System

Abstract

A system is provided.SOLUTION: The system includes a means for displaying a plurality of questions about hobbies and values to a user and collecting answers, a means for analyzing answer data of the user and specifying common hobbies and values, and a means for proposing a specific conversation topic and a date course on the basis of the specified common hobbies and values.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, the spread of online matching services has led to an increase in first-time dates. However, in many cases, good communication is hindered due to initial nervousness and anxiety about conversation, resulting in missed opportunities to meet. This problem is particularly serious for users who are not used to dating. The present invention provides a method for promoting smooth conversation on first dates and making dates more natural and enjoyable. [Means for solving the problem]

[0005] The present invention provides a means for displaying multiple questions about hobbies and values ​​to users and collecting their answers. It then provides a means for analyzing the collected user response data and identifying common hobbies and values. It also provides a system that includes a means for suggesting specific conversation topics and date courses based on the identified common hobbies and values. This system helps ease tension during first meetings, enabling smooth and enjoyable conversations and maximizing opportunities for good communication.

[0006] A "user" is an individual who uses the system to provide information about their hobbies and values.

[0007] A "hobby" is an activity that an individual is interested in and enjoys on a daily basis.

[0008] "Values" are the thoughts and beliefs that an individual considers important in their life and actions.

[0009] The "means for displaying questions and collecting answers" refers to a process or device that has the function of presenting questions about hobbies and values ​​to users and collecting the answers as data.

[0010] The "means for analyzing response data and identifying common interests and values" refers to a process or device that processes collected responses and has the function of finding commonalities between users.

[0011] A "means for suggesting conversation topics and date courses" is a process or device that has the function of showing the user specific conversation topics and date plans based on identified common interests and values.

[0012] "System" refers to the entire mechanical or electronic mechanism that performs a series of processes based on information collected from users, identifying common interests and values, and suggesting subsequent conversations and date plans. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] The present invention is a system that allows users to smoothly advance conversations and enjoy a natural, enjoyable experience on first dates. The system consists of the following main modules: an interactive question processing module, a data analysis module, and a suggestion module.

[0035] Interactive Question Processing Module

[0036] The server generates multiple questions for the user about their hobbies and values. These questions are designed to dig deeper into the user's interests and lifestyle. The device displays these questions to the user and collects their answers. For example, if the server asks User 1, "What are your hobbies?" and the user answers, "Visiting art museums," the answer is sent to the server.

[0037] Data Analysis Module

[0038] The server passes the collected user response data to a data analysis module. This module compares the hobbies and values ​​of two users and extracts common hobbies and values. For example, if User 1 and User 2 both enjoy mountain climbing, the data analysis module will identify this as a common hobby.

[0039] Suggestion Module

[0040] The server passes the shared hobbies and values ​​obtained from the data analysis module to the suggestion module. This module generates specific date courses and conversation topics based on the identified shared hobbies and values. For example, if "mountain climbing" is a shared hobby, the suggestion module will suggest a "hiking course plan" and display it on the device. This allows users to smoothly start conversations on their first date and makes it easier to plan the date.

[0041] Specific examples

[0042] 1. The server generates questions such as "What are your hobbies?" and "What do you do on the weekends?" and sends them to the device.

[0043] 2. The device displays these questions to the users, and User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[0044] 3. The server passes the collected response data to the data analysis module to identify common interests and values.

[0045] 4. The data analysis module compares the data of User 1 and User 2 and identifies, for example, "outdoor activities" as a common hobby.

[0046] 5. The server passes the identified common interests to a suggestion module to generate a specific date plan.

[0047] 6. The proposal module generates a "Plan for enjoying a picnic in a nature park" and displays it on the device.

[0048] 7. Users can plan a first date based on the generated plan and naturally bring up the topic.

[0049] The above is a specific embodiment for carrying out the present invention. By using this system, it is possible to ease the tension of meeting someone for the first time and achieve smooth communication.

[0050] The processing flow will be explained below.

[0051] Step 1:

[0052] The server generates multiple questions to understand the user's hobbies and values ​​and sends them to the terminal, where the user is ready to answer the questions from the system.

[0053] Step 2:

[0054] The device displays the received question to the user and asks for an answer, such as "What are your hobbies?" or "What do you do on the weekend?"

[0055] Step 3:

[0056] The users answer the questions through their devices. User 1 answers "visiting art museums," and User 2 answers "mountain climbing." These answers are immediately sent to the server by the device.

[0057] Step 4:

[0058] The server saves the user responses received from the device and passes them to the data analysis module. The response data for User 1 and User 2 are analyzed.

[0059] Step 5:

[0060] The data analysis module compares the response data of User 1 and User 2 to identify common hobbies and values. For example, if User 1 likes "visiting art museums" and "reading at cafes," and User 2 likes "reading at cafes" and "watching movies," "reading at cafes" will be identified as a common hobby.

[0061] Step 6:

[0062] The server passes the common interests and values ​​obtained from the data analysis module to the suggestion module, which then creates a list of common interests and inputs them into the suggestion module.

[0063] Step 7:

[0064] The suggestion module generates specific date courses and conversation topics based on the identified common interests and values. For example, if "reading at a cafe" is a common interest, a plan suggesting a date at a nearby cafe will be generated.

[0065] Step 8:

[0066] The server transmits the generated date plan to the terminal, and the terminal displays the date plan to the user, allowing the user to plan a first date based on the proposed plan.

[0067] Step 9:

[0068] The user can check the proposed plan through the device and decide on the details of the first date, allowing the user to enjoy a smooth and comfortable first date.

[0069] The above are the specific processing steps of the system of the present invention, which helps users ease tension when meeting someone for the first time and enjoy natural conversation.

[0070] Example 1

[0071] 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."

[0072] On a first date, especially if it is difficult to find a conversation starter or common topics to talk about, users feel nervous and anxious, making it difficult to communicate smoothly. Therefore, there is a need for a means to make a first date go smoothly.

[0073] 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.

[0074] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to users and collecting answers, means for storing the collected user answer data in a database, means for analyzing the stored user answer data and identifying common hobbies and values ​​of the plurality of users, means for suggesting specific conversation topics and date courses using a generative AI model based on the identified common hobbies and values, and means for displaying the suggested conversation topics and date courses on the user's terminal. This reduces tension on first dates and enables users to have natural and enjoyable communication based on common hobbies and topics.

[0075] "User" refers to a person who uses the system.

[0076] "Questions about hobbies and values" refer to questions asked to find out the user's everyday interests and important beliefs.

[0077] "Means for collecting answers" refers to the function or device that receives and records the information entered by the user in response to the questions.

[0078] "Means for storing in a database" refers to a function or device that stores collected user response data in an organized and structured format.

[0079] "Means for analyzing data" refers to functions and technologies for processing saved response data, extracting meaning, and discovering commonalities between users.

[0080] "Means for identifying common interests and values" refers to a function or device that finds common interests and values ​​among multiple users based on analyzed data.

[0081] A "generative AI model" refers to a program or system that uses artificial intelligence techniques to automatically generate new information or suggestions.

[0082] "Means for suggesting conversation topics and date courses" refers to functions and technologies that provide specific topics to talk about and date plans based on users' shared hobbies and values.

[0083] "Terminal" refers to an electronic device used by a user to access the system and enter or receive information.

[0084] The present invention is a system that helps users smoothly advance conversations and enjoy natural conversations during first dates. This system consists of the following main modules: an interactive question processing module, a data analysis module, and a suggestion module.

[0085] Interactive Question Processing Module

[0086] The server uses the generative AI model to generate multiple questions for the user about their hobbies and values. This allows for deeper insight into the user's interests and lifestyle, allowing for more accurate data collection. An example of a specific prompt is "Please generate questions about the user's hobbies." The server sends the generated questions to the device, which then displays them to the user. The user answers the displayed questions, and the device sends the answers to the server for collection.

[0087] Data Analysis Module

[0088] The server stores the collected user response data in a database. The stored response data is analyzed by a data analysis module. This module uses an AI algorithm to compare the responses of multiple users and identify common hobbies and values. For example, if User 1 and User 2 are both interested in "outdoor activities," this will be identified as a common hobby.

[0089] Suggestion Module

[0090] The server passes the shared hobbies and values ​​obtained from the data analysis module to the suggestion module. The suggestion module uses a generative AI model to generate specific date plans and conversation topics. For example, based on the shared hobby of "outdoor activities," the module suggests a plan to "enjoy a picnic in a nature park." The server sends the generated plan to the device, which then displays the proposal to the user.

[0091] Specific examples

[0092] 1. The server uses a generative AI model to generate questions such as "What are your hobbies?" and "What do you do on the weekend?"

[0093] 2. The device displays these questions to the users, and User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[0094] 3. The server receives the response data sent from the terminal and stores it in a database.

[0095] 4. The data analysis module analyzes the stored data and identifies the common hobby of User 1 and User 2 as "outdoor activities."

[0096] 5. The proposal module generates a plan for enjoying a picnic in a nature park based on common interests.

[0097] 6. The server sends this plan to the device, which displays the proposal to the user.

[0098] This allows the system to help users find common ground during first dates and promote smooth conversation. Detailed embodiments of the invention allow users to communicate naturally and enjoyably.

[0099] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0100] Step 1:

[0101] Question Generation

[0102] The server uses the generative AI model to generate multiple questions for the user about their hobbies and values. As input, it passes the prompt sentence "Generate questions about the user's hobbies" to the AI ​​model. As output, it obtains generated example questions such as "What are your hobbies?" and "What do you do on the weekend?". Specifically, the server processes the prompt sentence through the AI ​​model and obtains questions to elicit answers.

[0103] Step 2:

[0104] Submit a Question

[0105] The server sends the generated question to the terminal. The question generated in step 1 is used as input. The output is data that allows the generated question to be displayed on the terminal. In concrete terms, the server sends the question data to the terminal via the network.

[0106] Step 3:

[0107] Collecting user responses

[0108] The terminal displays the question received from the server to the user. The question data sent in step 2 is used as input. The answer data entered by the user is obtained as output. In concrete terms, the terminal displays the question to the user, and the user enters the answer. Consider an example in which User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[0109] Step 4:

[0110] Sending response data

[0111] The terminal sends the user's answer to the server. The answer data obtained in step 3 is used as input. The answer data is saved on the server as output. Specifically, the terminal sends the answer data to the server via the network.

[0112] Step 5:

[0113] Saving response data

[0114] The server receives the user's response data sent from the terminal and saves it in the database. The response data sent in step 4 is used as input. The response data is saved in the database as output. The specific operation is to store the data received by the server in the database.

[0115] Step 6:

[0116] Data analysis

[0117] The server passes the response data to the data analysis module, which analyzes the responses of the two users. The response data stored in the database is used as input. The output is the identification of common hobbies and values. Specifically, the data analysis module uses an AI algorithm to analyze the response data and find commonalities. For example, it identifies "outdoor activities" as a common hobby between User 1 and User 2.

[0118] Step 7:

[0119] Proposal Generation

[0120] The server passes the common hobbies and values ​​obtained from the data analysis module to the suggestion module. The analysis results obtained in step 6 are used as input. Specific date plans and conversation topics are generated as output. Specifically, the suggestion module uses a generative AI model to generate suggestions based on the analysis results. For example, it generates a "plan to enjoy a picnic in a nature park."

[0121] Step 8:

[0122] View Suggestions

[0123] The server sends the generated date plan to the terminal. The date plan generated in step 7 is used as input. The date plan is displayed on the terminal as output. In concrete terms, the server sends the proposed data to the terminal via the network. The terminal displays the proposed date plan to the user, allowing the user to confirm the plan.

[0124] In this way, processing involving specific actions and data flows is carried out at each step, allowing the user to have a natural and enjoyable dating experience.

[0125] (Application example 1)

[0126] 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."

[0127] Conventional systems that suggest date plans and conversation topics have difficulty making appropriate suggestions based on the user's hobbies and values, which can lead to tension and conversation breakdowns on first dates. Furthermore, there is a lack of a way to dig deeper into the user's interests and values, which can cause problems with conversations on first dates.

[0128] 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.

[0129] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to the user and collecting answers, means for analyzing the user's answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for displaying date plans and conversation topics using a smart device, means for generating prompt sentences that utilize the analysis results for date plans based on the collected data, and means for selecting an appropriate date plan using a generative AI model. This allows users to smoothly advance conversations on their first dates and reduce tension.

[0130] A "user" refers to a person who uses the system and is the entity that inputs their hobbies and values.

[0131] "Multiple questions about hobbies and values" refers to questions that dig deeper into the user's interests and lifestyle, and are necessary for smooth communication when meeting for the first time.

[0132] "Response data" refers to the information and selections provided by users in response to questions, and is data used for analysis.

[0133] "Analysis" refers to the process of finding similarities and differences based on collected response data, and may involve the use of statistical methods or machine learning.

[0134] "Common hobbies and values" refer to interests and beliefs that are shared between different users, and form the basis for date plans and conversation topics.

[0135] "Specific conversation topics" refer to themes of conversation during a first date that are generated based on common hobbies and values.

[0136] A "date course" refers to a plan of activities and locations suggested for a user to actually go on a date.

[0137] "Smart devices" refers to electronic devices that can connect to the Internet, such as smartphones, tablets, smart glasses, and head-mounted displays.

[0138] "Prompt sentences to be used for date planning" refer to sentences generated to suggest appropriate date plans to users, and are input into the generative AI model.

[0139] "Generative AI model" refers to an artificial intelligence model used to generate optimal date plans and conversation topics based on user data.

[0140] This invention is implemented as an application system called Smart Date Planner. This system is composed of the following main means:

[0141] Displaying questions about hobbies and values ​​and collecting answers

[0142] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the screen of the smart device. The user inputs answers to these questions. For example, questions may be in the form of "What are your hobbies?" or "What do you do on the weekends?" These answers are sent to the server and saved for analysis.

[0143] Data analysis

[0144] The server uses a data analysis module to analyze the collected user response data and extract common hobbies and values. This module compares data between users to find patterns of common interests and lifestyles. For example, if User 1 answers "visiting art museums" as a hobby and User 2 answers "mountain climbing" and "visiting art museums" as hobbies, the common hobby will be identified as "visiting art museums."

[0145] Date planning and conversation topic suggestions

[0146] The server uses a suggestion module to suggest date courses and conversation topics based on shared hobbies and values ​​obtained from the data analysis module. Specifically, it uses a generative AI model to suggest appropriate date plans. In this case, prompts are generated based on the collected data. For example, if "visiting art museums" is a shared hobby, a "museum date plan" will be suggested and displayed on the user's smart device. Through this process, users can smoothly advance conversations on their first date.

[0147] Hardware and software used

[0148] This system uses smart devices such as smartphones and tablets. The server uses Python, with application frameworks (e.g., Flask and Django) as needed. Machine learning libraries (e.g., TensorFlow and PyTorch) are used for data analysis and generative AI models.

[0149] Specific examples

[0150] User 1 and User 2 first install the app and answer questions about their hobbies and values. For example, if User 1 answers "visiting art museums" and User 2 answers "mountain climbing and visiting art museums," the server analyzes this data and identifies "visiting art museums" as a common hobby. The suggestion module then generates a "museum date plan" and displays it on the smartphone screen.

[0151] Prompt Sentence Examples

[0152] "User, please answer the question: What are your hobbies?"

[0153] "Tell me how you spend your weekends."

[0154] In this way, by implementing the present invention, users can smoothly advance conversations and have fun on first dates, and can easily plan appropriate dates to ease tension.

[0155] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0156] Step 1:

[0157] The server generates multiple questions for the user about their hobbies and values ​​and sends them to the smart device. The user answers these questions using a smartphone or tablet. For example, the user might answer "visiting art museums" to the question "What are your hobbies?" The input is the questions generated by the server, and the output is the user's answer data. Specifically, the server generates a list of questions and sends them to the terminal. The terminal displays the questions and receives the user's input.

[0158] Step 2:

[0159] The server stores the user's response data sent from the device in a database. For example, a response such as "visiting art museums" is recorded in the database. The user's response data is input, and as output, it is converted into a format that can be saved in the database. Specifically, the data received on the server side is converted into a format that is easy to analyze and stored in the database.

[0160] Step 3:

[0161] The server analyzes the collected user response data and extracts common hobbies and values. For example, if User 1 answers "outdoor activities" and User 2 answers "mountain climbing and visiting art museums," "visiting art museums" is identified as a common hobby. The input is the response data of multiple users, and the output is the common hobbies and values. Specifically, the data analysis module performs comparison operations on the response data to extract commonalities.

[0162] Step 4:

[0163] The server uses a generative AI model to suggest date plans and conversation topics based on shared hobbies and values. For example, if "visiting art museums" is a common hobby, a "museum date plan" is generated. The input is common hobbies and values, and the output is an appropriate date plan. Specifically, the common points are input into the generative AI model as prompts, and the model generates appropriate date plans and topics.

[0164] Step 5:

[0165] The server displays the generated date plan and conversation topics on the user's smart device. The user can review this and use it when they go on an actual date. For example, a plan centered around "visiting art museums" is displayed on a smartphone. The generated date plan is the input, and the information displayed on the user's device is the output. Specifically, the generated plan and conversation topics are notified to the smart device and displayed in a format that the user can easily access.

