collects and analyzes chat content between the user and the generative AI model in real time.

[1354] Input: The interaction between the user and the generative AI model.

[1355] How it works: The server collects chat content and analyzes it using a natural language processing library (e.g., NLTK). Through the analysis, it extracts information about the user's personality, conversational tendencies, and desired conditions.

[1356] Output: User characteristic information as the analysis result.

[1357] Step 7: Generate a digital avatar

[1358] Based on the analysis results, the server generates a digital avatar that reflects the user's characteristics and wishes.

[1359] Input: User characteristics information.

[1360] How it works: The server generates a digital avatar based on the user's characteristics.

[1361] Output: The generated digital avatar.

[1362] Step 8: Setting up a chat session between avatars

[1363] The server sets up a chat session between the generated digital avatars.

[1364] Input: A generated digital avatar.

[1365] How it works: A server sets up chat sessions between digital avatars and records the conversations.

[1366] Output: Configured avatar chat sessions and recorded dialogue.

[1367] Step 9: Record and analyze chat content

[1368] The server records the content of the conversation between the avatars and analyzes the content.

[1369] Input: Conversation between avatars.

[1370] How it works: The server analyzes the recorded conversations and calculates the relevance using machine learning algorithms.

[1371] Output: The calculated fitness.

[1372] Step 10: Recommending matching results

[1373] The server selects dialogue content with high suitability and recommends it to the user.

[1374] Input: The calculated fitness.

[1375] Operation: The server selects the dialogue content to recommend based on the relevance result and creates a recommendation list.

[1376] Output: Recommended dialogue for the user.

[1377] Step 11: Confirm your match preference

[1378] The terminal displays the recommended dialogue content to the user and provides a means for the user to confirm it.

[1379] Input: Recommended dialogue.

[1380] Operation: The device displays the recommendations to the user and allows the user to select a match.

[1381] Output: Confirmation of user's match preference.

[1382] Step 12: Send your match request and get it done

[1383] If the user selects a match, that information is sent to the server.

[1384] Input: User's match preference selection.

[1385] Operation: The device sends the user's selection status to the server. The server confirms whether both users wish to be matched and establishes the match.

[1386] Output: Matches made and notifications.

[1387] Through the above processing steps, the system can analyze the user's characteristics and preferences in detail and achieve highly accurate matching.

[1388] (Application example 1)

[1389] 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."

[1390] To improve production efficiency in factories, it is important to create optimal team structures based on the characteristics of each robot. However, efficient team building is difficult because there is no established method for evaluating the compatibility and collaborative effectiveness of factory robots. The present invention aims to provide a means to solve this problem.

[1391] 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.

[1392] In this invention, the server includes means for a user to input basic information via a terminal, means for the server to receive the basic information and store it in a database, means for a user to issue a request to start a sample chat with an AI, means for the terminal to send the request to the server, means for the server to generate a chat session with the AI ​​based on the request, means for the terminal to provide a chat interface to the user, means for the server to collect and analyze chat content between the user and the AI, means for the server to generate an avatar that reflects the user's characteristics based on the analysis results, and means for the server to set up a chat session between the avatars and display the chat content. The system includes a means for recording chat content, a means for the server to analyze the recorded chat content and calculate a degree of matching, a means for the server to recommend chat logs with a high degree of matching to the user, a means for the terminal to display the recommended chat content to the user and for confirmation, a means for the user to select a desired match, a means for the terminal to transmit the selected state of the desired match to the server, a means for the server to establish a match when both users desire a match, a means for inputting basic information about the factory robot, a means for generating an avatar based on the characteristics of the robot, and a means for analyzing chat sessions between the avatars and recommending an optimal team composition. This enables evaluation of the compatibility between factory robots and efficient team building.

[1393] "Users" are factory managers and operators who input information and use the system's various functions.

[1394] A "terminal" is a device used by a user to enter information or interact with a system.

[1395] "Basic information" refers to data that includes detailed information about users and robots, such as their characteristics and roles.

[1396] A "server" is a device that receives basic information about users and robots, analyzes and stores the data, and manages and processes the entire system.

[1397] A "database" is a storage device for storing various data such as basic information and analysis results.

[1398] A "request" is a request or command given by a user to a system.

[1399] "Artificial intelligence" refers to computer programs used within the system to generate chat sessions and analyze the characteristics of users and robots.

[1400] A "chat session" is a series of conversations that take place between a user or a robot and an artificial intelligence.

[1401] A "chat interface" is a screen or application that allows users and robots to conduct chat sessions.

[1402] "Chat Content" means the text and messages exchanged during a chat session.

[1403] "Analysis" is the process of analyzing collected chat content and extracting characteristics and trends.

