system

Abstract

We provide the system. [Solution] A means of acquiring knowledge from elderly people as voice or text data using speech recognition technology, A method for analyzing the acquired data using natural language processing algorithms and classifying it into general themes, A means of storing classified data on a digital information storage medium and providing it to users as needed, A means of providing an interface for sharing knowledge about the elderly among caregivers, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is 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 character of the chatbot, 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 an aging society, there is a problem that the rich knowledge and experience of the elderly are not sufficiently passed on to the next generation. Also, it is difficult for the elderly to master digital technology, and there is a problem that their knowledge cannot be digitized and utilized across generations. Furthermore, since there is a lack of means to link and preserve the knowledge of the elderly with the local culture and history, there is a risk that the unique traditions of the region will be lost to the next generation. It is necessary to solve such problems and construct a means to effectively and efficiently inherit the knowledge of the elderly to the next generation.

Means for Solving the Problems

[0005] This invention provides a means for acquiring knowledge from elderly individuals as audio or text data. The acquired data is analyzed using a natural language processing algorithm and classified by theme to clarify the information structure. The classified data is then stored in a digital database and made available to users as needed via a user interface. Furthermore, by organizing the data based on unique local culture and history, the invention promotes the transmission of local traditions. This creates a system that enables the next generation to receive and utilize the knowledge and experience of the elderly in an easily accessible format.

[0006] The term "elderly" generally refers to individuals aged 65 and over who possess a wealth of life experience and knowledge.

[0007] "Audio or text data" refers to a format for recording the knowledge and experience of older adults, and includes information expressed as audio data or written words.

[0008] "Natural language processing algorithms" refer to algorithms used by computers to understand, analyze, and process human language.

[0009] "Classifying by theme" refers to the act of organizing diverse information according to a specific subject or topic, and grouping related information together.

[0010] A "digital database" refers to a collection of information stored in digital format, characterized by its structured nature for easy searching and retrieval.

[0011] "User interface" refers to the screen design and usage methods that allow users to interact with a system and access information.

[0012] "Regional culture and history" refers to lifestyles, arts, beliefs, customs, or events that have developed and been passed down uniquely within a particular region. [Brief explanation of the drawing]

[0013] [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]

[0014] An example of an embodiment of the system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

[0016] In the following embodiments, a numbered 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.

[0017] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a numbered 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.

[0019] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0020] 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."

[0021] [First Embodiment]

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

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0028] 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.

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

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] The system of this invention is designed to effectively collect, classify, and store knowledge and experience from the elderly and provide it to future generations. First, the terminal functions as an interface for the elderly, acquiring information through voice or text input. In this case, voice input is converted into text data using speech recognition technology. For example, if an elderly person tells a story about how a special farming method was used in this area in the past, this is recorded as text data.

[0035] Next, the server analyzes the received text data. Using natural language processing algorithms, it extracts keywords and relationships within the text and classifies them under themes such as "agricultural technology." The classified data is stored in a digital database, enabling information structuring and efficient searching.

[0036] Furthermore, the server has an interface that provides structured data to users. It is designed so that young people and educators can search and view information from the database, and if a user seeks information on, for example, the "history of agricultural technology," that organized knowledge will be immediately available for reference. The system presents information in a visually easy-to-understand layout and provides valuable information to users through interactive elements.

[0037] Furthermore, the server provides additional information related to local culture and history, building a foundation for understanding and utilizing unique local cultural customs. This also promotes intergenerational exchange within the community when used in local events.

[0038] Thus, the system of the present invention provides an effective means of digitally preserving the valuable knowledge possessed by the elderly and passing it on to future generations. As a specific example, it can be used to collect agricultural know-how from elderly people in rural areas and make it accessible to young people in the region, thereby supporting the development of new agricultural practices that utilize local resources.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The device acquires voice input from the elderly person. At this time, the voice input function is activated and configured to collect information from the spoken words. The collected voice data is converted into text format in real time by a speech recognition module.

[0042] Step 2:

[0043] The terminal sends the converted text data to the server. This transmission is secure, with the data encrypted for security purposes, and uses a reliable communication protocol.

[0044] Step 3:

[0045] The server analyzes the received text data. It utilizes natural language processing algorithms to extract keywords from the text and classify the content into specific categories. For example, it organizes data according to themes such as "agricultural technology" or "lifestyle and culture."

[0046] Step 4:

[0047] The server stores the classified data in a digital database. This storage process involves tagging the data, adding metadata, and generating indexes to improve search efficiency.

[0048] Step 5:

[0049] Users can access the database and search for topics that interest them. Through the user interface, they can easily enter keywords into the search field and quickly retrieve relevant information.

[0050] Step 6:

[0051] The server extracts relevant information from the database in response to a user's search request and displays it in the user interface. It provides a detailed view of the information the user is looking for, offering knowledge in a visually organized manner.

[0052] Step 7:

[0053] The server also integrates information about the region's unique culture and history, and notifies users of local community events. This allows users to learn about local cultural assets and deepen their experience through actual interaction.

[0054] (Example 1)

[0055] 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."

[0056] In an aging society, there is a need to efficiently collect the valuable knowledge and experience of the elderly and pass it on to younger generations and local communities. However, systems for systematically organizing and preserving information about the elderly and providing it to users who need it in a visually and easily understandable way are currently not adequately developed. Furthermore, mechanisms for promoting intergenerational knowledge exchange by utilizing unique local cultures and histories are also insufficient.

[0057] 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.

[0058] In this invention, the server includes means for using a device to acquire knowledge from elderly people as voice or text data and converting it into digital signals, means for converting the acquired voice data into text data, and means for analyzing the text data using natural language processing technology to extract keywords and classify them by theme. This enables the efficient transmission of knowledge to younger generations and the preservation of regional cultural values ​​by digitizing and systematically storing the knowledge of elderly people.

[0059] The term "elderly" refers to people who are considered older in society and are mature individuals with a wealth of experience and knowledge.

[0060] "Audio data" refers to a collection of information in which human voices are recorded in digital format.

[0061] "Text data" refers to a collection of information recorded in digital format using character data.

[0062] A "digital signal" is a signal format suitable for communication and processing using digital data.

[0063] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0064] A "keyword" is a word or phrase that has important meaning within a text or data.

[0065] A "theme" is the main topic or category used when organizing and analyzing information.

[0066] A "digital storage device" is a device or system for storing information in digital format.

[0067] A "visual and interactive format" refers to a method of presentation in which information is presented to the user in a way that is easy to see and allows for interaction.

[0068] "Regional cultural characteristics" refer to unique customs and values ​​found only in a particular region.

[0069] "Historical background" refers to past events and circumstances that constitute the process by which things are formed.

[0070] A "user interface" is a concept that refers to the screens and means of operation that users use to interact with a system.

[0071] "Activity information" refers to detailed information about a specific event or activity.

[0072] This invention is a system for digitizing the knowledge of the elderly and transmitting it to the next generation by linking an information acquisition device and a server.

[0073] First, the terminal functions as a device for acquiring voice or text data from elderly individuals. Voice data is captured in real time using a highly sensitive microphone and acoustic signal processing software (e.g., a common speech recognition API). The voice data is converted into a digital signal, and then into text data. This textual information forms the basis for subsequent analysis.

[0074] After receiving this text data, the server analyzes it using natural language processing techniques (e.g., a common natural language processing library). The server extracts keywords from the text and classifies them based on specific themes. The classified data is stored in a digital storage device for efficient retrieval and use later.

[0075] Furthermore, the server provides a user interface for users to view information. This interface enables visual display and interactive manipulation of data, and is designed to make knowledge more easily understood by older adults. This creates an environment where information is readily available.

[0076] For example, if an elderly person shares information such as, "In the past, a specific farming method was used in agriculture in this region," that information could be stored in a digital memory device under the theme of "agricultural technology." Then, a system would be provided that allows young people or researchers to easily access this information when they search for information such as "the history of agricultural technology."

[0077] An example of a prompt would be, "Please tell me about the agricultural techniques that have been practiced in this region for a long time, including specific methods and their background." This makes it possible to provide a system that allows users to easily obtain a wealth of information about region-specific knowledge and history.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] The device acquires voices from elderly individuals. Using a high-sensitivity microphone, it converts the voice signal into digital data in real time. The input is the elderly person's voice, and the output is the digitized voice signal. Specifically, when an elderly person speaks about old farming methods, the device records their words in digital format.

[0081] Step 2:

[0082] The terminal converts acquired digital audio signals into text data. Using speech recognition technology, it analyzes the audio signal and generates text data. The input to this process is a digital audio signal, and the output is text. Specifically, the audio data is converted into text about a particular technique, such as agricultural technology.

[0083] Step 3:

[0084] The server receives text data from the terminal. The server prepares to receive and store the data. The input is the text data sent from the terminal, and the output is the storage of the data within the server. Specifically, the data converted into text on the terminal is sent to the server.

[0085] Step 4:

[0086] The server analyzes the received text data using natural language processing techniques. It tokenizes the data and extracts keywords. In this process, the input is the received text data, and the output is a keyword list. Specifically, the keyword "agricultural technology" is identified and extracted.

[0087] Step 5:

[0088] The server classifies the text data based on the extracted keywords. It classifies the data by theme and stores it in a digital storage device. The input to this process is a keyword list and text data, and the output is a structured data set. Specifically, the data is stored in the "Agricultural Technology" section of the database.

[0089] Step 6:

[0090] The server provides a user interface that allows users to search and view information. It searches the database and displays relevant information visually. The input to this process is the user's search query, and the output is the visualized search results. For example, if a user enters the query "history of agricultural technology," the relevant information will be displayed in an easy-to-read format.

[0091] (Application Example 1)

[0092] 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."

[0093] There is a need to effectively collect the knowledge and experience of the elderly and preserve it in a form that can be used in caregiving and education settings. In particular, there is a lack of interfaces to not only preserve the knowledge of the elderly as digital data, but also to easily share it among different generations and maximize its value. Against this backdrop, the challenge is to provide a system that effectively utilizes the knowledge of the elderly while promoting intergenerational exchange.

[0094] 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.

[0095] In this invention, the server includes means for acquiring knowledge from elderly people as voice or text data using speech recognition technology, means for classifying the acquired data into general themes using a natural language processing algorithm, and means for storing the classified data in a digital information storage medium and providing it to users as needed. This enables the effective sharing of elderly people's knowledge among caregivers and the revitalization of intergenerational exchange based on that knowledge.

[0096] "Speech recognition technology" is a technology that converts speech data into text data, making it possible to treat speech information obtained from elderly people as text information.

[0097] A "natural language processing algorithm" is a technology that analyzes the meaning and relationships of acquired text data and classifies it into specific themes or categories.

[0098] A "digital information storage medium" refers to a medium that can store data electronically and is used to preserve and manage the knowledge of elderly people over long periods of time.

[0099] "Users" refer to those who access and utilize the knowledge and experience of the elderly through this system.

[0100] An "interface" is the part of a system that provides a user interface and user experience for users to interact with the system.

[0101] A "caregiver" is someone who specializes in caring for the elderly, and who plays a role in using this system to collect knowledge about the elderly and utilize it in caregiving.

[0102] To realize this application, a system is needed that integrates speech recognition technology, natural language processing algorithms, digital information storage media, and a user interface.

[0103] The server uses the Google® Cloud Speech-to-Text API to convert speech data obtained from elderly individuals into text data. The transcribed data is then analyzed using natural language processing algorithms and categorized into general themes. The categorized data is stored on digital information storage media such as Google FI® rebase and made accessible to users.

[0104] The device takes the form of a smartphone or tablet and provides a smooth interface for caregivers to collect knowledge while directly interacting with the elderly. This allows caregivers to efficiently record the elderly's knowledge and share it with other users.

[0105] For example, when an elderly person talks about their unique gardening techniques, their voice is instantly transcribed into text, categorized based on similar themes, and then saved so that it can be accessed by other care facilities. This makes knowledge sharing across regions a reality.

[0106] An example of a prompt for a generative AI model is: "Convert the following audio data to text, extract the keywords, and save them. The topic is gardening techniques for seniors."

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The device collects voice data through conversations with elderly individuals. This voice data is input using the microphone of a smartphone or tablet. The voice data is then transmitted to a server as a stream.