[0166] 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.

[0167] This invention is a system for realizing smooth and enjoyable conversations on first dates, and by combining it with an emotion engine that recognizes the user's emotions, it makes more advanced suggestions. This system is composed of an interactive question processing module, a data analysis module, a suggestion module, and an emotion engine.

[0168] Interactive Question Processing Module

[0169] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the device. The user answers these questions, and the device collects the answers and sends them to the server. For example, User 1 answers "visiting art museums" to the question "What are your hobbies?", and User 2 answers "reading."

[0170] Data Analysis Module

[0171] The server passes the collected user response data to a data analysis module, which analyzes the responses of User 1 and User 2. This module identifies and lists common hobbies and values. For example, if User 1 and User 2 both enjoy "cafe hopping," that hobby is added to the list.

[0172] Emotion Engine

[0173] The server combines the analyzed data with an emotion engine that detects and recognizes the user's emotions based on the date course generated by the suggestion module. The emotion engine analyzes the user's facial expressions, tone of voice, and corresponding responses to determine positive or negative emotions. This information is fed back to the suggestion module.

[0174] Suggestion Module

[0175] The suggestion module generates specific date courses and conversation topics based on shared hobbies and values. Furthermore, based on feedback from the emotion engine, it prioritizes and suggests plans for which the user expressed positive emotions. For example, if "cafe hopping" is listed as a shared hobby and the user responded positively to it, it will generate and suggest a plan to visit recommended nearby cafes.

[0176] Specific examples

[0177] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[0178] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[0179] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[0180] 4. The suggestion module generates a specific date plan based on the shared hobby of "cafe hopping." Furthermore, the emotion engine analyzes the user's reactions and prioritizes date plans that show positive emotions.

[0181] 5. The server sends the generated plan to the device, which displays it to the user. The user can plan a date based on the proposed plan and enjoy natural conversation.

[0182] This system proposes date plans that take into consideration not only the user's hobbies and values, but also their emotions, thereby providing a more appropriate and satisfying date experience.

[0183] The processing flow will be explained below.

[0184] Step 1:

[0185] The server generates questions to understand the user's hobbies and values ​​and sends them to the device. For example, questions such as "What are your hobbies?" or "How do you spend your weekends?" are generated.

[0186] Step 2:

[0187] The device displays the received question to the user, who then answers it. For example, user 1 answers "visiting museums," and user 2 answers "reading books." The answers are then sent from the device to the server.

[0188] Step 3:

[0189] The server saves the user's answers and passes them to the data analysis module. Specifically, User 1's answer "visiting museums" and User 2's answer "reading books" are saved and sent to the data analysis module as their respective user data.

[0190] Step 4:

[0191] The data analysis module analyzes the users' responses and finds common hobbies and values. For example, if both User 1 and User 2 enjoy spending time at cafes, it identifies this as a common hobby.

[0192] Step 5:

[0193] The server passes the analysis results to the emotion engine, which then analyzes the user's emotions. The emotion engine detects emotions from the user's facial expressions and tone of voice and determines whether they are positive or negative.

[0194] Step 6:

[0195] The server passes the analysis results of the emotion engine to the suggestion module, which generates specific date plans and conversation topics based on common interests, values, and the user's emotional state.

[0196] Step 7:

[0197] For example, based on the shared hobby of "cafe hopping," the suggestion module generates a "date plan at a recommended cafe." This plan reflects the results of the emotion engine and is provided to users who show positive emotions.

[0198] Step 8:

[0199] The server sends the generated date plan to the terminal, which displays it to the user, who can then confirm the proposed plan and plan the details of the first date.

[0200] Step 9:

[0201] Based on the date plan proposed by the user, the conversation can proceed smoothly and the date can be enjoyed. The plan is based on common interests and feelings, promoting natural conversation.

[0202] The above are the specific processing steps of the system of the present invention. This system proposes date plans taking into consideration not only the user's hobbies and values ​​but also their emotions, thereby providing an appropriate and satisfying date experience.

[0203] Example 2

[0204] 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."

[0205] While existing systems for suggesting dates and conversations take into account a user's hobbies and values ​​to some extent, they lack the ability to analyze the user's emotional responses in real time and adjust the content of the suggestions based on that information. As a result, the system may suggest date plans or conversation topics that dissatisfy the user. The present invention aims to provide a system that takes into account the user's emotions and suggests more personalized date plans and conversation topics.

[0206] 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.

[0207] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to the user and collecting answers, means for analyzing the user's answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for detecting and recognizing the user's emotions, and means for adjusting the suggested content based on the emotion analysis results, thereby making it possible to suggest more appropriate and satisfying date plans and conversation topics that match the user's emotions and interests.

[0208] A "user" is a person who operates and interacts with a particular system.

[0209] A "hobby" is an activity or interest that an individual engages in for enjoyment.

[0210] "Values" refer to an individual's beliefs, creeds, and standards for evaluating things.

[0211] A question is a question asked to elicit specific information.

[0212] An "answer" is a response to a question or the content of the response.

[0213] "Data analysis" is the process of organizing and interpreting collected data to extract useful information and knowledge.

[0214] "Common" refers to characteristics or interests shared between two or more users.

[0215] "Analysis" is the process of breaking down data or information and revealing details.

[0216] An "emotion" is a psychological state or feeling experienced by an individual.

[0217] "Discovery" is the process of finding specific data or information.

[0218] "Cognition" is the ability to understand and grasp specific information or situations.

[0219] A "suggestion" is an action or content that recommends doing something.

[0220] "Means" are the methods or tools used to achieve a particular purpose.

[0221] A "date course" is a set of activities and places planned for a first meeting or for friends to enjoy together.

[0222] A "topic of conversation" is a central theme or topic of a conversation or discussion.

[0223] "Adjustment" is the process of making changes or modifications to suit specific conditions or circumstances.

[0224] This invention is a system for ensuring smooth and enjoyable conversations on first dates. This system is composed of a series of modules that analyze user response data and suggest conversation topics and date itineraries based on shared interests and values. It also analyzes the user's emotions in real time and reflects them in the suggestions to generate more personalized date plans.

[0225] This system consists of an interactive question processing module, a data analysis module, a proposal module, and an emotion engine. Each module is described in detail below.

[0226] Interactive Question Processing Module

[0227] The server generates multiple questions about the user's hobbies and values ​​and displays them through the terminal. For example, questions such as "What are your hobbies?" or "What is your favorite food?" are created and sent to the terminal. The terminal displays these questions to the user and collects the user's answers. The user enters the answers into the terminal, which then sends them to the server. Questions can be generated using an SQL database.

[0228] Data Analysis Module

[0229] The server passes the collected user response data to a data analysis module, which analyzes the responses of User 1 and User 2. This module uses data analysis software such as Python or R to identify and list common hobbies and values. For example, if User 1 answers "visiting art museums" and User 2 answers "reading," "cafe hopping" will be identified as a common hobby.

[0230] Emotion Engine

[0231] The server combines the analyzed data and the travel itinerary generated by the suggestion module with an emotion engine that detects and recognizes the user's emotions. The emotion engine uses image recognition technology (e.g., OpenCV) and voice analysis technology (e.g., Google Cloud Speech-to-Text) to analyze the user's facial expressions and voice tone and determine positive or negative emotions. This information is fed back to the suggestion module.

[0232] Suggestion Module

[0233] The suggestion module generates specific date courses and conversation topics based on the common interests and values ​​identified by the data analysis module. Furthermore, based on feedback from the emotion engine, it prioritizes and suggests plans for which the user expressed positive emotions. For example, if "cafe hopping" is identified as a common hobby and is judged positive by emotion analysis, it will generate and suggest a "plan to visit recommended nearby cafes."

[0234] Specific examples

[0235] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[0236] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[0237] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[0238] 4. The suggestion module generates a specific date plan based on the shared hobby of "cafe hopping." Furthermore, the emotion engine analyzes the user's reactions and prioritizes date plans that show positive emotions.

[0239] 5. The server sends the generated plan to the device, which displays it to the user. The user can then plan a date and enjoy conversation based on the plan.

[0240] This system proposes date plans that take into consideration not only the user's hobbies and values, but also their emotions, thereby providing a more appropriate and satisfying date experience.

[0241] Prompt Sentence Examples

[0242] "Design a system that generates date plans based on the user's hobbies and values, and optimizes the suggestions to the user through emotional analysis. Specifically, the system should be able to make suggestions based on shared hobbies and values, and provide the optimal date plan according to the user's emotional response."

[0243] This "Description of the Invention" clarifies the operation of the entire system and the role of each module, which can be used as a reference for other people to understand and practice this invention.

[0244] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0245] Step 1:

[0246] The server generates a number of questions about the user's hobbies and values.

[0247] Input: User information

[0248] For example, create a list of questions such as "What are your hobbies?" and "What is your favorite food?"

[0249] Output: Generated questionnaire list

[0250] The server sends this list of questions to the terminal.

[0251] Step 2:

[0252] The terminal displays the list of questions received from the server to the user.

[0253] Input: Generated questionnaire list

[0254] The users input answers to each question: User 1 answers "visiting museums," User 2 answers "reading books," and so on.

[0255] Output: User response data

[0256] The terminal transmits these response data to the server.

[0257] Step 3:

[0258] The server passes the user's response data sent from the terminal to the data analysis module.

[0259] Input: User response data

[0260] The data analysis module uses programming languages ​​such as Python to analyze user response data and identify common hobbies and values.

[0261] Output: A list of parsed common interests and values

[0262] Specifically, if user 1 answers "visiting art museums" and user 2 answers "reading," then "visiting cafes" is identified as a common hobby.

[0263] Step 4:

[0264] The server passes the analyzed data and the date plan generation data to the emotion engine.

[0265] Input: A list of parsed common interests and values

[0266] The emotion engine uses image recognition technology (such as OpenCV) and voice analysis technology (such as Google Cloud Speech-to-Text) to analyze the user's facial expressions and voice tone to determine positive and negative emotions.

[0267] Output: Emotion analysis results

[0268] As a specific example, if a user responds with a smile to a plan to "visit cafes," this is determined to be a positive reaction.

[0269] Step 5:

[0270] The suggestion module generates date plans based on the common interests and values ​​identified in the data analysis module.

[0271] Input: List of analyzed common hobbies and values ​​and sentiment analysis results

[0272] Based on the results of sentiment analysis, plans that users express positive emotions about are prioritized and suggested.

[0273] Output: prioritized date plans

[0274] For example, if "cafe hopping" is identified as a common hobby and a positive response is received, a plan to "visit recommended nearby cafes" will be generated.

[0275] Step 6:

[0276] The server transmits the generated date plan to the terminal.

[0277] Input: prioritized date plans

[0278] The terminal displays the date plan to the user.

[0279] Output: The date plan displayed to the user

[0280] The user can plan a date based on the proposed plan and enjoy conversation.

[0281] Through this series of processes, the system proposes optimal date plans that take into account the user's hobbies, values, and emotions, providing a more satisfying experience.

[0282] (Application example 2)

[0283] 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."

[0284] Modern systems that support date planning and communication often only consider the user's hobbies and values. As a result, the proposed date plans and conversation topics do not necessarily provide a positive experience for the user, without taking the user's emotions into account. Furthermore, there are only a limited number of systems that can provide a dating experience in a virtual space, leaving users in remote locations without a means to have a natural dating experience. In this situation, there is a growing need for a system that can appropriately detect and analyze the user's emotions and suggest date plans and conversation topics based on them.

[0285] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to users and collecting answers, means for analyzing the users' answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for analyzing the user's facial expressions and tone of voice using an emotion engine to determine emotions, and means for the user to enjoy a date in a virtual space. This makes it possible to suggest appropriate date plans and conversation topics that take into account the user's emotions as well as their hobbies and values, allowing users in remote locations to enjoy a natural dating experience in a virtual space.

[0286] "Hobbies and values" is a general term for activities that interest a user, beliefs, and things that a user finds desirable.

[0287] The "means for displaying questions" is a mechanism for presenting questions to users via their terminals and providing an interface for collecting answers.

[0288] A "means for collecting responses" is a system that stores the responses entered by users and stores them in a database for analysis.

[0289] "Means for analyzing response data" refers to algorithms or software that process response data collected from users and derive common interests and values.

[0290] "Means for identifying common interests and values" refers to a process for extracting common interests and beliefs among multiple users from the analysis results.

[0291] The "means for suggesting a date course" is a mechanism for generating appropriate date plans and conversation topics based on identified common interests and values.

[0292] An "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to determine whether they are expressing positive or negative emotions.

[0293] The "means for analyzing facial expressions and voice tones" refers to a software system that uses sensors such as a camera and microphone to collect the user's facial expressions and voice and analyze their emotions.

[0294] A "virtual dating platform" is an infrastructure or platform that allows users to interact with each other in a virtual reality environment and simulate a dating experience.

[0295] This invention relates to a system that allows users to enjoy a natural dating experience in a virtual space, and is composed of the following main components:

[0296] System Configuration

[0297] Interactive Question Processing Module

[0298] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the device. These questions are personalized based on the user's interests and past answer data. The user can answer the questions using smart glasses or a head-mounted display (HMD), and the answer data is sent to the server.

[0299] Data Analysis Module

[0300] The server passes the collected user response data to a data analysis module for analysis. This module uses algorithms and generative AI models to analyze the user response data and identify common hobbies and values. For example, if User 1 likes "visiting museums" and User 2 likes "reading," "cafe hopping" will be identified as a common hobby.

[0301] Emotion Engine

[0302] The server combines the analysis results passed from the data analysis module with an emotion engine that detects and recognizes the user's emotions in relation to the date plans generated by the suggestion module. The emotion engine analyzes the user's facial expressions and voice tone in real time to distinguish between positive and negative emotions. This information is fed back to the suggestion module. For example, if a user responds to a plan to "visit cafes" with a smile or a happy voice, it will be recognized as a positive emotion.

[0303] Suggestion Module

[0304] The suggestion module generates specific date plans based on shared hobbies and values. At this time, it prioritizes and suggests plans that the user expresses positive emotions about based on feedback from the emotion engine. For example, if "cafe hopping" is identified as a shared hobby and the user responds positively to it, it will generate and suggest a "plan to visit a virtual cafe together."

[0305] Implementation in virtual space

[0306] Users can wear smart glasses or an HMD and enjoy dates with other users in a virtual space. In this virtual space, users can experience various scenarios based on proposed date plans. For example, they can sit together and chat in a virtual cafe or virtually stroll through a museum.

[0307] Specific examples

[0308] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[0309] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[0310] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[0311] 4. Using the emotion engine, analyze the user's emotions from their facial expressions and voice, and if a positive reaction is shown, feed that data back to the suggestion module.

[0312] 5. The proposal module generates a specific date plan based on "cafe hopping" and sends it to the device for the user to enjoy in the virtual space.

[0313] Prompt Sentence Examples

[0314] If User 1 likes "visiting museums" and User 2 likes "reading," identify "cafe hopping" as a common hobby and generate topics that users can enjoy talking about in an online virtual cafe. Also, add questions and suggestions that elicit positive emotions based on the results of emotion analysis based on the user's facial expressions and tone of voice.

[0315] With the above system, users can enjoy conversations and dates while receiving appropriate suggestions tailored to their emotions and hobbies in real time through virtual dates.

[0316] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0317] Step 1:

[0318] The server generates multiple questions for the user about their hobbies and values, and displays them on the device. The user inputs answers to the questions using smart glasses or a head-mounted display (HMD). Input: Answers to the user's questions. Output: Answer data collected from the user.

[0319] Step 2:

[0320] The server passes the collected user response data to the data analysis module for analysis. The analysis module uses a generative AI model to identify common interests and values. Input: User response data. Output: List of common interests and values.

[0321] Step 3:

[0322] The server receives the analysis results from the data analysis module and passes them to the emotion engine. The emotion engine analyzes the user's facial expressions and voice tone to determine positive or negative emotions. Input: User's facial and voice data. Output: User's emotional state.

[0323] Step 4:

[0324] Based on the emotional data obtained from the emotion engine, the server proposes date plans and conversation topics based on common hobbies and values. Plans that elicit positive emotions are generated with priority. Input: A list of common hobbies and values ​​and the user's emotional state. Output: Specific date plans and conversation topics.

[0325] Step 5:

[0326] The server sends the date plans and conversation topics generated by the suggestion module to the device and displays them to the user. The user checks and selects the proposed plans through smart glasses or an HMD. Input: Specific date plans and conversation topics. Output: The plan selected by the user.

[0327] Step 6:

[0328] The device starts a date in a virtual space based on the user's selection. The virtual space provides the user with a realistic dating experience through smart glasses or an HMD. Input: A date plan selected by the user. Output: A dating experience in a virtual space.

[0329] Through the above steps, users can enjoy a date in a virtual space while receiving appropriate suggestions tailored to their emotions and hobbies in real time.

[0330] 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.

[0331] 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.

[0332] 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.

[0333] [Second embodiment]

[0334] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0335] 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.

[0336] 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).

[0337] 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.

[0338] 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.

[0339] 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).

[0340] 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.

[0341] 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.

[0342] 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.

