system

Abstract

We provide the system. [Solution] A means of receiving input information from the user and analyzing that information, A means for searching for and proposing the optimal public service from a data storage device based on the analysis results, A means for automatically generating necessary records related to the proposed public service, A means of periodically updating information by referring to an external data storage device, A means of obtaining feedback and using it to improve public services, A means to enable users to select public services using their mobile devices and download documents related to those procedures to their devices, A system that includes this.

Description

Technical Field

[0004] , , , ,

[0005] , , , ,

[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 the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003] <00^00016>

Patent Document 1

Summary of Invention

Problems to be Solved by the Invention

[0004] In modern society, due to the effects of aging and declining birthrates, family health problems and economic insecurity are increasing. Along with this, the need for individuals to use administrative and welfare services is growing, but it is often difficult to determine which services to use and how to use them. In addition, there are not a few individuals who feel resistance to consulting these problems within a company. The present invention aims to provide an environment in which users can comfortably consult such personal problems and anxieties, propose necessary administrative services and welfare services, and further provide means for quickly and accurately assisting in procedures.

Means for Solving the Problems

[0005] This invention comprises means for receiving and analyzing user input data, means for searching a database for and proposing appropriate services based on the analysis results, and means for automatically generating necessary documents related to the proposed services. It also includes means for periodically updating information by referencing an external database, ensuring users always have the latest information. Furthermore, by obtaining feedback and utilizing it to improve services, the system provides a precise response to user problems. This configuration allows users to efficiently utilize appropriate services.

[0006] A "user" refers to an individual who uses the system to input their consultation details and seek support from administrative or welfare services.

[0007] "Input data" refers to text and audio information provided by users to the system, used to express problems or concerns.

[0008] "Means of analysis" refers to the process of identifying user problems and needs by using semantic analysis and natural language processing techniques on input data received from users.

[0009] A "database" is a storage device that stores information about administrative and welfare services, and is used to search for appropriate services based on user needs.

[0010] "The means of proposing" refers to the process of selecting the most suitable service for the user based on the analysis results and presenting that information to the user.

[0011] "Methods for automatically generating necessary documents" refers to technologies that automatically create the documents required to use the proposed service based on templates.

[0012] An "external database" refers to an information source located outside the system that is referenced to obtain the latest information on administration and welfare.

[0013] "Feedback" refers to the process by which users return their evaluations and opinions about the services and information provided to the system.

[0014] "Service improvement" refers to continuous efforts to improve the quality of the services provided by the system based on user feedback, enabling more effective support. [Brief explanation of the drawing]

[0015] [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] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the 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), etc.

[0019] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the 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.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] The system of the present invention is designed to allow users to confidently discuss personal problems and anxieties, and to receive suggestions and procedural support for the most suitable administrative and welfare services. The following describes embodiments for carrying out the present invention.

[0037] Users input their inquiries in text or voice format via their device. The device sends this input data to the server. The server analyzes the received data using semantic analysis and natural language processing techniques to identify the user's needs and problems.

[0038] After the analysis is complete, the server consults its internal database to find the most suitable administrative and welfare services for the user. This process includes an algorithm that considers evaluation parameters such as service effectiveness and usability to select the optimal service.

[0039] Next, the server sends information to the terminal to notify the user of the proposed service. The terminal displays this information to the user, presenting the specific service details and usage procedures. In some cases, the server can also automatically generate and provide the user with any necessary documents related to the proposed service.

[0040] Furthermore, the server periodically accesses external databases to obtain the latest information on administrative and welfare services. This ensures that the system always maintains and provides users with the most up-to-date information.

[0041] When a user provides feedback on the usefulness of the information and services provided, the device sends this feedback to the server. The server uses the received feedback to improve the system and provide better services.

[0042] As a concrete example, consider a case where a user seeks advice regarding family care. The server searches its database for care-related services and suggests options such as "community-based integrated care centers" and the "long-term care insurance system." It then automatically generates the necessary application documents, supporting the user in smoothly completing the process.

[0043] Thus, the system of the present invention aims to provide prompt and accurate support for various problems faced by users.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The user enters their inquiry into the device as text or voice. Let's assume the user enters "I want to know about support regarding caring for my parents."

[0047] Step 2:

[0048] The terminal receives data entered by the user and sends it to the server. In the case of voice data, speech recognition technology is used beforehand to convert it to text.

[0049] Step 3:

[0050] The server processes the received text data for semantic analysis and extracts keywords related to elderly care. This analysis identifies the type of service the user needs.

[0051] Step 4:

[0052] The server consults its internal database to find the administrative and welfare services best suited to the user's needs. For example, it might suggest access to a "community-based integrated care center" or the "long-term care insurance system."

[0053] Step 5:

[0054] The server automatically generates the necessary documents from templates based on the proposed service. These documents are required for the user to submit when receiving care services.

[0055] Step 6:

[0056] The server sends the search results and automatically generated documents to the user's device to notify them.

[0057] Step 7:

[0058] The terminal displays information received from the server to the user, providing access to specific service proposals and generated documents.

[0059] Step 8:

[0060] The user either proceeds with the procedure according to the suggestion, or enters feedback on the device if further assistance is needed.

[0061] Step 9:

[0062] The device receives feedback from users and sends it to the server. This allows the server to use the feedback to improve the services it provides.

[0063] This ensures users receive consistent support and promotes the use of appropriate services.

[0064] (Example 1)

[0065] 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."

[0066] In modern society, there is a need to quickly and accurately propose appropriate public services and support to address the diverse problems individuals face. Furthermore, since information is updated daily, it is necessary to always provide the latest service information. However, doing this manually is inefficient and can lead to individual inconsistencies. Moreover, the lack of opportunities for users to provide feedback on the services they receive, and the insufficient mechanisms for using that information to improve the system, makes it difficult to provide sophisticated support.

[0067] 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.

[0068] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching a knowledge base for and proposing appropriate public services based on the analysis results, and means for automatically generating necessary information related to the proposed public services. This enables the user to always receive the latest and most optimal service information and to receive rapid problem-solving support.

[0069] "Input information" refers to data obtained from the user in text or audio format, including individual problems and consultation details.

[0070] "Analysis" is the process of analyzing received input information using semantic analysis and natural language processing techniques to identify user needs and problems.

[0071] "Public services" refer to administrative and welfare services provided by government agencies and related organizations, and include specific support available to users to solve problems.

[0072] A "knowledge base" is a dataset that systematically organizes information about possible public services and allows for searching and referencing as needed.

[0073] "Automatic generation" refers to the process of generating necessary information and documents using a program without human intervention, thereby supporting the user's specific procedures.

[0074] "External information sources" refer to databases and information services outside the system that can be referenced to obtain the latest information at all times.

[0075] "Feedback" refers to comments and opinions made by users regarding the usefulness and satisfaction level of the proposed service, and is used to improve the system.

[0076] "Voice information" refers to data in audio format obtained from users, including information entered via voice regarding the content of the consultation.

[0077] "Text information" refers to data in text format that has been converted by speech recognition, and is the subject of analysis.

[0078] "Latest service information" refers to the most up-to-date information on administrative and welfare services, and represents the current information that should be provided to users.

[0079] The system of this invention helps users to access appropriate public services more effectively. Based on information entered by the user via a terminal, the system selects and provides suggested services using a variety of technologies.

[0080] First, the user enters their inquiry details using text or voice via their device. If voice information is entered, the device uses a speech recognition engine to convert the voice to text. In this process, general speech recognition software is used, but a specific example is Google® Speech-to-Text API.

[0081] Next, the server receives the text information sent from the terminal and analyzes it using semantic analysis and natural language processing. Natural language processing libraries such as "spaCy" and "NLTK" can be used for this analysis. This helps identify the user's needs and problems.

[0082] The server searches its internal knowledge base based on the analysis results. This knowledge base organizes information on various public services and includes data for recommending appropriate services. Algorithms utilizing machine learning libraries such as "scikit-learn" and "TENSORFLOW®" can be applied to select services.

[0083] Proposed public services are notified to the user via a terminal. The terminal can display this information and provide detailed guidance on the procedures and required documents for the relevant process. The server automatically generates documents as needed and helps users efficiently proceed with the process, for example, by creating PDF documents using "ReportLab".

[0084] Furthermore, the server periodically references external sources to obtain the latest service information and update its knowledge base. This ensures that users are always provided with the most up-to-date information.

[0085] When a user provides feedback on a service they have used, the terminal transmits this feedback to the server. The server then uses this feedback to improve the system and enhance the quality of public services provided. An example of a specific prompt would be: "Please describe a system that analyzes a user's inquiry in natural language and suggests appropriate welfare services."

[0086] This system is designed to be an essential support for users, helping them access public services quickly and reliably.

[0087] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0088] Step 1:

[0089] The user enters their consultation details via a terminal. The input format is either text or voice. At this stage, the input is raw information from the user. If voice input is received, the terminal uses a speech recognition engine to convert the voice information into text information. Through this conversion process, the user's consultation details are standardized into text format and sent to the server.

[0090] Step 2:

[0091] The server receives text information sent from the terminal. The received text data is subjected to semantic analysis and natural language processing. This processing uses libraries such as "spaCy" and "NLTK" to identify the user's problems and needs. The analysis output provides keywords and problem categories.

[0092] Step 3:

[0093] The server searches its internal knowledge base based on the analysis results. This knowledge base is a database containing detailed information about public services. During this search, the server uses machine learning techniques to select the appropriate services. As a result, a list of services that meet the user's needs is output.

[0094] Step 4:

[0095] The server sends the selected service information to the terminal. The terminal displays the received information to the user, conveying the specific service content along with details of the related procedures. For example, information on the "Long-Term Care Insurance System" and "Regional Medical Support Center" may be displayed. The output of this step is detailed information about the services that can be displayed.

[0096] Step 5:

[0097] The server automatically generates the information required for the proposed service. It uses libraries such as "ReportLab" to generate the necessary documents in PDF format. This process outputs instructions for the next steps the user should take.

[0098] Step 6:

[0099] The server periodically references external data sources to update its knowledge base. This ensures that the latest administrative and welfare service information is obtained and reflected in the system. References to external data update the knowledge base, establishing a foundation for providing up-to-date information.

[0100] Step 7:

[0101] Users provide feedback on the services offered through their devices. This feedback information is sent from the device to the server. The server analyzes the received feedback and uses it to improve the system. The results of this analysis improve the accuracy of future service proposals.

[0102] (Application Example 1)

[0103] 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."

[0104] A challenge exists in that users lack quick and accurate means of accessing the latest public services available to resolve personal problems, and the procedures for doing so are often cumbersome, resulting in ineffective support. This invention aims to improve this situation and enable users to easily find and smoothly utilize the services they need.

[0105] 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.

[0106] In this invention, the server includes means for receiving input information from the user and analyzing that information, means for searching for and proposing the most suitable public service from a data storage device, and means for referring to an external data storage device and periodically updating the information. This makes it possible for users to quickly search for public services that match their needs and to easily perform the detailed procedures.

[0107] A "user" refers to an individual or organization that uses the system to seek advice and receive suggestions for the most suitable public services.

[0108] "Input information" refers to data such as text and audio that users provide to the system in order to resolve their own problems or concerns.

[0109] "Means of analysis" refers to the technical process of analyzing received input information to identify user needs and challenges.

[0110] "Public services" refer to services provided by government agencies and related organizations, including the support and procedures necessary to resolve the individual problems of users.

[0111] A "data storage device" refers to a database or other storage means that a system accesses, searches for, and stores information.

[0112] "Means of automatic generation" refers to the process by which a system automatically creates necessary records and procedures and provides them to the user.

[0113] An "external data storage device" refers to an external database or information source that a system references to periodically update its information.

[0114] "Feedback" refers to evaluations and opinions provided by users regarding the usefulness of proposed services or procedures.

[0115] "Mobile information terminals" refer to information processing devices that can be used while on the go, such as mobile phones and tablets.

[0116] This invention comprises a system used via a smartphone or other mobile information terminal. The user inputs their problems or anxieties into the terminal as text or voice. The terminal sends this input information to a server in the cloud, where it is analyzed using semantic analysis and natural language processing techniques. This process utilizes Python and the natural language processing library SpaCy, or the Google Cloud Natural Language API.

[0117] Based on the analysis results, the server identifies the most suitable public service from the data storage device and proposes it to the user. The service selection uses an algorithm that considers effectiveness and usability. The server then automatically generates and provides the user with the necessary materials related to the proposed service. This function is implemented using cloud services such as AWS® or GCP.

[0118] Furthermore, the server periodically references an external data storage device to obtain the latest information on public services and update the database. This ensures that users are always provided with the most up-to-date service information. The system also includes a feature that allows users to easily select specific public services and download relevant materials using their smartphones.

[0119] As a concrete example, consider a user who "wants advice about using day care services for their elderly parent." The server analyzes the user's inquiry and presents a list of local day care facilities. It provides the user with detailed information, including ratings and fees, and automatically generates and makes available for download the necessary application documents for the selected facility.