[0110] Step 2:

[0111] The server sends the received audio data to the Google Cloud Speech-to-Text API, where it is converted into text data. The input is audio data, and the output is the corresponding text data. The server then passes the converted text data to the next processing step.

[0112] Step 3:

[0113] The server feeds the received text data into a natural language processing (NLP) algorithm to perform keyword extraction and theme classification. This process takes text data as input and generates keywords and theme classifications as output. Specifically, it uses TF-IDF and topic modeling techniques.

[0114] Step 4:

[0115] The server stores the categorized data in Google Firebase. This step takes categorized text data as input and outputs it by saving it to the database. Firebase has the advantage of being able to store and retrieve data quickly.

[0116] Step 5:

[0117] The user accesses stored data and searches for necessary information using a user interface. This step takes the user's search query as input and returns relevant categorized data as output. Specific actions include implementing a search function within the UI.

[0118] 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.

[0119] The system of this invention collects the knowledge and experience of elderly people and passes it on to the next generation, while also recognizing the emotional state of users and using this information for interaction and information provision. First, the terminal acquires voice or text data from the elderly person. This data is converted into text using speech recognition technology and sent to the server. The server uses a natural language processing algorithm to analyze the acquired data and classify it by theme. The classified data is stored in a database and provided to the user as needed.

[0120] Furthermore, this system incorporates an emotion engine that analyzes user input and responses in real time and has the capability to recognize emotions. Emotion recognition includes facial expression analysis and voice tone analysis, analyzing various data points to identify emotional states. For example, if the system detects "interest" from a user's facial expression while they are viewing information, it can immediately suggest additional information or related events that correspond to that emotion.

[0121] Based on recognized emotions, the server appropriately modifies the interface and provides content that will pique the user's interest. For example, if the emotion engine detects a positive reaction when a user is browsing information about local folklore, information about relevant events taking place in that region will be displayed on the screen. Through this process, users can obtain a more interesting and personalized experience.

[0122] This system configuration facilitates user interaction through emotion recognition, thereby improving the quality of communication. Furthermore, it can effectively support the deepening of intergenerational exchange and the transmission of local culture.

[0123] The following describes the processing flow.

[0124] Step 1:

[0125] The device acquires voice or text data from the elderly person. In the case of voice input, it converts it to text in real time using speech recognition. The converted text data is encrypted and prepared for transmission to the server.

[0126] Step 2:

[0127] The server receives text data sent from the terminal. The received data is analyzed using natural language processing algorithms to extract important keywords and topics. This allows the data to be categorized into specific themes.

[0128] Step 3:

[0129] The server stores the classified text data in a digital database. During storage, tags are added to generate metadata and create an index to facilitate future searching.

[0130] Step 4:

[0131] The emotion engine recognizes the user's emotional state through the user interface. It uses sensor data and microphone input to analyze facial expressions and voice tone to identify emotions.

[0132] Step 5:

[0133] The server dynamically adapts the interface based on the recognized user's emotions. For example, if the user expresses "surprise" or "interest," it displays relevant visual effects and additional information on the interface.

[0134] Step 6:

[0135] Users can view information provided through emotional feedback and act based on the system's suggestions. For example, information encouraging participation in a specific cultural event may be displayed, and users can then take steps to participate directly from the screen.

[0136] Step 7:

[0137] The server records user actions and accumulates data on usage patterns and emotional responses. This creates a feedback loop to improve the accuracy of future suggestions and make the user experience more personalized.

[0138] (Example 2)

[0139] 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".

[0140] In an aging society, passing on knowledge and culture to the next generation is a crucial challenge. However, there is a lack of effective means to collect, structure, and transmit the abundant knowledge and experience of the elderly to the next generation. Furthermore, there is a need to improve user interest and understanding by providing information that takes into account the emotional state of individuals. To address these challenges, there is a need for systems that promote intergenerational exchange and realize the transmission and utilization of information.

[0141] 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.

[0142] In this invention, the server includes means for acquiring information as voice or text data from the person providing the information, means for analyzing the acquired data using an information processing algorithm and classifying it into categories, means for storing the classified data on a recording medium and providing it to the user as needed, means for sensing the user's emotional state, and means for adjusting and providing the presented information based on the sensed emotions. This makes it possible not only to effectively collect and structure the knowledge and experience of the elderly, but also to provide users with customized information that matches their emotions. This realizes the transmission of culture and the promotion of intergenerational exchange.

[0143] "Target recipients of information" refers to individuals or groups that are the primary source of data collection, and primarily includes elderly people.

[0144] "Audio or text data" refers to a form of information transmitted through language, including audio recordings and text-typed information.

[0145] An "information processing algorithm" refers to a computational method for analyzing, structuring, and classifying received data, and includes natural language processing techniques.

[0146] "Classifying by category" refers to the act of grouping data according to its content or theme, which makes it easier to search for and use information.

[0147] "Recording medium" refers to a technical means for storing digital data, and includes databases and cloud storage.

[0148] "Users" refers to individuals or groups who are able to receive and use information from the system, and includes those who play a role in intergenerational exchange.

[0149] "Emotional state sensing" refers to the technological process of detecting and analyzing an individual's emotional responses, and includes facial recognition and voice analysis.

[0150] "Adjusting and providing information" refers to the act of optimizing the selection and display of information according to the user's emotions and circumstances, thereby achieving personalized information delivery.

[0151] The system of the present invention effectively collects the knowledge and experience of the elderly and passes it on to the next generation, while also recognizing the emotional state of the user and utilizing this information for interaction and information provision. Specific embodiments for carrying out the invention are shown below.

[0152] The terminal is responsible for collecting data from information providers through voice or text input. Voice data is converted into text data using speech recognition technology. Specifically, a common speech recognition API is used to convert speech to text, and the result is sent to the server. In this process, for example, a general-purpose voice input device or keyboard is used.

[0153] The server analyzes the received text data using natural language processing algorithms. Here, general-purpose natural language processing software is used to classify the data into specific themes and categories. This classified data is stored on a storage medium called a database and provided to the user as needed. Furthermore, to analyze the user's emotional state, the server uses image processing and speech analysis technologies to recognize emotions in real time. This process utilizes common facial expression analysis software and speech tone analysis tools.

[0154] Users can enjoy a personalized experience based on the information they receive through the system. By recognizing the user's emotional state, the server can appropriately present information that matches that emotion. For example, if a user expresses positive emotions while viewing information including local folklore, information about related events will be provided. In this way, users can obtain customized information based on their interests and preferences.

[0155] Examples of prompts include, "How can we collect testimonials from elderly people and pass on that knowledge to the next generation?" and "How can we improve the user experience through emotion recognition?" Such prompts can be used to effectively utilize the system's functions.

[0156] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0157] Step 1:

[0158] The terminal obtains information from the information provider as voice or text data. In the case of voice data, the terminal collects the voice using a voice input device. The input voice data is converted into text data by speech recognition software, and this text is sent to the server. In the case of text data, it is entered directly via a keyboard or similar device and sent to the server.

[0159] Step 2:

[0160] The server analyzes the received text data using natural language processing algorithms. At this stage, the server classifies the data into different categories. Using a generative AI model, it identifies the theme of each data point from the input text data and obtains classification information as output. This output is stored in the database as text data with category labels. Specifically, categories such as "culture" and "history" are used.

[0161] Step 3:

[0162] The server stores the classified data on a storage medium called a database. In this step, the organized data is stored in a format that can be easily searched and accessed later. By using database software to tag related information, subsequent query processing becomes more efficient. The information stored in the database can be retrieved when requested by the user.

[0163] Step 4:

[0164] When a user accesses the system, the server senses the user's emotional state before providing information to the interface. The user's facial expressions and voice tone become input data, which are then analyzed by an emotion recognition engine. Based on the detected emotional information, the information provided to the user is customized. This process involves image processing and voice analysis tools.

[0165] Step 5:

[0166] The server presents the user with information tailored to their emotional state. Relevant information is selected from the user's emotional data and stored data, and output to the user in visual and auditory ways. For example, if a user indicates "interest," relevant local event information is displayed, enriching the user's experience. This allows the user to access personalized information.

[0167] (Application Example 2)

[0168] 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".

[0169] In modern society, the wealth of knowledge and experience possessed by the elderly is not being adequately passed on to the next generation, and there is a particular risk of losing information about unique local cultures and histories. Furthermore, there is a lack of smooth communication between the elderly and younger generations, highlighting the need to promote intergenerational exchange. Additionally, a challenge remains: there is no system in place to appropriately recognize the emotional state of the elderly and provide them with appropriate information accordingly.

[0170] 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.

[0171] In this invention, the server includes means for acquiring knowledge from elderly people as voice or text data; means for analyzing the acquired data using a natural language processing algorithm and classifying it by theme; means for storing the classified data in an information storage means and providing it to the user as needed; means for analyzing the user's facial expressions and tone of voice to identify their emotional state; means for presenting relevant information and event information to the user based on the identified emotions; and a software program for operating the means on a smart device. This enables the effective transfer of elderly people's knowledge and experience to the next generation, facilitates interaction with elderly people, and allows for the provision of personalized information according to the user's emotional state.

[0172] "Elderly people" are individuals above a certain age who possess abundant knowledge and experience and are expected to pass it on to the next generation.

[0173] "Voice or text data" refers to information obtained from elderly individuals, and is data expressed in either voice input or text input format.

[0174] A "natural language processing algorithm" is a set of computational procedures for analyzing acquired audio or text data and classifying and organizing it in a way that humans can understand.

[0175] "Classifying by theme" means organizing acquired data based on specific topics or areas and consolidating it into a database.

[0176] "Information storage means" refers to a digital storage device for storing analyzed and classified data.

[0177] A "user" is an individual or organization that uses the system to receive information or services.

[0178] "Analyzing facial expressions and tone of voice" means using facial recognition technology and voice analysis technology to evaluate changes in these in order to identify the user's emotional state.

[0179] "Presenting relevant information and event information" means displaying appropriate supplementary information or information about events that interest the user, tailored to their emotional state, on the device screen.

[0180] A "smart device" is a portable electronic device capable of performing calculations, and examples include mobile phones and tablet devices.

[0181] A "software program" is a set of instructions or code that constitutes a system and performs a specific function.

[0182] The system for implementing this invention aims to acquire knowledge from the elderly and provide users with information that is more emotionally responsive. The system's program is structured as follows:

[0183] The device acquires voice or text data from the elderly person. The voice data is converted into text data using speech recognition technology. Specifically, speech recognition software such as the Google Cloud Speech-to-Text API is used. The converted text data is sent to the server.

[0184] The server analyzes this text data using natural language processing algorithms. For example, by using a natural language processing library such as spaCy, the data is classified into specific themes. The classified data is then stored in an information storage system. When a user needs the data, they can access the database and retrieve the information.

[0185] Furthermore, the terminal and server analyze the user's facial expressions and tone of voice to identify their emotional state. By utilizing Microsoft® Azure® Face API and Emotion API, it is possible to analyze the user's emotions in real time. Based on the analyzed emotions, relevant information and event information are displayed on the terminal screen.

[0186] For example, if an elderly person is sharing a local folktale and a user who is interested in the story smiles, the system can then provide information about events related to that area or additional reading material. This deepens communication and promotes intergenerational exchange.

[0187] This system can be used to provide an even higher level of user experience. An example of a prompt when using a generative AI model is: "Design an application that converts the voices of elderly people from audio to text, analyzes the content, and categorizes it. It also detects changes in emotion using a camera and microphone and suggests additional content to engage that person."

[0188] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0189] Step 1:

[0190] The device acquires voice or text data from the elderly person. The input is voice or text data from the elderly person; if it's voice data, it's converted to text data using the Google Cloud Speech-to-Text API. The output is the text data sent to the server.

[0191] Step 2:

[0192] The server analyzes received text data using natural language processing algorithms. The input is transformed text data, utilizing libraries such as spaCy. The data is categorized by theme based on its content. The output is the categorized text data.

[0193] Step 3:

[0194] The server stores the classified data in an information storage system. The input is text data classified by theme, and this data is stored in a database. The output is the data stored in the database.

[0195] Step 4:

[0196] The device analyzes the user's facial expressions and tone of voice to identify their emotional state. Input consists of the user's facial expression and voice data, which are processed using the Microsoft Azure Face API and Emotion API. The output is the identified emotional state.