[0343] 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.

[0344] 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.

[0345] 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."

[0346] The present invention is a system that allows users to smoothly advance conversations and enjoy a natural, enjoyable experience on first dates. The system consists of the following main modules: an interactive question processing module, a data analysis module, and a suggestion module.

[0347] Interactive Question Processing Module

[0348] The server generates multiple questions for the user about their hobbies and values. These questions are designed to dig deeper into the user's interests and lifestyle. The device displays these questions to the user and collects their answers. For example, if the server asks User 1, "What are your hobbies?" and the user answers, "Visiting art museums," the answer is sent to the server.

[0349] Data Analysis Module

[0350] The server passes the collected user response data to a data analysis module. This module compares the hobbies and values ​​of two users and extracts common hobbies and values. For example, if User 1 and User 2 both enjoy mountain climbing, the data analysis module will identify this as a common hobby.

[0351] Suggestion Module

[0352] The server passes the shared hobbies and values ​​obtained from the data analysis module to the suggestion module. This module generates specific date courses and conversation topics based on the identified shared hobbies and values. For example, if "mountain climbing" is a shared hobby, the suggestion module will suggest a "hiking course plan" and display it on the device. This allows users to smoothly start conversations on their first date and makes it easier to plan the date.

[0353] Specific examples

[0354] 1. The server generates questions such as "What are your hobbies?" and "What do you do on the weekends?" and sends them to the device.

[0355] 2. The device displays these questions to the users, and User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[0356] 3. The server passes the collected response data to the data analysis module to identify common interests and values.

[0357] 4. The data analysis module compares the data of User 1 and User 2 and identifies, for example, "outdoor activities" as a common hobby.

[0358] 5. The server passes the identified common interests to a suggestion module to generate a specific date plan.

[0359] 6. The proposal module generates a "Plan for enjoying a picnic in a nature park" and displays it on the device.

[0360] 7. Users can plan a first date based on the generated plan and naturally bring up the topic.

[0361] The above is a specific embodiment for carrying out the present invention. By using this system, it is possible to ease the tension of meeting someone for the first time and achieve smooth communication.

[0362] The processing flow will be explained below.

[0363] Step 1:

[0364] The server generates multiple questions to understand the user's hobbies and values ​​and sends them to the terminal, where the user is ready to answer the questions from the system.

[0365] Step 2:

[0366] The device displays the received question to the user and asks for an answer, such as "What are your hobbies?" or "What do you do on the weekend?"

[0367] Step 3:

[0368] The users answer the questions through their devices. User 1 answers "visiting art museums," and User 2 answers "mountain climbing." These answers are immediately sent to the server by the device.

[0369] Step 4:

[0370] The server saves the user responses received from the device and passes them to the data analysis module. The response data for User 1 and User 2 are analyzed.

[0371] Step 5:

[0372] The data analysis module compares the response data of User 1 and User 2 to identify common hobbies and values. For example, if User 1 likes "visiting art museums" and "reading at cafes," and User 2 likes "reading at cafes" and "watching movies," "reading at cafes" will be identified as a common hobby.

[0373] Step 6:

[0374] The server passes the common interests and values ​​obtained from the data analysis module to the suggestion module, which then creates a list of common interests and inputs them into the suggestion module.

[0375] Step 7:

[0376] The suggestion module generates specific date courses and conversation topics based on the identified common interests and values. For example, if "reading at a cafe" is a common interest, a plan suggesting a date at a nearby cafe will be generated.

[0377] Step 8:

[0378] The server transmits the generated date plan to the terminal, and the terminal displays the date plan to the user, allowing the user to plan a first date based on the proposed plan.

[0379] Step 9:

[0380] The user can check the proposed plan through the device and decide on the details of the first date, allowing the user to enjoy a smooth and comfortable first date.

[0381] The above are the specific processing steps of the system of the present invention, which helps users ease tension when meeting someone for the first time and enjoy natural conversation.

[0382] Example 1

[0383] 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."

[0384] On a first date, especially if it is difficult to find a conversation starter or common topics to talk about, users feel nervous and anxious, making it difficult to communicate smoothly. Therefore, there is a need for a means to make a first date go smoothly.

[0385] 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.

[0386] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to users and collecting answers, means for storing the collected user answer data in a database, means for analyzing the stored user answer data and identifying common hobbies and values ​​of the plurality of users, means for suggesting specific conversation topics and date courses using a generative AI model based on the identified common hobbies and values, and means for displaying the suggested conversation topics and date courses on the user's terminal. This reduces tension on first dates and enables users to have natural and enjoyable communication based on common hobbies and topics.

[0387] "User" refers to a person who uses the system.

[0388] "Questions about hobbies and values" refer to questions asked to find out the user's everyday interests and important beliefs.

[0389] "Means for collecting answers" refers to the function or device that receives and records the information entered by the user in response to the questions.

[0390] "Means for storing in a database" refers to a function or device that stores collected user response data in an organized and structured format.

[0391] "Means for analyzing data" refers to functions and technologies for processing saved response data, extracting meaning, and discovering commonalities between users.

[0392] "Means for identifying common interests and values" refers to a function or device that finds common interests and values ​​among multiple users based on analyzed data.

[0393] A "generative AI model" refers to a program or system that uses artificial intelligence techniques to automatically generate new information or suggestions.

[0394] "Means for suggesting conversation topics and date courses" refers to functions and technologies that provide specific topics to talk about and date plans based on users' shared hobbies and values.

[0395] "Terminal" refers to an electronic device used by a user to access the system and enter or receive information.

[0396] The present invention is a system that helps users smoothly advance conversations and enjoy natural conversations during first dates. This system consists of the following main modules: an interactive question processing module, a data analysis module, and a suggestion module.

[0397] Interactive Question Processing Module

[0398] The server uses the generative AI model to generate multiple questions for the user about their hobbies and values. This allows for deeper insight into the user's interests and lifestyle, allowing for more accurate data collection. An example of a specific prompt is "Please generate questions about the user's hobbies." The server sends the generated questions to the device, which then displays them to the user. The user answers the displayed questions, and the device sends the answers to the server for collection.

[0399] Data Analysis Module

[0400] The server stores the collected user response data in a database. The stored response data is analyzed by a data analysis module. This module uses an AI algorithm to compare the responses of multiple users and identify common hobbies and values. For example, if User 1 and User 2 are both interested in "outdoor activities," this will be identified as a common hobby.

[0401] Suggestion Module

[0402] The server passes the shared hobbies and values ​​obtained from the data analysis module to the suggestion module. The suggestion module uses a generative AI model to generate specific date plans and conversation topics. For example, based on the shared hobby of "outdoor activities," the module suggests a plan to "enjoy a picnic in a nature park." The server sends the generated plan to the device, which then displays the proposal to the user.

[0403] Specific examples

[0404] 1. The server uses a generative AI model to generate questions such as "What are your hobbies?" and "What do you do on the weekend?"

[0405] 2. The device displays these questions to the users, and User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[0406] 3. The server receives the response data sent from the terminal and stores it in a database.

[0407] 4. The data analysis module analyzes the stored data and identifies the common hobby of User 1 and User 2 as "outdoor activities."

[0408] 5. The proposal module generates a plan for enjoying a picnic in a nature park based on common interests.

[0409] 6. The server sends this plan to the device, which displays the proposal to the user.

[0410] This allows the system to help users find common ground during first dates and promote smooth conversation. Detailed embodiments of the invention allow users to communicate naturally and enjoyably.

[0411] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0412] Step 1:

[0413] Question Generation

[0414] The server uses the generative AI model to generate multiple questions for the user about their hobbies and values. As input, it passes the prompt sentence "Generate questions about the user's hobbies" to the AI ​​model. As output, it obtains generated example questions such as "What are your hobbies?" and "What do you do on the weekend?". Specifically, the server processes the prompt sentence through the AI ​​model and obtains questions to elicit answers.

[0415] Step 2:

[0416] Submit a Question

[0417] The server sends the generated question to the terminal. The question generated in step 1 is used as input. The output is data that allows the generated question to be displayed on the terminal. In concrete terms, the server sends the question data to the terminal via the network.

[0418] Step 3:

[0419] Collecting user responses

[0420] The terminal displays the question received from the server to the user. The question data sent in step 2 is used as input. The answer data entered by the user is obtained as output. In concrete terms, the terminal displays the question to the user, and the user enters the answer. Consider an example in which User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[0421] Step 4:

[0422] Sending response data

[0423] The terminal sends the user's answer to the server. The answer data obtained in step 3 is used as input. The answer data is saved on the server as output. Specifically, the terminal sends the answer data to the server via the network.

[0424] Step 5:

[0425] Saving response data

[0426] The server receives the user's response data sent from the terminal and saves it in the database. The response data sent in step 4 is used as input. The response data is saved in the database as output. The specific operation is to store the data received by the server in the database.

[0427] Step 6:

[0428] Data analysis

[0429] The server passes the response data to the data analysis module, which analyzes the responses of the two users. The response data stored in the database is used as input. The output is the identification of common hobbies and values. Specifically, the data analysis module uses an AI algorithm to analyze the response data and find commonalities. For example, it identifies "outdoor activities" as a common hobby between User 1 and User 2.

[0430] Step 7:

[0431] Proposal Generation

[0432] The server passes the common hobbies and values ​​obtained from the data analysis module to the suggestion module. The analysis results obtained in step 6 are used as input. Specific date plans and conversation topics are generated as output. Specifically, the suggestion module uses a generative AI model to generate suggestions based on the analysis results. For example, it generates a "plan to enjoy a picnic in a nature park."

[0433] Step 8:

[0434] View Suggestions

[0435] The server sends the generated date plan to the terminal. The date plan generated in step 7 is used as input. The date plan is displayed on the terminal as output. In concrete terms, the server sends the proposed data to the terminal via the network. The terminal displays the proposed date plan to the user, allowing the user to confirm the plan.

[0436] In this way, processing involving specific actions and data flows is carried out at each step, allowing the user to have a natural and enjoyable dating experience.

[0437] (Application example 1)

[0438] 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."

[0439] Conventional systems that suggest date plans and conversation topics have difficulty making appropriate suggestions based on the user's hobbies and values, which can lead to tension and conversation breakdowns on first dates. Furthermore, there is a lack of a way to dig deeper into the user's interests and values, which can cause problems with conversations on first dates.

[0440] 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.

[0441] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to the user and collecting answers, means for analyzing the user's answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for displaying date plans and conversation topics using a smart device, means for generating prompt sentences that utilize the analysis results for date plans based on the collected data, and means for selecting an appropriate date plan using a generative AI model. This allows users to smoothly advance conversations on their first dates and reduce tension.

[0442] A "user" refers to a person who uses the system and is the entity that inputs their hobbies and values.

[0443] "Multiple questions about hobbies and values" refers to questions that dig deeper into the user's interests and lifestyle, and are necessary for smooth communication when meeting for the first time.

[0444] "Response data" refers to the information and selections provided by users in response to questions, and is data used for analysis.

[0445] "Analysis" refers to the process of finding similarities and differences based on collected response data, and may involve the use of statistical methods or machine learning.

[0446] "Common hobbies and values" refer to interests and beliefs that are shared between different users, and form the basis for date plans and conversation topics.

[0447] "Specific conversation topics" refer to themes of conversation during a first date that are generated based on common hobbies and values.

[0448] A "date course" refers to a plan of activities and locations suggested for a user to actually go on a date.

[0449] "Smart devices" refers to electronic devices that can connect to the Internet, such as smartphones, tablets, smart glasses, and head-mounted displays.

[0450] "Prompt sentences to be used for date planning" refer to sentences generated to suggest appropriate date plans to users, and are input into the generative AI model.

[0451] "Generative AI model" refers to an artificial intelligence model used to generate optimal date plans and conversation topics based on user data.

[0452] This invention is implemented as an application system called Smart Date Planner. This system is composed of the following main means:

[0453] Displaying questions about hobbies and values ​​and collecting answers

[0454] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the screen of the smart device. The user inputs answers to these questions. For example, questions may be in the form of "What are your hobbies?" or "What do you do on the weekends?" These answers are sent to the server and saved for analysis.

[0455] Data analysis

[0456] The server uses a data analysis module to analyze the collected user response data and extract common hobbies and values. This module compares data between users to find patterns of common interests and lifestyles. For example, if User 1 answers "visiting art museums" as a hobby and User 2 answers "mountain climbing" and "visiting art museums" as hobbies, the common hobby will be identified as "visiting art museums."

[0457] Date planning and conversation topic suggestions

[0458] The server uses a suggestion module to suggest date courses and conversation topics based on shared hobbies and values ​​obtained from the data analysis module. Specifically, it uses a generative AI model to suggest appropriate date plans. In this case, prompts are generated based on the collected data. For example, if "visiting art museums" is a shared hobby, a "museum date plan" will be suggested and displayed on the user's smart device. Through this process, users can smoothly advance conversations on their first date.

[0459] Hardware and software used

[0460] This system uses smart devices such as smartphones and tablets. The server uses Python, with application frameworks (e.g., Flask and Django) as needed. Machine learning libraries (e.g., TensorFlow and PyTorch) are used for data analysis and generative AI models.

[0461] Specific examples

[0462] User 1 and User 2 first install the app and answer questions about their hobbies and values. For example, if User 1 answers "visiting art museums" and User 2 answers "mountain climbing and visiting art museums," the server analyzes this data and identifies "visiting art museums" as a common hobby. The suggestion module then generates a "museum date plan" and displays it on the smartphone screen.

[0463] Prompt Sentence Examples

[0464] "User, please answer the question: What are your hobbies?"

[0465] "Tell me how you spend your weekends."

[0466] In this way, by implementing the present invention, users can smoothly advance conversations and have fun on first dates, and can easily plan appropriate dates to ease tension.

[0467] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0468] Step 1:

[0469] The server generates multiple questions for the user about their hobbies and values ​​and sends them to the smart device. The user answers these questions using a smartphone or tablet. For example, the user might answer "visiting art museums" to the question "What are your hobbies?" The input is the questions generated by the server, and the output is the user's answer data. Specifically, the server generates a list of questions and sends them to the terminal. The terminal displays the questions and receives the user's input.

[0470] Step 2:

[0471] The server stores the user's response data sent from the device in a database. For example, a response such as "visiting art museums" is recorded in the database. The user's response data is input, and as output, it is converted into a format that can be saved in the database. Specifically, the data received on the server side is converted into a format that is easy to analyze and stored in the database.

[0472] Step 3:

[0473] The server analyzes the collected user response data and extracts common hobbies and values. For example, if User 1 answers "outdoor activities" and User 2 answers "mountain climbing and visiting art museums," "visiting art museums" is identified as a common hobby. The input is the response data of multiple users, and the output is the common hobbies and values. Specifically, the data analysis module performs comparison operations on the response data to extract commonalities.

[0474] Step 4:

[0475] The server uses a generative AI model to suggest date plans and conversation topics based on shared hobbies and values. For example, if "visiting art museums" is a common hobby, a "museum date plan" is generated. The input is common hobbies and values, and the output is an appropriate date plan. Specifically, the common points are input into the generative AI model as prompts, and the model generates appropriate date plans and topics.

[0476] Step 5:

[0477] The server displays the generated date plan and conversation topics on the user's smart device. The user can review this and use it when they go on an actual date. For example, a plan centered around "visiting art museums" is displayed on a smartphone. The generated date plan is the input, and the information displayed on the user's device is the output. Specifically, the generated plan and conversation topics are notified to the smart device and displayed in a format that the user can easily access.

[0478] 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.

[0479] This invention is a system for realizing smooth and enjoyable conversations on first dates, and by combining it with an emotion engine that recognizes the user's emotions, it makes more advanced suggestions. This system is composed of an interactive question processing module, a data analysis module, a suggestion module, and an emotion engine.

[0480] Interactive Question Processing Module

[0481] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the device. The user answers these questions, and the device collects the answers and sends them to the server. For example, User 1 answers "visiting art museums" to the question "What are your hobbies?", and User 2 answers "reading."

[0482] Data Analysis Module

[0483] The server passes the collected user response data to a data analysis module, which analyzes the responses of User 1 and User 2. This module identifies and lists common hobbies and values. For example, if User 1 and User 2 both enjoy "cafe hopping," that hobby is added to the list.

[0484] Emotion Engine

[0485] The server combines the analyzed data with an emotion engine that detects and recognizes the user's emotions based on the date course generated by the suggestion module. The emotion engine analyzes the user's facial expressions, tone of voice, and corresponding responses to determine positive or negative emotions. This information is fed back to the suggestion module.

[0486] Suggestion Module

[0487] The suggestion module generates specific date courses and conversation topics based on shared hobbies and values. Furthermore, based on feedback from the emotion engine, it prioritizes and suggests plans for which the user expressed positive emotions. For example, if "cafe hopping" is listed as a shared hobby and the user responded positively to it, it will generate and suggest a plan to visit recommended nearby cafes.

[0488] Specific examples

[0489] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[0490] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[0491] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[0492] 4. The suggestion module generates a specific date plan based on the shared hobby of "cafe hopping." Furthermore, the emotion engine analyzes the user's reactions and prioritizes date plans that show positive emotions.