[0120] An example of a prompt message to provide to the generating AI model is: "Please enter your concerns regarding caregiving. For example, regarding the selection of a care facility or the procedures for long-term care insurance. We will suggest the most suitable care services."

[0121] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0122] Step 1:

[0123] The user uses a smartphone or mobile device to input their consultation details in text or voice format. This input data is temporarily stored on the device and prepared to be sent to the server for analysis. In the case of voice input, the device converts the input voice into text data. Input: User's consultation details (text / voice). Output: Text data ready to be sent to the server.

[0124] Step 2:

[0125] The server analyzes text data received from the terminal. Here, the server uses natural language processing techniques to semantically analyze the input data in order to understand the user's needs and problems. The analysis uses Python and either SpaCy or the Google Cloud Natural Language API. Input: Text data. Output: Analysis results (user needs).

[0126] Step 3:

[0127] Based on the analysis results, the server searches for the most suitable public services from the data storage device. The search uses an algorithm that considers service content, effectiveness, and availability to find the optimal solution to the user's specific problem. Input: Analysis results. Output: List of optimal public services.

[0128] Step 4:

[0129] The server automatically generates the necessary documents related to the selected public service. This allows users to smoothly proceed with applying for and using the service. This document generation and management are handled using AWS or GCP cloud services. Input: List of optimal public services. Output: Required documents.

[0130] Step 5:

[0131] The server periodically updates its database by referencing an external data storage device to maintain the latest public service information. This process ensures that the information provided to users is always up-to-date. Input: External data. Output: Updated internal database.

[0132] Step 6:

[0133] The user uses their smartphone to view information on the most suitable public services presented by the server and download the necessary documents. This process makes it easy for the user to select services and complete procedures. Input: Service information from the server. Output: Procedure documents available to the user.

[0134] 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.

[0135] This invention allows users to input their consultation details through a system, which then proposes appropriate administrative and welfare services, automatically generates necessary documents, and provides support for procedures. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, the aim is to provide a more personalized service.

[0136] Users input their consultation details using their device. If the user inputs by voice, the data is converted into text using speech recognition technology on the device. The device then sends the data to the server.

[0137] When the server analyzes the received data, it first performs semantic analysis to extract the user's needs. This process incorporates an emotion engine that can detect the user's emotional state based on the content of the text data. For example, if the text contains many keywords such as "anxiety" or "worry," the server will recognize the user's emotion as "anxiety."

[0138] Next, the server searches its internal database for appropriate administrative and welfare services based on the analyzed data. During this process, it can adjust the suggested services based on the user's emotional assessment. For example, for a user experiencing anxiety, it prioritizes suggesting services with more comprehensive support or those that include emotional care.

[0139] The server automatically generates the necessary documents related to the proposed service and prepares to notify the user. This allows the user to proceed with the process smoothly.

[0140] Once the proposal is finalized, the server sends this information to the terminal. The terminal displays the information to the user, providing details about the proposed service, instructions for using it, and how to access the generated documents.

[0141] Finally, users are allowed to provide feedback on the usefulness of the information and services, and this data is sent from the device to the server. By receiving user feedback, the server continuously improves the quality of the services provided.

[0142] For example, if a user enters "I'm worried about caring for a family member," the server will suggest caregiving-related support services and also offer counseling services to alleviate the user's anxiety. In this way, personalized support is achieved.

[0143] The following describes the processing flow.

[0144] Step 1:

[0145] Users use their devices to input their concerns as text or voice. For example, they might type, "I'm worried about caring for my parents."

[0146] Step 2:

[0147] The terminal receives the input data. In the case of voice data, it uses speech recognition technology to convert it into text data. The converted text data is then sent to the server.

[0148] Step 3:

[0149] The server analyzes the received text data. Using a semantic analysis engine, it extracts keywords present in the consultation content and determines the user's needs.

[0150] Step 4:

[0151] The server's emotion engine recognizes the user's emotions from extracted keywords and sentence structure. In this case, it recognizes the user's emotion as "anxiety" based on words such as "anxiety" and "worry."

[0152] Step 5:

[0153] Based on the results of analysis and emotion recognition, the server searches its internal database for appropriate administrative and welfare services. Options include "care consultation services" and "mental health counseling."

[0154] Step 6:

[0155] The server automatically generates the necessary documents for the proposed service, such as application forms for care support and appointment forms for counseling.

[0156] Step 7:

[0157] The server sends the selected service information to the terminal along with the generated document. This includes specific service details and usage instructions.

[0158] Step 8:

[0159] The device displays the received information to the user. The screen shows an overview and links to each suggested service, as well as options for downloading documents.

[0160] Step 9:

[0161] Users review the proposed information and procedures and enter feedback into their device. For example, they might describe their satisfaction with the proposal or their progress in using the service.

[0162] Step 10:

[0163] The device sends user feedback to the server. This information is used as data to improve the quality of the service.

[0164] Through these steps, users will be able to receive more appropriate and personalized assistance for their problems.

[0165] (Example 2)

[0166] 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".

[0167] In modern society, users face the challenge of obtaining appropriate advice and services for the various problems they encounter. Furthermore, there is a demand for highly personalized services that respond to users' emotions and needs, as well as for efficient processing of necessary procedures. Conventional systems suffer from insufficient consideration of user emotions in service suggestions and continuous improvement through the use of feedback.

[0168] 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.

[0169] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching for and proposing appropriate functions from information sources based on the analysis results, and means for determining the user's emotional state using an emotion analysis engine. This makes it possible to propose services that meet the individual needs and emotional state of the user, thereby realizing efficient and personalized support.

[0170] "Input information" refers to data that a user provides to the system, including in various formats such as audio and text.

[0171] "Analysis" is the process of analyzing received information to understand the user's needs and emotional state.

[0172] A "function" refers to a specific service or action that provides the advice and support that the user is looking for.

[0173] "Information sources" refer to a collection of databases and resources used to search for appropriate features to suggest to users.

[0174] "Required documents" refer to automatically generated documents and forms that are necessary for users to proceed with the proposed functionality.

[0175] An "emotion analysis engine" is a general term for technologies and algorithms used to determine an emotional state based on user input.

[0176] "Personalized support" means providing services that are customized to the specific needs and emotions of each individual user.

[0177] This invention is a system consisting of a user terminal and a server equipped with multiple data analysis means.

[0178] Users can use a terminal to provide their consultation details either by typing or by voice. In the case of voice input, the terminal uses speech recognition technology to convert the content into text data. The terminal incorporates commonly used speech recognition software and employs a device capable of converting speech to text in real time.

[0179] The terminal sends the received text data to the server. The server analyzes the received data using advanced natural language processing technology. In particular, it uses a generative AI model to extract the user's intentions and the support they need from the data, and also uses an emotion analysis engine to determine the user's emotional state. This makes it possible to suggest appropriate functions that meet the user's needs.

[0180] The server has the capability to automatically generate materials related to the proposed functionality, providing users with the documents and instructions they need immediately. Accordingly, it regularly references external sources to update information and ensure that it always provides the latest data. Digital document generation technology is utilized in this process.

[0181] The terminal displays information received from the server to the user and provides instructions on how to use the suggested functions and related materials. Finally, the user enters feedback on the usefulness of the service, and this data is sent to the server, contributing to the improvement of the entire system.

[0182] For example, if a user enters a prompt message such as, "I would like to seek advice regarding domestic stress and find out what kind of support I can receive," the server can suggest stress-related counseling services and introduce activities that are effective in reducing stress. Providing individually customized support to the user in this way is a key feature of the present invention.

[0183] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0184] Step 1:

[0185] The user enters their consultation details using a device. The input is provided in either text or voice format. In the case of voice input, the device uses speech recognition technology to convert the voice data into text data. This results in the user's intended consultation content being output as text. Specifically, the speech recognition engine analyzes the input voice waveform and converts it into a string based on a language model.

[0186] Step 2:

[0187] The terminal sends the converted text data to the server. The text data is transferred to the server via network communication. A secure protocol (e.g., HTTPS) is typically used for this communication. The terminal divides the data into packets and sends them sequentially to the server.

[0188] Step 3:

[0189] The server analyzes the received text data. First, it performs semantic analysis using natural language processing techniques to extract the meaning of the text and the user's needs. This analysis utilizes generative AI models to deepen contextual understanding. In this process, it identifies specific keywords and phrases from the input text and clarifies the user's requests.

[0190] Step 4:

[0191] The server uses an emotion analysis engine to determine the user's emotional state. It analyzes emotional patterns from vocabulary and expressions within text data and outputs emotions such as "anxiety" or "happiness." Emotion analysis is achieved using emotion dictionaries and machine learning models.

[0192] Step 5:

[0193] Based on the analysis results, the server searches for and proposes appropriate functions from internal sources. The function suggestion system selects and outputs a list of the most suitable support options based on the user's needs and emotional state. Database query techniques are utilized in this step to ensure efficient searching.

[0194] Step 6:

[0195] The server automatically generates the necessary documentation related to the proposed functionality. Using a digital document generation library, it creates the forms and instructions required to implement the service and outputs them as formatted electronic documents for the user.

[0196] Step 7:

[0197] The server sends proposed functions and related materials to the terminal. The terminal receives these and displays them visualized on the user interface. The user can then view the details of the functions on the screen and proceed with the necessary procedures.

[0198] Step 8:

[0199] Users input feedback and send it to the server via their device. This feedback information is analyzed on the server to improve the user experience and is used for future feature improvements. The feedback is collected in text format as user ratings and impressions.

[0200] (Application Example 2)

[0201] 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".

[0202] In recent years, the variety and content of services in the fields of elderly care and welfare have become so diverse that it is difficult to receive proposals that are tailored to individual needs. Furthermore, the lack of personalized service provision that takes into account the psychological state of users is a significant challenge. Additionally, the time and effort required to generate and manage the necessary documents and information for procedures places a heavy burden on users.

[0203] 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.

[0204] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching for and proposing appropriate public services from an information storage unit based on the analysis results, and means for integrating an emotion recognition engine that analyzes the user's psychological state. As a result, users can receive suggestions for care and welfare services that are tailored to their individual needs, and furthermore, detailed support tailored to their psychological state is provided, thereby reducing the burden on the user.

[0205] "Input information" refers to data obtained from user submissions and can take various forms, such as audio and text.

[0206] "Means of analysis" refer to methods and devices for processing input information and understanding its content.

[0207] "Public services" are services provided by government and welfare agencies that individuals and families use to improve their quality of life.

[0208] An "information storage unit" is a recording medium or database for storing data, and it stores the information necessary for the proposed service.

[0209] An "emotion recognition engine" is software or a program that analyzes emotions from user input information and estimates their psychological state.

[0210] "Proposed means" refers to methods and devices for presenting users with the most suitable public services based on the analyzed information.

[0211] A "guideline" is a set of instructions that outlines the necessary steps and methods for carrying out a procedure.

[0212] The system implementing this invention primarily operates through the cooperation of three parties: a server, a terminal, and a user. Details are provided below.

[0213] The server receives input information sent by the user. If the user uses voice input, the server converts the voice information into text using the terminal's speech recognition technology (e.g., Google Cloud Speech-to-Text). The converted text information is then analyzed using a natural language processing library on the server (e.g., NLTK or spaCy). During the analysis process, an emotion recognition engine (e.g., IBM Watson® Tone Analyzer) is used to estimate the user's psychological state.

[0214] Based on the analysis results, the server searches for appropriate public services from its information storage and makes suggestions to the user. This search process takes into account the user's psychological state and adjusts the priority of the suggested services as needed. The generated suggestions include a function to automatically generate necessary information documents related to the relevant service.

[0215] Regarding the acquisition and processing of feedback, user evaluations are received via terminals and stored and analyzed on the server. This allows the system to strive to improve the quality of the public services it provides. For example, if a user inputs "I'm having trouble with the procedures for long-term care recently," the system can automatically generate the necessary documents and provide related suggestions such as home care services and counseling.

[0216] An example of a prompt for a generative AI model is: "Create an assistant that can provide advice on caregiving. Analyze the user's emotions from the content of the consultation and suggest appropriate welfare services." This prompt is referenced during system development and testing.

[0217] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0218] Step 1:

[0219] The user inputs their inquiry using a device. If the user inputs by voice, the device uses speech recognition technology to convert the voice information into text. At this stage, the input is either voice or text information, and the output is text information.

[0220] Step 2:

[0221] The terminal sends the converted text information to the server. In this step, data transfer from the terminal to the server takes place. The input is text information, and the output is the status of completion of transmission to the server.

[0222] Step 3:

[0223] The server analyzes the received text information using a natural language processing library. Specifically, it extracts keywords related to the user's needs from the text information. The input for this step is the text information, and the output is the analyzed keywords and needs information.

[0224] Step 4:

[0225] The server uses an emotion recognition engine to analyze the user's psychological state. The emotion recognition engine estimates the psychological state based on text information and provides the result. The input is the analyzed text information, and the output is the evaluation result of the emotional state.

