system

Abstract

Provide a system. A means for a user to answer a questionnaire about hobbies and preferences; A means for the server to receive and analyze user input information; A means for generating an interactive AI partner that matches the user's preferences using a generative AI model; means for interacting with a user using the generated artificial intelligence partner; a means for storing a user's conversation history in a database; A system including:

Description

[Technical Field]

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

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

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

[0004] In modern society, the number of people suffering from loneliness and mental anxiety is increasing. In particular, the increase in social withdrawal and suicides is a serious social problem, and effective measures to address this issue are needed. However, at present, there is insufficient provision of appropriate support to alleviate the loneliness and anxiety caused by the lack of trustworthy friends or partners. Furthermore, existing methods are one-way, making it difficult to provide interactions that match the user's interests and preferences. Therefore, new technological means are needed to solve this problem. [Means for solving the problem]

[0005] The present invention provides a means for users to answer a questionnaire about their hobbies and preferences, thereby collecting information about the user's interests and preferences. A server then provides means for receiving and analyzing this information, thereby creating a profile based on the user's preferences. A generative AI model is then provided to generate a conversational AI partner that matches the user's preferences. This AI partner has means for engaging in a dialogue with the user and further has means for storing the user's conversation history in a database. This can improve the quality of the dialogue and reduce the user's sense of loneliness. Additionally, the conversational AI partner has means for analyzing the content of the user's conversation and making suggestions based on the user's preferences, as well as means for suggesting outgoing events and activities, thereby providing a system that promotes social connections and provides emotional support to the user.

[0006] A "user terminal" is a device through which a user operates an interface and inputs and receives information.

[0007] A "server" is a central system that receives user-submitted information, analyzes it, and processes it using generative artificial intelligence models.

[0008] A "database" is a place where data such as user profile information and conversation history is stored.

[0009] A "generative artificial intelligence model" is an artificial intelligence technology for generating the optimal interactive artificial intelligence partner based on user input information.

[0010] A "conversational artificial intelligence partner" is an artificial intelligence system designed to engage in natural conversation with a user and provide emotional support.

[0011] A "questionnaire" is a question-based input method for collecting information about a user's hobbies, preferences, and personality.

[0012] A "profile" is individual characteristic data created based on a user's hobbies, preferences, and personality.

[0013] "Conversation History" is a record of all conversations that take place between a user and their conversational AI partner.

[0014] "Suggestions" are recommendations or activities made by a conversational AI partner based on a user's preferences and behavioral patterns.

[0015] "Extroverted events and activities" are gatherings or activities that users can participate in physically or online to foster social connections. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] This invention is a system that provides a conversational AI partner (AI Friends, AI Girlfriend / Boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, and a database.

[0038] System Configuration Overview

[0039] 1. User Device:

[0040] It is a device on which users install applications and enter basic information and questionnaires.

[0041] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[0042] 2. Server:

[0043] This is a system that receives and analyzes survey results and conversation data sent by users.

[0044] It uses a generative artificial intelligence model to generate the best AI partner based on the user's profile.

[0045] Based on the content of the conversation, the AI ​​partner generates a response and sends it to the user.

[0046] 3. Database:

[0047] Stores user basic information, survey results, conversation history, etc.

[0048] Detailed program processing

[0049] User registration and survey entry

[0050] Users install and launch the app, then enter basic information such as their name, age, and hobbies, and answer a questionnaire about their personality and interests.

[0051] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[0052] The terminal transmits the input information and the survey results to the server.

[0053] AI Partner Generation

[0054] The server analyzes the received user information and creates a profile based on the user's interests and preferences, then uses a generative AI model to generate an AI partner that best matches the user's profile.

[0055] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[0056] Initiating and sustaining dialogue

[0057] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[0058] The terminal sends this question to the server.

[0059] The server analyzes the question and generates an appropriate response, such as "There's a movie that's been getting a lot of buzz lately. Why don't you check it out?"

[0060] The terminal displays the response from the server to the user.

[0061] Conversation history storage and analysis

[0062] The server stores the conversation history between the user and the AI ​​partner in a database, which can be used to improve the quality of future conversations.

[0063] Example: Based on the conversation history between the user and their AI partner, the next interaction will recommend movies that reflect the user's preferences.

[0064] Promoting social connections

[0065] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a film festival this weekend, why don't you join us?"

[0066] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[0067] Specific examples

[0068] 1. Initial settings and questionnaire entry:

[0069] The user launches the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[0070] 2. AI Partner Generation:

[0071] The server creates a profile for Ichiro Tanaka and generates a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sends an initial message saying, "Hello, Tanaka! There's a good suspense movie out recently."

[0072] 3. Continuing the dialogue:

[0073] Ichiro Tanaka asks, "What recent suspense movie do you recommend?" The server recommends "Inception," and displays it to Ichiro Tanaka.

[0074] 4. Social suggestions:

[0075] The server notifies him, "A suspense film festival is being held at a nearby movie theater. Why don't you come and participate?" Ichiro Tanaka checks the details and decides to participate.

[0076] In this way, the present invention is a system that not only provides psychological support to users but also contributes to promoting social activities.

[0077] The processing flow will be explained below.

[0078] Step 1:

[0079] A user installs the app and enters basic information, such as name "Yamada Taro," age "25," and hobby "reading."

[0080] Step 2:

[0081] The device temporarily stores the user's input information, then displays a questionnaire about the user's hobbies, preferences, and personality, prompting the user to respond.

[0082] Step 3:

[0083] A user answers a survey. For example, the user answers "science fiction" to the question "What is your favorite movie genre?"

[0084] Step 4:

[0085] The terminal collects the user's survey responses and sends them to the server.

[0086] Step 5:

[0087] The server analyzes the received user information and generates a profile. For example, the server might record in the profile that the user "likes science fiction."

[0088] Step 6:

[0089] The server uses the generative AI model to generate a conversational AI partner based on the profile, in this case an AI partner with an interest in science fiction.

[0090] Step 7:

[0091] The server stores the initial profile of the generated AI partner in a database.

[0092] Step 8:

[0093] The server generates an initial message for the conversational AI partner and sends it to the user: "Hello, Yamada-san. I see you like science fiction!"

[0094] Step 9:

[0095] The terminal displays a welcome message from the server to the user.

[0096] Step 10:

[0097] The user initiates a dialogue by typing a question: "What science fiction movie should I watch today?"

[0098] Step 11:

[0099] The terminal sends the user's question to the server.

[0100] Step 12:

[0101] The server analyzes the received question and uses a generative AI model to generate an appropriate response, such as "I recommend the popular movie 'Interstellar'."

[0102] Step 13:

[0103] The server sends the generated response to the terminal.

[0104] Step 14:

[0105] The terminal displays the response message from the server to the user.

[0106] Step 15:

[0107] If the user interaction continues, the user enters more messages which are sent to the server, and the process repeats.

[0108] Step 16:

[0109] The server stores the conversation history with the user in a database to help with future interactions.

[0110] Step 17:

[0111] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a science fiction film festival in your neighborhood. Why don't you go?"

[0112] Step 18:

[0113] The terminal displays the suggestions from the server to the user, allowing the user to check the detailed information.

[0114] In this way, the system of the present invention repeatedly interacts with the user and analyzes data, contributing to providing psychological support to the user and promoting social activities.

[0115] Example 1

[0116] 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."

[0117] Conventional conversational AI systems are limited in the dialogue and suggestions they provide based on the user's personal hobbies and preferences, and are unable to fully alleviate the user's feelings of loneliness and stress. Furthermore, they lack a mechanism for utilizing the user's dialogue history to improve the quality of future conversations. Furthermore, they lack the functionality to encourage users' social activities by suggesting social activities and events based on the user's preferences.

[0118] 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.

[0119] In this invention, the server includes a means for analyzing the user's question, generating a response, and sending it to the terminal, a means for using the conversation history as data for improving the quality of future conversations, and a means for generating an interactive AI partner using a generative AI model based on the user profile. This enables dialogue and suggestions based on the user's individual hobbies and preferences, improving the quality of conversations and promoting social activities.

[0120] "User" refers to an individual who uses the system to enter a questionnaire about basic information and hobbies and preferences and engages in conversation with an interactive AI partner.

[0121] "Terminal" refers to the device on which a user enters basic information and survey results and sends them to the server, as well as the device on which a user can converse with an interactive AI partner.

[0122] "Server" refers to a computer system that receives and analyzes user information, generates a conversational artificial intelligence partner using a generative AI model, analyzes the content of the dialogue with the user to generate a response, and stores the conversation history in a database.

[0123] "Generative AI Model" means an artificial intelligence model used to generate a conversational artificial intelligence partner that is tailored to a user's preferences and interests based on the user's profile.

[0124] "Prompt" refers to the text of an instruction or question input to a generative AI model.

[0125] "Conversational AI partner" refers to an AI agent generated by a generative AI model that engages in text or voice dialogue with a user.

[0126] "Conversation history" refers to a record of all conversations between a user and their conversational AI partner.

[0127] "Database" refers to a data storage system that stores basic information, survey results, and conversation history of users, and retrieves or analyzes information as needed.

[0128] "Extroverted events and activities" refer to public events and group activities that users can participate in that are proposed to promote social activity for users.

[0129] A "user profile" refers to individual characteristic information generated based on information such as a user's hobbies, preferences, personality, and survey results.

[0130] This invention is a system that provides a conversational AI partner (AI Friends, AI Girlfriend / Boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, and a database.

[0131] System Configuration Overview

[0132] 1. User Device:

[0133] It is a device on which users install applications and enter basic information and questionnaires.

[0134] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[0135] Specific examples include smartphones and tablets.

[0136] 2. Server:

[0137] This is a system that receives and analyzes survey results and conversation data sent by users.

[0138] It uses a generative artificial intelligence model (e.g., GPT-3®) to generate the optimal AI partner based on the user's profile.

[0139] Based on the content of the conversation, the AI ​​partner generates a response and sends it to the user.

[0140] 3. Database:

[0141] Stores user basic information, survey results, conversation history, etc.

[0142] Use a database management system (e.g., MySQL (registered trademark) or PostgreSQL).

[0143] Specific processing of the program

[0144] User registration and survey entry

[0145] Users install and launch the app, then enter basic information such as their name, age, and hobbies, and answer a questionnaire about their personality and interests.

[0146] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[0147] The terminal transmits the input information and the survey results to the server.

[0148] AI Partner Generation

[0149] The server analyzes the received user information and creates a profile based on the user's interests and preferences, then uses a generative AI model to generate an AI partner that best matches the user's profile.

[0150] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[0151] Example prompt: "The user likes watching movies. What recent movies do you recommend?"

[0152] Initiating and sustaining dialogue

[0153] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[0154] The terminal sends this question to the server.

[0155] The server analyzes the question and generates an appropriate response, such as "There's a movie that's been getting a lot of buzz lately. Why don't you check it out?"

[0156] The terminal displays the response from the server to the user.

[0157] Conversation history storage and analysis

[0158] The server stores the conversation history between the user and the AI ​​partner in a database, which can be used to improve the quality of future conversations.

[0159] Example: Based on the conversation history between the user and their AI partner, the next interaction will recommend movies that reflect the user's preferences.

[0160] Promoting social connections

[0161] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a film festival this weekend, why don't you join us?"

[0162] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[0163] Specific examples

[0164] 1. Initial settings and questionnaire entry:

[0165] The user starts the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[0166] 2. AI Partner Generation:

[0167] The server creates a profile for Ichiro Tanaka and generates a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sends an initial message saying, "Hello, Tanaka! There are some good suspense movies out there these days."

[0168] 3. Continuing the dialogue:

[0169] Ichiro Tanaka asks, "What recent suspense movie would you recommend?" The server recommends "Inception is interesting," and displays it to Ichiro Tanaka.

[0170] 4. Social suggestions:

[0171] The server sends a message saying, "A suspense film festival is being held at a nearby movie theater. Why don't you come and participate?" Ichiro Tanaka checks the details and decides to participate.

[0172] In this way, the present invention is a system that not only provides psychological support to users but also contributes to promoting social activities, which is expected to improve the quality of life of users.

[0173] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0174] Step 1:

[0175] The user installs and launches the app. This displays the app's initial setup screen. The user enters basic information such as name, age, and hobbies, and answers a questionnaire about their personality and interests. Specifically, the user fills in the input form with information such as "Name: Ichiro Tanaka," "Age: 30," and "Hobbies: Watching movies."

[0176] Input: Name, age, hobbies, and survey responses about personality and interests.

[0177] Output: User basic information and survey results.

[0178] Step 2:

[0179] The device compiles the entered basic information and survey results and sends them to the server. Specifically, when the user presses the input completion button, the device compiles the information and sends it to the server via an HTTP POST request.

[0180] Input: User basic information and survey results.

[0181] Output: The user information sent to the server.

[0182] Step 3:

[0183] The server analyzes the received user information and generates a user profile. Specifically, the server analyzes the information temporarily stored in the database and generates a profile such as "I like watching movies," "30-year-old male," and "suspense movie lover."

[0184] Input: The user information sent to the server.

[0185] Output: The generated user profile.

[0186] Step 4:

[0187] The server uses a generative AI model to generate a conversational AI partner based on the user profile. Specifically, the server invokes a generative AI model (e.g., GPT-3), inputs the profile as a prompt, and generates the AI ​​partner's personality and initial message.

[0188] Input: User profile, prompt statement.

[0189] Output: The generated conversational artificial intelligence partner.

[0190] Step 5:

[0191] The user initiates a conversation with the AI ​​partner through the application, for example by typing a question into a text box, such as "What movie should I watch today?", and then pressing the send button.

[0192] Input: The user's question.

[0193] Output: The question asked by the user.

[0194] Step 6:

[0195] The device sends the user's question to the server by collecting the contents of the text box and sending it to the server via an HTTP POST request.

[0196] Input: The user's question.

[0197] Output: The question sent to the server.

[0198] Step 7:

[0199] The server analyzes the question and generates an appropriate response. Specifically, the server analyzes the question using natural language processing and uses a generative AI model to generate a response such as "Inception is interesting."

[0200] Input: The user's question.

[0201] Output: The generated response.

[0202] Step 8:

[0203] The terminal displays the response from the server to the user. Specifically, the response text received from the server is displayed on the message screen.

[0204] Input: The generated response.

[0205] Output: The response displayed to the user.

[0206] Step 9:

[0207] The server stores the conversation history between the user and the AI ​​partner in a database. Specifically, the server stores the contents of each message sent and received in the conversation in the database.

[0208] Input: The conversation between the user and their AI partner.

[0209] Output: Conversation history stored in a database.

[0210] Step 10:

[0211] The server uses the conversation history as data to improve the quality of future conversations. Specifically, it analyzes the saved conversation history and learns the user's preference patterns to improve the accuracy of responses in the next dialogue.

[0212] Input: Conversation history stored in a database.

[0213] Output: Data to improve the quality of future conversations.

[0214] Step 11:

[0215] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as generating notifications like "There's a film festival this weekend, why don't you join us?"

[0216] Input: User conversation content.

[0217] Output: Extroverted event and activity suggestions.

[0218] Step 12:

[0219] The user's device will notify the user of this suggestion by displaying a push notification in the app, which can be tapped to display more information.

[0220] Input: Extroverted event and activity suggestions.

[0221] Output: The suggestion notified to the user.

[0222] (Application example 1)

[0223] 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."

[0224] In recent years, the number of people experiencing loneliness has been increasing, raising concerns about the resulting deterioration of mental health. Conversational AI partners have also been attracting attention as a means of alleviating loneliness. However, existing conversational AI partners often fail to adequately respond to the individual interests and preferences of users, particularly in terms of food delivery and meal support. This leaves people experiencing loneliness with a lack of concrete support in their daily lives.

[0225] 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.

[0226] In this invention, the server includes a means for a user to input information about preferences, a means for the server to receive and analyze the user's input information, and a means for generating an interactive AI partner based on the user's preferences using the generated AI model, thereby making it possible to provide food delivery suggestions according to the user's individual preferences.

[0227] "Means for users to input information about preferences" is a function that provides an interface for users to input information such as their hobbies, food preferences, allergies, etc.

[0228] "Means for the server to receive and analyze user input information" refers to the function of the server receiving information sent by the user, analyzing that information, and determining the user's preferences and needs.

[0229] "Means for generating an interactive AI partner based on the user's preferences using the generated AI model" is a function that creates an interactive AI partner that is optimal for the user's preferences and hobbies based on an AI model.

[0230] The "means for conversing with the user using the AI ​​partner" is a function for conversing with the user via text or voice via the generated conversational AI partner.

[0231] The "means for saving the user's conversation history in a storage medium" is a function for recording and saving the content of the conversation between the user and the interactive AI partner so that it can be referenced later.

[0232] "Means for making food delivery-related suggestions" refers to a function that provides meal suggestions and information on the most suitable food delivery service based on the user's preferences and current conversation content.

[0233] "Food ordering assistance" is a function that assists a user in placing an order for the selected meal with an appropriate food delivery service.

[0234] The present invention is a system that provides an interactive artificial intelligence partner (hereinafter referred to as "AI partner") to support users who feel lonely. The main components of this system are a user terminal, a server, and a database.

[0235] 1. User terminal

[0236] A user device is a device on which a user installs the application and enters basic information and questionnaires. It can be a smartphone, tablet, or PC. The application interface on the user device provides a means for the user to converse with the AI ​​partner via text or voice.

[0237] 2. Server

[0238] The server has the following functions:

[0239] Information analysis function: Receives and analyzes survey results and conversation data sent by users.

[0240] Execution of generative AI model: Using a generative artificial intelligence model, we generate the optimal AI partner based on the user's preferences.

[0241] Conversation response generation: Generates appropriate responses based on the user's profile and conversation content and sends them to the user's terminal.

[0242] 3. Database

[0243] The database stores basic information about users, survey results, conversation history, etc. This data will be used to improve the quality of future conversations.

[0244] As a concrete example, take the following steps:

[0245] 1. User registration and questionnaire entry

[0246] Users install and launch the application, enter basic information such as their name, age, and hobbies, and answer a questionnaire about their preferences. For example, "I like cooking" or "I don't like spicy food."

[0247] 2. Creating AI Partners

[0248] The server analyzes the received user information and creates a profile based on the user's preferences. Using the generative AI model, it generates an AI partner that is best suited to the user. For example, a "friendly AI partner who is knowledgeable about Italian cuisine" is generated.

[0249] 3. Initiating and sustaining dialogue

[0250] Through the application, users can interact with the AI ​​partner via text or voice, for example, by asking, "What Italian dish would you recommend for dinner tonight?"

[0251] 4. Food delivery proposals

[0252] The AI ​​partner analyzes the conversation and makes food delivery suggestions based on the user's preferences, such as "Margherita pizza and fruit salad would be good."

[0253] 5. Order assistance

[0254] If a user requests food delivery, the AI ​​partner will send the order to the appropriate delivery service and notify the user.

[0255] The software used is Python, the server uses Flask to provide the API, and the database uses SQLite. This system can be used with cloud infrastructure such as AWS (registered trademark) or Google (registered trademark) Cloud to improve scalability.

[0256] For example, consider the following prompt:

[0257] "What Italian dishes would you recommend for dinner tonight?"

[0258] "Can you recommend a nearby pizzeria?"

[0259] This will make it possible to enrich the eating habits of users who feel lonely and improve their satisfaction.

[0260] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0261] Step 1: Register and enter basic information

[0262] The terminal provides an interface where the user can install applications and enter basic information (such as name, age, preferences, etc.).

[0263] Input: Basic information and preference survey data entered by the user

[0264] Output: The entered user information is sent to the server.

[0265] Specific operation: The application on the device displays items such as the user's name, age, and food preferences in sequence and prompts them to enter them. Once the input is complete, the data is formatted and sent to the server. For example, the user may enter "I like pasta" and "I don't like spicy food."

[0266] Step 2: Receiving and parsing user information

[0267] The server receives the user information sent from the terminal and analyzes it.

[0268] Input: Basic information and preference data sent from your device

[0269] Output: As a result of the analysis, a user profile is generated and stored in a database.

[0270] Specific operation: The server parses the received data in JSON format and extracts the user's preferences and basic information. Next, a user profile is created based on this information and saved in the database. For example, a profile such as "Ichiro Tanaka, 30 years old, likes pasta, dislikes spicy food" is created.

[0271] Step 3: Generate an AI partner

[0272] The server uses the generative AI model to generate a conversational artificial intelligence partner based on the user's preferences.

[0273] Input: Generated user profile

[0274] Output: AI partner that matches user profile

[0275] Specific operation: Using the generative AI model, the system analyzes the user profile and generates the optimal conversational AI partner. For example, it generates a "friendly AI partner who is knowledgeable about Italian cuisine and is a good fit for Ichiro Tanaka, who loves pasta."

[0276] Step 4: Start a conversation

[0277] The terminal provides an interface through which the user can interact with the generated AI partner.

[0278] Input: Questions and conversations from users

[0279] Output: The conversation as a response from the server

[0280] Specific operation: When a user types "What Italian dish would you recommend for dinner tonight?" into a device, the question is sent to the server. The server analyzes the question, generates the most appropriate response, and sends it to the device. For example, it generates a response such as "Margherita pizza or fruit salad would be good."