[0493] 5. The server sends the generated plan to the device, which displays it to the user. The user can plan a date based on the proposed plan and enjoy natural conversation.

[0494] This system proposes date plans that take into consideration not only the user's hobbies and values, but also their emotions, thereby providing a more appropriate and satisfying date experience.

[0495] The processing flow will be explained below.

[0496] Step 1:

[0497] The server generates questions to understand the user's hobbies and values ​​and sends them to the device. For example, questions such as "What are your hobbies?" or "How do you spend your weekends?" are generated.

[0498] Step 2:

[0499] The device displays the received question to the user, who then answers it. For example, user 1 answers "visiting museums," and user 2 answers "reading books." The answers are then sent from the device to the server.

[0500] Step 3:

[0501] The server saves the user's answers and passes them to the data analysis module. Specifically, User 1's answer "visiting museums" and User 2's answer "reading books" are saved and sent to the data analysis module as their respective user data.

[0502] Step 4:

[0503] The data analysis module analyzes the users' responses and finds common hobbies and values. For example, if both User 1 and User 2 enjoy spending time at cafes, it identifies this as a common hobby.

[0504] Step 5:

[0505] The server passes the analysis results to the emotion engine, which then analyzes the user's emotions. The emotion engine detects emotions from the user's facial expressions and tone of voice and determines whether they are positive or negative.

[0506] Step 6:

[0507] The server passes the analysis results of the emotion engine to the suggestion module, which generates specific date plans and conversation topics based on common interests, values, and the user's emotional state.

[0508] Step 7:

[0509] For example, based on the shared hobby of "cafe hopping," the suggestion module generates a "date plan at a recommended cafe." This plan reflects the results of the emotion engine and is provided to users who show positive emotions.

[0510] Step 8:

[0511] The server sends the generated date plan to the terminal, which displays it to the user, who can then confirm the proposed plan and plan the details of the first date.

[0512] Step 9:

[0513] Based on the date plan proposed by the user, the conversation can proceed smoothly and the date can be enjoyed. The plan is based on common interests and feelings, promoting natural conversation.

[0514] The above are the specific processing steps of the system of the present invention. This system proposes date plans taking into consideration not only the user's hobbies and values ​​but also their emotions, thereby providing an appropriate and satisfying date experience.

[0515] Example 2

[0516] 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."

[0517] While existing systems for suggesting dates and conversations take into account a user's hobbies and values ​​to some extent, they lack the ability to analyze the user's emotional responses in real time and adjust the content of the suggestions based on that information. As a result, the system may suggest date plans or conversation topics that dissatisfy the user. The present invention aims to provide a system that takes into account the user's emotions and suggests more personalized date plans and conversation topics.

[0518] 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.

[0519] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to the user and collecting answers, means for analyzing the user's answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for detecting and recognizing the user's emotions, and means for adjusting the suggested content based on the emotion analysis results, thereby making it possible to suggest more appropriate and satisfying date plans and conversation topics that match the user's emotions and interests.

[0520] A "user" is a person who operates and interacts with a particular system.

[0521] A "hobby" is an activity or interest that an individual engages in for enjoyment.

[0522] "Values" refer to an individual's beliefs, creeds, and standards for evaluating things.

[0523] A question is a question asked to elicit specific information.

[0524] An "answer" is a response to a question or the content of the response.

[0525] "Data analysis" is the process of organizing and interpreting collected data to extract useful information and knowledge.

[0526] "Common" refers to characteristics or interests shared between two or more users.

[0527] "Analysis" is the process of breaking down data or information and revealing details.

[0528] An "emotion" is a psychological state or feeling experienced by an individual.

[0529] "Discovery" is the process of finding specific data or information.

[0530] "Cognition" is the ability to understand and grasp specific information or situations.

[0531] A "suggestion" is an action or content that recommends doing something.

[0532] "Means" are the methods or tools used to achieve a particular purpose.

[0533] A "date course" is a set of activities and places planned for a first meeting or for friends to enjoy together.

[0534] A "topic of conversation" is a central theme or topic of a conversation or discussion.

[0535] "Adjustment" is the process of making changes or modifications to suit specific conditions or circumstances.

[0536] This invention is a system for ensuring smooth and enjoyable conversations on first dates. This system is composed of a series of modules that analyze user response data and suggest conversation topics and date itineraries based on shared interests and values. It also analyzes the user's emotions in real time and reflects them in the suggestions to generate more personalized date plans.

[0537] This system consists of an interactive question processing module, a data analysis module, a proposal module, and an emotion engine. Each module is described in detail below.

[0538] Interactive Question Processing Module

[0539] The server generates multiple questions about the user's hobbies and values ​​and displays them through the terminal. For example, questions such as "What are your hobbies?" or "What is your favorite food?" are created and sent to the terminal. The terminal displays these questions to the user and collects the user's answers. The user enters the answers into the terminal, which then sends them to the server. Questions can be generated using an SQL database.

[0540] Data Analysis Module

[0541] The server passes the collected user response data to a data analysis module, which analyzes the responses of User 1 and User 2. This module uses data analysis software such as Python or R to identify and list common hobbies and values. For example, if User 1 answers "visiting art museums" and User 2 answers "reading," "cafe hopping" will be identified as a common hobby.

[0542] Emotion Engine

[0543] The server combines the analyzed data and the travel itinerary generated by the suggestion module with an emotion engine that detects and recognizes the user's emotions. The emotion engine uses image recognition technology (e.g., OpenCV) and voice analysis technology (e.g., Google Cloud Speech-to-Text) to analyze the user's facial expressions and voice tone and determine positive or negative emotions. This information is fed back to the suggestion module.

[0544] Suggestion Module

[0545] The suggestion module generates specific date courses and conversation topics based on the common interests and values ​​identified by the data analysis module. Furthermore, based on feedback from the emotion engine, it prioritizes and suggests plans for which the user expressed positive emotions. For example, if "cafe hopping" is identified as a common hobby and is judged positive by emotion analysis, it will generate and suggest a "plan to visit recommended nearby cafes."

[0546] Specific examples

[0547] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[0548] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[0549] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[0550] 4. The suggestion module generates a specific date plan based on the shared hobby of "cafe hopping." Furthermore, the emotion engine analyzes the user's reactions and prioritizes date plans that show positive emotions.

[0551] 5. The server sends the generated plan to the device, which displays it to the user. The user can then plan a date and enjoy conversation based on the plan.

[0552] This system proposes date plans that take into consideration not only the user's hobbies and values, but also their emotions, thereby providing a more appropriate and satisfying date experience.

[0553] Prompt Sentence Examples

[0554] "Design a system that generates date plans based on the user's hobbies and values, and optimizes the suggestions to the user through emotional analysis. Specifically, the system should be able to make suggestions based on shared hobbies and values, and provide the optimal date plan according to the user's emotional response."

[0555] This "Description of the Invention" clarifies the operation of the entire system and the role of each module, which can be used as a reference for other people to understand and practice this invention.

[0556] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0557] Step 1:

[0558] The server generates a number of questions about the user's hobbies and values.

[0559] Input: User information

[0560] For example, create a list of questions such as "What are your hobbies?" and "What is your favorite food?"

[0561] Output: Generated questionnaire list

[0562] The server sends this list of questions to the terminal.

[0563] Step 2:

[0564] The terminal displays the list of questions received from the server to the user.

[0565] Input: Generated questionnaire list

[0566] The users input answers to each question: User 1 answers "visiting museums," User 2 answers "reading books," and so on.

[0567] Output: User response data

[0568] The terminal transmits these response data to the server.

[0569] Step 3:

[0570] The server passes the user's response data sent from the terminal to the data analysis module.

[0571] Input: User response data

[0572] The data analysis module uses programming languages ​​such as Python to analyze user response data and identify common hobbies and values.

[0573] Output: A list of parsed common interests and values

[0574] Specifically, if user 1 answers "visiting art museums" and user 2 answers "reading," then "visiting cafes" is identified as a common hobby.

[0575] Step 4:

[0576] The server passes the analyzed data and the date plan generation data to the emotion engine.

[0577] Input: A list of parsed common interests and values

[0578] The emotion engine uses image recognition technology (such as OpenCV) and voice analysis technology (such as Google Cloud Speech-to-Text) to analyze the user's facial expressions and voice tone to determine positive and negative emotions.

[0579] Output: Emotion analysis results

[0580] As a specific example, if a user responds with a smile to a plan to "visit cafes," this is determined to be a positive reaction.

[0581] Step 5:

[0582] The suggestion module generates date plans based on the common interests and values ​​identified in the data analysis module.

[0583] Input: List of analyzed common hobbies and values ​​and sentiment analysis results

[0584] Based on the results of sentiment analysis, plans that users express positive emotions about are prioritized and suggested.

[0585] Output: prioritized date plans

[0586] For example, if "cafe hopping" is identified as a common hobby and a positive response is received, a plan to "visit recommended nearby cafes" will be generated.

[0587] Step 6:

[0588] The server transmits the generated date plan to the terminal.

[0589] Input: prioritized date plans

[0590] The terminal displays the date plan to the user.

[0591] Output: The date plan displayed to the user

[0592] The user can plan a date based on the proposed plan and enjoy conversation.

[0593] Through this series of processes, the system proposes optimal date plans that take into account the user's hobbies, values, and emotions, providing a more satisfying experience.

[0594] (Application example 2)

[0595] 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."

[0596] Modern systems that support date planning and communication often only consider the user's hobbies and values. As a result, the proposed date plans and conversation topics do not necessarily provide a positive experience for the user, without taking the user's emotions into account. Furthermore, there are only a limited number of systems that can provide a dating experience in a virtual space, leaving users in remote locations without a means to have a natural dating experience. In this situation, there is a growing need for a system that can appropriately detect and analyze the user's emotions and suggest date plans and conversation topics based on them.

[0597] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to users and collecting answers, means for analyzing the users' answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for analyzing the user's facial expressions and tone of voice using an emotion engine to determine emotions, and means for the user to enjoy a date in a virtual space. This makes it possible to suggest appropriate date plans and conversation topics that take into account the user's emotions as well as their hobbies and values, allowing users in remote locations to enjoy a natural dating experience in a virtual space.

[0598] "Hobbies and values" is a general term for activities that interest a user, beliefs, and things that a user finds desirable.

[0599] The "means for displaying questions" is a mechanism for presenting questions to users via their terminals and providing an interface for collecting answers.

[0600] A "means for collecting responses" is a system that stores the responses entered by users and stores them in a database for analysis.

[0601] "Means for analyzing response data" refers to algorithms or software that process response data collected from users and derive common interests and values.

[0602] "Means for identifying common interests and values" refers to a process for extracting common interests and beliefs among multiple users from the analysis results.

[0603] The "means for suggesting a date course" is a mechanism for generating appropriate date plans and conversation topics based on identified common interests and values.

[0604] An "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to determine whether they are expressing positive or negative emotions.

[0605] The "means for analyzing facial expressions and voice tones" refers to a software system that uses sensors such as a camera and microphone to collect the user's facial expressions and voice and analyze their emotions.

[0606] A "virtual dating platform" is an infrastructure or platform that allows users to interact with each other in a virtual reality environment and simulate a dating experience.

[0607] This invention relates to a system that allows users to enjoy a natural dating experience in a virtual space, and is composed of the following main components:

[0608] System Configuration

[0609] Interactive Question Processing Module

[0610] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the device. These questions are personalized based on the user's interests and past answer data. The user can answer the questions using smart glasses or a head-mounted display (HMD), and the answer data is sent to the server.

[0611] Data Analysis Module

[0612] The server passes the collected user response data to a data analysis module for analysis. This module uses algorithms and generative AI models to analyze the user response data and identify common hobbies and values. For example, if User 1 likes "visiting museums" and User 2 likes "reading," "cafe hopping" will be identified as a common hobby.

[0613] Emotion Engine

[0614] The server combines the analysis results passed from the data analysis module with an emotion engine that detects and recognizes the user's emotions in relation to the date plans generated by the suggestion module. The emotion engine analyzes the user's facial expressions and voice tone in real time to distinguish between positive and negative emotions. This information is fed back to the suggestion module. For example, if a user responds to a plan to "visit cafes" with a smile or a happy voice, it will be recognized as a positive emotion.

[0615] Suggestion Module

[0616] The suggestion module generates specific date plans based on shared hobbies and values. At this time, it prioritizes and suggests plans that the user expresses positive emotions about based on feedback from the emotion engine. For example, if "cafe hopping" is identified as a shared hobby and the user responds positively to it, it will generate and suggest a "plan to visit a virtual cafe together."

[0617] Implementation in virtual space

[0618] Users can wear smart glasses or an HMD and enjoy dates with other users in a virtual space. In this virtual space, users can experience various scenarios based on proposed date plans. For example, they can sit together and chat in a virtual cafe or virtually stroll through a museum.

[0619] Specific examples

[0620] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[0621] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[0622] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[0623] 4. Using the emotion engine, analyze the user's emotions from their facial expressions and voice, and if a positive reaction is shown, feed that data back to the suggestion module.

[0624] 5. The proposal module generates a specific date plan based on "cafe hopping" and sends it to the device for the user to enjoy in the virtual space.

[0625] Prompt Sentence Examples

[0626] If User 1 likes "visiting museums" and User 2 likes "reading," identify "cafe hopping" as a common hobby and generate topics that users can enjoy talking about in an online virtual cafe. Also, add questions and suggestions that elicit positive emotions based on the results of emotion analysis based on the user's facial expressions and tone of voice.

[0627] With the above system, users can enjoy conversations and dates while receiving appropriate suggestions tailored to their emotions and hobbies in real time through virtual dates.

[0628] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0629] Step 1:

[0630] The server generates multiple questions for the user about their hobbies and values, and displays them on the device. The user inputs answers to the questions using smart glasses or a head-mounted display (HMD). Input: Answers to the user's questions. Output: Answer data collected from the user.

[0631] Step 2:

[0632] The server passes the collected user response data to the data analysis module for analysis. The analysis module uses a generative AI model to identify common interests and values. Input: User response data. Output: List of common interests and values.

[0633] Step 3:

[0634] The server receives the analysis results from the data analysis module and passes them to the emotion engine. The emotion engine analyzes the user's facial expressions and voice tone to determine positive or negative emotions. Input: User's facial and voice data. Output: User's emotional state.

[0635] Step 4:

[0636] Based on the emotional data obtained from the emotion engine, the server proposes date plans and conversation topics based on common hobbies and values. Plans that elicit positive emotions are generated with priority. Input: A list of common hobbies and values ​​and the user's emotional state. Output: Specific date plans and conversation topics.

[0637] Step 5:

[0638] The server sends the date plans and conversation topics generated by the suggestion module to the device and displays them to the user. The user checks and selects the proposed plans through smart glasses or an HMD. Input: Specific date plans and conversation topics. Output: The plan selected by the user.

[0639] Step 6:

[0640] The device starts a date in a virtual space based on the user's selection. The virtual space provides the user with a realistic dating experience through smart glasses or an HMD. Input: A date plan selected by the user. Output: A dating experience in a virtual space.

[0641] Through the above steps, users can enjoy a date in a virtual space while receiving appropriate suggestions tailored to their emotions and hobbies in real time.

[0642] 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.

[0643] 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.

[0644] 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.

[0645] [Third embodiment]

[0646] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0647] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0648] 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).

[0649] 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.

[0650] 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.

[0651] 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).

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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.

[0656] 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.

[0657] 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."

[0658] The present invention is a system that allows users to smoothly advance conversations and enjoy a natural, enjoyable experience on first dates. The system consists of the following main modules: an interactive question processing module, a data analysis module, and a suggestion module.

[0659] Interactive Question Processing Module

[0660] The server generates multiple questions for the user about their hobbies and values. These questions are designed to dig deeper into the user's interests and lifestyle. The device displays these questions to the user and collects their answers. For example, if the server asks User 1, "What are your hobbies?" and the user answers, "Visiting art museums," the answer is sent to the server.

[0661] Data Analysis Module

[0662] The server passes the collected user response data to a data analysis module. This module compares the hobbies and values ​​of two users and extracts common hobbies and values. For example, if User 1 and User 2 both enjoy mountain climbing, the data analysis module will identify this as a common hobby.

[0663] Suggestion Module

[0664] The server passes the shared hobbies and values ​​obtained from the data analysis module to the suggestion module. This module generates specific date courses and conversation topics based on the identified shared hobbies and values. For example, if "mountain climbing" is a shared hobby, the suggestion module will suggest a "hiking course plan" and display it on the device. This allows users to smoothly start conversations on their first date and makes it easier to plan the date.

[0665] Specific examples

[0666] 1. The server generates questions such as "What are your hobbies?" and "What do you do on the weekends?" and sends them to the device.

[0667] 2. The device displays these questions to the users, and User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[0668] 3. The server passes the collected response data to the data analysis module to identify common interests and values.

[0669] 4. The data analysis module compares the data of User 1 and User 2 and identifies, for example, "outdoor activities" as a common hobby.

[0670] 5. The server passes the identified common interests to a suggestion module to generate a specific date plan.

[0671] 6. The proposal module generates a "Plan for enjoying a picnic in a nature park" and displays it on the device.