[0197] Step 5:

[0198] The server displays relevant and event information on the device screen based on the identified emotions. The input consists of emotional states and related data, and the content is selected to match the user's interests. The output is the final content displayed on the device screen.

[0199] 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.

[0200] Data generation model 58 is a type of 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.

[0201] 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.

[0202] [Second Embodiment]

[0203] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0204] 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.

[0205] 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).

[0206] 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.

[0207] 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.

[0208] 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).

[0209] 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.

[0210] 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.

[0211] 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.

[0212] 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.

[0213] 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.

[0214] 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".

[0215] The system of this invention is designed to effectively collect, classify, and store knowledge and experience from the elderly and provide it to future generations. First, the terminal functions as an interface for the elderly, acquiring information through voice or text input. In this case, voice input is converted into text data using speech recognition technology. For example, if an elderly person tells a story about how a special farming method was used in this area in the past, this is recorded as text data.

[0216] Next, the server analyzes the received text data. Using natural language processing algorithms, it extracts keywords and relationships within the text and classifies them under themes such as "agricultural technology." The classified data is stored in a digital database, enabling information structuring and efficient searching.

[0217] Furthermore, the server has an interface that provides structured data to users. It is designed so that young people and educators can search and view information from the database, and if a user seeks information on, for example, the "history of agricultural technology," that organized knowledge will be immediately available for reference. The system presents information in a visually easy-to-understand layout and provides valuable information to users through interactive elements.

[0218] Furthermore, the server provides additional information related to local culture and history, building a foundation for understanding and utilizing unique local cultural customs. This also promotes intergenerational exchange within the community when used in local events.

[0219] Thus, the system of the present invention provides an effective means of digitally preserving the valuable knowledge possessed by the elderly and passing it on to future generations. As a specific example, it can be used to collect agricultural know-how from elderly people in rural areas and make it accessible to young people in the region, thereby supporting the development of new agricultural practices that utilize local resources.

[0220] The following describes the processing flow.

[0221] Step 1:

[0222] The device acquires voice input from the elderly person. At this time, the voice input function is activated and configured to collect information from the spoken words. The collected voice data is converted into text format in real time by a speech recognition module.

[0223] Step 2:

[0224] The terminal sends the converted text data to the server. This transmission is secure, with the data encrypted for security purposes, and uses a reliable communication protocol.

[0225] Step 3:

[0226] The server analyzes the received text data. It utilizes natural language processing algorithms to extract keywords from the text and classify the content into specific categories. For example, it organizes data according to themes such as "agricultural technology" or "lifestyle and culture."

[0227] Step 4:

[0228] The server stores the classified data in a digital database. This storage process involves tagging the data, adding metadata, and generating indexes to improve search efficiency.

[0229] Step 5:

[0230] Users can access the database and search for topics that interest them. Through the user interface, they can easily enter keywords into the search field and quickly retrieve relevant information.

[0231] Step 6:

[0232] The server extracts relevant information from the database in response to a user's search request and displays it in the user interface. It provides a detailed view of the information the user is looking for, offering knowledge in a visually organized manner.

[0233] Step 7:

[0234] The server also integrates information about the region's unique culture and history, and notifies users of local community events. This allows users to learn about local cultural assets and deepen their experience through actual interaction.

[0235] (Example 1)

[0236] 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."

[0237] In an aging society, there is a need to efficiently collect the valuable knowledge and experience of the elderly and pass it on to younger generations and local communities. However, systems for systematically organizing and preserving information about the elderly and providing it to users who need it in a visually and easily understandable way are currently not adequately developed. Furthermore, mechanisms for promoting intergenerational knowledge exchange by utilizing unique local cultures and histories are also insufficient.

[0238] 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.

[0239] In this invention, the server includes means for using a device to acquire knowledge from elderly people as voice or text data and converting it into digital signals, means for converting the acquired voice data into text data, and means for analyzing the text data using natural language processing technology to extract keywords and classify them by theme. This enables the efficient transmission of knowledge to younger generations and the preservation of regional cultural values ​​by digitizing and systematically storing the knowledge of elderly people.

[0240] The term "elderly" refers to people who are considered older in society and are mature individuals with a wealth of experience and knowledge.

[0241] "Audio data" refers to a collection of information in which human voices are recorded in digital format.

[0242] "Text data" refers to a collection of information recorded in digital format using character data.

[0243] A "digital signal" is a signal format suitable for communication and processing using digital data.

[0244] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0245] A "keyword" is a word or phrase that has important meaning within a text or data.

[0246] A "theme" is the main topic or category used when organizing and analyzing information.

[0247] A "digital storage device" is a device or system for storing information in digital format.

[0248] A "visual and interactive format" refers to a method of presentation in which information is presented to the user in a way that is easy to see and allows for interaction.

[0249] "Regional cultural characteristics" refer to unique customs and values ​​found only in a particular region.

[0250] "Historical background" refers to past events and circumstances that constitute the process by which things are formed.

[0251] A "user interface" is a concept that refers to the screens and means of operation that users use to interact with a system.

[0252] "Activity information" refers to detailed information about a specific event or activity.

[0253] This invention is a system for digitizing the knowledge of the elderly and transmitting it to the next generation by linking an information acquisition device and a server.

[0254] First, the terminal functions as a device for acquiring voice or text data from elderly individuals. Voice data is captured in real time using a highly sensitive microphone and acoustic signal processing software (e.g., a common speech recognition API). The voice data is converted into a digital signal, and then into text data. This textual information forms the basis for subsequent analysis.

[0255] After receiving this text data, the server analyzes it using natural language processing techniques (e.g., a common natural language processing library). The server extracts keywords from the text and classifies them based on specific themes. The classified data is stored in a digital storage device for efficient retrieval and use later.

[0256] Furthermore, the server provides a user interface for users to view information. This interface enables visual display and interactive manipulation of data, and is designed to make knowledge more easily understood by older adults. This creates an environment where information is readily available.

[0257] For example, if an elderly person shares information such as, "In the past, a specific farming method was used in agriculture in this region," that information could be stored in a digital memory device under the theme of "agricultural technology." Then, a system would be provided that allows young people or researchers to easily access this information when they search for information such as "the history of agricultural technology."

[0258] An example of a prompt would be, "Please tell me about the agricultural techniques that have been practiced in this region for a long time, including specific methods and their background." This makes it possible to provide a system that allows users to easily obtain a wealth of information about region-specific knowledge and history.

[0259] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0260] Step 1:

[0261] The device acquires voices from elderly individuals. Using a high-sensitivity microphone, it converts the voice signal into digital data in real time. The input is the elderly person's voice, and the output is the digitized voice signal. Specifically, when an elderly person speaks about old farming methods, the device records their words in digital format.

[0262] Step 2:

[0263] The terminal converts acquired digital audio signals into text data. Using speech recognition technology, it analyzes the audio signal and generates text data. The input to this process is a digital audio signal, and the output is text. Specifically, the audio data is converted into text about a particular technique, such as agricultural technology.

[0264] Step 3:

[0265] The server receives text data from the terminal. The server prepares to receive and store the data. The input is the text data sent from the terminal, and the output is the storage of the data within the server. Specifically, the data converted into text on the terminal is sent to the server.

[0266] Step 4:

[0267] The server analyzes the received text data using natural language processing techniques. It tokenizes the data and extracts keywords. In this process, the input is the received text data, and the output is a keyword list. Specifically, the keyword "agricultural technology" is identified and extracted.

[0268] Step 5:

[0269] The server classifies the text data based on the extracted keywords. It classifies the data by theme and stores it in a digital storage device. The input to this process is a keyword list and text data, and the output is a structured data set. Specifically, the data is stored in the "Agricultural Technology" section of the database.

[0270] Step 6:

[0271] The server provides a user interface that allows users to search and view information. It searches the database and displays relevant information visually. The input to this process is the user's search query, and the output is the visualized search results. For example, if a user enters the query "history of agricultural technology," the relevant information will be displayed in an easy-to-read format.

[0272] (Application Example 1)

[0273] 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 glasses 214 will be referred to as the "terminal."

[0274] There is a need to effectively collect the knowledge and experience of the elderly and preserve it in a form that can be used in caregiving and education settings. In particular, there is a lack of interfaces to not only preserve the knowledge of the elderly as digital data, but also to easily share it among different generations and maximize its value. Against this backdrop, the challenge is to provide a system that effectively utilizes the knowledge of the elderly while promoting intergenerational exchange.

[0275] 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.

[0276] In this invention, the server includes means for acquiring knowledge from elderly people as voice or text data using speech recognition technology, means for classifying the acquired data into general themes using a natural language processing algorithm, and means for storing the classified data in a digital information storage medium and providing it to users as needed. This enables the effective sharing of elderly people's knowledge among caregivers and the revitalization of intergenerational exchange based on that knowledge.

[0277] "Speech recognition technology" is a technology that converts speech data into text data, making it possible to treat speech information obtained from elderly people as text information.

[0278] A "natural language processing algorithm" is a technology that analyzes the meaning and relationships of acquired text data and classifies it into specific themes or categories.

[0279] A "digital information storage medium" refers to a medium that can store data electronically and is used to preserve and manage the knowledge of elderly people over long periods of time.

[0280] "Users" refer to those who access and utilize the knowledge and experience of the elderly through this system.

[0281] An "interface" is the part of a system that provides a user interface and user experience for users to interact with the system.

[0282] A "caregiver" is someone who specializes in caring for the elderly, and who plays a role in using this system to collect knowledge about the elderly and utilize it in caregiving.

[0283] To realize this application, a system is needed that integrates speech recognition technology, natural language processing algorithms, digital information storage media, and a user interface.

[0284] The server uses the Google Cloud Speech-to-Text API to convert the voice data obtained from the elderly into text data. The texturized data is analyzed by applying natural language processing algorithms and classified into general themes. The classified data is stored in a digital information storage medium such as Google Firebase and becomes accessible to users.

[0285] The terminal takes the form of a smartphone or tablet and provides a smooth operation for caregivers to collect knowledge while directly interacting with the elderly through an interface. This enables caregivers to efficiently record the knowledge of the elderly and share it with other users.

[0286] For example, when an elderly person talks about their unique gardening techniques, the voice is immediately texturized, classified based on similar themes, and then stored so that it can be accessed by other care facilities as well. This makes cross-regional knowledge sharing a reality.

[0287] Examples of prompt texts for the generative AI model include "Please convert the following voice data into text, extract keywords, and save them. The topic is related to the gardening techniques of the elderly."

[0288] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0289] Step 1:

[0290] The terminal collects voice data through interaction with the elderly. This voice data is input using the microphone of a smartphone or tablet. The voice data is sent to the server as a stream.

[0291] Step 2:

[0292] The server sends the received audio data to the Google Cloud Speech-to-Text API, where it is converted into text data. The input is audio data, and the output is the corresponding text data. The server then passes the converted text data to the next processing step.

[0293] Step 3:

[0294] The server feeds the received text data into a natural language processing (NLP) algorithm to perform keyword extraction and theme classification. This process takes text data as input and generates keywords and theme classifications as output. Specifically, it uses TF-IDF and topic modeling techniques.

[0295] Step 4:

[0296] The server stores the categorized data in Google Firebase. This step takes categorized text data as input and outputs it by saving it to the database. Firebase has the advantage of being able to store and retrieve data quickly.

[0297] Step 5:

[0298] The user accesses stored data and searches for necessary information using a user interface. This step takes the user's search query as input and returns relevant categorized data as output. Specific actions include implementing a search function within the UI.

[0299] 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.

[0300] The system of this invention collects the knowledge and experience of elderly people and passes it on to the next generation, while also recognizing the emotional state of users and using this information for interaction and information provision. First, the terminal acquires voice or text data from the elderly person. This data is converted into text using speech recognition technology and sent to the server. The server uses a natural language processing algorithm to analyze the acquired data and classify it by theme. The classified data is stored in a database and provided to the user as needed.

[0301] Furthermore, this system incorporates an emotion engine that analyzes user input and responses in real time and has the capability to recognize emotions. Emotion recognition includes facial expression analysis and voice tone analysis, analyzing various data points to identify emotional states. For example, if the system detects "interest" from a user's facial expression while they are viewing information, it can immediately suggest additional information or related events that correspond to that emotion.