[0281] Step 5: Save your conversation history

[0282] The server stores the conversation history between the user and the AI ​​partner in a database.

[0283] Input: Conversation between user and AI partner

[0284] Output: Saved conversation history

[0285] Specific operation: After each conversation, the server records the conversation content in a database so that it can be used in the next conversation. For example, it saves the question "What Italian food do you recommend for dinner tonight?" and the response.

[0286] Step 6: Food delivery proposal

[0287] The server makes food delivery suggestions based on the user's preferences and current conversation.

[0288] Input: User preferences and current conversation

[0289] Output: Food delivery suggestions

[0290] How it works: The generative AI model analyzes the user's preferences and conversation content to suggest the most suitable food delivery service. For example, it might suggest, "There's a recommended pizzeria nearby. Would you like to order from it?"

[0291] Step 7: Order Assistance

[0292] The server assists the user in ordering the selected meal from the appropriate food delivery service.

[0293] Input: Your meal and delivery service selections

[0294] Output: Completed order information

[0295] Specific operation: If the user accepts the offer, the server calls the delivery service API and submits the user's order. It then sends a notification of order completion to the user's device. For example, it may notify the user that "Your order for a Margherita pizza has been submitted. It will arrive in 30 minutes."

[0296] 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.

[0297] This invention is a system that provides a conversational AI partner (AI friend, AI girlfriend / boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, a database, and an emotion engine.

[0298] System Configuration Overview

[0299] 1. User Device:

[0300] It is a device on which users install applications and enter basic information and questionnaires.

[0301] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[0302] 2. Server:

[0303] This is a system that receives and analyzes information sent by users (basic information, survey results, conversation data).

[0304] A generative artificial intelligence model is used to generate an interactive artificial intelligence partner based on the user's profile.

[0305] Emotion analysis is performed based on conversation data to recognize the user's emotional state.

[0306] 3. Database:

[0307] Stores user basic information, survey results, conversation history, and emotional data.

[0308] 4. Emotion Engine:

[0309] This is a system that analyzes the user's input information and dialogue content and recognizes their emotions.

[0310] Adjust the tone and content of your response messages based on the perceived emotion.

[0311] Detailed program processing

[0312] User registration and survey entry

[0313] Users install the app and enter basic information such as their name, age, hobbies, etc. They then fill out a questionnaire about their personality and interests.

[0314] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[0315] The terminal transmits the input information and the survey results to the server.

[0316] AI Partner Generation

[0317] The server analyzes the received user information and generates a profile, then uses a generative AI model to generate an AI partner that best suits the user's profile.

[0318] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[0319] Applying the Emotion Engine

[0320] The server analyzes the user's input and dialogue and recognizes emotions using an emotion engine. For example, if a user inputs "I'm feeling a bit down today," the emotion engine will detect "sadness" or "anxiety."

[0321] Example: When a user types "I'm tired today," the emotion engine recognizes "fatigue" and "stress."

[0322] Initiating and sustaining dialogue

[0323] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[0324] The terminal sends this question to the server.

[0325] The server analyzes the question and generates an appropriate response taking into account the results of the emotion engine, for example, "I recommend this movie as a relaxing one."

[0326] The terminal displays the response from the server to the user.

[0327] Conversation history storage and analysis

[0328] The server stores the conversation history and recognized emotion data between the user and the AI ​​partner in a database, which can be used to improve the quality of future interactions.

[0329] Example: Based on the conversation history and emotional state of the user and their AI partner, advice tailored to the user's emotions is provided in the next interaction.

[0330] Promoting social connections

[0331] The server periodically analyzes the user's conversational and emotional data and suggests outgoing events and activities, such as "You seem to be feeling like you need to relax lately. Why don't you try participating in a relaxing event?"

[0332] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[0333] Specific examples

[0334] 1. Initial settings and questionnaire entry:

[0335] The user launches the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[0336] 2. AI Partner Generation:

[0337] The server created a profile for Ichiro Tanaka and generated a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sent an initial message saying, "Hello, Mr. Tanaka. I see you like suspense movies."

[0338] 3. Dialogue and Sentiment Analysis:

[0339] Ichiro Tanaka asks, "What recent suspense movie would you recommend?" The server recommends "Inception is interesting," and displays this to Ichiro Tanaka. If the user feels "anxiety" based on the emotion engine, the server adds a response such as, "There are also some lighter movies that are recommended for when you're feeling anxious."

[0340] 4. Social suggestions:

[0341] The server notifies the user, "You seem to be feeling stressed lately. There's a relaxation event going on nearby. Why don't you join?" Ichiro Tanaka checks the details and decides to participate.

[0342] In this way, the system of the present invention contributes to providing psychological support and promoting social activities to users by combining dialogue with the user and emotion analysis. It also provides more personalized support by providing appropriate responses according to the user's emotional state.

[0343] The processing flow will be explained below.

[0344] Step 1:

[0345] The user installs the app and enters basic information, such as name "Yamada Taro," age "25," and hobby "reading."

[0346] Step 2:

[0347] The device temporarily stores the information entered by the user, then displays a questionnaire about hobbies, preferences, and personality, prompting the user to answer.

[0348] Step 3:

[0349] A user answers a survey. For example, the user answers "science fiction" to the question "What is your favorite movie genre?"

[0350] Step 4:

[0351] The terminal collects the user's survey responses and sends them to the server.

[0352] Step 5:

[0353] The server analyzes the received user information and generates a profile. For example, the server might record in the profile that the user "likes science fiction."

[0354] Step 6:

[0355] The server uses the generative AI model to generate a conversational AI partner based on the profile, in this case an AI partner with an interest in science fiction.

[0356] Step 7:

[0357] The server stores the initial profile of the generated AI partner in a database.

[0358] Step 8:

[0359] The server generates an initial message for the conversational AI partner and sends it to the user: "Hello, Yamada-san. I see you like science fiction!"

[0360] Step 9:

[0361] The terminal displays a welcome message from the server to the user.

[0362] Step 10:

[0363] The user initiates the interaction by typing the question, "What science fiction movie should I watch today?"

[0364] Step 11:

[0365] The terminal sends the user's question to the server.

[0366] Step 12:

[0367] The server analyzes the received question and uses an emotion engine to recognize the user's emotions. For example, if a user types "I'm feeling down today," the emotion engine will detect "sadness" or "anxiety."

[0368] Step 13:

[0369] The server generates an appropriate response based on the recognition results of the emotion engine, such as "I recommend 'Interstellar' as a relaxing movie."

[0370] Step 14:

[0371] The server generates a response and sends it to the terminal.

[0372] Step 15:

[0373] The terminal displays the response message from the server to the user.

[0374] Step 16:

[0375] If the user confirms the response and wishes to continue the dialogue, the next message is entered and the process is repeated.

[0376] Step 17:

[0377] The server stores the conversation history and recognized emotion data in a database, which can be used to improve the quality of future interactions.

[0378] Step 18:

[0379] The server periodically analyzes the user's conversational content and emotional data and suggests outward-looking events and activities. For example, it may notify the user, "It seems like you've been feeling like you need to relax lately. Why don't you try participating in a relaxing event?"

[0380] Step 19:

[0381] The device will display this proposal to the user and provide specific participation methods and detailed information.

[0382] In this way, the system of the present invention repeatedly engages in dialogue with the user and analyzes their emotions, contributing to providing psychological support to the user and promoting social activities.

[0383] Example 2

[0384] 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."

[0385] In modern society, the number of people experiencing loneliness is increasing, making it necessary to provide emotional support and social connections. The present invention aims to alleviate this sense of loneliness and promote emotional stability and social participation by providing users with personalized support. However, conventional systems have difficulty providing appropriate responses based on the user's emotional state, and their ability to analyze the user's emotions through continuous dialogue has been insufficient.

[0386] 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.

[0387] In this invention, the server includes means for analyzing the user's input information and dialogue content and recognizing emotions with an emotion engine, means for generating a response message based on the recognized emotion and sending it to the terminal, and means for saving the user's conversation history and emotion data in a database, thereby enabling the provision of appropriate responses according to the user's emotional state and personalized support based on the emotion analysis results.

[0388] "Users" refer to people who use the system, who install the application, and who input information and answer questionnaires.

[0389] A "terminal" is a device that allows a user to input information and send it to a server, and includes electronic devices such as smartphones, tablets, and personal computers.

[0390] The "server" is a central processing unit that analyzes user input information, generates an AI partner, and recognizes emotions using an emotion engine.

[0391] "Generative AI model" refers to an algorithm or model for generating an optimal conversational AI partner based on a user's profile.

[0392] A "conversational artificial intelligence partner" is an artificial intelligence-based application or service that interacts with and assists users.

[0393] An "emotion engine" refers to a system or algorithm that analyzes user input information and dialogue content to recognize emotions.

[0394] The "database" is a system for storing basic information, survey results, conversation history, and emotional data of users.

[0395] "Conversation history" refers to a record of interactions between a user and their conversational AI partner, and is data used to improve the quality of future interactions.

[0396] This invention is a system that provides conversational AI partners (AI Friends, AI Girlfriends / Boyfriends) to support people who feel lonely. The main components of this system are a user terminal, a server, a database, and an emotion engine.

[0397] First, a user installs an application on a user device such as a smartphone or tablet. Then, the user launches the application, enters basic information such as their name, age, and hobbies, and then answers a questionnaire about their hobbies and interests. For example, a user might enter "I like watching movies" or "I don't like the outdoors." This information plays an important role in each process described below.

[0398] The device automatically sends the basic information and survey results entered by the user to the server. This involves converting the data format and sending it via API. Specifically, the device converts the entered data into JSON format and sends it to the server via an HTTP POST request.

[0399] The server analyzes the received user information and generates a profile. This profile includes the user's basic information, hobbies, interests, and survey results. It then uses a generative AI model to generate a conversational AI partner based on the profile. In this case, the server runs an algorithm such as "for a user who likes watching movies, to generate an AI partner with a common interest."

[0400] Next, the server analyzes the user's input information and dialogue content, and recognizes emotions using an emotion engine. For example, if a user inputs "I'm feeling a little down today," the emotion engine has the ability to detect "sadness" or "anxiety." Based on the recognized emotion, the server generates a response message and sends it to the user's device. For example, if a user inputs "I'm tired today," the server generates a response message such as "I recommend XX as a relaxing movie."

[0401] The user device receives the response message sent from the server and displays it to the user, allowing the user to interact with the AI ​​partner via text or voice.

[0402] Furthermore, the server stores the conversation history and recognized emotional data between the user and the AI ​​partner in a database. This data is used to improve the quality of future interactions. The system also periodically analyzes the conversation and emotional data to suggest extroverted events and activities to the user. For example, it might suggest, "You seem to be feeling stressed lately. Why not join a relaxation event nearby?"

[0403] As a concrete example, if a user uses an application to ask, "What recent movies do you recommend?", the server will take into consideration the results of the emotion engine and recommend, "Inception is interesting." Furthermore, if the emotion engine indicates that the user is feeling "anxious," the server will generate an additional response such as, "There are also some lighter movies that are recommended for when you are anxious."

[0404] In this way, this system contributes to providing psychological support and promoting social activities by combining dialogue with the user and emotion analysis. In addition, the generated conversational AI partner provides more personalized and appropriate support.

[0405] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0406] Step 1:

[0407] The user installs the application and answers a questionnaire about basic information and interests.

[0408] Input: Name, age, hobbies, survey answers

[0409] Action: Launch the application and fill out the form.

[0410] Output: Dataset of basic information and survey results

[0411] Step 2:

[0412] The terminal transmits the information entered by the user and the survey results to the server.

[0413] Input: Dataset of basic information and survey results

[0414] What it does: Converts data into JSON format and sends it to the server via an HTTP POST request.

[0415] Output: Data sent to the server

[0416] Step 3:

[0417] The server analyzes the received user information and survey results and generates a profile.

[0418] Input: Submitted basic information and survey result data

[0419] How it works: It uses analytics algorithms to generate a profile of the user, extracting traits such as "I like watching movies, I don't like the outdoors."

[0420] Output: User profile

[0421] Step 4:

[0422] The server uses the generated artificial intelligence model to generate an interactive artificial intelligence partner based on the user profile.

[0423] Input: User profile

[0424] How it works: Calls the generative AI model, passes the profile data as input, and generates the optimal AI partner. For example, "For a user who likes watching movies, generates an AI partner with the same interests."

[0425] Output: Generated AI partner

[0426] Step 5:

[0427] The server interacts with the user using a conversational artificial intelligence partner.

[0428] Input: User questions and statements

[0429] How it works: Your conversational AI partner receives and analyzes your input and generates an appropriate response. For example, to the question, "What movie do you recommend?", it might respond, "Inception is a great movie."

[0430] Output: Dialogue response message

[0431] Step 6:

[0432] The server analyzes the user's input information and dialogue content, and recognizes emotions using an emotion engine.

[0433] Input: What the user says or types

[0434] How it works: The emotion engine is used to parse emotions from user utterances and identify emotional states, for example recognizing "sadness" or "anxiety" from the statement "I'm feeling bad today."

[0435] Output: Recognized emotion data

[0436] Step 7:

[0437] The server generates a response message based on the recognized emotion and sends it to the terminal.

[0438] Input: Recognized emotion data

[0439] Operation: Based on the emotion data, a response appropriate to the user's state is generated and sent to the device. For example, in response to the emotion "I'm tired today," the system responds with "I recommend this movie as a relaxing one."

[0440] Output: Emotion-based response message

[0441] Step 8:

[0442] The terminal displays the response message from the server to the user.

[0443] Input: Sentiment-based response message

[0444] Behavior: Display the received response message in the application's UI. For example, display a message such as "We recommend XX as a relaxing movie."

[0445] Output: The message displayed to the user

[0446] Step 9:

[0447] The server stores the conversation history between the user and the AI ​​partner and the recognized emotion data in a database.

[0448] Input: Conversation history and emotion data

[0449] How it works: The received data is stored in a database and used to improve the quality of future interactions.

[0450] Output: Conversation history and emotion data stored in a database

[0451] Step 10:

[0452] The server periodically analyzes the user's conversation content and emotional data and suggests outgoing events and activities.

[0453] Input: Conversation history and emotion data stored in a database

[0454] How it works: It analyzes the accumulated data and suggests events and activities that will be beneficial to the user. For example, it may notify the user, "It seems like you've been feeling like you need to relax lately. There's a relaxation event in your neighborhood. Why don't you join us?"

[0455] Output: Proposal message

[0456] (Application example 2)

[0457] 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."

[0458] Conversational AI partner systems designed to support people experiencing loneliness primarily aim to provide psychological support to users, but their application to specific tasks is limited. As a result, the security service sector lacks systems that can adequately address mental issues such as staff stress levels and reduced concentration. This can result in reduced work efficiency and safety for security staff. Therefore, a new system is needed that can improve efficiency and safety by monitoring the mental state of security staff in real time and providing appropriate support.

[0459] The identification processing 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 the user to answer a questionnaire about hobbies and preferences, means for the server to receive and analyze the user's input information, means for using a generative AI model to generate an interactive AI partner that matches the user's preferences, means for interacting with the user using the generated AI partner, means for saving the user's conversation history in a database, means for analyzing the emotions of security staff and monitoring their stress levels and concentration in real time, and means for providing appropriate advice based on the analysis results. This makes it possible to constantly understand the mental state of security staff and provide appropriate support in a timely manner.

[0460] A "user terminal" is a device on which a user installs applications and enters basic information and questionnaires.

[0461] A "server" is a system that receives and analyzes information sent by users.

[0462] A "generative artificial intelligence model" is a model that generates an interactive artificial intelligence partner based on a user's profile.

[0463] A "conversational AI partner" is an AI that can converse with a user via text or voice.

[0464] The "database" is a system that stores basic information, survey results, conversation history, and emotional data of users.

[0465] An "emotion engine" is a system that analyzes user input information and dialogue content to recognize emotions.

[0466] "Real-time monitoring" is the process of constantly monitoring the emotional state of security staff and obtaining data at the appropriate time.

[0467] "Providing advice" is a function that provides appropriate instructions and advice to security staff based on the analysis results.

[0468] A "conversation history" is a record of the conversation that took place between a user and an interactive AI partner.

[0469] This invention is a conversational AI partner system for supporting people who feel lonely, particularly in the field of security services, which monitors the mental state of security staff in real time and provides appropriate support. The system mainly consists of a user terminal, a server, a database, and an emotion engine.

[0470] System Configuration Overview

[0471] 1. User Device:

[0472] This is a device on which users install an application and enter basic information and a questionnaire. Through this terminal, security staff can converse with a conversational AI partner via text or voice. For example, this could be a smartphone or a head-mounted display (HMD).

[0473] 2. Server:

[0474] The server is a system that receives and analyzes information sent by users (basic information, survey results, conversation data). It uses a generative AI model to generate a conversational AI partner based on the user's profile. It also performs emotion analysis based on the conversation data to recognize the user's emotional state.

[0475] 3. Database:

[0476] The database is a system that stores basic information, survey results, conversation history, and emotional data of users. This data is used to improve the quality of future interactions.

[0477] 4. Emotion Engine:

[0478] The emotion engine is a system that analyzes user input and dialogue content to recognize their emotions, and adjusts the tone and content of the response message based on the recognized emotions.

[0479] Detailed program processing

[0480] The server uses the speech_recognition library for speech recognition to acquire voice input from security staff. The acquired speech is converted into text, and the text is input into the sentiment analysis model. The sentiment analysis model uses a model built with Keras. The analyzed sentiment data is sent to the server using the requests library.

[0481] The server uses this data to monitor the stress levels and concentration of security staff in real time, and provides appropriate advice based on the results of emotion analysis, such as "Take a 15-minute break and relax" or "You seem anxious. Take a deep breath and relax."

[0482] Specific examples

[0483] 1. Initial settings and questionnaire entry:

[0484] Security staff install the app and enter basic information such as their name, job description, and working hours, then answer a questionnaire about situations that make them feel stressed and how they relax.

[0485] 2. Real-time monitoring and analysis:

[0486] If a security staff member voice-types "I'm feeling a bit tired" while on duty, the emotion engine will recognize this as "fatigue" and provide a response such as "Take a 15-minute break and relax."

[0487] 3. Anomaly detection and alerting:

[0488] AI detects anomalies in surveillance camera footage and alerts security staff, and if the emotion engine identifies a staff member as stressed, the alert is delivered in a calmer, more soothing tone.

[0489] Prompt Sentence Examples

[0490] If a user says, "I've been feeling anxious lately and can't sleep," the emotion engine will recognize "anxiety" and generate a response like this:

[0491] "You seem to be experiencing anxiety. Perhaps you should talk to your doctor about it?"

[0492] In this way, the system of this invention combines dialogue with the user and emotion analysis to contribute to improving the user's mental support and work efficiency. Real-time monitoring and appropriate responses support the mental health of security staff. Furthermore, by providing appropriate responses according to the user's emotional state, more personalized support is realized.

[0493] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0494] Step 1:

[0495] The user installs the application and fills out a questionnaire and basic information.

[0496] Input: Basic information such as name, age, hobbies, and questionnaire results about your personality and interests.

[0497] Processing: The device collects the entered information and sends it to the server, where it is stored in a database.

[0498] Output: User information and survey results sent to the server.

[0499] Step 2:

[0500] The server analyzes the received user information and generates a profile.

[0501] Input: User's basic information and survey results.

[0502] Processing: The server uses the generated AI model to generate a conversational AI partner based on the user's profile.

[0503] Output: The best conversational artificial intelligence partner for the user.

[0504] Step 3:

[0505] The user initiates a dialogue with the generated conversational artificial intelligence partner.

[0506] Input: User text or voice input.

[0507] Processing: The device receives the input and sends it to the server, which uses an emotion engine to analyze the emotion and generate an appropriate response.

[0508] Output: A response message from your conversational AI partner.

[0509] Step 4:

[0510] The server monitors the user's emotional state in real time.

[0511] Input: User interaction and emotion data.

[0512] Processing: The emotion engine analyzes the user's emotions, assessing their stress level and concentration. The emotion data is stored in a database.

[0513] Output: Evaluation of the user's emotional state.

[0514] Step 5:

[0515] Based on the analysis results, the server provides appropriate advice to the user.

[0516] Input: Analysis results of the emotion engine and dialogue history.

[0517] Processing: The server generates an appropriate response message based on the analysis results and sends it to the device. The device then displays or audibly presents the response message to the user.

[0518] Output: Advice or instructions provided to the user.

[0519] Step 6:

[0520] Conversation history and emotion data are stored in a database.

[0521] Input: Conversation history between the user and their conversational AI partner, as well as emotional data.

[0522] Processing: The server stores this data in a database and uses it for future analysis and to improve the quality of the interaction.

[0523] Output: Conversation history and sentiment data stored in a database.

[0524] Prompt Sentence Examples

[0525] If a user says, "I've been feeling anxious lately and can't sleep," the emotion engine will recognize "anxiety" and generate a response like this:

[0526] "You seem to be experiencing anxiety. Perhaps you should talk to your doctor about it?"