[0672] 7. Users can plan a first date based on the generated plan and naturally bring up the topic.

[0673] The above is a specific embodiment for carrying out the present invention. By using this system, it is possible to ease the tension of meeting someone for the first time and achieve smooth communication.

[0674] The processing flow will be explained below.

[0675] Step 1:

[0676] The server generates multiple questions to understand the user's hobbies and values ​​and sends them to the terminal, where the user is ready to answer the questions from the system.

[0677] Step 2:

[0678] The device displays the received question to the user and asks for an answer, such as "What are your hobbies?" or "What do you do on the weekend?"

[0679] Step 3:

[0680] The users answer the questions through their devices. User 1 answers "visiting art museums," and User 2 answers "mountain climbing." These answers are immediately sent to the server by the device.

[0681] Step 4:

[0682] The server saves the user responses received from the device and passes them to the data analysis module. The response data for User 1 and User 2 are analyzed.

[0683] Step 5:

[0684] The data analysis module compares the response data of User 1 and User 2 to identify common hobbies and values. For example, if User 1 likes "visiting art museums" and "reading at cafes," and User 2 likes "reading at cafes" and "watching movies," "reading at cafes" will be identified as a common hobby.

[0685] Step 6:

[0686] The server passes the common interests and values ​​obtained from the data analysis module to the suggestion module, which then creates a list of common interests and inputs them into the suggestion module.

[0687] Step 7:

[0688] The suggestion module generates specific date courses and conversation topics based on the identified common interests and values. For example, if "reading at a cafe" is a common interest, a plan suggesting a date at a nearby cafe will be generated.

[0689] Step 8:

[0690] The server transmits the generated date plan to the terminal, and the terminal displays the date plan to the user, allowing the user to plan a first date based on the proposed plan.

[0691] Step 9:

[0692] The user can check the proposed plan through the device and decide on the details of the first date, allowing the user to enjoy a smooth and comfortable first date.

[0693] The above are the specific processing steps of the system of the present invention, which helps users ease tension when meeting someone for the first time and enjoy natural conversation.

[0694] Example 1

[0695] 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."

[0696] On a first date, especially if it is difficult to find a conversation starter or common topics to talk about, users feel nervous and anxious, making it difficult to communicate smoothly. Therefore, there is a need for a means to make a first date go smoothly.

[0697] 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.

[0698] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to users and collecting answers, means for storing the collected user answer data in a database, means for analyzing the stored user answer data and identifying common hobbies and values ​​of the plurality of users, means for suggesting specific conversation topics and date courses using a generative AI model based on the identified common hobbies and values, and means for displaying the suggested conversation topics and date courses on the user's terminal. This reduces tension on first dates and enables users to have natural and enjoyable communication based on common hobbies and topics.

[0699] "User" refers to a person who uses the system.

[0700] "Questions about hobbies and values" refer to questions asked to find out the user's everyday interests and important beliefs.

[0701] "Means for collecting answers" refers to the function or device that receives and records the information entered by the user in response to the questions.

[0702] "Means for storing in a database" refers to a function or device that stores collected user response data in an organized and structured format.

[0703] "Means for analyzing data" refers to functions and technologies for processing saved response data, extracting meaning, and discovering commonalities between users.

[0704] "Means for identifying common interests and values" refers to a function or device that finds common interests and values ​​among multiple users based on analyzed data.

[0705] A "generative AI model" refers to a program or system that uses artificial intelligence techniques to automatically generate new information or suggestions.

[0706] "Means for suggesting conversation topics and date courses" refers to functions and technologies that provide specific topics to talk about and date plans based on users' shared hobbies and values.

[0707] "Terminal" refers to an electronic device used by a user to access the system and enter or receive information.

[0708] The present invention is a system that helps users smoothly advance conversations and enjoy natural conversations during first dates. This system consists of the following main modules: an interactive question processing module, a data analysis module, and a suggestion module.

[0709] Interactive Question Processing Module

[0710] The server uses the generative AI model to generate multiple questions for the user about their hobbies and values. This allows for deeper insight into the user's interests and lifestyle, allowing for more accurate data collection. An example of a specific prompt is "Please generate questions about the user's hobbies." The server sends the generated questions to the device, which then displays them to the user. The user answers the displayed questions, and the device sends the answers to the server for collection.

[0711] Data Analysis Module

[0712] The server stores the collected user response data in a database. The stored response data is analyzed by a data analysis module. This module uses an AI algorithm to compare the responses of multiple users and identify common hobbies and values. For example, if User 1 and User 2 are both interested in "outdoor activities," this will be identified as a common hobby.

[0713] Suggestion Module

[0714] The server passes the shared hobbies and values ​​obtained from the data analysis module to the suggestion module. The suggestion module uses a generative AI model to generate specific date plans and conversation topics. For example, based on the shared hobby of "outdoor activities," the module suggests a plan to "enjoy a picnic in a nature park." The server sends the generated plan to the device, which then displays the proposal to the user.

[0715] Specific examples

[0716] 1. The server uses a generative AI model to generate questions such as "What are your hobbies?" and "What do you do on the weekend?"

[0717] 2. The device displays these questions to the users, and User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[0718] 3. The server receives the response data sent from the terminal and stores it in a database.

[0719] 4. The data analysis module analyzes the stored data and identifies the common hobby of User 1 and User 2 as "outdoor activities."

[0720] 5. The proposal module generates a plan for enjoying a picnic in a nature park based on common interests.

[0721] 6. The server sends this plan to the device, which displays the proposal to the user.

[0722] This allows the system to help users find common ground during first dates and promote smooth conversation. Detailed embodiments of the invention allow users to communicate naturally and enjoyably.

[0723] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0724] Step 1:

[0725] Question Generation

[0726] The server uses the generative AI model to generate multiple questions for the user about their hobbies and values. As input, it passes the prompt sentence "Generate questions about the user's hobbies" to the AI ​​model. As output, it obtains generated example questions such as "What are your hobbies?" and "What do you do on the weekend?". Specifically, the server processes the prompt sentence through the AI ​​model and obtains questions to elicit answers.

[0727] Step 2:

[0728] Submit a Question

[0729] The server sends the generated question to the terminal. The question generated in step 1 is used as input. The output is data that allows the generated question to be displayed on the terminal. In concrete terms, the server sends the question data to the terminal via the network.

[0730] Step 3:

[0731] Collecting user responses

[0732] The terminal displays the question received from the server to the user. The question data sent in step 2 is used as input. The answer data entered by the user is obtained as output. In concrete terms, the terminal displays the question to the user, and the user enters the answer. Consider an example in which User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[0733] Step 4:

[0734] Sending response data

[0735] The terminal sends the user's answer to the server. The answer data obtained in step 3 is used as input. The answer data is saved on the server as output. Specifically, the terminal sends the answer data to the server via the network.

[0736] Step 5:

[0737] Saving response data

[0738] The server receives the user's response data sent from the terminal and saves it in the database. The response data sent in step 4 is used as input. The response data is saved in the database as output. The specific operation is to store the data received by the server in the database.

[0739] Step 6:

[0740] Data analysis

[0741] The server passes the response data to the data analysis module, which analyzes the responses of the two users. The response data stored in the database is used as input. The output is the identification of common hobbies and values. Specifically, the data analysis module uses an AI algorithm to analyze the response data and find commonalities. For example, it identifies "outdoor activities" as a common hobby between User 1 and User 2.

[0742] Step 7:

[0743] Proposal Generation

[0744] The server passes the common hobbies and values ​​obtained from the data analysis module to the suggestion module. The analysis results obtained in step 6 are used as input. Specific date plans and conversation topics are generated as output. Specifically, the suggestion module uses a generative AI model to generate suggestions based on the analysis results. For example, it generates a "plan to enjoy a picnic in a nature park."

[0745] Step 8:

[0746] View Suggestions

[0747] The server sends the generated date plan to the terminal. The date plan generated in step 7 is used as input. The date plan is displayed on the terminal as output. In concrete terms, the server sends the proposed data to the terminal via the network. The terminal displays the proposed date plan to the user, allowing the user to confirm the plan.

[0748] In this way, processing involving specific actions and data flows is carried out at each step, allowing the user to have a natural and enjoyable dating experience.

[0749] (Application example 1)

[0750] 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."

[0751] Conventional systems that suggest date plans and conversation topics have difficulty making appropriate suggestions based on the user's hobbies and values, which can lead to tension and conversation breakdowns on first dates. Furthermore, there is a lack of a way to dig deeper into the user's interests and values, which can cause problems with conversations on first dates.

[0752] 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.

[0753] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to the user and collecting answers, means for analyzing the user's answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for displaying date plans and conversation topics using a smart device, means for generating prompt sentences that utilize the analysis results for date plans based on the collected data, and means for selecting an appropriate date plan using a generative AI model. This allows users to smoothly advance conversations on their first dates and reduce tension.

[0754] A "user" refers to a person who uses the system and is the entity that inputs their hobbies and values.

[0755] "Multiple questions about hobbies and values" refers to questions that dig deeper into the user's interests and lifestyle, and are necessary for smooth communication when meeting for the first time.

[0756] "Response data" refers to the information and selections provided by users in response to questions, and is data used for analysis.

[0757] "Analysis" refers to the process of finding similarities and differences based on collected response data, and may involve the use of statistical methods or machine learning.

[0758] "Common hobbies and values" refer to interests and beliefs that are shared between different users, and form the basis for date plans and conversation topics.

[0759] "Specific conversation topics" refer to themes of conversation during a first date that are generated based on common hobbies and values.

[0760] A "date course" refers to a plan of activities and locations suggested for a user to actually go on a date.

[0761] "Smart devices" refers to electronic devices that can connect to the Internet, such as smartphones, tablets, smart glasses, and head-mounted displays.

[0762] "Prompt sentences to be used for date planning" refer to sentences generated to suggest appropriate date plans to users, and are input into the generative AI model.

[0763] "Generative AI model" refers to an artificial intelligence model used to generate optimal date plans and conversation topics based on user data.

[0764] This invention is implemented as an application system called Smart Date Planner. This system is composed of the following main means:

[0765] Displaying questions about hobbies and values ​​and collecting answers

[0766] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the screen of the smart device. The user inputs answers to these questions. For example, questions may be in the form of "What are your hobbies?" or "What do you do on the weekends?" These answers are sent to the server and saved for analysis.

[0767] Data analysis

[0768] The server uses a data analysis module to analyze the collected user response data and extract common hobbies and values. This module compares data between users to find patterns of common interests and lifestyles. For example, if User 1 answers "visiting art museums" as a hobby and User 2 answers "mountain climbing" and "visiting art museums" as hobbies, the common hobby will be identified as "visiting art museums."

[0769] Date planning and conversation topic suggestions

[0770] The server uses a suggestion module to suggest date courses and conversation topics based on shared hobbies and values ​​obtained from the data analysis module. Specifically, it uses a generative AI model to suggest appropriate date plans. In this case, prompts are generated based on the collected data. For example, if "visiting art museums" is a shared hobby, a "museum date plan" will be suggested and displayed on the user's smart device. Through this process, users can smoothly advance conversations on their first date.

[0771] Hardware and software used

[0772] This system uses smart devices such as smartphones and tablets. The server uses Python, with application frameworks (e.g., Flask and Django) as needed. Machine learning libraries (e.g., TensorFlow and PyTorch) are used for data analysis and generative AI models.

[0773] Specific examples

[0774] User 1 and User 2 first install the app and answer questions about their hobbies and values. For example, if User 1 answers "visiting art museums" and User 2 answers "mountain climbing and visiting art museums," the server analyzes this data and identifies "visiting art museums" as a common hobby. The suggestion module then generates a "museum date plan" and displays it on the smartphone screen.

[0775] Prompt Sentence Examples

[0776] "User, please answer the question: What are your hobbies?"

[0777] "Tell me how you spend your weekends."

[0778] In this way, by implementing the present invention, users can smoothly advance conversations and have fun on first dates, and can easily plan appropriate dates to ease tension.

[0779] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0780] Step 1:

[0781] The server generates multiple questions for the user about their hobbies and values ​​and sends them to the smart device. The user answers these questions using a smartphone or tablet. For example, the user might answer "visiting art museums" to the question "What are your hobbies?" The input is the questions generated by the server, and the output is the user's answer data. Specifically, the server generates a list of questions and sends them to the terminal. The terminal displays the questions and receives the user's input.

[0782] Step 2:

[0783] The server stores the user's response data sent from the device in a database. For example, a response such as "visiting art museums" is recorded in the database. The user's response data is input, and as output, it is converted into a format that can be saved in the database. Specifically, the data received on the server side is converted into a format that is easy to analyze and stored in the database.

[0784] Step 3:

[0785] The server analyzes the collected user response data and extracts common hobbies and values. For example, if User 1 answers "outdoor activities" and User 2 answers "mountain climbing and visiting art museums," "visiting art museums" is identified as a common hobby. The input is the response data of multiple users, and the output is the common hobbies and values. Specifically, the data analysis module performs comparison operations on the response data to extract commonalities.

[0786] Step 4:

[0787] The server uses a generative AI model to suggest date plans and conversation topics based on shared hobbies and values. For example, if "visiting art museums" is a common hobby, a "museum date plan" is generated. The input is common hobbies and values, and the output is an appropriate date plan. Specifically, the common points are input into the generative AI model as prompts, and the model generates appropriate date plans and topics.

[0788] Step 5:

[0789] The server displays the generated date plan and conversation topics on the user's smart device. The user can review this and use it when they go on an actual date. For example, a plan centered around "visiting art museums" is displayed on a smartphone. The generated date plan is the input, and the information displayed on the user's device is the output. Specifically, the generated plan and conversation topics are notified to the smart device and displayed in a format that the user can easily access.

[0790] 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.

[0791] This invention is a system for realizing smooth and enjoyable conversations on first dates, and by combining it with an emotion engine that recognizes the user's emotions, it makes more advanced suggestions. This system is composed of an interactive question processing module, a data analysis module, a suggestion module, and an emotion engine.

[0792] Interactive Question Processing Module

[0793] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the device. The user answers these questions, and the device collects the answers and sends them to the server. For example, User 1 answers "visiting art museums" to the question "What are your hobbies?", and User 2 answers "reading."

[0794] Data Analysis Module

[0795] The server passes the collected user response data to a data analysis module, which analyzes the responses of User 1 and User 2. This module identifies and lists common hobbies and values. For example, if User 1 and User 2 both enjoy "cafe hopping," that hobby is added to the list.

[0796] Emotion Engine

[0797] The server combines the analyzed data with an emotion engine that detects and recognizes the user's emotions based on the date course generated by the suggestion module. The emotion engine analyzes the user's facial expressions, tone of voice, and corresponding responses to determine positive or negative emotions. This information is fed back to the suggestion module.

[0798] Suggestion Module

[0799] The suggestion module generates specific date courses and conversation topics based on shared hobbies and values. Furthermore, based on feedback from the emotion engine, it prioritizes and suggests plans for which the user expressed positive emotions. For example, if "cafe hopping" is listed as a shared hobby and the user responded positively to it, it will generate and suggest a plan to visit recommended nearby cafes.

[0800] Specific examples

[0801] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[0802] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[0803] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[0804] 4. The suggestion module generates a specific date plan based on the shared hobby of "cafe hopping." Furthermore, the emotion engine analyzes the user's reactions and prioritizes date plans that show positive emotions.

[0805] 5. The server sends the generated plan to the device, which displays it to the user. The user can plan a date based on the proposed plan and enjoy natural conversation.

[0806] This system proposes date plans that take into consideration not only the user's hobbies and values, but also their emotions, thereby providing a more appropriate and satisfying date experience.

[0807] The processing flow will be explained below.

[0808] Step 1:

[0809] The server generates questions to understand the user's hobbies and values ​​and sends them to the device. For example, questions such as "What are your hobbies?" or "How do you spend your weekends?" are generated.

[0810] Step 2:

[0811] The device displays the received question to the user, who then answers it. For example, user 1 answers "visiting museums," and user 2 answers "reading books." The answers are then sent from the device to the server.

[0812] Step 3:

[0813] The server saves the user's answers and passes them to the data analysis module. Specifically, User 1's answer "visiting museums" and User 2's answer "reading books" are saved and sent to the data analysis module as their respective user data.

[0814] Step 4:

[0815] The data analysis module analyzes the users' responses and finds common hobbies and values. For example, if both User 1 and User 2 enjoy spending time at cafes, it identifies this as a common hobby.

[0816] Step 5:

[0817] The server passes the analysis results to the emotion engine, which then analyzes the user's emotions. The emotion engine detects emotions from the user's facial expressions and tone of voice and determines whether they are positive or negative.

[0818] Step 6:

[0819] The server passes the analysis results of the emotion engine to the suggestion module, which generates specific date plans and conversation topics based on common interests, values, and the user's emotional state.

[0820] Step 7:

[0821] For example, based on the shared hobby of "cafe hopping," the suggestion module generates a "date plan at a recommended cafe." This plan reflects the results of the emotion engine and is provided to users who show positive emotions.

[0822] Step 8:

[0823] The server sends the generated date plan to the terminal, which displays it to the user, who can then confirm the proposed plan and plan the details of the first date.

