system

Abstract

We provide the system. [Solution] A means of collecting interest data from users of different age groups and generating personalized conversations using natural language processing technology based on that data, A means of selecting and providing activities that stimulate cognitive function according to the user's age and interests, A means of analyzing the emotional states of users during their interactions and activities, and providing responses and support as needed. A system that includes means for suggesting interaction activities among users with common interests.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, the aging process is advancing, and along with it, the decline of cognitive function and social isolation of the elderly have become major problems. Also, among the younger generation, there is a lack of communication experience with the elderly, which is a concern that may have an adverse effect on the development of sociality. In such a situation, new means are required to enable dementia prevention through active communication between different generations and improve the quality of individual lives.

Means for Solving the Problems

[0005] This invention provides a system that collects interest data from users of different age groups and generates personalized conversations using natural language processing technology based on that data. Furthermore, it aims to maintain brain function by selecting and providing activities that stimulate cognitive function according to the user's age and interests. It also promotes better interaction by analyzing the emotional state of users during conversations and activities and providing necessary responses and support. In addition, it deepens intergenerational bonds and strengthens social connections by suggesting interaction activities between users with common interests. In this way, it aims to maintain cognitive function in the elderly and promote the development of social skills in young people.

[0006] "Interest data" is a collection of information that shows each user's hobbies, preferences, experiences, and areas of interest.

[0007] "Natural language processing technology" is a general term for technologies that enable computers to understand, generate, and respond to human language.

[0008] "Personalized conversation" refers to generating and providing conversations with content and themes tailored to specific users, based on their individual interests and preferences.

[0009] "Activities that stimulate cognitive function" refer to activities such as questions, games, and tasks aimed at maintaining or improving the user's brain function.

[0010] "Analysis of emotional state" is a process of collecting data on the responses shown by users during conversations and activities, and then analyzing what emotions the users are currently experiencing based on that data.

[0011] "Exchange activities" are events and programs proposed to promote communication and collaborative work among users who share common interests. [Brief explanation of the drawing]

[0012] [Figure 1]This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0016] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0017] In the following embodiments, a labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0018] In the following embodiments, a labeled communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), etc.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] This invention is a system that promotes dialogue and interaction between elderly and younger users, aiming to maintain cognitive function and strengthen social connections. The main embodiments of the invention are shown below.

[0034] The system's core is a server, which has the function of collecting and analyzing user interest data. The server stores data such as basic information (age and hobbies) provided by users during registration, survey responses, and past conversation history in a database. Based on this data, the server uses natural language processing technology to generate personalized conversations tailored to each user.

[0035] The device interactively displays generated conversation content and activity suggestions to the user. The displayed content is tailored to the user's age and interests. For example, the device might ask an elderly user, "Tell me about your favorite gardening activity lately." The user's responses are used for further analysis by the server.

[0036] The system also features a function to analyze the user's emotional state in real time. This emotion analysis allows the server to detect the user's reactions during conversations and activities, and to provide the user with necessary support and encouragement messages as needed. For example, if the user is showing signs of anxiety, a message such as "Please let me know if there is anything I can do to help" will be displayed on the device.

[0037] Furthermore, the server generates suggestions to facilitate interaction among users. These suggestions are based on common interests and themes across different generations and are offered in the form of online or offline events. For example, younger users might be offered a suggestion such as, "Why not participate in a virtual gardening workshop to enjoy with seniors?"

[0038] For example, if an elderly person A and a young person B use this system, the server will generate conversation topics and activities based on A's extensive experience in gardening. At the same time, it will incorporate B's interest in outdoor activities, providing conversations and activities that both can enjoy.

[0039] In this way, the present invention provides a system that promotes interaction between different generations, maintains cognitive function, and deepens social bonds, and specifically illustrates embodiments based on the claims.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] Users log into the system and answer questionnaires about their basic information and interests. These responses include age, hobbies, and past activities.

[0043] Step 2:

[0044] The server receives the information provided by the user and stores it in a database. This data is saved as a specific profile for each user.

[0045] Step 3:

[0046] The server analyzes the accumulated data and uses natural language processing technology to generate conversation topics and questions that are best suited to the user. This process takes into account the user's interests and past conversation history.

[0047] Step 4:

[0048] The terminal displays the conversation content generated by the server to the user. For example, the terminal might display a specific question such as, "Tell me about your recent gardening activities."

[0049] Step 5:

[0050] The user enters answers or responses based on prompts displayed on the device. These answers will be used for analysis in the next stage.

[0051] Step 6:

[0052] The server receives user input data and performs sentiment analysis. Based on the analysis results, it adjusts necessary support messages and suggestions for the next conversation.

[0053] Step 7:

[0054] Based on the results of sentiment analysis and profile data, the server suggests activities that promote intergenerational interaction. These include virtual events and shared hobbies.

[0055] Step 8:

[0056] The device notifies the user of activity information suggested by the server and prompts them to choose whether or not they are interested.

[0057] Step 9:

[0058] Users select proposals that interest them and provide feedback to the system indicating their willingness to participate. This information will be used to improve future proposals.

[0059] (Example 1)

[0060] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0061] In modern society, a lack of interaction between different generations is a problem, leading to concerns about social isolation and cognitive decline among the elderly. Furthermore, younger generations face challenges due to limited opportunities to share different perspectives and experiences. To address these issues, a system is needed that promotes smooth communication between both generations and strengthens social connections.

[0062] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0063] In this invention, the server includes means for collecting interest data from different age groups and generating personalized conversations using a generative model based on that data; means for analyzing the emotional state of users during conversations and activities and providing necessary responses and support; and means for interactively displaying the generated conversation content and activity suggestions to users via a terminal. This facilitates conversations between elderly and younger users, enabling the maintenance of cognitive function and the strengthening of social connections.

[0064] "Different age groups" refers to a collection of individuals or groups belonging to different generations, and is a social division that mainly includes the elderly and younger generations.

[0065] "Interest data" is a collection of information about a user's hobbies, preferences, and activities, and is used to provide a personalized experience.

[0066] A "generative model" is an algorithm or system that automatically generates new content, particularly natural language conversations, based on input data.

[0067] "Personalized conversation" refers to dialogue content that is customized to take into account the individual characteristics and interests of each user.

[0068] "Emotional state" is an indicator that shows the user's current psychological state, and is mainly inferred from language and facial expressions.

[0069] "Interactive display" refers to a format in which information is presented in a way that allows users to receive and respond to information interactively through their devices.

[0070] "Support" refers to assistance, advice, and encouraging messages provided according to the user's needs.

[0071] An "intergenerational exchange event" refers to an activity or gathering in which people from different generations can participate based on common interests or themes.

[0072] This invention is a system that promotes dialogue and interaction between elderly and younger users, thereby maintaining cognitive function and strengthening social connections. The system primarily consists of a server and terminals, and provides a personalized experience utilizing a generative AI model.

[0073] The server collects basic information provided by the user (age, hobbies), past conversation history, and survey responses, and stores them in a database. MySQL® or PostgreSQL can be used as the database management system for this purpose. Based on this information, the server generates conversation content tailored to the user using a generative AI model (e.g., GPT-4®). During this generation process, specific conversations are elicited by providing prompts such as "Generate questions related to the user's interests."

[0074] The terminal's role is to interactively display conversation content and activity suggestions sent from the server to the user. Specifically, it is designed to allow users to easily participate in communication via a touchscreen or voice interface. Users can convey their opinions and feelings to the system by directly reacting to the display on the terminal.

[0075] The server also analyzes text and voice data in real time to assess the user's emotional state. This process can utilize an emotion analysis API (for example, Google® Cloud Natural Language API). Based on the results of the emotion analysis, the server provides appropriate responses and encouragement tailored to the user's feelings. For example, if the user shows anxiety, a message such as "Please let me know if there is anything I can do to help" will be displayed on the device.

[0076] Furthermore, the server generates suggestions to uncover common interests across different generations and promote intergenerational interaction. These suggestions are presented as online or offline events. By suggesting specific events to younger users, such as "Why not participate in a virtual gardening workshop to enjoy with seniors?", the aim is to deepen intergenerational bonds.

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

[0078] Step 1:

[0079] The server collects basic user information (age, hobbies), past conversation history, and survey responses. The input data is information provided by the user during registration and is recorded in the database. A database management system (e.g., MySQL, PostgreSQL) is used to build user profiles, which serve as the basis for subsequent processing.

[0080] Step 2:

[0081] The server uses a generative AI model (e.g., GPT-4) based on the collected data to generate personalized conversations. The input is the interest data collected in step 1, and by sending prompt sentences to the model, output conversations tailored to individual users are generated. This generated conversation content serves as material for subsequent interactions.

[0082] Step 3:

[0083] The terminal receives the conversation content generated by the server and displays it interactively to the user. The input is the conversation data generated in step 2, which is presented via a touchscreen or voice interface. The user can directly respond to the displayed questions and suggestions. Specific actions include the user tapping the screen to select an answer.

[0084] Step 4:

[0085] The server analyzes text and audio data obtained from user interactions in real time to evaluate their emotional state. The input data consists of user responses on the device, which are processed using an emotion analysis API to obtain output indicating the user's emotional state. Based on the obtained emotion analysis results, the server provides appropriate responses and support.

[0086] Step 5:

[0087] The server generates event suggestions to promote intergenerational interaction based on user information. Inputs include past activity history and current emotional state, and the server considers this to suggest events, either online or offline, that match the user. Specifically, it might suggest things like "participating in a virtual gardening workshop to enjoy with seniors," providing output to promote intergenerational interaction.

[0088] (Application Example 1)

[0089] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0090] In modern society, interaction between different age groups is decreasing, leading to problems such as cognitive decline among the elderly and feelings of isolation among younger generations. Therefore, there is a need for means to promote interaction across age groups and deepen mutual understanding. In particular, given the current difficulty in naturally building intergenerational relationships within local communities, there is a need for efficient and effective systems.

[0091] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0092] In this invention, the server includes means for collecting interest information from users of different age groups and generating personalized conversations using natural language processing technology based on that information; means for selecting and providing activities that stimulate cognitive functions according to the user's age and interests; and means for using information on local events and activities to suggest activities suitable for the user. This makes it possible to naturally promote interaction across age groups and deepen mutual understanding.

[0093] "Different age groups" refers to groups of people of different ages within a society, particularly the elderly and younger generations.

[0094] "Interest information" refers to information related to the user's interests and hobbies.

[0095] "Natural language processing technology" is the technology that processes and understands human language using computers.

[0096] "Personalized conversation" refers to dialogue content that is customized to the individual user's characteristics and interests.

[0097] "Cognitive function" refers to the ability to understand information and solve problems, and is important for maintaining the health of the elderly.

[0098] "Local community events and activities information" refers to information about events and activities that take place within a specific region.

[0099] "Suggesting activities suitable for the user" means recommending activities that match the user's interests and circumstances.

[0100] This invention provides a system to facilitate interaction between users of different age groups. The server collects user interest information and stores it in a database using cloud computing technology. Based on basic information provided by the user, survey responses, and past conversation history, personalized conversations are generated using natural language processing technology. Examples of natural language processing APIs used here include the Google Cloud Natural Language API.

[0101] The terminal displays personalized conversation content and local event information sent from the server to the user. Based on this information, suggestions are made to encourage participation in social activities and events that match the user's interests. This not only helps maintain the user's cognitive function but also deepens their connection with the local community.

[0102] Furthermore, the server has the capability to analyze the user's emotional state in real time. Based on the results of the emotional analysis, it provides the user with necessary support and encouraging messages. AI technology is applied to this analysis. For example, an emotional recognition service such as Microsoft's Cognitive Services may be used.

[0103] As a concrete example, the system might suggest "recent favorite gardening topics" to older users, while simultaneously recommending "participation in local recycling activities" to younger users. In such a case, a possible prompt message might be, "Based on the user's interests, suggest local events they can participate in. Examples: gardening, outdoor activities."

[0104] In this way, the aim is to promote natural interaction among users of different age groups and to foster a sense of unity with the local community.

[0105] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0106] Step 1:

[0107] The server collects user registration information. It receives basic information (age, hobbies, etc.) and survey responses provided by the user as input. This data is stored in a database and processed as foundational data for extracting information about the user's interests.

[0108] Step 2:

[0109] The server analyzes past conversation history. It uses records of past conversations as input, and analyzes preferences and patterns based on that data using natural language processing techniques. As output, it generates personalized conversation content for each user.

[0110] Step 3:

[0111] The server selects and prepares recommended activities for the user. The inputs used are interest information and information on local events and activities. This information is obtained from the internet. Based on this, a generative AI model is used to create optimal activity suggestions. The output is a list of specific events and activities.

[0112] Step 4:

[0113] The terminal presents information to the user. As input, it displays personalized conversation content and suggested activity information received from the server. A user interface (UI) is provided to help the user determine if they are able to participate. As output, the user is presented with the dialogue and activity suggestions.