[0302] Based on recognized emotions, the server appropriately modifies the interface and provides content that will pique the user's interest. For example, if the emotion engine detects a positive reaction when a user is browsing information about local folklore, information about relevant events taking place in that region will be displayed on the screen. Through this process, users can obtain a more interesting and personalized experience.

[0303] This system configuration facilitates user interaction through emotion recognition, thereby improving the quality of communication. Furthermore, it can effectively support the deepening of intergenerational exchange and the transmission of local culture.

[0304] The following describes the processing flow.

[0305] Step 1:

[0306] The terminal acquires voice or text data from the elderly. In the case of voice input, it is converted into text in real time using a voice recognition function. The converted text data is encrypted and prepared for transmission to the server.

[0307] Step 2:

[0308] The server receives the text data transmitted from the terminal. The received data is analyzed by applying a natural language processing algorithm to extract important keywords and topics. Thereby, the data is classified into specific themes.

[0309] Step 3:

[0310] The server stores the classified text data in a digital database. When storing, tags are assigned to generate metadata and an index is created to facilitate later searches.

[0311] Step 4:

[0312] The emotion engine recognizes the user's emotional state through the user interface. Using sensor data and microphone input, it analyzes facial expressions and voice tones to identify emotions.

[0313] Step 5:

[0314] The server dynamically adapts the interface based on the recognized user emotions. For example, when the user shows "surprise" or "interest", relevant visual effects and additional information are displayed on the interface.

[0315] Step 6:

[0316] The user can view the information provided from the emotion feedback and act based on the system's suggestions. For example, information promoting participation in specific cultural events is displayed and the method of participation can be executed from the screen.

[0317] Step 7:

[0318] The server records user actions and accumulates data on usage patterns and emotional responses. This creates a feedback loop to improve the accuracy of future suggestions and make the user experience more personalized.

[0319] (Example 2)

[0320] 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".

[0321] In an aging society, passing on knowledge and culture to the next generation is a crucial challenge. However, there is a lack of effective means to collect, structure, and transmit the abundant knowledge and experience of the elderly to the next generation. Furthermore, there is a need to improve user interest and understanding by providing information that takes into account the emotional state of individuals. To address these challenges, there is a need for systems that promote intergenerational exchange and realize the transmission and utilization of information.

[0322] 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.

[0323] In this invention, the server includes means for acquiring information as voice or text data from the person providing the information, means for analyzing the acquired data using an information processing algorithm and classifying it into categories, means for storing the classified data on a recording medium and providing it to the user as needed, means for sensing the user's emotional state, and means for adjusting and providing the presented information based on the sensed emotions. This makes it possible not only to effectively collect and structure the knowledge and experience of the elderly, but also to provide users with customized information that matches their emotions. This realizes the transmission of culture and the promotion of intergenerational exchange.

[0324] "Target recipients of information" refers to individuals or groups that are the primary source of data collection, and primarily includes elderly people.

[0325] "Audio or text data" refers to a form of information transmitted through language, including audio recordings and text-typed information.

[0326] An "information processing algorithm" refers to a computational method for analyzing, structuring, and classifying received data, and includes natural language processing techniques.

[0327] "Classifying by category" refers to the act of grouping data according to its content or theme, which makes it easier to search for and use information.

[0328] "Recording medium" refers to a technical means for storing digital data, and includes databases and cloud storage.

[0329] "Users" refers to individuals or groups who are able to receive and use information from the system, and includes those who play a role in intergenerational exchange.

[0330] "Emotional state sensing" refers to the technological process of detecting and analyzing an individual's emotional responses, and includes facial recognition and voice analysis.

[0331] "Adjusting and providing information" refers to the act of optimizing the selection and display of information according to the user's emotions and circumstances, thereby achieving personalized information delivery.

[0332] The system of the present invention effectively collects the knowledge and experience of the elderly and passes it on to the next generation, while also recognizing the emotional state of the user and utilizing this information for interaction and information provision. Specific embodiments for carrying out the invention are shown below.

[0333] The terminal is responsible for collecting data from information providers through voice or text input. Voice data is converted into text data using speech recognition technology. Specifically, a common speech recognition API is used to convert speech to text, and the result is sent to the server. In this process, for example, a general-purpose voice input device or keyboard is used.

[0334] The server analyzes the received text data using natural language processing algorithms. Here, general-purpose natural language processing software is used to classify the data into specific themes and categories. This classified data is stored on a storage medium called a database and provided to the user as needed. Furthermore, to analyze the user's emotional state, the server uses image processing and speech analysis technologies to recognize emotions in real time. This process utilizes common facial expression analysis software and speech tone analysis tools.

[0335] Users can enjoy a personalized experience based on the information they receive through the system. By recognizing the user's emotional state, the server can appropriately present information that matches that emotion. For example, if a user expresses positive emotions while viewing information including local folklore, information about related events will be provided. In this way, users can obtain customized information based on their interests and preferences.

[0336] Examples of prompts include, "How can we collect testimonials from elderly people and pass on that knowledge to the next generation?" and "How can we improve the user experience through emotion recognition?" Such prompts can be used to effectively utilize the system's functions.

[0337] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0338] Step 1:

[0339] The terminal obtains information from the information provider as voice or text data. In the case of voice data, the terminal collects the voice using a voice input device. The input voice data is converted into text data by speech recognition software, and this text is sent to the server. In the case of text data, it is entered directly via a keyboard or similar device and sent to the server.

[0340] Step 2:

[0341] The server analyzes the received text data using natural language processing algorithms. At this stage, the server classifies the data into different categories. Using a generative AI model, it identifies the theme of each data point from the input text data and obtains classification information as output. This output is stored in the database as text data with category labels. Specifically, categories such as "culture" and "history" are used.

[0342] Step 3:

[0343] The server stores the classified data on a storage medium called a database. In this step, the organized data is stored in a format that can be easily searched and accessed later. By using database software to tag related information, subsequent query processing becomes more efficient. The information stored in the database can be retrieved when requested by the user.

[0344] Step 4:

[0345] When a user accesses the system, the server senses the user's emotional state before providing information to the interface. The user's facial expressions and voice tone become input data, which are then analyzed by an emotion recognition engine. Based on the detected emotional information, the information provided to the user is customized. This process involves image processing and voice analysis tools.

[0346] Step 5:

[0347] The server presents the user with information tailored to their emotional state. Relevant information is selected from the user's emotional data and stored data, and output to the user in visual and auditory ways. For example, if a user indicates "interest," relevant local event information is displayed, enriching the user's experience. This allows the user to access personalized information.

[0348] (Application Example 2)

[0349] 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."

[0350] In modern society, the wealth of knowledge and experience possessed by the elderly is not being adequately passed on to the next generation, and there is a particular risk of losing information about unique local cultures and histories. Furthermore, there is a lack of smooth communication between the elderly and younger generations, highlighting the need to promote intergenerational exchange. Additionally, a challenge remains: there is no system in place to appropriately recognize the emotional state of the elderly and provide them with appropriate information accordingly.

[0351] 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.

[0352] In this invention, the server includes means for acquiring knowledge from elderly people as voice or text data; means for analyzing the acquired data using a natural language processing algorithm and classifying it by theme; means for storing the classified data in an information storage means and providing it to the user as needed; means for analyzing the user's facial expressions and tone of voice to identify their emotional state; means for presenting relevant information and event information to the user based on the identified emotions; and a software program for operating the means on a smart device. This enables the effective transfer of elderly people's knowledge and experience to the next generation, facilitates interaction with elderly people, and allows for the provision of personalized information according to the user's emotional state.

[0353] "Elderly people" are individuals above a certain age who possess abundant knowledge and experience and are expected to pass it on to the next generation.

[0354] "Voice or text data" refers to information obtained from elderly individuals, and is data expressed in either voice input or text input format.

[0355] A "natural language processing algorithm" is a set of computational procedures for analyzing acquired audio or text data and classifying and organizing it in a way that humans can understand.

[0356] "Classifying by theme" means organizing acquired data based on specific topics or areas and consolidating it into a database.

[0357] "Information storage means" refers to a digital storage device for storing analyzed and classified data.

[0358] A "user" is an individual or organization that uses the system to receive information or services.

[0359] "Analyzing facial expressions and tone of voice" means using facial recognition technology and voice analysis technology to evaluate changes in these in order to identify the user's emotional state.

[0360] "Presenting relevant information and event information" means displaying appropriate supplementary information or information about events that interest the user, tailored to their emotional state, on the device screen.

[0361] A "smart device" is a portable electronic device capable of performing calculations, and examples include mobile phones and tablet devices.

[0362] A "software program" is a set of instructions or code that constitutes a system and performs a specific function.

[0363] The system for implementing this invention aims to acquire knowledge from the elderly and provide users with information that is more emotionally responsive. The system's program is structured as follows:

[0364] The device acquires voice or text data from the elderly person. The voice data is converted into text data using speech recognition technology. Specifically, speech recognition software such as the Google Cloud Speech-to-Text API is used. The converted text data is sent to the server.

[0365] The server analyzes this text data using natural language processing algorithms. For example, by using a natural language processing library such as spaCy, the data is classified into specific themes. The classified data is then stored in an information storage system. When a user needs the data, they can access the database and retrieve the information.

[0366] Furthermore, the terminal and server analyze the user's facial expressions and tone of voice to identify their emotional state. By utilizing the Microsoft Azure Face API and Emotion API, it is possible to analyze the user's emotions in real time. Based on the analyzed emotions, relevant information and event information are displayed on the terminal screen.

[0367] For example, if an elderly person is sharing a local folktale and a user who is interested in the story smiles, the system can then provide information about events related to that area or additional reading material. This deepens communication and promotes intergenerational exchange.

[0368] This system can be used to provide an even higher level of user experience. An example of a prompt when using a generative AI model is: "Design an application that converts the voices of elderly people from audio to text, analyzes the content, and categorizes it. It also detects changes in emotion using a camera and microphone and suggests additional content to engage that person."

[0369] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0370] Step 1:

[0371] The device acquires voice or text data from the elderly person. The input is voice or text data from the elderly person; if it's voice data, it's converted to text data using the Google Cloud Speech-to-Text API. The output is the text data sent to the server.

[0372] Step 2:

[0373] The server analyzes received text data using natural language processing algorithms. The input is transformed text data, utilizing libraries such as spaCy. The data is categorized by theme based on its content. The output is the categorized text data.

[0374] Step 3:

[0375] The server stores the classified data in an information storage system. The input is text data classified by theme, and this data is stored in a database. The output is the data stored in the database.

[0376] Step 4:

[0377] The device analyzes the user's facial expressions and tone of voice to identify their emotional state. Input consists of the user's facial expression and voice data, which are processed using the Microsoft Azure Face API and Emotion API. The output is the identified emotional state.

[0378] Step 5:

[0379] The server displays relevant and event information on the device screen based on the identified emotions. The input consists of emotional states and related data, and the content is selected to match the user's interests. The output is the final content displayed on the device screen.

[0380] 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.

[0381] 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.

[0382] 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.

[0383] [Third Embodiment]

[0384] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0385] 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.

[0386] 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).

[0387] 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.

[0388] 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.

[0389] 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).

[0390] 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.

[0391] 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.

[0392] 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.

[0393] 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.

[0394] 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.

[0395] 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".

[0396] The system of this invention is designed to effectively collect, classify, and store knowledge and experience from the elderly and provide it to future generations. First, the terminal functions as an interface for the elderly, acquiring information through voice or text input. In this case, voice input is converted into text data using speech recognition technology. For example, if an elderly person tells a story about how a special farming method was used in this area in the past, this is recorded as text data.

[0397] Next, the server analyzes the received text data. Using natural language processing algorithms, it extracts keywords and relationships within the text and classifies them under themes such as "agricultural technology." The classified data is stored in a digital database, enabling information structuring and efficient searching.

[0398] Furthermore, the server has an interface that provides structured data to users. It is designed so that young people and educators can search and view information from the database, and if a user seeks information on, for example, the "history of agricultural technology," that organized knowledge will be immediately available for reference. The system presents information in a visually easy-to-understand layout and provides valuable information to users through interactive elements.

[0399] Furthermore, the server provides additional information related to local culture and history, building a foundation for understanding and utilizing unique local cultural customs. This also promotes intergenerational exchange within the community when used in local events.