[0226] Step 5:

[0227] The server searches for appropriate public services from its internal information storage. The search considers analysis results and sentiment evaluations to provide optimal suggestions. The input at this stage is the user's needs and sentiment evaluation results, and the output is a list of suggested public services.

[0228] Step 6:

[0229] The server automatically generates the necessary information documents and prepares to notify the user. The input is the proposed public service information, and the output is the automatically generated information document. The server then prepares to send this back to the terminal.

[0230] Step 7:

[0231] Users can receive suggested service details through their device and provide feedback. Sending this feedback to the server helps improve the quality of the service. The input is the user's feedback information, and the output is the feedback reception status.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] [Second Embodiment]

[0236] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0237] 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.

[0238] 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).

[0239] 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.

[0240] 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.

[0241] 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).

[0242] 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.

[0243] 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.

[0244] 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.

[0245] 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.

[0246] 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.

[0247] 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".

[0248] The system of the present invention is designed to allow users to confidently discuss personal problems and anxieties, and to receive suggestions and procedural support for the most suitable administrative and welfare services. The following describes embodiments for carrying out the present invention.

[0249] Users input their inquiries in text or voice format via their device. The device sends this input data to the server. The server analyzes the received data using semantic analysis and natural language processing techniques to identify the user's needs and problems.

[0250] After the analysis is complete, the server consults its internal database to find the most suitable administrative and welfare services for the user. This process includes an algorithm that considers evaluation parameters such as service effectiveness and usability to select the optimal service.

[0251] Next, the server sends information to the terminal to notify the user of the proposed service. The terminal displays this information to the user, presenting the specific service details and usage procedures. In some cases, the server can also automatically generate and provide the user with any necessary documents related to the proposed service.

[0252] Furthermore, the server periodically accesses external databases to obtain the latest information on administrative and welfare services. This ensures that the system always maintains and provides users with the most up-to-date information.

[0253] When a user provides feedback on the usefulness of the information and services provided, the device sends this feedback to the server. The server uses the received feedback to improve the system and provide better services.

[0254] As a concrete example, consider a case where a user seeks advice regarding family care. The server searches its database for care-related services and suggests options such as "community-based integrated care centers" and the "long-term care insurance system." It then automatically generates the necessary application documents, supporting the user in smoothly completing the process.

[0255] Thus, the system of the present invention aims to provide prompt and accurate support for various problems faced by users.

[0256] The following describes the processing flow.

[0257] Step 1:

[0258] The user enters their inquiry into the device as text or voice. Let's assume the user enters "I want to know about support regarding caring for my parents."

[0259] Step 2:

[0260] The terminal receives data entered by the user and sends it to the server. In the case of voice data, speech recognition technology is used beforehand to convert it to text.

[0261] Step 3:

[0262] The server processes the received text data for semantic analysis and extracts keywords related to elderly care. This analysis identifies the type of service the user needs.

[0263] Step 4:

[0264] The server consults its internal database to find the administrative and welfare services best suited to the user's needs. For example, it might suggest access to a "community-based integrated care center" or the "long-term care insurance system."

[0265] Step 5:

[0266] The server automatically generates the necessary documents from templates based on the proposed service. These documents are required for the user to submit when receiving care services.

[0267] Step 6:

[0268] The server sends the search results and automatically generated documents to the user's device to notify them.

[0269] Step 7:

[0270] The terminal displays information received from the server to the user, providing access to specific service proposals and generated documents.

[0271] Step 8:

[0272] The user either proceeds with the procedure according to the suggestion, or enters feedback on the device if further assistance is needed.

[0273] Step 9:

[0274] The device receives feedback from users and sends it to the server. This allows the server to use the feedback to improve the services it provides.

[0275] This ensures users receive consistent support and promotes the use of appropriate services.

[0276] (Example 1)

[0277] 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."

[0278] In modern society, there is a need to quickly and accurately propose appropriate public services and support to address the diverse problems individuals face. Furthermore, since information is updated daily, it is necessary to always provide the latest service information. However, doing this manually is inefficient and can lead to individual inconsistencies. Moreover, the lack of opportunities for users to provide feedback on the services they receive, and the insufficient mechanisms for using that information to improve the system, makes it difficult to provide sophisticated support.

[0279] 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.

[0280] In this invention, the server includes means for receiving and analyzing input information from a user, means for searching and proposing appropriate public services from a knowledge base based on the analysis result, and means for automatically generating necessary information related to the proposed public services. Thereby, it is possible to always provide the user with the latest and optimal service information and to support rapid problem-solving.

[0281] The "input information" is data in the form of text or voice obtained from the user and includes individual problems and consultation contents.

[0282] "Analysis" is a process of analyzing the received input information using semantic analysis and natural language processing techniques to identify the user's needs and problems.

[0283] The "public service" refers to administrative services and welfare services provided by government agencies and related organizations and includes specific support available to users for problem-solving.

[0284] How to translate this sentence? Please provide more context or clarify the specific requirements. The "knowledge base" is a dataset that systematically organizes information about proposed public services and can be searched and referenced as needed.

[0285] "Automatic generation" refers to a process of generating necessary information and documents without human intervention by a program, which supports the user's specific procedures.

[0286] The "external information source" refers to databases and information-providing services outside the system and can be referenced to obtain always-updated information.

[0287] "Feedback" refers to comments and opinions regarding the usefulness and satisfaction of the proposed service by the user, which are utilized for system improvement.

[0288] The "voice information" refers to data in the form of voice obtained from the user and includes information input by voice regarding consultation contents. It should be noted that for the part marked with a question mark in the translation, more context is needed to accurately translate it.

[0289] "Text information" refers to data in text format that has been converted by speech recognition, and is the subject of analysis.

[0290] "Latest service information" refers to the most up-to-date information on administrative and welfare services, and represents the current information that should be provided to users.

[0291] The system of this invention helps users to access appropriate public services more effectively. Based on information entered by the user via a terminal, the system selects and provides suggested services using a variety of technologies.

[0292] First, the user enters their inquiry details using text or voice via their device. If voice information is entered, the device uses a speech recognition engine to convert the voice to text. While general speech recognition software is used for this purpose, a specific example is the Google Speech-to-Text API.

[0293] Next, the server receives the text information sent from the terminal and analyzes it using semantic analysis and natural language processing. Natural language processing libraries such as "spaCy" and "NLTK" can be used for this analysis. This helps identify the user's needs and problems.

[0294] The server searches its internal knowledge base based on the analysis results. This knowledge base organizes information on various public services and includes data for recommending appropriate services. Algorithms utilizing machine learning libraries such as "scikit-learn" and "TensorFlow" can be applied to service selection.

[0295] Proposed public services are notified to the user via a terminal. The terminal can display this information and provide detailed guidance on the procedures and required documents for the relevant process. The server automatically generates documents as needed and helps users efficiently proceed with the process, for example, by creating PDF documents using "ReportLab".

[0296] Furthermore, the server periodically references external sources to obtain the latest service information and update its knowledge base. This ensures that users are always provided with the most up-to-date information.

[0297] When a user provides feedback on a service they have used, the terminal transmits this feedback to the server. The server then uses this feedback to improve the system and enhance the quality of public services provided. An example of a specific prompt would be: "Please describe a system that analyzes a user's inquiry in natural language and suggests appropriate welfare services."

[0298] This system is designed to be an essential support for users, helping them access public services quickly and reliably.

[0299] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0300] Step 1:

[0301] The user enters their consultation details via a terminal. The input format is either text or voice. At this stage, the input is raw information from the user. If voice input is received, the terminal uses a speech recognition engine to convert the voice information into text information. Through this conversion process, the user's consultation details are standardized into text format and sent to the server.

[0302] Step 2:

[0303] The server receives the text information sent from the terminal. It performs semantic analysis and natural language processing on the received text data. By using libraries such as "spaCy" and "NLTK" for this processing, the problems and needs of the user are identified. As the output of the analysis, keywords and problem categories are obtained.

[0304] Step 3:

[0305] The server searches the internal knowledge base based on the analysis results. The knowledge base is a database containing detailed information on public services. In this search operation, the server uses machine learning techniques to select appropriate services. Thereby, a list of services corresponding to the user's needs is output.

[0306] Step 4:

[0307] The server sends the selected service information to the terminal. The terminal displays the received information to the user and conveys the specific service content along with the details of the related procedures. As a specific example, information on "Long-Term Care Insurance System" and "Regional Medical Support Center" is displayed. The output of this step is the detailed information of the displayable services.

[0308] Step 5:

[0309] [[ID=​​​​​​​​​​ Step 7:

[0313] Users provide feedback on the services offered through their devices. This feedback information is sent from the device to the server. The server analyzes the received feedback and uses it to improve the system. The results of this analysis improve the accuracy of future service proposals.

[0314] (Application Example 1)

[0315] 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."

[0316] A challenge exists in that users lack quick and accurate means of accessing the latest public services available to resolve personal problems, and the procedures for doing so are often cumbersome, resulting in ineffective support. This invention aims to improve this situation and enable users to easily find and smoothly utilize the services they need.

[0317] 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.

[0318] In this invention, the server includes means for receiving input information from the user and analyzing that information, means for searching for and proposing the most suitable public service from a data storage device, and means for referring to an external data storage device and periodically updating the information. This makes it possible for users to quickly search for public services that match their needs and to easily perform the detailed procedures.

[0319] A "user" refers to an individual or organization that uses the system to seek advice and receive suggestions for the most suitable public services.

[0320] "Input information" refers to data such as text and audio that users provide to the system in order to resolve their own problems or concerns.

[0321] "Means of analysis" refers to the technical process of analyzing received input information to identify user needs and challenges.

[0322] "Public services" refer to services provided by government agencies and related organizations, including the support and procedures necessary to resolve the individual problems of users.

[0323] A "data storage device" refers to a database or other storage means that a system accesses, searches for, and stores information.

[0324] "Means of automatic generation" refers to the process by which a system automatically creates necessary records and procedures and provides them to the user.

[0325] An "external data storage device" refers to an external database or information source that a system references to periodically update its information.

[0326] "Feedback" refers to evaluations and opinions provided by users regarding the usefulness of proposed services or procedures.

[0327] "Mobile information terminals" refer to information processing devices that can be used while on the go, such as mobile phones and tablets.

[0328] This invention comprises a system used via a smartphone or other mobile information terminal. The user inputs their problems or anxieties into the terminal as text or voice. The terminal sends this input information to a server in the cloud, where it is analyzed using semantic analysis and natural language processing techniques. This process utilizes Python and the natural language processing library SpaCy, or the Google Cloud Natural Language API.

[0329] Based on the analysis results, the server identifies the most suitable public services from the data storage device and proposes them to the user. The service selection uses algorithms that consider effectiveness and usability. The server then automatically generates and provides the user with the necessary materials related to the proposed service. This functionality is implemented using cloud services such as AWS or GCP.

[0330] Furthermore, the server periodically references an external data storage device to obtain the latest information on public services and update the database. This ensures that users are always provided with the most up-to-date service information. The system also includes a feature that allows users to easily select specific public services and download relevant materials using their smartphones.

[0331] As a concrete example, consider a user who "wants advice about using day care services for their elderly parent." The server analyzes the user's inquiry and presents a list of local day care facilities. It provides the user with detailed information, including ratings and fees, and automatically generates and makes available for download the necessary application documents for the selected facility.

[0332] An example of a prompt message to provide to the generating AI model is: "Please enter your concerns regarding caregiving. For example, regarding the selection of a care facility or the procedures for long-term care insurance. We will suggest the most suitable care services."

[0333] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0334] Step 1:

[0335] The user uses a smartphone or mobile device to input their consultation details in text or voice format. This input data is temporarily stored on the device and prepared to be sent to the server for analysis. In the case of voice input, the device converts the input voice into text data. Input: User's consultation details (text / voice). Output: Text data ready to be sent to the server.

[0336] Step 2:

[0337] The server analyzes text data received from the terminal. Here, the server uses natural language processing techniques to semantically analyze the input data in order to understand the user's needs and problems. The analysis uses Python and either SpaCy or the Google Cloud Natural Language API. Input: Text data. Output: Analysis results (user needs).

[0338] Step 3:

[0339] Based on the analysis results, the server searches for the most suitable public services from the data storage device. The search uses an algorithm that considers service content, effectiveness, and availability to find the optimal solution to the user's specific problem. Input: Analysis results. Output: List of optimal public services.

[0340] Step 4:

[0341] The server automatically generates the necessary documents related to the selected public service. This allows users to smoothly proceed with applying for and using the service. This document generation and management are handled using AWS or GCP cloud services. Input: List of optimal public services. Output: Required documents.

[0342] Step 5:

[0343] The server periodically updates its database by referencing an external data storage device to maintain the latest public service information. This process ensures that the information provided to users is always up-to-date. Input: External data. Output: Updated internal database.

[0344] Step 6:

[0345] The user uses their smartphone to view information on the most suitable public services presented by the server and download the necessary documents. This process makes it easy for the user to select services and complete procedures. Input: Service information from the server. Output: Procedure documents available to the user.

[0346] 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.