[1404] An "avatar" is a virtual character that reflects the characteristics of a user or a robot.

[1405] "Matching degree" is a score that indicates the compatibility and cooperative effect between avatars.

[1406] "Recommendation" means that the system suggests specific avatars and team compositions to users based on analysis results and compatibility scores.

[1407] "Confirmation" refers to the process by which a user decides whether to accept a recommendation from the system.

[1408] A "factory robot" is an automated mechanical device that performs work on a production line or in a factory.

[1409] A "team composition" is a combination of multiple robot avatars working together to achieve optimal production efficiency.

[1410] This invention is a system that understands the characteristics of robots used in factories and recommends optimal team composition. The system starts operation when a user inputs basic information using a terminal and sends it to a server.

[1411] Enter and save basic information

[1412] The user inputs basic information about the factory robot (model, functions, capabilities, role, etc.) via a terminal. This information is sent to a server and stored in a database. The database is stored in a cloud environment or on a server installed in the factory, where the information is managed and accessed.

[1413] Starting and running a sample chat

[1414] When a user requests a sample chat, the device sends the request to the server. Based on the received request, the server sets up a chat session using a generative AI model. An avatar is generated based on the robot's basic information, and this avatar chats with the AI.

[1415] Collection and analysis of chat content

[1416] The terminal provides the user with a chat interface, and the server collects chat content between the robot and the AI ​​in real time. The collected data is analyzed using a generative AI model to extract information about the robot's characteristics, performance, and collaboration tendencies.

[1417] Avatar generation and matching evaluation

[1418] Based on the analysis results, the server generates avatars that reflect the characteristics of each robot. Chat sessions are set up between the generated avatars, and the chat content is recorded. The server then analyzes the recorded data again to calculate the degree of matching between the avatars, which is used to evaluate their compatibility and collaborative effectiveness.

[1419] Recommendations and Match Confirmation

[1420] The server recommends chat logs of avatars with a high degree of matching to the user. The device displays these recommendations to the user, who then checks the recommendations and selects their desired match. The user's selection is sent to the server, which then works to create the optimal team composition.

[1421] Hardware and Software Use

[1422] The system uses cloud servers, factory servers, and user devices (tablets and PCs) as hardware. Python and OpenAI API (GPT-4 model) are used as software. A relational database management system (RDBMS) is used for database management.

[1423] Specific examples

[1424] For example, suppose factory robot A is an arm robot responsible for welding, and robot B is a transport robot responsible for transporting materials. The user enters basic information about these robots into a terminal and sends it to the server. The server generates avatars using a generative AI model and initiates a chat session between the avatars. Below is a specific example of a prompt sentence.

[1425] Example prompt sentence:

[1426] Start chatting as robot named Robo1, model: arm robot, ability: welding, assembly, role: welder.

[1427] A chat session is held based on this prompt, and the server analyzes the collected data and recommends the optimal team composition to the user, thereby improving the factory's production efficiency.

[1428] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1429] Step 1:

[1430] The user uses a terminal to input basic information about the factory robot. Specifically, they input detailed information such as the robot's model, functions, capabilities, and role, and then press the send button. The input information is sent from the terminal to the server. The server stores the received basic information in a database. This information is used to understand the robot's characteristics.

[1431] Step 2:

[1432] A user issues a request to start a sample chat. Specifically, the request is sent to the server by pressing the Start Sample Chat button on the device. Based on the received request, the server generates an avatar for each robot and sets up a chat session using the generative AI model. At this time, a prompt sentence is generated and input into the AI ​​model.

[1433] Step 3:

[1434] The server calls the generative AI model and initiates a chat session with each robot avatar. The device provides the user with a chat interface, and the chat session proceeds in real time. The server collects and stores the content of the conversation between the robot and the AI ​​in real time. The chat content is dynamically generated by the generative AI based on the input prompt.

[1435] Step 4:

[1436] The server analyzes the chat content collected. Using a generative AI model, it analyzes each robot's characteristics, conversational tendencies, and collaboration potential. Specifically, it extracts the robot's characteristic patterns and working behavior from the chat content and converts them into numerical data and categorical information. The results of this analysis are reflected in each robot's avatar.

[1437] Step 5:

[1438] Based on the analysis results, the server generates an avatar that reflects the characteristics of each robot. This avatar is a virtual character that corresponds to the robot's characteristics and is used to interact with other avatars. The generated avatar is displayed in a way that is easy for users and administrators to understand.

[1439] Step 6:

[1440] The server sets up a chat session between the generated avatars. The avatars converse and record the content. Specifically, a conversation between the avatars is simulated to evaluate the effectiveness of collaboration and compatibility. A scenario is generated based on the prompt text, and the conversation between the avatars progresses.