[0527] 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.

[0528] 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.

[0529] 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.

[0530] [Second embodiment]

[0531] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0532] 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.

[0533] 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).

[0534] 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.

[0535] 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.

[0536] 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).

[0537] 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.

[0538] 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.

[0539] 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.

[0540] 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.

[0541] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0542] 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."

[0543] This invention is a system that provides a conversational AI partner (AI Friends, AI Girlfriend / Boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, and a database.

[0544] System Configuration Overview

[0545] 1. User Device:

[0546] It is a device on which users install applications and enter basic information and questionnaires.

[0547] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[0548] 2. Server:

[0549] This is a system that receives and analyzes survey results and conversation data sent by users.

[0550] It uses a generative artificial intelligence model to generate the best AI partner based on the user's profile.

[0551] Based on the content of the conversation, the AI ​​partner generates a response and sends it to the user.

[0552] 3. Database:

[0553] Stores user basic information, survey results, conversation history, etc.

[0554] Detailed program processing

[0555] User registration and survey entry

[0556] Users install and launch the app, then enter basic information such as their name, age, and hobbies, and answer a questionnaire about their personality and interests.

[0557] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[0558] The terminal transmits the input information and the survey results to the server.

[0559] AI Partner Generation

[0560] The server analyzes the received user information and creates a profile based on the user's interests and preferences, then uses a generative AI model to generate an AI partner that best matches the user's profile.

[0561] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[0562] Initiating and sustaining dialogue

[0563] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[0564] The terminal sends this question to the server.

[0565] The server analyzes the question and generates an appropriate response, such as "There's a movie that's been getting a lot of buzz lately. Why don't you check it out?"

[0566] The terminal displays the response from the server to the user.

[0567] Conversation history storage and analysis

[0568] The server stores the conversation history between the user and the AI ​​partner in a database, which can be used to improve the quality of future conversations.

[0569] Example: Based on the conversation history between the user and their AI partner, the next interaction will recommend movies that reflect the user's preferences.

[0570] Promoting social connections

[0571] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a film festival this weekend, why don't you join us?"

[0572] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[0573] Specific examples

[0574] 1. Initial settings and questionnaire entry:

[0575] The user launches the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[0576] 2. AI Partner Generation:

[0577] The server creates a profile for Ichiro Tanaka and generates a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sends an initial message saying, "Hello, Tanaka! There's a good suspense movie out recently."

[0578] 3. Continuing the dialogue:

[0579] Ichiro Tanaka asks, "What recent suspense movie do you recommend?" The server recommends "Inception," and displays it to Ichiro Tanaka.

[0580] 4. Social suggestions:

[0581] The server notifies him, "A suspense film festival is being held at a nearby movie theater. Why don't you come and participate?" Ichiro Tanaka checks the details and decides to participate.

[0582] In this way, the present invention is a system that not only provides psychological support to users but also contributes to promoting social activities.

[0583] The processing flow will be explained below.

[0584] Step 1:

[0585] A user installs the app and enters basic information, such as name "Yamada Taro," age "25," and hobby "reading."

[0586] Step 2:

[0587] The device temporarily stores the user's input information, then displays a questionnaire about the user's hobbies, preferences, and personality, prompting the user to respond.

[0588] Step 3:

[0589] A user answers a survey. For example, the user answers "science fiction" to the question "What is your favorite movie genre?"

[0590] Step 4:

[0591] The terminal collects the user's survey responses and sends them to the server.

[0592] Step 5:

[0593] The server analyzes the received user information and generates a profile. For example, the server might record in the profile that the user "likes science fiction."

[0594] Step 6:

[0595] The server uses the generative AI model to generate a conversational AI partner based on the profile, in this case an AI partner with an interest in science fiction.

[0596] Step 7:

[0597] The server stores the initial profile of the generated AI partner in a database.

[0598] Step 8:

[0599] The server generates an initial message for the conversational AI partner and sends it to the user: "Hello, Yamada-san. I see you like science fiction!"

[0600] Step 9:

[0601] The terminal displays a welcome message from the server to the user.

[0602] Step 10:

[0603] The user initiates a dialogue by typing a question: "What science fiction movie should I watch today?"

[0604] Step 11:

[0605] The terminal sends the user's question to the server.

[0606] Step 12:

[0607] The server analyzes the received question and uses a generative AI model to generate an appropriate response, such as "I recommend the popular movie 'Interstellar'."

[0608] Step 13:

[0609] The server sends the generated response to the terminal.

[0610] Step 14:

[0611] The terminal displays the response message from the server to the user.

[0612] Step 15:

[0613] If the user interaction continues, the user enters more messages which are sent to the server, and the process repeats.

[0614] Step 16:

[0615] The server stores the conversation history with the user in a database to help with future interactions.

[0616] Step 17:

[0617] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a science fiction film festival in your neighborhood. Why don't you go?"

[0618] Step 18:

[0619] The terminal displays the suggestions from the server to the user, allowing the user to check the detailed information.

[0620] In this way, the system of the present invention repeatedly interacts with the user and analyzes data, contributing to providing psychological support to the user and promoting social activities.

[0621] Example 1

[0622] 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."

[0623] Conventional conversational AI systems are limited in the dialogue and suggestions they provide based on the user's personal hobbies and preferences, and are unable to fully alleviate the user's feelings of loneliness and stress. Furthermore, they lack a mechanism for utilizing the user's dialogue history to improve the quality of future conversations. Furthermore, they lack the functionality to encourage users' social activities by suggesting social activities and events based on the user's preferences.

[0624] 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.

[0625] In this invention, the server includes a means for analyzing the user's question, generating a response, and sending it to the terminal, a means for using the conversation history as data for improving the quality of future conversations, and a means for generating an interactive AI partner using a generative AI model based on the user profile. This enables dialogue and suggestions based on the user's individual hobbies and preferences, improving the quality of conversations and promoting social activities.

[0626] "User" refers to an individual who uses the system to enter a questionnaire about basic information and hobbies and preferences and engages in conversation with an interactive AI partner.

[0627] "Terminal" refers to the device on which a user enters basic information and survey results and sends them to the server, as well as the device on which a user can converse with an interactive AI partner.

[0628] "Server" refers to a computer system that receives and analyzes user information, generates a conversational artificial intelligence partner using a generative AI model, analyzes the content of the dialogue with the user to generate a response, and stores the conversation history in a database.

[0629] "Generative AI Model" means an artificial intelligence model used to generate a conversational artificial intelligence partner that is tailored to a user's preferences and interests based on the user's profile.

[0630] "Prompt" refers to the text of an instruction or question input to a generative AI model.

[0631] "Conversational AI partner" refers to an AI agent generated by a generative AI model that engages in text or voice dialogue with a user.

[0632] "Conversation history" refers to a record of all conversations between a user and their conversational AI partner.

[0633] "Database" refers to a data storage system that stores basic information, survey results, and conversation history of users, and retrieves or analyzes information as needed.

[0634] "Extroverted events and activities" refer to public events and group activities that users can participate in that are proposed to promote social activity for users.

[0635] A "user profile" refers to individual characteristic information generated based on information such as a user's hobbies, preferences, personality, and survey results.

[0636] This invention is a system that provides a conversational AI partner (AI Friends, AI Girlfriend / Boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, and a database.

[0637] System Configuration Overview

[0638] 1. User Device:

[0639] It is a device on which users install applications and enter basic information and questionnaires.

[0640] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[0641] Specific examples include smartphones and tablets.

[0642] 2. Server:

[0643] This is a system that receives and analyzes survey results and conversation data sent by users.

[0644] Uses generative artificial intelligence models (e.g., GPT-3) to generate the best AI partner based on the user's profile.

[0645] Based on the content of the conversation, the AI ​​partner generates a response and sends it to the user.

[0646] 3. Database:

[0647] Stores user basic information, survey results, conversation history, etc.

[0648] Use a database management system (e.g., MySQL or PostgreSQL).

[0649] Specific processing of the program

[0650] User registration and survey entry

[0651] Users install and launch the app, then enter basic information such as their name, age, and hobbies, and answer a questionnaire about their personality and interests.

[0652] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[0653] The terminal transmits the input information and the survey results to the server.

[0654] AI Partner Generation

[0655] The server analyzes the received user information and creates a profile based on the user's interests and preferences, then uses a generative AI model to generate an AI partner that best matches the user's profile.

[0656] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[0657] Example prompt: "The user likes watching movies. What recent movies do you recommend?"

[0658] Initiating and sustaining dialogue

[0659] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[0660] The terminal sends this question to the server.

[0661] The server analyzes the question and generates an appropriate response, such as "There's a movie that's been getting a lot of buzz lately. Why don't you check it out?"

[0662] The terminal displays the response from the server to the user.

[0663] Conversation history storage and analysis

[0664] The server stores the conversation history between the user and the AI ​​partner in a database, which can be used to improve the quality of future conversations.

[0665] Example: Based on the conversation history between the user and their AI partner, the next interaction will recommend movies that reflect the user's preferences.

[0666] Promoting social connections

[0667] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a film festival this weekend, why don't you join us?"

[0668] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[0669] Specific examples

[0670] 1. Initial settings and questionnaire entry:

[0671] The user starts the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[0672] 2. AI Partner Generation:

[0673] The server creates a profile for Ichiro Tanaka and generates a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sends an initial message saying, "Hello, Tanaka! There are some good suspense movies out there these days."

[0674] 3. Continuing the dialogue:

[0675] Ichiro Tanaka asks, "What recent suspense movie would you recommend?" The server recommends "Inception is interesting," and displays it to Ichiro Tanaka.

[0676] 4. Social suggestions:

[0677] The server sends a message saying, "A suspense film festival is being held at a nearby movie theater. Why don't you come and participate?" Ichiro Tanaka checks the details and decides to participate.

[0678] In this way, the present invention is a system that not only provides psychological support to users but also contributes to promoting social activities, which is expected to improve the quality of life of users.

[0679] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0680] Step 1:

[0681] The user installs and launches the app. This displays the app's initial setup screen. The user enters basic information such as name, age, and hobbies, and answers a questionnaire about their personality and interests. Specifically, the user fills in the input form with information such as "Name: Ichiro Tanaka," "Age: 30," and "Hobbies: Watching movies."

[0682] Input: Name, age, hobbies, and survey responses about personality and interests.

[0683] Output: User basic information and survey results.

[0684] Step 2:

[0685] The device compiles the entered basic information and survey results and sends them to the server. Specifically, when the user presses the input completion button, the device compiles the information and sends it to the server via an HTTP POST request.

[0686] Input: User basic information and survey results.

[0687] Output: The user information sent to the server.

[0688] Step 3:

[0689] The server analyzes the received user information and generates a user profile. Specifically, the server analyzes the information temporarily stored in the database and generates a profile such as "I like watching movies," "30-year-old male," and "suspense movie lover."

[0690] Input: The user information sent to the server.

[0691] Output: The generated user profile.

[0692] Step 4:

[0693] The server uses a generative AI model to generate a conversational AI partner based on the user profile. Specifically, the server invokes a generative AI model (e.g., GPT-3), inputs the profile as a prompt, and generates the AI ​​partner's personality and initial message.

[0694] Input: User profile, prompt statement.

[0695] Output: The generated conversational artificial intelligence partner.

[0696] Step 5:

[0697] The user initiates a conversation with the AI ​​partner through the application, for example by typing a question into a text box, such as "What movie should I watch today?", and then pressing the send button.

[0698] Input: The user's question.

[0699] Output: The question asked by the user.

[0700] Step 6:

[0701] The device sends the user's question to the server by collecting the contents of the text box and sending it to the server via an HTTP POST request.

[0702] Input: The user's question.

[0703] Output: The question sent to the server.

[0704] Step 7:

[0705] The server analyzes the question and generates an appropriate response. Specifically, the server analyzes the question using natural language processing and uses a generative AI model to generate a response such as "Inception is interesting."

[0706] Input: The user's question.

[0707] Output: The generated response.

[0708] Step 8:

[0709] The terminal displays the response from the server to the user. Specifically, the response text received from the server is displayed on the message screen.

[0710] Input: The generated response.

[0711] Output: The response displayed to the user.

[0712] Step 9:

[0713] The server stores the conversation history between the user and the AI ​​partner in a database. Specifically, the server stores the contents of each message sent and received in the conversation in the database.

[0714] Input: The conversation between the user and their AI partner.

[0715] Output: Conversation history stored in a database.

[0716] Step 10:

[0717] The server uses the conversation history as data to improve the quality of future conversations. Specifically, it analyzes the saved conversation history and learns the user's preference patterns to improve the accuracy of responses in the next dialogue.

[0718] Input: Conversation history stored in a database.

[0719] Output: Data to improve the quality of future conversations.

[0720] Step 11:

[0721] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as generating notifications like "There's a film festival this weekend, why don't you join us?"

[0722] Input: User conversation content.

[0723] Output: Extroverted event and activity suggestions.

[0724] Step 12:

[0725] The user's device will notify the user of this suggestion by displaying a push notification in the app, which can be tapped to display more information.

[0726] Input: Extroverted event and activity suggestions.

[0727] Output: The suggestion notified to the user.

[0728] (Application example 1)

[0729] 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."

[0730] In recent years, the number of people experiencing loneliness has been increasing, raising concerns about the resulting deterioration of mental health. Conversational AI partners have also been attracting attention as a means of alleviating loneliness. However, existing conversational AI partners often fail to adequately respond to the individual interests and preferences of users, particularly in terms of food delivery and meal support. This leaves people experiencing loneliness with a lack of concrete support in their daily lives.

[0731] 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.

[0732] In this invention, the server includes a means for a user to input information about preferences, a means for the server to receive and analyze the user's input information, and a means for generating an interactive AI partner based on the user's preferences using the generated AI model, thereby making it possible to provide food delivery suggestions according to the user's individual preferences.

[0733] "Means for users to input information about preferences" is a function that provides an interface for users to input information such as their hobbies, food preferences, allergies, etc.

[0734] "Means for the server to receive and analyze user input information" refers to the function of the server receiving information sent by the user, analyzing that information, and determining the user's preferences and needs.

[0735] "Means for generating an interactive AI partner based on the user's preferences using the generated AI model" is a function that creates an interactive AI partner that is optimal for the user's preferences and hobbies based on an AI model.

[0736] The "means for conversing with the user using the AI ​​partner" is a function for conversing with the user via text or voice via the generated conversational AI partner.

[0737] The "means for saving the user's conversation history in a storage medium" is a function for recording and saving the content of the conversation between the user and the interactive AI partner so that it can be referenced later.

[0738] "Means for making food delivery-related suggestions" refers to a function that provides meal suggestions and information on the most suitable food delivery service based on the user's preferences and current conversation content.

[0739] "Food ordering assistance" is a function that assists a user in placing an order for the selected meal with an appropriate food delivery service.

[0740] The present invention is a system that provides an interactive artificial intelligence partner (hereinafter referred to as "AI partner") to support users who feel lonely. The main components of this system are a user terminal, a server, and a database.

[0741] 1. User terminal

[0742] A user device is a device on which a user installs the application and enters basic information and questionnaires. It can be a smartphone, tablet, or PC. The application interface on the user device provides a means for the user to converse with the AI ​​partner via text or voice.

[0743] 2. Server

[0744] The server has the following functions:

[0745] Information analysis function: Receives and analyzes survey results and conversation data sent by users.

[0746] Execution of generative AI model: Using a generative artificial intelligence model, we generate the optimal AI partner based on the user's preferences.

[0747] Conversation response generation: Generates appropriate responses based on the user's profile and conversation content and sends them to the user's terminal.

[0748] 3. Database

[0749] The database stores basic information about users, survey results, conversation history, etc. This data will be used to improve the quality of future conversations.

[0750] As a concrete example, take the following steps:

[0751] 1. User registration and questionnaire entry

[0752] Users install and launch the application, enter basic information such as their name, age, and hobbies, and answer a questionnaire about their preferences. For example, "I like cooking" or "I don't like spicy food."

[0753] 2. Creating AI Partners

[0754] The server analyzes the received user information and creates a profile based on the user's preferences. Using the generative AI model, it generates an AI partner that is best suited to the user. For example, a "friendly AI partner who is knowledgeable about Italian cuisine" is generated.

[0755] 3. Initiating and sustaining dialogue

[0756] Through the application, users can interact with the AI ​​partner via text or voice, for example, by asking, "What Italian dish would you recommend for dinner tonight?"

[0757] 4. Food delivery proposals

[0758] The AI ​​partner analyzes the conversation and makes food delivery suggestions based on the user's preferences, such as "Margherita pizza and fruit salad would be good."

[0759] 5. Order assistance

[0760] If a user requests food delivery, the AI ​​partner will send the order to the appropriate delivery service and notify the user.

[0761] The software used is Python, the server uses Flask to provide the API, and the database uses SQLite. This system can be used with cloud infrastructure such as AWS or Google Cloud to improve scalability.

[0762] For example, consider the following prompt:

[0763] "What Italian dishes would you recommend for dinner tonight?"

[0764] "Can you recommend a nearby pizzeria?"

[0765] This will make it possible to enrich the eating habits of users who feel lonely and improve their satisfaction.

[0766] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0767] Step 1: Register and enter basic information

[0768] The terminal provides an interface where the user can install applications and enter basic information (such as name, age, preferences, etc.).

[0769] Input: Basic information and preference survey data entered by the user

[0770] Output: The entered user information is sent to the server.

[0771] Specific operation: The application on the device displays items such as the user's name, age, and food preferences in sequence and prompts them to enter them. Once the input is complete, the data is formatted and sent to the server. For example, the user may enter "I like pasta" and "I don't like spicy food."

[0772] Step 2: Receiving and parsing user information

[0773] The server receives the user information sent from the terminal and analyzes it.

[0774] Input: Basic information and preference data sent from your device

[0775] Output: As a result of the analysis, a user profile is generated and stored in a database.

[0776] Specific operation: The server parses the received data in JSON format and extracts the user's preferences and basic information. Next, a user profile is created based on this information and saved in the database. For example, a profile such as "Ichiro Tanaka, 30 years old, likes pasta, dislikes spicy food" is created.

[0777] Step 3: Generate an AI partner

[0778] The server uses the generative AI model to generate a conversational artificial intelligence partner based on the user's preferences.

[0779] Input: Generated user profile

[0780] Output: AI partner that matches user profile

[0781] Specific operation: Using the generative AI model, the system analyzes the user profile and generates the optimal conversational AI partner. For example, it generates a "friendly AI partner who is knowledgeable about Italian cuisine and is a good fit for Ichiro Tanaka, who loves pasta."

[0782] Step 4: Start a conversation

[0783] The terminal provides an interface through which the user can interact with the generated AI partner.

[0784] Input: Questions and conversations from users

[0785] Output: The conversation as a response from the server

[0786] Specific operation: When a user types "What Italian dish would you recommend for dinner tonight?" into a device, the question is sent to the server. The server analyzes the question, generates the most appropriate response, and sends it to the device. For example, it generates a response such as "Margherita pizza or fruit salad would be good."

[0787] Step 5: Save your conversation history

[0788] The server stores the conversation history between the user and the AI ​​partner in a database.

[0789] Input: Conversation between user and AI partner

[0790] Output: Saved conversation history

[0791] Specific operation: After each conversation, the server records the conversation content in a database so that it can be used in the next conversation. For example, it saves the question "What Italian food do you recommend for dinner tonight?" and the response.

[0792] Step 6: Food delivery proposal

[0793] The server makes food delivery suggestions based on the user's preferences and current conversation.

[0794] Input: User preferences and current conversation

[0795] Output: Food delivery suggestions

[0796] How it works: The generative AI model analyzes the user's preferences and conversation content to suggest the most suitable food delivery service. For example, it might suggest, "There's a recommended pizzeria nearby. Would you like to order from it?"

[0797] Step 7: Order Assistance

[0798] The server assists the user in ordering the selected meal from the appropriate food delivery service.

[0799] Input: Your meal and delivery service selections

[0800] Output: Completed order information

[0801] Specific operation: If the user accepts the offer, the server calls the delivery service API and submits the user's order. It then sends a notification of order completion to the user's device. For example, it may notify the user that "Your order for a Margherita pizza has been submitted. It will arrive in 30 minutes."

[0802] 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.

[0803] This invention is a system that provides a conversational AI partner (AI friend, AI girlfriend / boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, a database, and an emotion engine.

[0804] System Configuration Overview

[0805] 1. User Device:

[0806] It is a device on which users install applications and enter basic information and questionnaires.

[0807] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[0808] 2. Server:

[0809] This is a system that receives and analyzes information sent by users (basic information, survey results, conversation data).

[0810] A generative artificial intelligence model is used to generate an interactive artificial intelligence partner based on the user's profile.

[0811] Emotion analysis is performed based on conversation data to recognize the user's emotional state.

[0812] 3. Database:

[0813] Stores user basic information, survey results, conversation history, and emotional data.

[0814] 4. Emotion Engine:

[0815] This is a system that analyzes the user's input information and dialogue content and recognizes their emotions.

[0816] Adjust the tone and content of your response messages based on the perceived emotion.