[0347] This invention allows users to input their consultation details through a system, which then proposes appropriate administrative and welfare services, automatically generates necessary documents, and provides support for procedures. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, the aim is to provide a more personalized service.

[0348] Users input their consultation details using their device. If the user inputs by voice, the data is converted into text using speech recognition technology on the device. The device then sends the data to the server.

[0349] When the server analyzes the received data, it first performs semantic analysis to extract the user's needs. This process incorporates an emotion engine that can detect the user's emotional state based on the content of the text data. For example, if the text contains many keywords such as "anxiety" or "worry," the server will recognize the user's emotion as "anxiety."

[0350] Next, the server searches its internal database for appropriate administrative and welfare services based on the analyzed data. During this process, it can adjust the suggested services based on the user's emotional assessment. For example, for a user experiencing anxiety, it prioritizes suggesting services with more comprehensive support or those that include emotional care.

[0351] The server automatically generates the necessary documents related to the proposed service and prepares to notify the user. This allows the user to proceed with the process smoothly.

[0352] Once the proposal is finalized, the server sends this information to the terminal. The terminal displays the information to the user, providing details about the proposed service, instructions for using it, and how to access the generated documents.

[0353] Finally, users are allowed to provide feedback on the usefulness of the information and services, and this data is sent from the device to the server. By receiving user feedback, the server continuously improves the quality of the services provided.

[0354] For example, if a user enters "I'm worried about caring for a family member," the server will suggest caregiving-related support services and also offer counseling services to alleviate the user's anxiety. In this way, personalized support is achieved.

[0355] The following describes the processing flow.

[0356] Step 1:

[0357] Users use their devices to input their concerns as text or voice. For example, they might type, "I'm worried about caring for my parents."

[0358] Step 2:

[0359] The terminal receives the input data. In the case of voice data, it uses speech recognition technology to convert it into text data. The converted text data is then sent to the server.

[0360] Step 3:

[0361] The server analyzes the received text data. Using a semantic analysis engine, it extracts keywords present in the consultation content and determines the user's needs.

[0362] Step 4:

[0363] The server's emotion engine recognizes the user's emotions from extracted keywords and sentence structure. In this case, it recognizes the user's emotion as "anxiety" based on words such as "anxiety" and "worry."

[0364] Step 5:

[0365] Based on the results of analysis and emotion recognition, the server searches its internal database for appropriate administrative and welfare services. Options include "care consultation services" and "mental health counseling."

[0366] Step 6:

[0367] The server automatically generates the necessary documents for the proposed service, such as application forms for care support and appointment forms for counseling.

[0368] Step 7:

[0369] The server sends the selected service information to the terminal along with the generated document. This includes specific service details and usage instructions.

[0370] Step 8:

[0371] The device displays the received information to the user. The screen shows an overview and links to each suggested service, as well as options for downloading documents.

[0372] Step 9:

[0373] Users review the proposed information and procedures and enter feedback into their device. For example, they might describe their satisfaction with the proposal or their progress in using the service.

[0374] Step 10:

[0375] The device sends user feedback to the server. This information is used as data to improve the quality of the service.

[0376] Through these steps, users will be able to receive more appropriate and personalized assistance for their problems.

[0377] (Example 2)

[0378] 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".

[0379] In modern society, users face the challenge of obtaining appropriate advice and services for the various problems they encounter. Furthermore, there is a demand for highly personalized services that respond to users' emotions and needs, as well as for efficient processing of necessary procedures. Conventional systems suffer from insufficient consideration of user emotions in service suggestions and continuous improvement through the use of feedback.

[0380] 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.

[0381] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching for and proposing appropriate functions from information sources based on the analysis results, and means for determining the user's emotional state using an emotion analysis engine. This makes it possible to propose services that meet the individual needs and emotional state of the user, thereby realizing efficient and personalized support.

[0382] "Input information" refers to data that a user provides to the system, including in various formats such as audio and text.

[0383] "Analysis" is the process of analyzing received information to understand the user's needs and emotional state.

[0384] A "function" refers to a specific service or action that provides the advice and support that the user is looking for.

[0385] "Information sources" refer to a collection of databases and resources used to search for appropriate features to suggest to users.

[0386] "Required documents" refer to automatically generated documents and forms that are necessary for users to proceed with the proposed functionality.

[0387] An "emotion analysis engine" is a general term for technologies and algorithms used to determine an emotional state based on user input.

[0388] "Personalized support" means providing services that are customized to the specific needs and emotions of each individual user.

[0389] This invention is a system consisting of a user terminal and a server equipped with multiple data analysis means.

[0390] Users can use a terminal to provide their consultation details either by typing or by voice. In the case of voice input, the terminal uses speech recognition technology to convert the content into text data. The terminal incorporates commonly used speech recognition software and employs a device capable of converting speech to text in real time.

[0391] The terminal sends the received text data to the server. The server analyzes the received data using advanced natural language processing technology. In particular, it uses a generative AI model to extract the user's intentions and the support they need from the data, and also uses an emotion analysis engine to determine the user's emotional state. This makes it possible to suggest appropriate functions that meet the user's needs.

[0392] The server has the capability to automatically generate materials related to the proposed functionality, providing users with the documents and instructions they need immediately. Accordingly, it regularly references external sources to update information and ensure that it always provides the latest data. Digital document generation technology is utilized in this process.

[0393] The terminal displays information received from the server to the user and provides instructions on how to use the suggested functions and related materials. Finally, the user enters feedback on the usefulness of the service, and this data is sent to the server, contributing to the improvement of the entire system.

[0394] For example, if a user enters a prompt message such as, "I would like to seek advice regarding domestic stress and find out what kind of support I can receive," the server can suggest stress-related counseling services and introduce activities that are effective in reducing stress. Providing individually customized support to the user in this way is a key feature of the present invention.

[0395] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0396] Step 1:

[0397] The user enters their consultation details using a device. The input is provided in either text or voice format. In the case of voice input, the device uses speech recognition technology to convert the voice data into text data. This results in the user's intended consultation content being output as text. Specifically, the speech recognition engine analyzes the input voice waveform and converts it into a string based on a language model.

[0398] Step 2:

[0399] The terminal sends the converted text data to the server. The text data is transferred to the server via network communication. A secure protocol (e.g., HTTPS) is typically used for this communication. The terminal divides the data into packets and sends them sequentially to the server.

[0400] Step 3:

[0401] The server analyzes the received text data. First, it performs semantic analysis using natural language processing techniques to extract the meaning of the text and the user's needs. This analysis utilizes generative AI models to deepen contextual understanding. In this process, it identifies specific keywords and phrases from the input text and clarifies the user's requests.

[0402] Step 4:

[0403] The server uses an emotion analysis engine to determine the user's emotional state. It analyzes emotional patterns from vocabulary and expressions within text data and outputs emotions such as "anxiety" or "happiness." Emotion analysis is achieved using emotion dictionaries and machine learning models.

[0404] Step 5:

[0405] Based on the analysis results, the server searches for and proposes appropriate functions from internal sources. The function suggestion system selects and outputs a list of the most suitable support options based on the user's needs and emotional state. Database query techniques are utilized in this step to ensure efficient searching.

[0406] Step 6:

[0407] The server automatically generates the necessary documentation related to the proposed functionality. Using a digital document generation library, it creates the forms and instructions required to implement the service and outputs them as formatted electronic documents for the user.

[0408] Step 7:

[0409] The server sends proposed functions and related materials to the terminal. The terminal receives these and displays them visualized on the user interface. The user can then view the details of the functions on the screen and proceed with the necessary procedures.

[0410] Step 8:

[0411] Users input feedback and send it to the server via their device. This feedback information is analyzed on the server to improve the user experience and is used for future feature improvements. The feedback is collected in text format as user ratings and impressions.

[0412] (Application Example 2)

[0413] 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."

[0414] In recent years, the variety and content of services in the fields of elderly care and welfare have become so diverse that it is difficult to receive proposals that are tailored to individual needs. Furthermore, the lack of personalized service provision that takes into account the psychological state of users is a significant challenge. Additionally, the time and effort required to generate and manage the necessary documents and information for procedures places a heavy burden on users.

[0415] 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.

[0416] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching for and proposing appropriate public services from an information storage unit based on the analysis results, and means for integrating an emotion recognition engine that analyzes the user's psychological state. As a result, users can receive suggestions for care and welfare services that are tailored to their individual needs, and furthermore, detailed support tailored to their psychological state is provided, thereby reducing the burden on the user.

[0417] "Input information" refers to data obtained from user submissions and can take various forms, such as audio and text.

[0418] "Means of analysis" refer to methods and devices for processing input information and understanding its content.

[0419] "Public services" are services provided by government and welfare agencies that individuals and families use to improve their quality of life.

[0420] An "information storage unit" is a recording medium or database for storing data, and it stores the information necessary for the proposed service.

[0421] An "emotion recognition engine" is software or a program that analyzes emotions from user input information and estimates their psychological state.

[0422] "Proposed means" refers to methods and devices for presenting users with the most suitable public services based on the analyzed information.

[0423] A "guideline" is a set of instructions that outlines the necessary steps and methods for carrying out a procedure.

[0424] The system implementing this invention primarily operates through the cooperation of three parties: a server, a terminal, and a user. Details are provided below.

[0425] The server receives input information sent by the user. If the user uses voice input, the server converts the voice information into text using the terminal's speech recognition technology (e.g., Google Cloud Speech-to-Text). The converted text information is then analyzed using a natural language processing library on the server (e.g., NLTK or spaCy). During the analysis process, an emotion recognition engine (e.g., IBM Watson Tone Analyzer) is used to estimate the user's psychological state.

[0426] Based on the analysis results, the server searches for appropriate public services from its information storage and makes suggestions to the user. This search process takes into account the user's psychological state and adjusts the priority of the suggested services as needed. The generated suggestions include a function to automatically generate necessary information documents related to the relevant service.

[0427] Regarding the acquisition and processing of feedback, user evaluations are received via terminals and stored and analyzed on the server. This allows the system to strive to improve the quality of the public services it provides. For example, if a user inputs "I'm having trouble with the procedures for long-term care recently," the system can automatically generate the necessary documents and provide related suggestions such as home care services and counseling.

[0428] An example of a prompt for a generative AI model is: "Create an assistant that can provide advice on caregiving. Analyze the user's emotions from the content of the consultation and suggest appropriate welfare services." This prompt is referenced during system development and testing.

[0429] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0430] Step 1:

[0431] The user inputs their inquiry using a device. If the user inputs by voice, the device uses speech recognition technology to convert the voice information into text. At this stage, the input is either voice or text information, and the output is text information.

[0432] Step 2:

[0433] The terminal sends the converted text information to the server. In this step, data transfer from the terminal to the server takes place. The input is text information, and the output is the status of completion of transmission to the server.

[0434] Step 3:

[0435] The server analyzes the received text information using a natural language processing library. Specifically, it extracts keywords related to the user's needs from the text information. The input for this step is the text information, and the output is the analyzed keywords and needs information.

[0436] Step 4:

[0437] The server uses an emotion recognition engine to analyze the user's psychological state. The emotion recognition engine estimates the psychological state based on text information and provides the result. The input is the analyzed text information, and the output is the evaluation result of the emotional state.

[0438] Step 5:

[0439] The server searches for appropriate public services from its internal information storage. The search considers analysis results and sentiment evaluations to provide optimal suggestions. The input at this stage is the user's needs and sentiment evaluation results, and the output is a list of suggested public services.

[0440] Step 6:

[0441] The server automatically generates the necessary information documents and prepares to notify the user. The input is the proposed public service information, and the output is the automatically generated information document. The server then prepares to send this back to the terminal.

[0442] Step 7:

[0443] Users can receive suggested service details through their device and provide feedback. Sending this feedback to the server helps improve the quality of the service. The input is the user's feedback information, and the output is the feedback reception status.

[0444] 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.

[0445] 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.

[0446] 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.

[0447] [Third Embodiment]

[0448] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0449] 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.

[0450] 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).

[0451] 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.

[0452] 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.

[0453] 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).

[0454] 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.

[0455] 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.

[0456] 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.

[0457] 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.

[0458] 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.

[0459] 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".

[0460] The system of the present invention is designed to allow users to confidently discuss personal problems and anxieties, and to receive suggestions and procedural support for the most suitable administrative and welfare services. The following describes embodiments for carrying out the present invention.

[0461] Users input their inquiries in text or voice format via their device. The device sends this input data to the server. The server analyzes the received data using semantic analysis and natural language processing techniques to identify the user's needs and problems.

[0462] After the analysis is complete, the server consults its internal database to find the most suitable administrative and welfare services for the user. This process includes an algorithm that considers evaluation parameters such as service effectiveness and usability to select the optimal service.

[0463] Next, the server sends information to the terminal to notify the user of the proposed service. The terminal displays this information to the user, presenting the specific service details and usage procedures. In some cases, the server can also automatically generate and provide the user with any necessary documents related to the proposed service.

[0464] Furthermore, the server periodically accesses external databases to obtain the latest information on administrative and welfare services. This ensures that the system always maintains and provides users with the most up-to-date information.