[1441] Step 7:

[1442] The server analyzes the recorded chat content and calculates the degree of matching between avatars. Specifically, it evaluates the consistency and cooperation of the chat content and outputs a numerical compatibility score. This allows the compatibility of each avatar and their suitability as a team to be evaluated.

[1443] Step 8:

[1444] The server recommends chat logs with a high degree of matching to the user. The device displays the recommended chat content to the user, who then confirms it. Specifically, avatars are recommended based on compatibility scores, and the user can view the recommended content and decide whether or not it is suitable for them.

[1445] Step 9:

[1446] The user checks the recommended chat content and selects whether they wish to be matched. The device sends the user's selection to the server. If both users wish to be matched, the server establishes the match and sends appropriate notifications. This determines the optimal team composition and reflects it on the actual production line.

[1447] 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.

[1448] The system of the present invention combines an emotion engine that recognizes the user's emotions, analyzes the user's characteristics through a chat session between the user and a generating AI (artificial intelligence), and generates an "avatar" based on the user. Furthermore, the system allows the generated avatars to chat with each other, evaluates the degree of matching, and recommends to the user partners with high compatibility. The system of the present invention can be implemented as follows.

[1449] User Registration

[1450] The device provides an interface for users to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand what kind of match the user is looking for.

[1451] Start a sample chat

[1452] The terminal provides the user with a button to start a sample chat. When the user presses this button, the terminal sends a request to start a sample chat to the server. Based on the received request, the server sets up a chat session with the AI ​​and makes the necessary preparations.

[1453] Sample chat

[1454] The server calls the generated AI and starts a chat session between the user and the AI. The device provides the user with a chat interface and helps them answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions. At this time, the emotion engine also extracts the user's emotional information and incorporates it into the analysis.

[1455] Avatar generation

[1456] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and wishes. This avatar converses with other avatars on the user's behalf, improving the efficiency of user matching. Emotional information obtained from the emotion engine is also reflected, improving the avatar's expressiveness and enabling more natural and realistic conversations.

[1457] Avatar-to-avatar chat

[1458] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of the avatar chat and calculates the degree of matching (compatibility score).

[1459] Matching evaluation and recommendation

[1460] The server selects chat contents with a high degree of matching and recommends them to the user. The terminal displays the recommended chat contents to the user and confirms whether the user actually wants to be matched.

[1461] Confirmation and establishment of matching requests

[1462] If a user checks the recommended chat content and wishes to be matched, the device sends that request to the server. The server then checks whether both users wish to be matched. If both agree, the server establishes the match and notifies both users.

[1463] Specific examples

[1464] For example, suppose that user A and user B use this system. User A first enters basic information and sends it to the server. Next, user A participates in a sample chat with the generation AI, and the server analyzes the chat content and extracts user A's characteristics. Based on the results, the server generates an avatar for user A. At this time, the emotion engine also analyzes user A's emotional information and reflects it in the avatar.

[1465] Meanwhile, User B also enters basic information and participates in a sample chat with the generation AI. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[1466] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[1467] This system will make it easier for users with little dating experience to find a suitable partner, which will help combat the declining birthrate and increase the number of marriages.In addition, the use of an emotion engine will make avatar conversations more natural and friendly, improving the user experience.

[1468] The processing flow will be explained below.

[1469] Step 1:

[1470] The user inputs basic information (such as name, age, gender, hobbies, and desired partner conditions) via the terminal, which then sends this information to the server.

[1471] Step 2:

[1472] The server stores the received basic information in a database.

[1473] Step 3:

[1474] The user presses the start button for the sample chat via the terminal, and the terminal sends a request to start the sample chat to the server.

[1475] Step 4:

[1476] The server calls the generation AI, sets up a chat session, and initializes the emotion engine to prepare for analyzing the chat content.

[1477] Step 5:

[1478] The device provides the user with a chat interface, where the user initiates a dialogue with the generated AI and answers questions posed by the generated AI.

[1479] Step 6:

[1480] The server collects chat content in real time and extracts the user's emotional information using an emotion engine. The analysis results include information on the user's personality, conversational tendencies, desired conditions, and other emotional information.

[1481] Step 7:

[1482] Based on the information extracted by the server, an avatar is generated that reflects the user's characteristics and also includes emotional information.

[1483] Step 8:

[1484] The server sets up chat sessions with other users' avatars, and the avatars converse with each other. The server also records the emotional information that the avatars acquire through the conversation.

[1485] Step 9:

[1486] The server records the chat content and emotional information between avatars, and analyzes the degree of matching (compatibility score) based on these records.

