System

Abstract

An object of a system according to an embodiment is to provide highly reliable information on childcare.SOLUTION: A system according to an embodiment includes an information acquisition unit, an information examination unit, and an information provision unit. The information acquisition unit acquires information on child care. The information review unit reviews the information acquired by the information acquisition unit. The information providing unit provides the information reviewed by the information reviewing unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has had the problem that there is an excess of information on childcare, making it difficult to select information that is reliable and appropriate.

[0005] The system according to the embodiment aims to provide highly reliable information about childcare. [Means for solving the problem]

[0006] The system according to the embodiment includes an information acquisition unit, an information review unit, and an information provision unit. The information acquisition unit acquires information related to childcare. The information review unit reviews the information acquired by the information acquisition unit. The information provision unit provides the information reviewed by the information review unit. [Effects of the Invention]

[0007] The system according to the embodiment can provide reliable information about childcare. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The childcare information provision system according to an embodiment of the present invention is a system in which information about childcare is acquired, scrutinized by a generation AI, and provided to users. This enables the childcare information provision system to efficiently provide reliable information about childcare.

[0029] A childcare information providing system according to an embodiment includes an information acquisition unit, an information scrutiny unit, and an information providing unit. The information acquisition unit acquires information related to childcare. For example, the information acquisition unit collects the latest childcare information through an internet search. The information acquisition unit can also acquire reliable information through database access. The information acquisition unit can also collect individual childcare information through user input. For example, the information acquisition unit uses an internet search engine to collect the latest articles and research on childcare. The information acquisition unit accesses a database to acquire opinions from medical institutions and experts. Through user input, a user inputs specific questions or concerns and collects information based on the input. The information scrutiny unit scrutinizes the information acquired by the information acquisition unit. For example, the information scrutiny unit evaluates the reliability and confirms the accuracy of the information. The information scrutiny unit can also evaluate the relevance of the information and select information that is useful to the user. The information scrutiny unit can also check the recency of the information and eliminate outdated information. For example, the information scrutiny unit evaluates the reliability of the information source and selects only information from reliable sources. To confirm the accuracy of the information, multiple information sources are compared and matching information is selected. The relevance of the information is evaluated, and information that matches the user's child-rearing environment and values ​​is selected. The information providing unit provides the information scrutinized by the information scrutiny unit. For example, the information providing unit displays the information through a user interface. The information providing unit can also provide the information to the user through a notification method. The information providing unit can also select the format of the information and provide the information in a format that is easy for the user to understand. For example, the information providing unit displays the information through a website or an application. The information is provided through email or push notification as the notification method. The information format is selected to be text, image, video, or the like, and the information is provided in a format that is easy for the user to understand. This allows the child-rearing information providing system according to the embodiment to efficiently provide reliable information related to child-rearing. For example, the user can quickly obtain information from reliable information sources and solve worries and problems related to child-rearing. The user can easily search for information and obtain the necessary information through the user interface.Through notification methods, you can receive the latest information in real time.

[0030] The information acquisition unit can acquire information based on the user's child-rearing environment and values. For example, the information acquisition unit conducts a questionnaire survey to quantitatively evaluate the degree of child-rearing participation of fathers on parental leave and redefines the target demographic based on the results. For example, an online questionnaire is conducted for fathers on parental leave to quantitatively evaluate the degree of child-rearing participation. The information acquisition unit also conducts regular questionnaire surveys to evaluate the degree of child-rearing participation of fathers on parental leave and tracks changes in the degree of child-rearing participation over time. For example, questions are asked about the frequency and content of child-rearing activities each month and the results are analyzed. The information acquisition unit also evaluates the degree of child-rearing participation of fathers on parental leave based on the results of the questionnaire survey and subdivides the target demographic. For example, it distinguishes between fathers with a high degree of child-rearing participation and fathers with a low degree of child-rearing participation and provides information appropriate for each. This makes it possible to provide information that matches the user's child-rearing environment and values.

[0031] The Information Review Department can review information from reliable sources. For example, the Information Review Department analyzes the psychological barriers that fathers on parental leave have to participating in childcare and proposes specific measures to remove those barriers. For example, the Information Review Department conducts interviews with fathers on parental leave and identifies the psychological barriers to participating in childcare. The Information Review Department also holds workshops to remove the psychological barriers that fathers on parental leave have and promotes the improvement of childcare skills and understanding in the workplace. For example, the Information Review Department holds seminars to teach knowledge and techniques related to childcare. The Information Review Department also analyzes the psychological barriers that fathers on parental leave have and proposes specific measures based on the results. For example, the Information Review Department proposes online courses to improve childcare skills and the introduction of childcare support systems in the workplace. This enables the provision of highly reliable information.