[0400] Thus, the system of the present invention provides an effective means of digitally preserving the valuable knowledge possessed by the elderly and passing it on to future generations. As a specific example, it can be used to collect agricultural know-how from elderly people in rural areas and make it accessible to young people in the region, thereby supporting the development of new agricultural practices that utilize local resources.

[0401] The following describes the processing flow.

[0402] Step 1:

[0403] The device acquires voice input from the elderly person. At this time, the voice input function is activated and configured to collect information from the spoken words. The collected voice data is converted into text format in real time by a speech recognition module.

[0404] Step 2:

[0405] The terminal sends the converted text data to the server. This transmission is secure, with the data encrypted for security purposes, and uses a reliable communication protocol.

[0406] Step 3:

[0407] The server analyzes the received text data. It utilizes natural language processing algorithms to extract keywords from the text and classify the content into specific categories. For example, it organizes data according to themes such as "agricultural technology" or "lifestyle and culture."

[0408] Step 4:

[0409] The server stores the classified data in a digital database. This storage process involves tagging the data, adding metadata, and generating indexes to improve search efficiency.

[0410] Step 5:

[0411] Users can access the database and search for topics that interest them. Through the user interface, they can easily enter keywords into the search field and quickly retrieve relevant information.

[0412] Step 6:

[0413] The server extracts relevant information from the database in response to a user's search request and displays it in the user interface. It provides a detailed view of the information the user is looking for, offering knowledge in a visually organized manner.

[0414] Step 7:

[0415] The server also integrates information about the region's unique culture and history, and notifies users of local community events. This allows users to learn about local cultural assets and deepen their experience through actual interaction.

[0416] (Example 1)

[0417] 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."

[0418] In an aging society, there is a need to efficiently collect the valuable knowledge and experience of the elderly and pass it on to younger generations and local communities. However, systems for systematically organizing and preserving information about the elderly and providing it to users who need it in a visually and easily understandable way are currently not adequately developed. Furthermore, mechanisms for promoting intergenerational knowledge exchange by utilizing unique local cultures and histories are also insufficient.

[0419] 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.

[0420] In this invention, the server includes means for using a device to acquire knowledge from elderly people as voice or text data and converting it into digital signals, means for converting the acquired voice data into text data, and means for analyzing the text data using natural language processing technology to extract keywords and classify them by theme. This enables the efficient transmission of knowledge to younger generations and the preservation of regional cultural values ​​by digitizing and systematically storing the knowledge of elderly people.

[0421] The term "elderly" refers to people who are considered older in society and are mature individuals with a wealth of experience and knowledge.

[0422] "Audio data" refers to a collection of information in which human voices are recorded in digital format.

[0423] "Text data" refers to a collection of information recorded in digital format using character data.

[0424] A "digital signal" is a signal format suitable for communication and processing using digital data.

[0425] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0426] A "keyword" is a word or phrase that has important meaning within a text or data.

[0427] A "theme" is the main topic or category used when organizing and analyzing information.

[0428] A "digital storage device" is a device or system for storing information in digital format.

[0429] A "visual and interactive format" refers to a method of presentation in which information is presented to the user in a way that is easy to see and allows for interaction.

[0430] "Regional cultural characteristics" refer to unique customs and values ​​found only in a particular region.

[0431] "Historical background" refers to past events and circumstances that constitute the process by which things are formed.

[0432] A "user interface" is a concept that refers to the screens and means of operation that users use to interact with a system.

[0433] "Activity information" refers to detailed information about a specific event or activity.

[0434] This invention is a system for digitizing the knowledge of the elderly and transmitting it to the next generation by linking an information acquisition device and a server.

[0435] First, the terminal functions as a device for acquiring voice or text data from elderly individuals. Voice data is captured in real time using a highly sensitive microphone and acoustic signal processing software (e.g., a common speech recognition API). The voice data is converted into a digital signal, and then into text data. This textual information forms the basis for subsequent analysis.

[0436] After receiving this text data, the server analyzes it using natural language processing techniques (e.g., a common natural language processing library). The server extracts keywords from the text and classifies them based on specific themes. The classified data is stored in a digital storage device for efficient retrieval and use later.

[0437] Furthermore, the server provides a user interface for users to view information. This interface enables visual display and interactive manipulation of data, and is designed to make knowledge more easily understood by older adults. This creates an environment where information is readily available.

[0438] For example, if an elderly person shares information such as, "In the past, a specific farming method was used in agriculture in this region," that information could be stored in a digital memory device under the theme of "agricultural technology." Then, a system would be provided that allows young people or researchers to easily access this information when they search for information such as "the history of agricultural technology."

[0439] An example of a prompt would be, "Please tell me about the agricultural techniques that have been practiced in this region for a long time, including specific methods and their background." This makes it possible to provide a system that allows users to easily obtain a wealth of information about region-specific knowledge and history.

[0440] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0441] Step 1:

[0442] The device acquires voices from elderly individuals. Using a high-sensitivity microphone, it converts the voice signal into digital data in real time. The input is the elderly person's voice, and the output is the digitized voice signal. Specifically, when an elderly person speaks about old farming methods, the device records their words in digital format.

[0443] Step 2:

[0444] The terminal converts acquired digital audio signals into text data. Using speech recognition technology, it analyzes the audio signal and generates text data. The input to this process is a digital audio signal, and the output is text. Specifically, the audio data is converted into text about a particular technique, such as agricultural technology.

[0445] Step 3:

[0446] The server receives text data from the terminal. The server prepares to receive and store the data. The input is the text data sent from the terminal, and the output is the storage of the data within the server. Specifically, the data converted into text on the terminal is sent to the server.

[0447] Step 4:

[0448] The server analyzes the received text data using natural language processing techniques. It tokenizes the data and extracts keywords. In this process, the input is the received text data, and the output is a keyword list. Specifically, the keyword "agricultural technology" is identified and extracted.

[0449] Step 5:

[0450] The server classifies the text data based on the extracted keywords. It classifies the data by theme and stores it in a digital storage device. The input to this process is a keyword list and text data, and the output is a structured data set. Specifically, the data is stored in the "Agricultural Technology" section of the database.

[0451] Step 6:

[0452] The server provides a user interface that allows users to search and view information. It searches the database and displays relevant information visually. The input to this process is the user's search query, and the output is the visualized search results. For example, if a user enters the query "history of agricultural technology," the relevant information will be displayed in an easy-to-read format.

[0453] (Application Example 1)

[0454] 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."

[0455] There is a need to effectively collect the knowledge and experience of the elderly and preserve it in a form that can be used in caregiving and education settings. In particular, there is a lack of interfaces to not only preserve the knowledge of the elderly as digital data, but also to easily share it among different generations and maximize its value. Against this backdrop, the challenge is to provide a system that effectively utilizes the knowledge of the elderly while promoting intergenerational exchange.

[0456] 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.

[0457] In this invention, the server includes means for acquiring knowledge from elderly people as voice or text data using speech recognition technology, means for classifying the acquired data into general themes using a natural language processing algorithm, and means for storing the classified data in a digital information storage medium and providing it to users as needed. This enables the effective sharing of elderly people's knowledge among caregivers and the revitalization of intergenerational exchange based on that knowledge.

[0458] "Speech recognition technology" is a technology that converts speech data into text data, making it possible to treat speech information obtained from elderly people as text information.

[0459] A "natural language processing algorithm" is a technology that analyzes the meaning and relationships of acquired text data and classifies it into specific themes or categories.

[0460] A "digital information storage medium" refers to a medium that can store data electronically and is used to preserve and manage the knowledge of elderly people over long periods of time.

[0461] "Users" refer to those who access and utilize the knowledge and experience of the elderly through this system.

[0462] An "interface" is the part of a system that provides a user interface and user experience for users to interact with the system.

[0463] A "caregiver" is someone who specializes in caring for the elderly, and who plays a role in using this system to collect knowledge about the elderly and utilize it in caregiving.

[0464] To realize this application, a system is needed that integrates speech recognition technology, natural language processing algorithms, digital information storage media, and a user interface.

[0465] The server uses the Google Cloud Speech-to-Text API to convert speech data obtained from elderly individuals into text data. The transcribed data is then analyzed using natural language processing algorithms and categorized into general themes. The categorized data is stored on digital storage media such as Google Firebase and made accessible to users.

[0466] The device takes the form of a smartphone or tablet and provides a smooth interface for caregivers to collect knowledge while directly interacting with the elderly. This allows caregivers to efficiently record the elderly's knowledge and share it with other users.

[0467] For example, when an elderly person talks about their unique gardening techniques, their voice is instantly transcribed into text, categorized based on similar themes, and then saved so that it can be accessed by other care facilities. This makes knowledge sharing across regions a reality.

[0468] An example of a prompt for a generative AI model is: "Convert the following audio data to text, extract the keywords, and save them. The topic is gardening techniques for seniors."

[0469] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0470] Step 1:

[0471] The device collects voice data through conversations with elderly individuals. This voice data is input using the microphone of a smartphone or tablet. The voice data is then transmitted to a server as a stream.

[0472] Step 2:

[0473] The server sends the received audio data to the Google Cloud Speech-to-Text API, where it is converted into text data. The input is audio data, and the output is the corresponding text data. The server then passes the converted text data to the next processing step.

[0474] Step 3:

[0475] The server feeds the received text data into a natural language processing (NLP) algorithm to perform keyword extraction and theme classification. This process takes text data as input and generates keywords and theme classifications as output. Specifically, it uses TF-IDF and topic modeling techniques.

[0476] Step 4:

[0477] The server stores the categorized data in Google Firebase. This step takes categorized text data as input and outputs it by saving it to the database. Firebase has the advantage of being able to store and retrieve data quickly.

[0478] Step 5:

[0479] The user accesses stored data and searches for necessary information using a user interface. This step takes the user's search query as input and returns relevant categorized data as output. Specific actions include implementing a search function within the UI.

[0480] 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.

[0481] The system of this invention collects the knowledge and experience of elderly people and passes it on to the next generation, while also recognizing the emotional state of users and using this information for interaction and information provision. First, the terminal acquires voice or text data from the elderly person. This data is converted into text using speech recognition technology and sent to the server. The server uses a natural language processing algorithm to analyze the acquired data and classify it by theme. The classified data is stored in a database and provided to the user as needed.

[0482] Furthermore, this system incorporates an emotion engine that analyzes user input and responses in real time and has the capability to recognize emotions. Emotion recognition includes facial expression analysis and voice tone analysis, analyzing various data points to identify emotional states. For example, if the system detects "interest" from a user's facial expression while they are viewing information, it can immediately suggest additional information or related events that correspond to that emotion.

[0483] Based on recognized emotions, the server appropriately modifies the interface and provides content that will pique the user's interest. For example, if the emotion engine detects a positive reaction when a user is browsing information about local folklore, information about relevant events taking place in that region will be displayed on the screen. Through this process, users can obtain a more interesting and personalized experience.

[0484] This system configuration facilitates user interaction through emotion recognition, thereby improving the quality of communication. Furthermore, it can effectively support the deepening of intergenerational exchange and the transmission of local culture.

[0485] The following describes the processing flow.

[0486] Step 1:

[0487] The device acquires voice or text data from the elderly person. In the case of voice input, it converts it to text in real time using speech recognition. The converted text data is encrypted and prepared for transmission to the server.

[0488] Step 2:

[0489] The server receives text data sent from the terminal. The received data is analyzed using natural language processing algorithms to extract important keywords and topics. This allows the data to be categorized into specific themes.

[0490] Step 3:

[0491] The server stores the classified text data in a digital database. During storage, tags are added to generate metadata and create an index to facilitate future searching.

[0492] Step 4:

[0493] The emotion engine recognizes the user's emotional state through the user interface. It uses sensor data and microphone input to analyze facial expressions and voice tone to identify emotions.

[0494] Step 5:

[0495] The server dynamically adapts the interface based on the recognized user's emotions. For example, if the user expresses "surprise" or "interest," it displays relevant visual effects and additional information on the interface.

[0496] Step 6:

[0497] Users can view information provided through emotional feedback and act based on the system's suggestions. For example, information encouraging participation in a specific cultural event may be displayed, and users can then take steps to participate directly from the screen.