[0817] Detailed program processing

[0818] User registration and survey entry

[0819] Users install the app and enter basic information such as their name, age, hobbies, etc. They then fill out a questionnaire about their personality and interests.

[0820] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[0821] The terminal transmits the input information and the survey results to the server.

[0822] AI Partner Generation

[0823] The server analyzes the received user information and generates a profile, then uses a generative AI model to generate an AI partner that best suits the user's profile.

[0824] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[0825] Applying the Emotion Engine

[0826] The server analyzes the user's input and dialogue and recognizes emotions using an emotion engine. For example, if a user inputs "I'm feeling a bit down today," the emotion engine will detect "sadness" or "anxiety."

[0827] Example: When a user types "I'm tired today," the emotion engine recognizes "fatigue" and "stress."

[0828] Initiating and sustaining dialogue

[0829] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[0830] The terminal sends this question to the server.

[0831] The server analyzes the question and generates an appropriate response taking into account the results of the emotion engine, for example, "I recommend this movie as a relaxing one."

[0832] The terminal displays the response from the server to the user.

[0833] Conversation history storage and analysis

[0834] The server stores the conversation history and recognized emotion data between the user and the AI ​​partner in a database, which can be used to improve the quality of future interactions.

[0835] Example: Based on the conversation history and emotional state of the user and their AI partner, advice tailored to the user's emotions is provided in the next interaction.

[0836] Promoting social connections

[0837] The server periodically analyzes the user's conversational and emotional data and suggests outgoing events and activities, such as "You seem to be feeling like you need to relax lately. Why don't you try participating in a relaxing event?"

[0838] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[0839] Specific examples

[0840] 1. Initial settings and questionnaire entry:

[0841] The user launches the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[0842] 2. AI Partner Generation:

[0843] The server created a profile for Ichiro Tanaka and generated a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sent an initial message saying, "Hello, Mr. Tanaka. I see you like suspense movies."

[0844] 3. Dialogue and Sentiment Analysis:

[0845] Ichiro Tanaka asks, "What recent suspense movie would you recommend?" The server recommends "Inception is interesting," and displays this to Ichiro Tanaka. If the user feels "anxiety" based on the emotion engine, the server adds a response such as, "There are also some lighter movies that are recommended for when you're feeling anxious."

[0846] 4. Social suggestions:

[0847] The server notifies the user, "You seem to be feeling stressed lately. There's a relaxation event going on nearby. Why don't you join?" Ichiro Tanaka checks the details and decides to participate.

[0848] In this way, the system of the present invention contributes to providing psychological support and promoting social activities to users by combining dialogue with the user and emotion analysis. It also provides more personalized support by providing appropriate responses according to the user's emotional state.

[0849] The processing flow will be explained below.

[0850] Step 1:

[0851] The user installs the app and enters basic information, such as name "Yamada Taro," age "25," and hobby "reading."

[0852] Step 2:

[0853] The device temporarily stores the information entered by the user, then displays a questionnaire about hobbies, preferences, and personality, prompting the user to answer.

[0854] Step 3:

[0855] A user answers a survey. For example, the user answers "science fiction" to the question "What is your favorite movie genre?"

[0856] Step 4:

[0857] The terminal collects the user's survey responses and sends them to the server.

[0858] Step 5:

[0859] The server analyzes the received user information and generates a profile. For example, the server might record in the profile that the user "likes science fiction."

[0860] Step 6:

[0861] The server uses the generative AI model to generate a conversational AI partner based on the profile, in this case an AI partner with an interest in science fiction.

[0862] Step 7:

[0863] The server stores the initial profile of the generated AI partner in a database.

[0864] Step 8:

[0865] The server generates an initial message for the conversational AI partner and sends it to the user: "Hello, Yamada-san. I see you like science fiction!"

[0866] Step 9:

[0867] The terminal displays a welcome message from the server to the user.

[0868] Step 10:

[0869] The user initiates the interaction by typing the question, "What science fiction movie should I watch today?"

[0870] Step 11:

[0871] The terminal sends the user's question to the server.

[0872] Step 12:

[0873] The server analyzes the received question and uses an emotion engine to recognize the user's emotions. For example, if a user types "I'm feeling down today," the emotion engine will detect "sadness" or "anxiety."

[0874] Step 13:

[0875] The server generates an appropriate response based on the recognition results of the emotion engine, such as "I recommend 'Interstellar' as a relaxing movie."

[0876] Step 14:

[0877] The server generates a response and sends it to the terminal.

[0878] Step 15:

[0879] The terminal displays the response message from the server to the user.

[0880] Step 16:

[0881] If the user confirms the response and wishes to continue the dialogue, the next message is entered and the process is repeated.

[0882] Step 17:

[0883] The server stores the conversation history and recognized emotion data in a database, which can be used to improve the quality of future interactions.

[0884] Step 18:

[0885] The server periodically analyzes the user's conversational content and emotional data and suggests outward-looking events and activities. For example, it may notify the user, "It seems like you've been feeling like you need to relax lately. Why don't you try participating in a relaxing event?"

[0886] Step 19:

[0887] The device will display this proposal to the user and provide specific participation methods and detailed information.

[0888] In this way, the system of the present invention repeatedly engages in dialogue with the user and analyzes their emotions, contributing to providing psychological support to the user and promoting social activities.

[0889] Example 2

[0890] 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."

[0891] In modern society, the number of people experiencing loneliness is increasing, making it necessary to provide emotional support and social connections. The present invention aims to alleviate this sense of loneliness and promote emotional stability and social participation by providing users with personalized support. However, conventional systems have difficulty providing appropriate responses based on the user's emotional state, and their ability to analyze the user's emotions through continuous dialogue has been insufficient.

[0892] 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.

[0893] In this invention, the server includes means for analyzing the user's input information and dialogue content and recognizing emotions with an emotion engine, means for generating a response message based on the recognized emotion and sending it to the terminal, and means for saving the user's conversation history and emotion data in a database, thereby enabling the provision of appropriate responses according to the user's emotional state and personalized support based on the emotion analysis results.

[0894] "Users" refer to people who use the system, who install the application, and who input information and answer questionnaires.

[0895] A "terminal" is a device that allows a user to input information and send it to a server, and includes electronic devices such as smartphones, tablets, and personal computers.

[0896] The "server" is a central processing unit that analyzes user input information, generates an AI partner, and recognizes emotions using an emotion engine.

[0897] "Generative AI model" refers to an algorithm or model for generating an optimal conversational AI partner based on a user's profile.

[0898] A "conversational artificial intelligence partner" is an artificial intelligence-based application or service that interacts with and assists users.

[0899] An "emotion engine" refers to a system or algorithm that analyzes user input information and dialogue content to recognize emotions.

[0900] The "database" is a system for storing basic information, survey results, conversation history, and emotional data of users.

[0901] "Conversation history" refers to a record of interactions between a user and their conversational AI partner, and is data used to improve the quality of future interactions.

[0902] This invention is a system that provides conversational AI partners (AI Friends, AI Girlfriends / Boyfriends) to support people who feel lonely. The main components of this system are a user terminal, a server, a database, and an emotion engine.

[0903] First, a user installs an application on a user device such as a smartphone or tablet. Then, the user launches the application, enters basic information such as their name, age, and hobbies, and then answers a questionnaire about their hobbies and interests. For example, a user might enter "I like watching movies" or "I don't like the outdoors." This information plays an important role in each process described below.

[0904] The device automatically sends the basic information and survey results entered by the user to the server. This involves converting the data format and sending it via API. Specifically, the device converts the entered data into JSON format and sends it to the server via an HTTP POST request.

[0905] The server analyzes the received user information and generates a profile. This profile includes the user's basic information, hobbies, interests, and survey results. It then uses a generative AI model to generate a conversational AI partner based on the profile. In this case, the server runs an algorithm such as "for a user who likes watching movies, to generate an AI partner with a common interest."

[0906] Next, the server analyzes the user's input information and dialogue content, and recognizes emotions using an emotion engine. For example, if a user inputs "I'm feeling a little down today," the emotion engine has the ability to detect "sadness" or "anxiety." Based on the recognized emotion, the server generates a response message and sends it to the user's device. For example, if a user inputs "I'm tired today," the server generates a response message such as "I recommend XX as a relaxing movie."

[0907] The user device receives the response message sent from the server and displays it to the user, allowing the user to interact with the AI ​​partner via text or voice.

[0908] Furthermore, the server stores the conversation history and recognized emotional data between the user and the AI ​​partner in a database. This data is used to improve the quality of future interactions. The system also periodically analyzes the conversation and emotional data to suggest extroverted events and activities to the user. For example, it might suggest, "You seem to be feeling stressed lately. Why not join a relaxation event nearby?"

[0909] As a concrete example, if a user uses an application to ask, "What recent movies do you recommend?", the server will take into consideration the results of the emotion engine and recommend, "Inception is interesting." Furthermore, if the emotion engine indicates that the user is feeling "anxious," the server will generate an additional response such as, "There are also some lighter movies that are recommended for when you are anxious."

[0910] In this way, this system contributes to providing psychological support and promoting social activities by combining dialogue with the user and emotion analysis. In addition, the generated conversational AI partner provides more personalized and appropriate support.

[0911] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0912] Step 1:

[0913] The user installs the application and answers a questionnaire about basic information and interests.

[0914] Input: Name, age, hobbies, survey answers

[0915] Action: Launch the application and fill out the form.

[0916] Output: Dataset of basic information and survey results

[0917] Step 2:

[0918] The terminal transmits the information entered by the user and the survey results to the server.

[0919] Input: Dataset of basic information and survey results

[0920] What it does: Converts data into JSON format and sends it to the server via an HTTP POST request.

[0921] Output: Data sent to the server

[0922] Step 3:

[0923] The server analyzes the received user information and survey results and generates a profile.

[0924] Input: Submitted basic information and survey result data

[0925] How it works: It uses analytics algorithms to generate a profile of the user, extracting traits such as "I like watching movies, I don't like the outdoors."

[0926] Output: User profile

[0927] Step 4:

[0928] The server uses the generated artificial intelligence model to generate an interactive artificial intelligence partner based on the user profile.

[0929] Input: User profile

[0930] How it works: Calls the generative AI model, passes the profile data as input, and generates the optimal AI partner. For example, "For a user who likes watching movies, generates an AI partner with the same interests."

[0931] Output: Generated AI partner

[0932] Step 5:

[0933] The server interacts with the user using a conversational artificial intelligence partner.

[0934] Input: User questions and statements

[0935] How it works: Your conversational AI partner receives and analyzes your input and generates an appropriate response. For example, to the question, "What movie do you recommend?", it might respond, "Inception is a great movie."

[0936] Output: Dialogue response message

[0937] Step 6:

[0938] The server analyzes the user's input information and dialogue content, and recognizes emotions using an emotion engine.

[0939] Input: What the user says or types

[0940] How it works: The emotion engine is used to parse emotions from user utterances and identify emotional states, for example recognizing "sadness" or "anxiety" from the statement "I'm feeling bad today."

[0941] Output: Recognized emotion data

[0942] Step 7:

[0943] The server generates a response message based on the recognized emotion and sends it to the terminal.

[0944] Input: Recognized emotion data

[0945] Operation: Based on the emotion data, a response appropriate to the user's state is generated and sent to the device. For example, in response to the emotion "I'm tired today," the system responds with "I recommend this movie as a relaxing one."

[0946] Output: Emotion-based response message

[0947] Step 8:

[0948] The terminal displays the response message from the server to the user.

[0949] Input: Sentiment-based response message

[0950] Behavior: Display the received response message in the application's UI. For example, display a message such as "We recommend XX as a relaxing movie."

[0951] Output: The message displayed to the user

[0952] Step 9:

[0953] The server stores the conversation history between the user and the AI ​​partner and the recognized emotion data in a database.

[0954] Input: Conversation history and emotion data

[0955] How it works: The received data is stored in a database and used to improve the quality of future interactions.

[0956] Output: Conversation history and emotion data stored in a database

[0957] Step 10:

[0958] The server periodically analyzes the user's conversation content and emotional data and suggests outgoing events and activities.

[0959] Input: Conversation history and emotion data stored in a database

[0960] How it works: It analyzes the accumulated data and suggests events and activities that will be beneficial to the user. For example, it may notify the user, "It seems like you've been feeling like you need to relax lately. There's a relaxation event in your neighborhood. Why don't you join us?"

[0961] Output: Proposal message

[0962] (Application example 2)

[0963] 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."

[0964] Conversational AI partner systems designed to support people experiencing loneliness primarily aim to provide psychological support to users, but their application to specific tasks is limited. As a result, the security service sector lacks systems that can adequately address mental issues such as staff stress levels and reduced concentration. This can result in reduced work efficiency and safety for security staff. Therefore, a new system is needed that can improve efficiency and safety by monitoring the mental state of security staff in real time and providing appropriate support.

[0965] The identification processing 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 the user to answer a questionnaire about hobbies and preferences, means for the server to receive and analyze the user's input information, means for using a generative AI model to generate an interactive AI partner that matches the user's preferences, means for interacting with the user using the generated AI partner, means for saving the user's conversation history in a database, means for analyzing the emotions of security staff and monitoring their stress levels and concentration in real time, and means for providing appropriate advice based on the analysis results. This makes it possible to constantly understand the mental state of security staff and provide appropriate support in a timely manner.

[0966] A "user terminal" is a device on which a user installs applications and enters basic information and questionnaires.

[0967] A "server" is a system that receives and analyzes information sent by users.

[0968] A "generative artificial intelligence model" is a model that generates an interactive artificial intelligence partner based on a user's profile.

[0969] A "conversational AI partner" is an AI that can converse with a user via text or voice.

[0970] The "database" is a system that stores basic information, survey results, conversation history, and emotional data of users.

[0971] An "emotion engine" is a system that analyzes user input information and dialogue content to recognize emotions.

[0972] "Real-time monitoring" is the process of constantly monitoring the emotional state of security staff and obtaining data at the appropriate time.

[0973] "Providing advice" is a function that provides appropriate instructions and advice to security staff based on the analysis results.

[0974] A "conversation history" is a record of the conversation that took place between a user and an interactive AI partner.

[0975] This invention is a conversational AI partner system for supporting people who feel lonely, particularly in the field of security services, which monitors the mental state of security staff in real time and provides appropriate support. The system mainly consists of a user terminal, a server, a database, and an emotion engine.

[0976] System Configuration Overview

[0977] 1. User Device:

[0978] This is a device on which users install an application and enter basic information and a questionnaire. Through this terminal, security staff can converse with a conversational AI partner via text or voice. For example, this could be a smartphone or a head-mounted display (HMD).

[0979] 2. Server:

[0980] The server is a system that receives and analyzes information sent by users (basic information, survey results, conversation data). It uses a generative AI model to generate a conversational AI partner based on the user's profile. It also performs emotion analysis based on the conversation data to recognize the user's emotional state.

[0981] 3. Database:

[0982] The database is a system that stores basic information, survey results, conversation history, and emotional data of users. This data is used to improve the quality of future interactions.

[0983] 4. Emotion Engine:

[0984] The emotion engine is a system that analyzes user input and dialogue content to recognize their emotions, and adjusts the tone and content of the response message based on the recognized emotions.

[0985] Detailed program processing

[0986] The server uses the speech_recognition library for speech recognition to acquire voice input from security staff. The acquired speech is converted into text, and the text is input into the sentiment analysis model. The sentiment analysis model uses a model built with Keras. The analyzed sentiment data is sent to the server using the requests library.

[0987] The server uses this data to monitor the stress levels and concentration of security staff in real time, and provides appropriate advice based on the results of emotion analysis, such as "Take a 15-minute break and relax" or "You seem anxious. Take a deep breath and relax."

[0988] Specific examples

[0989] 1. Initial settings and questionnaire entry:

[0990] Security staff install the app and enter basic information such as their name, job description, and working hours, then answer a questionnaire about situations that make them feel stressed and how they relax.

[0991] 2. Real-time monitoring and analysis:

[0992] If a security staff member voice-types "I'm feeling a bit tired" while on duty, the emotion engine will recognize this as "fatigue" and provide a response such as "Take a 15-minute break and relax."

[0993] 3. Anomaly detection and alerting:

[0994] AI detects anomalies in surveillance camera footage and alerts security staff, and if the emotion engine identifies a staff member as stressed, the alert is delivered in a calmer, more soothing tone.

[0995] Prompt Sentence Examples

[0996] If a user says, "I've been feeling anxious lately and can't sleep," the emotion engine will recognize "anxiety" and generate a response like this:

[0997] "You seem to be experiencing anxiety. Perhaps you should talk to your doctor about it?"

[0998] In this way, the system of this invention combines dialogue with the user and emotion analysis to contribute to improving the user's mental support and work efficiency. Real-time monitoring and appropriate responses support the mental health of security staff. Furthermore, by providing appropriate responses according to the user's emotional state, more personalized support is realized.

[0999] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1000] Step 1:

[1001] The user installs the application and fills out a questionnaire and basic information.

[1002] Input: Basic information such as name, age, hobbies, and questionnaire results about your personality and interests.

[1003] Processing: The device collects the entered information and sends it to the server, where it is stored in a database.

[1004] Output: User information and survey results sent to the server.

[1005] Step 2:

[1006] The server analyzes the received user information and generates a profile.

[1007] Input: User's basic information and survey results.

[1008] Processing: The server uses the generated AI model to generate a conversational AI partner based on the user's profile.

[1009] Output: The best conversational artificial intelligence partner for the user.

[1010] Step 3:

[1011] The user initiates a dialogue with the generated conversational artificial intelligence partner.

[1012] Input: User text or voice input.

[1013] Processing: The device receives the input and sends it to the server, which uses an emotion engine to analyze the emotion and generate an appropriate response.

[1014] Output: A response message from your conversational AI partner.

[1015] Step 4:

[1016] The server monitors the user's emotional state in real time.

[1017] Input: User interaction and emotion data.

[1018] Processing: The emotion engine analyzes the user's emotions, assessing their stress level and concentration. The emotion data is stored in a database.

[1019] Output: Evaluation of the user's emotional state.

[1020] Step 5:

[1021] Based on the analysis results, the server provides appropriate advice to the user.

[1022] Input: Analysis results of the emotion engine and dialogue history.

[1023] Processing: The server generates an appropriate response message based on the analysis results and sends it to the device. The device then displays or audibly presents the response message to the user.

[1024] Output: Advice or instructions provided to the user.

[1025] Step 6:

[1026] Conversation history and emotion data are stored in a database.

[1027] Input: Conversation history between the user and their conversational AI partner, as well as emotional data.

[1028] Processing: The server stores this data in a database and uses it for future analysis and to improve the quality of the interaction.

[1029] Output: Conversation history and sentiment data stored in a database.

[1030] Prompt Sentence Examples

[1031] If a user says, "I've been feeling anxious lately and can't sleep," the emotion engine will recognize "anxiety" and generate a response like this:

[1032] "You seem to be experiencing anxiety. Perhaps you should talk to your doctor about it?"

[1033] 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.

[1034] 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.

[1035] 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.

[1036] [Third embodiment]

[1037] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1038] 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.

[1039] 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).

[1040] 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.

[1041] 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.

[1042] 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).

[1043] 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.

[1044] 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.

[1045] 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.

[1046] 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.

[1047] 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.

[1048] 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."

[1049] This invention is a system that provides a conversational AI partner (AI Friends, AI Girlfriend / Boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, and a database.

[1050] System Configuration Overview

[1051] 1. User Device:

[1052] It is a device on which users install applications and enter basic information and questionnaires.

[1053] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[1054] 2. Server:

[1055] This is a system that receives and analyzes survey results and conversation data sent by users.

[1056] It uses a generative artificial intelligence model to generate the best AI partner based on the user's profile.

[1057] Based on the content of the conversation, the AI ​​partner generates a response and sends it to the user.

[1058] 3. Database:

[1059] Stores user basic information, survey results, conversation history, etc.

[1060] Detailed program processing

[1061] User registration and survey entry

[1062] Users install and launch the app, then enter basic information such as their name, age, and hobbies, and answer a questionnaire about their personality and interests.

[1063] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[1064] The terminal transmits the input information and the survey results to the server.

[1065] AI Partner Generation

[1066] The server analyzes the received user information and creates a profile based on the user's interests and preferences, then uses a generative AI model to generate an AI partner that best matches the user's profile.

[1067] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[1068] Initiating and sustaining dialogue

[1069] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[1070] The terminal sends this question to the server.

[1071] The server analyzes the question and generates an appropriate response, such as "There's a movie that's been getting a lot of buzz lately. Why don't you check it out?"

[1072] The terminal displays the response from the server to the user.

[1073] Conversation history storage and analysis

[1074] The server stores the conversation history between the user and the AI ​​partner in a database, which can be used to improve the quality of future conversations.

[1075] Example: Based on the conversation history between the user and their AI partner, the next interaction will recommend movies that reflect the user's preferences.

[1076] Promoting social connections

[1077] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a film festival this weekend, why don't you join us?"