[1487] Step 10:

[1488] The server selects chat content and emotional information with a high degree of matching and creates it as a recommended chat.

[1489] Step 11:

[1490] The device displays the recommended chat content to the user, who then checks the chat content and considers the emotional information.

[1491] Step 12:

[1492] The user selects their desired match, and the device sends that preference to the server.

[1493] Step 13:

[1494] The server checks whether both users want to be matched, and if both agree, the server makes the match happen.

[1495] Step 14:

[1496] The server will notify both users that a match has been made.

[1497] Example 2

[1498] 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."

[1499] Conventional matching systems are inefficient when handling a large number of user information and have difficulty properly reflecting user characteristics and emotional information. Furthermore, the accuracy of matching between users is low, making it difficult to find a compatible partner. Furthermore, if a user has little interaction experience, they are unable to communicate appropriately, resulting in low satisfaction. The present invention aims to solve these problems through highly accurate analysis using an emotion engine and simulation using avatars.

[1500] 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.

[1501] In this invention, the server includes a means for generating a chat session with the generative AI model, a means for collecting and analyzing chat content between the user and the generative AI model, and a means for using an emotion engine to analyze emotional information and reflect it in the avatar. This allows for highly accurate analysis of user characteristics and emotional information, thereby improving the accuracy of matching between users.

[1502] A "generative AI model" is a type of artificial intelligence that uses natural language processing and machine learning techniques to enable dialogue with users.

[1503] "Basic information" refers to personal information such as name, age, sex, hobbies, and desired partner conditions that a user enters into the system.

[1504] A "chat session" refers to a series of interactions between a user and a generative AI model, or between avatars.

[1505] "Chat interface" refers to the screen and input devices that allow users to interact with generated AI models and other avatars.

[1506] An "emotion engine" refers to software or algorithms that analyze and extract emotional information from user dialogue.

[1507] An "avatar" is a virtual conversational agent that is generated to reflect the user's characteristics and emotional information.

[1508] The "matching degree" is an index that indicates the compatibility or degree of compatibility between users, calculated by analyzing the content of chats between avatars.

[1509] "Recommendation" refers to the act of the server presenting chat logs and avatars with a high degree of matching to the user.

[1510] "Talk tendencies" is information about what topics and expressions a user likes to use in conversations.

[1511] "Desired conditions" refer to the attributes and conditions that a user desires in a partner with whom they wish to be matched.

[1512] "Analysis" refers to the process of analyzing data based on chat content and emotional information collected by the server and extracting user characteristics and emotions.

[1513] The present invention provides a system for improving the efficiency of matching between users by utilizing avatars that reflect the user's emotional information. A method for specifically implementing this system will be described below.

[1514] First, the device provides an interface for the user to enter basic information (such as name, age, gender, hobbies, and desired partner conditions). When the user enters this information and presses the send button, the device sends this information to the server. The server stores the received information in a database and uses it for subsequent processing. This information is used to understand the type of match the user is looking for.

[1515] Next, the device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. Based on the request, the server sets up a chat session with a generative AI model (e.g., GPT-4) and makes the necessary preparations.

[1516] The server calls the generative AI model and initiates a chat session between the user and the AI. The device provides the user with a chat interface and helps them answer questions posed by the AI. The server collects the entire content of this chat session in real time and analyzes information such as the user's personality, conversational tendencies, and desired conditions. At this time, the server also extracts the user's emotional information using an emotion engine and incorporates it into the analysis.

[1517] A specific example of a question would be for the generative AI model to ask, "Hello, what happened today?" and for the user to respond, "I read a new book today."

[1518] Once the analysis is complete, the server generates an avatar that reflects the user's characteristics and wishes based on the analysis results. This avatar converses with other avatars on the user's behalf, improving the efficiency of user matching. Emotional information obtained from the emotion engine is also reflected, improving the avatar's expressiveness and enabling more natural and realistic conversations.

[1519] The server sets up a chat session between the generated avatars. The avatars converse with each other and record the content of the conversation. The server analyzes the content of these avatar chats and calculates the degree of matching (compatibility score). The server selects chat content with a high degree of matching and recommends it to the user. The device displays the recommended chat content to the user and confirms whether the user actually wishes to be matched.

[1520] Specifically, User A enters basic information and sends it to the server. Next, User A participates in a sample chat with the generative AI model, and the server analyzes the chat content to extract User A's characteristics. Based on the results, the server generates an avatar for User A. Meanwhile, User B also enters basic information and participates in a sample chat with the generative AI model. The server also generates an avatar for User B. The server then chats between User A's avatar and User B's avatar, recording and analyzing the chat content. Based on the analysis results, the server calculates the degree of match, and if the degree of match between the two is high, it notifies User A and User B.