[0032] The information providing unit can provide information based on the user's specific questions and concerns about child-rearing. The information providing unit, for example, uses an emotion estimation function to analyze the emotions of fathers on parental leave toward child-rearing and segment the target demographic based on those emotions. For example, the emotion estimation function is used to analyze the emotions of fathers on parental leave toward child-rearing in real time. The information providing unit also collects emotional data on fathers on parental leave and segments the target demographic based on that data. For example, it distinguishes between fathers who have positive emotions toward child-rearing and fathers who have negative emotions, and provides information appropriate for each. The information providing unit also uses the emotion estimation function to analyze the emotions of fathers on parental leave toward child-rearing and redefines the target demographic based on the results. For example, it tracks changes in emotions toward child-rearing and understands the needs of the target demographic. This makes it possible to provide information that addresses the user's specific questions and concerns.

[0033] The information providing unit can build a database to achieve centralization of information and establish a process for regularly updating the database. For example, the information providing unit builds a database to achieve centralization of information and establishes a process for regularly updating the database. For example, a database is built to centrally manage information related to childcare. The information providing unit also automates the database update process so that when new information is added, it is automatically reflected in the database. For example, an RSS feed is used to automatically collect information. The information providing unit also builds a database to achieve centralization of information and establishes a process for regularly updating the database. For example, a database is built to centrally manage information related to childcare and the information is updated regularly. This makes it possible to centralize and regularly update information.

[0034] The information providing unit can design a user interface to simplify the method of obtaining information and evaluate it through user testing. For example, the information providing unit designs a user interface to simplify the method of obtaining information and evaluates the interface through user testing. For example, it designs an interface that can be operated intuitively. The information providing unit also conducts user testing and improves the interface based on user feedback. For example, it reflects user opinions to improve the usability of the interface. The information providing unit also designs a user interface to simplify the method of obtaining information and evaluates the interface through user testing. For example, it designs an interface that can be operated intuitively and evaluates it through user testing. This makes it possible to provide an interface that allows users to easily obtain information.

[0035] The information providing unit can cooperate with other childcare-related services and apps to promote information sharing in order to realize the centralization of information. The information providing unit, for example, cooperates with other childcare-related services and apps to promote information sharing in order to realize the centralization of information. For example, it builds a platform where information about childcare can be shared. The information providing unit also cooperates with other childcare-related services and apps to build a system where information about childcare can be shared. For example, it develops an API where information about childcare can be shared. The information providing unit also cooperates with other childcare-related services and apps to promote information sharing in order to realize the centralization of information. For example, it builds a platform where information about childcare can be shared and cooperates with other services. This makes it possible to realize the centralization of information by cooperating with childcare-related services and apps.

[0036] The information providing unit may introduce a voice assistant or a chatbot to diversify the ways in which information is obtained, thereby enabling users to search for information in natural language. For example, the information providing unit may introduce a voice assistant or a chatbot to diversify the ways in which information is obtained, thereby enabling users to search for information in natural language. For example, a system may be built that allows users to search for childcare information using voice commands. The information providing unit may also introduce a chatbot to build a system that allows users to search for childcare information in natural language. For example, the system may answer questions about childcare in a chat format. The information providing unit may also introduce a voice assistant or a chatbot to diversify the ways in which information is obtained, thereby enabling users to search for information in natural language. For example, a system may be built that allows users to search for childcare information using voice commands, thereby enabling users to easily obtain information. This allows users to search for information in natural language, thereby diversifying the ways in which information is obtained.

[0037] The generation AI can automatically generate a specific childcare plan based on information provided by the information providing unit when a user does not know what to do when raising a child for the first time. For example, the generation AI automatically generates a specific childcare plan based on the provided information when the user does not know what to do when raising a child for the first time. For example, it automatically creates daily childcare tasks and schedules. The generation AI also builds a system that automatically generates a childcare plan based on the provided information and provides it to the user. For example, it lists the preparations and procedures necessary for childcare. The generation AI also adds a function that automatically generates a specific childcare plan based on the provided information when the user does not know what to do when raising a child for the first time, allowing the user to start childcare with peace of mind. For example, it provides a step-by-step guide for childcare. This makes it possible to automatically generate a specific plan for first-time childcare.

[0038] The generation AI can create a personalized news feed based on the information provided by the information providing unit when a user wants to know the latest information and trends related to childcare. For example, when a user wants to know the latest information and trends related to childcare, the generation AI creates a personalized news feed based on the provided information. For example, it provides the latest childcare information based on the user's interests. The generation AI also creates a news feed tailored to the user's interests based on the provided information and builds a system that provides the latest childcare information. For example, it provides the latest research results and trends related to childcare. The generation AI also creates a personalized news feed based on the provided information when a user wants to know the latest information and trends related to childcare, allowing the user to efficiently collect information. For example, an app that provides the latest childcare information based on the user's interests can be developed. This makes it possible to provide the latest childcare information based on the user's interests.