[1078] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[1079] Specific examples

[1080] 1. Initial settings and questionnaire entry:

[1081] The user launches the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[1082] 2. AI Partner Generation:

[1083] The server creates a profile for Ichiro Tanaka and generates a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sends an initial message saying, "Hello, Tanaka! There's a good suspense movie out recently."

[1084] 3. Continuing the dialogue:

[1085] Ichiro Tanaka asks, "What recent suspense movie do you recommend?" The server recommends "Inception," and displays it to Ichiro Tanaka.

[1086] 4. Social suggestions:

[1087] The server notifies him, "A suspense film festival is being held at a nearby movie theater. Why don't you come and participate?" Ichiro Tanaka checks the details and decides to participate.

[1088] In this way, the present invention is a system that not only provides psychological support to users but also contributes to promoting social activities.

[1089] The processing flow will be explained below.

[1090] Step 1:

[1091] A user installs the app and enters basic information, such as name "Yamada Taro," age "25," and hobby "reading."

[1092] Step 2:

[1093] The device temporarily stores the user's input information, then displays a questionnaire about the user's hobbies, preferences, and personality, prompting the user to respond.

[1094] Step 3:

[1095] A user answers a survey. For example, the user answers "science fiction" to the question "What is your favorite movie genre?"

[1096] Step 4:

[1097] The terminal collects the user's survey responses and sends them to the server.

[1098] Step 5:

[1099] The server analyzes the received user information and generates a profile. For example, the server might record in the profile that the user "likes science fiction."

[1100] Step 6:

[1101] The server uses the generative AI model to generate a conversational AI partner based on the profile, in this case an AI partner with an interest in science fiction.

[1102] Step 7:

[1103] The server stores the initial profile of the generated AI partner in a database.

[1104] Step 8:

[1105] The server generates an initial message for the conversational AI partner and sends it to the user: "Hello, Yamada-san. I see you like science fiction!"

[1106] Step 9:

[1107] The terminal displays a welcome message from the server to the user.

[1108] Step 10:

[1109] The user initiates a dialogue by typing a question: "What science fiction movie should I watch today?"

[1110] Step 11:

[1111] The terminal sends the user's question to the server.

[1112] Step 12:

[1113] The server analyzes the received question and uses a generative AI model to generate an appropriate response, such as "I recommend the popular movie 'Interstellar'."

[1114] Step 13:

[1115] The server sends the generated response to the terminal.

[1116] Step 14:

[1117] The terminal displays the response message from the server to the user.

[1118] Step 15:

[1119] If the user interaction continues, the user enters more messages which are sent to the server, and the process repeats.

[1120] Step 16:

[1121] The server stores the conversation history with the user in a database to help with future interactions.

[1122] Step 17:

[1123] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a science fiction film festival in your neighborhood. Why don't you go?"

[1124] Step 18:

[1125] The terminal displays the suggestions from the server to the user, allowing the user to check the detailed information.

[1126] In this way, the system of the present invention repeatedly interacts with the user and analyzes data, contributing to providing psychological support to the user and promoting social activities.

[1127] Example 1

[1128] 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."

[1129] Conventional conversational AI systems are limited in the dialogue and suggestions they provide based on the user's personal hobbies and preferences, and are unable to fully alleviate the user's feelings of loneliness and stress. Furthermore, they lack a mechanism for utilizing the user's dialogue history to improve the quality of future conversations. Furthermore, they lack the functionality to encourage users' social activities by suggesting social activities and events based on the user's preferences.

[1130] 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.

[1131] In this invention, the server includes a means for analyzing the user's question, generating a response, and sending it to the terminal, a means for using the conversation history as data for improving the quality of future conversations, and a means for generating an interactive AI partner using a generative AI model based on the user profile. This enables dialogue and suggestions based on the user's individual hobbies and preferences, improving the quality of conversations and promoting social activities.

[1132] "User" refers to an individual who uses the system to enter a questionnaire about basic information and hobbies and preferences and engages in conversation with an interactive AI partner.

[1133] "Terminal" refers to the device on which a user enters basic information and survey results and sends them to the server, as well as the device on which a user can converse with an interactive AI partner.

[1134] "Server" refers to a computer system that receives and analyzes user information, generates a conversational artificial intelligence partner using a generative AI model, analyzes the content of the dialogue with the user to generate a response, and stores the conversation history in a database.

[1135] "Generative AI Model" means an artificial intelligence model used to generate a conversational artificial intelligence partner that is tailored to a user's preferences and interests based on the user's profile.

[1136] "Prompt" refers to the text of an instruction or question input to a generative AI model.

[1137] "Conversational AI partner" refers to an AI agent generated by a generative AI model that engages in text or voice dialogue with a user.

[1138] "Conversation history" refers to a record of all conversations between a user and their conversational AI partner.

[1139] "Database" refers to a data storage system that stores basic information, survey results, and conversation history of users, and retrieves or analyzes information as needed.

[1140] "Extroverted events and activities" refer to public events and group activities that users can participate in that are proposed to promote social activity for users.

[1141] A "user profile" refers to individual characteristic information generated based on information such as a user's hobbies, preferences, personality, and survey results.

[1142] This invention is a system that provides a conversational AI partner (AI Friends, AI Girlfriend / Boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, and a database.

[1143] System Configuration Overview

[1144] 1. User Device:

[1145] It is a device on which users install applications and enter basic information and questionnaires.

[1146] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[1147] Specific examples include smartphones and tablets.

[1148] 2. Server:

[1149] This is a system that receives and analyzes survey results and conversation data sent by users.

[1150] Uses generative artificial intelligence models (e.g., GPT-3) to generate the best AI partner based on the user's profile.

[1151] Based on the content of the conversation, the AI ​​partner generates a response and sends it to the user.

[1152] 3. Database:

[1153] Stores user basic information, survey results, conversation history, etc.

[1154] Use a database management system (e.g., MySQL or PostgreSQL).

[1155] Specific processing of the program

[1156] User registration and survey entry

[1157] Users install and launch the app, then enter basic information such as their name, age, and hobbies, and answer a questionnaire about their personality and interests.

[1158] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[1159] The terminal transmits the input information and the survey results to the server.

[1160] AI Partner Generation

[1161] The server analyzes the received user information and creates a profile based on the user's interests and preferences, then uses a generative AI model to generate an AI partner that best matches the user's profile.

[1162] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[1163] Example prompt: "The user likes watching movies. What recent movies do you recommend?"

[1164] Initiating and sustaining dialogue

[1165] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[1166] The terminal sends this question to the server.

[1167] The server analyzes the question and generates an appropriate response, such as "There's a movie that's been getting a lot of buzz lately. Why don't you check it out?"

[1168] The terminal displays the response from the server to the user.

[1169] Conversation history storage and analysis

[1170] The server stores the conversation history between the user and the AI ​​partner in a database, which can be used to improve the quality of future conversations.

[1171] Example: Based on the conversation history between the user and their AI partner, the next interaction will recommend movies that reflect the user's preferences.

[1172] Promoting social connections

[1173] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a film festival this weekend, why don't you join us?"

[1174] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[1175] Specific examples

[1176] 1. Initial settings and questionnaire entry:

[1177] The user starts the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[1178] 2. AI Partner Generation:

[1179] The server creates a profile for Ichiro Tanaka and generates a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sends an initial message saying, "Hello, Tanaka! There are some good suspense movies out there these days."

[1180] 3. Continuing the dialogue:

[1181] Ichiro Tanaka asks, "What recent suspense movie would you recommend?" The server recommends "Inception is interesting," and displays it to Ichiro Tanaka.

[1182] 4. Social suggestions:

[1183] The server sends a message saying, "A suspense film festival is being held at a nearby movie theater. Why don't you come and participate?" Ichiro Tanaka checks the details and decides to participate.

[1184] In this way, the present invention is a system that not only provides psychological support to users but also contributes to promoting social activities, which is expected to improve the quality of life of users.

[1185] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1186] Step 1:

[1187] The user installs and launches the app. This displays the app's initial setup screen. The user enters basic information such as name, age, and hobbies, and answers a questionnaire about their personality and interests. Specifically, the user fills in the input form with information such as "Name: Ichiro Tanaka," "Age: 30," and "Hobbies: Watching movies."

[1188] Input: Name, age, hobbies, and survey responses about personality and interests.

[1189] Output: User basic information and survey results.

[1190] Step 2:

[1191] The device compiles the entered basic information and survey results and sends them to the server. Specifically, when the user presses the input completion button, the device compiles the information and sends it to the server via an HTTP POST request.

[1192] Input: User basic information and survey results.

[1193] Output: The user information sent to the server.

[1194] Step 3:

[1195] The server analyzes the received user information and generates a user profile. Specifically, the server analyzes the information temporarily stored in the database and generates a profile such as "I like watching movies," "30-year-old male," and "suspense movie lover."

[1196] Input: The user information sent to the server.

[1197] Output: The generated user profile.

[1198] Step 4:

[1199] The server uses a generative AI model to generate a conversational AI partner based on the user profile. Specifically, the server invokes a generative AI model (e.g., GPT-3), inputs the profile as a prompt, and generates the AI ​​partner's personality and initial message.

[1200] Input: User profile, prompt statement.

[1201] Output: The generated conversational artificial intelligence partner.

[1202] Step 5:

[1203] The user initiates a conversation with the AI ​​partner through the application, for example by typing a question into a text box, such as "What movie should I watch today?", and then pressing the send button.

[1204] Input: The user's question.

[1205] Output: The question asked by the user.

[1206] Step 6:

[1207] The device sends the user's question to the server by collecting the contents of the text box and sending it to the server via an HTTP POST request.

[1208] Input: The user's question.

[1209] Output: The question sent to the server.

[1210] Step 7:

[1211] The server analyzes the question and generates an appropriate response. Specifically, the server analyzes the question using natural language processing and uses a generative AI model to generate a response such as "Inception is interesting."

[1212] Input: The user's question.

[1213] Output: The generated response.

[1214] Step 8:

[1215] The terminal displays the response from the server to the user. Specifically, the response text received from the server is displayed on the message screen.

[1216] Input: The generated response.

[1217] Output: The response displayed to the user.

[1218] Step 9:

[1219] The server stores the conversation history between the user and the AI ​​partner in a database. Specifically, the server stores the contents of each message sent and received in the conversation in the database.

[1220] Input: The conversation between the user and their AI partner.

[1221] Output: Conversation history stored in a database.

[1222] Step 10:

[1223] The server uses the conversation history as data to improve the quality of future conversations. Specifically, it analyzes the saved conversation history and learns the user's preference patterns to improve the accuracy of responses in the next dialogue.

[1224] Input: Conversation history stored in a database.

[1225] Output: Data to improve the quality of future conversations.

[1226] Step 11:

[1227] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as generating notifications like "There's a film festival this weekend, why don't you join us?"

[1228] Input: User conversation content.

[1229] Output: Extroverted event and activity suggestions.

[1230] Step 12:

[1231] The user's device will notify the user of this suggestion by displaying a push notification in the app, which can be tapped to display more information.

[1232] Input: Extroverted event and activity suggestions.

[1233] Output: The suggestion notified to the user.

[1234] (Application example 1)

[1235] 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."

[1236] In recent years, the number of people experiencing loneliness has been increasing, raising concerns about the resulting deterioration of mental health. Conversational AI partners have also been attracting attention as a means of alleviating loneliness. However, existing conversational AI partners often fail to adequately respond to the individual interests and preferences of users, particularly in terms of food delivery and meal support. This leaves people experiencing loneliness with a lack of concrete support in their daily lives.

[1237] 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.

[1238] In this invention, the server includes a means for a user to input information about preferences, a means for the server to receive and analyze the user's input information, and a means for generating an interactive AI partner based on the user's preferences using the generated AI model, thereby making it possible to provide food delivery suggestions according to the user's individual preferences.

[1239] "Means for users to input information about preferences" is a function that provides an interface for users to input information such as their hobbies, food preferences, allergies, etc.

[1240] "Means for the server to receive and analyze user input information" refers to the function of the server receiving information sent by the user, analyzing that information, and determining the user's preferences and needs.

[1241] "Means for generating an interactive AI partner based on the user's preferences using the generated AI model" is a function that creates an interactive AI partner that is optimal for the user's preferences and hobbies based on an AI model.

[1242] The "means for conversing with the user using the AI ​​partner" is a function for conversing with the user via text or voice via the generated conversational AI partner.

[1243] The "means for saving the user's conversation history in a storage medium" is a function for recording and saving the content of the conversation between the user and the interactive AI partner so that it can be referenced later.

[1244] "Means for making food delivery-related suggestions" refers to a function that provides meal suggestions and information on the most suitable food delivery service based on the user's preferences and current conversation content.

[1245] "Food ordering assistance" is a function that assists a user in placing an order for the selected meal with an appropriate food delivery service.

[1246] The present invention is a system that provides an interactive artificial intelligence partner (hereinafter referred to as "AI partner") to support users who feel lonely. The main components of this system are a user terminal, a server, and a database.

[1247] 1. User terminal

[1248] A user device is a device on which a user installs the application and enters basic information and questionnaires. It can be a smartphone, tablet, or PC. The application interface on the user device provides a means for the user to converse with the AI ​​partner via text or voice.

[1249] 2. Server

[1250] The server has the following functions:

[1251] Information analysis function: Receives and analyzes survey results and conversation data sent by users.

[1252] Execution of generative AI model: Using a generative artificial intelligence model, we generate the optimal AI partner based on the user's preferences.

[1253] Conversation response generation: Generates appropriate responses based on the user's profile and conversation content and sends them to the user's terminal.

[1254] 3. Database

[1255] The database stores basic information about users, survey results, conversation history, etc. This data will be used to improve the quality of future conversations.

[1256] As a concrete example, take the following steps:

[1257] 1. User registration and questionnaire entry

[1258] Users install and launch the application, enter basic information such as their name, age, and hobbies, and answer a questionnaire about their preferences. For example, "I like cooking" or "I don't like spicy food."

[1259] 2. Creating AI Partners

[1260] The server analyzes the received user information and creates a profile based on the user's preferences. Using the generative AI model, it generates an AI partner that is best suited to the user. For example, a "friendly AI partner who is knowledgeable about Italian cuisine" is generated.

[1261] 3. Initiating and sustaining dialogue

[1262] Through the application, users can interact with the AI ​​partner via text or voice, for example, by asking, "What Italian dish would you recommend for dinner tonight?"

[1263] 4. Food delivery proposals

[1264] The AI ​​partner analyzes the conversation and makes food delivery suggestions based on the user's preferences, such as "Margherita pizza and fruit salad would be good."

[1265] 5. Order assistance

[1266] If a user requests food delivery, the AI ​​partner will send the order to the appropriate delivery service and notify the user.

[1267] The software used is Python, the server uses Flask to provide the API, and the database uses SQLite. This system can be used with cloud infrastructure such as AWS or Google Cloud to improve scalability.

[1268] For example, consider the following prompt:

[1269] "What Italian dishes would you recommend for dinner tonight?"

[1270] "Can you recommend a nearby pizzeria?"

[1271] This will make it possible to enrich the eating habits of users who feel lonely and improve their satisfaction.

[1272] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1273] Step 1: Register and enter basic information

[1274] The terminal provides an interface where the user can install applications and enter basic information (such as name, age, preferences, etc.).

[1275] Input: Basic information and preference survey data entered by the user

[1276] Output: The entered user information is sent to the server.

[1277] Specific operation: The application on the device displays items such as the user's name, age, and food preferences in sequence and prompts them to enter them. Once the input is complete, the data is formatted and sent to the server. For example, the user may enter "I like pasta" and "I don't like spicy food."

[1278] Step 2: Receiving and parsing user information

[1279] The server receives the user information sent from the terminal and analyzes it.

[1280] Input: Basic information and preference data sent from your device

[1281] Output: As a result of the analysis, a user profile is generated and stored in a database.

[1282] Specific operation: The server parses the received data in JSON format and extracts the user's preferences and basic information. Next, a user profile is created based on this information and saved in the database. For example, a profile such as "Ichiro Tanaka, 30 years old, likes pasta, dislikes spicy food" is created.

[1283] Step 3: Generate an AI partner

[1284] The server uses the generative AI model to generate a conversational artificial intelligence partner based on the user's preferences.

[1285] Input: Generated user profile

[1286] Output: AI partner that matches user profile

[1287] Specific operation: Using the generative AI model, the system analyzes the user profile and generates the optimal conversational AI partner. For example, it generates a "friendly AI partner who is knowledgeable about Italian cuisine and is a good fit for Ichiro Tanaka, who loves pasta."

[1288] Step 4: Start a conversation

[1289] The terminal provides an interface through which the user can interact with the generated AI partner.

[1290] Input: Questions and conversations from users

[1291] Output: The conversation as a response from the server

[1292] Specific operation: When a user types "What Italian dish would you recommend for dinner tonight?" into a device, the question is sent to the server. The server analyzes the question, generates the most appropriate response, and sends it to the device. For example, it generates a response such as "Margherita pizza or fruit salad would be good."

[1293] Step 5: Save your conversation history

[1294] The server stores the conversation history between the user and the AI ​​partner in a database.

[1295] Input: Conversation between user and AI partner

[1296] Output: Saved conversation history

[1297] Specific operation: After each conversation, the server records the conversation content in a database so that it can be used in the next conversation. For example, it saves the question "What Italian food do you recommend for dinner tonight?" and the response.

[1298] Step 6: Food delivery proposal

[1299] The server makes food delivery suggestions based on the user's preferences and current conversation.

[1300] Input: User preferences and current conversation

[1301] Output: Food delivery suggestions

[1302] How it works: The generative AI model analyzes the user's preferences and conversation content to suggest the most suitable food delivery service. For example, it might suggest, "There's a recommended pizzeria nearby. Would you like to order from it?"

[1303] Step 7: Order Assistance

[1304] The server assists the user in ordering the selected meal from the appropriate food delivery service.

[1305] Input: Your meal and delivery service selections

[1306] Output: Completed order information

[1307] Specific operation: If the user accepts the offer, the server calls the delivery service API and submits the user's order. It then sends a notification of order completion to the user's device. For example, it may notify the user that "Your order for a Margherita pizza has been submitted. It will arrive in 30 minutes."

[1308] 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.

[1309] This invention is a system that provides a conversational AI partner (AI friend, AI girlfriend / boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, a database, and an emotion engine.

[1310] System Configuration Overview

[1311] 1. User Device:

[1312] It is a device on which users install applications and enter basic information and questionnaires.

[1313] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[1314] 2. Server:

[1315] This is a system that receives and analyzes information sent by users (basic information, survey results, conversation data).

[1316] A generative artificial intelligence model is used to generate an interactive artificial intelligence partner based on the user's profile.

[1317] Emotion analysis is performed based on conversation data to recognize the user's emotional state.

[1318] 3. Database:

[1319] Stores user basic information, survey results, conversation history, and emotional data.

[1320] 4. Emotion Engine:

[1321] This is a system that analyzes the user's input information and dialogue content and recognizes their emotions.

[1322] Adjust the tone and content of your response messages based on the perceived emotion.

[1323] Detailed program processing

[1324] User registration and survey entry

[1325] Users install the app and enter basic information such as their name, age, hobbies, etc. They then fill out a questionnaire about their personality and interests.

[1326] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[1327] The terminal transmits the input information and the survey results to the server.

[1328] AI Partner Generation

[1329] The server analyzes the received user information and generates a profile, then uses a generative AI model to generate an AI partner that best suits the user's profile.

[1330] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[1331] Applying the Emotion Engine

[1332] The server analyzes the user's input and dialogue and recognizes emotions using an emotion engine. For example, if a user inputs "I'm feeling a bit down today," the emotion engine will detect "sadness" or "anxiety."

[1333] Example: When a user types "I'm tired today," the emotion engine recognizes "fatigue" and "stress."

[1334] Initiating and sustaining dialogue

[1335] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[1336] The terminal sends this question to the server.

[1337] The server analyzes the question and generates an appropriate response taking into account the results of the emotion engine, for example, "I recommend this movie as a relaxing one."

[1338] The terminal displays the response from the server to the user.

[1339] Conversation history storage and analysis

[1340] The server stores the conversation history and recognized emotion data between the user and the AI ​​partner in a database, which can be used to improve the quality of future interactions.

[1341] Example: Based on the conversation history and emotional state of the user and their AI partner, advice tailored to the user's emotions is provided in the next interaction.

[1342] Promoting social connections

[1343] The server periodically analyzes the user's conversational and emotional data and suggests outgoing events and activities, such as "You seem to be feeling like you need to relax lately. Why don't you try participating in a relaxing event?"

[1344] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[1345] Specific examples

[1346] 1. Initial settings and questionnaire entry:

[1347] The user launches the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[1348] 2. AI Partner Generation:

[1349] The server created a profile for Ichiro Tanaka and generated a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sent an initial message saying, "Hello, Mr. Tanaka. I see you like suspense movies."

[1350] 3. Dialogue and Sentiment Analysis:

[1351] Ichiro Tanaka asks, "What recent suspense movie would you recommend?" The server recommends "Inception is interesting," and displays this to Ichiro Tanaka. If the user feels "anxiety" based on the emotion engine, the server adds a response such as, "There are also some lighter movies that are recommended for when you're feeling anxious."