[1521] User A and User B each check the recommended chat content, and when they each choose to match, the server will establish a match and notify both parties. In this way, users can match more effectively and efficiently.

[1522] An example of a prompt is as follows:

[1523] When inputting the user's basic information: The terminal provides an interface for inputting the user's basic information.

[1524] At the start of a sample chat: When the user presses the Start Sample Chat button, the terminal sends a request to the server.

[1525] When generating an avatar: The server generates an avatar based on the analysis results, and also reflects emotional information.

[1526] Through the above steps, the system of the present invention can achieve highly accurate matching by using an avatar that reflects the user's characteristics and emotional information.

[1527] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1528] Step 1:

[1529] User registration interface provided

[1530] The terminal provides an interface for the user to input basic information (such as name, age, gender, hobbies, and desired partner conditions). The user's input becomes input to the terminal, and the terminal sends this information to the server. Specifically, the terminal displays a form, and when the user enters information and presses the send button, the data is sent to the server. The server saves this information in a database. The input is the user's basic information, and the output is the user information saved in the database.

[1531] Step 2:

[1532] Sample Chat Start Request

[1533] The device provides the user with a button to start a sample chat. When the user presses this button, the device sends a request to start a sample chat to the server. The server receives the request and prepares to set up a chat session with the generative AI model. The input is the user's request to start a sample chat, and the output is a state in which preparations for a chat session with the generative AI model are complete.

[1534] Step 3:

[1535] Sample chat

[1536] The server calls the generative AI model and starts a chat session between the user and the AI. The device provides the user with a chat interface and supports the user in answering questions from the AI. Specifically, the generative AI model asks, "Hello, what happened today?" and the user replies, "I read a new book today." The server collects and analyzes the entire content of this chat session in real time. The input is the chat content between the user and the AI, and the output is analyzed user characteristic information.

[1537] Step 4:

[1538] Emotional information analysis

[1539] The server uses an emotion engine to extract the user's emotional information during the chat session and incorporates it into the analysis data. Specifically, it identifies emotions such as positive, negative, and neutral from the user's comments and records them as numerical values. The input is the chat content, and the output is the analyzed emotional information.

[1540] Step 5:

[1541] Avatar generation

[1542] Based on the analysis results, the server generates an avatar that reflects the user's characteristics and wishes. Emotional information obtained from the emotion engine is also reflected in the avatar. Specifically, the server generates an avatar with a specific profile based on data such as "User ID: 001, Personality: Curious, Hobby: Reading, Emotional Information: Happy." The input is the analysis results and emotional information, and the output is the generated avatar.

[1543] Step 6:

[1544] Avatar-to-avatar chat

[1545] The server sets up a chat session between the generated avatars. The avatars begin a conversation, and the content of that conversation is recorded. As a specific example of a conversation, avatar A might ask, "What kind of books do you like?" and avatar B might reply, "I like mystery novels." The input is the generated avatar, and the output is the recorded chat content.

[1546] Step 7:

[1547] Matching evaluation and recommendation

[1548] The server analyzes the recorded chat content and calculates the degree of matching. It selects chat content with a high compatibility score and recommends it to the user. Specifically, the server analyzes the chat content, calculates a score, and creates a ranking. The input is the chat content, and the output is the recommended chat content and its compatibility score.

[1549] Step 8:

[1550] View and review recommendations

[1551] The terminal displays the recommended chat content to the user and confirms whether the user actually wants to be matched. The input is the recommended chat content, and the output is the user's choice of desired match.

[1552] Step 9:

[1553] Confirmation and establishment of matching requests

[1554] The server checks whether both users wish to be matched. If both agree, the match is established and a notification is sent to both users. Specifically, the server checks the wishes of "User ID: 001" and "User ID: 002" and sends a notification if a match is established. The input is the user's match request, and the output is a notification that a match has been established.

[1555] (Application example 2)

[1556] 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."

[1557] Conventional food delivery systems have the problem of not being able to recommend dishes that match a user's preferences and mood. Users may also have difficulty choosing the best dish based on their emotional state. Furthermore, simple recommendation systems often do not improve the user experience, resulting in a decrease in user satisfaction.

[1558] The identification process by the identification 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 means for analyzing a user's emotions in real time using an emotion engine and providing recommendations based on the user's preferences and mood, means for recommending restaurants and dishes for food delivery to the user, and means for analyzing chat content using artificial intelligence and extracting information such as the user's conversation tendencies, desired conditions, personality, and emotional information. This makes it possible to recommend optimal dishes based on the user's emotions and preferences, enabling a food delivery service with high user satisfaction.