[0039] The generating AI can develop an online consultation service based on the information provided by the information providing unit to help users solve specific worries and problems related to child-rearing. The generating AI, for example, develops an online consultation service based on the provided information to help users solve specific worries and problems related to child-rearing. For example, it builds an online platform where experts answer questions about child-rearing. The generating AI also develops an online consultation service related to child-rearing based on the provided information, allowing users to receive expert advice. For example, it builds a system where users can consult experts about specific worries and problems related to child-rearing. The generating AI also develops an online consultation service based on the provided information to help users solve specific worries and problems related to child-rearing, allowing users to efficiently collect information. For example, it builds an online platform where experts answer questions about child-rearing. This makes it possible to provide an online consultation service to help users solve specific worries and problems related to child-rearing.

[0040] The information providing unit can add a service that not only provides information about childcare but also provides reviews and comparison information on childcare products. For example, the information providing unit adds a service that not only provides information about childcare but also provides reviews and comparison information on childcare products. For example, it provides ratings and usage impressions of childcare products to users. The information providing unit also adds a service that provides reviews and comparison information on childcare products based on information provided by the generation AI, allowing users to select the most suitable childcare product. For example, it builds a system that provides ratings and usage impressions of childcare products to users. The information providing unit also adds a service that not only provides information about childcare but also provides reviews and comparison information on childcare products, allowing users to efficiently collect information. For example, it develops an app that provides ratings and usage impressions of childcare products to users. This allows users to select the most suitable childcare product by providing reviews and comparison information on childcare products.

[0041] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0042] The information acquisition unit not only acquires information about childcare, but also collects behavioral data related to childcare from users. For example, it analyzes the usage history of childcare apps and the contents of childcare diaries to understand the user's childcare style and interests. The information acquisition unit can also analyze childcare-related social media posts to understand trends and user interests. Furthermore, the information acquisition unit can use the user's location information to collect childcare information by region and provide childcare problems and solutions specific to that region. This makes it possible to provide more personalized childcare information based on the user's behavioral data and regional information.

[0043] The information provision unit can add a service that not only provides information about childcare but also provides reviews and comparison information on childcare products. For example, it can provide users with ratings and usage impressions of childcare products. The information provision unit can also add a service that provides reviews and comparison information on childcare products based on the information provided by the generation AI, allowing users to select the most suitable childcare product. For example, it can build a system that provides users with ratings and usage impressions of childcare products. The information provision unit can also add a service that not only provides information about childcare but also provides reviews and comparison information on childcare products, allowing users to collect information efficiently. For example, it can develop an app that provides users with ratings and usage impressions of childcare products. This allows users to select the most suitable childcare product by providing reviews and comparison information on childcare products.

[0044] The information providing unit not only provides information about child-rearing, but also builds an online community related to child-rearing, providing a place for users to share information with each other. For example, it sets up a forum or chat room related to child-rearing, allowing users to freely exchange questions and opinions. The information providing unit also builds a system that provides a place for users to share information about child-rearing with each other through the online community. For example, it sets up a forum for each topic related to child-rearing, providing an environment where users can easily share information. The information providing unit not only provides information about child-rearing, but also provides a place for users to share information with each other through the online community, allowing users to collect information efficiently. This allows users to share information with each other and collect information about child-rearing more effectively.

[0045] The information providing unit can add a service that not only provides information about childcare but also provides information about events and seminars related to childcare. For example, it provides users with information about seminars and workshops related to childcare. The information providing unit can also add a service that provides information about events and seminars related to childcare based on the information provided by the generation AI, thereby providing users with an opportunity to deepen their knowledge about childcare. For example, it can build a system that provides users with information about seminars and workshops related to childcare. The information providing unit can also add a service that not only provides information about childcare but also provides information about events and seminars related to childcare, allowing users to efficiently collect information. For example, it can develop an app that provides users with information about seminars and workshops related to childcare. This provides users with an opportunity to deepen their knowledge about childcare by providing information about events and seminars related to childcare.

[0046] The information providing unit can add a service that not only provides information about child-rearing but also provides expert advice on child-rearing. For example, it provides expert advice on child-rearing to users. The information providing unit can also add a service that provides expert advice on child-rearing based on the information provided by the generation AI, allowing users to obtain expert knowledge. For example, it can build a system that provides expert advice on child-rearing to users. The information providing unit can also add a service that not only provides information about child-rearing but also provides expert advice on child-rearing, allowing users to efficiently collect information. For example, it can develop an app that provides expert advice on child-rearing to users. This allows users to obtain expert knowledge by providing expert advice on child-rearing.