[0465] When a user provides feedback on the usefulness of the information and services provided, the device sends this feedback to the server. The server uses the received feedback to improve the system and provide better services.

[0466] As a concrete example, consider a case where a user seeks advice regarding family care. The server searches its database for care-related services and suggests options such as "community-based integrated care centers" and the "long-term care insurance system." It then automatically generates the necessary application documents, supporting the user in smoothly completing the process.

[0467] Thus, the system of the present invention aims to provide prompt and accurate support for various problems faced by users.

[0468] The following describes the processing flow.

[0469] Step 1:

[0470] The user enters their inquiry into the device as text or voice. Let's assume the user enters "I want to know about support regarding caring for my parents."

[0471] Step 2:

[0472] The terminal receives data entered by the user and sends it to the server. In the case of voice data, speech recognition technology is used beforehand to convert it to text.

[0473] Step 3:

[0474] The server processes the received text data for semantic analysis and extracts keywords related to elderly care. This analysis identifies the type of service the user needs.

[0475] Step 4:

[0476] The server consults its internal database to find the administrative and welfare services best suited to the user's needs. For example, it might suggest access to a "community-based integrated care center" or the "long-term care insurance system."

[0477] Step 5:

[0478] The server automatically generates the necessary documents from templates based on the proposed service. These documents are required for the user to submit when receiving care services.

[0479] Step 6:

[0480] The server sends the search results and automatically generated documents to the user's device to notify them.

[0481] Step 7:

[0482] The terminal displays information received from the server to the user, providing access to specific service proposals and generated documents.

[0483] Step 8:

[0484] The user either proceeds with the procedure according to the suggestion, or enters feedback on the device if further assistance is needed.

[0485] Step 9:

[0486] The device receives feedback from users and sends it to the server. This allows the server to use the feedback to improve the services it provides.

[0487] This ensures users receive consistent support and promotes the use of appropriate services.

[0488] (Example 1)

[0489] 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."

[0490] In modern society, there is a need to quickly and accurately propose appropriate public services and support to address the diverse problems individuals face. Furthermore, since information is updated daily, it is necessary to always provide the latest service information. However, doing this manually is inefficient and can lead to individual inconsistencies. Moreover, the lack of opportunities for users to provide feedback on the services they receive, and the insufficient mechanisms for using that information to improve the system, makes it difficult to provide sophisticated support.

[0491] 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.

[0492] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching a knowledge base for and proposing appropriate public services based on the analysis results, and means for automatically generating necessary information related to the proposed public services. This enables the user to always receive the latest and most optimal service information and to receive rapid problem-solving support.

[0493] "Input information" refers to data obtained from the user in text or audio format, including individual problems and consultation details.

[0494] "Analysis" is the process of analyzing received input information using semantic analysis and natural language processing techniques to identify user needs and problems.

[0495] "Public services" refer to administrative and welfare services provided by government agencies and related organizations, and include specific support available to users to solve problems.

[0496] A "knowledge base" is a dataset that systematically organizes information about possible public services and allows for searching and referencing as needed.

[0497] "Automatic generation" refers to the process of generating necessary information and documents using a program without human intervention, thereby supporting the user's specific procedures.

[0498] "External information sources" refer to databases and information services outside the system that can be referenced to obtain the latest information at all times.

[0499] "Feedback" refers to comments and opinions made by users regarding the usefulness and satisfaction level of the proposed service, and is used to improve the system.

[0500] "Voice information" refers to data in audio format obtained from users, including information entered via voice regarding the content of the consultation.

[0501] "Text information" refers to data in text format that has been converted by speech recognition, and is the subject of analysis.

[0502] "Latest service information" refers to the most up-to-date information on administrative and welfare services, and represents the current information that should be provided to users.

[0503] The system of this invention helps users to access appropriate public services more effectively. Based on information entered by the user via a terminal, the system selects and provides suggested services using a variety of technologies.

[0504] First, the user enters their inquiry details using text or voice via their device. If voice information is entered, the device uses a speech recognition engine to convert the voice to text. While general speech recognition software is used for this purpose, a specific example is the Google Speech-to-Text API.

[0505] Next, the server receives the text information sent from the terminal and analyzes it using semantic analysis and natural language processing. Natural language processing libraries such as "spaCy" and "NLTK" can be used for this analysis. This helps identify the user's needs and problems.

[0506] The server searches its internal knowledge base based on the analysis results. This knowledge base organizes information on various public services and includes data for recommending appropriate services. Algorithms utilizing machine learning libraries such as "scikit-learn" and "TensorFlow" can be applied to service selection.

[0507] Proposed public services are notified to the user via a terminal. The terminal can display this information and provide detailed guidance on the procedures and required documents for the relevant process. The server automatically generates documents as needed and helps users efficiently proceed with the process, for example, by creating PDF documents using "ReportLab".

[0508] Furthermore, the server periodically references external sources to obtain the latest service information and update its knowledge base. This ensures that users are always provided with the most up-to-date information.

[0509] When a user provides feedback on a service they have used, the terminal transmits this feedback to the server. The server then uses this feedback to improve the system and enhance the quality of public services provided. An example of a specific prompt would be: "Please describe a system that analyzes a user's inquiry in natural language and suggests appropriate welfare services."

[0510] This system is designed to be an essential support for users, helping them access public services quickly and reliably.

[0511] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0512] Step 1:

[0513] The user enters their consultation details via a terminal. The input format is either text or voice. At this stage, the input is raw information from the user. If voice input is received, the terminal uses a speech recognition engine to convert the voice information into text information. Through this conversion process, the user's consultation details are standardized into text format and sent to the server.

[0514] Step 2:

[0515] The server receives text information sent from the terminal. The received text data is subjected to semantic analysis and natural language processing. This processing uses libraries such as "spaCy" and "NLTK" to identify the user's problems and needs. The analysis output provides keywords and problem categories.

[0516] Step 3:

[0517] The server searches its internal knowledge base based on the analysis results. This knowledge base is a database containing detailed information about public services. During this search, the server uses machine learning techniques to select the appropriate services. As a result, a list of services that meet the user's needs is output.

[0518] Step 4:

[0519] The server sends the selected service information to the terminal. The terminal displays the received information to the user, conveying the specific service content along with details of the related procedures. For example, information on the "Long-Term Care Insurance System" and "Regional Medical Support Center" may be displayed. The output of this step is detailed information about the services that can be displayed.

[0520] Step 5:

[0521] The server automatically generates the information required for the proposed service. It uses libraries such as "ReportLab" to generate the necessary documents in PDF format. This process outputs instructions for the next steps the user should take.

[0522] Step 6:

[0523] The server periodically references external data sources to update its knowledge base. This ensures that the latest administrative and welfare service information is obtained and reflected in the system. References to external data update the knowledge base, establishing a foundation for providing up-to-date information.

[0524] Step 7:

[0525] Users provide feedback on the services offered through their devices. This feedback information is sent from the device to the server. The server analyzes the received feedback and uses it to improve the system. The results of this analysis improve the accuracy of future service proposals.

[0526] (Application Example 1)

[0527] 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."

[0528] A challenge exists in that users lack quick and accurate means of accessing the latest public services available to resolve personal problems, and the procedures for doing so are often cumbersome, resulting in ineffective support. This invention aims to improve this situation and enable users to easily find and smoothly utilize the services they need.

[0529] 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.

[0530] In this invention, the server includes means for receiving input information from the user and analyzing that information, means for searching for and proposing the most suitable public service from a data storage device, and means for referring to an external data storage device and periodically updating the information. This makes it possible for users to quickly search for public services that match their needs and to easily perform the detailed procedures.

[0531] A "user" refers to an individual or organization that uses the system to seek advice and receive suggestions for the most suitable public services.

[0532] "Input information" refers to data such as text and audio that users provide to the system in order to resolve their own problems or concerns.

[0533] "Means of analysis" refers to the technical process of analyzing received input information to identify user needs and challenges.

[0534] "Public services" refer to services provided by government agencies and related organizations, including the support and procedures necessary to resolve the individual problems of users.

[0535] A "data storage device" refers to a database or other storage means that a system accesses, searches for, and stores information.

[0536] "Means of automatic generation" refers to the process by which a system automatically creates necessary records and procedures and provides them to the user.

[0537] An "external data storage device" refers to an external database or information source that a system references to periodically update its information.

[0538] "Feedback" refers to evaluations and opinions provided by users regarding the usefulness of proposed services or procedures.

[0539] "Mobile information terminals" refer to information processing devices that can be used while on the go, such as mobile phones and tablets.

[0540] This invention comprises a system used via a smartphone or other mobile information terminal. The user inputs their problems or anxieties into the terminal as text or voice. The terminal sends this input information to a server in the cloud, where it is analyzed using semantic analysis and natural language processing techniques. This process utilizes Python and the natural language processing library SpaCy, or the Google Cloud Natural Language API.

[0541] Based on the analysis results, the server identifies the most suitable public services from the data storage device and proposes them to the user. The service selection uses algorithms that consider effectiveness and usability. The server then automatically generates and provides the user with the necessary materials related to the proposed service. This functionality is implemented using cloud services such as AWS or GCP.

[0542] Furthermore, the server periodically references an external data storage device to obtain the latest information on public services and update the database. This ensures that users are always provided with the most up-to-date service information. The system also includes a feature that allows users to easily select specific public services and download relevant materials using their smartphones.

[0543] As a concrete example, consider a user who "wants advice about using day care services for their elderly parent." The server analyzes the user's inquiry and presents a list of local day care facilities. It provides the user with detailed information, including ratings and fees, and automatically generates and makes available for download the necessary application documents for the selected facility.

[0544] An example of a prompt message to provide to the generating AI model is: "Please enter your concerns regarding caregiving. For example, regarding the selection of a care facility or the procedures for long-term care insurance. We will suggest the most suitable care services."

[0545] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0546] Step 1:

[0547] The user uses a smartphone or mobile device to input their consultation details in text or voice format. This input data is temporarily stored on the device and prepared to be sent to the server for analysis. In the case of voice input, the device converts the input voice into text data. Input: User's consultation details (text / voice). Output: Text data ready to be sent to the server.

[0548] Step 2:

[0549] The server analyzes text data received from the terminal. Here, the server uses natural language processing techniques to semantically analyze the input data in order to understand the user's needs and problems. The analysis uses Python and either SpaCy or the Google Cloud Natural Language API. Input: Text data. Output: Analysis results (user needs).

[0550] Step 3:

[0551] Based on the analysis results, the server searches for the most suitable public services from the data storage device. The search uses an algorithm that considers service content, effectiveness, and availability to find the optimal solution to the user's specific problem. Input: Analysis results. Output: List of optimal public services.

[0552] Step 4:

[0553] The server automatically generates the necessary documents related to the selected public service. This allows users to smoothly proceed with applying for and using the service. This document generation and management are handled using AWS or GCP cloud services. Input: List of optimal public services. Output: Required documents.

[0554] Step 5:

[0555] The server periodically updates its database by referencing an external data storage device to maintain the latest public service information. This process ensures that the information provided to users is always up-to-date. Input: External data. Output: Updated internal database.

[0556] Step 6:

[0557] The user uses their smartphone to view information on the most suitable public services presented by the server and download the necessary documents. This process makes it easy for the user to select services and complete procedures. Input: Service information from the server. Output: Procedure documents available to the user.

[0558] 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.

[0559] This invention allows users to input their consultation details through a system, which then proposes appropriate administrative and welfare services, automatically generates necessary documents, and provides support for procedures. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, the aim is to provide a more personalized service.

[0560] Users input their consultation details using their device. If the user inputs by voice, the data is converted into text using speech recognition technology on the device. The device then sends the data to the server.

[0561] When the server analyzes the received data, it first performs semantic analysis to extract the user's needs. This process incorporates an emotion engine that can detect the user's emotional state based on the content of the text data. For example, if the text contains many keywords such as "anxiety" or "worry," the server will recognize the user's emotion as "anxiety."

[0562] Next, the server searches its internal database for appropriate administrative and welfare services based on the analyzed data. During this process, it can adjust the suggested services based on the user's emotional assessment. For example, for a user experiencing anxiety, it prioritizes suggesting services with more comprehensive support or those that include emotional care.

[0563] The server automatically generates the necessary documents related to the proposed service and prepares to notify the user. This allows the user to proceed with the process smoothly.

[0564] Once the proposal is finalized, the server sends this information to the terminal. The terminal displays the information to the user, providing details about the proposed service, instructions for using it, and how to access the generated documents.

[0565] Finally, users are allowed to provide feedback on the usefulness of the information and services, and this data is sent from the device to the server. By receiving user feedback, the server continuously improves the quality of the services provided.

[0566] For example, if a user enters "I'm worried about caring for a family member," the server will suggest caregiving-related support services and also offer counseling services to alleviate the user's anxiety. In this way, personalized support is achieved.

[0567] The following describes the processing flow.

[0568] Step 1:

[0569] Users use their devices to input their concerns as text or voice. For example, they might type, "I'm worried about caring for my parents."