[1559] "User" refers to an individual who uses the Service.

[1560] A "terminal" is an electronic device that allows a user to input or receive information, and includes smartphones, computers, and the like.

[1561] "Basic information" refers to personal information about the user, such as name, age, gender, preferences, and allergies.

[1562] "Server" refers to a computer system that processes and stores information received from users and provides necessary functionality.

[1563] A "database" refers to a system for storing various information in an organized manner and making it accessible.

[1564] A "request" refers to a request by a user to initiate a particular action.

[1565] "Artificial intelligence" refers to systems or programs designed to mimic human intelligence, and in this case refers to generative AI models.

[1566] An "emotion engine" refers to a system or program for analyzing a user's emotions.

[1567] "Chat session" refers to a period of interaction or activity between a user and an artificial intelligence.

[1568] "Chat interface" refers to the screen and input means that allow users to interact with artificial intelligence.

[1569] An "avatar" refers to a virtual character created to reflect a user's characteristics and wishes.

[1570] "Matching degree" refers to a compatibility score calculated by analyzing the content of the conversation between avatars.

[1571] "Recommendation" refers to the act of a system suggesting specific information or options to a user.

[1572] "Food delivery" refers to a service that delivers food ordered by a user to a specified location.

[1573] The system of this invention combines an emotion engine that recognizes the user's emotions with a generative AI to recommend food delivery options based on the user's preferences and mood. The user inputs basic information using a terminal, and the server processes and analyzes that information.

[1574] Hardware and software used

[1575] Hardware:

[1576] Smartphone

[1577] server

[1578] software:

[1579] Emotion engine libraries (e.g., Affective Computing)

[1580] Generative AI models (e.g., GPT-4)

[1581] Database management system (e.g. MySQL)

[1582] Front-end frameworks (e.g. React Native)

[1583] System processing steps

[1584] User Registration:

[1585] Users enter basic information (such as name, age, gender, favorite foods, allergies, and desired food conditions) via a smartphone app. This basic information is sent to the server via the device and stored in a database.

[1586] Start a sample chat:

[1587] The user initiates a chat session with the emotion engine and generative AI by pressing the chat button on the device, which sends a request to the server and starts the chat session.

[1588] Sample chat execution:

[1589] The server uses a generative AI model to communicate with the user, and an emotion engine analyzes emotions in real time from the content of the user's conversation and uses this information to determine the user's preferences and mood.

[1590] Avatar Creation:

[1591] The server generates an avatar that reflects the user's characteristics and wishes based on the analysis results of the emotion engine. The generated avatar acts as a proxy character for the user and interacts with other users' avatars.

[1592] Restaurant and food recommendations:

[1593] The server analyzes the interactions between the generated avatars and recommends restaurants and dishes that go well together. It also lists food delivery options and provides optimal recommendations to users.

[1594] User presentation and confirmation:

[1595] The recommended dishes and restaurants are displayed on the device screen, and the user can review the recommended options and decide whether to actually order.

[1596] Order confirmation:

[1597] Once the order is confirmed, the server sends the order to the corresponding restaurant, and the order history is saved in the user's database.

[1598] Processing example

[1599] For example, a user logs in to the app and taps the "Recommend me today's specials!" button. At that time, the app starts an AI chat and asks, "How are you feeling today?" If the user replies, "I feel like eating something a little spicy today," the emotion engine analyzes the user's emotions and preferences and generates a list of spicy dishes. Next, the AI ​​chat suggests, "How about the Shin Ramyun from this restaurant?" If the user accepts the suggestion and confirms the order, the system sends the order to the restaurant.

[1600] Prompt Sentence Examples

[1601] "Would you like me to help you find a dish that matches your mood today? Tell me how you're feeling right now."

[1602] Using this system, recommended dishes and restaurants can be efficiently recommended based on the user's emotions and preferences, thereby improving user satisfaction.

[1603] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1604] Step 1:

[1605] The user enters basic information (such as name, age, gender, favorite foods, allergies, and desired food conditions) via a smartphone app. The entered basic information is sent to the server through the smartphone's input interface. The server stores the received information in a database. In this process, the user's input data is sent to the server and inserted into the user table in the database.

[1606] Step 2:

[1607] The user presses the "Start Chat" button on the smartphone app to start a chat session between the emotion engine and the generative AI. This causes the device to send a chat session request to the server. The server receives the request and calls the generative AI model to generate the chat session. In this process, the server creates a chat session object using the generative AI model and imports the user's basic information.