[0047] The information providing unit can add a service that not only provides information about childcare but also provides recommended information about books and resources related to childcare. For example, it provides recommended information about books and resources related to childcare to users. The information providing unit can also add a service that provides recommended information about books and resources related to childcare based on information provided by the generation AI, thereby providing users with an opportunity to deepen their knowledge about childcare. For example, it can build a system that provides recommended information about books and resources related to childcare to users. The information providing unit can also add a service that not only provides information about childcare but also provides recommended information about books and resources related to childcare, allowing users to efficiently collect information. For example, it can develop an app that provides recommended information about books and resources related to childcare to users. This provides recommended information about books and resources related to childcare, thereby providing users with an opportunity to deepen their knowledge about childcare.

[0048] The processing flow of the first embodiment will be briefly explained below.

[0049] Step 1: The information acquisition unit acquires information related to childcare. For example, the latest childcare information is collected through internet searches. Reliable information can also be acquired through database access. Furthermore, individual childcare information can be collected through user input. Specifically, the unit collects the latest articles and research on childcare using internet search engines, obtains opinions from medical institutions and experts through database access, and collects information based on specific questions or concerns through user input. Step 2: The information scrutiny unit scrutinizes the information acquired by the information acquisition unit. For example, it evaluates the reliability and checks the accuracy of the information. It can also evaluate the relevance of the information and select information that is useful to the user. It also checks the recency of the information and eliminates outdated information. Specifically, it checks the reliability of the information source, selects only information from reliable sources, compares multiple information sources and selects matching information, and selects information that matches the user's child-rearing environment and values. Step 3: The information providing unit provides the information reviewed by the information reviewing unit. For example, the information may be displayed through a user interface. The information may also be provided to the user through a notification method. Furthermore, the information format may be selected and the information may be provided in a format that is easy for the user to understand. Specifically, the information may be displayed through a website or application, provided via email or push notification, or provided in the form of text, images, video, etc.

[0050] (Example 2) The childcare information provision system according to an embodiment of the present invention is a system in which information about childcare is acquired, scrutinized by a generation AI, and provided to users. This enables the childcare information provision system to efficiently provide reliable information about childcare.

[0051] A childcare information providing system according to an embodiment includes an information acquisition unit, an information scrutiny unit, and an information providing unit. The information acquisition unit acquires information related to childcare. For example, the information acquisition unit collects the latest childcare information through an internet search. The information acquisition unit can also acquire reliable information through database access. The information acquisition unit can also collect individual childcare information through user input. For example, the information acquisition unit uses an internet search engine to collect the latest articles and research on childcare. The information acquisition unit accesses a database to acquire opinions from medical institutions and experts. Through user input, a user inputs specific questions or concerns and collects information based on the input. The information scrutiny unit scrutinizes the information acquired by the information acquisition unit. For example, the information scrutiny unit evaluates the reliability and confirms the accuracy of the information. The information scrutiny unit can also evaluate the relevance of the information and select information that is useful to the user. The information scrutiny unit can also check the recency of the information and eliminate outdated information. For example, the information scrutiny unit evaluates the reliability of the information source and selects only information from reliable sources. To confirm the accuracy of the information, multiple information sources are compared and matching information is selected. The relevance of the information is evaluated, and information that matches the user's child-rearing environment and values ​​is selected. The information providing unit provides the information scrutinized by the information scrutiny unit. For example, the information providing unit displays the information through a user interface. The information providing unit can also provide the information to the user through a notification method. The information providing unit can also select the format of the information and provide the information in a format that is easy for the user to understand. For example, the information providing unit displays the information through a website or an application. The information is provided through email or push notification as the notification method. The information format is selected to be text, image, video, or the like, and the information is provided in a format that is easy for the user to understand. This allows the child-rearing information providing system according to the embodiment to efficiently provide reliable information related to child-rearing. For example, the user can quickly obtain information from reliable information sources and solve worries and problems related to child-rearing. The user can easily search for information and obtain the necessary information through the user interface.Through notification methods, you can receive the latest information in real time.

[0052] The information acquisition unit can acquire information based on the user's child-rearing environment and values. For example, the information acquisition unit conducts a questionnaire survey to quantitatively evaluate the degree of child-rearing participation of fathers on parental leave and redefines the target demographic based on the results. For example, an online questionnaire is conducted for fathers on parental leave to quantitatively evaluate the degree of child-rearing participation. The information acquisition unit also conducts regular questionnaire surveys to evaluate the degree of child-rearing participation of fathers on parental leave and tracks changes in the degree of child-rearing participation over time. For example, questions are asked about the frequency and content of child-rearing activities each month and the results are analyzed. The information acquisition unit also evaluates the degree of child-rearing participation of fathers on parental leave based on the results of the questionnaire survey and subdivides the target demographic. For example, it distinguishes between fathers with a high degree of child-rearing participation and fathers with a low degree of child-rearing participation and provides information appropriate for each. This makes it possible to provide information that matches the user's child-rearing environment and values.