[0498] Step 7:

[0499] The server records user actions and accumulates data on usage patterns and emotional responses. This creates a feedback loop to improve the accuracy of future suggestions and make the user experience more personalized.

[0500] (Example 2)

[0501] 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."

[0502] In an aging society, passing on knowledge and culture to the next generation is a crucial challenge. However, there is a lack of effective means to collect, structure, and transmit the abundant knowledge and experience of the elderly to the next generation. Furthermore, there is a need to improve user interest and understanding by providing information that takes into account the emotional state of individuals. To address these challenges, there is a need for systems that promote intergenerational exchange and realize the transmission and utilization of information.

[0503] 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.

[0504] In this invention, the server includes means for acquiring information as voice or text data from the person providing the information, means for analyzing the acquired data using an information processing algorithm and classifying it into categories, means for storing the classified data on a recording medium and providing it to the user as needed, means for sensing the user's emotional state, and means for adjusting and providing the presented information based on the sensed emotions. This makes it possible not only to effectively collect and structure the knowledge and experience of the elderly, but also to provide users with customized information that matches their emotions. This realizes the transmission of culture and the promotion of intergenerational exchange.

[0505] "Target recipients of information" refers to individuals or groups that are the primary source of data collection, and primarily includes elderly people.

[0506] "Audio or text data" refers to a form of information transmitted through language, including audio recordings and text-typed information.

[0507] An "information processing algorithm" refers to a computational method for analyzing, structuring, and classifying received data, and includes natural language processing techniques.

[0508] "Classifying by category" refers to the act of grouping data according to its content or theme, which makes it easier to search for and use information.

[0509] "Recording medium" refers to a technical means for storing digital data, and includes databases and cloud storage.

[0510] "Users" refers to individuals or groups who are able to receive and use information from the system, and includes those who play a role in intergenerational exchange.

[0511] "Emotional state sensing" refers to the technological process of detecting and analyzing an individual's emotional responses, and includes facial recognition and voice analysis.

[0512] "Adjusting and providing information" refers to the act of optimizing the selection and display of information according to the user's emotions and circumstances, thereby achieving personalized information delivery.

[0513] The system of the present invention effectively collects the knowledge and experience of the elderly and passes it on to the next generation, while also recognizing the emotional state of the user and utilizing this information for interaction and information provision. Specific embodiments for carrying out the invention are shown below.

[0514] The terminal is responsible for collecting data from information providers through voice or text input. Voice data is converted into text data using speech recognition technology. Specifically, a common speech recognition API is used to convert speech to text, and the result is sent to the server. In this process, for example, a general-purpose voice input device or keyboard is used.

[0515] The server analyzes the received text data using natural language processing algorithms. Here, general-purpose natural language processing software is used to classify the data into specific themes and categories. This classified data is stored on a storage medium called a database and provided to the user as needed. Furthermore, to analyze the user's emotional state, the server uses image processing and speech analysis technologies to recognize emotions in real time. This process utilizes common facial expression analysis software and speech tone analysis tools.

[0516] Users can enjoy a personalized experience based on the information they receive through the system. By recognizing the user's emotional state, the server can appropriately present information that matches that emotion. For example, if a user expresses positive emotions while viewing information including local folklore, information about related events will be provided. In this way, users can obtain customized information based on their interests and preferences.

[0517] Examples of prompts include, "How can we collect testimonials from elderly people and pass on that knowledge to the next generation?" and "How can we improve the user experience through emotion recognition?" Such prompts can be used to effectively utilize the system's functions.

[0518] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0519] Step 1:

[0520] The terminal obtains information from the information provider as voice or text data. In the case of voice data, the terminal collects the voice using a voice input device. The input voice data is converted into text data by speech recognition software, and this text is sent to the server. In the case of text data, it is entered directly via a keyboard or similar device and sent to the server.

[0521] Step 2:

[0522] The server analyzes the received text data using natural language processing algorithms. At this stage, the server classifies the data into different categories. Using a generative AI model, it identifies the theme of each data point from the input text data and obtains classification information as output. This output is stored in the database as text data with category labels. Specifically, categories such as "culture" and "history" are used.

[0523] Step 3:

[0524] The server stores the classified data on a storage medium called a database. In this step, the organized data is stored in a format that can be easily searched and accessed later. By using database software to tag related information, subsequent query processing becomes more efficient. The information stored in the database can be retrieved when requested by the user.

[0525] Step 4:

[0526] When a user accesses the system, the server senses the user's emotional state before providing information to the interface. The user's facial expressions and voice tone become input data, which are then analyzed by an emotion recognition engine. Based on the detected emotional information, the information provided to the user is customized. This process involves image processing and voice analysis tools.

[0527] Step 5:

[0528] The server presents the user with information tailored to their emotional state. Relevant information is selected from the user's emotional data and stored data, and output to the user in visual and auditory ways. For example, if a user indicates "interest," relevant local event information is displayed, enriching the user's experience. This allows the user to access personalized information.

[0529] (Application Example 2)

[0530] 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."

[0531] In modern society, the wealth of knowledge and experience possessed by the elderly is not being adequately passed on to the next generation, and there is a particular risk of losing information about unique local cultures and histories. Furthermore, there is a lack of smooth communication between the elderly and younger generations, highlighting the need to promote intergenerational exchange. Additionally, a challenge remains: there is no system in place to appropriately recognize the emotional state of the elderly and provide them with appropriate information accordingly.

[0532] 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.

[0533] In this invention, the server includes means for acquiring knowledge from elderly people as voice or text data; means for analyzing the acquired data using a natural language processing algorithm and classifying it by theme; means for storing the classified data in an information storage means and providing it to the user as needed; means for analyzing the user's facial expressions and tone of voice to identify their emotional state; means for presenting relevant information and event information to the user based on the identified emotions; and a software program for operating the means on a smart device. This enables the effective transfer of elderly people's knowledge and experience to the next generation, facilitates interaction with elderly people, and allows for the provision of personalized information according to the user's emotional state.

[0534] "Elderly people" are individuals above a certain age who possess abundant knowledge and experience and are expected to pass it on to the next generation.

[0535] "Voice or text data" refers to information obtained from elderly individuals, and is data expressed in either voice input or text input format.

[0536] A "natural language processing algorithm" is a set of computational procedures for analyzing acquired audio or text data and classifying and organizing it in a way that humans can understand.

[0537] "Classifying by theme" means organizing acquired data based on specific topics or areas and consolidating it into a database.

[0538] "Information storage means" refers to a digital storage device for storing analyzed and classified data.

[0539] A "user" is an individual or organization that uses the system to receive information or services.

[0540] "Analyzing facial expressions and tone of voice" means using facial recognition technology and voice analysis technology to evaluate changes in these in order to identify the user's emotional state.

[0541] "Presenting relevant information and event information" means displaying appropriate supplementary information or information about events that interest the user, tailored to their emotional state, on the device screen.

[0542] A "smart device" is a portable electronic device capable of performing calculations, and examples include mobile phones and tablet devices.

[0543] A "software program" is a set of instructions or code that constitutes a system and performs a specific function.

[0544] The system for implementing this invention aims to acquire knowledge from the elderly and provide users with information that is more emotionally responsive. The system's program is structured as follows:

[0545] The device acquires voice or text data from the elderly person. The voice data is converted into text data using speech recognition technology. Specifically, speech recognition software such as the Google Cloud Speech-to-Text API is used. The converted text data is sent to the server.

[0546] The server analyzes this text data using natural language processing algorithms. For example, by using a natural language processing library such as spaCy, the data is classified into specific themes. The classified data is then stored in an information storage system. When a user needs the data, they can access the database and retrieve the information.

[0547] Furthermore, the terminal and server analyze the user's facial expressions and tone of voice to identify their emotional state. By utilizing the Microsoft Azure Face API and Emotion API, it is possible to analyze the user's emotions in real time. Based on the analyzed emotions, relevant information and event information are displayed on the terminal screen.

[0548] For example, if an elderly person is sharing a local folktale and a user who is interested in the story smiles, the system can then provide information about events related to that area or additional reading material. This deepens communication and promotes intergenerational exchange.

[0549] This system can be used to provide an even higher level of user experience. An example of a prompt when using a generative AI model is: "Design an application that converts the voices of elderly people from audio to text, analyzes the content, and categorizes it. It also detects changes in emotion using a camera and microphone and suggests additional content to engage that person."

[0550] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0551] Step 1:

[0552] The device acquires voice or text data from the elderly person. The input is voice or text data from the elderly person; if it's voice data, it's converted to text data using the Google Cloud Speech-to-Text API. The output is the text data sent to the server.

[0553] Step 2:

[0554] The server analyzes received text data using natural language processing algorithms. The input is transformed text data, utilizing libraries such as spaCy. The data is categorized by theme based on its content. The output is the categorized text data.

[0555] Step 3:

[0556] The server stores the classified data in an information storage system. The input is text data classified by theme, and this data is stored in a database. The output is the data stored in the database.

[0557] Step 4:

[0558] The device analyzes the user's facial expressions and tone of voice to identify their emotional state. Input consists of the user's facial expression and voice data, which are processed using the Microsoft Azure Face API and Emotion API. The output is the identified emotional state.

[0559] Step 5:

[0560] The server displays relevant and event information on the device screen based on the identified emotions. The input consists of emotional states and related data, and the content is selected to match the user's interests. The output is the final content displayed on the device screen.

[0561] 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.

[0562] 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.

[0563] 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.

[0564] [Fourth Embodiment]

[0565] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0566] 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.

[0567] 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).

[0568] 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.

[0569] 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.

[0570] 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).

[0571] 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.

[0572] 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.

[0573] 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.

[0574] 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.

[0575] 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.

[0576] 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.

[0577] 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".

[0578] The system of this invention is designed to effectively collect, classify, and store knowledge and experience from the elderly and provide it to future generations. First, the terminal functions as an interface for the elderly, acquiring information through voice or text input. In this case, voice input is converted into text data using speech recognition technology. For example, if an elderly person tells a story about how a special farming method was used in this area in the past, this is recorded as text data.

[0579] Next, the server analyzes the received text data. Using natural language processing algorithms, it extracts keywords and relationships within the text and classifies them under themes such as "agricultural technology." The classified data is stored in a digital database, enabling information structuring and efficient searching.

[0580] Furthermore, the server has an interface that provides structured data to users. It is designed so that young people and educators can search and view information from the database, and if a user seeks information on, for example, the "history of agricultural technology," that organized knowledge will be immediately available for reference. The system presents information in a visually easy-to-understand layout and provides valuable information to users through interactive elements.

[0581] Furthermore, the server provides additional information related to local culture and history, building a foundation for understanding and utilizing unique local cultural customs. This also promotes intergenerational exchange within the community when used in local events.

[0582] Thus, the system of the present invention provides an effective means of digitally preserving the valuable knowledge possessed by the elderly and passing it on to future generations. As a specific example, it can be used to collect agricultural know-how from elderly people in rural areas and make it accessible to young people in the region, thereby supporting the development of new agricultural practices that utilize local resources.

[0583] The following describes the processing flow.

[0584] Step 1:

[0585] The device acquires voice input from the elderly person. At this time, the voice input function is activated and configured to collect information from the spoken words. The collected voice data is converted into text format in real time by a speech recognition module.

[0586] Step 2:

[0587] The terminal sends the converted text data to the server. This transmission is secure, with the data encrypted for security purposes, and uses a reliable communication protocol.

[0588] Step 3:

[0589] The server analyzes the received text data. It utilizes natural language processing algorithms to extract keywords from the text and classify the content into specific categories. For example, it organizes data according to themes such as "agricultural technology" or "lifestyle and culture."

[0590] Step 4:

[0591] The server stores the classified data in a digital database. This storage process involves tagging the data, adding metadata, and generating indexes to improve search efficiency.

[0592] Step 5:

[0593] Users can access the database and search for topics that interest them. Through the user interface, they can easily enter keywords into the search field and quickly retrieve relevant information.

[0594] Step 6:

[0595] The server extracts relevant information from the database in response to a user's search request and displays it in the user interface. It provides a detailed view of the information the user is looking for, offering knowledge in a visually organized manner.

[0596] Step 7:

[0597] The server also integrates information about the region's unique culture and history, and notifies users of local community events. This allows users to learn about local cultural assets and deepen their experience through actual interaction.

[0598] (Example 1)

[0599] 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".