[0114] Step 5:

[0115] Users provide feedback on proposed activities. Input involves indicating their willingness to participate in the proposed activities displayed on their device, or responding to topics that interest them. Output involves transferring preferences and participation intentions to the server, which are then used to inform future proposals.

[0116] Step 6:

[0117] The server performs sentiment analysis on the user. It receives data obtained from the user's statements and actions as input to the sentiment analysis engine. As output, it determines the emotional state, generates appropriate support messages, and sends them to the user.

[0118] Step 7:

[0119] The device displays necessary support messages to facilitate a better experience. It receives sentiment analysis results from the server as input and presents encouraging and cautionary messages to the user. As output, it provides appropriate feedback to the user.

[0120] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0121] This invention is a system that promotes dialogue and interaction among users of different age groups, improves users' cognitive functions, and strengthens social connections. In particular, it is characterized by its effectiveness in evaluating users' emotional states using an emotion engine and providing optimal responses and activities based on those evaluations.

[0122] The server collects each user's interest data and past conversation history, and stores this in a database. This enables the generation of personalized conversations optimized for each user. Furthermore, natural language processing technology is used to analyze the content of conversations between users and generate new conversation themes based on that analysis.

[0123] A key component of this system is the emotion engine, which evaluates the user's emotional state. The emotion engine analyzes the user's text and voice data to recognize their current emotions in real time. This information is combined with the user's profile data for analysis, providing the basis for optimal conversation content and activities.

[0124] The device displays personalized conversations and activities sent from the server to the user through a user interface. For example, the device might ask the user, "How are you feeling today?" and adjust the next conversation and suggestions based on the user's response.

[0125] Furthermore, based on the analysis results from the emotion engine, the server can provide users with appropriate support messages and words of encouragement. For example, if a user is showing signs of stress, the server might send a message such as, "Shall we think about ways to relax together?" In this way, more personalized support is provided, helping to deepen the bonds between users.

[0126] As a concrete example, when an elderly user A and a younger user B use the system, the server generates topics based on A's experiences and themes that interest B. At the same time, the emotional engine evaluates the emotional state of both users and provides support to improve the quality of the conversation. If the younger user B shows signs of stress, the server suggests a relaxing exercise to A as a follow-up, helping to deepen their mutual understanding.

[0127] Thus, the present invention aims to promote meaningful interaction between different generations and enhance cognitive function and social connections through a system that includes an emotion engine.

[0128] The following describes the processing flow.

[0129] Step 1:

[0130] Users access the system and answer questionnaires about their basic information and interests. These questionnaires include questions about age, hobbies, and past activities.

[0131] Step 2:

[0132] The server receives data collected from users and stores it in a database. This data is managed as a user profile and used for subsequent processing.

[0133] Step 3:

[0134] The server analyzes accumulated user data and uses natural language processing technology to generate personalized conversation content and dialogue themes. In doing so, it takes into account the user's interests and preferences.

[0135] Step 4:

[0136] The terminal displays the conversation content generated by the server to the user. The content presented may include, for example, discussion topics based on the user's interests or specific questions.

[0137] Step 5:

[0138] The user responds and inputs based on the presented conversation content. During this process, the emotion engine receives the user's input data and performs emotion analysis in real time.

[0139] Step 6:

[0140] The server evaluates the user's emotional state based on the analysis results from the emotion engine. Based on this evaluation, it adjusts the conversation content and generates support messages.

[0141] Step 7:

[0142] The device displays adjusted conversation content and supportive messages tailored to the user's emotional state. For example, if the device determines that the user is tired, it will display messages suggesting ways to relax or encouraging them to take a break.

[0143] Step 8:

[0144] The server uses emotion engine data to suggest interaction activities based on shared interests among users. These suggested activities include online events and discussions based on common topics.

[0145] Step 9:

[0146] Users review the activity suggestions displayed on their devices, select those that interest them, and participate. This feedback is sent to the server and influences future suggestions.

[0147] (Example 2)

[0148] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0149] In modern society, a lack of interaction among users of different age groups is a cause of social isolation and cognitive decline. This can potentially impair users' physical and mental health and social connections. Furthermore, conventional systems have struggled to adequately understand users' emotional states and provide appropriate dialogue and support. It is necessary to address these challenges and improve users' social interaction and cognitive function.

[0150] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0151] In this invention, the server includes means for collecting characteristic information of users of different age groups and generating personalized dialogues using language analysis technology based on that information; means for analyzing the user's voice and text information using a machine learning model and evaluating their emotions in real time; and means for integrating the user's emotional state and profile information to generate material for providing optimal dialogue content and actions. This promotes meaningful interaction among users of different age groups and, by providing support tailored to their emotions, enables improvement of users' cognitive functions and strengthens their social connections.

[0152] "Characteristic information" refers to information, including a user's interests, age, and past behavioral history, that is used to identify a user and provide a personalized experience.

[0153] "Language analysis technology" refers to the technology that allows computer systems to analyze text and audio data obtained from users, understand their meaning, and generate responses.

[0154] "Personalized dialogue" refers to a type of dialogue that is optimized and personalized based on the user's interests, preferences, and emotional state.

[0155] A "machine learning model" refers to a technical framework in which algorithms are trained using large amounts of data to make predictions and decisions based on new data.

[0156] "Real-time emotional assessment" refers to a process that instantly analyzes information obtained from voice and text to immediately recognize the user's emotional state.

[0157] "Profile information" refers to a comprehensive set of information that summarizes a user's attributes, history, interests, behavioral patterns, and more.

[0158] "Materials for providing dialogue content and actions" refers to information and data used to suggest appropriate communication and activities according to the user's emotions and interests.

[0159] "User cognitive function" refers to the brain's ability to acquire, understand, and apply information, enabling conscious thinking and problem-solving.

[0160] "Social connections" refer to the human relationships and networks formed through users influencing and supporting each other.

[0161] This invention is a system that promotes dialogue and interaction among users of different age groups, enhances users' cognitive functions, and strengthens social connections. Specific embodiments for carrying out this invention are described below.

[0162] First, the server plays a central role in data collection. The server collects user characteristic information and stores it in a database. This information includes interests, age, and past behavioral history. Then, using language analysis technology, it generates personalized dialogue optimized for the user. The server uses generative AI models, such as OpenAI's GPT, to form the dialogue content. Voice and text information is collected with the user's permission and used as characteristic information.

[0163] Next, the emotion engine connects to the server, analyzes the user's voice and text data, and evaluates their emotions in real time. This engine uses emotion analysis algorithms to evaluate the user's emotional state as numerical data, providing the server with the necessary information.

[0164] The terminal then provides the user with personalized conversations and action suggestions received from the server. The terminal's user interface operates on hardware devices such as smartphones and tablets, enabling interaction with the user. Specifically, the terminal displays prompts on the screen such as "How are you feeling today?" and allows the user to input how they are feeling.

[0165] Users experience interactions and activities based on personalized conversations and suggestions presented by the device. For example, when elderly and young users use the system, the system generates topics tailored to their respective interests and provides support to improve the quality of the conversation based on their emotional state.

[0166] An example of a prompt might be: "Please suggest a dialogue topic that takes into account the user's current emotional state and promotes meaningful interaction between different age groups."

[0167] In this way, the system aims to promote interaction between different generations and improve users' cognitive function and social connections.

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] The server collects user characteristic information. As input, it retrieves user registration data, interest data, and past conversation history. To store this data in the database, it converts and organizes it into a structured format. This process prepares the foundational data for future conversation generation. Specifically, it uses APIs to retrieve data from external sources and stores it in internal data storage.

[0171] Step 2:

[0172] The emotion engine analyzes the user's voice and text data. It receives voice and text input from the user via their device as input. Using an analysis algorithm, it detects the emotional state from each data point and outputs it as numerical data. Specifically, it uses speech recognition software to convert voice to text, and then processes that text with the emotion analysis algorithm.

[0173] Step 3:

[0174] The server generates personalized conversations based on collected trait information and sentiment data. It uses user trait information and sentiment data as input to send prompts to the generative AI model. The output is a conversation optimized for the user. Specifically, it calls the generative AI model and sends data via an API to generate prompt sentences.

[0175] Step 4:

[0176] The terminal presents the user with personalized conversations retrieved from the server. It uses conversation data received from the server as input. As output, it displays the conversation content on the user interface and prompts the user for a response. Specifically, it displays prompts through the screen display and receives user input.

[0177] Step 5:

[0178] The server updates the content it provides based on user feedback. It receives user responses and comments sent from the terminal as input. As output, it saves the feedback to a database and incorporates it into future dialogue generation. Specifically, it analyzes the response data and adds newly obtained data to the characteristic information.

[0179] Through these steps, the system provides a personalized experience based on the user's emotions and interests, and promotes meaningful interaction between different age groups.

[0180] (Application Example 2)

[0181] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0182] There is a need to facilitate communication among users of different age groups and provide appropriate conversations and activities based on the emotional state of the users, thereby improving cognitive function and strengthening social connections.

[0183] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0184] In this invention, the server includes means for collecting interest data from users of different age groups and generating personalized conversations using natural language processing technology based on that data; means for selecting and providing activities that stimulate cognitive functions according to the user's age and interests; means for analyzing the emotional state of users during conversations and activities and providing necessary responses and support; and means for adjusting optimal conversations and suggestions in real time based on the user's emotional state to support communication through online dialogue. This promotes meaningful interaction between different generations and enables improvement of users' cognitive functions and strengthening of social connections.

[0185] "Different age groups" refers to groups of users of different ages, such as elderly people and young people.

[0186] "Interest data" refers to information about the things and hobbies that users are interested in, which enables the delivery of personalized content.

[0187] "Natural language processing technology" is a technology that processes human language using computers, and is used for tasks such as text generation and sentiment analysis.

[0188] "Personalized conversation" refers to dialogue content optimized based on the individual user's interests and emotions, with the aim of providing meaningful conversations for the user.

[0189] "Activities that stimulate cognitive function" refer to activities designed to improve users' cognitive abilities, such as memory and thinking skills.

[0190] "Emotional state" refers to the emotions a user feels in a particular situation, encompassing psychological states such as joy, sadness, and stress.

[0191] "Responses and support" refers to replies, helpful actions, and messages provided in response to the user's statements and emotions.

[0192] "Exchange activities" refer to activities in which different users interact with each other and communicate based on common interests and themes.

[0193] "Real-time adjustment" refers to a state where the system's responses and suggestions are immediately optimized based on user feedback.

[0194] The system for implementing this invention consists of a server, a terminal, and a user working together. The server collects interest data from users of different age groups and stores it in a database. Using natural language processing technology, it generates personalized conversations based on the collected data. The Google Natural Language API is used to achieve this natural language processing. The server also uses IBM Watson® Tone Analyzer to analyze the user's emotional state and personalize responses as needed.

[0195] The device visually and audibly presents personalized conversations and activities sent from the server to the user. This allows the user to enjoy interesting content in real time. By using a mobile device such as a smartphone, the device provides a user-friendly interface.

[0196] Users provide feedback on the information received via their devices, and the conversation is adjusted in real time based on this feedback. This system facilitates meaningful dialogue between older and younger generations, leading to improved cognitive function and strengthened social connections.

[0197] As a concrete example, consider a case where a grandmother and grandchild living far apart use this system to deepen their online connection. When the grandmother starts talking about caring for her garden plants, the system can analyze her interests and provide more detailed gardening tips. This allows the grandmother to continue the conversation with her grandchild on a variety of topics, leading to natural communication.

[0198] An example of a prompt to the generation AI model is, "Generate conversation topics that both older and younger users can enjoy." Through this prompt, the system generates new ideas to enrich interactions between users of different age groups.

[0199] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0200] Step 1:

[0201] The server collects user interest data from a database. The input is user profile information (age, hobbies, past conversation history, etc.), and the output is a dataset organized for personalized conversation generation. This data is used to prepare for identifying conversation topics suitable for each user.

[0202] Step 2:

[0203] The server generates personalized conversations using the Google Natural Language API based on the collected data. The input is user interest data, and the output is a conversation script presented to the user. A natural language processing engine then creates the most optimal conversation flow for the user.

[0204] Step 3:

[0205] The server uses IBM Watson Tone Analyzer to analyze the user's emotional state. Input is user voice and text data, and output is real-time evaluated emotional state data. Based on this analysis, the server identifies the user's emotions and prepares an appropriate response.

[0206] Step 4:

[0207] The device presents the user with personalized conversation and activity suggestions sent from the server through a user interface. Input consists of conversation scripts and suggested activities from the server, while output is a visual and auditory representation of the content on the user interface. This allows the user to initiate a dialogue.

[0208] Step 5:

[0209] The user provides feedback while interacting through the device. Input is the user's responses and interactions, and output is feedback data sent to the server. Based on this feedback, the server adjusts the next conversation or activity.

[0210] Step 6:

[0211] The server analyzes user feedback in real time and adjusts the conversation topic and activities as needed. Inputs include feedback data and analyzed sentiment states, while outputs include updated dialogue scripts and activity suggestions. This ensures the conversation flows optimally.