[0053] The Information Review Department can review information from reliable sources. For example, the Information Review Department analyzes the psychological barriers that fathers on parental leave have to participating in childcare and proposes specific measures to remove those barriers. For example, the Information Review Department conducts interviews with fathers on parental leave and identifies the psychological barriers to participating in childcare. The Information Review Department also holds workshops to remove the psychological barriers that fathers on parental leave have and promotes the improvement of childcare skills and understanding in the workplace. For example, the Information Review Department holds seminars to teach knowledge and techniques related to childcare. The Information Review Department also analyzes the psychological barriers that fathers on parental leave have and proposes specific measures based on the results. For example, the Information Review Department proposes online courses to improve childcare skills and the introduction of childcare support systems in the workplace. This enables the provision of highly reliable information.

[0054] The information providing unit can provide information based on the user's specific questions and concerns about child-rearing. The information providing unit, for example, uses an emotion estimation function to analyze the emotions of fathers on parental leave toward child-rearing and segment the target demographic based on those emotions. For example, the emotion estimation function is used to analyze the emotions of fathers on parental leave toward child-rearing in real time. The information providing unit also collects emotional data on fathers on parental leave and segments the target demographic based on that data. For example, it distinguishes between fathers who have positive emotions toward child-rearing and fathers who have negative emotions, and provides information appropriate for each. The information providing unit also uses the emotion estimation function to analyze the emotions of fathers on parental leave toward child-rearing and redefines the target demographic based on the results. For example, it tracks changes in emotions toward child-rearing and understands the needs of the target demographic. This makes it possible to provide information that addresses the user's specific questions and concerns.

[0055] The information providing unit can build a database to achieve centralization of information and establish a process for regularly updating the database. For example, the information providing unit builds a database to achieve centralization of information and establishes a process for regularly updating the database. For example, a database is built to centrally manage information related to childcare. The information providing unit also automates the database update process so that when new information is added, it is automatically reflected in the database. For example, an RSS feed is used to automatically collect information. The information providing unit also builds a database to achieve centralization of information and establishes a process for regularly updating the database. For example, a database is built to centrally manage information related to childcare and the information is updated regularly. This makes it possible to centralize and regularly update information.

[0056] The information providing unit can design a user interface to simplify the method of obtaining information and evaluate it through user testing. For example, the information providing unit designs a user interface to simplify the method of obtaining information and evaluates the interface through user testing. For example, it designs an interface that can be operated intuitively. The information providing unit also conducts user testing and improves the interface based on user feedback. For example, it reflects user opinions to improve the usability of the interface. The information providing unit also designs a user interface to simplify the method of obtaining information and evaluates the interface through user testing. For example, it designs an interface that can be operated intuitively and evaluates it through user testing. This makes it possible to provide an interface that allows users to easily obtain information.

[0057] The emotion estimation function can be used to analyze the emotions a user has when obtaining information, and improve the user interface based on those emotions. The emotion estimation function can be used, for example, to analyze the emotions a user has when obtaining information in real time. For example, the user's facial expressions and voice can be analyzed to track changes in emotions. The emotion estimation function can also be used to build a system that improves the user interface based on user emotion data. For example, an interface with a high percentage of positive emotions can be provided preferentially. The emotion estimation function can also be used to analyze the emotions a user has when obtaining information, and improve the user interface based on those emotions. For example, an interface with a low percentage of negative emotions can be provided. This makes it possible to optimize the interface based on the user's emotions.

[0058] The information providing unit can cooperate with other childcare-related services and apps to promote information sharing in order to realize the centralization of information. The information providing unit, for example, cooperates with other childcare-related services and apps to promote information sharing in order to realize the centralization of information. For example, it builds a platform where information about childcare can be shared. The information providing unit also cooperates with other childcare-related services and apps to build a system where information about childcare can be shared. For example, it develops an API where information about childcare can be shared. The information providing unit also cooperates with other childcare-related services and apps to promote information sharing in order to realize the centralization of information. For example, it builds a platform where information about childcare can be shared and cooperates with other services. This makes it possible to realize the centralization of information by cooperating with childcare-related services and apps.

[0059] The information providing unit may introduce a voice assistant or a chatbot to diversify the ways in which information is obtained, thereby enabling users to search for information in natural language. For example, the information providing unit may introduce a voice assistant or a chatbot to diversify the ways in which information is obtained, thereby enabling users to search for information in natural language. For example, a system may be built that allows users to search for childcare information using voice commands. The information providing unit may also introduce a chatbot to build a system that allows users to search for childcare information in natural language. For example, the system may answer questions about childcare in a chat format. The information providing unit may also introduce a voice assistant or a chatbot to diversify the ways in which information is obtained, thereby enabling users to search for information in natural language. For example, a system may be built that allows users to search for childcare information using voice commands, thereby enabling users to easily obtain information. This allows users to search for information in natural language, thereby diversifying the ways in which information is obtained.