[0570] Step 2:

[0571] The terminal receives the input data. In the case of voice data, it uses speech recognition technology to convert it into text data. The converted text data is then sent to the server.

[0572] Step 3:

[0573] The server analyzes the received text data. Using a semantic analysis engine, it extracts keywords present in the consultation content and determines the user's needs.

[0574] Step 4:

[0575] The server's emotion engine recognizes the user's emotions from extracted keywords and sentence structure. In this case, it recognizes the user's emotion as "anxiety" based on words such as "anxiety" and "worry."

[0576] Step 5:

[0577] Based on the results of analysis and emotion recognition, the server searches its internal database for appropriate administrative and welfare services. Options include "care consultation services" and "mental health counseling."

[0578] Step 6:

[0579] The server automatically generates the necessary documents for the proposed service, such as application forms for care support and appointment forms for counseling.

[0580] Step 7:

[0581] The server sends the selected service information to the terminal along with the generated document. This includes specific service details and usage instructions.

[0582] Step 8:

[0583] The device displays the received information to the user. The screen shows an overview and links to each suggested service, as well as options for downloading documents.

[0584] Step 9:

[0585] Users review the proposed information and procedures and enter feedback into their device. For example, they might describe their satisfaction with the proposal or their progress in using the service.

[0586] Step 10:

[0587] The device sends user feedback to the server. This information is used as data to improve the quality of the service.

[0588] Through these steps, users will be able to receive more appropriate and personalized assistance for their problems.

[0589] (Example 2)

[0590] 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."

[0591] In modern society, users face the challenge of obtaining appropriate advice and services for the various problems they encounter. Furthermore, there is a demand for highly personalized services that respond to users' emotions and needs, as well as for efficient processing of necessary procedures. Conventional systems suffer from insufficient consideration of user emotions in service suggestions and continuous improvement through the use of feedback.

[0592] 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.

[0593] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching for and proposing appropriate functions from information sources based on the analysis results, and means for determining the user's emotional state using an emotion analysis engine. This makes it possible to propose services that meet the individual needs and emotional state of the user, thereby realizing efficient and personalized support.

[0594] "Input information" refers to data that a user provides to the system, including in various formats such as audio and text.

[0595] "Analysis" is the process of analyzing received information to understand the user's needs and emotional state.

[0596] A "function" refers to a specific service or action that provides the advice and support that the user is looking for.

[0597] "Information sources" refer to a collection of databases and resources used to search for appropriate features to suggest to users.

[0598] "Required documents" refer to automatically generated documents and forms that are necessary for users to proceed with the proposed functionality.

[0599] An "emotion analysis engine" is a general term for technologies and algorithms used to determine an emotional state based on user input.

[0600] "Personalized support" means providing services that are customized to the specific needs and emotions of each individual user.

[0601] This invention is a system consisting of a user terminal and a server equipped with multiple data analysis means.

[0602] Users can use a terminal to provide their consultation details either by typing or by voice. In the case of voice input, the terminal uses speech recognition technology to convert the content into text data. The terminal incorporates commonly used speech recognition software and employs a device capable of converting speech to text in real time.

[0603] The terminal sends the received text data to the server. The server analyzes the received data using advanced natural language processing technology. In particular, it uses a generative AI model to extract the user's intentions and the support they need from the data, and also uses an emotion analysis engine to determine the user's emotional state. This makes it possible to suggest appropriate functions that meet the user's needs.

[0604] The server has the capability to automatically generate materials related to the proposed functionality, providing users with the documents and instructions they need immediately. Accordingly, it regularly references external sources to update information and ensure that it always provides the latest data. Digital document generation technology is utilized in this process.

[0605] The terminal displays information received from the server to the user and provides instructions on how to use the suggested functions and related materials. Finally, the user enters feedback on the usefulness of the service, and this data is sent to the server, contributing to the improvement of the entire system.

[0606] For example, if a user enters a prompt message such as, "I would like to seek advice regarding domestic stress and find out what kind of support I can receive," the server can suggest stress-related counseling services and introduce activities that are effective in reducing stress. Providing individually customized support to the user in this way is a key feature of the present invention.

[0607] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0608] Step 1:

[0609] The user enters their consultation details using a device. The input is provided in either text or voice format. In the case of voice input, the device uses speech recognition technology to convert the voice data into text data. This results in the user's intended consultation content being output as text. Specifically, the speech recognition engine analyzes the input voice waveform and converts it into a string based on a language model.

[0610] Step 2:

[0611] The terminal sends the converted text data to the server. The text data is transferred to the server via network communication. A secure protocol (e.g., HTTPS) is typically used for this communication. The terminal divides the data into packets and sends them sequentially to the server.

[0612] Step 3:

[0613] The server analyzes the received text data. First, it performs semantic analysis using natural language processing techniques to extract the meaning of the text and the user's needs. This analysis utilizes generative AI models to deepen contextual understanding. In this process, it identifies specific keywords and phrases from the input text and clarifies the user's requests.

[0614] Step 4:

[0615] The server uses an emotion analysis engine to determine the user's emotional state. It analyzes emotional patterns from vocabulary and expressions within text data and outputs emotions such as "anxiety" or "happiness." Emotion analysis is achieved using emotion dictionaries and machine learning models.

[0616] Step 5:

[0617] Based on the analysis results, the server searches for and proposes appropriate functions from internal sources. The function suggestion system selects and outputs a list of the most suitable support options based on the user's needs and emotional state. Database query techniques are utilized in this step to ensure efficient searching.

[0618] Step 6:

[0619] The server automatically generates the necessary documentation related to the proposed functionality. Using a digital document generation library, it creates the forms and instructions required to implement the service and outputs them as formatted electronic documents for the user.

[0620] Step 7:

[0621] The server sends proposed functions and related materials to the terminal. The terminal receives these and displays them visualized on the user interface. The user can then view the details of the functions on the screen and proceed with the necessary procedures.

[0622] Step 8:

[0623] Users input feedback and send it to the server via their device. This feedback information is analyzed on the server to improve the user experience and is used for future feature improvements. The feedback is collected in text format as user ratings and impressions.

[0624] (Application Example 2)

[0625] 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."

[0626] In recent years, the variety and content of services in the fields of elderly care and welfare have become so diverse that it is difficult to receive proposals that are tailored to individual needs. Furthermore, the lack of personalized service provision that takes into account the psychological state of users is a significant challenge. Additionally, the time and effort required to generate and manage the necessary documents and information for procedures places a heavy burden on users.

[0627] 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.

[0628] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching for and proposing appropriate public services from an information storage unit based on the analysis results, and means for integrating an emotion recognition engine that analyzes the user's psychological state. As a result, users can receive suggestions for care and welfare services that are tailored to their individual needs, and furthermore, detailed support tailored to their psychological state is provided, thereby reducing the burden on the user.

[0629] "Input information" refers to data obtained from user submissions and can take various forms, such as audio and text.

[0630] "Means of analysis" refer to methods and devices for processing input information and understanding its content.

[0631] "Public services" are services provided by government and welfare agencies that individuals and families use to improve their quality of life.

[0632] An "information storage unit" is a recording medium or database for storing data, and it stores the information necessary for the proposed service.

[0633] An "emotion recognition engine" is software or a program that analyzes emotions from user input information and estimates their psychological state.

[0634] "Proposed means" refers to methods and devices for presenting users with the most suitable public services based on the analyzed information.

[0635] A "guideline" is a set of instructions that outlines the necessary steps and methods for carrying out a procedure.

[0636] The system implementing this invention primarily operates through the cooperation of three parties: a server, a terminal, and a user. Details are provided below.

[0637] The server receives input information sent by the user. If the user uses voice input, the server converts the voice information into text using the terminal's speech recognition technology (e.g., Google Cloud Speech-to-Text). The converted text information is then analyzed using a natural language processing library on the server (e.g., NLTK or spaCy). During the analysis process, an emotion recognition engine (e.g., IBM Watson Tone Analyzer) is used to estimate the user's psychological state.

[0638] Based on the analysis results, the server searches for appropriate public services from its information storage and makes suggestions to the user. This search process takes into account the user's psychological state and adjusts the priority of the suggested services as needed. The generated suggestions include a function to automatically generate necessary information documents related to the relevant service.

[0639] Regarding the acquisition and processing of feedback, user evaluations are received via terminals and stored and analyzed on the server. This allows the system to strive to improve the quality of the public services it provides. For example, if a user inputs "I'm having trouble with the procedures for long-term care recently," the system can automatically generate the necessary documents and provide related suggestions such as home care services and counseling.

[0640] An example of a prompt for a generative AI model is: "Create an assistant that can provide advice on caregiving. Analyze the user's emotions from the content of the consultation and suggest appropriate welfare services." This prompt is referenced during system development and testing.

[0641] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0642] Step 1:

[0643] The user inputs their inquiry using a device. If the user inputs by voice, the device uses speech recognition technology to convert the voice information into text. At this stage, the input is either voice or text information, and the output is text information.

[0644] Step 2:

[0645] The terminal sends the converted text information to the server. In this step, data transfer from the terminal to the server takes place. The input is text information, and the output is the status of completion of transmission to the server.

[0646] Step 3:

[0647] The server analyzes the received text information using a natural language processing library. Specifically, it extracts keywords related to the user's needs from the text information. The input for this step is the text information, and the output is the analyzed keywords and needs information.

[0648] Step 4:

[0649] The server uses an emotion recognition engine to analyze the user's psychological state. The emotion recognition engine estimates the psychological state based on text information and provides the result. The input is the analyzed text information, and the output is the evaluation result of the emotional state.

[0650] Step 5:

[0651] The server searches for appropriate public services from its internal information storage. The search considers analysis results and sentiment evaluations to provide optimal suggestions. The input at this stage is the user's needs and sentiment evaluation results, and the output is a list of suggested public services.

[0652] Step 6:

[0653] The server automatically generates the necessary information documents and prepares to notify the user. The input is the proposed public service information, and the output is the automatically generated information document. The server then prepares to send this back to the terminal.

[0654] Step 7:

[0655] Users can receive suggested service details through their device and provide feedback. Sending this feedback to the server helps improve the quality of the service. The input is the user's feedback information, and the output is the feedback reception status.

[0656] 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.

[0657] 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.

[0658] 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.

[0659] [Fourth Embodiment]

[0660] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0661] 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.

[0662] 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).

[0663] 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.

[0664] 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.

[0665] 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).

[0666] 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.

[0667] 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.

[0668] 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.

[0669] 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.

[0670] 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.

[0671] 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.

[0672] 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".

[0673] The system of the present invention is designed to allow users to confidently discuss personal problems and anxieties, and to receive suggestions and procedural support for the most suitable administrative and welfare services. The following describes embodiments for carrying out the present invention.

[0674] Users input their inquiries in text or voice format via their device. The device sends this input data to the server. The server analyzes the received data using semantic analysis and natural language processing techniques to identify the user's needs and problems.

[0675] After the analysis is complete, the server consults its internal database to find the most suitable administrative and welfare services for the user. This process includes an algorithm that considers evaluation parameters such as service effectiveness and usability to select the optimal service.

[0676] Next, the server sends information to the terminal to notify the user of the proposed service. The terminal displays this information to the user, presenting the specific service details and usage procedures. In some cases, the server can also automatically generate and provide the user with any necessary documents related to the proposed service.

[0677] Furthermore, the server periodically accesses external databases to obtain the latest information on administrative and welfare services. This ensures that the system always maintains and provides users with the most up-to-date information.

[0678] When a user provides feedback on the usefulness of the information and services provided, the device sends this feedback to the server. The server uses the received feedback to improve the system and provide better services.

[0679] As a concrete example, consider a case where a user seeks advice regarding family care. The server searches its database for care-related services and suggests options such as "community-based integrated care centers" and the "long-term care insurance system." It then automatically generates the necessary application documents, supporting the user in smoothly completing the process.

[0680] Thus, the system of the present invention aims to provide prompt and accurate support for various problems faced by users.

[0681] The following describes the processing flow.

[0682] Step 1:

[0683] The user enters their inquiry into the device as text or voice. Let's assume the user enters "I want to know about support regarding caring for my parents."

[0684] Step 2:

[0685] The terminal receives data entered by the user and sends it to the server. In the case of voice data, speech recognition technology is used beforehand to convert it to text.

[0686] Step 3:

[0687] The server processes the received text data for semantic analysis and extracts keywords related to elderly care. This analysis identifies the type of service the user needs.

[0688] Step 4:

[0689] The server consults its internal database to find the administrative and welfare services best suited to the user's needs. For example, it might suggest access to a "community-based integrated care center" or the "long-term care insurance system."

[0690] Step 5:

[0691] The server automatically generates the necessary documents from templates based on the proposed service. These documents are required for the user to submit when receiving care services.

[0692] Step 6:

[0693] The server sends the search results and automatically generated documents to the user's device to notify them.

[0694] Step 7:

[0695] The terminal displays information received from the server to the user, providing access to specific service proposals and generated documents.