[0212] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0213] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0214] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0215] [Second Embodiment]

[0216] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0217] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0218] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0219] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0220] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0221] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0222] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0223] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0224] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0225] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0226] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0227] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0228] This invention is a system that promotes dialogue and interaction between elderly and younger users, aiming to maintain cognitive function and strengthen social connections. The main embodiments of the invention are shown below.

[0229] The system's core is a server, which has the function of collecting and analyzing user interest data. The server stores data such as basic information (age and hobbies) provided by users during registration, survey responses, and past conversation history in a database. Based on this data, the server uses natural language processing technology to generate personalized conversations tailored to each user.

[0230] The device interactively displays generated conversation content and activity suggestions to the user. The displayed content is tailored to the user's age and interests. For example, the device might ask an elderly user, "Tell me about your favorite gardening activity lately." The user's responses are used for further analysis by the server.

[0231] The system also features a function to analyze the user's emotional state in real time. This emotion analysis allows the server to detect the user's reactions during conversations and activities, and to provide the user with necessary support and encouragement messages as needed. For example, if the user is showing signs of anxiety, a message such as "Please let me know if there is anything I can do to help" will be displayed on the device.

[0232] Furthermore, the server generates suggestions to facilitate interaction among users. These suggestions are based on common interests and themes across different generations and are offered in the form of online or offline events. For example, younger users might be offered a suggestion such as, "Why not participate in a virtual gardening workshop to enjoy with seniors?"

[0233] For example, if an elderly person A and a young person B use this system, the server will generate conversation topics and activities based on A's extensive experience in gardening. At the same time, it will incorporate B's interest in outdoor activities, providing conversations and activities that both can enjoy.

[0234] In this way, the present invention provides a system that promotes interaction between different generations, maintains cognitive function, and deepens social bonds, and specifically illustrates embodiments based on the claims.

[0235] The following describes the processing flow.

[0236] Step 1:

[0237] Users log into the system and answer questionnaires about their basic information and interests. These responses include age, hobbies, and past activities.

[0238] Step 2:

[0239] The server receives the information provided by the user and stores it in a database. This data is saved as a specific profile for each user.

[0240] Step 3:

[0241] The server analyzes the accumulated data and uses natural language processing technology to generate conversation topics and questions that are best suited to the user. This process takes into account the user's interests and past conversation history.

[0242] Step 4:

[0243] The terminal displays the conversation content generated by the server to the user. For example, the terminal might display a specific question such as, "Tell me about your recent gardening activities."

[0244] Step 5:

[0245] The user enters answers or responses based on prompts displayed on the device. These answers will be used for analysis in the next stage.

[0246] Step 6:

[0247] The server receives user input data and performs sentiment analysis. Based on the analysis results, it adjusts necessary support messages and suggestions for the next conversation.

[0248] Step 7:

[0249] Based on the results of sentiment analysis and profile data, the server suggests activities that promote intergenerational interaction. These include virtual events and shared hobbies.

[0250] Step 8:

[0251] The device notifies the user of activity information suggested by the server and prompts them to choose whether or not they are interested.

[0252] Step 9:

[0253] Users select proposals that interest them and provide feedback to the system indicating their willingness to participate. This information will be used to improve future proposals.

[0254] (Example 1)

[0255] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0256] In modern society, a lack of interaction between different generations is a problem, leading to concerns about social isolation and cognitive decline among the elderly. Furthermore, younger generations face challenges due to limited opportunities to share different perspectives and experiences. To address these issues, a system is needed that promotes smooth communication between both generations and strengthens social connections.

[0257] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0258] In this invention, the server includes means for collecting interest data from different age groups and generating personalized conversations using a generative model based on that data; means for analyzing the emotional state of users during conversations and activities and providing necessary responses and support; and means for interactively displaying the generated conversation content and activity suggestions to users via a terminal. This facilitates conversations between elderly and younger users, enabling the maintenance of cognitive function and the strengthening of social connections.

[0259] "Different age groups" refers to a collection of individuals or groups belonging to different generations, and is a social division that mainly includes the elderly and younger generations.

[0260] "Interest data" is a collection of information about a user's hobbies, preferences, and activities, and is used to provide a personalized experience.

[0261] A "generative model" is an algorithm or system that automatically generates new content, particularly natural language conversations, based on input data.

[0262] "Personalized conversation" refers to dialogue content that is customized to take into account the individual characteristics and interests of each user.

[0263] "Emotional state" is an indicator that shows the user's current psychological state, and is mainly inferred from language and facial expressions.

[0264] "Interactive display" refers to a format in which information is presented in a way that allows users to receive and respond to information interactively through their devices.

[0265] "Support" refers to assistance, advice, and encouraging messages provided according to the user's needs.

[0266] An "intergenerational exchange event" refers to an activity or gathering in which people from different generations can participate based on common interests or themes.

[0267] This invention is a system that promotes dialogue and interaction between elderly and younger users, thereby maintaining cognitive function and strengthening social connections. The system primarily consists of a server and terminals, and provides a personalized experience utilizing a generative AI model.

[0268] The server collects basic information provided by the user (age, hobbies), past conversation history, and survey responses, and stores them in a database. MySQL or PostgreSQL can be used as the database management system for this purpose. Based on this information, the server generates conversation content tailored to the user using a generative AI model (e.g., GPT-4). During this generation process, specific conversations are elicited by providing prompts such as "Generate questions related to the user's interests."

[0269] The terminal's role is to interactively display conversation content and activity suggestions sent from the server to the user. Specifically, it is designed to allow users to easily participate in communication via a touchscreen or voice interface. Users can convey their opinions and feelings to the system by directly reacting to the display on the terminal.

[0270] The server also analyzes text and audio data in real time to assess the user's emotional state. This process can utilize an emotion analysis API (such as the Google Cloud Natural Language API). Based on the emotion analysis results, the server provides appropriate responses and encouragement tailored to the user's feelings. For example, if the user expresses anxiety, the server might display a message on the device such as, "Please let me know if there's anything I can do to help."

[0271] Furthermore, the server generates suggestions to uncover common interests across different generations and promote intergenerational interaction. These suggestions are presented as online or offline events. By suggesting specific events to younger users, such as "Why not participate in a virtual gardening workshop to enjoy with seniors?", the aim is to deepen intergenerational bonds.

[0272] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0273] Step 1:

[0274] The server collects basic user information (age, hobbies), past conversation history, and survey responses. The input data is information provided by the user during registration and is recorded in the database. A database management system (e.g., MySQL, PostgreSQL) is used to build user profiles, which serve as the basis for subsequent processing.

[0275] Step 2:

[0276] The server uses a generative AI model (e.g., GPT-4) based on the collected data to generate personalized conversations. The input is the interest data collected in step 1, and by sending prompt sentences to the model, output conversations tailored to individual users are generated. This generated conversation content serves as material for subsequent interactions.

[0277] Step 3:

[0278] The terminal receives the conversation content generated by the server and displays it interactively to the user. The input is the conversation data generated in step 2, which is presented via a touchscreen or voice interface. The user can directly respond to the displayed questions and suggestions. Specific actions include the user tapping the screen to select an answer.

[0279] Step 4:

[0280] The server analyzes text and audio data obtained from user interactions in real time to evaluate their emotional state. The input data consists of user responses on the device, which are processed using an emotion analysis API to obtain output indicating the user's emotional state. Based on the obtained emotion analysis results, the server provides appropriate responses and support.

[0281] Step 5:

[0282] The server generates event proposals for promoting communication across generations based on user information. The input is the past activity history and the current emotional state, and based on this, events that match the user are proposed online or offline. Specifically, proposals such as "participation in a virtual gardening workshop to have fun with the elderly" are made to provide an output for promoting communication across generations.

[0283] (Application Example 1)

[0284] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0285] In modern society, communication between different age groups has decreased, and problems such as the decline in the cognitive functions of the elderly and the sense of isolation among the younger generation have emerged. Therefore, means for promoting communication across age groups and deepening mutual understanding are required. In particular, in the current situation where it is difficult to naturally build intergenerational relationships in local communities, it is necessary to provide an efficient and effective system.

[0286] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0287] In this invention, the server includes means for collecting the interest information of users in different age groups and generating personalized conversations using natural language processing technology based on that information, means for selecting and providing activities that stimulate cognitive functions according to the age and interests of the users, and means for using information on events and activities in the local community to propose activities suitable for the users. Thereby, it becomes possible to naturally promote communication across age groups and deepen mutual understanding.

[0288] "Different age groups" refers to groups with different ages existing in society, particularly the elderly and the younger generation.

[0289] "Interest information" refers to information related to matters and hobbies that the user is interested in.

[0290] "Natural language processing technology" is the technology that processes and understands human language using computers.

[0291] "Personalized conversation" refers to dialogue content that is customized to the individual user's characteristics and interests.

[0292] "Cognitive function" refers to the ability to understand information and solve problems, and is important for maintaining the health of the elderly.

[0293] "Local community events and activities information" refers to information about events and activities that take place within a specific region.

[0294] "Suggesting activities suitable for the user" means recommending activities that match the user's interests and circumstances.

[0295] This invention provides a system to facilitate interaction between users of different age groups. The server collects user interest information and stores it in a database using cloud computing technology. Based on basic information provided by the user, survey responses, and past conversation history, personalized conversations are generated using natural language processing technology. Examples of natural language processing APIs used here include the Google Cloud Natural Language API.

[0296] The terminal displays personalized conversation content and local event information sent from the server to the user. Based on this information, suggestions are made to encourage participation in social activities and events that match the user's interests. This not only helps maintain the user's cognitive function but also deepens their connection with the local community.

[0297] Furthermore, the server has the capability to analyze the user's emotional state in real time. Based on the results of the emotional analysis, it provides the user with necessary support and encouraging messages. AI technology is applied to this analysis. For example, an emotional recognition service such as Microsoft's Cognitive Services may be used.

[0298] As a concrete example, the system might suggest "recent favorite gardening topics" to older users, while simultaneously recommending "participation in local recycling activities" to younger users. In such a case, a possible prompt message might be, "Based on the user's interests, suggest local events they can participate in. Examples: gardening, outdoor activities."

[0299] In this way, the aim is to promote natural interaction among users of different age groups and to foster a sense of unity with the local community.

[0300] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0301] Step 1:

[0302] The server collects user registration information. It receives basic information (age, hobbies, etc.) and survey responses provided by the user as input. This data is stored in a database and processed as foundational data for extracting information about the user's interests.

[0303] Step 2:

[0304] The server analyzes past conversation history. It uses records of past conversations as input, and analyzes preferences and patterns based on that data using natural language processing techniques. As output, it generates personalized conversation content for each user.

[0305] Step 3:

[0306] The server selects and prepares recommended activities for the user. As input, interest information and information on events and activities in the local community are used. The information is obtained from the Internet. Based on these, an AI model is generated and used to create optimal activity proposals. As output, a list of specific events and activities is generated.

[0307] Step 4:

[0308] The terminal presents information to the user. As input, it displays the personalized conversation content and the proposed activity information received from the server. Here, a UI is provided to determine whether the user can participate. As output, a dialogue and activity proposal are presented to the user.

[0309] Step 5:

[0310] The user provides feedback on the proposed activity. As input, it indicates the intention to participate in the proposed content displayed on the terminal. Or, it provides a response regarding the theme of interest. As output, the preferences and intention to participate are transferred to the server and reflected in future proposals.

[0311] Step 6:

[0312] The server performs sentiment analysis on the user. As input, the data obtained from the user's speech and actions is passed to the sentiment analysis engine. As output, the sentiment state is judged, a support message as needed is generated, and sent to the user.

[0313] Step 7:

[0314] The terminal displays the necessary support message and promotes a better experience. As input, it receives the sentiment analysis result from the server and presents a message of encouragement or warning to the user. As output, appropriate feedback to the user is provided.

[0315] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0316] This invention is a system that promotes dialogue and interaction among users of different age groups, improves users' cognitive functions, and strengthens social connections. In particular, it is characterized by its effectiveness in evaluating users' emotional states using an emotion engine and providing optimal responses and activities based on those evaluations.

[0317] The server collects each user's interest data and past conversation history, and stores this in a database. This enables the generation of personalized conversations optimized for each user. Furthermore, natural language processing technology is used to analyze the content of conversations between users and generate new conversation themes based on that analysis.

[0318] A key component of this system is the emotion engine, which evaluates the user's emotional state. The emotion engine analyzes the user's text and voice data to recognize their current emotions in real time. This information is combined with the user's profile data for analysis, providing the basis for optimal conversation content and activities.

[0319] The device displays personalized conversations and activities sent from the server to the user through a user interface. For example, the device might ask the user, "How are you feeling today?" and adjust the next conversation and suggestions based on the user's response.