[0060] The emotion estimation function can be used to monitor the emotions of users when obtaining information in real time, and the method of providing information can be optimized based on the data. The emotion estimation function can be used to monitor the emotions of users when obtaining information in real time, for example, by analyzing the user's facial expressions and voice and tracking changes in emotions. The emotion estimation function can also be used to build a system that optimizes the method of providing information based on the user's emotion data, for example, by providing information with a high proportion of positive emotions. The emotion estimation function can also be used to monitor the emotions of users when obtaining information in real time, and the method of providing information can be optimized based on that data, for example, by providing information with a low proportion of negative emotions. This makes it possible to optimize the method of providing information based on the user's emotions.

[0061] The generation AI can automatically generate a specific childcare plan based on information provided by the information providing unit when a user does not know what to do when raising a child for the first time. For example, the generation AI automatically generates a specific childcare plan based on the provided information when the user does not know what to do when raising a child for the first time. For example, it automatically creates daily childcare tasks and schedules. The generation AI also builds a system that automatically generates a childcare plan based on the provided information and provides it to the user. For example, it lists the preparations and procedures necessary for childcare. The generation AI also adds a function that automatically generates a specific childcare plan based on the provided information when the user does not know what to do when raising a child for the first time, allowing the user to start childcare with peace of mind. For example, it provides a step-by-step guide for childcare. This makes it possible to automatically generate a specific plan for first-time childcare.

[0062] The generation AI can create a personalized news feed based on the information provided by the information providing unit when a user wants to know the latest information and trends related to childcare. For example, when a user wants to know the latest information and trends related to childcare, the generation AI creates a personalized news feed based on the provided information. For example, it provides the latest childcare information based on the user's interests. The generation AI also creates a news feed tailored to the user's interests based on the provided information and builds a system that provides the latest childcare information. For example, it provides the latest research results and trends related to childcare. The generation AI also creates a personalized news feed based on the provided information when a user wants to know the latest information and trends related to childcare, allowing the user to efficiently collect information. For example, an app that provides the latest childcare information based on the user's interests can be developed. This makes it possible to provide the latest childcare information based on the user's interests.

[0063] The emotion estimation function can be used to analyze the emotions felt when a user inputs specific worries or problems related to child-rearing, and provide optimal information based on those emotions. The emotion estimation function can be used to analyze the emotions felt when a user inputs specific worries or problems related to child-rearing in real time. For example, the user's facial expressions and voice can be analyzed to track changes in emotions. The emotion estimation function can also be used to build a system that provides optimal information based on the user's emotion data. For example, information with a high proportion of positive emotions can be provided preferentially. The emotion estimation function can also be used to analyze the emotions felt when a user inputs specific worries or problems related to child-rearing, and provide optimal information based on those emotions. For example, information with a low proportion of negative emotions can be provided. This makes it possible to provide optimal information based on the user's emotions.

[0064] The generating AI can develop an online consultation service based on the information provided by the information providing unit to help users solve specific worries and problems related to child-rearing. The generating AI, for example, develops an online consultation service based on the provided information to help users solve specific worries and problems related to child-rearing. For example, it builds an online platform where experts answer questions about child-rearing. The generating AI also develops an online consultation service related to child-rearing based on the provided information, allowing users to receive expert advice. For example, it builds a system where users can consult experts about specific worries and problems related to child-rearing. The generating AI also develops an online consultation service based on the provided information to help users solve specific worries and problems related to child-rearing, allowing users to efficiently collect information. For example, it builds an online platform where experts answer questions about child-rearing. This makes it possible to provide an online consultation service to help users solve specific worries and problems related to child-rearing.

[0065] The information providing unit can add a service that not only provides information about childcare but also provides reviews and comparison information on childcare products. For example, the information providing unit adds a service that not only provides information about childcare but also provides reviews and comparison information on childcare products. For example, it provides ratings and usage impressions of childcare products to users. The information providing unit also adds a service that provides reviews and comparison information on childcare products based on information provided by the generation AI, allowing users to select the most suitable childcare product. For example, it builds a system that provides ratings and usage impressions of childcare products to users. The information providing unit also adds a service that not only provides information about childcare but also provides reviews and comparison information on childcare products, allowing users to efficiently collect information. For example, it develops an app that provides ratings and usage impressions of childcare products to users. This allows users to select the most suitable childcare product by providing reviews and comparison information on childcare products.