[0600] In an aging society, there is a need to efficiently collect the valuable knowledge and experience of the elderly and pass it on to younger generations and local communities. However, systems for systematically organizing and preserving information about the elderly and providing it to users who need it in a visually and easily understandable way are currently not adequately developed. Furthermore, mechanisms for promoting intergenerational knowledge exchange by utilizing unique local cultures and histories are also insufficient.

[0601] 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.

[0602] In this invention, the server includes means for using a device to acquire knowledge from elderly people as voice or text data and converting it into digital signals, means for converting the acquired voice data into text data, and means for analyzing the text data using natural language processing technology to extract keywords and classify them by theme. This enables the efficient transmission of knowledge to younger generations and the preservation of regional cultural values ​​by digitizing and systematically storing the knowledge of elderly people.

[0603] The term "elderly" refers to people who are considered older in society and are mature individuals with a wealth of experience and knowledge.

[0604] "Audio data" refers to a collection of information in which human voices are recorded in digital format.

[0605] "Text data" refers to a collection of information recorded in digital format using character data.

[0606] A "digital signal" is a signal format suitable for communication and processing using digital data.

[0607] "Natural language processing technology" is a technology that enables computers to understand and generate human language.

[0608] A "keyword" is a word or phrase that has important meaning within a text or data.

[0609] A "theme" is the main topic or category used when organizing and analyzing information.

[0610] A "digital storage device" is a device or system for storing information in digital format.

[0611] A "visual and interactive format" refers to a method of presentation in which information is presented to the user in a way that is easy to see and allows for interaction.

[0612] "Regional cultural characteristics" refer to unique customs and values ​​found only in a particular region.

[0613] "Historical background" refers to past events and circumstances that constitute the process by which things are formed.

[0614] A "user interface" is a concept that refers to the screens and means of operation that users use to interact with a system.

[0615] "Activity information" refers to detailed information about a specific event or activity.

[0616] This invention is a system for digitizing the knowledge of the elderly and transmitting it to the next generation by linking an information acquisition device and a server.

[0617] First, the terminal functions as a device for acquiring voice or text data from elderly individuals. Voice data is captured in real time using a highly sensitive microphone and acoustic signal processing software (e.g., a common speech recognition API). The voice data is converted into a digital signal, and then into text data. This textual information forms the basis for subsequent analysis.

[0618] After receiving this text data, the server analyzes it using natural language processing techniques (e.g., a common natural language processing library). The server extracts keywords from the text and classifies them based on specific themes. The classified data is stored in a digital storage device for efficient retrieval and use later.

[0619] Furthermore, the server provides a user interface for users to view information. This interface enables visual display and interactive manipulation of data, and is designed to make knowledge more easily understood by older adults. This creates an environment where information is readily available.

[0620] For example, if an elderly person shares information such as, "In the past, a specific farming method was used in agriculture in this region," that information could be stored in a digital memory device under the theme of "agricultural technology." Then, a system would be provided that allows young people or researchers to easily access this information when they search for information such as "the history of agricultural technology."

[0621] An example of a prompt would be, "Please tell me about the agricultural techniques that have been practiced in this region for a long time, including specific methods and their background." This makes it possible to provide a system that allows users to easily obtain a wealth of information about region-specific knowledge and history.

[0622] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0623] Step 1:

[0624] The device acquires voices from elderly individuals. Using a high-sensitivity microphone, it converts the voice signal into digital data in real time. The input is the elderly person's voice, and the output is the digitized voice signal. Specifically, when an elderly person speaks about old farming methods, the device records their words in digital format.

[0625] Step 2:

[0626] The terminal converts acquired digital audio signals into text data. Using speech recognition technology, it analyzes the audio signal and generates text data. The input to this process is a digital audio signal, and the output is text. Specifically, the audio data is converted into text about a particular technique, such as agricultural technology.

[0627] Step 3:

[0628] The server receives text data from the terminal. The server prepares to receive and store the data. The input is the text data sent from the terminal, and the output is the storage of the data within the server. Specifically, the data converted into text on the terminal is sent to the server.

[0629] Step 4:

[0630] The server analyzes the received text data using natural language processing techniques. It tokenizes the data and extracts keywords. In this process, the input is the received text data, and the output is a keyword list. Specifically, the keyword "agricultural technology" is identified and extracted.

[0631] Step 5:

[0632] The server classifies the text data based on the extracted keywords. It classifies the data by theme and stores it in a digital storage device. The input to this process is a keyword list and text data, and the output is a structured data set. Specifically, the data is stored in the "Agricultural Technology" section of the database.

[0633] Step 6:

[0634] The server provides a user interface that allows users to search and view information. It searches the database and displays relevant information visually. The input to this process is the user's search query, and the output is the visualized search results. For example, if a user enters the query "history of agricultural technology," the relevant information will be displayed in an easy-to-read format.

[0635] (Application Example 1)

[0636] 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".

[0637] There is a need to effectively collect the knowledge and experience of the elderly and preserve it in a form that can be used in caregiving and education settings. In particular, there is a lack of interfaces to not only preserve the knowledge of the elderly as digital data, but also to easily share it among different generations and maximize its value. Against this backdrop, the challenge is to provide a system that effectively utilizes the knowledge of the elderly while promoting intergenerational exchange.

[0638] 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.

[0639] In this invention, the server includes means for acquiring knowledge from elderly people as voice or text data using speech recognition technology, means for classifying the acquired data into general themes using a natural language processing algorithm, and means for storing the classified data in a digital information storage medium and providing it to users as needed. This enables the effective sharing of elderly people's knowledge among caregivers and the revitalization of intergenerational exchange based on that knowledge.

[0640] "Speech recognition technology" is a technology that converts speech data into text data, making it possible to treat speech information obtained from elderly people as text information.

[0641] A "natural language processing algorithm" is a technology that analyzes the meaning and relationships of acquired text data and classifies it into specific themes or categories.

[0642] A "digital information storage medium" refers to a medium that can store data electronically and is used to preserve and manage the knowledge of elderly people over long periods of time.

[0643] "Users" refer to those who access and utilize the knowledge and experience of the elderly through this system.

[0644] An "interface" is the part of a system that provides a user interface and user experience for users to interact with the system.

[0645] A "caregiver" is someone who specializes in caring for the elderly, and who plays a role in using this system to collect knowledge about the elderly and utilize it in caregiving.

[0646] To realize this application, a system is needed that integrates speech recognition technology, natural language processing algorithms, digital information storage media, and a user interface.

[0647] The server uses the Google Cloud Speech-to-Text API to convert speech data obtained from elderly individuals into text data. The transcribed data is then analyzed using natural language processing algorithms and categorized into general themes. The categorized data is stored on digital storage media such as Google Firebase and made accessible to users.

[0648] The device takes the form of a smartphone or tablet and provides a smooth interface for caregivers to collect knowledge while directly interacting with the elderly. This allows caregivers to efficiently record the elderly's knowledge and share it with other users.

[0649] For example, when an elderly person talks about their unique gardening techniques, their voice is instantly transcribed into text, categorized based on similar themes, and then saved so that it can be accessed by other care facilities. This makes knowledge sharing across regions a reality.

[0650] An example of a prompt for a generative AI model is: "Convert the following audio data to text, extract the keywords, and save them. The topic is gardening techniques for seniors."

[0651] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0652] Step 1:

[0653] The device collects voice data through conversations with elderly individuals. This voice data is input using the microphone of a smartphone or tablet. The voice data is then transmitted to a server as a stream.

[0654] Step 2:

[0655] The server sends the received audio data to the Google Cloud Speech-to-Text API, where it is converted into text data. The input is audio data, and the output is the corresponding text data. The server then passes the converted text data to the next processing step.

[0656] Step 3:

[0657] The server feeds the received text data into a natural language processing (NLP) algorithm to perform keyword extraction and theme classification. This process takes text data as input and generates keywords and theme classifications as output. Specifically, it uses TF-IDF and topic modeling techniques.

[0658] Step 4:

[0659] The server stores the categorized data in Google Firebase. This step takes categorized text data as input and outputs it by saving it to the database. Firebase has the advantage of being able to store and retrieve data quickly.

[0660] Step 5:

[0661] The user accesses stored data and searches for necessary information using a user interface. This step takes the user's search query as input and returns relevant categorized data as output. Specific actions include implementing a search function within the UI.

[0662] 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.

[0663] The system of this invention collects the knowledge and experience of elderly people and passes it on to the next generation, while also recognizing the emotional state of users and using this information for interaction and information provision. First, the terminal acquires voice or text data from the elderly person. This data is converted into text using speech recognition technology and sent to the server. The server uses a natural language processing algorithm to analyze the acquired data and classify it by theme. The classified data is stored in a database and provided to the user as needed.

[0664] Furthermore, this system incorporates an emotion engine that analyzes user input and responses in real time and has the capability to recognize emotions. Emotion recognition includes facial expression analysis and voice tone analysis, analyzing various data points to identify emotional states. For example, if the system detects "interest" from a user's facial expression while they are viewing information, it can immediately suggest additional information or related events that correspond to that emotion.

[0665] Based on recognized emotions, the server appropriately modifies the interface and provides content that will pique the user's interest. For example, if the emotion engine detects a positive reaction when a user is browsing information about local folklore, information about relevant events taking place in that region will be displayed on the screen. Through this process, users can obtain a more interesting and personalized experience.

[0666] This system configuration facilitates user interaction through emotion recognition, thereby improving the quality of communication. Furthermore, it can effectively support the deepening of intergenerational exchange and the transmission of local culture.

[0667] The following describes the processing flow.

[0668] Step 1:

[0669] The device acquires voice or text data from the elderly person. In the case of voice input, it converts it to text in real time using speech recognition. The converted text data is encrypted and prepared for transmission to the server.

[0670] Step 2:

[0671] The server receives text data sent from the terminal. The received data is analyzed using natural language processing algorithms to extract important keywords and topics. This allows the data to be categorized into specific themes.

[0672] Step 3:

[0673] The server stores the classified text data in a digital database. During storage, tags are added to generate metadata and create an index to facilitate future searching.

[0674] Step 4:

[0675] The emotion engine recognizes the user's emotional state through the user interface. It uses sensor data and microphone input to analyze facial expressions and voice tone to identify emotions.

[0676] Step 5:

[0677] The server dynamically adapts the interface based on the recognized user's emotions. For example, if the user expresses "surprise" or "interest," it displays relevant visual effects and additional information on the interface.

[0678] Step 6:

[0679] Users can view information provided through emotional feedback and act based on the system's suggestions. For example, information encouraging participation in a specific cultural event may be displayed, and users can then take steps to participate directly from the screen.

[0680] Step 7:

[0681] The server records user actions and accumulates data on usage patterns and emotional responses. This creates a feedback loop to improve the accuracy of future suggestions and make the user experience more personalized.

[0682] (Example 2)

[0683] 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".

[0684] In an aging society, passing on knowledge and culture to the next generation is a crucial challenge. However, there is a lack of effective means to collect, structure, and transmit the abundant knowledge and experience of the elderly to the next generation. Furthermore, there is a need to improve user interest and understanding by providing information that takes into account the emotional state of individuals. To address these challenges, there is a need for systems that promote intergenerational exchange and realize the transmission and utilization of information.

[0685] 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.

[0686] In this invention, the server includes means for acquiring information as voice or text data from the person providing the information, means for analyzing the acquired data using an information processing algorithm and classifying it into categories, means for storing the classified data on a recording medium and providing it to the user as needed, means for sensing the user's emotional state, and means for adjusting and providing the presented information based on the sensed emotions. This makes it possible not only to effectively collect and structure the knowledge and experience of the elderly, but also to provide users with customized information that matches their emotions. This realizes the transmission of culture and the promotion of intergenerational exchange.

[0687] "Target recipients of information" refers to individuals or groups that are the primary source of data collection, and primarily includes elderly people.

[0688] "Audio or text data" refers to a form of information transmitted through language, including audio recordings and text-typed information.

[0689] An "information processing algorithm" refers to a computational method for analyzing, structuring, and classifying received data, and includes natural language processing techniques.

[0690] "Classifying by category" refers to the act of grouping data according to its content or theme, which makes it easier to search for and use information.

[0691] "Recording medium" refers to a technical means for storing digital data, and includes databases and cloud storage.