[0824] Step 9:

[0825] Based on the date plan proposed by the user, the conversation can proceed smoothly and the date can be enjoyed. The plan is based on common interests and feelings, promoting natural conversation.

[0826] The above are the specific processing steps of the system of the present invention. This system proposes date plans taking into consideration not only the user's hobbies and values ​​but also their emotions, thereby providing an appropriate and satisfying date experience.

[0827] Example 2

[0828] 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."

[0829] While existing systems for suggesting dates and conversations take into account a user's hobbies and values ​​to some extent, they lack the ability to analyze the user's emotional responses in real time and adjust the content of the suggestions based on that information. As a result, the system may suggest date plans or conversation topics that dissatisfy the user. The present invention aims to provide a system that takes into account the user's emotions and suggests more personalized date plans and conversation topics.

[0830] 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.

[0831] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to the user and collecting answers, means for analyzing the user's answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for detecting and recognizing the user's emotions, and means for adjusting the suggested content based on the emotion analysis results, thereby making it possible to suggest more appropriate and satisfying date plans and conversation topics that match the user's emotions and interests.

[0832] A "user" is a person who operates and interacts with a particular system.

[0833] A "hobby" is an activity or interest that an individual engages in for enjoyment.

[0834] "Values" refer to an individual's beliefs, creeds, and standards for evaluating things.

[0835] A question is a question asked to elicit specific information.

[0836] An "answer" is a response to a question or the content of the response.

[0837] "Data analysis" is the process of organizing and interpreting collected data to extract useful information and knowledge.

[0838] "Common" refers to characteristics or interests shared between two or more users.

[0839] "Analysis" is the process of breaking down data or information and revealing details.

[0840] An "emotion" is a psychological state or feeling experienced by an individual.

[0841] "Discovery" is the process of finding specific data or information.

[0842] "Cognition" is the ability to understand and grasp specific information or situations.

[0843] A "suggestion" is an action or content that recommends doing something.

[0844] "Means" are the methods or tools used to achieve a particular purpose.

[0845] A "date course" is a set of activities and places planned for a first meeting or for friends to enjoy together.

[0846] A "topic of conversation" is a central theme or topic of a conversation or discussion.

[0847] "Adjustment" is the process of making changes or modifications to suit specific conditions or circumstances.

[0848] This invention is a system for ensuring smooth and enjoyable conversations on first dates. This system is composed of a series of modules that analyze user response data and suggest conversation topics and date itineraries based on shared interests and values. It also analyzes the user's emotions in real time and reflects them in the suggestions to generate more personalized date plans.

[0849] This system consists of an interactive question processing module, a data analysis module, a proposal module, and an emotion engine. Each module is described in detail below.

[0850] Interactive Question Processing Module

[0851] The server generates multiple questions about the user's hobbies and values ​​and displays them through the terminal. For example, questions such as "What are your hobbies?" or "What is your favorite food?" are created and sent to the terminal. The terminal displays these questions to the user and collects the user's answers. The user enters the answers into the terminal, which then sends them to the server. Questions can be generated using an SQL database.

[0852] Data Analysis Module

[0853] The server passes the collected user response data to a data analysis module, which analyzes the responses of User 1 and User 2. This module uses data analysis software such as Python or R to identify and list common hobbies and values. For example, if User 1 answers "visiting art museums" and User 2 answers "reading," "cafe hopping" will be identified as a common hobby.

[0854] Emotion Engine

[0855] The server combines the analyzed data and the travel itinerary generated by the suggestion module with an emotion engine that detects and recognizes the user's emotions. The emotion engine uses image recognition technology (e.g., OpenCV) and voice analysis technology (e.g., Google Cloud Speech-to-Text) to analyze the user's facial expressions and voice tone and determine positive or negative emotions. This information is fed back to the suggestion module.

[0856] Suggestion Module

[0857] The suggestion module generates specific date courses and conversation topics based on the common interests and values ​​identified by the data analysis module. Furthermore, based on feedback from the emotion engine, it prioritizes and suggests plans for which the user expressed positive emotions. For example, if "cafe hopping" is identified as a common hobby and is judged positive by emotion analysis, it will generate and suggest a "plan to visit recommended nearby cafes."

[0858] Specific examples

[0859] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[0860] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[0861] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[0862] 4. The suggestion module generates a specific date plan based on the shared hobby of "cafe hopping." Furthermore, the emotion engine analyzes the user's reactions and prioritizes date plans that show positive emotions.

[0863] 5. The server sends the generated plan to the device, which displays it to the user. The user can then plan a date and enjoy conversation based on the plan.

[0864] This system proposes date plans that take into consideration not only the user's hobbies and values, but also their emotions, thereby providing a more appropriate and satisfying date experience.

[0865] Prompt Sentence Examples

[0866] "Design a system that generates date plans based on the user's hobbies and values, and optimizes the suggestions to the user through emotional analysis. Specifically, the system should be able to make suggestions based on shared hobbies and values, and provide the optimal date plan according to the user's emotional response."

[0867] This "Description of the Invention" clarifies the operation of the entire system and the role of each module, which can be used as a reference for other people to understand and practice this invention.

[0868] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0869] Step 1:

[0870] The server generates a number of questions about the user's hobbies and values.

[0871] Input: User information

[0872] For example, create a list of questions such as "What are your hobbies?" and "What is your favorite food?"

[0873] Output: Generated questionnaire list

[0874] The server sends this list of questions to the terminal.

[0875] Step 2:

[0876] The terminal displays the list of questions received from the server to the user.

[0877] Input: Generated questionnaire list

[0878] The users input answers to each question: User 1 answers "visiting museums," User 2 answers "reading books," and so on.

[0879] Output: User response data

[0880] The terminal transmits these response data to the server.

[0881] Step 3:

[0882] The server passes the user's response data sent from the terminal to the data analysis module.

[0883] Input: User response data

[0884] The data analysis module uses programming languages ​​such as Python to analyze user response data and identify common hobbies and values.

[0885] Output: A list of parsed common interests and values

[0886] Specifically, if user 1 answers "visiting art museums" and user 2 answers "reading," then "visiting cafes" is identified as a common hobby.

[0887] Step 4:

[0888] The server passes the analyzed data and the date plan generation data to the emotion engine.

[0889] Input: A list of parsed common interests and values

[0890] The emotion engine uses image recognition technology (such as OpenCV) and voice analysis technology (such as Google Cloud Speech-to-Text) to analyze the user's facial expressions and voice tone to determine positive and negative emotions.

[0891] Output: Emotion analysis results

[0892] As a specific example, if a user responds with a smile to a plan to "visit cafes," this is determined to be a positive reaction.

[0893] Step 5:

[0894] The suggestion module generates date plans based on the common interests and values ​​identified in the data analysis module.

[0895] Input: List of analyzed common hobbies and values ​​and sentiment analysis results

[0896] Based on the results of sentiment analysis, plans that users express positive emotions about are prioritized and suggested.

[0897] Output: prioritized date plans

[0898] For example, if "cafe hopping" is identified as a common hobby and a positive response is received, a plan to "visit recommended nearby cafes" will be generated.

[0899] Step 6:

[0900] The server transmits the generated date plan to the terminal.

[0901] Input: prioritized date plans

[0902] The terminal displays the date plan to the user.

[0903] Output: The date plan displayed to the user

[0904] The user can plan a date based on the proposed plan and enjoy conversation.

[0905] Through this series of processes, the system proposes optimal date plans that take into account the user's hobbies, values, and emotions, providing a more satisfying experience.

[0906] (Application example 2)

[0907] 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."

[0908] Modern systems that support date planning and communication often only consider the user's hobbies and values. As a result, the proposed date plans and conversation topics do not necessarily provide a positive experience for the user, without taking the user's emotions into account. Furthermore, there are only a limited number of systems that can provide a dating experience in a virtual space, leaving users in remote locations without a means to have a natural dating experience. In this situation, there is a growing need for a system that can appropriately detect and analyze the user's emotions and suggest date plans and conversation topics based on them.

[0909] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to users and collecting answers, means for analyzing the users' answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for analyzing the user's facial expressions and tone of voice using an emotion engine to determine emotions, and means for the user to enjoy a date in a virtual space. This makes it possible to suggest appropriate date plans and conversation topics that take into account the user's emotions as well as their hobbies and values, allowing users in remote locations to enjoy a natural dating experience in a virtual space.

[0910] "Hobbies and values" is a general term for activities that interest a user, beliefs, and things that a user finds desirable.

[0911] The "means for displaying questions" is a mechanism for presenting questions to users via their terminals and providing an interface for collecting answers.

[0912] A "means for collecting responses" is a system that stores the responses entered by users and stores them in a database for analysis.

[0913] "Means for analyzing response data" refers to algorithms or software that process response data collected from users and derive common interests and values.

[0914] "Means for identifying common interests and values" refers to a process for extracting common interests and beliefs among multiple users from the analysis results.

[0915] The "means for suggesting a date course" is a mechanism for generating appropriate date plans and conversation topics based on identified common interests and values.

[0916] An "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to determine whether they are expressing positive or negative emotions.

[0917] The "means for analyzing facial expressions and voice tones" refers to a software system that uses sensors such as a camera and microphone to collect the user's facial expressions and voice and analyze their emotions.

[0918] A "virtual dating platform" is an infrastructure or platform that allows users to interact with each other in a virtual reality environment and simulate a dating experience.

[0919] This invention relates to a system that allows users to enjoy a natural dating experience in a virtual space, and is composed of the following main components:

[0920] System Configuration

[0921] Interactive Question Processing Module

[0922] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the device. These questions are personalized based on the user's interests and past answer data. The user can answer the questions using smart glasses or a head-mounted display (HMD), and the answer data is sent to the server.

[0923] Data Analysis Module

[0924] The server passes the collected user response data to a data analysis module for analysis. This module uses algorithms and generative AI models to analyze the user response data and identify common hobbies and values. For example, if User 1 likes "visiting museums" and User 2 likes "reading," "cafe hopping" will be identified as a common hobby.

[0925] Emotion Engine

[0926] The server combines the analysis results passed from the data analysis module with an emotion engine that detects and recognizes the user's emotions in relation to the date plans generated by the suggestion module. The emotion engine analyzes the user's facial expressions and voice tone in real time to distinguish between positive and negative emotions. This information is fed back to the suggestion module. For example, if a user responds to a plan to "visit cafes" with a smile or a happy voice, it will be recognized as a positive emotion.

[0927] Suggestion Module

[0928] The suggestion module generates specific date plans based on shared hobbies and values. At this time, it prioritizes and suggests plans that the user expresses positive emotions about based on feedback from the emotion engine. For example, if "cafe hopping" is identified as a shared hobby and the user responds positively to it, it will generate and suggest a "plan to visit a virtual cafe together."

[0929] Implementation in virtual space

[0930] Users can wear smart glasses or an HMD and enjoy dates with other users in a virtual space. In this virtual space, users can experience various scenarios based on proposed date plans. For example, they can sit together and chat in a virtual cafe or virtually stroll through a museum.

[0931] Specific examples

[0932] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[0933] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[0934] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[0935] 4. Using the emotion engine, analyze the user's emotions from their facial expressions and voice, and if a positive reaction is shown, feed that data back to the suggestion module.

[0936] 5. The proposal module generates a specific date plan based on "cafe hopping" and sends it to the device for the user to enjoy in the virtual space.

[0937] Prompt Sentence Examples

[0938] If User 1 likes "visiting museums" and User 2 likes "reading," identify "cafe hopping" as a common hobby and generate topics that users can enjoy talking about in an online virtual cafe. Also, add questions and suggestions that elicit positive emotions based on the results of emotion analysis based on the user's facial expressions and tone of voice.

[0939] With the above system, users can enjoy conversations and dates while receiving appropriate suggestions tailored to their emotions and hobbies in real time through virtual dates.

[0940] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0941] Step 1:

[0942] The server generates multiple questions for the user about their hobbies and values, and displays them on the device. The user inputs answers to the questions using smart glasses or a head-mounted display (HMD). Input: Answers to the user's questions. Output: Answer data collected from the user.

[0943] Step 2:

[0944] The server passes the collected user response data to the data analysis module for analysis. The analysis module uses a generative AI model to identify common interests and values. Input: User response data. Output: List of common interests and values.

[0945] Step 3:

[0946] The server receives the analysis results from the data analysis module and passes them to the emotion engine. The emotion engine analyzes the user's facial expressions and voice tone to determine positive or negative emotions. Input: User's facial and voice data. Output: User's emotional state.

[0947] Step 4:

[0948] Based on the emotional data obtained from the emotion engine, the server proposes date plans and conversation topics based on common hobbies and values. Plans that elicit positive emotions are generated with priority. Input: A list of common hobbies and values ​​and the user's emotional state. Output: Specific date plans and conversation topics.

[0949] Step 5:

[0950] The server sends the date plans and conversation topics generated by the suggestion module to the device and displays them to the user. The user checks and selects the proposed plans through smart glasses or an HMD. Input: Specific date plans and conversation topics. Output: The plan selected by the user.

[0951] Step 6:

[0952] The device starts a date in a virtual space based on the user's selection. The virtual space provides the user with a realistic dating experience through smart glasses or an HMD. Input: A date plan selected by the user. Output: A dating experience in a virtual space.

[0953] Through the above steps, users can enjoy a date in a virtual space while receiving appropriate suggestions tailored to their emotions and hobbies in real time.

[0954] 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.

[0955] 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.

[0956] 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.

[0957] [Fourth embodiment]

[0958] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0959] 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.

[0960] 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).

[0961] 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.

[0962] 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.

[0963] 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).

[0964] 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.

[0965] 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.

[0966] 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.

[0967] 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.

[0968] 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.

[0969] 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.

[0970] 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."

[0971] The present invention is a system that allows users to smoothly advance conversations and enjoy a natural, enjoyable experience on first dates. The system consists of the following main modules: an interactive question processing module, a data analysis module, and a suggestion module.

[0972] Interactive Question Processing Module

[0973] The server generates multiple questions for the user about their hobbies and values. These questions are designed to dig deeper into the user's interests and lifestyle. The device displays these questions to the user and collects their answers. For example, if the server asks User 1, "What are your hobbies?" and the user answers, "Visiting art museums," the answer is sent to the server.

[0974] Data Analysis Module

[0975] The server passes the collected user response data to a data analysis module. This module compares the hobbies and values ​​of two users and extracts common hobbies and values. For example, if User 1 and User 2 both enjoy mountain climbing, the data analysis module will identify this as a common hobby.

[0976] Suggestion Module

[0977] The server passes the shared hobbies and values ​​obtained from the data analysis module to the suggestion module. This module generates specific date courses and conversation topics based on the identified shared hobbies and values. For example, if "mountain climbing" is a shared hobby, the suggestion module will suggest a "hiking course plan" and display it on the device. This allows users to smoothly start conversations on their first date and makes it easier to plan the date.

[0978] Specific examples

[0979] 1. The server generates questions such as "What are your hobbies?" and "What do you do on the weekends?" and sends them to the device.

[0980] 2. The device displays these questions to the users, and User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[0981] 3. The server passes the collected response data to the data analysis module to identify common interests and values.

[0982] 4. The data analysis module compares the data of User 1 and User 2 and identifies, for example, "outdoor activities" as a common hobby.

[0983] 5. The server passes the identified common interests to a suggestion module to generate a specific date plan.

[0984] 6. The proposal module generates a "Plan for enjoying a picnic in a nature park" and displays it on the device.

[0985] 7. Users can plan a first date based on the generated plan and naturally bring up the topic.

[0986] The above is a specific embodiment for carrying out the present invention. By using this system, it is possible to ease the tension of meeting someone for the first time and achieve smooth communication.

[0987] The processing flow will be explained below.

[0988] Step 1:

[0989] The server generates multiple questions to understand the user's hobbies and values ​​and sends them to the terminal, where the user is ready to answer the questions from the system.

[0990] Step 2:

[0991] The device displays the received question to the user and asks for an answer, such as "What are your hobbies?" or "What do you do on the weekend?"

[0992] Step 3:

[0993] The users answer the questions through their devices. User 1 answers "visiting art museums," and User 2 answers "mountain climbing." These answers are immediately sent to the server by the device.

[0994] Step 4:

[0995] The server saves the user responses received from the device and passes them to the data analysis module. The response data for User 1 and User 2 are analyzed.

[0996] Step 5:

[0997] The data analysis module compares the response data of User 1 and User 2 to identify common hobbies and values. For example, if User 1 likes "visiting art museums" and "reading at cafes," and User 2 likes "reading at cafes" and "watching movies," "reading at cafes" will be identified as a common hobby.

[0998] Step 6:

[0999] The server passes the common interests and values ​​obtained from the data analysis module to the suggestion module, which then creates a list of common interests and inputs them into the suggestion module.

[1000] Step 7:

[1001] The suggestion module generates specific date courses and conversation topics based on the identified common interests and values. For example, if "reading at a cafe" is a common interest, a plan suggesting a date at a nearby cafe will be generated.

[1002] Step 8:

[1003] The server transmits the generated date plan to the terminal, and the terminal displays the date plan to the user, allowing the user to plan a first date based on the proposed plan.