[0066] The emotion estimation function can be used to monitor in real time the emotions of a user when entering specific worries or problems related to child-rearing, and the method of providing information can be optimized based on the data. The emotion estimation function can be used to monitor in real time the emotions of a user when entering specific worries or problems related to child-rearing. For example, the user's facial expressions and voice can be analyzed to track changes in emotions. The emotion estimation function can also be used to build a system that optimizes the method of providing information based on the user's emotion data. For example, information with a high proportion of positive emotions can be provided preferentially. The emotion estimation function can also be used to monitor in real time the emotions of a user when entering specific worries or problems related to child-rearing, and the method of providing information can be optimized based on the data. For example, information with a low proportion of negative emotions can be provided. This makes it possible to optimize the method of providing information based on the user's emotions.

[0067] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0068] The information acquisition unit not only acquires information about childcare, but also collects behavioral data related to childcare from users. For example, it analyzes the usage history of childcare apps and the contents of childcare diaries to understand the user's childcare style and interests. The information acquisition unit can also analyze childcare-related social media posts to understand trends and user interests. Furthermore, the information acquisition unit can use the user's location information to collect childcare information by region and provide childcare problems and solutions specific to that region. This makes it possible to provide more personalized childcare information based on the user's behavioral data and regional information.

[0069] The information scrutiny unit not only scrutinizes information from reliable information sources, but also estimates the user's emotions and evaluates the reliability of the information based on those emotions. For example, it analyzes the user's facial expressions and voice when viewing information to estimate the reliability of the information. The information scrutiny unit can also evaluate the reliability of information based on the user's emotional data and provide highly reliable information preferentially. Furthermore, the information scrutiny unit can optimize the method of providing information based on the user's emotions. For example, it can provide information that evokes positive emotions preferentially. This makes it possible to provide highly reliable information based on the user's emotions.

[0070] The information providing unit not only provides information based on the user's specific questions and concerns about child-rearing, but can also estimate the user's emotions and provide information based on those emotions. For example, it analyzes the user's facial expressions and voice when entering a question to track changes in emotions. The information providing unit also builds a system that provides optimal information based on the user's emotional data. For example, it provides encouraging and supportive information to a user with negative emotions. Furthermore, the information providing unit can optimize the method of providing information based on the user's emotions. For example, it prioritizes the provision of information that elicits positive emotions. This makes it possible to provide optimal information based on the user's emotions.

[0071] To achieve the centralization of information, the information providing unit not only cooperates with other childcare-related services and apps to promote information sharing, but also estimates the user's emotions and optimizes the information sharing method based on those emotions. For example, it analyzes the user's facial expressions and voice when sharing information to track changes in emotions. The information providing unit also builds a system that optimizes the information sharing method based on the user's emotional data. For example, it prioritizes providing an information sharing method that elicits positive emotions. Furthermore, the information providing unit can also optimize the information sharing method based on the user's emotions. This makes it possible to provide the optimal information sharing method based on the user's emotions.

[0072] In order to diversify the ways in which information can be obtained, the information providing unit not only introduces a voice assistant or chatbot to allow users to search for information in natural language, but also estimates the user's emotions and optimizes the information search method based on those emotions. For example, the information providing unit analyzes the user's facial expressions and voice when using the voice assistant to track changes in emotions. The information providing unit also builds a system that optimizes the information search method based on the user's emotional data. For example, it preferentially provides search methods that elicit positive emotions. Furthermore, the information providing unit can also optimize the information search method based on the user's emotions. This makes it possible to provide the optimal information search method based on the user's emotions.

[0073] The information provision unit can add a service that not only provides information about childcare but also provides reviews and comparison information on childcare products. For example, it can provide users with ratings and usage impressions of childcare products. The information provision unit can also add a service that provides reviews and comparison information on childcare products based on the information provided by the generation AI, allowing users to select the most suitable childcare product. For example, it can build a system that provides users with ratings and usage impressions of childcare products. The information provision unit can also add a service that not only provides information about childcare but also provides reviews and comparison information on childcare products, allowing users to collect information efficiently. For example, it can develop an app that provides users with ratings and usage impressions of childcare products. This allows users to select the most suitable childcare product by providing reviews and comparison information on childcare products.

[0074] The information providing unit not only provides information about child-rearing, but also builds an online community related to child-rearing, providing a place for users to share information with each other. For example, it sets up a forum or chat room related to child-rearing, allowing users to freely exchange questions and opinions. The information providing unit also builds a system that provides a place for users to share information about child-rearing with each other through the online community. For example, it sets up a forum for each topic related to child-rearing, providing an environment where users can easily share information. The information providing unit not only provides information about child-rearing, but also provides a place for users to share information with each other through the online community, allowing users to collect information efficiently. This allows users to share information with each other and collect information about child-rearing more effectively.