[1352] 4. Social suggestions:

[1353] The server notifies the user, "You seem to be feeling stressed lately. There's a relaxation event going on nearby. Why don't you join?" Ichiro Tanaka checks the details and decides to participate.

[1354] In this way, the system of the present invention contributes to providing psychological support and promoting social activities to users by combining dialogue with the user and emotion analysis. It also provides more personalized support by providing appropriate responses according to the user's emotional state.

[1355] The processing flow will be explained below.

[1356] Step 1:

[1357] The user installs the app and enters basic information, such as name "Yamada Taro," age "25," and hobby "reading."

[1358] Step 2:

[1359] The device temporarily stores the information entered by the user, then displays a questionnaire about hobbies, preferences, and personality, prompting the user to answer.

[1360] Step 3:

[1361] A user answers a survey. For example, the user answers "science fiction" to the question "What is your favorite movie genre?"

[1362] Step 4:

[1363] The terminal collects the user's survey responses and sends them to the server.

[1364] Step 5:

[1365] The server analyzes the received user information and generates a profile. For example, the server might record in the profile that the user "likes science fiction."

[1366] Step 6:

[1367] The server uses the generative AI model to generate a conversational AI partner based on the profile, in this case an AI partner with an interest in science fiction.

[1368] Step 7:

[1369] The server stores the initial profile of the generated AI partner in a database.

[1370] Step 8:

[1371] The server generates an initial message for the conversational AI partner and sends it to the user: "Hello, Yamada-san. I see you like science fiction!"

[1372] Step 9:

[1373] The terminal displays a welcome message from the server to the user.

[1374] Step 10:

[1375] The user initiates the interaction by typing the question, "What science fiction movie should I watch today?"

[1376] Step 11:

[1377] The terminal sends the user's question to the server.

[1378] Step 12:

[1379] The server analyzes the received question and uses an emotion engine to recognize the user's emotions. For example, if a user types "I'm feeling down today," the emotion engine will detect "sadness" or "anxiety."

[1380] Step 13:

[1381] The server generates an appropriate response based on the recognition results of the emotion engine, such as "I recommend 'Interstellar' as a relaxing movie."

[1382] Step 14:

[1383] The server generates a response and sends it to the terminal.

[1384] Step 15:

[1385] The terminal displays the response message from the server to the user.

[1386] Step 16:

[1387] If the user confirms the response and wishes to continue the dialogue, the next message is entered and the process is repeated.

[1388] Step 17:

[1389] The server stores the conversation history and recognized emotion data in a database, which can be used to improve the quality of future interactions.

[1390] Step 18:

[1391] The server periodically analyzes the user's conversational content and emotional data and suggests outward-looking events and activities. For example, it may notify the user, "It seems like you've been feeling like you need to relax lately. Why don't you try participating in a relaxing event?"

[1392] Step 19:

[1393] The device will display this proposal to the user and provide specific participation methods and detailed information.

[1394] In this way, the system of the present invention repeatedly engages in dialogue with the user and analyzes their emotions, contributing to providing psychological support to the user and promoting social activities.

[1395] Example 2

[1396] 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."

[1397] In modern society, the number of people experiencing loneliness is increasing, making it necessary to provide emotional support and social connections. The present invention aims to alleviate this sense of loneliness and promote emotional stability and social participation by providing users with personalized support. However, conventional systems have difficulty providing appropriate responses based on the user's emotional state, and their ability to analyze the user's emotions through continuous dialogue has been insufficient.

[1398] 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.

[1399] In this invention, the server includes means for analyzing the user's input information and dialogue content and recognizing emotions with an emotion engine, means for generating a response message based on the recognized emotion and sending it to the terminal, and means for saving the user's conversation history and emotion data in a database, thereby enabling the provision of appropriate responses according to the user's emotional state and personalized support based on the emotion analysis results.

[1400] "Users" refer to people who use the system, who install the application, and who input information and answer questionnaires.

[1401] A "terminal" is a device that allows a user to input information and send it to a server, and includes electronic devices such as smartphones, tablets, and personal computers.

[1402] The "server" is a central processing unit that analyzes user input information, generates an AI partner, and recognizes emotions using an emotion engine.

[1403] "Generative AI model" refers to an algorithm or model for generating an optimal conversational AI partner based on a user's profile.

[1404] A "conversational artificial intelligence partner" is an artificial intelligence-based application or service that interacts with and assists users.

[1405] An "emotion engine" refers to a system or algorithm that analyzes user input information and dialogue content to recognize emotions.

[1406] The "database" is a system for storing basic information, survey results, conversation history, and emotional data of users.

[1407] "Conversation history" refers to a record of interactions between a user and their conversational AI partner, and is data used to improve the quality of future interactions.

[1408] This invention is a system that provides conversational AI partners (AI Friends, AI Girlfriends / Boyfriends) to support people who feel lonely. The main components of this system are a user terminal, a server, a database, and an emotion engine.

[1409] First, a user installs an application on a user device such as a smartphone or tablet. Then, the user launches the application, enters basic information such as their name, age, and hobbies, and then answers a questionnaire about their hobbies and interests. For example, a user might enter "I like watching movies" or "I don't like the outdoors." This information plays an important role in each process described below.

[1410] The device automatically sends the basic information and survey results entered by the user to the server. This involves converting the data format and sending it via API. Specifically, the device converts the entered data into JSON format and sends it to the server via an HTTP POST request.

[1411] The server analyzes the received user information and generates a profile. This profile includes the user's basic information, hobbies, interests, and survey results. It then uses a generative AI model to generate a conversational AI partner based on the profile. In this case, the server runs an algorithm such as "for a user who likes watching movies, to generate an AI partner with a common interest."

[1412] Next, the server analyzes the user's input information and dialogue content, and recognizes emotions using an emotion engine. For example, if a user inputs "I'm feeling a little down today," the emotion engine has the ability to detect "sadness" or "anxiety." Based on the recognized emotion, the server generates a response message and sends it to the user's device. For example, if a user inputs "I'm tired today," the server generates a response message such as "I recommend XX as a relaxing movie."

[1413] The user device receives the response message sent from the server and displays it to the user, allowing the user to interact with the AI ​​partner via text or voice.

[1414] Furthermore, the server stores the conversation history and recognized emotional data between the user and the AI ​​partner in a database. This data is used to improve the quality of future interactions. The system also periodically analyzes the conversation and emotional data to suggest extroverted events and activities to the user. For example, it might suggest, "You seem to be feeling stressed lately. Why not join a relaxation event nearby?"

[1415] As a concrete example, if a user uses an application to ask, "What recent movies do you recommend?", the server will take into consideration the results of the emotion engine and recommend, "Inception is interesting." Furthermore, if the emotion engine indicates that the user is feeling "anxious," the server will generate an additional response such as, "There are also some lighter movies that are recommended for when you are anxious."

[1416] In this way, this system contributes to providing psychological support and promoting social activities by combining dialogue with the user and emotion analysis. In addition, the generated conversational AI partner provides more personalized and appropriate support.

[1417] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1418] Step 1:

[1419] The user installs the application and answers a questionnaire about basic information and interests.

[1420] Input: Name, age, hobbies, survey answers

[1421] Action: Launch the application and fill out the form.

[1422] Output: Dataset of basic information and survey results

[1423] Step 2:

[1424] The terminal transmits the information entered by the user and the survey results to the server.

[1425] Input: Dataset of basic information and survey results

[1426] What it does: Converts data into JSON format and sends it to the server via an HTTP POST request.

[1427] Output: Data sent to the server

[1428] Step 3:

[1429] The server analyzes the received user information and survey results and generates a profile.

[1430] Input: Submitted basic information and survey result data

[1431] How it works: It uses analytics algorithms to generate a profile of the user, extracting traits such as "I like watching movies, I don't like the outdoors."

[1432] Output: User profile

[1433] Step 4:

[1434] The server uses the generated artificial intelligence model to generate an interactive artificial intelligence partner based on the user profile.

[1435] Input: User profile

[1436] How it works: Calls the generative AI model, passes the profile data as input, and generates the optimal AI partner. For example, "For a user who likes watching movies, generates an AI partner with the same interests."

[1437] Output: Generated AI partner

[1438] Step 5:

[1439] The server interacts with the user using a conversational artificial intelligence partner.

[1440] Input: User questions and statements

[1441] How it works: Your conversational AI partner receives and analyzes your input and generates an appropriate response. For example, to the question, "What movie do you recommend?", it might respond, "Inception is a great movie."

[1442] Output: Dialogue response message

[1443] Step 6:

[1444] The server analyzes the user's input information and dialogue content, and recognizes emotions using an emotion engine.

[1445] Input: What the user says or types

[1446] How it works: The emotion engine is used to parse emotions from user utterances and identify emotional states, for example recognizing "sadness" or "anxiety" from the statement "I'm feeling bad today."

[1447] Output: Recognized emotion data

[1448] Step 7:

[1449] The server generates a response message based on the recognized emotion and sends it to the terminal.

[1450] Input: Recognized emotion data

[1451] Operation: Based on the emotion data, a response appropriate to the user's state is generated and sent to the device. For example, in response to the emotion "I'm tired today," the system responds with "I recommend this movie as a relaxing one."

[1452] Output: Emotion-based response message

[1453] Step 8:

[1454] The terminal displays the response message from the server to the user.

[1455] Input: Sentiment-based response message

[1456] Behavior: Display the received response message in the application's UI. For example, display a message such as "We recommend XX as a relaxing movie."

[1457] Output: The message displayed to the user

[1458] Step 9:

[1459] The server stores the conversation history between the user and the AI ​​partner and the recognized emotion data in a database.

[1460] Input: Conversation history and emotion data

[1461] How it works: The received data is stored in a database and used to improve the quality of future interactions.

[1462] Output: Conversation history and emotion data stored in a database

[1463] Step 10:

[1464] The server periodically analyzes the user's conversation content and emotional data and suggests outgoing events and activities.

[1465] Input: Conversation history and emotion data stored in a database

[1466] How it works: It analyzes the accumulated data and suggests events and activities that will be beneficial to the user. For example, it may notify the user, "It seems like you've been feeling like you need to relax lately. There's a relaxation event in your neighborhood. Why don't you join us?"

[1467] Output: Proposal message

[1468] (Application example 2)

[1469] 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."

[1470] Conversational AI partner systems designed to support people experiencing loneliness primarily aim to provide psychological support to users, but their application to specific tasks is limited. As a result, the security service sector lacks systems that can adequately address mental issues such as staff stress levels and reduced concentration. This can result in reduced work efficiency and safety for security staff. Therefore, a new system is needed that can improve efficiency and safety by monitoring the mental state of security staff in real time and providing appropriate support.

[1471] The identification processing 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 the user to answer a questionnaire about hobbies and preferences, means for the server to receive and analyze the user's input information, means for using a generative AI model to generate an interactive AI partner that matches the user's preferences, means for interacting with the user using the generated AI partner, means for saving the user's conversation history in a database, means for analyzing the emotions of security staff and monitoring their stress levels and concentration in real time, and means for providing appropriate advice based on the analysis results. This makes it possible to constantly understand the mental state of security staff and provide appropriate support in a timely manner.

[1472] A "user terminal" is a device on which a user installs applications and enters basic information and questionnaires.

[1473] A "server" is a system that receives and analyzes information sent by users.

[1474] A "generative artificial intelligence model" is a model that generates an interactive artificial intelligence partner based on a user's profile.

[1475] A "conversational AI partner" is an AI that can converse with a user via text or voice.

[1476] The "database" is a system that stores basic information, survey results, conversation history, and emotional data of users.

[1477] An "emotion engine" is a system that analyzes user input information and dialogue content to recognize emotions.

[1478] "Real-time monitoring" is the process of constantly monitoring the emotional state of security staff and obtaining data at the appropriate time.

[1479] "Providing advice" is a function that provides appropriate instructions and advice to security staff based on the analysis results.

[1480] A "conversation history" is a record of the conversation that took place between a user and an interactive AI partner.

[1481] This invention is a conversational AI partner system for supporting people who feel lonely, particularly in the field of security services, which monitors the mental state of security staff in real time and provides appropriate support. The system mainly consists of a user terminal, a server, a database, and an emotion engine.

[1482] System Configuration Overview

[1483] 1. User Device:

[1484] This is a device on which users install an application and enter basic information and a questionnaire. Through this terminal, security staff can converse with a conversational AI partner via text or voice. For example, this could be a smartphone or a head-mounted display (HMD).

[1485] 2. Server:

[1486] The server is a system that receives and analyzes information sent by users (basic information, survey results, conversation data). It uses a generative AI model to generate a conversational AI partner based on the user's profile. It also performs emotion analysis based on the conversation data to recognize the user's emotional state.

[1487] 3. Database:

[1488] The database is a system that stores basic information, survey results, conversation history, and emotional data of users. This data is used to improve the quality of future interactions.

[1489] 4. Emotion Engine:

[1490] The emotion engine is a system that analyzes user input and dialogue content to recognize their emotions, and adjusts the tone and content of the response message based on the recognized emotions.

[1491] Detailed program processing

[1492] The server uses the speech_recognition library for speech recognition to acquire voice input from security staff. The acquired speech is converted into text, and the text is input into the sentiment analysis model. The sentiment analysis model uses a model built with Keras. The analyzed sentiment data is sent to the server using the requests library.

[1493] The server uses this data to monitor the stress levels and concentration of security staff in real time, and provides appropriate advice based on the results of emotion analysis, such as "Take a 15-minute break and relax" or "You seem anxious. Take a deep breath and relax."

[1494] Specific examples

[1495] 1. Initial settings and questionnaire entry:

[1496] Security staff install the app and enter basic information such as their name, job description, and working hours, then answer a questionnaire about situations that make them feel stressed and how they relax.

[1497] 2. Real-time monitoring and analysis:

[1498] If a security staff member voice-types "I'm feeling a bit tired" while on duty, the emotion engine will recognize this as "fatigue" and provide a response such as "Take a 15-minute break and relax."

[1499] 3. Anomaly detection and alerting:

[1500] AI detects anomalies in surveillance camera footage and alerts security staff, and if the emotion engine identifies a staff member as stressed, the alert is delivered in a calmer, more soothing tone.

[1501] Prompt Sentence Examples

[1502] If a user says, "I've been feeling anxious lately and can't sleep," the emotion engine will recognize "anxiety" and generate a response like this:

[1503] "You seem to be experiencing anxiety. Perhaps you should talk to your doctor about it?"

[1504] In this way, the system of this invention combines dialogue with the user and emotion analysis to contribute to improving the user's mental support and work efficiency. Real-time monitoring and appropriate responses support the mental health of security staff. Furthermore, by providing appropriate responses according to the user's emotional state, more personalized support is realized.

[1505] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1506] Step 1:

[1507] The user installs the application and fills out a questionnaire and basic information.

[1508] Input: Basic information such as name, age, hobbies, and questionnaire results about your personality and interests.

[1509] Processing: The device collects the entered information and sends it to the server, where it is stored in a database.

[1510] Output: User information and survey results sent to the server.

[1511] Step 2:

[1512] The server analyzes the received user information and generates a profile.

[1513] Input: User's basic information and survey results.

[1514] Processing: The server uses the generated AI model to generate a conversational AI partner based on the user's profile.

[1515] Output: The best conversational artificial intelligence partner for the user.

[1516] Step 3:

[1517] The user initiates a dialogue with the generated conversational artificial intelligence partner.

[1518] Input: User text or voice input.

[1519] Processing: The device receives the input and sends it to the server, which uses an emotion engine to analyze the emotion and generate an appropriate response.

[1520] Output: A response message from your conversational AI partner.

[1521] Step 4:

[1522] The server monitors the user's emotional state in real time.

[1523] Input: User interaction and emotion data.

[1524] Processing: The emotion engine analyzes the user's emotions, assessing their stress level and concentration. The emotion data is stored in a database.

[1525] Output: Evaluation of the user's emotional state.

[1526] Step 5:

[1527] Based on the analysis results, the server provides appropriate advice to the user.

[1528] Input: Analysis results of the emotion engine and dialogue history.

[1529] Processing: The server generates an appropriate response message based on the analysis results and sends it to the device. The device then displays or audibly presents the response message to the user.

[1530] Output: Advice or instructions provided to the user.

[1531] Step 6:

[1532] Conversation history and emotion data are stored in a database.

[1533] Input: Conversation history between the user and their conversational AI partner, as well as emotional data.

[1534] Processing: The server stores this data in a database and uses it for future analysis and to improve the quality of the interaction.

[1535] Output: Conversation history and sentiment data stored in a database.

[1536] Prompt Sentence Examples

[1537] If a user says, "I've been feeling anxious lately and can't sleep," the emotion engine will recognize "anxiety" and generate a response like this:

[1538] "You seem to be experiencing anxiety. Perhaps you should talk to your doctor about it?"

[1539] 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.

[1540] 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.

[1541] 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.

[1542] [Fourth embodiment]

[1543] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1544] 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.

[1545] 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).

[1546] 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.

[1547] 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.

[1548] 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).

[1549] 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.

[1550] 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.

[1551] 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.

[1552] 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.

[1553] 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.

[1554] 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.

[1555] 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."

[1556] This invention is a system that provides a conversational AI partner (AI Friends, AI Girlfriend / Boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, and a database.

[1557] System Configuration Overview

[1558] 1. User Device:

[1559] It is a device on which users install applications and enter basic information and questionnaires.

[1560] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[1561] 2. Server:

[1562] This is a system that receives and analyzes survey results and conversation data sent by users.

[1563] It uses a generative artificial intelligence model to generate the best AI partner based on the user's profile.

[1564] Based on the content of the conversation, the AI ​​partner generates a response and sends it to the user.

[1565] 3. Database:

[1566] Stores user basic information, survey results, conversation history, etc.

[1567] Detailed program processing

[1568] User registration and survey entry

[1569] Users install and launch the app, then enter basic information such as their name, age, and hobbies, and answer a questionnaire about their personality and interests.

[1570] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[1571] The terminal transmits the input information and the survey results to the server.

[1572] AI Partner Generation

[1573] The server analyzes the received user information and creates a profile based on the user's interests and preferences, then uses a generative AI model to generate an AI partner that best matches the user's profile.

[1574] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[1575] Initiating and sustaining dialogue

[1576] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[1577] The terminal sends this question to the server.

[1578] The server analyzes the question and generates an appropriate response, such as "There's a movie that's been getting a lot of buzz lately. Why don't you check it out?"

[1579] The terminal displays the response from the server to the user.

[1580] Conversation history storage and analysis

[1581] The server stores the conversation history between the user and the AI ​​partner in a database, which can be used to improve the quality of future conversations.

[1582] Example: Based on the conversation history between the user and their AI partner, the next interaction will recommend movies that reflect the user's preferences.

[1583] Promoting social connections

[1584] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a film festival this weekend, why don't you join us?"

[1585] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[1586] Specific examples

[1587] 1. Initial settings and questionnaire entry:

[1588] The user launches the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[1589] 2. AI Partner Generation:

[1590] The server creates a profile for Ichiro Tanaka and generates a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sends an initial message saying, "Hello, Tanaka! There's a good suspense movie out recently."

[1591] 3. Continuing the dialogue:

[1592] Ichiro Tanaka asks, "What recent suspense movie do you recommend?" The server recommends "Inception," and displays it to Ichiro Tanaka.

[1593] 4. Social suggestions:

[1594] The server notifies him, "A suspense film festival is being held at a nearby movie theater. Why don't you come and participate?" Ichiro Tanaka checks the details and decides to participate.

[1595] In this way, the present invention is a system that not only provides psychological support to users but also contributes to promoting social activities.

[1596] The processing flow will be explained below.

[1597] Step 1:

[1598] A user installs the app and enters basic information, such as name "Yamada Taro," age "25," and hobby "reading."

[1599] Step 2:

[1600] The device temporarily stores the user's input information, then displays a questionnaire about the user's hobbies, preferences, and personality, prompting the user to respond.

[1601] Step 3:

[1602] A user answers a survey. For example, the user answers "science fiction" to the question "What is your favorite movie genre?"

[1603] Step 4:

[1604] The terminal collects the user's survey responses and sends them to the server.

[1605] Step 5:

[1606] The server analyzes the received user information and generates a profile. For example, the server might record in the profile that the user "likes science fiction."

[1607] Step 6:

[1608] The server uses the generative AI model to generate a conversational AI partner based on the profile, in this case an AI partner with an interest in science fiction.

[1609] Step 7:

[1610] The server stores the initial profile of the generated AI partner in a database.

[1611] Step 8:

[1612] The server generates an initial message for the conversational AI partner and sends it to the user: "Hello, Yamada-san. I see you like science fiction!"

[1613] Step 9:

[1614] The terminal displays a welcome message from the server to the user.

[1615] Step 10:

[1616] The user initiates a dialogue by typing a question: "What science fiction movie should I watch today?"

[1617] Step 11:

[1618] The terminal sends the user's question to the server.

[1619] Step 12:

[1620] The server analyzes the received question and uses a generative AI model to generate an appropriate response, such as "I recommend the popular movie 'Interstellar'."