[1004] Step 9:

[1005] The user can check the proposed plan through the device and decide on the details of the first date, allowing the user to enjoy a smooth and comfortable first date.

[1006] The above are the specific processing steps of the system of the present invention, which helps users ease tension when meeting someone for the first time and enjoy natural conversation.

[1007] Example 1

[1008] 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."

[1009] On a first date, especially if it is difficult to find a conversation starter or common topics to talk about, users feel nervous and anxious, making it difficult to communicate smoothly. Therefore, there is a need for a means to make a first date go smoothly.

[1010] 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.

[1011] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to users and collecting answers, means for storing the collected user answer data in a database, means for analyzing the stored user answer data and identifying common hobbies and values ​​of the plurality of users, means for suggesting specific conversation topics and date courses using a generative AI model based on the identified common hobbies and values, and means for displaying the suggested conversation topics and date courses on the user's terminal. This reduces tension on first dates and enables users to have natural and enjoyable communication based on common hobbies and topics.

[1012] "User" refers to a person who uses the system.

[1013] "Questions about hobbies and values" refer to questions asked to find out the user's everyday interests and important beliefs.

[1014] "Means for collecting answers" refers to the function or device that receives and records the information entered by the user in response to the questions.

[1015] "Means for storing in a database" refers to a function or device that stores collected user response data in an organized and structured format.

[1016] "Means for analyzing data" refers to functions and technologies for processing saved response data, extracting meaning, and discovering commonalities between users.

[1017] "Means for identifying common interests and values" refers to a function or device that finds common interests and values ​​among multiple users based on analyzed data.

[1018] A "generative AI model" refers to a program or system that uses artificial intelligence techniques to automatically generate new information or suggestions.

[1019] "Means for suggesting conversation topics and date courses" refers to functions and technologies that provide specific topics to talk about and date plans based on users' shared hobbies and values.

[1020] "Terminal" refers to an electronic device used by a user to access the system and enter or receive information.

[1021] The present invention is a system that helps users smoothly advance conversations and enjoy natural conversations during first dates. This system consists of the following main modules: an interactive question processing module, a data analysis module, and a suggestion module.

[1022] Interactive Question Processing Module

[1023] The server uses the generative AI model to generate multiple questions for the user about their hobbies and values. This allows for deeper insight into the user's interests and lifestyle, allowing for more accurate data collection. An example of a specific prompt is "Please generate questions about the user's hobbies." The server sends the generated questions to the device, which then displays them to the user. The user answers the displayed questions, and the device sends the answers to the server for collection.

[1024] Data Analysis Module

[1025] The server stores the collected user response data in a database. The stored response data is analyzed by a data analysis module. This module uses an AI algorithm to compare the responses of multiple users and identify common hobbies and values. For example, if User 1 and User 2 are both interested in "outdoor activities," this will be identified as a common hobby.

[1026] Suggestion Module

[1027] The server passes the shared hobbies and values ​​obtained from the data analysis module to the suggestion module. The suggestion module uses a generative AI model to generate specific date plans and conversation topics. For example, based on the shared hobby of "outdoor activities," the module suggests a plan to "enjoy a picnic in a nature park." The server sends the generated plan to the device, which then displays the proposal to the user.

[1028] Specific examples

[1029] 1. The server uses a generative AI model to generate questions such as "What are your hobbies?" and "What do you do on the weekend?"

[1030] 2. The device displays these questions to the users, and User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[1031] 3. The server receives the response data sent from the terminal and stores it in a database.

[1032] 4. The data analysis module analyzes the stored data and identifies the common hobby of User 1 and User 2 as "outdoor activities."

[1033] 5. The proposal module generates a plan for enjoying a picnic in a nature park based on common interests.

[1034] 6. The server sends this plan to the device, which displays the proposal to the user.

[1035] This allows the system to help users find common ground during first dates and promote smooth conversation. Detailed embodiments of the invention allow users to communicate naturally and enjoyably.

[1036] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1037] Step 1:

[1038] Question Generation

[1039] The server uses the generative AI model to generate multiple questions for the user about their hobbies and values. As input, it passes the prompt sentence "Generate questions about the user's hobbies" to the AI ​​model. As output, it obtains generated example questions such as "What are your hobbies?" and "What do you do on the weekend?". Specifically, the server processes the prompt sentence through the AI ​​model and obtains questions to elicit answers.

[1040] Step 2:

[1041] Submit a Question

[1042] The server sends the generated question to the terminal. The question generated in step 1 is used as input. The output is data that allows the generated question to be displayed on the terminal. In concrete terms, the server sends the question data to the terminal via the network.

[1043] Step 3:

[1044] Collecting user responses

[1045] The terminal displays the question received from the server to the user. The question data sent in step 2 is used as input. The answer data entered by the user is obtained as output. In concrete terms, the terminal displays the question to the user, and the user enters the answer. Consider an example in which User 1 answers "visiting art museums" and User 2 answers "mountain climbing."

[1046] Step 4:

[1047] Sending response data

[1048] The terminal sends the user's answer to the server. The answer data obtained in step 3 is used as input. The answer data is saved on the server as output. Specifically, the terminal sends the answer data to the server via the network.

[1049] Step 5:

[1050] Saving response data

[1051] The server receives the user's response data sent from the terminal and saves it in the database. The response data sent in step 4 is used as input. The response data is saved in the database as output. The specific operation is to store the data received by the server in the database.

[1052] Step 6:

[1053] Data analysis

[1054] The server passes the response data to the data analysis module, which analyzes the responses of the two users. The response data stored in the database is used as input. The output is the identification of common hobbies and values. Specifically, the data analysis module uses an AI algorithm to analyze the response data and find commonalities. For example, it identifies "outdoor activities" as a common hobby between User 1 and User 2.

[1055] Step 7:

[1056] Proposal Generation

[1057] The server passes the common hobbies and values ​​obtained from the data analysis module to the suggestion module. The analysis results obtained in step 6 are used as input. Specific date plans and conversation topics are generated as output. Specifically, the suggestion module uses a generative AI model to generate suggestions based on the analysis results. For example, it generates a "plan to enjoy a picnic in a nature park."

[1058] Step 8:

[1059] View Suggestions

[1060] The server sends the generated date plan to the terminal. The date plan generated in step 7 is used as input. The date plan is displayed on the terminal as output. In concrete terms, the server sends the proposed data to the terminal via the network. The terminal displays the proposed date plan to the user, allowing the user to confirm the plan.

[1061] In this way, processing involving specific actions and data flows is carried out at each step, allowing the user to have a natural and enjoyable dating experience.

[1062] (Application example 1)

[1063] 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."

[1064] Conventional systems that suggest date plans and conversation topics have difficulty making appropriate suggestions based on the user's hobbies and values, which can lead to tension and conversation breakdowns on first dates. Furthermore, there is a lack of a way to dig deeper into the user's interests and values, which can cause problems with conversations on first dates.

[1065] 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.

[1066] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to the user and collecting answers, means for analyzing the user's answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for displaying date plans and conversation topics using a smart device, means for generating prompt sentences that utilize the analysis results for date plans based on the collected data, and means for selecting an appropriate date plan using a generative AI model. This allows users to smoothly advance conversations on their first dates and reduce tension.

[1067] A "user" refers to a person who uses the system and is the entity that inputs their hobbies and values.

[1068] "Multiple questions about hobbies and values" refers to questions that dig deeper into the user's interests and lifestyle, and are necessary for smooth communication when meeting for the first time.

[1069] "Response data" refers to the information and selections provided by users in response to questions, and is data used for analysis.

[1070] "Analysis" refers to the process of finding similarities and differences based on collected response data, and may involve the use of statistical methods or machine learning.

[1071] "Common hobbies and values" refer to interests and beliefs that are shared between different users, and form the basis for date plans and conversation topics.

[1072] "Specific conversation topics" refer to themes of conversation during a first date that are generated based on common hobbies and values.

[1073] A "date course" refers to a plan of activities and locations suggested for a user to actually go on a date.

[1074] "Smart devices" refers to electronic devices that can connect to the Internet, such as smartphones, tablets, smart glasses, and head-mounted displays.

[1075] "Prompt sentences to be used for date planning" refer to sentences generated to suggest appropriate date plans to users, and are input into the generative AI model.

[1076] "Generative AI model" refers to an artificial intelligence model used to generate optimal date plans and conversation topics based on user data.

[1077] This invention is implemented as an application system called Smart Date Planner. This system is composed of the following main means:

[1078] Displaying questions about hobbies and values ​​and collecting answers

[1079] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the screen of the smart device. The user inputs answers to these questions. For example, questions may be in the form of "What are your hobbies?" or "What do you do on the weekends?" These answers are sent to the server and saved for analysis.

[1080] Data analysis

[1081] The server uses a data analysis module to analyze the collected user response data and extract common hobbies and values. This module compares data between users to find patterns of common interests and lifestyles. For example, if User 1 answers "visiting art museums" as a hobby and User 2 answers "mountain climbing" and "visiting art museums" as hobbies, the common hobby will be identified as "visiting art museums."

[1082] Date planning and conversation topic suggestions

[1083] The server uses a suggestion module to suggest date courses and conversation topics based on shared hobbies and values ​​obtained from the data analysis module. Specifically, it uses a generative AI model to suggest appropriate date plans. In this case, prompts are generated based on the collected data. For example, if "visiting art museums" is a shared hobby, a "museum date plan" will be suggested and displayed on the user's smart device. Through this process, users can smoothly advance conversations on their first date.

[1084] Hardware and software used

[1085] This system uses smart devices such as smartphones and tablets. The server uses Python, with application frameworks (e.g., Flask and Django) as needed. Machine learning libraries (e.g., TensorFlow and PyTorch) are used for data analysis and generative AI models.

[1086] Specific examples

[1087] User 1 and User 2 first install the app and answer questions about their hobbies and values. For example, if User 1 answers "visiting art museums" and User 2 answers "mountain climbing and visiting art museums," the server analyzes this data and identifies "visiting art museums" as a common hobby. The suggestion module then generates a "museum date plan" and displays it on the smartphone screen.

[1088] Prompt Sentence Examples

[1089] "User, please answer the question: What are your hobbies?"

[1090] "Tell me how you spend your weekends."

[1091] In this way, by implementing the present invention, users can smoothly advance conversations and have fun on first dates, and can easily plan appropriate dates to ease tension.

[1092] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1093] Step 1:

[1094] The server generates multiple questions for the user about their hobbies and values ​​and sends them to the smart device. The user answers these questions using a smartphone or tablet. For example, the user might answer "visiting art museums" to the question "What are your hobbies?" The input is the questions generated by the server, and the output is the user's answer data. Specifically, the server generates a list of questions and sends them to the terminal. The terminal displays the questions and receives the user's input.

[1095] Step 2:

[1096] The server stores the user's response data sent from the device in a database. For example, a response such as "visiting art museums" is recorded in the database. The user's response data is input, and as output, it is converted into a format that can be saved in the database. Specifically, the data received on the server side is converted into a format that is easy to analyze and stored in the database.

[1097] Step 3:

[1098] The server analyzes the collected user response data and extracts common hobbies and values. For example, if User 1 answers "outdoor activities" and User 2 answers "mountain climbing and visiting art museums," "visiting art museums" is identified as a common hobby. The input is the response data of multiple users, and the output is the common hobbies and values. Specifically, the data analysis module performs comparison operations on the response data to extract commonalities.

[1099] Step 4:

[1100] The server uses a generative AI model to suggest date plans and conversation topics based on shared hobbies and values. For example, if "visiting art museums" is a common hobby, a "museum date plan" is generated. The input is common hobbies and values, and the output is an appropriate date plan. Specifically, the common points are input into the generative AI model as prompts, and the model generates appropriate date plans and topics.

[1101] Step 5:

[1102] The server displays the generated date plan and conversation topics on the user's smart device. The user can review this and use it when they go on an actual date. For example, a plan centered around "visiting art museums" is displayed on a smartphone. The generated date plan is the input, and the information displayed on the user's device is the output. Specifically, the generated plan and conversation topics are notified to the smart device and displayed in a format that the user can easily access.

[1103] 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.

[1104] This invention is a system for realizing smooth and enjoyable conversations on first dates, and by combining it with an emotion engine that recognizes the user's emotions, it makes more advanced suggestions. This system is composed of an interactive question processing module, a data analysis module, a suggestion module, and an emotion engine.

[1105] Interactive Question Processing Module

[1106] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the device. The user answers these questions, and the device collects the answers and sends them to the server. For example, User 1 answers "visiting art museums" to the question "What are your hobbies?", and User 2 answers "reading."

[1107] Data Analysis Module

[1108] The server passes the collected user response data to a data analysis module, which analyzes the responses of User 1 and User 2. This module identifies and lists common hobbies and values. For example, if User 1 and User 2 both enjoy "cafe hopping," that hobby is added to the list.

[1109] Emotion Engine

[1110] The server combines the analyzed data with an emotion engine that detects and recognizes the user's emotions based on the date course generated by the suggestion module. The emotion engine analyzes the user's facial expressions, tone of voice, and corresponding responses to determine positive or negative emotions. This information is fed back to the suggestion module.

[1111] Suggestion Module

[1112] The suggestion module generates specific date courses and conversation topics based on shared hobbies and values. Furthermore, based on feedback from the emotion engine, it prioritizes and suggests plans for which the user expressed positive emotions. For example, if "cafe hopping" is listed as a shared hobby and the user responded positively to it, it will generate and suggest a plan to visit recommended nearby cafes.

[1113] Specific examples

[1114] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[1115] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[1116] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[1117] 4. The suggestion module generates a specific date plan based on the shared hobby of "cafe hopping." Furthermore, the emotion engine analyzes the user's reactions and prioritizes date plans that show positive emotions.

[1118] 5. The server sends the generated plan to the device, which displays it to the user. The user can plan a date based on the proposed plan and enjoy natural conversation.

[1119] This system proposes date plans that take into consideration not only the user's hobbies and values, but also their emotions, thereby providing a more appropriate and satisfying date experience.

[1120] The processing flow will be explained below.

[1121] Step 1:

[1122] The server generates questions to understand the user's hobbies and values ​​and sends them to the device. For example, questions such as "What are your hobbies?" or "How do you spend your weekends?" are generated.

[1123] Step 2:

[1124] The device displays the received question to the user, who then answers it. For example, user 1 answers "visiting museums," and user 2 answers "reading books." The answers are then sent from the device to the server.

[1125] Step 3:

[1126] The server saves the user's answers and passes them to the data analysis module. Specifically, User 1's answer "visiting museums" and User 2's answer "reading books" are saved and sent to the data analysis module as their respective user data.

[1127] Step 4:

[1128] The data analysis module analyzes the users' responses and finds common hobbies and values. For example, if both User 1 and User 2 enjoy spending time at cafes, it identifies this as a common hobby.

[1129] Step 5:

[1130] The server passes the analysis results to the emotion engine, which then analyzes the user's emotions. The emotion engine detects emotions from the user's facial expressions and tone of voice and determines whether they are positive or negative.

[1131] Step 6:

[1132] The server passes the analysis results of the emotion engine to the suggestion module, which generates specific date plans and conversation topics based on common interests, values, and the user's emotional state.

[1133] Step 7:

[1134] For example, based on the shared hobby of "cafe hopping," the suggestion module generates a "date plan at a recommended cafe." This plan reflects the results of the emotion engine and is provided to users who show positive emotions.

[1135] Step 8:

[1136] The server sends the generated date plan to the terminal, which displays it to the user, who can then confirm the proposed plan and plan the details of the first date.

[1137] Step 9:

[1138] Based on the date plan proposed by the user, the conversation can proceed smoothly and the date can be enjoyed. The plan is based on common interests and feelings, promoting natural conversation.

[1139] The above are the specific processing steps of the system of the present invention. This system proposes date plans taking into consideration not only the user's hobbies and values ​​but also their emotions, thereby providing an appropriate and satisfying date experience.

[1140] Example 2

[1141] 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."

[1142] While existing systems for suggesting dates and conversations take into account a user's hobbies and values ​​to some extent, they lack the ability to analyze the user's emotional responses in real time and adjust the content of the suggestions based on that information. As a result, the system may suggest date plans or conversation topics that dissatisfy the user. The present invention aims to provide a system that takes into account the user's emotions and suggests more personalized date plans and conversation topics.

[1143] 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.

[1144] In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to the user and collecting answers, means for analyzing the user's answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for detecting and recognizing the user's emotions, and means for adjusting the suggested content based on the emotion analysis results, thereby making it possible to suggest more appropriate and satisfying date plans and conversation topics that match the user's emotions and interests.

[1145] A "user" is a person who operates and interacts with a particular system.

[1146] A "hobby" is an activity or interest that an individual engages in for enjoyment.

[1147] "Values" refer to an individual's beliefs, creeds, and standards for evaluating things.

[1148] A question is a question asked to elicit specific information.

[1149] An "answer" is a response to a question or the content of the response.

[1150] "Data analysis" is the process of organizing and interpreting collected data to extract useful information and knowledge.

[1151] "Common" refers to characteristics or interests shared between two or more users.

[1152] "Analysis" is the process of breaking down data or information and revealing details.