[1608] Step 3:

[1609] The server uses the generative AI model to provide a chat interface to users. Users answer questions posed by the AI ​​through the chat screen on their smartphones. The server collects chat content in real time and performs emotion analysis using an emotion engine. In this process, the user's text input is sent to the server and analyzed by the emotion engine.

[1610] Step 4:

[1611] The server generates an avatar that reflects the user's characteristics and wishes based on the analysis results of the emotion engine. This avatar is required to act as the user's representative character and to interact with other users' avatars. The generated avatar information is saved in a database. In this process, avatar data is created by combining emotion data and basic information.

[1612] Step 5:

[1613] The server sets up chat sessions between the generated avatars. The content of the avatar chats is recorded and analyzed by the server to calculate the degree of matching. In this process, the avatar conversation logs are analyzed and a compatibility score is calculated using a matching algorithm.

[1614] Step 6:

[1615] The server recommends chat logs with a high degree of matching to the user. The recommended dishes and restaurants are displayed on the smartphone screen. The user checks the options and decides whether to actually order. In this process, the recommendations are displayed on the user interface.

[1616] Step 7:

[1617] When a user confirms an order for a recommended dish or restaurant, the order confirmation information is sent from the smartphone to the server. The server then sends the order to the restaurant based on that information and saves the order history in the user's database. In this process, the order data is sent to the restaurant's system and recorded in the database.

[1618] This trend will enable food delivery recommendations based on users' emotions and preferences, making it possible to provide a service that highly satisfies users.

[1619] 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.

[1620] 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.

[1621] 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.

[1622] 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.

[1623] FIG. 9 is a diagram illustrating 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 actions 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.

[1624] 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.

[1625] 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).

[1626] 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.

[1627] 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."

[1628] 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.

[1629] 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).

[1630] 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.

[1631] 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.

[1632] 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.

[1633] 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.

[1634] 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.

[1635] 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.

[1636] 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.

[1637] 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.

[1638] 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.

[1639] 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.

[1640] The following is further disclosed regarding the above embodiment.

[1641] (Claim 1)

[1642] A means for a user to input basic information via a terminal;

[1643] A server receives the basic information and stores it in a database;

[1644] a means for a user to submit a request to initiate a sample chat with the artificial intelligence;

[1645] means for the terminal to send the request to a server;

[1646] A means for the server to generate a chat session with an artificial intelligence based on the request;

[1647] means for the terminal to provide a chat interface to the user;

[1648] A means for the server to collect and analyze chat contents between the user and the AI;

[1649] A means for the server to generate an avatar that reflects the user's characteristics based on the analysis results;

[1650] A server sets up chat sessions between avatars and records the content of the chats;

[1651] A server analyzes the recorded chat content and calculates a matching degree;

[1652] A means for the server to recommend chat logs with high matching degrees to the user;

[1653] A means for displaying the recommended chat content to the user and for the user to confirm;

[1654] A means for a user to select a match preference;

[1655] A means for the terminal to transmit a selection state of a match-making preference to a server;

[1656] The server is the means by which a match is made if both users wish to be matched.

[1657] A system including:

[1658] (Claim 2)

[1659] The system according to claim 1, wherein the server includes means for analyzing chat content using artificial intelligence and extracting information such as the user's talking tendencies, desired conditions, and personality.

[1660] (Claim 3)

[1661] 2. The system according to claim 1, wherein the server includes means for sending a notification of a match to both users when a match is made.

[1662] "Example 1"

[1663] (Claim 1)

[1664] A means for a user to input basic information via a terminal;

[1665] A server receives the basic information and stores it in a storage device;

[1666] a means for a user to submit a request to initiate a sample chat with the artificial intelligence;

[1667] means for the terminal to send the request to a server;

[1668] means for the server to generate an interactive session with an artificial intelligence based on said request;

[1669] means by which the terminal provides a dialogue interface to a user;

[1670] A means for the server to collect and analyze the content of the dialogue between the user and the AI;

[1671] A means for the server to generate a digital avatar that reflects the user's characteristics based on the analysis results;

[1672] a means for the server to set up an interaction session between the digital avatars and record the content of the interaction;

[1673] a means for the server to analyze the recorded dialogue content and calculate the degree of conformance;

[1674] A means for the server to recommend dialogue logs with high relevance to the user;

[1675] a means for displaying the recommended dialogue content to the user and allowing the user to confirm the dialogue content;

[1676] a means for a user to select a desired match;

[1677] A means for the terminal to transmit a selection state of a desired match to the server;

[1678] The server is the means by which a match is made when both users desire a match.

[1679] A system including:

[1680] (Claim 2)

[1681] The system of claim 1, wherein the server analyzes the content of the conversation using artificial intelligence, extracts information such as the user's speaking habits, desired conditions, and personality, and generates a digital avatar based on this information.