[1621] Step 13:

[1622] The server sends the generated response to the terminal.

[1623] Step 14:

[1624] The terminal displays the response message from the server to the user.

[1625] Step 15:

[1626] If the user interaction continues, the user enters more messages which are sent to the server, and the process repeats.

[1627] Step 16:

[1628] The server stores the conversation history with the user in a database to help with future interactions.

[1629] Step 17:

[1630] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a science fiction film festival in your neighborhood. Why don't you go?"

[1631] Step 18:

[1632] The terminal displays the suggestions from the server to the user, allowing the user to check the detailed information.

[1633] In this way, the system of the present invention repeatedly interacts with the user and analyzes data, contributing to providing psychological support to the user and promoting social activities.

[1634] Example 1

[1635] 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."

[1636] Conventional conversational AI systems are limited in the dialogue and suggestions they provide based on the user's personal hobbies and preferences, and are unable to fully alleviate the user's feelings of loneliness and stress. Furthermore, they lack a mechanism for utilizing the user's dialogue history to improve the quality of future conversations. Furthermore, they lack the functionality to encourage users' social activities by suggesting social activities and events based on the user's preferences.

[1637] 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.

[1638] In this invention, the server includes a means for analyzing the user's question, generating a response, and sending it to the terminal, a means for using the conversation history as data for improving the quality of future conversations, and a means for generating an interactive AI partner using a generative AI model based on the user profile. This enables dialogue and suggestions based on the user's individual hobbies and preferences, improving the quality of conversations and promoting social activities.

[1639] "User" refers to an individual who uses the system to enter a questionnaire about basic information and hobbies and preferences and engages in conversation with an interactive AI partner.

[1640] "Terminal" refers to the device on which a user enters basic information and survey results and sends them to the server, as well as the device on which a user can converse with an interactive AI partner.

[1641] "Server" refers to a computer system that receives and analyzes user information, generates a conversational artificial intelligence partner using a generative AI model, analyzes the content of the dialogue with the user to generate a response, and stores the conversation history in a database.

[1642] "Generative AI Model" means an artificial intelligence model used to generate a conversational artificial intelligence partner that is tailored to a user's preferences and interests based on the user's profile.

[1643] "Prompt" refers to the text of an instruction or question input to a generative AI model.

[1644] "Conversational AI partner" refers to an AI agent generated by a generative AI model that engages in text or voice dialogue with a user.

[1645] "Conversation history" refers to a record of all conversations between a user and their conversational AI partner.

[1646] "Database" refers to a data storage system that stores basic information, survey results, and conversation history of users, and retrieves or analyzes information as needed.

[1647] "Extroverted events and activities" refer to public events and group activities that users can participate in that are proposed to promote social activity for users.

[1648] A "user profile" refers to individual characteristic information generated based on information such as a user's hobbies, preferences, personality, and survey results.

[1649] This invention is a system that provides a conversational AI partner (AI Friends, AI Girlfriend / Boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, and a database.

[1650] System Configuration Overview

[1651] 1. User Device:

[1652] It is a device on which users install applications and enter basic information and questionnaires.

[1653] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[1654] Specific examples include smartphones and tablets.

[1655] 2. Server:

[1656] This is a system that receives and analyzes survey results and conversation data sent by users.

[1657] Uses generative artificial intelligence models (e.g., GPT-3) to generate the best AI partner based on the user's profile.

[1658] Based on the content of the conversation, the AI ​​partner generates a response and sends it to the user.

[1659] 3. Database:

[1660] Stores user basic information, survey results, conversation history, etc.

[1661] Use a database management system (e.g., MySQL or PostgreSQL).

[1662] Specific processing of the program

[1663] User registration and survey entry

[1664] Users install and launch the app, then enter basic information such as their name, age, and hobbies, and answer a questionnaire about their personality and interests.

[1665] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[1666] The terminal transmits the input information and the survey results to the server.

[1667] AI Partner Generation

[1668] The server analyzes the received user information and creates a profile based on the user's interests and preferences, then uses a generative AI model to generate an AI partner that best matches the user's profile.

[1669] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[1670] Example prompt: "The user likes watching movies. What recent movies do you recommend?"

[1671] Initiating and sustaining dialogue

[1672] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[1673] The terminal sends this question to the server.

[1674] The server analyzes the question and generates an appropriate response, such as "There's a movie that's been getting a lot of buzz lately. Why don't you check it out?"

[1675] The terminal displays the response from the server to the user.

[1676] Conversation history storage and analysis

[1677] The server stores the conversation history between the user and the AI ​​partner in a database, which can be used to improve the quality of future conversations.

[1678] Example: Based on the conversation history between the user and their AI partner, the next interaction will recommend movies that reflect the user's preferences.

[1679] Promoting social connections

[1680] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as "There's a film festival this weekend, why don't you join us?"

[1681] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[1682] Specific examples

[1683] 1. Initial settings and questionnaire entry:

[1684] The user starts the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[1685] 2. AI Partner Generation:

[1686] The server creates a profile for Ichiro Tanaka and generates a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sends an initial message saying, "Hello, Tanaka! There are some good suspense movies out there these days."

[1687] 3. Continuing the dialogue:

[1688] Ichiro Tanaka asks, "What recent suspense movie would you recommend?" The server recommends "Inception is interesting," and displays it to Ichiro Tanaka.

[1689] 4. Social suggestions:

[1690] The server sends a message saying, "A suspense film festival is being held at a nearby movie theater. Why don't you come and participate?" Ichiro Tanaka checks the details and decides to participate.

[1691] In this way, the present invention is a system that not only provides psychological support to users but also contributes to promoting social activities, which is expected to improve the quality of life of users.

[1692] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1693] Step 1:

[1694] The user installs and launches the app. This displays the app's initial setup screen. The user enters basic information such as name, age, and hobbies, and answers a questionnaire about their personality and interests. Specifically, the user fills in the input form with information such as "Name: Ichiro Tanaka," "Age: 30," and "Hobbies: Watching movies."

[1695] Input: Name, age, hobbies, and survey responses about personality and interests.

[1696] Output: User basic information and survey results.

[1697] Step 2:

[1698] The device compiles the entered basic information and survey results and sends them to the server. Specifically, when the user presses the input completion button, the device compiles the information and sends it to the server via an HTTP POST request.

[1699] Input: User basic information and survey results.

[1700] Output: The user information sent to the server.

[1701] Step 3:

[1702] The server analyzes the received user information and generates a user profile. Specifically, the server analyzes the information temporarily stored in the database and generates a profile such as "I like watching movies," "30-year-old male," and "suspense movie lover."

[1703] Input: The user information sent to the server.

[1704] Output: The generated user profile.

[1705] Step 4:

[1706] The server uses a generative AI model to generate a conversational AI partner based on the user profile. Specifically, the server invokes a generative AI model (e.g., GPT-3), inputs the profile as a prompt, and generates the AI ​​partner's personality and initial message.

[1707] Input: User profile, prompt statement.

[1708] Output: The generated conversational artificial intelligence partner.

[1709] Step 5:

[1710] The user initiates a conversation with the AI ​​partner through the application, for example by typing a question into a text box, such as "What movie should I watch today?", and then pressing the send button.

[1711] Input: The user's question.

[1712] Output: The question asked by the user.

[1713] Step 6:

[1714] The device sends the user's question to the server by collecting the contents of the text box and sending it to the server via an HTTP POST request.

[1715] Input: The user's question.

[1716] Output: The question sent to the server.

[1717] Step 7:

[1718] The server analyzes the question and generates an appropriate response. Specifically, the server analyzes the question using natural language processing and uses a generative AI model to generate a response such as "Inception is interesting."

[1719] Input: The user's question.

[1720] Output: The generated response.

[1721] Step 8:

[1722] The terminal displays the response from the server to the user. Specifically, the response text received from the server is displayed on the message screen.

[1723] Input: The generated response.

[1724] Output: The response displayed to the user.

[1725] Step 9:

[1726] The server stores the conversation history between the user and the AI ​​partner in a database. Specifically, the server stores the contents of each message sent and received in the conversation in the database.

[1727] Input: The conversation between the user and their AI partner.

[1728] Output: Conversation history stored in a database.

[1729] Step 10:

[1730] The server uses the conversation history as data to improve the quality of future conversations. Specifically, it analyzes the saved conversation history and learns the user's preference patterns to improve the accuracy of responses in the next dialogue.

[1731] Input: Conversation history stored in a database.

[1732] Output: Data to improve the quality of future conversations.

[1733] Step 11:

[1734] The server periodically analyzes the user's conversations and suggests outward-looking events and activities, such as generating notifications like "There's a film festival this weekend, why don't you join us?"

[1735] Input: User conversation content.

[1736] Output: Extroverted event and activity suggestions.

[1737] Step 12:

[1738] The user's device will notify the user of this suggestion by displaying a push notification in the app, which can be tapped to display more information.

[1739] Input: Extroverted event and activity suggestions.

[1740] Output: The suggestion notified to the user.

[1741] (Application example 1)

[1742] 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."

[1743] In recent years, the number of people experiencing loneliness has been increasing, raising concerns about the resulting deterioration of mental health. Conversational AI partners have also been attracting attention as a means of alleviating loneliness. However, existing conversational AI partners often fail to adequately respond to the individual interests and preferences of users, particularly in terms of food delivery and meal support. This leaves people experiencing loneliness with a lack of concrete support in their daily lives.

[1744] 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.

[1745] In this invention, the server includes a means for a user to input information about preferences, a means for the server to receive and analyze the user's input information, and a means for generating an interactive AI partner based on the user's preferences using the generated AI model, thereby making it possible to provide food delivery suggestions according to the user's individual preferences.

[1746] "Means for users to input information about preferences" is a function that provides an interface for users to input information such as their hobbies, food preferences, allergies, etc.

[1747] "Means for the server to receive and analyze user input information" refers to the function of the server receiving information sent by the user, analyzing that information, and determining the user's preferences and needs.

[1748] "Means for generating an interactive AI partner based on the user's preferences using the generated AI model" is a function that creates an interactive AI partner that is optimal for the user's preferences and hobbies based on an AI model.

[1749] The "means for conversing with the user using the AI ​​partner" is a function for conversing with the user via text or voice via the generated conversational AI partner.

[1750] The "means for saving the user's conversation history in a storage medium" is a function for recording and saving the content of the conversation between the user and the interactive AI partner so that it can be referenced later.

[1751] "Means for making food delivery-related suggestions" refers to a function that provides meal suggestions and information on the most suitable food delivery service based on the user's preferences and current conversation content.

[1752] "Food ordering assistance" is a function that assists a user in placing an order for the selected meal with an appropriate food delivery service.

[1753] The present invention is a system that provides an interactive artificial intelligence partner (hereinafter referred to as "AI partner") to support users who feel lonely. The main components of this system are a user terminal, a server, and a database.

[1754] 1. User terminal

[1755] A user device is a device on which a user installs the application and enters basic information and questionnaires. It can be a smartphone, tablet, or PC. The application interface on the user device provides a means for the user to converse with the AI ​​partner via text or voice.

[1756] 2. Server

[1757] The server has the following functions:

[1758] Information analysis function: Receives and analyzes survey results and conversation data sent by users.

[1759] Execution of generative AI model: Using a generative artificial intelligence model, we generate the optimal AI partner based on the user's preferences.

[1760] Conversation response generation: Generates appropriate responses based on the user's profile and conversation content and sends them to the user's terminal.

[1761] 3. Database

[1762] The database stores basic information about users, survey results, conversation history, etc. This data will be used to improve the quality of future conversations.

[1763] As a concrete example, take the following steps:

[1764] 1. User registration and questionnaire entry

[1765] Users install and launch the application, enter basic information such as their name, age, and hobbies, and answer a questionnaire about their preferences. For example, "I like cooking" or "I don't like spicy food."

[1766] 2. Creating AI Partners

[1767] The server analyzes the received user information and creates a profile based on the user's preferences. Using the generative AI model, it generates an AI partner that is best suited to the user. For example, a "friendly AI partner who is knowledgeable about Italian cuisine" is generated.

[1768] 3. Initiating and sustaining dialogue

[1769] Through the application, users can interact with the AI ​​partner via text or voice, for example, by asking, "What Italian dish would you recommend for dinner tonight?"

[1770] 4. Food delivery proposals

[1771] The AI ​​partner analyzes the conversation and makes food delivery suggestions based on the user's preferences, such as "Margherita pizza and fruit salad would be good."

[1772] 5. Order assistance

[1773] If a user requests food delivery, the AI ​​partner will send the order to the appropriate delivery service and notify the user.

[1774] The software used is Python, the server uses Flask to provide the API, and the database uses SQLite. This system can be used with cloud infrastructure such as AWS or Google Cloud to improve scalability.

[1775] For example, consider the following prompt:

[1776] "What Italian dishes would you recommend for dinner tonight?"

[1777] "Can you recommend a nearby pizzeria?"

[1778] This will make it possible to enrich the eating habits of users who feel lonely and improve their satisfaction.

[1779] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1780] Step 1: Register and enter basic information

[1781] The terminal provides an interface where the user can install applications and enter basic information (such as name, age, preferences, etc.).

[1782] Input: Basic information and preference survey data entered by the user

[1783] Output: The entered user information is sent to the server.

[1784] Specific operation: The application on the device displays items such as the user's name, age, and food preferences in sequence and prompts them to enter them. Once the input is complete, the data is formatted and sent to the server. For example, the user may enter "I like pasta" and "I don't like spicy food."

[1785] Step 2: Receiving and parsing user information

[1786] The server receives the user information sent from the terminal and analyzes it.

[1787] Input: Basic information and preference data sent from your device

[1788] Output: As a result of the analysis, a user profile is generated and stored in a database.

[1789] Specific operation: The server parses the received data in JSON format and extracts the user's preferences and basic information. Next, a user profile is created based on this information and saved in the database. For example, a profile such as "Ichiro Tanaka, 30 years old, likes pasta, dislikes spicy food" is created.

[1790] Step 3: Generate an AI partner

[1791] The server uses the generative AI model to generate a conversational artificial intelligence partner based on the user's preferences.

[1792] Input: Generated user profile

[1793] Output: AI partner that matches user profile

[1794] Specific operation: Using the generative AI model, the system analyzes the user profile and generates the optimal conversational AI partner. For example, it generates a "friendly AI partner who is knowledgeable about Italian cuisine and is a good fit for Ichiro Tanaka, who loves pasta."

[1795] Step 4: Start a conversation

[1796] The terminal provides an interface through which the user can interact with the generated AI partner.

[1797] Input: Questions and conversations from users

[1798] Output: The conversation as a response from the server

[1799] Specific operation: When a user types "What Italian dish would you recommend for dinner tonight?" into a device, the question is sent to the server. The server analyzes the question, generates the most appropriate response, and sends it to the device. For example, it generates a response such as "Margherita pizza or fruit salad would be good."

[1800] Step 5: Save your conversation history

[1801] The server stores the conversation history between the user and the AI ​​partner in a database.

[1802] Input: Conversation between user and AI partner

[1803] Output: Saved conversation history

[1804] Specific operation: After each conversation, the server records the conversation content in a database so that it can be used in the next conversation. For example, it saves the question "What Italian food do you recommend for dinner tonight?" and the response.

[1805] Step 6: Food delivery proposal

[1806] The server makes food delivery suggestions based on the user's preferences and current conversation.

[1807] Input: User preferences and current conversation

[1808] Output: Food delivery suggestions

[1809] How it works: The generative AI model analyzes the user's preferences and conversation content to suggest the most suitable food delivery service. For example, it might suggest, "There's a recommended pizzeria nearby. Would you like to order from it?"

[1810] Step 7: Order Assistance

[1811] The server assists the user in ordering the selected meal from the appropriate food delivery service.

[1812] Input: Your meal and delivery service selections

[1813] Output: Completed order information

[1814] Specific operation: If the user accepts the offer, the server calls the delivery service API and submits the user's order. It then sends a notification of order completion to the user's device. For example, it may notify the user that "Your order for a Margherita pizza has been submitted. It will arrive in 30 minutes."

[1815] 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.

[1816] This invention is a system that provides a conversational AI partner (AI friend, AI girlfriend / boyfriend) to support people who feel lonely. This system mainly consists of a user terminal, a server, a database, and an emotion engine.

[1817] System Configuration Overview

[1818] 1. User Device:

[1819] It is a device on which users install applications and enter basic information and questionnaires.

[1820] It provides an interface for users to have text or voice conversations with their interactive artificial intelligence partners.

[1821] 2. Server:

[1822] This is a system that receives and analyzes information sent by users (basic information, survey results, conversation data).

[1823] A generative artificial intelligence model is used to generate an interactive artificial intelligence partner based on the user's profile.

[1824] Emotion analysis is performed based on conversation data to recognize the user's emotional state.

[1825] 3. Database:

[1826] Stores user basic information, survey results, conversation history, and emotional data.

[1827] 4. Emotion Engine:

[1828] This is a system that analyzes the user's input information and dialogue content and recognizes their emotions.

[1829] Adjust the tone and content of your response messages based on the perceived emotion.

[1830] Detailed program processing

[1831] User registration and survey entry

[1832] Users install the app and enter basic information such as their name, age, hobbies, etc. They then fill out a questionnaire about their personality and interests.

[1833] Example: A user inputs information such as "I like watching movies" or "I don't like the outdoors."

[1834] The terminal transmits the input information and the survey results to the server.

[1835] AI Partner Generation

[1836] The server analyzes the received user information and generates a profile, then uses a generative AI model to generate an AI partner that best suits the user's profile.

[1837] Example: The server generates an AI partner with a common interest for a user who likes watching movies.

[1838] Applying the Emotion Engine

[1839] The server analyzes the user's input and dialogue and recognizes emotions using an emotion engine. For example, if a user inputs "I'm feeling a bit down today," the emotion engine will detect "sadness" or "anxiety."

[1840] Example: When a user types "I'm tired today," the emotion engine recognizes "fatigue" and "stress."

[1841] Initiating and sustaining dialogue

[1842] Through the application, users can interact with their AI partner via text or voice, asking questions such as, "What movie should I watch today?"

[1843] The terminal sends this question to the server.

[1844] The server analyzes the question and generates an appropriate response taking into account the results of the emotion engine, for example, "I recommend this movie as a relaxing one."

[1845] The terminal displays the response from the server to the user.

[1846] Conversation history storage and analysis

[1847] The server stores the conversation history and recognized emotion data between the user and the AI ​​partner in a database, which can be used to improve the quality of future interactions.

[1848] Example: Based on the conversation history and emotional state of the user and their AI partner, advice tailored to the user's emotions is provided in the next interaction.

[1849] Promoting social connections

[1850] The server periodically analyzes the user's conversational and emotional data and suggests outgoing events and activities, such as "You seem to be feeling like you need to relax lately. Why don't you try participating in a relaxing event?"

[1851] The user terminal displays this proposal to the user and provides specific participation methods and detailed information.

[1852] Specific examples

[1853] 1. Initial settings and questionnaire entry:

[1854] The user launches the app and enters basic information such as their name "Ichiro Tanaka," their age "30," and their hobby "watching movies." They then answer a questionnaire detailing their preferences, such as "I like suspense movies" and "I don't like the outdoors."

[1855] 2. AI Partner Generation:

[1856] The server created a profile for Ichiro Tanaka and generated a "friendly AI partner who is knowledgeable about suspense movies." The AI ​​partner sent an initial message saying, "Hello, Mr. Tanaka. I see you like suspense movies."

[1857] 3. Dialogue and Sentiment Analysis:

[1858] Ichiro Tanaka asks, "What recent suspense movie would you recommend?" The server recommends "Inception is interesting," and displays this to Ichiro Tanaka. If the user feels "anxiety" based on the emotion engine, the server adds a response such as, "There are also some lighter movies that are recommended for when you're feeling anxious."

[1859] 4. Social suggestions:

[1860] The server notifies the user, "You seem to be feeling stressed lately. There's a relaxation event going on nearby. Why don't you join?" Ichiro Tanaka checks the details and decides to participate.

[1861] In this way, the system of the present invention contributes to providing psychological support and promoting social activities to users by combining dialogue with the user and emotion analysis. It also provides more personalized support by providing appropriate responses according to the user's emotional state.

[1862] The processing flow will be explained below.

[1863] Step 1:

[1864] The user installs the app and enters basic information, such as name "Yamada Taro," age "25," and hobby "reading."

[1865] Step 2:

[1866] The device temporarily stores the information entered by the user, then displays a questionnaire about hobbies, preferences, and personality, prompting the user to answer.

[1867] Step 3:

[1868] A user answers a survey. For example, the user answers "science fiction" to the question "What is your favorite movie genre?"

[1869] Step 4:

[1870] The terminal collects the user's survey responses and sends them to the server.

[1871] Step 5:

[1872] The server analyzes the received user information and generates a profile. For example, the server might record in the profile that the user "likes science fiction."

[1873] Step 6:

[1874] The server uses the generative AI model to generate a conversational AI partner based on the profile, in this case an AI partner with an interest in science fiction.

[1875] Step 7:

[1876] The server stores the initial profile of the generated AI partner in a database.