[0692] "Users" refers to individuals or groups who are able to receive and use information from the system, and includes those who play a role in intergenerational exchange.

[0693] "Emotional state sensing" refers to the technological process of detecting and analyzing an individual's emotional responses, and includes facial recognition and voice analysis.

[0694] "Adjusting and providing information" refers to the act of optimizing the selection and display of information according to the user's emotions and circumstances, thereby achieving personalized information delivery.

[0695] The system of the present invention effectively collects the knowledge and experience of the elderly and passes it on to the next generation, while also recognizing the emotional state of the user and utilizing this information for interaction and information provision. Specific embodiments for carrying out the invention are shown below.

[0696] The terminal is responsible for collecting data from information providers through voice or text input. Voice data is converted into text data using speech recognition technology. Specifically, a common speech recognition API is used to convert speech to text, and the result is sent to the server. In this process, for example, a general-purpose voice input device or keyboard is used.

[0697] The server analyzes the received text data using natural language processing algorithms. Here, general-purpose natural language processing software is used to classify the data into specific themes and categories. This classified data is stored on a storage medium called a database and provided to the user as needed. Furthermore, to analyze the user's emotional state, the server uses image processing and speech analysis technologies to recognize emotions in real time. This process utilizes common facial expression analysis software and speech tone analysis tools.

[0698] Users can enjoy a personalized experience based on the information they receive through the system. By recognizing the user's emotional state, the server can appropriately present information that matches that emotion. For example, if a user expresses positive emotions while viewing information including local folklore, information about related events will be provided. In this way, users can obtain customized information based on their interests and preferences.

[0699] Examples of prompts include, "How can we collect testimonials from elderly people and pass on that knowledge to the next generation?" and "How can we improve the user experience through emotion recognition?" Such prompts can be used to effectively utilize the system's functions.

[0700] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0701] Step 1:

[0702] The terminal obtains information from the information provider as voice or text data. In the case of voice data, the terminal collects the voice using a voice input device. The input voice data is converted into text data by speech recognition software, and this text is sent to the server. In the case of text data, it is entered directly via a keyboard or similar device and sent to the server.

[0703] Step 2:

[0704] The server analyzes the received text data using natural language processing algorithms. At this stage, the server classifies the data into different categories. Using a generative AI model, it identifies the theme of each data point from the input text data and obtains classification information as output. This output is stored in the database as text data with category labels. Specifically, categories such as "culture" and "history" are used.

[0705] Step 3:

[0706] The server stores the classified data on a storage medium called a database. In this step, the organized data is stored in a format that can be easily searched and accessed later. By using database software to tag related information, subsequent query processing becomes more efficient. The information stored in the database can be retrieved when requested by the user.

[0707] Step 4:

[0708] When a user accesses the system, the server senses the user's emotional state before providing information to the interface. The user's facial expressions and voice tone become input data, which are then analyzed by an emotion recognition engine. Based on the detected emotional information, the information provided to the user is customized. This process involves image processing and voice analysis tools.

[0709] Step 5:

[0710] The server presents the user with information tailored to their emotional state. Relevant information is selected from the user's emotional data and stored data, and output to the user in visual and auditory ways. For example, if a user indicates "interest," relevant local event information is displayed, enriching the user's experience. This allows the user to access personalized information.

[0711] (Application Example 2)

[0712] 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".

[0713] In modern society, the wealth of knowledge and experience possessed by the elderly is not being adequately passed on to the next generation, and there is a particular risk of losing information about unique local cultures and histories. Furthermore, there is a lack of smooth communication between the elderly and younger generations, highlighting the need to promote intergenerational exchange. Additionally, a challenge remains: there is no system in place to appropriately recognize the emotional state of the elderly and provide them with appropriate information accordingly.

[0714] 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.

[0715] In this invention, the server includes means for acquiring knowledge from elderly people as voice or text data; means for analyzing the acquired data using a natural language processing algorithm and classifying it by theme; means for storing the classified data in an information storage means and providing it to the user as needed; means for analyzing the user's facial expressions and tone of voice to identify their emotional state; means for presenting relevant information and event information to the user based on the identified emotions; and a software program for operating the means on a smart device. This enables the effective transfer of elderly people's knowledge and experience to the next generation, facilitates interaction with elderly people, and allows for the provision of personalized information according to the user's emotional state.

[0716] "Elderly people" are individuals above a certain age who possess abundant knowledge and experience and are expected to pass it on to the next generation.

[0717] "Voice or text data" refers to information obtained from elderly individuals, and is data expressed in either voice input or text input format.

[0718] A "natural language processing algorithm" is a set of computational procedures for analyzing acquired audio or text data and classifying and organizing it in a way that humans can understand.

[0719] "Classifying by theme" means organizing acquired data based on specific topics or areas and consolidating it into a database.

[0720] "Information storage means" refers to a digital storage device for storing analyzed and classified data.

[0721] A "user" is an individual or organization that uses the system to receive information or services.

[0722] "Analyzing facial expressions and tone of voice" means using facial recognition technology and voice analysis technology to evaluate changes in these in order to identify the user's emotional state.

[0723] "Presenting relevant information and event information" means displaying appropriate supplementary information or information about events that interest the user, tailored to their emotional state, on the device screen.

[0724] A "smart device" is a portable electronic device capable of performing calculations, and examples include mobile phones and tablet devices.

[0725] A "software program" is a set of instructions or code that constitutes a system and performs a specific function.

[0726] The system for implementing this invention aims to acquire knowledge from the elderly and provide users with information that is more emotionally responsive. The system's program is structured as follows:

[0727] The device acquires voice or text data from the elderly person. The voice data is converted into text data using speech recognition technology. Specifically, speech recognition software such as the Google Cloud Speech-to-Text API is used. The converted text data is sent to the server.

[0728] The server analyzes this text data using natural language processing algorithms. For example, by using a natural language processing library such as spaCy, the data is classified into specific themes. The classified data is then stored in an information storage system. When a user needs the data, they can access the database and retrieve the information.

[0729] Furthermore, the terminal and server analyze the user's facial expressions and tone of voice to identify their emotional state. By utilizing the Microsoft Azure Face API and Emotion API, it is possible to analyze the user's emotions in real time. Based on the analyzed emotions, relevant information and event information are displayed on the terminal screen.

[0730] For example, if an elderly person is sharing a local folktale and a user who is interested in the story smiles, the system can then provide information about events related to that area or additional reading material. This deepens communication and promotes intergenerational exchange.

[0731] This system can be used to provide an even higher level of user experience. An example of a prompt when using a generative AI model is: "Design an application that converts the voices of elderly people from audio to text, analyzes the content, and categorizes it. It also detects changes in emotion using a camera and microphone and suggests additional content to engage that person."

[0732] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0733] Step 1:

[0734] The device acquires voice or text data from the elderly person. The input is voice or text data from the elderly person; if it's voice data, it's converted to text data using the Google Cloud Speech-to-Text API. The output is the text data sent to the server.

[0735] Step 2:

[0736] The server analyzes received text data using natural language processing algorithms. The input is transformed text data, utilizing libraries such as spaCy. The data is categorized by theme based on its content. The output is the categorized text data.

[0737] Step 3:

[0738] The server stores the classified data in an information storage system. The input is text data classified by theme, and this data is stored in a database. The output is the data stored in the database.

[0739] Step 4:

[0740] The device analyzes the user's facial expressions and tone of voice to identify their emotional state. Input consists of the user's facial expression and voice data, which are processed using the Microsoft Azure Face API and Emotion API. The output is the identified emotional state.

[0741] Step 5:

[0742] The server displays relevant and event information on the device screen based on the identified emotions. The input consists of emotional states and related data, and the content is selected to match the user's interests. The output is the final content displayed on the device screen.

[0743] 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.

[0744] 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.

[0745] 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 robot 414.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] 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.

[0750] 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.

[0751] 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."

[0752] 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.

[0753] 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.

[0754] 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.

[0755] 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.

[0756] 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.

[0757] 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.

[0758] 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.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] 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.

[0763] 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.

[0764] The following is further disclosed regarding the embodiments described above.

[0765] (Claim 1)

[0766] Means of acquiring knowledge from the elderly as audio or text data,

[0767] A method for analyzing acquired data using natural language processing algorithms and classifying it by theme,

[0768] A means of storing classified data in a database and providing it to users as needed,

[0769] A system that includes this.

[0770] (Claim 2)

[0771] The system according to claim 1, comprising means for classifying data obtained from elderly people based on the unique culture and history of the region and constructing a database.

[0772] (Claim 3)

[0773] The system according to claim 1, comprising means for providing event information to promote intergenerational exchange through a user interface.

[0774] "Example 1"

[0775] (Claim 1)

[0776] A device that acquires knowledge from elderly people as voice or text data, and a means for converting it into a digital signal,

[0777] A means of converting acquired audio data into text data,

[0778] A method for analyzing text data using natural language processing techniques, extracting keywords, and classifying them by theme,

[0779] A means of storing classified data in a digital storage device and providing it to the user in a visual and interactive format,

[0780] A system that includes this.

[0781] (Claim 2)

[0782] The system according to claim 1, comprising means for further classifying information obtained from elderly people based on unique cultural characteristics and historical background of the region, and constructing a digital storage device.

[0783] (Claim 3)

[0784] The system according to claim 1, comprising means for providing activity information to promote intergenerational exchange within an organization through a user interface.

[0785] "Application Example 1"

[0786] (Claim 1)

[0787] A means of acquiring knowledge from elderly people as voice or text data using speech recognition technology,

[0788] A method for analyzing the acquired data using natural language processing algorithms and classifying it into general themes,

[0789] A means of storing classified data on a digital information storage medium and providing it to users as needed,

[0790] A means of providing an interface for sharing knowledge about the elderly among caregivers,

[0791] A system that includes this.

[0792] (Claim 2)

[0793] The system according to claim 1, comprising means for classifying data obtained from elderly people based on the unique culture and history of the region, and constructing an information storage medium.

[0794] (Claim 3)

[0795] The system according to claim 1, comprising means for providing event information for promoting interaction based on the knowledge of the elderly through a user interface.

[0796] "Example 2 of combining an emotion engine"

[0797] (Claim 1)

[0798] Means for obtaining information as audio or text data from the person providing the information,

[0799] A means of analyzing the acquired data using an information processing algorithm and classifying it into categories,

[0800] A means of storing classified data on a recording medium and providing it to users as needed,

[0801] A means of sensing the emotional state of the user,

[0802] A means of adjusting and providing presented information based on sensed emotions,

[0803] A system that includes this.

[0804] (Claim 2)

[0805] The system according to claim 1, comprising means for classifying data obtained from information providers based on local culture and history, and for constructing a recording medium.

[0806] (Claim 3)

[0807] The system according to claim 1, comprising means for providing activity information to promote intergenerational interaction through a user interface.

[0808] "Application example 2 when combining with an emotional engine"

[0809] (Claim 1)

[0810] Means of acquiring knowledge from the elderly as audio or text data,

[0811] A method for analyzing acquired data using natural language processing algorithms and classifying it by theme,

[0812] A means for storing classified data in an information storage means and providing it to users as needed,

[0813] A method for identifying the emotional state of a user by analyzing their facial expressions and tone of voice,

[0814] A means of presenting users with relevant information and event information based on identified emotions,

[0815] A software program for operating the means on a smart device,

[0816] A system that includes this.

[0817] (Claim 2)

[0818] The system according to claim 1, comprising means for classifying data obtained from elderly people based on the unique culture and history of the region, and constructing an information storage means.

[0819] (Claim 3)

[0820] The system according to claim 1, comprising means for analyzing the emotional state of a user and providing personalized interaction and information in response to that user's reaction. [Explanation of Symbols]

[0821] 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 acquiring knowledge from elderly people as voice or text data using speech recognition technology, A method for analyzing the acquired data using natural language processing algorithms and classifying it into general themes, A means of storing classified data on a digital information storage medium and providing it to users as needed, A means of providing an interface for sharing knowledge about the elderly among caregivers, A system that includes this.

2. The system according to claim 1, comprising means for classifying data obtained from elderly people based on the unique culture and history of the region, and constructing an information storage medium.

3. The system according to claim 1, comprising means for providing event information for promoting interaction based on the knowledge of the elderly through a user interface.

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