[0320] Furthermore, based on the analysis results from the emotion engine, the server can provide users with appropriate support messages and words of encouragement. For example, if a user is showing signs of stress, the server might send a message such as, "Shall we think about ways to relax together?" In this way, more personalized support is provided, helping to deepen the bonds between users.

[0321] As a concrete example, when an elderly user A and a younger user B use the system, the server generates topics based on A's experiences and themes that interest B. At the same time, the emotional engine evaluates the emotional state of both users and provides support to improve the quality of the conversation. If the younger user B shows signs of stress, the server suggests a relaxing exercise to A as a follow-up, helping to deepen their mutual understanding.

[0322] Thus, the present invention aims to promote meaningful interaction between different generations and enhance cognitive function and social connections through a system that includes an emotion engine.

[0323] The following describes the processing flow.

[0324] Step 1:

[0325] Users access the system and answer questionnaires about their basic information and interests. These questionnaires include questions about age, hobbies, and past activities.

[0326] Step 2:

[0327] The server receives data collected from users and stores it in a database. This data is managed as a user profile and used for subsequent processing.

[0328] Step 3:

[0329] The server analyzes accumulated user data and uses natural language processing technology to generate personalized conversation content and dialogue themes. In doing so, it takes into account the user's interests and preferences.

[0330] Step 4:

[0331] The terminal displays the conversation content generated by the server to the user. The content presented may include, for example, discussion topics based on the user's interests or specific questions.

[0332] Step 5:

[0333] The user responds and inputs based on the presented conversation content. During this process, the emotion engine receives the user's input data and performs emotion analysis in real time.

[0334] Step 6:

[0335] The server evaluates the user's emotional state based on the analysis results from the emotion engine. Based on this evaluation, it adjusts the conversation content and generates support messages.

[0336] Step 7:

[0337] The device displays adjusted conversation content and supportive messages tailored to the user's emotional state. For example, if the device determines that the user is tired, it will display messages suggesting ways to relax or encouraging them to take a break.

[0338] Step 8:

[0339] The server uses emotion engine data to suggest interaction activities based on shared interests among users. These suggested activities include online events and discussions based on common topics.

[0340] Step 9:

[0341] Users review the activity suggestions displayed on their devices, select those that interest them, and participate. This feedback is sent to the server and influences future suggestions.

[0342] (Example 2)

[0343] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0344] In modern society, a lack of interaction among users of different age groups is a cause of social isolation and cognitive decline. This can potentially impair users' physical and mental health and social connections. Furthermore, conventional systems have struggled to adequately understand users' emotional states and provide appropriate dialogue and support. It is necessary to address these challenges and improve users' social interaction and cognitive function.

[0345] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0346] In this invention, the server includes means for collecting characteristic information of users of different age groups and generating personalized dialogues using language analysis technology based on that information; means for analyzing the user's voice and text information using a machine learning model and evaluating their emotions in real time; and means for integrating the user's emotional state and profile information to generate material for providing optimal dialogue content and actions. This promotes meaningful interaction among users of different age groups and, by providing support tailored to their emotions, enables improvement of users' cognitive functions and strengthens their social connections.

[0347] "Characteristic information" refers to information, including a user's interests, age, and past behavioral history, that is used to identify a user and provide a personalized experience.

[0348] "Language analysis technology" refers to the technology that allows computer systems to analyze text and audio data obtained from users, understand their meaning, and generate responses.

[0349] "Personalized dialogue" refers to a type of dialogue that is optimized and personalized based on the user's interests, preferences, and emotional state.

[0350] A "machine learning model" refers to a technical framework in which algorithms are trained using large amounts of data to make predictions and decisions based on new data.

[0351] "Real-time emotional assessment" refers to a process that instantly analyzes information obtained from voice and text to immediately recognize the user's emotional state.

[0352] "Profile information" refers to a comprehensive set of information that summarizes a user's attributes, history, interests, behavioral patterns, and more.

[0353] "Materials for providing dialogue content and actions" refers to information and data used to suggest appropriate communication and activities according to the user's emotions and interests.

[0354] "User cognitive function" refers to the brain's ability to acquire, understand, and apply information, enabling conscious thinking and problem-solving.

[0355] "Social connections" refer to the human relationships and networks formed through users influencing and supporting each other.

[0356] This invention is a system that promotes dialogue and interaction among users of different age groups, enhances users' cognitive functions, and strengthens social connections. Specific embodiments for carrying out this invention are described below.

[0357] First, the server plays a central role in data collection. The server collects user characteristic information and stores it in a database. This information includes interests, age, and past behavioral history. Then, using language analysis technology, it generates personalized dialogue optimized for the user. The server uses generative AI models, such as OpenAI's GPT, to form the dialogue content. Voice and text information is collected with the user's permission and used as characteristic information.

[0358] Next, the emotion engine connects to the server, analyzes the user's voice and text data, and evaluates their emotions in real time. This engine uses emotion analysis algorithms to evaluate the user's emotional state as numerical data, providing the server with the necessary information.

[0359] The terminal then provides the user with personalized conversations and action suggestions received from the server. The terminal's user interface operates on hardware devices such as smartphones and tablets, enabling interaction with the user. Specifically, the terminal displays prompts on the screen such as "How are you feeling today?" and allows the user to input how they are feeling.

[0360] Users experience interactions and activities based on personalized conversations and suggestions presented by the device. For example, when elderly and young users use the system, the system generates topics tailored to their respective interests and provides support to improve the quality of the conversation based on their emotional state.

[0361] An example of a prompt might be: "Please suggest a dialogue topic that takes into account the user's current emotional state and promotes meaningful interaction between different age groups."

[0362] In this way, the system aims to promote interaction between different generations and improve users' cognitive function and social connections.

[0363] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0364] Step 1:

[0365] The server collects user characteristic information. As input, it retrieves user registration data, interest data, and past conversation history. To store this data in the database, it converts and organizes it into a structured format. This process prepares the foundational data for future conversation generation. Specifically, it uses APIs to retrieve data from external sources and stores it in internal data storage.

[0366] Step 2:

[0367] The emotion engine analyzes the user's voice and text data. It receives voice and text input from the user via their device as input. Using an analysis algorithm, it detects the emotional state from each data point and outputs it as numerical data. Specifically, it uses speech recognition software to convert voice to text, and then processes that text with the emotion analysis algorithm.

[0368] Step 3:

[0369] The server generates personalized conversations based on collected trait information and sentiment data. It uses user trait information and sentiment data as input to send prompts to the generative AI model. The output is a conversation optimized for the user. Specifically, it calls the generative AI model and sends data via an API to generate prompt sentences.

[0370] Step 4:

[0371] The terminal presents the user with personalized conversations retrieved from the server. It uses conversation data received from the server as input. As output, it displays the conversation content on the user interface and prompts the user for a response. Specifically, it displays prompts through the screen display and receives user input.

[0372] Step 5:

[0373] The server updates the content it provides based on user feedback. It receives user responses and comments sent from the terminal as input. As output, it saves the feedback to a database and incorporates it into future dialogue generation. Specifically, it analyzes the response data and adds newly obtained data to the characteristic information.

[0374] Through these steps, the system provides a personalized experience based on the user's emotions and interests, and promotes meaningful interaction between different age groups.

[0375] (Application Example 2)

[0376] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0377] There is a need to facilitate communication among users of different age groups and provide appropriate conversations and activities based on the emotional state of the users, thereby improving cognitive function and strengthening social connections.

[0378] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0379] In this invention, the server includes means for collecting interest data from users of different age groups and generating personalized conversations using natural language processing technology based on that data; means for selecting and providing activities that stimulate cognitive functions according to the user's age and interests; means for analyzing the emotional state of users during conversations and activities and providing necessary responses and support; and means for adjusting optimal conversations and suggestions in real time based on the user's emotional state to support communication through online dialogue. This promotes meaningful interaction between different generations and enables improvement of users' cognitive functions and strengthening of social connections.

[0380] "Different age groups" refers to groups of users of different ages, such as elderly people and young people.

[0381] "Interest data" refers to information about the things and hobbies that users are interested in, which enables the delivery of personalized content.

[0382] "Natural language processing technology" is a technology that processes human language using computers, and is used for tasks such as text generation and sentiment analysis.

[0383] "Personalized conversation" refers to dialogue content optimized based on the individual user's interests and emotions, with the aim of providing meaningful conversations for the user.

[0384] "Activities that stimulate cognitive function" refer to activities designed to improve users' cognitive abilities, such as memory and thinking skills.

[0385] "Emotional state" refers to the emotions a user feels in a particular situation, encompassing psychological states such as joy, sadness, and stress.

[0386] "Responses and support" refers to replies, helpful actions, and messages provided in response to the user's statements and emotions.

[0387] "Exchange activities" refer to activities in which different users interact with each other and communicate based on common interests and themes.

[0388] "Real-time adjustment" refers to a state where the system's responses and suggestions are immediately optimized based on user feedback.

[0389] The system for implementing this invention consists of a server, a terminal, and a user working together. The server collects interest data from users of different age groups and stores it in a database. Using natural language processing technology, it generates personalized conversations based on the collected data. The Google Natural Language API is used to achieve this natural language processing. The server also uses IBM Watson Tone Analyzer to analyze the user's emotional state and personalize responses as needed.

[0390] The device visually and audibly presents personalized conversations and activities sent from the server to the user. This allows the user to enjoy interesting content in real time. By using a mobile device such as a smartphone, the device provides a user-friendly interface.

[0391] Users provide feedback on the information received via their devices, and the conversation is adjusted in real time based on this feedback. This system facilitates meaningful dialogue between older and younger generations, leading to improved cognitive function and strengthened social connections.

[0392] As a concrete example, consider a case where a grandmother and grandchild living far apart use this system to deepen their online connection. When the grandmother starts talking about caring for her garden plants, the system can analyze her interests and provide more detailed gardening tips. This allows the grandmother to continue the conversation with her grandchild on a variety of topics, leading to natural communication.

[0393] An example of a prompt to the generation AI model is, "Generate conversation topics that both older and younger users can enjoy." Through this prompt, the system generates new ideas to enrich interactions between users of different age groups.

[0394] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0395] Step 1:

[0396] The server collects user interest data from a database. The input is user profile information (age, hobbies, past conversation history, etc.), and the output is a dataset organized for personalized conversation generation. This data is used to prepare for identifying conversation topics suitable for each user.

[0397] Step 2:

[0398] The server generates personalized conversations using the Google Natural Language API based on the collected data. The input is user interest data, and the output is a conversation script presented to the user. A natural language processing engine then creates the most optimal conversation flow for the user.

[0399] Step 3:

[0400] The server uses IBM Watson Tone Analyzer to analyze the user's emotional state. Input is user voice and text data, and output is real-time evaluated emotional state data. Based on this analysis, the server identifies the user's emotions and prepares an appropriate response.

[0401] Step 4:

[0402] The device presents the user with personalized conversation and activity suggestions sent from the server through a user interface. Input consists of conversation scripts and suggested activities from the server, while output is a visual and auditory representation of the content on the user interface. This allows the user to initiate a dialogue.

[0403] Step 5:

[0404] The user provides feedback while interacting through the device. Input is the user's responses and interactions, and output is feedback data sent to the server. Based on this feedback, the server adjusts the next conversation or activity.

[0405] Step 6:

[0406] The server analyzes user feedback in real time and adjusts the conversation topic and activities as needed. Inputs include feedback data and analyzed sentiment states, while outputs include updated dialogue scripts and activity suggestions. This ensures the conversation flows optimally.

[0407] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0408] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0409] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0410] [Third Embodiment]

[0411] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0412] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0413] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0414] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0415] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0416] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0417] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0418] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0419] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0420] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0421] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0422] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0423] This invention is a system that promotes dialogue and interaction between elderly and younger users, aiming to maintain cognitive function and strengthen social connections. The main embodiments of the invention are shown below.

[0424] The system's core is a server, which has the function of collecting and analyzing user interest data. The server stores data such as basic information (age and hobbies) provided by users during registration, survey responses, and past conversation history in a database. Based on this data, the server uses natural language processing technology to generate personalized conversations tailored to each user.

[0425] The device interactively displays generated conversation content and activity suggestions to the user. The displayed content is tailored to the user's age and interests. For example, the device might ask an elderly user, "Tell me about your favorite gardening activity lately." The user's responses are used for further analysis by the server.

[0426] The system also features a function to analyze the user's emotional state in real time. This emotion analysis allows the server to detect the user's reactions during conversations and activities, and to provide the user with necessary support and encouragement messages as needed. For example, if the user is showing signs of anxiety, a message such as "Please let me know if there is anything I can do to help" will be displayed on the device.

[0427] Furthermore, the server generates suggestions to facilitate interaction among users. These suggestions are based on common interests and themes across different generations and are offered in the form of online or offline events. For example, younger users might be offered a suggestion such as, "Why not participate in a virtual gardening workshop to enjoy with seniors?"

[0428] For example, if an elderly person A and a young person B use this system, the server will generate conversation topics and activities based on A's extensive experience in gardening. At the same time, it will incorporate B's interest in outdoor activities, providing conversations and activities that both can enjoy.