[1877] Step 8:

[1878] The server generates an initial message for the conversational AI partner and sends it to the user: "Hello, Yamada-san. I see you like science fiction!"

[1879] Step 9:

[1880] The terminal displays a welcome message from the server to the user.

[1881] Step 10:

[1882] The user initiates the interaction by typing the question, "What science fiction movie should I watch today?"

[1883] Step 11:

[1884] The terminal sends the user's question to the server.

[1885] Step 12:

[1886] The server analyzes the received question and uses an emotion engine to recognize the user's emotions. For example, if a user types "I'm feeling down today," the emotion engine will detect "sadness" or "anxiety."

[1887] Step 13:

[1888] The server generates an appropriate response based on the recognition results of the emotion engine, such as "I recommend 'Interstellar' as a relaxing movie."

[1889] Step 14:

[1890] The server generates a response and sends it to the terminal.

[1891] Step 15:

[1892] The terminal displays the response message from the server to the user.

[1893] Step 16:

[1894] If the user confirms the response and wishes to continue the dialogue, the next message is entered and the process is repeated.

[1895] Step 17:

[1896] The server stores the conversation history and recognized emotion data in a database, which can be used to improve the quality of future interactions.

[1897] Step 18:

[1898] The server periodically analyzes the user's conversational content and emotional data and suggests outward-looking events and activities. For example, it may notify the user, "It seems like you've been feeling like you need to relax lately. Why don't you try participating in a relaxing event?"

[1899] Step 19:

[1900] The device will display this proposal to the user and provide specific participation methods and detailed information.

[1901] In this way, the system of the present invention repeatedly engages in dialogue with the user and analyzes their emotions, contributing to providing psychological support to the user and promoting social activities.

[1902] Example 2

[1903] 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."

[1904] In modern society, the number of people experiencing loneliness is increasing, making it necessary to provide emotional support and social connections. The present invention aims to alleviate this sense of loneliness and promote emotional stability and social participation by providing users with personalized support. However, conventional systems have difficulty providing appropriate responses based on the user's emotional state, and their ability to analyze the user's emotions through continuous dialogue has been insufficient.

[1905] 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.

[1906] In this invention, the server includes means for analyzing the user's input information and dialogue content and recognizing emotions with an emotion engine, means for generating a response message based on the recognized emotion and sending it to the terminal, and means for saving the user's conversation history and emotion data in a database, thereby enabling the provision of appropriate responses according to the user's emotional state and personalized support based on the emotion analysis results.

[1907] "Users" refer to people who use the system, who install the application, and who input information and answer questionnaires.

[1908] A "terminal" is a device that allows a user to input information and send it to a server, and includes electronic devices such as smartphones, tablets, and personal computers.

[1909] The "server" is a central processing unit that analyzes user input information, generates an AI partner, and recognizes emotions using an emotion engine.

[1910] "Generative AI model" refers to an algorithm or model for generating an optimal conversational AI partner based on a user's profile.

[1911] A "conversational artificial intelligence partner" is an artificial intelligence-based application or service that interacts with and assists users.

[1912] An "emotion engine" refers to a system or algorithm that analyzes user input information and dialogue content to recognize emotions.

[1913] The "database" is a system for storing basic information, survey results, conversation history, and emotional data of users.

[1914] "Conversation history" refers to a record of interactions between a user and their conversational AI partner, and is data used to improve the quality of future interactions.

[1915] This invention is a system that provides conversational AI partners (AI Friends, AI Girlfriends / Boyfriends) to support people who feel lonely. The main components of this system are a user terminal, a server, a database, and an emotion engine.

[1916] First, a user installs an application on a user device such as a smartphone or tablet. Then, the user launches the application, enters basic information such as their name, age, and hobbies, and then answers a questionnaire about their hobbies and interests. For example, a user might enter "I like watching movies" or "I don't like the outdoors." This information plays an important role in each process described below.

[1917] The device automatically sends the basic information and survey results entered by the user to the server. This involves converting the data format and sending it via API. Specifically, the device converts the entered data into JSON format and sends it to the server via an HTTP POST request.

[1918] The server analyzes the received user information and generates a profile. This profile includes the user's basic information, hobbies, interests, and survey results. It then uses a generative AI model to generate a conversational AI partner based on the profile. In this case, the server runs an algorithm such as "for a user who likes watching movies, to generate an AI partner with a common interest."

[1919] Next, the server analyzes the user's input information and dialogue content, and recognizes emotions using an emotion engine. For example, if a user inputs "I'm feeling a little down today," the emotion engine has the ability to detect "sadness" or "anxiety." Based on the recognized emotion, the server generates a response message and sends it to the user's device. For example, if a user inputs "I'm tired today," the server generates a response message such as "I recommend XX as a relaxing movie."

[1920] The user device receives the response message sent from the server and displays it to the user, allowing the user to interact with the AI ​​partner via text or voice.

[1921] Furthermore, the server stores the conversation history and recognized emotional data between the user and the AI ​​partner in a database. This data is used to improve the quality of future interactions. The system also periodically analyzes the conversation and emotional data to suggest extroverted events and activities to the user. For example, it might suggest, "You seem to be feeling stressed lately. Why not join a relaxation event nearby?"

[1922] As a concrete example, if a user uses an application to ask, "What recent movies do you recommend?", the server will take into consideration the results of the emotion engine and recommend, "Inception is interesting." Furthermore, if the emotion engine indicates that the user is feeling "anxious," the server will generate an additional response such as, "There are also some lighter movies that are recommended for when you are anxious."

[1923] In this way, this system contributes to providing psychological support and promoting social activities by combining dialogue with the user and emotion analysis. In addition, the generated conversational AI partner provides more personalized and appropriate support.

[1924] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1925] Step 1:

[1926] The user installs the application and answers a questionnaire about basic information and interests.

[1927] Input: Name, age, hobbies, survey answers

[1928] Action: Launch the application and fill out the form.

[1929] Output: Dataset of basic information and survey results

[1930] Step 2:

[1931] The terminal transmits the information entered by the user and the survey results to the server.

[1932] Input: Dataset of basic information and survey results

[1933] What it does: Converts data into JSON format and sends it to the server via an HTTP POST request.

[1934] Output: Data sent to the server

[1935] Step 3:

[1936] The server analyzes the received user information and survey results and generates a profile.

[1937] Input: Submitted basic information and survey result data

[1938] How it works: It uses analytics algorithms to generate a profile of the user, extracting traits such as "I like watching movies, I don't like the outdoors."

[1939] Output: User profile

[1940] Step 4:

[1941] The server uses the generated artificial intelligence model to generate an interactive artificial intelligence partner based on the user profile.

[1942] Input: User profile

[1943] How it works: Calls the generative AI model, passes the profile data as input, and generates the optimal AI partner. For example, "For a user who likes watching movies, generates an AI partner with the same interests."

[1944] Output: Generated AI partner

[1945] Step 5:

[1946] The server interacts with the user using a conversational artificial intelligence partner.

[1947] Input: User questions and statements

[1948] How it works: Your conversational AI partner receives and analyzes your input and generates an appropriate response. For example, to the question, "What movie do you recommend?", it might respond, "Inception is a great movie."

[1949] Output: Dialogue response message

[1950] Step 6:

[1951] The server analyzes the user's input information and dialogue content, and recognizes emotions using an emotion engine.

[1952] Input: What the user says or types

[1953] How it works: The emotion engine is used to parse emotions from user utterances and identify emotional states, for example recognizing "sadness" or "anxiety" from the statement "I'm feeling bad today."

[1954] Output: Recognized emotion data

[1955] Step 7:

[1956] The server generates a response message based on the recognized emotion and sends it to the terminal.

[1957] Input: Recognized emotion data

[1958] Operation: Based on the emotion data, a response appropriate to the user's state is generated and sent to the device. For example, in response to the emotion "I'm tired today," the system responds with "I recommend this movie as a relaxing one."

[1959] Output: Emotion-based response message

[1960] Step 8:

[1961] The terminal displays the response message from the server to the user.

[1962] Input: Sentiment-based response message

[1963] Behavior: Display the received response message in the application's UI. For example, display a message such as "We recommend XX as a relaxing movie."

[1964] Output: The message displayed to the user

[1965] Step 9:

[1966] The server stores the conversation history between the user and the AI ​​partner and the recognized emotion data in a database.

[1967] Input: Conversation history and emotion data

[1968] How it works: The received data is stored in a database and used to improve the quality of future interactions.

[1969] Output: Conversation history and emotion data stored in a database

[1970] Step 10:

[1971] The server periodically analyzes the user's conversation content and emotional data and suggests outgoing events and activities.

[1972] Input: Conversation history and emotion data stored in a database

[1973] How it works: It analyzes the accumulated data and suggests events and activities that will be beneficial to the user. For example, it may notify the user, "It seems like you've been feeling like you need to relax lately. There's a relaxation event in your neighborhood. Why don't you join us?"

[1974] Output: Proposal message

[1975] (Application example 2)

[1976] 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."

[1977] Conversational AI partner systems designed to support people experiencing loneliness primarily aim to provide psychological support to users, but their application to specific tasks is limited. As a result, the security service sector lacks systems that can adequately address mental issues such as staff stress levels and reduced concentration. This can result in reduced work efficiency and safety for security staff. Therefore, a new system is needed that can improve efficiency and safety by monitoring the mental state of security staff in real time and providing appropriate support.

[1978] The identification processing 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 the user to answer a questionnaire about hobbies and preferences, means for the server to receive and analyze the user's input information, means for using a generative AI model to generate an interactive AI partner that matches the user's preferences, means for interacting with the user using the generated AI partner, means for saving the user's conversation history in a database, means for analyzing the emotions of security staff and monitoring their stress levels and concentration in real time, and means for providing appropriate advice based on the analysis results. This makes it possible to constantly understand the mental state of security staff and provide appropriate support in a timely manner.

[1979] A "user terminal" is a device on which a user installs applications and enters basic information and questionnaires.

[1980] A "server" is a system that receives and analyzes information sent by users.

[1981] A "generative artificial intelligence model" is a model that generates an interactive artificial intelligence partner based on a user's profile.

[1982] A "conversational AI partner" is an AI that can converse with a user via text or voice.

[1983] The "database" is a system that stores basic information, survey results, conversation history, and emotional data of users.

[1984] An "emotion engine" is a system that analyzes user input information and dialogue content to recognize emotions.

[1985] "Real-time monitoring" is the process of constantly monitoring the emotional state of security staff and obtaining data at the appropriate time.

[1986] "Providing advice" is a function that provides appropriate instructions and advice to security staff based on the analysis results.

[1987] A "conversation history" is a record of the conversation that took place between a user and an interactive AI partner.

[1988] This invention is a conversational AI partner system for supporting people who feel lonely, particularly in the field of security services, which monitors the mental state of security staff in real time and provides appropriate support. The system mainly consists of a user terminal, a server, a database, and an emotion engine.

[1989] System Configuration Overview

[1990] 1. User Device:

[1991] This is a device on which users install an application and enter basic information and a questionnaire. Through this terminal, security staff can converse with a conversational AI partner via text or voice. For example, this could be a smartphone or a head-mounted display (HMD).

[1992] 2. Server:

[1993] The server is a system that receives and analyzes information sent by users (basic information, survey results, conversation data). It uses a generative AI model to generate a conversational AI partner based on the user's profile. It also performs emotion analysis based on the conversation data to recognize the user's emotional state.

[1994] 3. Database:

[1995] The database is a system that stores basic information, survey results, conversation history, and emotional data of users. This data is used to improve the quality of future interactions.

[1996] 4. Emotion Engine:

[1997] The emotion engine is a system that analyzes user input and dialogue content to recognize their emotions, and adjusts the tone and content of the response message based on the recognized emotions.

[1998] Detailed program processing

[1999] The server uses the speech_recognition library for speech recognition to acquire voice input from security staff. The acquired speech is converted into text, and the text is input into the sentiment analysis model. The sentiment analysis model uses a model built with Keras. The analyzed sentiment data is sent to the server using the requests library.

[2000] The server uses this data to monitor the stress levels and concentration of security staff in real time, and provides appropriate advice based on the results of emotion analysis, such as "Take a 15-minute break and relax" or "You seem anxious. Take a deep breath and relax."

[2001] Specific examples

[2002] 1. Initial settings and questionnaire entry:

[2003] Security staff install the app and enter basic information such as their name, job description, and working hours, then answer a questionnaire about situations that make them feel stressed and how they relax.

[2004] 2. Real-time monitoring and analysis:

[2005] If a security staff member voice-types "I'm feeling a bit tired" while on duty, the emotion engine will recognize this as "fatigue" and provide a response such as "Take a 15-minute break and relax."

[2006] 3. Anomaly detection and alerting:

[2007] AI detects anomalies in surveillance camera footage and alerts security staff, and if the emotion engine identifies a staff member as stressed, the alert is delivered in a calmer, more soothing tone.

[2008] Prompt Sentence Examples

[2009] If a user says, "I've been feeling anxious lately and can't sleep," the emotion engine will recognize "anxiety" and generate a response like this:

[2010] "You seem to be experiencing anxiety. Perhaps you should talk to your doctor about it?"

[2011] In this way, the system of this invention combines dialogue with the user and emotion analysis to contribute to improving the user's mental support and work efficiency. Real-time monitoring and appropriate responses support the mental health of security staff. Furthermore, by providing appropriate responses according to the user's emotional state, more personalized support is realized.

[2012] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2013] Step 1:

[2014] The user installs the application and fills out a questionnaire and basic information.

[2015] Input: Basic information such as name, age, hobbies, and questionnaire results about your personality and interests.

[2016] Processing: The device collects the entered information and sends it to the server, where it is stored in a database.

[2017] Output: User information and survey results sent to the server.

[2018] Step 2:

[2019] The server analyzes the received user information and generates a profile.

[2020] Input: User's basic information and survey results.

[2021] Processing: The server uses the generated AI model to generate a conversational AI partner based on the user's profile.

[2022] Output: The best conversational artificial intelligence partner for the user.

[2023] Step 3:

[2024] The user initiates a dialogue with the generated conversational artificial intelligence partner.

[2025] Input: User text or voice input.

[2026] Processing: The device receives the input and sends it to the server, which uses an emotion engine to analyze the emotion and generate an appropriate response.

[2027] Output: A response message from your conversational AI partner.

[2028] Step 4:

[2029] The server monitors the user's emotional state in real time.

[2030] Input: User interaction and emotion data.

[2031] Processing: The emotion engine analyzes the user's emotions, assessing their stress level and concentration. The emotion data is stored in a database.

[2032] Output: Evaluation of the user's emotional state.

[2033] Step 5:

[2034] Based on the analysis results, the server provides appropriate advice to the user.

[2035] Input: Analysis results of the emotion engine and dialogue history.

[2036] Processing: The server generates an appropriate response message based on the analysis results and sends it to the device. The device then displays or audibly presents the response message to the user.

[2037] Output: Advice or instructions provided to the user.

[2038] Step 6:

[2039] Conversation history and emotion data are stored in a database.

[2040] Input: Conversation history between the user and their conversational AI partner, as well as emotional data.

[2041] Processing: The server stores this data in a database and uses it for future analysis and to improve the quality of the interaction.

[2042] Output: Conversation history and sentiment data stored in a database.

[2043] Prompt Sentence Examples

[2044] If a user says, "I've been feeling anxious lately and can't sleep," the emotion engine will recognize "anxiety" and generate a response like this:

[2045] "You seem to be experiencing anxiety. Perhaps you should talk to your doctor about it?"

[2046] 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.

[2047] 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.

[2048] 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 robot 414.

[2049] 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.

[2050] 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.

[2051] 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.

[2052] 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).

[2053] 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.

[2054] 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."

[2055] 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.

[2056] 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).

[2057] 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.

[2058] 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.

[2059] 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.

[2060] 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.

[2061] 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.

[2062] 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.

[2063] 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.

[2064] 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.

[2065] 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.

[2066] 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.

[2067] The following is further disclosed regarding the above embodiment.

[2068] (Claim 1)

[2069] A means for users to answer questionnaires about their hobbies and preferences;

[2070] A means for the server to receive and analyze user input information;

[2071] A means for generating an interactive AI partner that matches the user's preferences using a generative AI model;

[2072] means for interacting with a user using the generated artificial intelligence partner;

[2073] a means for storing a user's conversation history in a database;

[2074] A system including:

[2075] (Claim 2)

[2076] 10. The system of claim 1, further comprising means for the interactive artificial intelligence partner to analyze the content of the user's conversation and make suggestions based on the user's preferences.

[2077] (Claim 3)

[2078] 10. The system of claim 1, further comprising means for the interactive artificial intelligence partner to suggest outgoing events and activities.

[2079] "Example 1"

[2080] (Claim 1)

[2081] A means for users to complete a questionnaire about their basic information and preferences;

[2082] A means for the terminal to transmit the input information and the survey results to a server;

[2083] means for analyzing the received information by the server to generate a user profile;

[2084] a means for utilizing the generative AI model to generate a conversational artificial intelligence partner based on a user profile;

[2085] a means for a user to engage in a conversation with an interactive artificial intelligence partner;

[2086] means for the terminal to transmit a user's question to a server;

[2087] a means for the server to analyze the query, generate a response and send it to the terminal;

[2088] a means for the server to store the user's conversation history in a database;

[2089] A means for the server to use the stored conversation history as data to improve the quality of future conversations;

[2090] A system including:

[2091] (Claim 2)

[2092] 10. The system of claim 1, further comprising means for the conversational artificial intelligence partner to analyze the content of the user's conversation and use a generative AI model to provide responses and suggestions based on the user's preferences.

[2093] (Claim 3)

[2094] 10. The system of claim 1, further comprising means for the conversational artificial intelligence partner to suggest outgoing events and activities based on the user's conversation history.

[2095] "Application Example 1"

[2096] (Claim 1)

[2097] a means for a user to input preference information;

[2098] A means for the server to receive and analyze user input information;

[2099] A means for generating an interactive AI partner based on the user's preferences using the generated AI model;

[2100] means for interacting with a user using said artificial intelligence partner;

[2101] means for storing the user's conversation history in a storage medium;

[2102] a means of making food delivery-related offers;

[2103] a means of assisting with food ordering;

[2104] A system including:

[2105] (Claim 2)

[2106] 10. The system of claim 1, further comprising means for the interactive artificial intelligence partner to analyze the content of the user's conversation and make suggestions based on the user's preferences.

[2107] (Claim 3)

[2108] 10. The system of claim 1, further comprising means for the interactive artificial intelligence partner to suggest social activities and events.

[2109] "Example 2: Combining Emotion Engines"

[2110] (Claim 1)

[2111] A means for users to answer a questionnaire about their basic information and hobbies and preferences;

[2112] a means for transmitting the input information and the survey results to a server by the terminal;

[2113] A means for analyzing the received user information by the server and generating a profile;

[2114] A means for generating an interactive AI partner that matches the user's preferences using a generative AI model;

[2115] A means for the server to interact with the user using the generated interactive artificial intelligence partner;

[2116] A means for the server to analyze the user's input information and dialogue content and recognize emotions using an emotion engine;

[2117] a means for the server to generate a response message based on the recognized emotion and transmit the response message to the terminal;

[2118] A server stores the user's conversation history and emotion data in a database;

[2119] A system including:

[2120] (Claim 2)

[2121] 10. The system of claim 1, further comprising means for the interactive artificial intelligence partner to analyze the content of the user's conversation and make suggestions based on the user's preferences and emotions.

[2122] (Claim 3)

[2123] 10. The system of claim 1, further comprising means for the conversational artificial intelligence partner to suggest extroverted events and activities based on the user's emotional data and conversation history.

[2124] "Application example 2 when combining emotion engines"

[2125] (Claim 1)

[2126] A means for users to answer questionnaires about their hobbies and preferences;

[2127] A means for the server to receive and analyze user input information;

[2128] A means for generating an interactive AI partner that matches the user's preferences using a generative AI model;

[2129] means for interacting with a user using the generated artificial intelligence partner;

[2130] a means for storing a user's conversation history in a database;

[2131] A method for analyzing the emotions of security staff and monitoring their stress levels and concentration in real time,

[2132] A means of providing appropriate advice based on the analysis results;

[2133] A system including:

[2134] (Claim 2)

[2135] 10. The system of claim 1, further comprising means for the interactive artificial intelligence partner to analyze the content of the user's conversation and make suggestions based on the user's preferences.

[2136] (Claim 3)

[2137] 10. The system of claim 1, further comprising means for the interactive artificial intelligence partner to suggest outgoing events and activities. [Explanation of symbols]

[2138] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to answer questionnaires about their hobbies and preferences; A means for the server to receive and analyze user input information; A means for generating an interactive AI partner that matches the user's preferences using a generative AI model; means for interacting with a user using the generated artificial intelligence partner; a means for storing a user's conversation history in a database; A system including:

2. The system of claim 1 , further comprising means for the interactive artificial intelligence partner to analyze the content of the user's conversation and make suggestions based on the user's preferences.

3. The system of claim 1 , further comprising means for the interactive artificial intelligence partner to suggest outgoing events and activities.

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