[0075] The information providing unit can add a service that not only provides information about childcare but also provides information about events and seminars related to childcare. For example, it provides users with information about seminars and workshops related to childcare. The information providing unit can also add a service that provides information about events and seminars related to childcare based on the information provided by the generation AI, thereby providing users with an opportunity to deepen their knowledge about childcare. For example, it can build a system that provides users with information about seminars and workshops related to childcare. The information providing unit can also add a service that not only provides information about childcare but also provides information about events and seminars related to childcare, allowing users to efficiently collect information. For example, it can develop an app that provides users with information about seminars and workshops related to childcare. This provides users with an opportunity to deepen their knowledge about childcare by providing information about events and seminars related to childcare.

[0076] The information providing unit can add a service that not only provides information about child-rearing but also provides expert advice on child-rearing. For example, it provides expert advice on child-rearing to users. The information providing unit can also add a service that provides expert advice on child-rearing based on the information provided by the generation AI, allowing users to obtain expert knowledge. For example, it can build a system that provides expert advice on child-rearing to users. The information providing unit can also add a service that not only provides information about child-rearing but also provides expert advice on child-rearing, allowing users to efficiently collect information. For example, it can develop an app that provides expert advice on child-rearing to users. This allows users to obtain expert knowledge by providing expert advice on child-rearing.

[0077] The information providing unit can add a service that not only provides information about childcare but also provides recommended information about books and resources related to childcare. For example, it provides recommended information about books and resources related to childcare to users. The information providing unit can also add a service that provides recommended information about books and resources related to childcare based on information provided by the generation AI, thereby providing users with an opportunity to deepen their knowledge about childcare. For example, it can build a system that provides recommended information about books and resources related to childcare to users. The information providing unit can also add a service that not only provides information about childcare but also provides recommended information about books and resources related to childcare, allowing users to efficiently collect information. For example, it can develop an app that provides recommended information about books and resources related to childcare to users. This provides recommended information about books and resources related to childcare, thereby providing users with an opportunity to deepen their knowledge about childcare.

[0078] The processing flow of the second embodiment will be briefly explained below.

[0079] Step 1: The information acquisition unit acquires information related to childcare. For example, the latest childcare information is collected through internet searches. Reliable information can also be acquired through database access. Furthermore, individual childcare information can be collected through user input. Specifically, the unit collects the latest articles and research on childcare using internet search engines, obtains opinions from medical institutions and experts through database access, and collects information based on specific questions or concerns through user input. Step 2: The information scrutiny unit scrutinizes the information acquired by the information acquisition unit. For example, it evaluates the reliability and checks the accuracy of the information. It can also evaluate the relevance of the information and select information that is useful to the user. It also checks the recency of the information and eliminates outdated information. Specifically, it checks the reliability of the information source, selects only information from reliable sources, compares multiple information sources and selects matching information, and selects information that matches the user's child-rearing environment and values. Step 3: The information providing unit provides the information reviewed by the information reviewing unit. For example, the information may be displayed through a user interface. The information may also be provided to the user through a notification method. Furthermore, the information format may be selected and the information may be provided in a format that is easy for the user to understand. Specifically, the information may be displayed through a website or application, provided via email or push notification, or provided in the form of text, images, video, etc.

[0080] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0081] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0082] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0083] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0084] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0085] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0086] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0087] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0088] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0089] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0090] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0091] 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.

[0092] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0093] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0094] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0095] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0096] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0097] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0098] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0099] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0100] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0101] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0102] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0103] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0104] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0105] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0106] 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.

[0107] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0108] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0109] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0110] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0111] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0112] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0113] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0114] 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.

[0115] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0116] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0117] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0119] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0120] The control 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0121] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0122] 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.

[0123] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0124] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0125] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0126] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0127] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0128] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0129] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0130] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0131] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0132] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0133] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0134] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0135] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0136] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0137] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0138] 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.

[0139] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0140] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0141] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0142] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0143] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0144] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0145] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0146] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0147] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. an information acquisition unit that acquires information related to childcare; an information review unit that reviews the information acquired by the information acquisition unit; an information providing unit that provides the information reviewed by the information review unit; A system characterized by:

2. The information acquisition unit Obtain information based on the user's childcare environment and values 2. The system of claim 1.

3. The information scrutiny unit Verify information from reliable sources 2. The system of claim 1.

4. The information providing unit Providing information based on the user's specific questions and concerns about childcare 2. The system of claim 1.

5. The information providing unit Construct a database to centralize the information, Establish a process for regularly updating said database 2. The system of claim 1.

6. The information providing unit Designing a user interface to simplify access to said information; Evaluate through user testing 2. The system of claim 1.

7. Analyze the emotions users have when obtaining information, Improve the user interface based on the emotion 2. The system of claim 1.

8. The information providing unit In order to achieve the centralization of the above information, In cooperation with other childcare-related services and apps, Facilitate the sharing of such information 2. The system of claim 1.

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