[0429] In this way, the present invention provides a system that promotes interaction between different generations, maintains cognitive function, and deepens social bonds, and specifically illustrates embodiments based on the claims.

[0430] The following describes the processing flow.

[0431] Step 1:

[0432] Users log into the system and answer questionnaires about their basic information and interests. These responses include age, hobbies, and past activities.

[0433] Step 2:

[0434] The server receives the information provided by the user and stores it in a database. This data is saved as a specific profile for each user.

[0435] Step 3:

[0436] The server analyzes the accumulated data and uses natural language processing technology to generate conversation topics and questions that are best suited to the user. This process takes into account the user's interests and past conversation history.

[0437] Step 4:

[0438] The terminal displays the conversation content generated by the server to the user. For example, the terminal might display a specific question such as, "Tell me about your recent gardening activities."

[0439] Step 5:

[0440] The user enters answers or responses based on prompts displayed on the device. These answers will be used for analysis in the next stage.

[0441] Step 6:

[0442] The server receives user input data and performs sentiment analysis. Based on the analysis results, it adjusts necessary support messages and suggestions for the next conversation.

[0443] Step 7:

[0444] Based on the results of sentiment analysis and profile data, the server suggests activities that promote intergenerational interaction. These include virtual events and shared hobbies.

[0445] Step 8:

[0446] The device notifies the user of activity information suggested by the server and prompts them to choose whether or not they are interested.

[0447] Step 9:

[0448] Users select proposals that interest them and provide feedback to the system indicating their willingness to participate. This information will be used to improve future proposals.

[0449] (Example 1)

[0450] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0451] In modern society, a lack of interaction between different generations is a problem, leading to concerns about social isolation and cognitive decline among the elderly. Furthermore, younger generations face challenges due to limited opportunities to share different perspectives and experiences. To address these issues, a system is needed that promotes smooth communication between both generations and strengthens social connections.

[0452] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0453] In this invention, the server includes means for collecting interest data from different age groups and generating personalized conversations using a generative model based on that data; means for analyzing the emotional state of users during conversations and activities and providing necessary responses and support; and means for interactively displaying the generated conversation content and activity suggestions to users via a terminal. This facilitates conversations between elderly and younger users, enabling the maintenance of cognitive function and the strengthening of social connections.

[0454] "Different age groups" refers to a collection of individuals or groups belonging to different generations, and is a social division that mainly includes the elderly and younger generations.

[0455] "Interest data" is a collection of information about a user's hobbies, preferences, and activities, and is used to provide a personalized experience.

[0456] A "generative model" is an algorithm or system that automatically generates new content, particularly natural language conversations, based on input data.

[0457] "Personalized conversation" refers to dialogue content that is customized to take into account the individual characteristics and interests of each user.

[0458] "Emotional state" is an indicator that shows the user's current psychological state, and is mainly inferred from language and facial expressions.

[0459] "Interactive display" refers to a format in which information is presented in a way that allows users to receive and respond to information interactively through their devices.

[0460] "Support" refers to assistance, advice, and encouraging messages provided according to the user's needs.

[0461] An "intergenerational exchange event" refers to an activity or gathering in which people from different generations can participate based on common interests or themes.

[0462] This invention is a system that promotes dialogue and interaction between elderly and younger users, thereby maintaining cognitive function and strengthening social connections. The system primarily consists of a server and terminals, and provides a personalized experience utilizing a generative AI model.

[0463] The server collects basic information provided by the user (age, hobbies), past conversation history, and survey responses, and stores them in a database. MySQL or PostgreSQL can be used as the database management system for this purpose. Based on this information, the server generates conversation content tailored to the user using a generative AI model (e.g., GPT-4). During this generation process, specific conversations are elicited by providing prompts such as "Generate questions related to the user's interests."

[0464] The terminal's role is to interactively display conversation content and activity suggestions sent from the server to the user. Specifically, it is designed to allow users to easily participate in communication via a touchscreen or voice interface. Users can convey their opinions and feelings to the system by directly reacting to the display on the terminal.

[0465] The server also analyzes text and audio data in real time to assess the user's emotional state. This process can utilize an emotion analysis API (such as the Google Cloud Natural Language API). Based on the emotion analysis results, the server provides appropriate responses and encouragement tailored to the user's feelings. For example, if the user expresses anxiety, the server might display a message on the device such as, "Please let me know if there's anything I can do to help."

[0466] Furthermore, the server generates suggestions to uncover common interests across different generations and promote intergenerational interaction. These suggestions are presented as online or offline events. By suggesting specific events to younger users, such as "Why not participate in a virtual gardening workshop to enjoy with seniors?", the aim is to deepen intergenerational bonds.

[0467] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0468] Step 1:

[0469] The server collects basic user information (age, hobbies), past conversation history, and survey responses. The input data is information provided by the user during registration and is recorded in the database. A database management system (e.g., MySQL, PostgreSQL) is used to build user profiles, which serve as the basis for subsequent processing.

[0470] Step 2:

[0471] The server uses a generative AI model (e.g., GPT-4) based on the collected data to generate personalized conversations. The input is the interest data collected in step 1, and by sending prompt sentences to the model, output conversations tailored to individual users are generated. This generated conversation content serves as material for subsequent interactions.

[0472] Step 3:

[0473] The terminal receives the conversation content generated by the server and displays it interactively to the user. The input is the conversation data generated in step 2, which is presented via a touchscreen or voice interface. The user can directly respond to the displayed questions and suggestions. Specific actions include the user tapping the screen to select an answer.

[0474] Step 4:

[0475] The server analyzes text and audio data obtained from user interactions in real time to evaluate their emotional state. The input data consists of user responses on the device, which are processed using an emotion analysis API to obtain output indicating the user's emotional state. Based on the obtained emotion analysis results, the server provides appropriate responses and support.

[0476] Step 5:

[0477] The server generates event suggestions to promote intergenerational interaction based on user information. Inputs include past activity history and current emotional state, and the server considers this to suggest events, either online or offline, that match the user. Specifically, it might suggest things like "participating in a virtual gardening workshop to enjoy with seniors," providing output to promote intergenerational interaction.

[0478] (Application Example 1)

[0479] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0480] In modern society, interaction between different age groups is decreasing, leading to problems such as cognitive decline among the elderly and feelings of isolation among younger generations. Therefore, there is a need for means to promote interaction across age groups and deepen mutual understanding. In particular, given the current difficulty in naturally building intergenerational relationships within local communities, there is a need for efficient and effective systems.

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

[0482] In this invention, the server includes means for collecting interest information from users of different age groups and generating personalized conversations using natural language processing technology based on that information; means for selecting and providing activities that stimulate cognitive functions according to the user's age and interests; and means for using information on local events and activities to suggest activities suitable for the user. This makes it possible to naturally promote interaction across age groups and deepen mutual understanding.

[0483] "Different age groups" refers to groups of people of different ages within a society, particularly the elderly and younger generations.

[0484] "Interest information" refers to information related to the user's interests and hobbies.

[0485] "Natural language processing technology" is the technology that processes and understands human language using computers.

[0486] "Personalized conversation" refers to dialogue content that is customized to the individual user's characteristics and interests.

[0487] "Cognitive function" refers to the ability to understand information and solve problems, and is important for maintaining the health of the elderly.

[0488] "Local community events and activities information" refers to information about events and activities that take place within a specific region.

[0489] "Suggesting activities suitable for the user" means recommending activities that match the user's interests and circumstances.

[0490] This invention provides a system to facilitate interaction between users of different age groups. The server collects user interest information and stores it in a database using cloud computing technology. Based on basic information provided by the user, survey responses, and past conversation history, personalized conversations are generated using natural language processing technology. Examples of natural language processing APIs used here include the Google Cloud Natural Language API.

[0491] The terminal displays personalized conversation content and local event information sent from the server to the user. Based on this information, suggestions are made to encourage participation in social activities and events that match the user's interests. This not only helps maintain the user's cognitive function but also deepens their connection with the local community.

[0492] Furthermore, the server has the capability to analyze the user's emotional state in real time. Based on the results of the emotional analysis, it provides the user with necessary support and encouraging messages. AI technology is applied to this analysis. For example, an emotional recognition service such as Microsoft's Cognitive Services may be used.

[0493] As a concrete example, the system might suggest "recent favorite gardening topics" to older users, while simultaneously recommending "participation in local recycling activities" to younger users. In such a case, a possible prompt message might be, "Based on the user's interests, suggest local events they can participate in. Examples: gardening, outdoor activities."

[0494] In this way, the aim is to promote natural interaction among users of different age groups and to foster a sense of unity with the local community.

[0495] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0496] Step 1:

[0497] The server collects user registration information. It receives basic information (age, hobbies, etc.) and survey responses provided by the user as input. This data is stored in a database and processed as foundational data for extracting information about the user's interests.

[0498] Step 2:

[0499] The server analyzes past conversation history. It uses records of past conversations as input, and analyzes preferences and patterns based on that data using natural language processing techniques. As output, it generates personalized conversation content for each user.

[0500] Step 3:

[0501] The server selects and prepares recommended activities for the user. The inputs used are interest information and information on local events and activities. This information is obtained from the internet. Based on this, a generative AI model is used to create optimal activity suggestions. The output is a list of specific events and activities.

[0502] Step 4:

[0503] The terminal presents information to the user. As input, it displays personalized conversation content and suggested activity information received from the server. A user interface (UI) is provided to help the user determine if they are able to participate. As output, the user is presented with the dialogue and activity suggestions.

[0504] Step 5:

[0505] Users provide feedback on proposed activities. Input involves indicating their willingness to participate in the proposed activities displayed on their device, or responding to topics that interest them. Output involves transferring preferences and participation intentions to the server, which are then used to inform future proposals.

[0506] Step 6:

[0507] The server performs sentiment analysis on the user. It receives data obtained from the user's statements and actions as input to the sentiment analysis engine. As output, it determines the emotional state, generates appropriate support messages, and sends them to the user.

[0508] Step 7:

[0509] The device displays necessary support messages to facilitate a better experience. It receives sentiment analysis results from the server as input and presents encouraging and cautionary messages to the user. As output, it provides appropriate feedback to the user.

[0510] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0511] This invention is a system that promotes dialogue and interaction among users of different age groups, improves users' cognitive functions, and strengthens social connections. In particular, it is characterized by its effectiveness in evaluating users' emotional states using an emotion engine and providing optimal responses and activities based on those evaluations.

[0512] The server collects each user's interest data and past conversation history, and stores this in a database. This enables the generation of personalized conversations optimized for each user. Furthermore, natural language processing technology is used to analyze the content of conversations between users and generate new conversation themes based on that analysis.

[0513] A key component of this system is the emotion engine, which evaluates the user's emotional state. The emotion engine analyzes the user's text and voice data to recognize their current emotions in real time. This information is combined with the user's profile data for analysis, providing the basis for optimal conversation content and activities.

[0514] The device displays personalized conversations and activities sent from the server to the user through a user interface. For example, the device might ask the user, "How are you feeling today?" and adjust the next conversation and suggestions based on the user's response.

[0515] Furthermore, based on the analysis results from the emotion engine, the server can provide users with appropriate support messages and words of encouragement. For example, if a user is showing signs of stress, the server might send a message such as, "Shall we think about ways to relax together?" In this way, more personalized support is provided, helping to deepen the bonds between users.

[0516] As a concrete example, when an elderly user A and a younger user B use the system, the server generates topics based on A's experiences and themes that interest B. At the same time, the emotional engine evaluates the emotional state of both users and provides support to improve the quality of the conversation. If the younger user B shows signs of stress, the server suggests a relaxing exercise to A as a follow-up, helping to deepen their mutual understanding.

[0517] Thus, the present invention aims to promote meaningful interaction between different generations and enhance cognitive function and social connections through a system that includes an emotion engine.

[0518] The following describes the processing flow.

[0519] Step 1:

[0520] Users access the system and answer questionnaires about their basic information and interests. These questionnaires include questions about age, hobbies, and past activities.

[0521] Step 2:

[0522] The server receives data collected from users and stores it in a database. This data is managed as a user profile and used for subsequent processing.

[0523] Step 3:

[0524] The server analyzes accumulated user data and uses natural language processing technology to generate personalized conversation content and dialogue themes. In doing so, it takes into account the user's interests and preferences.

[0525] Step 4:

[0526] The terminal displays the conversation content generated by the server to the user. The content presented may include, for example, discussion topics based on the user's interests or specific questions.

[0527] Step 5:

[0528] The user responds and inputs based on the presented conversation content. During this process, the emotion engine receives the user's input data and performs emotion analysis in real time.

[0529] Step 6:

[0530] The server evaluates the user's emotional state based on the analysis results from the emotion engine. Based on this evaluation, it adjusts the conversation content and generates support messages.

[0531] Step 7:

[0532] The device displays adjusted conversation content and supportive messages tailored to the user's emotional state. For example, if the device determines that the user is tired, it will display messages suggesting ways to relax or encouraging them to take a break.