[1153] An "emotion" is a psychological state or feeling experienced by an individual.

[1154] "Discovery" is the process of finding specific data or information.

[1155] "Cognition" is the ability to understand and grasp specific information or situations.

[1156] A "suggestion" is an action or content that recommends doing something.

[1157] "Means" are the methods or tools used to achieve a particular purpose.

[1158] A "date course" is a set of activities and places planned for a first meeting or for friends to enjoy together.

[1159] A "topic of conversation" is a central theme or topic of a conversation or discussion.

[1160] "Adjustment" is the process of making changes or modifications to suit specific conditions or circumstances.

[1161] This invention is a system for ensuring smooth and enjoyable conversations on first dates. This system is composed of a series of modules that analyze user response data and suggest conversation topics and date itineraries based on shared interests and values. It also analyzes the user's emotions in real time and reflects them in the suggestions to generate more personalized date plans.

[1162] This system consists of an interactive question processing module, a data analysis module, a proposal module, and an emotion engine. Each module is described in detail below.

[1163] Interactive Question Processing Module

[1164] The server generates multiple questions about the user's hobbies and values ​​and displays them through the terminal. For example, questions such as "What are your hobbies?" or "What is your favorite food?" are created and sent to the terminal. The terminal displays these questions to the user and collects the user's answers. The user enters the answers into the terminal, which then sends them to the server. Questions can be generated using an SQL database.

[1165] Data Analysis Module

[1166] The server passes the collected user response data to a data analysis module, which analyzes the responses of User 1 and User 2. This module uses data analysis software such as Python or R to identify and list common hobbies and values. For example, if User 1 answers "visiting art museums" and User 2 answers "reading," "cafe hopping" will be identified as a common hobby.

[1167] Emotion Engine

[1168] The server combines the analyzed data and the travel itinerary generated by the suggestion module with an emotion engine that detects and recognizes the user's emotions. The emotion engine uses image recognition technology (e.g., OpenCV) and voice analysis technology (e.g., Google Cloud Speech-to-Text) to analyze the user's facial expressions and voice tone and determine positive or negative emotions. This information is fed back to the suggestion module.

[1169] Suggestion Module

[1170] The suggestion module generates specific date courses and conversation topics based on the common interests and values ​​identified by the data analysis module. Furthermore, based on feedback from the emotion engine, it prioritizes and suggests plans for which the user expressed positive emotions. For example, if "cafe hopping" is identified as a common hobby and is judged positive by emotion analysis, it will generate and suggest a "plan to visit recommended nearby cafes."

[1171] Specific examples

[1172] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[1173] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[1174] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[1175] 4. The suggestion module generates a specific date plan based on the shared hobby of "cafe hopping." Furthermore, the emotion engine analyzes the user's reactions and prioritizes date plans that show positive emotions.

[1176] 5. The server sends the generated plan to the device, which displays it to the user. The user can then plan a date and enjoy conversation based on the plan.

[1177] This system proposes date plans that take into consideration not only the user's hobbies and values, but also their emotions, thereby providing a more appropriate and satisfying date experience.

[1178] Prompt Sentence Examples

[1179] "Design a system that generates date plans based on the user's hobbies and values, and optimizes the suggestions to the user through emotional analysis. Specifically, the system should be able to make suggestions based on shared hobbies and values, and provide the optimal date plan according to the user's emotional response."

[1180] This "Description of the Invention" clarifies the operation of the entire system and the role of each module, which can be used as a reference for other people to understand and practice this invention.

[1181] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1182] Step 1:

[1183] The server generates a number of questions about the user's hobbies and values.

[1184] Input: User information

[1185] For example, create a list of questions such as "What are your hobbies?" and "What is your favorite food?"

[1186] Output: Generated questionnaire list

[1187] The server sends this list of questions to the terminal.

[1188] Step 2:

[1189] The terminal displays the list of questions received from the server to the user.

[1190] Input: Generated questionnaire list

[1191] The users input answers to each question: User 1 answers "visiting museums," User 2 answers "reading books," and so on.

[1192] Output: User response data

[1193] The terminal transmits these response data to the server.

[1194] Step 3:

[1195] The server passes the user's response data sent from the terminal to the data analysis module.

[1196] Input: User response data

[1197] The data analysis module uses programming languages ​​such as Python to analyze user response data and identify common hobbies and values.

[1198] Output: A list of parsed common interests and values

[1199] Specifically, if user 1 answers "visiting art museums" and user 2 answers "reading," then "visiting cafes" is identified as a common hobby.

[1200] Step 4:

[1201] The server passes the analyzed data and the date plan generation data to the emotion engine.

[1202] Input: A list of parsed common interests and values

[1203] The emotion engine uses image recognition technology (such as OpenCV) and voice analysis technology (such as Google Cloud Speech-to-Text) to analyze the user's facial expressions and voice tone to determine positive and negative emotions.

[1204] Output: Emotion analysis results

[1205] As a specific example, if a user responds with a smile to a plan to "visit cafes," this is determined to be a positive reaction.

[1206] Step 5:

[1207] The suggestion module generates date plans based on the common interests and values ​​identified in the data analysis module.

[1208] Input: List of analyzed common hobbies and values ​​and sentiment analysis results

[1209] Based on the results of sentiment analysis, plans that users express positive emotions about are prioritized and suggested.

[1210] Output: prioritized date plans

[1211] For example, if "cafe hopping" is identified as a common hobby and a positive response is received, a plan to "visit recommended nearby cafes" will be generated.

[1212] Step 6:

[1213] The server transmits the generated date plan to the terminal.

[1214] Input: prioritized date plans

[1215] The terminal displays the date plan to the user.

[1216] Output: The date plan displayed to the user

[1217] The user can plan a date based on the proposed plan and enjoy conversation.

[1218] Through this series of processes, the system proposes optimal date plans that take into account the user's hobbies, values, and emotions, providing a more satisfying experience.

[1219] (Application example 2)

[1220] 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."

[1221] Modern systems that support date planning and communication often only consider the user's hobbies and values. As a result, the proposed date plans and conversation topics do not necessarily provide a positive experience for the user, without taking the user's emotions into account. Furthermore, there are only a limited number of systems that can provide a dating experience in a virtual space, leaving users in remote locations without a means to have a natural dating experience. In this situation, there is a growing need for a system that can appropriately detect and analyze the user's emotions and suggest date plans and conversation topics based on them.

[1222] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for displaying a plurality of questions about hobbies and values ​​to users and collecting answers, means for analyzing the users' answer data and identifying common hobbies and values, means for suggesting specific conversation topics and date courses based on the identified common hobbies and values, means for analyzing the user's facial expressions and tone of voice using an emotion engine to determine emotions, and means for the user to enjoy a date in a virtual space. This makes it possible to suggest appropriate date plans and conversation topics that take into account the user's emotions as well as their hobbies and values, allowing users in remote locations to enjoy a natural dating experience in a virtual space.

[1223] "Hobbies and values" is a general term for activities that interest a user, beliefs, and things that a user finds desirable.

[1224] The "means for displaying questions" is a mechanism for presenting questions to users via their terminals and providing an interface for collecting answers.

[1225] A "means for collecting responses" is a system that stores the responses entered by users and stores them in a database for analysis.

[1226] "Means for analyzing response data" refers to algorithms or software that process response data collected from users and derive common interests and values.

[1227] "Means for identifying common interests and values" refers to a process for extracting common interests and beliefs among multiple users from the analysis results.

[1228] The "means for suggesting a date course" is a mechanism for generating appropriate date plans and conversation topics based on identified common interests and values.

[1229] An "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to determine whether they are expressing positive or negative emotions.

[1230] The "means for analyzing facial expressions and voice tones" refers to a software system that uses sensors such as a camera and microphone to collect the user's facial expressions and voice and analyze their emotions.

[1231] A "virtual dating platform" is an infrastructure or platform that allows users to interact with each other in a virtual reality environment and simulate a dating experience.

[1232] This invention relates to a system that allows users to enjoy a natural dating experience in a virtual space, and is composed of the following main components:

[1233] System Configuration

[1234] Interactive Question Processing Module

[1235] The server generates multiple questions for the user about their hobbies and values ​​and displays them on the device. These questions are personalized based on the user's interests and past answer data. The user can answer the questions using smart glasses or a head-mounted display (HMD), and the answer data is sent to the server.

[1236] Data Analysis Module

[1237] The server passes the collected user response data to a data analysis module for analysis. This module uses algorithms and generative AI models to analyze the user response data and identify common hobbies and values. For example, if User 1 likes "visiting museums" and User 2 likes "reading," "cafe hopping" will be identified as a common hobby.

[1238] Emotion Engine

[1239] The server combines the analysis results passed from the data analysis module with an emotion engine that detects and recognizes the user's emotions in relation to the date plans generated by the suggestion module. The emotion engine analyzes the user's facial expressions and voice tone in real time to distinguish between positive and negative emotions. This information is fed back to the suggestion module. For example, if a user responds to a plan to "visit cafes" with a smile or a happy voice, it will be recognized as a positive emotion.

[1240] Suggestion Module

[1241] The suggestion module generates specific date plans based on shared hobbies and values. At this time, it prioritizes and suggests plans that the user expresses positive emotions about based on feedback from the emotion engine. For example, if "cafe hopping" is identified as a shared hobby and the user responds positively to it, it will generate and suggest a "plan to visit a virtual cafe together."

[1242] Implementation in virtual space

[1243] Users can wear smart glasses or an HMD and enjoy dates with other users in a virtual space. In this virtual space, users can experience various scenarios based on proposed date plans. For example, they can sit together and chat in a virtual cafe or virtually stroll through a museum.

[1244] Specific examples

[1245] 1. The server generates questions such as "What are your hobbies?" and "What is your favorite food?" and displays them to the user via the terminal.

[1246] 2. In response to the question displayed on the device, User 1 answers "visiting art museums" and User 2 answers "reading books."

[1247] 3. The server passes these response data to the data analysis module, which identifies and lists "cafe hopping" as a common hobby.

[1248] 4. Using the emotion engine, analyze the user's emotions from their facial expressions and voice, and if a positive reaction is shown, feed that data back to the suggestion module.

[1249] 5. The proposal module generates a specific date plan based on "cafe hopping" and sends it to the device for the user to enjoy in the virtual space.

[1250] Prompt Sentence Examples

[1251] If User 1 likes "visiting museums" and User 2 likes "reading," identify "cafe hopping" as a common hobby and generate topics that users can enjoy talking about in an online virtual cafe. Also, add questions and suggestions that elicit positive emotions based on the results of emotion analysis based on the user's facial expressions and tone of voice.

[1252] With the above system, users can enjoy conversations and dates while receiving appropriate suggestions tailored to their emotions and hobbies in real time through virtual dates.

[1253] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1254] Step 1:

[1255] The server generates multiple questions for the user about their hobbies and values, and displays them on the device. The user inputs answers to the questions using smart glasses or a head-mounted display (HMD). Input: Answers to the user's questions. Output: Answer data collected from the user.

[1256] Step 2:

[1257] The server passes the collected user response data to the data analysis module for analysis. The analysis module uses a generative AI model to identify common interests and values. Input: User response data. Output: List of common interests and values.

[1258] Step 3:

[1259] The server receives the analysis results from the data analysis module and passes them to the emotion engine. The emotion engine analyzes the user's facial expressions and voice tone to determine positive or negative emotions. Input: User's facial and voice data. Output: User's emotional state.

[1260] Step 4:

[1261] Based on the emotional data obtained from the emotion engine, the server proposes date plans and conversation topics based on common hobbies and values. Plans that elicit positive emotions are generated with priority. Input: A list of common hobbies and values ​​and the user's emotional state. Output: Specific date plans and conversation topics.

[1262] Step 5:

[1263] The server sends the date plans and conversation topics generated by the suggestion module to the device and displays them to the user. The user checks and selects the proposed plans through smart glasses or an HMD. Input: Specific date plans and conversation topics. Output: The plan selected by the user.

[1264] Step 6:

[1265] The device starts a date in a virtual space based on the user's selection. The virtual space provides the user with a realistic dating experience through smart glasses or an HMD. Input: A date plan selected by the user. Output: A dating experience in a virtual space.

[1266] Through the above steps, users can enjoy a date in a virtual space while receiving appropriate suggestions tailored to their emotions and hobbies in real time.

[1267] 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.

[1268] 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.

[1269] 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.

[1270] 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.

[1271] 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.

[1272] 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.

[1273] 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).

[1274] 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.

[1275] 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."

[1276] 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.

[1277] 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).

[1278] 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.

[1279] 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.

[1280] 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.

[1281] 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.

[1282] 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.

[1283] 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.

[1284] 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.

[1285] 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.

[1286] 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.

[1287] 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.

[1288] The following is further disclosed regarding the above embodiment.

[1289] (Claim 1)

[1290] A means for displaying a plurality of questions about hobbies and values ​​to a user and collecting answers;

[1291] A means of analyzing user response data to identify common interests and values,

[1292] A means to suggest specific conversation topics and date courses based on identified common interests and values,

[1293] A system including:

[1294] (Claim 2)

[1295] 2. The system according to claim 1, wherein the means for suggesting a date course based on common hobbies and values ​​includes means for selecting a date course from a database of predefined date plans.

[1296] (Claim 3)

[1297] 2. The system of claim 1, further comprising means for probing the user's interests and values ​​in the form of interactive questions.

[1298] "Example 1"

[1299] (Claim 1)

[1300] A means for displaying a plurality of questions about hobbies and values ​​to a user and collecting answers;

[1301] A means for storing the collected user response data in a database;

[1302] A means for analyzing saved user response data and identifying common interests and values ​​of multiple users;

[1303] A means of using generative AI models to suggest specific conversation topics and date courses based on identified shared interests and values; and

[1304] a means for displaying suggested conversation topics and date courses on a user's device;

[1305] A system including:

[1306] (Claim 2)

[1307] 2. The system according to claim 1, further comprising means for selecting a date course based on common interests and values ​​from a database of predefined date plans.

[1308] (Claim 3)

[1309] 2. The system of claim 1, further comprising means for probing the user's interests and values ​​in the form of interactive questions.

[1310] "Application Example 1"

[1311] (Claim 1)

[1312] A means for displaying a plurality of questions about hobbies and values ​​to a user and collecting answers;

[1313] A means of analyzing user response data to identify common interests and values,

[1314] A means to suggest specific conversation topics and date courses based on identified common interests and values,

[1315] A means for displaying date plans and conversation topics using a smart device;

[1316] A means for generating prompt sentences that utilize the analysis results based on the collected data for date planning;

[1317] A means for selecting an appropriate date plan using a generative AI model;

[1318] A system including:

[1319] (Claim 2)

[1320] 2. The system according to claim 1, wherein the means for suggesting a date course based on common hobbies and values ​​includes means for selecting a date course from a database of predefined date plans.

[1321] (Claim 3)

[1322] 2. The system of claim 1, further comprising means for probing the user's interests and values ​​in the form of interactive questions.

[1323] "Example 2: Combining Emotion Engines"

[1324] (Claim 1)

[1325] A means for displaying a plurality of questions about hobbies and values ​​to a user and collecting answers;

[1326] A means of analyzing user response data to identify common interests and values,

[1327] A means to suggest specific conversation topics and date courses based on identified common interests and values,

[1328] A means for detecting and recognizing user emotions;

[1329] a means for adjusting the content of the suggestions based on the sentiment analysis results;

[1330] ...

[1331] A system including:

[1332] (Claim 2)

[1333] 2. The system according to claim 1, wherein the means for suggesting a date course based on common hobbies and values ​​includes means for selecting a date course from a database of predefined date plans.

[1334] (Claim 3)

[1335] 2. The system of claim 1, further comprising means for probing the user's interests and values ​​in the form of interactive questions.

[1336] "Application example 2 when combining emotion engines"

[1337] (Claim 1)

[1338] A means for displaying a plurality of questions about hobbies and values ​​to a user and collecting answers;

[1339] A means of analyzing user response data to identify common interests and values,

[1340] A means to suggest specific conversation topics and date courses based on identified common interests and values,

[1341] A means for analyzing a user's facial expression and tone of voice using an emotion engine to determine the user's emotion;

[1342] A means for users to enjoy dating in a virtual space,

[1343] A system including:

[1344] (Claim 2)

[1345] The system of claim 1, wherein the means for suggesting a date course based on common hobbies and values ​​includes a means for selecting a date course from a database of predefined date plans and a means for generating conversation topics that elicit positive emotions based on the analysis results of the emotion engine.

[1346] (Claim 3)

[1347] 2. The system according to claim 1, further comprising: means for probing the user's interests and values ​​in the form of interactive questions; and means for naturally conducting a dialogue in the virtual space. [Explanation of symbols]

[1348] 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 displaying a plurality of questions about hobbies and values ​​to a user and collecting answers; A means of analyzing user response data to identify common interests and values, A means to suggest specific conversation topics and date courses based on identified common interests and values, A system including:

2. 2. The system according to claim 1, wherein the means for proposing a date course based on common hobbies and values ​​includes means for selecting a date course from a database of predefined date plans.

3. 2. The system according to claim 1, further comprising means for probing the user's interests and values ​​in the form of interactive questions.

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