[1682] (Claim 3)

[1683] 2. The system of claim 1, wherein the server sends a notification of a match to both users if a match is found.

[1684] "Application Example 1"

[1685] (Claim 1)

[1686] A means for a user to input basic information via a terminal;

[1687] A server receives the basic information and stores it in a database;

[1688] a means for a user to submit a request to initiate a sample chat with the artificial intelligence;

[1689] means for the terminal to send the request to a server;

[1690] A means for the server to generate a chat session with an artificial intelligence based on the request;

[1691] means for the terminal to provide a chat interface to the user;

[1692] A means for the server to collect and analyze chat contents between the user and the AI;

[1693] A means for the server to generate an avatar that reflects the user's characteristics based on the analysis results;

[1694] A server sets up chat sessions between avatars and records the content of the chats;

[1695] A server analyzes the recorded chat content and calculates a matching degree;

[1696] A means for the server to recommend chat logs with high matching degrees to the user;

[1697] A means for displaying the recommended chat content to the user and for the user to confirm;

[1698] A means for a user to select a match preference;

[1699] A means for the terminal to transmit a selection state of a match-making preference to a server;

[1700] A means for the server to establish a match when both users desire a match;

[1701] A means of inputting basic information about the factory robot;

[1702] means for generating an avatar based on the characteristics of the robot;

[1703] means for analyzing chat sessions between the avatars and recommending an optimal team composition;

[1704] A system including:

[1705] (Claim 2)

[1706] The system according to claim 1, wherein the server includes means for analyzing chat content using artificial intelligence and extracting information such as the user's talking tendencies, desired conditions, and personality.

[1707] (Claim 3)

[1708] 2. The system according to claim 1, wherein the server includes means for sending a notification of a match to both users when a match is made.

[1709] "Example 2: Combining Emotion Engines"

[1710] (Claim 1)

[1711] A means for a user to input basic information via a terminal;

[1712] A server receives the basic information and stores it in a database;

[1713] a means for a user to submit a request to initiate a sample chat with the artificial intelligence;

[1714] means for the terminal to send the request to a server;

[1715] A means for the server to generate a chat session with the generative AI model based on the request;

[1716] means for the terminal to provide a chat interface to the user;

[1717] A means for the server to collect and analyze chat content between the user and the generated AI model;

[1718] A means for the server to generate an avatar that reflects the user's characteristics based on the analysis results;

[1719] A server for setting up chat sessions between the generated avatars and recording the content of the chats;

[1720] A server analyzes the recorded chat content and calculates a matching degree;

[1721] A means for the server to recommend chat logs with high matching degrees to the user;

[1722] A means for displaying the recommended chat content to the user and for the user to confirm;

[1723] A means for a user to select a match preference;

[1724] A means for the terminal to transmit a selection state of a match-making preference to a server;

[1725] A means for the server to establish a match when both users desire a match;

[1726] A means for analyzing emotional information and using an emotion engine to reflect it in the avatar;

[1727] A system including:

[1728] (Claim 2)

[1729] The system according to claim 1, further comprising a means for the server to analyze chat content using the generated AI model and extract information such as the user's talk tendencies, desired conditions, personality, and emotional information.

[1730] (Claim 3)

[1731] 2. The system according to claim 1, wherein the server includes means for sending a notification of a match to both users when a match is made.

[1732] "Application example 2 when combining emotion engines"

[1733] (Claim 1)

[1734] A means for a user to input basic information via a terminal;

[1735] A server receives the basic info...

Claims

1. A means for a user to input basic information via a terminal; A server receives the basic information and stores it in a database; a means for a user to submit a request to initiate a sample chat with the artificial intelligence; means for the terminal to send the request to a server; A means for the server to generate a chat session with an artificial intelligence based on the request; means for the terminal to provide a chat interface to the user; A means for the server to collect and analyze chat contents between the user and the AI; A means for the server to generate an avatar that reflects the user's characteristics based on the analysis results; A server sets up chat sessions between avatars and records the content of the chats; A server analyzes the recorded chat content and calculates a matching degree; A means for the server to recommend chat logs with a high degree of matching to the user; A means for displaying the recommended chat content to the user and for the user to confirm; A means for a user to select a match preference; A means for the terminal to transmit a selection state of a match-making preference to a server; The server is the means by which a match is made if both users wish to be matched. A system including:

2. 2. The system according to claim 1, wherein the server includes means for analyzing chat content using artificial intelligence and extracting information such as the user's talking tendencies, desired conditions, and personality.

3. 2. The system according to claim 1, wherein the server includes means for sending a notification of a match to both users when a match is made.

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