[0533] Step 8:

[0534] The server uses emotion engine data to suggest interaction activities based on shared interests among users. These suggested activities include online events and discussions based on common topics.

[0535] Step 9:

[0536] Users review the activity suggestions displayed on their devices, select those that interest them, and participate. This feedback is sent to the server and influences future suggestions.

[0537] (Example 2)

[0538] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0539] In modern society, a lack of interaction among users of different age groups is a cause of social isolation and cognitive decline. This can potentially impair users' physical and mental health and social connections. Furthermore, conventional systems have struggled to adequately understand users' emotional states and provide appropriate dialogue and support. It is necessary to address these challenges and improve users' social interaction and cognitive function.

[0540] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0541] In this invention, the server includes means for collecting characteristic information of users of different age groups and generating personalized dialogues using language analysis technology based on that information; means for analyzing the user's voice and text information using a machine learning model and evaluating their emotions in real time; and means for integrating the user's emotional state and profile information to generate material for providing optimal dialogue content and actions. This promotes meaningful interaction among users of different age groups and, by providing support tailored to their emotions, enables improvement of users' cognitive functions and strengthens their social connections.

[0542] "Characteristic information" refers to information, including a user's interests, age, and past behavioral history, that is used to identify a user and provide a personalized experience.

[0543] "Language analysis technology" refers to the technology that allows computer systems to analyze text and audio data obtained from users, understand their meaning, and generate responses.

[0544] "Personalized dialogue" refers to a type of dialogue that is optimized and personalized based on the user's interests, preferences, and emotional state.

[0545] A "machine learning model" refers to a technical framework in which algorithms are trained using large amounts of data to make predictions and decisions based on new data.

[0546] "Real-time emotional assessment" refers to a process that instantly analyzes information obtained from voice and text to immediately recognize the user's emotional state.

[0547] "Profile information" refers to a comprehensive set of information that summarizes a user's attributes, history, interests, behavioral patterns, and more.

[0548] "Materials for providing dialogue content and actions" refers to information and data used to suggest appropriate communication and activities according to the user's emotions and interests.

[0549] "User cognitive function" refers to the brain's ability to acquire, understand, and apply information, enabling conscious thinking and problem-solving.

[0550] "Social connections" refer to the human relationships and networks formed through users influencing and supporting each other.

[0551] This invention is a system that promotes dialogue and interaction among users of different age groups, enhances users' cognitive functions, and strengthens social connections. Specific embodiments for carrying out this invention are described below.

[0552] First, the server plays a central role in data collection. The server collects user characteristic information and stores it in a database. This information includes interests, age, and past behavioral history. Then, using language analysis technology, it generates personalized dialogue optimized for the user. The server uses generative AI models, such as OpenAI's GPT, to form the dialogue content. Voice and text information is collected with the user's permission and used as characteristic information.

[0553] Next, the emotion engine connects to the server, analyzes the user's voice and text data, and evaluates their emotions in real time. This engine uses emotion analysis algorithms to evaluate the user's emotional state as numerical data, providing the server with the necessary information.

[0554] The terminal then provides the user with personalized conversations and action suggestions received from the server. The terminal's user interface operates on hardware devices such as smartphones and tablets, enabling interaction with the user. Specifically, the terminal displays prompts on the screen such as "How are you feeling today?" and allows the user to input how they are feeling.

[0555] Users experience interactions and activities based on personalized conversations and suggestions presented by the device. For example, when elderly and young users use the system, the system generates topics tailored to their respective interests and provides support to improve the quality of the conversation based on their emotional state.

[0556] An example of a prompt might be: "Please suggest a dialogue topic that takes into account the user's current emotional state and promotes meaningful interaction between different age groups."

[0557] In this way, the system aims to promote interaction between different generations and improve users' cognitive function and social connections.

[0558] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0559] Step 1:

[0560] The server collects user characteristic information. As input, it retrieves user registration data, interest data, and past conversation history. To store this data in the database, it converts and organizes it into a structured format. This process prepares the foundational data for future conversation generation. Specifically, it uses APIs to retrieve data from external sources and stores it in internal data storage.

[0561] Step 2:

[0562] The emotion engine analyzes the user's voice and text data. It receives voice and text input from the user via their device as input. Using an analysis algorithm, it detects the emotional state from each data point and outputs it as numerical data. Specifically, it uses speech recognition software to convert voice to text, and then processes that text with the emotion analysis algorithm.

[0563] Step 3:

[0564] The server generates personalized conversations based on collected trait information and sentiment data. It uses user trait information and sentiment data as input to send prompts to the generative AI model. The output is a conversation optimized for the user. Specifically, it calls the generative AI model and sends data via an API to generate prompt sentences.

[0565] Step 4:

[0566] The terminal presents the user with personalized conversations retrieved from the server. It uses conversation data received from the server as input. As output, it displays the conversation content on the user interface and prompts the user for a response. Specifically, it displays prompts through the screen display and receives user input.

[0567] Step 5:

[0568] The server updates the content it provides based on user feedback. It receives user responses and comments sent from the terminal as input. As output, it saves the feedback to a database and incorporates it into future dialogue generation. Specifically, it analyzes the response data and adds newly obtained data to the characteristic information.

[0569] Through these steps, the system provides a personalized experience based on the user's emotions and interests, and promotes meaningful interaction between different age groups.

[0570] (Application Example 2)

[0571] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0572] There is a need to facilitate communication among users of different age groups and provide appropriate conversations and activities based on the emotional state of the users, thereby improving cognitive function and strengthening social connections.

[0573] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0574] In this invention, the server includes means for collecting interest data from users of different age groups and generating personalized conversations using natural language processing technology based on that data; means for selecting and providing activities that stimulate cognitive functions according to the user's age and interests; means for analyzing the emotional state of users during conversations and activities and providing necessary responses and support; and means for adjusting optimal conversations and suggestions in real time based on the user's emotional state to support communication through online dialogue. This promotes meaningful interaction between different generations and enables improvement of users' cognitive functions and strengthening of social connections.

[0575] "Different age groups" refers to groups of users of different ages, such as elderly people and young people.

[0576] "Interest data" refers to information about the things and hobbies that users are interested in, which enables the delivery of personalized content.

[0577] "Natural language processing technology" is a technology that processes human language using computers, and is used for tasks such as text generation and sentiment analysis.

[0578] "Personalized conversation" refers to dialogue content optimized based on the individual user's interests and emotions, with the aim of providing meaningful conversations for the user.

[0579] "Activities that stimulate cognitive function" refer to activities designed to improve users' cognitive abilities, such as memory and thinking skills.

[0580] "Emotional state" refers to the emotions a user feels in a particular situation, encompassing psychological states such as joy, sadness, and stress.

[0581] "Responses and support" refers to replies, helpful actions, and messages provided in response to the user's statements and emotions.

[0582] "Exchange activities" refer to activities in which different users interact with each other and communicate based on common interests and themes.

[0583] "Real-time adjustment" refers to a state where the system's responses and suggestions are immediately optimized based on user feedback.

[0584] The system for implementing this invention consists of a server, a terminal, and a user working together. The server collects interest data from users of different age groups and stores it in a database. Using natural language processing technology, it generates personalized conversations based on the collected data. The Google Natural Language API is used to achieve this natural language processing. The server also uses IBM Watson Tone Analyzer to analyze the user's emotional state and personalize responses as needed.

[0585] The device visually and audibly presents personalized conversations and activities sent from the server to the user. This allows the user to enjoy interesting content in real time. By using a mobile device such as a smartphone, the device provides a user-friendly interface.

[0586] Users provide feedback on the information received via their devices, and the conversation is adjusted in real time based on this feedback. This system facilitates meaningful dialogue between older and younger generations, leading to improved cognitive function and strengthened social connections.

[0587] As a concrete example, consider a case where a grandmother and grandchild living far apart use this system to deepen their online connection. When the grandmother starts talking about caring for her garden plants, the system can analyze her interests and provide more detailed gardening tips. This allows the grandmother to continue the conversation with her grandchild on a variety of topics, leading to natural communication.

[0588] An example of a prompt to the generation AI model is, "Generate conversation topics that both older and younger users can enjoy." Through this prompt, the system generates new ideas to enrich interactions between users of different age groups.

[0589] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0590] Step 1:

[0591] The server collects user interest data from a database. The input is user profile information (age, hobbies, past conversation history, etc.), and the output is a dataset organized for personalized conversation generation. This data is used to prepare for identifying conversation topics suitable for each user.

[0592] Step 2:

[0593] The server generates personalized conversations using the Google Natural Language API based on the collected data. The input is user interest data, and the output is a conversation script presented to the user. A natural language processing engine then creates the most optimal conversation flow for the user.

[0594] Step 3:

[0595] The server uses IBM Watson Tone Analyzer to analyze the user's emotional state. Input is user voice and text data, and output is real-time evaluated emotional state data. Based on this analysis, the server identifies the user's emotions and prepares an appropriate response.

[0596] Step 4:

[0597] The device presents the user with personalized conversation and activity suggestions sent from the server through a user interface. Input consists of conversation scripts and suggested activities from the server, while output is a visual and auditory representation of the content on the user interface. This allows the user to initiate a dialogue.

[0598] Step 5:

[0599] The user provides feedback while interacting through the device. Input is the user's responses and interactions, and output is feedback data sent to the server. Based on this feedback, the server adjusts the next conversation or activity.

[0600] Step 6:

[0601] The server analyzes user feedback in real time and adjusts the conversation topic and activities as needed. Inputs include feedback data and analyzed sentiment states, while outputs include updated dialogue scripts and activity suggestions. This ensures the conversation flows optimally.

[0602] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0603] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0604] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0605] [Fourth Embodiment]

[0606] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0607] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0608] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0609] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0610] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0611] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0612] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0613] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0614] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0615] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0616] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0617] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0618] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0619] This invention is a system that promotes dialogue and interaction between elderly and younger users, aiming to maintain cognitive function and strengthen social connections. The main embodiments of the invention are shown below.

[0620] The system's core is a server, which has the function of collecting and analyzing user interest data. The server stores data such as basic information (age and hobbies) provided by users during registration, survey responses, and past conversation history in a database. Based on this data, the server uses natural language processing technology to generate personalized conversations tailored to each user.

[0621] The device interactively displays generated conversation content and activity suggestions to the user. The displayed content is tailored to the user's age and interests. For example, the device might ask an elderly user, "Tell me about your favorite gardening activity lately." The user's responses are used for further analysis by the server.

[0622] The system also features a function to analyze the user's emotional state in real time. This emotion analysis allows the server to detect the user's reactions during conversations and activities, and to provide the user with necessary support and encouragement messages as needed. For example, if the user is showing signs of anxiety, a message such as "Please let me know if there is anything I can do to help" will be displayed on the device.

[0623] Furthermore, the server generates suggestions to facilitate interaction among users. These suggestions are based on common interests and themes across different generations and are offered in the form of online or offline events. For example, younger users might be offered a suggestion such as, "Why not participate in a virtual gardening workshop to enjoy with seniors?"

[0624] For example, if an elderly person A and a young person B use this system, the server will generate conversation topics and activities based on A's extensive experience in gardening. At the same time, it will incorporate B's interest in outdoor activities, providing conversations and activities that both can enjoy.

[0625] In this way, the present invention provides a system that promotes interaction between different generations, maintains cognitive function, and deepens social bonds, and specifically illustrates embodiments based on the claims.

[0626] The following describes the processing flow.

[0627] Step 1:

[0628] Users log into the system and answer questionnaires about their basic information and interests. These responses include age, hobbies, and past activities.

[0629] Step 2:

[0630] The server receives the information provided by the user and stores it in a database. This data is saved as a specific profile for each user.

[0631] Step 3:

[0632] The server analyzes the accumulated data and uses natural language processing technology to generate conversation topics and questions that are best suited to the user. This process takes into account the user's interests and past conversation history.

[0633] Step 4:

[0634] The terminal displays the conversation content generated by the server to the user. For example, the terminal might display a specific question such as, "Tell me about your recent gardening activities."

[0635] Step 5:

[0636] The user enters answers or responses based on prompts displayed on the device. These answers will be used for analysis in the next stage.

[0637] Step 6:

[0638] The server receives user input data and performs sentiment analysis. Based on the analysis results, it adjusts necessary support messages and suggestions for the next conversation.

[0639] Step 7:

[0640] Based on the results of sentiment analysis and profile data, the server suggests activities that promote intergenerational interaction. These include virtual events and shared hobbies.

[0641] Step 8:

[0642] The device notifies the user of activity information suggested by the server and prompts them to choose whether or not they are interested.

[0643] Step 9:

[0644] Users select proposals that interest them and provide feedback to the system indicating their willingness to participate. This information will be used to improve future proposals.