[0696] Step 8:

[0697] The user either proceeds with the procedure according to the suggestion, or enters feedback on the device if further assistance is needed.

[0698] Step 9:

[0699] The device receives feedback from users and sends it to the server. This allows the server to use the feedback to improve the services it provides.

[0700] This ensures users receive consistent support and promotes the use of appropriate services.

[0701] (Example 1)

[0702] 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".

[0703] In modern society, there is a need to quickly and accurately propose appropriate public services and support to address the diverse problems individuals face. Furthermore, since information is updated daily, it is necessary to always provide the latest service information. However, doing this manually is inefficient and can lead to individual inconsistencies. Moreover, the lack of opportunities for users to provide feedback on the services they receive, and the insufficient mechanisms for using that information to improve the system, makes it difficult to provide sophisticated support.

[0704] 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.

[0705] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching a knowledge base for and proposing appropriate public services based on the analysis results, and means for automatically generating necessary information related to the proposed public services. This enables the user to always receive the latest and most optimal service information and to receive rapid problem-solving support.

[0706] "Input information" refers to data obtained from the user in text or audio format, including individual problems and consultation details.

[0707] "Analysis" is the process of analyzing received input information using semantic analysis and natural language processing techniques to identify user needs and problems.

[0708] "Public services" refer to administrative and welfare services provided by government agencies and related organizations, and include specific support available to users to solve problems.

[0709] A "knowledge base" is a dataset that systematically organizes information about possible public services and allows for searching and referencing as needed.

[0710] "Automatic generation" refers to the process of generating necessary information and documents using a program without human intervention, thereby supporting the user's specific procedures.

[0711] "External information sources" refer to databases and information services outside the system that can be referenced to obtain the latest information at all times.

[0712] "Feedback" refers to comments and opinions made by users regarding the usefulness and satisfaction level of the proposed service, and is used to improve the system.

[0713] "Voice information" refers to data in audio format obtained from users, including information entered via voice regarding the content of the consultation.

[0714] "Text information" refers to data in text format that has been converted by speech recognition, and is the subject of analysis.

[0715] "Latest service information" refers to the most up-to-date information on administrative and welfare services, and represents the current information that should be provided to users.

[0716] The system of this invention helps users to access appropriate public services more effectively. Based on information entered by the user via a terminal, the system selects and provides suggested services using a variety of technologies.

[0717] First, the user enters their inquiry details using text or voice via their device. If voice information is entered, the device uses a speech recognition engine to convert the voice to text. While general speech recognition software is used for this purpose, a specific example is the Google Speech-to-Text API.

[0718] Next, the server receives the text information sent from the terminal and analyzes it using semantic analysis and natural language processing. Natural language processing libraries such as "spaCy" and "NLTK" can be used for this analysis. This helps identify the user's needs and problems.

[0719] The server searches its internal knowledge base based on the analysis results. This knowledge base organizes information on various public services and includes data for recommending appropriate services. Algorithms utilizing machine learning libraries such as "scikit-learn" and "TensorFlow" can be applied to service selection.

[0720] Proposed public services are notified to the user via a terminal. The terminal can display this information and provide detailed guidance on the procedures and required documents for the relevant process. The server automatically generates documents as needed and helps users efficiently proceed with the process, for example, by creating PDF documents using "ReportLab".

[0721] Furthermore, the server periodically references external sources to obtain the latest service information and update its knowledge base. This ensures that users are always provided with the most up-to-date information.

[0722] When a user provides feedback on a service they have used, the terminal transmits this feedback to the server. The server then uses this feedback to improve the system and enhance the quality of public services provided. An example of a specific prompt would be: "Please describe a system that analyzes a user's inquiry in natural language and suggests appropriate welfare services."

[0723] This system is designed to be an essential support for users, helping them access public services quickly and reliably.

[0724] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0725] Step 1:

[0726] The user enters their consultation details via a terminal. The input format is either text or voice. At this stage, the input is raw information from the user. If voice input is received, the terminal uses a speech recognition engine to convert the voice information into text information. Through this conversion process, the user's consultation details are standardized into text format and sent to the server.

[0727] Step 2:

[0728] The server receives text information sent from the terminal. The received text data is subjected to semantic analysis and natural language processing. This processing uses libraries such as "spaCy" and "NLTK" to identify the user's problems and needs. The analysis output provides keywords and problem categories.

[0729] Step 3:

[0730] The server searches its internal knowledge base based on the analysis results. This knowledge base is a database containing detailed information about public services. During this search, the server uses machine learning techniques to select the appropriate services. As a result, a list of services that meet the user's needs is output.

[0731] Step 4:

[0732] The server sends the selected service information to the terminal. The terminal displays the received information to the user, conveying the specific service content along with details of the related procedures. For example, information on the "Long-Term Care Insurance System" and "Regional Medical Support Center" may be displayed. The output of this step is detailed information about the services that can be displayed.

[0733] Step 5:

[0734] The server automatically generates the information required for the proposed service. It uses libraries such as "ReportLab" to generate the necessary documents in PDF format. This process outputs instructions for the next steps the user should take.

[0735] Step 6:

[0736] The server periodically references external data sources to update its knowledge base. This ensures that the latest administrative and welfare service information is obtained and reflected in the system. References to external data update the knowledge base, establishing a foundation for providing up-to-date information.

[0737] Step 7:

[0738] Users provide feedback on the services offered through their devices. This feedback information is sent from the device to the server. The server analyzes the received feedback and uses it to improve the system. The results of this analysis improve the accuracy of future service proposals.

[0739] (Application Example 1)

[0740] 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".

[0741] A challenge exists in that users lack quick and accurate means of accessing the latest public services available to resolve personal problems, and the procedures for doing so are often cumbersome, resulting in ineffective support. This invention aims to improve this situation and enable users to easily find and smoothly utilize the services they need.

[0742] 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.

[0743] In this invention, the server includes means for receiving input information from the user and analyzing that information, means for searching for and proposing the most suitable public service from a data storage device, and means for referring to an external data storage device and periodically updating the information. This makes it possible for users to quickly search for public services that match their needs and to easily perform the detailed procedures.

[0744] A "user" refers to an individual or organization that uses the system to seek advice and receive suggestions for the most suitable public services.

[0745] "Input information" refers to data such as text and audio that users provide to the system in order to resolve their own problems or concerns.

[0746] "Means of analysis" refers to the technical process of analyzing received input information to identify user needs and challenges.

[0747] "Public services" refer to services provided by government agencies and related organizations, including the support and procedures necessary to resolve the individual problems of users.

[0748] A "data storage device" refers to a database or other storage means that a system accesses, searches for, and stores information.

[0749] "Means of automatic generation" refers to the process by which a system automatically creates necessary records and procedures and provides them to the user.

[0750] An "external data storage device" refers to an external database or information source that a system references to periodically update its information.

[0751] "Feedback" refers to evaluations and opinions provided by users regarding the usefulness of proposed services or procedures.

[0752] "Mobile information terminals" refer to information processing devices that can be used while on the go, such as mobile phones and tablets.

[0753] This invention comprises a system used via a smartphone or other mobile information terminal. The user inputs their problems or anxieties into the terminal as text or voice. The terminal sends this input information to a server in the cloud, where it is analyzed using semantic analysis and natural language processing techniques. This process utilizes Python and the natural language processing library SpaCy, or the Google Cloud Natural Language API.

[0754] Based on the analysis results, the server identifies the most suitable public services from the data storage device and proposes them to the user. The service selection uses algorithms that consider effectiveness and usability. The server then automatically generates and provides the user with the necessary materials related to the proposed service. This functionality is implemented using cloud services such as AWS or GCP.

[0755] Furthermore, the server periodically references an external data storage device to obtain the latest information on public services and update the database. This ensures that users are always provided with the most up-to-date service information. The system also includes a feature that allows users to easily select specific public services and download relevant materials using their smartphones.

[0756] As a concrete example, consider a user who "wants advice about using day care services for their elderly parent." The server analyzes the user's inquiry and presents a list of local day care facilities. It provides the user with detailed information, including ratings and fees, and automatically generates and makes available for download the necessary application documents for the selected facility.

[0757] An example of a prompt message to provide to the generating AI model is: "Please enter your concerns regarding caregiving. For example, regarding the selection of a care facility or the procedures for long-term care insurance. We will suggest the most suitable care services."

[0758] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0759] Step 1:

[0760] The user uses a smartphone or mobile device to input their consultation details in text or voice format. This input data is temporarily stored on the device and prepared to be sent to the server for analysis. In the case of voice input, the device converts the input voice into text data. Input: User's consultation details (text / voice). Output: Text data ready to be sent to the server.

[0761] Step 2:

[0762] The server analyzes text data received from the terminal. Here, the server uses natural language processing techniques to semantically analyze the input data in order to understand the user's needs and problems. The analysis uses Python and either SpaCy or the Google Cloud Natural Language API. Input: Text data. Output: Analysis results (user needs).

[0763] Step 3:

[0764] Based on the analysis results, the server searches for the most suitable public services from the data storage device. The search uses an algorithm that considers service content, effectiveness, and availability to find the optimal solution to the user's specific problem. Input: Analysis results. Output: List of optimal public services.

[0765] Step 4:

[0766] The server automatically generates the necessary documents related to the selected public service. This allows users to smoothly proceed with applying for and using the service. This document generation and management are handled using AWS or GCP cloud services. Input: List of optimal public services. Output: Required documents.

[0767] Step 5:

[0768] The server periodically updates its database by referencing an external data storage device to maintain the latest public service information. This process ensures that the information provided to users is always up-to-date. Input: External data. Output: Updated internal database.

[0769] Step 6:

[0770] The user uses their smartphone to view information on the most suitable public services presented by the server and download the necessary documents. This process makes it easy for the user to select services and complete procedures. Input: Service information from the server. Output: Procedure documents available to the user.

[0771] 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.

[0772] This invention allows users to input their consultation details through a system, which then proposes appropriate administrative and welfare services, automatically generates necessary documents, and provides support for procedures. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, the aim is to provide a more personalized service.

[0773] Users input their consultation details using their device. If the user inputs by voice, the data is converted into text using speech recognition technology on the device. The device then sends the data to the server.

[0774] When the server analyzes the received data, it first performs semantic analysis to extract the user's needs. This process incorporates an emotion engine that can detect the user's emotional state based on the content of the text data. For example, if the text contains many keywords such as "anxiety" or "worry," the server will recognize the user's emotion as "anxiety."

[0775] Next, the server searches its internal database for appropriate administrative and welfare services based on the analyzed data. During this process, it can adjust the suggested services based on the user's emotional assessment. For example, for a user experiencing anxiety, it prioritizes suggesting services with more comprehensive support or those that include emotional care.

[0776] The server automatically generates the necessary documents related to the proposed service and prepares to notify the user. This allows the user to proceed with the process smoothly.

[0777] Once the proposal is finalized, the server sends this information to the terminal. The terminal displays the information to the user, providing details about the proposed service, instructions for using it, and how to access the generated documents.

[0778] Finally, users are allowed to provide feedback on the usefulness of the information and services, and this data is sent from the device to the server. By receiving user feedback, the server continuously improves the quality of the services provided.

[0779] For example, if a user enters "I'm worried about caring for a family member," the server will suggest caregiving-related support services and also offer counseling services to alleviate the user's anxiety. In this way, personalized support is achieved.

[0780] The following describes the processing flow.

[0781] Step 1:

[0782] Users use their devices to input their concerns as text or voice. For example, they might type, "I'm worried about caring for my parents."

[0783] Step 2:

[0784] The terminal receives the input data. In the case of voice data, it uses speech recognition technology to convert it into text data. The converted text data is then sent to the server.

[0785] Step 3:

[0786] The server analyzes the received text data. Using a semantic analysis engine, it extracts keywords present in the consultation content and determines the user's needs.

[0787] Step 4:

[0788] The server's emotion engine recognizes the user's emotions from extracted keywords and sentence structure. In this case, it recognizes the user's emotion as "anxiety" based on words such as "anxiety" and "worry."

[0789] Step 5:

[0790] Based on the results of analysis and emotion recognition, the server searches its internal database for appropriate administrative and welfare services. Options include "care consultation services" and "mental health counseling."

[0791] Step 6:

[0792] The server automatically generates the necessary documents for the proposed service, such as application forms for care support and appointment forms for counseling.

[0793] Step 7:

[0794] The server sends the selected service information to the terminal along with the generated document. This includes specific service details and usage instructions.

[0795] Step 8:

[0796] The device displays the received information to the user. The screen shows an overview and links to each suggested service, as well as options for downloading documents.

[0797] Step 9:

[0798] Users review the proposed information and procedures and enter feedback into their device. For example, they might describe their satisfaction with the proposal or their progress in using the service.

[0799] Step 10:

[0800] The device sends user feedback to the server. This information is used as data to improve the quality of the service.

[0801] Through these steps, users will be able to receive more appropriate and personalized assistance for their problems.

[0802] (Example 2)

[0803] 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".