[0645] (Example 1)

[0646] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0647] In modern society, a lack of interaction between different generations is a problem, leading to concerns about social isolation and cognitive decline among the elderly. Furthermore, younger generations face challenges due to limited opportunities to share different perspectives and experiences. To address these issues, a system is needed that promotes smooth communication between both generations and strengthens social connections.

[0648] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0649] In this invention, the server includes means for collecting interest data from different age groups and generating personalized conversations using a generative model based on that data; means for analyzing the emotional state of users during conversations and activities and providing necessary responses and support; and means for interactively displaying the generated conversation content and activity suggestions to users via a terminal. This facilitates conversations between elderly and younger users, enabling the maintenance of cognitive function and the strengthening of social connections.

[0650] "Different age groups" refers to a collection of individuals or groups belonging to different generations, and is a social division that mainly includes the elderly and younger generations.

[0651] "Interest data" is a collection of information about a user's hobbies, preferences, and activities, and is used to provide a personalized experience.

[0652] A "generative model" is an algorithm or system that automatically generates new content, particularly natural language conversations, based on input data.

[0653] "Personalized conversation" refers to dialogue content that is customized to take into account the individual characteristics and interests of each user.

[0654] "Emotional state" is an indicator that shows the user's current psychological state, and is mainly inferred from language and facial expressions.

[0655] "Interactive display" refers to a format in which information is presented in a way that allows users to receive and respond to information interactively through their devices.

[0656] "Support" refers to assistance, advice, and encouraging messages provided according to the user's needs.

[0657] An "intergenerational exchange event" refers to an activity or gathering in which people from different generations can participate based on common interests or themes.

[0658] This invention is a system that promotes dialogue and interaction between elderly and younger users, thereby maintaining cognitive function and strengthening social connections. The system primarily consists of a server and terminals, and provides a personalized experience utilizing a generative AI model.

[0659] The server collects basic information provided by the user (age, hobbies), past conversation history, and survey responses, and stores them in a database. MySQL or PostgreSQL can be used as the database management system for this purpose. Based on this information, the server generates conversation content tailored to the user using a generative AI model (e.g., GPT-4). During this generation process, specific conversations are elicited by providing prompts such as "Generate questions related to the user's interests."

[0660] The terminal's role is to interactively display conversation content and activity suggestions sent from the server to the user. Specifically, it is designed to allow users to easily participate in communication via a touchscreen or voice interface. Users can convey their opinions and feelings to the system by directly reacting to the display on the terminal.

[0661] The server also analyzes text and audio data in real time to assess the user's emotional state. This process can utilize an emotion analysis API (such as the Google Cloud Natural Language API). Based on the emotion analysis results, the server provides appropriate responses and encouragement tailored to the user's feelings. For example, if the user expresses anxiety, the server might display a message on the device such as, "Please let me know if there's anything I can do to help."

[0662] Furthermore, the server generates suggestions to uncover common interests across different generations and promote intergenerational interaction. These suggestions are presented as online or offline events. By suggesting specific events to younger users, such as "Why not participate in a virtual gardening workshop to enjoy with seniors?", the aim is to deepen intergenerational bonds.

[0663] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0664] Step 1:

[0665] The server collects basic user information (age, hobbies), past conversation history, and survey responses. The input data is information provided by the user during registration and is recorded in the database. A database management system (e.g., MySQL, PostgreSQL) is used to build user profiles, which serve as the basis for subsequent processing.

[0666] Step 2:

[0667] The server uses a generative AI model (e.g., GPT-4) based on the collected data to generate personalized conversations. The input is the interest data collected in step 1, and by sending prompt sentences to the model, output conversations tailored to individual users are generated. This generated conversation content serves as material for subsequent interactions.

[0668] Step 3:

[0669] The terminal receives the conversation content generated by the server and displays it interactively to the user. The input is the conversation data generated in step 2, which is presented via a touchscreen or voice interface. The user can directly respond to the displayed questions and suggestions. Specific actions include the user tapping the screen to select an answer.

[0670] Step 4:

[0671] The server analyzes text and audio data obtained from user interactions in real time to evaluate their emotional state. The input data consists of user responses on the device, which are processed using an emotion analysis API to obtain output indicating the user's emotional state. Based on the obtained emotion analysis results, the server provides appropriate responses and support.

[0672] Step 5:

[0673] The server generates event suggestions to promote intergenerational interaction based on user information. Inputs include past activity history and current emotional state, and the server considers this to suggest events, either online or offline, that match the user. Specifically, it might suggest things like "participating in a virtual gardening workshop to enjoy with seniors," providing output to promote intergenerational interaction.

[0674] (Application Example 1)

[0675] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0676] In modern society, interaction between different age groups is decreasing, leading to problems such as cognitive decline among the elderly and feelings of isolation among younger generations. Therefore, there is a need for means to promote interaction across age groups and deepen mutual understanding. In particular, given the current difficulty in naturally building intergenerational relationships within local communities, there is a need for efficient and effective systems.

[0677] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0678] In this invention, the server includes means for collecting interest information from users of different age groups and generating personalized conversations using natural language processing technology based on that information; means for selecting and providing activities that stimulate cognitive functions according to the user's age and interests; and means for using information on local events and activities to suggest activities suitable for the user. This makes it possible to naturally promote interaction across age groups and deepen mutual understanding.

[0679] "Different age groups" refers to groups of people of different ages within a society, particularly the elderly and younger generations.

[0680] "Interest information" refers to information related to the user's interests and hobbies.

[0681] "Natural language processing technology" is the technology that processes and understands human language using computers.

[0682] "Personalized conversation" refers to dialogue content that is customized to the individual user's characteristics and interests.

[0683] "Cognitive function" refers to the ability to understand information and solve problems, and is important for maintaining the health of the elderly.

[0684] "Local community events and activities information" refers to information about events and activities that take place within a specific region.

[0685] "Suggesting activities suitable for the user" means recommending activities that match the user's interests and circumstances.

[0686] This invention provides a system to facilitate interaction between users of different age groups. The server collects user interest information and stores it in a database using cloud computing technology. Based on basic information provided by the user, survey responses, and past conversation history, personalized conversations are generated using natural language processing technology. Examples of natural language processing APIs used here include the Google Cloud Natural Language API.

[0687] The terminal displays personalized conversation content and local event information sent from the server to the user. Based on this information, suggestions are made to encourage participation in social activities and events that match the user's interests. This not only helps maintain the user's cognitive function but also deepens their connection with the local community.

[0688] Furthermore, the server has the capability to analyze the user's emotional state in real time. Based on the results of the emotional analysis, it provides the user with necessary support and encouraging messages. AI technology is applied to this analysis. For example, an emotional recognition service such as Microsoft's Cognitive Services may be used.

[0689] As a concrete example, the system might suggest "recent favorite gardening topics" to older users, while simultaneously recommending "participation in local recycling activities" to younger users. In such a case, a possible prompt message might be, "Based on the user's interests, suggest local events they can participate in. Examples: gardening, outdoor activities."

[0690] In this way, the aim is to promote natural interaction among users of different age groups and to foster a sense of unity with the local community.

[0691] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0692] Step 1:

[0693] The server collects user registration information. It receives basic information (age, hobbies, etc.) and survey responses provided by the user as input. This data is stored in a database and processed as foundational data for extracting information about the user's interests.

[0694] Step 2:

[0695] The server analyzes past conversation history. It uses records of past conversations as input, and analyzes preferences and patterns based on that data using natural language processing techniques. As output, it generates personalized conversation content for each user.

[0696] Step 3:

[0697] The server selects and prepares recommended activities for the user. The inputs used are interest information and information on local events and activities. This information is obtained from the internet. Based on this, a generative AI model is used to create optimal activity suggestions. The output is a list of specific events and activities.

[0698] Step 4:

[0699] The terminal presents information to the user. As input, it displays personalized conversation content and suggested activity information received from the server. A user interface (UI) is provided to help the user determine if they are able to participate. As output, the user is presented with the dialogue and activity suggestions.

[0700] Step 5:

[0701] Users provide feedback on proposed activities. Input involves indicating their willingness to participate in the proposed activities displayed on their device, or responding to topics that interest them. Output involves transferring preferences and participation intentions to the server, which are then used to inform future proposals.

[0702] Step 6:

[0703] The server performs sentiment analysis on the user. It receives data obtained from the user's statements and actions as input to the sentiment analysis engine. As output, it determines the emotional state, generates appropriate support messages, and sends them to the user.

[0704] Step 7:

[0705] The device displays necessary support messages to facilitate a better experience. It receives sentiment analysis results from the server as input and presents encouraging and cautionary messages to the user. As output, it provides appropriate feedback to the user.

[0706] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0707] This invention is a system that promotes dialogue and interaction among users of different age groups, improves users' cognitive functions, and strengthens social connections. In particular, it is characterized by its effectiveness in evaluating users' emotional states using an emotion engine and providing optimal responses and activities based on those evaluations.

[0708] The server collects each user's interest data and past conversation history, and stores this in a database. This enables the generation of personalized conversations optimized for each user. Furthermore, natural language processing technology is used to analyze the content of conversations between users and generate new conversation themes based on that analysis.

[0709] A key component of this system is the emotion engine, which evaluates the user's emotional state. The emotion engine analyzes the user's text and voice data to recognize their current emotions in real time. This information is combined with the user's profile data for analysis, providing the basis for optimal conversation content and activities.

[0710] The device displays personalized conversations and activities sent from the server to the user through a user interface. For example, the device might ask the user, "How are you feeling today?" and adjust the next conversation and suggestions based on the user's response.

[0711] Furthermore, based on the analysis results from the emotion engine, the server can provide users with appropriate support messages and words of encouragement. For example, if a user is showing signs of stress, the server might send a message such as, "Shall we think about ways to relax together?" In this way, more personalized support is provided, helping to deepen the bonds between users.

[0712] As a concrete example, when an elderly user A and a younger user B use the system, the server generates topics based on A's experiences and themes that interest B. At the same time, the emotional engine evaluates the emotional state of both users and provides support to improve the quality of the conversation. If the younger user B shows signs of stress, the server suggests a relaxing exercise to A as a follow-up, helping to deepen their mutual understanding.

[0713] Thus, the present invention aims to promote meaningful interaction between different generations and enhance cognitive function and social connections through a system that includes an emotion engine.

[0714] The following describes the processing flow.

[0715] Step 1:

[0716] Users access the system and answer questionnaires about their basic information and interests. These questionnaires include questions about age, hobbies, and past activities.

[0717] Step 2:

[0718] The server receives data collected from users and stores it in a database. This data is managed as a user profile and used for subsequent processing.

[0719] Step 3:

[0720] The server analyzes accumulated user data and uses natural language processing technology to generate personalized conversation content and dialogue themes. In doing so, it takes into account the user's interests and preferences.

[0721] Step 4:

[0722] The terminal displays the conversation content generated by the server to the user. The content presented may include, for example, discussion topics based on the user's interests or specific questions.

[0723] Step 5:

[0724] The user responds and inputs based on the presented conversation content. During this process, the emotion engine receives the user's input data and performs emotion analysis in real time.

[0725] Step 6:

[0726] The server evaluates the user's emotional state based on the analysis results from the emotion engine. Based on this evaluation, it adjusts the conversation content and generates support messages.

[0727] Step 7:

[0728] The device displays adjusted conversation content and supportive messages tailored to the user's emotional state. For example, if the device determines that the user is tired, it will display messages suggesting ways to relax or encouraging them to take a break.

[0729] Step 8:

[0730] The server uses emotion engine data to suggest interaction activities based on shared interests among users. These suggested activities include online events and discussions based on common topics.

[0731] Step 9:

[0732] Users review the activity suggestions displayed on their devices, select those that interest them, and participate. This feedback is sent to the server and influences future suggestions.

[0733] (Example 2)

[0734] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0735] In modern society, a lack of interaction among users of different age groups is a cause of social isolation and cognitive decline. This can potentially impair users' physical and mental health and social connections. Furthermore, conventional systems have struggled to adequately understand users' emotional states and provide appropriate dialogue and support. It is necessary to address these challenges and improve users' social interaction and cognitive function.

[0736] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0737] In this invention, the server includes means for collecting characteristic information of users of different age groups and generating personalized dialogues using language analysis technology based on that information; means for analyzing the user's voice and text information using a machine learning model and evaluating their emotions in real time; and means for integrating the user's emotional state and profile information to generate material for providing optimal dialogue content and actions. This promotes meaningful interaction among users of different age groups and, by providing support tailored to their emotions, enables improvement of users' cognitive functions and strengthens their social connections.

[0738] "Characteristic information" refers to information, including a user's interests, age, and past behavioral history, that is used to identify a user and provide a personalized experience.

[0739] "Language analysis technology" refers to the technology that allows computer systems to analyze text and audio data obtained from users, understand their meaning, and generate responses.

[0740] "Personalized dialogue" refers to a type of dialogue that is optimized and personalized based on the user's interests, preferences, and emotional state.

[0741] A "machine learning model" refers to a technical framework in which algorithms are trained using large amounts of data to make predictions and decisions based on new data.

[0742] "Real-time emotional assessment" refers to a process that instantly analyzes information obtained from voice and text to immediately recognize the user's emotional state.

[0743] "Profile information" refers to a comprehensive set of information that summarizes a user's attributes, history, interests, behavioral patterns, and more.

[0744] "Materials for providing dialogue content and actions" refers to information and data used to suggest appropriate communication and activities according to the user's emotions and interests.

[0745] "User cognitive function" refers to the brain's ability to acquire, understand, and apply information, enabling conscious thinking and problem-solving.

[0746] "Social connections" refer to the human relationships and networks formed through users influencing and supporting each other.

[0747] This invention is a system that promotes dialogue and interaction among users of different age groups, enhances users' cognitive functions, and strengthens social connections. Specific embodiments for carrying out this invention are described below.

[0748] First, the server plays a central role in data collection. The server collects user characteristic information and stores it in a database. This information includes interests, age, and past behavioral history. Then, using language analysis technology, it generates personalized dialogue optimized for the user. The server uses generative AI models, such as OpenAI's GPT, to form the dialogue content. Voice and text information is collected with the user's permission and used as characteristic information.

[0749] Next, the emotion engine connects to the server, analyzes the user's voice and text data, and evaluates their emotions in real time. This engine uses emotion analysis algorithms to evaluate the user's emotional state as numerical data, providing the server with the necessary information.

[0750] The terminal then provides the user with personalized conversations and action suggestions received from the server. The terminal's user interface operates on hardware devices such as smartphones and tablets, enabling interaction with the user. Specifically, the terminal displays prompts on the screen such as "How are you feeling today?" and allows the user to input how they are feeling.

[0751] Users experience interactions and activities based on personalized conversations and suggestions presented by the device. For example, when elderly and young users use the system, the system generates topics tailored to their respective interests and provides support to improve the quality of the conversation based on their emotional state.

[0752] An example of a prompt might be: "Please suggest a dialogue topic that takes into account the user's current emotional state and promotes meaningful interaction between different age groups."

[0753] In this way, the system aims to promote interaction between different generations and improve users' cognitive function and social connections.

[0754] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0755] Step 1:

[0756] The server collects user characteristic information. As input, it retrieves user registration data, interest data, and past conversation history. To store this data in the database, it converts and organizes it into a structured format. This process prepares the foundational data for future conversation generation. Specifically, it uses APIs to retrieve data from external sources and stores it in internal data storage.

[0757] Step 2:

[0758] The emotion engine analyzes the user's voice and text data. It receives voice and text input from the user via their device as input. Using an analysis algorithm, it detects the emotional state from each data point and outputs it as numerical data. Specifically, it uses speech recognition software to convert voice to text, and then processes that text with the emotion analysis algorithm.

[0759] Step 3:

[0760] The server generates personalized conversations based on collected trait information and sentiment data. It uses user trait information and sentiment data as input to send prompts to the generative AI model. The output is a conversation optimized for the user. Specifically, it calls the generative AI model and sends data via an API to generate prompt sentences.

[0761] Step 4:

[0762] The terminal presents the user with personalized conversations retrieved from the server. It uses conversation data received from the server as input. As output, it displays the conversation content on the user interface and prompts the user for a response. Specifically, it displays prompts through the screen display and receives user input.

[0763] Step 5:

[0764] The server updates the content it provides based on user feedback. It receives user responses and comments sent from the terminal as input. As output, it saves the feedback to a database and incorporates it into future dialogue generation. Specifically, it analyzes the response data and adds newly obtained data to the characteristic information.

[0765] Through these steps, the system provides a personalized experience based on the user's emotions and interests, and promotes meaningful interaction between different age groups.

[0766] (Application Example 2)

[0767] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0768] There is a need to facilitate communication among users of different age groups and provide appropriate conversations and activities based on the emotional state of the users, thereby improving cognitive function and strengthening social connections.

[0769] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0770] In this invention, the server includes means for collecting interest data from users of different age groups and generating personalized conversations using natural language processing technology based on that data; means for selecting and providing activities that stimulate cognitive functions according to the user's age and interests; means for analyzing the emotional state of users during conversations and activities and providing necessary responses and support; and means for adjusting optimal conversations and suggestions in real time based on the user's emotional state to support communication through online dialogue. This promotes meaningful interaction between different generations and enables improvement of users' cognitive functions and strengthening of social connections.

[0771] "Different age groups" refers to groups of users of different ages, such as elderly people and young people.

[0772] "Interest data" refers to information about the things and hobbies that users are interested in, which enables the delivery of personalized content.

[0773] "Natural language processing technology" is a technology that processes human language using computers, and is used for tasks such as text generation and sentiment analysis.

[0774] "Personalized conversation" refers to dialogue content optimized based on the individual user's interests and emotions, with the aim of providing meaningful conversations for the user.

[0775] "Activities that stimulate cognitive function" refer to activities designed to improve users' cognitive abilities, such as memory and thinking skills.

[0776] "Emotional state" refers to the emotions a user feels in a particular situation, encompassing psychological states such as joy, sadness, and stress.

[0777] "Responses and support" refers to replies, helpful actions, and messages provided in response to the user's statements and emotions.

[0778] "Exchange activities" refer to activities in which different users interact with each other and communicate based on common interests and themes.

[0779] "Real-time adjustment" refers to a state where the system's responses and suggestions are immediately optimized based on user feedback.

[0780] The system for implementing this invention consists of a server, a terminal, and a user working together. The server collects interest data from users of different age groups and stores it in a database. Using natural language processing technology, it generates personalized conversations based on the collected data. The Google Natural Language API is used to achieve this natural language processing. The server also uses IBM Watson Tone Analyzer to analyze the user's emotional state and personalize responses as needed.

[0781] The device visually and audibly presents personalized conversations and activities sent from the server to the user. This allows the user to enjoy interesting content in real time. By using a mobile device such as a smartphone, the device provides a user-friendly interface.

[0782] Users provide feedback on the information received via their devices, and the conversation is adjusted in real time based on this feedback. This system facilitates meaningful dialogue between older and younger generations, leading to improved cognitive function and strengthened social connections.

[0783] As a concrete example, consider a case where a grandmother and grandchild living far apart use this system to deepen their online connection. When the grandmother starts talking about caring for her garden plants, the system can analyze her interests and provide more detailed gardening tips. This allows the grandmother to continue the conversation with her grandchild on a variety of topics, leading to natural communication.

[0784] An example of a prompt to the generation AI model is, "Generate conversation topics that both older and younger users can enjoy." Through this prompt, the system generates new ideas to enrich interactions between users of different age groups.

[0785] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0786] Step 1:

[0787] The server collects user interest data from a database. The input is user profile information (age, hobbies, past conversation history, etc.), and the output is a dataset organized for personalized conversation generation. This data is used to prepare for identifying conversation topics suitable for each user.

[0788] Step 2:

[0789] The server generates personalized conversations using the Google Natural Language API based on the collected data. The input is user interest data, and the output is a conversation script presented to the user. A natural language processing engine then creates the most optimal conversation flow for the user.

[0790] Step 3:

[0791] The server uses IBM Watson Tone Analyzer to analyze the user's emotional state. Input is user voice and text data, and output is real-time evaluated emotional state data. Based on this analysis, the server identifies the user's emotions and prepares an appropriate response.

[0792] Step 4:

[0793] The device presents the user with personalized conversation and activity suggestions sent from the server through a user interface. Input consists of conversation scripts and suggested activities from the server, while output is a visual and auditory representation of the content on the user interface. This allows the user to initiate a dialogue.

[0794] Step 5:

[0795] The user provides feedback while interacting through the device. Input is the user's responses and interactions, and output is feedback data sent to the server. Based on this feedback, the server adjusts the next conversation or activity.

[0796] Step 6:

[0797] The server analyzes user feedback in real time and adjusts the conversation topic and activities as needed. Inputs include feedback data and analyzed sentiment states, while outputs include updated dialogue scripts and activity suggestions. This ensures the conversation flows optimally.

[0798] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0799] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0800] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0801] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0802] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0803] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0804] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0805] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0806] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0807] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0808] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0809] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0810] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0811] 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.

[0812] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0813] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0814] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0815] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0816] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0817] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0818] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0819] The following is further disclosed regarding the embodiments described above.

[0820] (Claim 1)

[0821] A means of collecting interest data from users of different age groups and generating personalized conversations using natural language processing technology based on that data,

[0822] A means of selecting and providing activities that stimulate cognitive function according to the user's age and interests,

[0823] A means of analyzing the emotional states of users during their interactions and activities, and providing responses and support as needed.

[0824] A system that includes means for suggesting interaction activities among users with common interests.

[0825] (Claim 2)

[0826] The system according to claim 1, which displays information via a user interface in order to present a user with a personalized conversation topic.

[0827] (Claim 3)

[0828] The system according to claim 1, which provides support messages according to the emotional state based on the results of sentiment analysis between users.

[0829] "Example 1"

[0830] (Claim 1)

[0831] A means of collecting interest data from users of different age groups and generating personalized conversations using a generative model based on that data,

[0832] A means of selecting and providing activities that stimulate cognitive function according to the user's age and interests,

[0833] A means of analyzing the emotional states of users during conversations and activities, and providing responses and support as needed.

[0834] A means of proposing interaction activities among users with common interests,

[0835] A means of interactively displaying conversation content and activity suggestions generated for the user via a terminal,

[0836] A means of responding to users in real time based on sentiment analysis results,

[0837] A system that includes means for suggesting intergenerational exchange events based on user information.

[0838] (Claim 2)

[0839] The system according to claim 1, which presents personalized conversation topics to the user via a user interface.

[0840] (Claim 3)

[0841] The system according to claim 1, which provides support messages according to emotional states based on the results of sentiment analysis between users.

[0842] "Application Example 1"

[0843] (Claim 1)

[0844] A means for collecting interest information from users of different age groups and generating personalized conversations using natural language processing technology based on that information,

[0845] A means of selecting and providing activities that stimulate cognitive function according to the user's age and interests,

[0846] A means of analyzing the emotional states of users during conversations and activities, and providing responses and support as needed.

[0847] A means of proposing interaction activities and events among users with common interests,

[0848] A system that utilizes information on local community events and activities to suggest activities suitable for users.

[0849] (Claim 2)

[0850] The system according to claim 1, which displays information via an information processing device in order to present users with personalized conversation topics and local activity information.

[0851] (Claim 3)

[0852] The system according to claim 1, which provides support messages according to the emotional state based on the results of sentiment analysis between users.

[0853] "Example 2 of combining an emotion engine"

[0854] (Claim 1)

[0855] A means for collecting characteristic information of users of different age groups and generating personalized dialogues using language analysis technology based on that information,

[0856] A method for analyzing user voice and text information using machine learning models to evaluate emotions in real time,

[0857] A means for integrating the user's emotional state and profile information to generate materials for providing optimal dialogue content and actions,

[0858] A means of displaying personalized conversations and suggestions via a communication terminal, and adjusting the conversations and suggestions according to the user's response,

[0859] A means to update data based on user feedback so that subsequent interactions and suggestions become more personalized,

[0860] A system that includes this.

[0861] (Claim 2)

[0862] The system according to claim 1, which displays information using a user interface in order to present dialogue themes and activities adapted to the user.

[0863] (Claim 3)

[0864] The system according to claim 1, which provides a support message appropriate to the user's emotional state based on the results of emotion analysis.

[0865] "Application example 2 when combining with an emotional engine"

[0866] (Claim 1)

[0867] A means of collecting interest data from users of different age groups and generating personalized conversations using natural language processing technology based on that data,

[0868] A means of selecting and providing activities that stimulate cognitive function according to the user's age and interests,

[0869] A means of analyzing the emotional states of users during their interactions and activities, and providing responses and support as needed.

[0870] A means of proposing interaction activities among users with common interests,

[0871] A means of supporting communication through online dialogue by adjusting the optimal conversation and suggestions in real time based on the user's emotional state,

[0872] A system that utilizes sentiment analysis to enhance specific dialogue themes and facilitate interaction among users.

[0873] (Claim 2)

[0874] The system according to claim 1, which uses a generative AI model to display information via a user interface in order to present conversation topics optimized for the user.

[0875] (Claim 3)

[0876] The system according to claim 1, which provides support messages tailored to the emotional state of users based on the results of sentiment analysis among users, thereby realizing a personalized experience. [Explanation of symbols]

[0877] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of collecting interest data from users of different age groups and generating personalized conversations using natural language processing technology based on that data, A means of selecting and providing activities that stimulate cognitive function according to the user's age and interests, A means of analyzing the emotional states of users during their interactions and activities, and providing responses and support as needed. A system that includes means for suggesting interaction activities among users with common interests.

2. The system according to claim 1, which displays information via a user interface in order to present a user with a personalized conversation topic.

3. The system according to claim 1, which provides support messages according to the emotional state based on the results of sentiment analysis between users.

Images