[0804] In modern society, users face the challenge of obtaining appropriate advice and services for the various problems they encounter. Furthermore, there is a demand for highly personalized services that respond to users' emotions and needs, as well as for efficient processing of necessary procedures. Conventional systems suffer from insufficient consideration of user emotions in service suggestions and continuous improvement through the use of feedback.

[0805] 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.

[0806] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching for and proposing appropriate functions from information sources based on the analysis results, and means for determining the user's emotional state using an emotion analysis engine. This makes it possible to propose services that meet the individual needs and emotional state of the user, thereby realizing efficient and personalized support.

[0807] "Input information" refers to data that a user provides to the system, including in various formats such as audio and text.

[0808] "Analysis" is the process of analyzing received information to understand the user's needs and emotional state.

[0809] A "function" refers to a specific service or action that provides the advice and support that the user is looking for.

[0810] "Information sources" refer to a collection of databases and resources used to search for appropriate features to suggest to users.

[0811] "Required documents" refer to automatically generated documents and forms that are necessary for users to proceed with the proposed functionality.

[0812] An "emotion analysis engine" is a general term for technologies and algorithms used to determine an emotional state based on user input.

[0813] "Personalized support" means providing services that are customized to the specific needs and emotions of each individual user.

[0814] This invention is a system consisting of a user terminal and a server equipped with multiple data analysis means.

[0815] Users can use a terminal to provide their consultation details either by typing or by voice. In the case of voice input, the terminal uses speech recognition technology to convert the content into text data. The terminal incorporates commonly used speech recognition software and employs a device capable of converting speech to text in real time.

[0816] The terminal sends the received text data to the server. The server analyzes the received data using advanced natural language processing technology. In particular, it uses a generative AI model to extract the user's intentions and the support they need from the data, and also uses an emotion analysis engine to determine the user's emotional state. This makes it possible to suggest appropriate functions that meet the user's needs.

[0817] The server has the capability to automatically generate materials related to the proposed functionality, providing users with the documents and instructions they need immediately. Accordingly, it regularly references external sources to update information and ensure that it always provides the latest data. Digital document generation technology is utilized in this process.

[0818] The terminal displays information received from the server to the user and provides instructions on how to use the suggested functions and related materials. Finally, the user enters feedback on the usefulness of the service, and this data is sent to the server, contributing to the improvement of the entire system.

[0819] For example, if a user enters a prompt message such as, "I would like to seek advice regarding domestic stress and find out what kind of support I can receive," the server can suggest stress-related counseling services and introduce activities that are effective in reducing stress. Providing individually customized support to the user in this way is a key feature of the present invention.

[0820] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0821] Step 1:

[0822] The user enters their consultation details using a device. The input is provided in either text or voice format. In the case of voice input, the device uses speech recognition technology to convert the voice data into text data. This results in the user's intended consultation content being output as text. Specifically, the speech recognition engine analyzes the input voice waveform and converts it into a string based on a language model.

[0823] Step 2:

[0824] The terminal sends the converted text data to the server. The text data is transferred to the server via network communication. A secure protocol (e.g., HTTPS) is typically used for this communication. The terminal divides the data into packets and sends them sequentially to the server.

[0825] Step 3:

[0826] The server analyzes the received text data. First, it performs semantic analysis using natural language processing techniques to extract the meaning of the text and the user's needs. This analysis utilizes generative AI models to deepen contextual understanding. In this process, it identifies specific keywords and phrases from the input text and clarifies the user's requests.

[0827] Step 4:

[0828] The server uses an emotion analysis engine to determine the user's emotional state. It analyzes emotional patterns from vocabulary and expressions within text data and outputs emotions such as "anxiety" or "happiness." Emotion analysis is achieved using emotion dictionaries and machine learning models.

[0829] Step 5:

[0830] Based on the analysis results, the server searches for and proposes appropriate functions from internal sources. The function suggestion system selects and outputs a list of the most suitable support options based on the user's needs and emotional state. Database query techniques are utilized in this step to ensure efficient searching.

[0831] Step 6:

[0832] The server automatically generates the necessary documentation related to the proposed functionality. Using a digital document generation library, it creates the forms and instructions required to implement the service and outputs them as formatted electronic documents for the user.

[0833] Step 7:

[0834] The server sends proposed functions and related materials to the terminal. The terminal receives these and displays them visualized on the user interface. The user can then view the details of the functions on the screen and proceed with the necessary procedures.

[0835] Step 8:

[0836] Users input feedback and send it to the server via their device. This feedback information is analyzed on the server to improve the user experience and is used for future feature improvements. The feedback is collected in text format as user ratings and impressions.

[0837] (Application Example 2)

[0838] 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".

[0839] In recent years, the variety and content of services in the fields of elderly care and welfare have become so diverse that it is difficult to receive proposals that are tailored to individual needs. Furthermore, the lack of personalized service provision that takes into account the psychological state of users is a significant challenge. Additionally, the time and effort required to generate and manage the necessary documents and information for procedures places a heavy burden on users.

[0840] 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.

[0841] In this invention, the server includes means for receiving and analyzing input information from the user, means for searching for and proposing appropriate public services from an information storage unit based on the analysis results, and means for integrating an emotion recognition engine that analyzes the user's psychological state. As a result, users can receive suggestions for care and welfare services that are tailored to their individual needs, and furthermore, detailed support tailored to their psychological state is provided, thereby reducing the burden on the user.

[0842] "Input information" refers to data obtained from user submissions and can take various forms, such as audio and text.

[0843] "Means of analysis" refer to methods and devices for processing input information and understanding its content.

[0844] "Public services" are services provided by government and welfare agencies that individuals and families use to improve their quality of life.

[0845] An "information storage unit" is a recording medium or database for storing data, and it stores the information necessary for the proposed service.

[0846] An "emotion recognition engine" is software or a program that analyzes emotions from user input information and estimates their psychological state.

[0847] "Proposed means" refers to methods and devices for presenting users with the most suitable public services based on the analyzed information.

[0848] A "guideline" is a set of instructions that outlines the necessary steps and methods for carrying out a procedure.

[0849] The system implementing this invention primarily operates through the cooperation of three parties: a server, a terminal, and a user. Details are provided below.

[0850] The server receives input information sent by the user. If the user uses voice input, the server converts the voice information into text using the terminal's speech recognition technology (e.g., Google Cloud Speech-to-Text). The converted text information is then analyzed using a natural language processing library on the server (e.g., NLTK or spaCy). During the analysis process, an emotion recognition engine (e.g., IBM Watson Tone Analyzer) is used to estimate the user's psychological state.

[0851] Based on the analysis results, the server searches for appropriate public services from its information storage and makes suggestions to the user. This search process takes into account the user's psychological state and adjusts the priority of the suggested services as needed. The generated suggestions include a function to automatically generate necessary information documents related to the relevant service.

[0852] Regarding the acquisition and processing of feedback, user evaluations are received via terminals and stored and analyzed on the server. This allows the system to strive to improve the quality of the public services it provides. For example, if a user inputs "I'm having trouble with the procedures for long-term care recently," the system can automatically generate the necessary documents and provide related suggestions such as home care services and counseling.

[0853] An example of a prompt for a generative AI model is: "Create an assistant that can provide advice on caregiving. Analyze the user's emotions from the content of the consultation and suggest appropriate welfare services." This prompt is referenced during system development and testing.

[0854] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0855] Step 1:

[0856] The user inputs their inquiry using a device. If the user inputs by voice, the device uses speech recognition technology to convert the voice information into text. At this stage, the input is either voice or text information, and the output is text information.

[0857] Step 2:

[0858] The terminal sends the converted text information to the server. In this step, data transfer from the terminal to the server takes place. The input is text information, and the output is the status of completion of transmission to the server.

[0859] Step 3:

[0860] The server analyzes the received text information using a natural language processing library. Specifically, it extracts keywords related to the user's needs from the text information. The input for this step is the text information, and the output is the analyzed keywords and needs information.

[0861] Step 4:

[0862] The server uses an emotion recognition engine to analyze the user's psychological state. The emotion recognition engine estimates the psychological state based on text information and provides the result. The input is the analyzed text information, and the output is the evaluation result of the emotional state.

[0863] Step 5:

[0864] The server searches for appropriate public services from its internal information storage. The search considers analysis results and sentiment evaluations to provide optimal suggestions. The input at this stage is the user's needs and sentiment evaluation results, and the output is a list of suggested public services.

[0865] Step 6:

[0866] The server automatically generates the necessary information documents and prepares to notify the user. The input is the proposed public service information, and the output is the automatically generated information document. The server then prepares to send this back to the terminal.

[0867] Step 7:

[0868] Users can receive suggested service details through their device and provide feedback. Sending this feedback to the server helps improve the quality of the service. The input is the user's feedback information, and the output is the feedback reception status.

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] 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."

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] The following is further disclosed regarding the embodiments described above.

[0891] (Claim 1)

[0892] A means of receiving and analyzing user input data,

[0893] A means for searching a database for and proposing an appropriate service based on the analysis results,

[0894] A means of automatically generating the necessary documents related to the proposed service,

[0895] A means of periodically updating information by referring to an external database,

[0896] A means of obtaining feedback and using it to improve the service,

[0897] A system that includes this.

[0898] (Claim 2)

[0899] The system according to claim 1, further comprising means for converting voice input from a user into text data.

[0900] (Claim 3)

[0901] The system according to claim 1, comprising means for generating and notifying detailed guidelines for the procedures relating to the proposed service.

[0902] "Example 1"

[0903] (Claim 1)

[0904] A means of receiving and analyzing user input information,

[0905] A means for searching for and proposing appropriate public services from a knowledge base based on the analysis results,

[0906] A means for automatically generating necessary information related to the proposed public service,

[0907] A means of regularly updating information by referring to external sources,

[0908] A means of obtaining feedback and using it to improve the overall service,

[0909] A means of converting audio information into text information,

[0910] A means to automatically update the latest service information,

[0911] A system that includes this.

[0912] (Claim 2)

[0913] The system according to claim 1, comprising means for generating and notifying detailed instructions for processing a proposed public service.

[0914] (Claim 3)

[0915] The system according to claim 1, comprising means for dynamically generating relevant documents based on user input information.

[0916] "Application Example 1"

[0917] (Claim 1)

[0918] A means of receiving input information from the user and analyzing that information,

[0919] A means for searching for and proposing the optimal public service from a data storage device based on the analysis results,

[0920] A means for automatically generating necessary records related to the proposed public service,

[0921] A means of periodically updating information by referring to an external data storage device,

[0922] A means of obtaining feedback and using it to improve public services,

[0923] A means to enable users to select public services using their mobile devices and download documents related to those procedures to their devices,

[0924] A system that includes this.

[0925] (Claim 2)

[0926] The system according to claim 1, further comprising means for converting voice input of a consultation into text information.

[0927] (Claim 3)

[0928] The system according to claim 1, comprising means for generating and notifying detailed instructions regarding the procedures for the proposed public service.

[0929] "Example 2 of combining an emotion engine"

[0930] (Claim 1)

[0931] A device that receives and analyzes user input information,

[0932] A device that searches for and proposes appropriate functions from information sources based on the analysis results,

[0933] A device that automatically generates necessary documents related to the proposed function,

[0934] A device that references external sources and updates information periodically,

[0935] A device that uses an emotion analysis engine to determine the user's emotional state,

[0936] A device that collects feedback and uses it to improve functionality,

[0937] A system that includes this.

[0938] (Claim 2)

[0939] The system according to claim 1, further comprising a device that converts voice input from a user into text information.

[0940] (Claim 3)

[0941] The system according to claim 1, comprising a device for generating and notifying detailed instructions regarding the procedures for the proposed function.

[0942] "Application example 2 when combining with an emotional engine"

[0943] (Claim 1)

[0944] A means for receiving and analyzing user input information,

[0945] A means for searching for and proposing appropriate public services from the information storage unit based on the analysis results,

[0946] A means for automatically generating information documents related to proposed public services,

[0947] Means for referencing an external information storage unit to periodically update information,

[0948] A means of integrating an emotion recognition engine that analyzes the user's psychological state,

[0949] The means of obtaining feedback and using it to improve the quality of public services,

[0950] A system that includes this.

[0951] (Claim 2)

[0952] The system according to claim 1, further comprising means for converting voice input into text information when a user inputs the content of their consultation by voice.

[0953] (Claim 3)

[0954] The system according to claim 1, comprising means for generating and notifying detailed guidelines for the procedures relating to the proposed public service. [Explanation of Symbols]

[0955] 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 receiving input information from the user and analyzing that information, A means for searching for and proposing the optimal public service from a data storage device based on the analysis results, A means for automatically generating necessary records related to the proposed public service, A means of periodically updating information by referring to an external data storage device, A means of obtaining feedback and using it to improve public services, A means to enable users to select public services using their mobile devices and download documents related to those procedures to their devices, A system that includes this.

2. The system according to claim 1, further comprising means for converting voice input of a consultation into text information.

3. The system according to claim 1, comprising means for generating and notifying detailed instructions regarding the procedures for the proposed public service.

Images