System

Abstract

An object of a system according to an embodiment is to propose an optimal childcare method according to a situation of a home or a child.SOLUTION: A system includes a database construction unit, an input unit, and a proposal unit. The database construction unit constructs a database of the childcare theory. The input unit inputs a situation of a home or a child. The proposal unit proposes an optimal childcare method on the basis of the information input by the input 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] With conventional technology, it was difficult to find the optimal parenting method that suited the situation of the family and the child.

[0005] The system according to the embodiment aims to propose an optimal child-rearing method according to the circumstances of the family and the child. [Means for solving the problem]

[0006] The system according to the embodiment includes a database construction unit, an input unit, and a suggestion unit. The database construction unit constructs a database of child-rearing theories. The input unit inputs information about the family and the child's circumstances. The suggestion unit suggests optimal child-rearing methods based on the information input by the input unit. [Effects of the Invention]

[0007] The system according to the embodiment can propose an optimal child-rearing method according to the situation of the family and the child. [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) A child-rearing support system according to an embodiment of the present invention is a system that uses AI technology to provide advice and support on child-rearing methods based on various child-rearing theories. As a result, the child-rearing support system can propose optimal child-rearing methods according to the circumstances of each family and child, manage progress, and provide feedback.

[0029] A child-rearing support system according to an embodiment includes a database construction unit, an input unit, and a suggestion unit. The database construction unit constructs a database of child-rearing theories. For example, the database constructs a database containing child-rearing theories and practical examples collected from fields such as psychology, pedagogy, and sociology. The database construction unit can also construct a database containing theories such as Montessori education, Piaget's developmental theory, and attachment theory. The input unit inputs information about the family and child. For example, the input information includes the child's age, personality, interests, home environment, and parental educational philosophy. The input unit can also input prompts containing instructions on what the user wants the AI ​​to do. The suggestion unit suggests optimal child-rearing methods based on the information input by the input unit. For example, if a child is introverted, the suggestion unit can suggest methods to deepen the parent-child bond based on attachment theory. Alternatively, if a child is curious, the suggestion unit can suggest methods to respect the child's independence based on Montessori education. This allows the child-rearing support system according to an embodiment to use AI to suggest optimal child-rearing methods based on child-rearing theories.

[0030] The database construction unit can add the latest research papers and academic presentations in real time, ensuring that the database always reflects the latest information. For example, the database construction unit could build a system that automatically collects the latest research papers and academic presentations and adds them to the database. For example, it could periodically crawl academic databases and automatically import new papers. The database construction unit could also analyze live streaming and recorded data from academic conferences to extract important information, so that the content of academic presentations can be updated in real time in the database. Furthermore, when adding the latest research results to the database, the database construction unit could automatically generate summaries using AI to make them easy to understand for users. For example, it could extract the key points of a paper and provide a concise summary. This would ensure that the latest parenting theories are always reflected.

[0031] The database construction unit can collect experimental data and statistical data to verify the effectiveness of each theory and evaluate the reliability of the theory. For example, the database construction unit collects experimental data and statistical data to verify the effectiveness of each parenting theory and registers it in a database. For example, it analyzes experimental results and survey data to evaluate the reliability of the theory. The database construction unit can also develop an algorithm to evaluate the effectiveness of each parenting theory based on the experimental data and statistical data. For example, it can build a system that prioritizes and proposes highly effective theories. The database construction unit can also visualize the empirical data to allow users to intuitively understand the effectiveness of each theory. For example, it can show the effects using graphs and charts. This makes it possible to evaluate the reliability of parenting theories.

[0032] The database construction unit can be expanded to create a global database that includes parenting theories from different cultural spheres and regions. For example, the database construction unit collects parenting theories from different cultural spheres and regions and adds them to the database. For example, it translates parenting books and papers from various countries and registers them in the database. The database construction unit can also integrate global parenting theories into the database, allowing users to select parenting methods that suit their region or culture. For example, it can add a filtering function by region. The database construction unit can also build a system that compares parenting theories from different cultural spheres and analyzes similarities and differences. For example, it can propose parenting methods that take cultural background into account. This makes it possible to reflect global parenting theories.

[0033] The database construction unit can integrate not only parenting theory but also information on children's health and nutrition to provide comprehensive parenting support. For example, the database construction unit can integrate information on children's health and nutrition in addition to parenting theory into the database. For example, it can collect information by referring to specialized books on nutrition and pediatrics. The database construction unit can also build a system that provides comprehensive parenting support based on the health and nutrition information. For example, it can propose meal plans and health management advice. The database construction unit can also integrate parenting theory and health and nutrition information to build a database that users can access centrally. For example, it can enhance the search function to quickly provide necessary information. This makes it possible to provide comprehensive parenting support.

[0034] The input unit can automatically collect information using voice input or image recognition technology, reducing the effort required for input. For example, the input unit can use voice input technology to automatically convert what parents say into text and build a system that collects information about the home and their children. For example, a smart speaker can be used to input information. The input unit can also use image recognition technology to develop a system that analyzes photos of the home and children and automatically grasps the situation. For example, a child's growth record can be extracted from the photos. The input unit can also combine voice input and image recognition to build a system that comprehensively collects information about the home and children. For example, the input unit can simultaneously analyze what parents say and photos and integrate the information. This reduces the effort required for input.

[0035] The input unit can add a reminder function for periodic updates, so that the latest information can always be maintained. For example, the input unit can add a reminder function for periodically updating the status of the home and child, so that parents do not forget to enter information. For example, the notification function of a smartphone can be used. The input unit can also use the reminder function to build a system in which parents periodically report on their child's growth and changes in the home. For example, a reminder can be set to enter monthly growth records. The input unit can also enhance the reminder function and develop a system that automatically analyzes the information entered by parents and suggests necessary updates. For example, the next update content can be suggested based on the input content. This allows the latest information to always be maintained.

[0036] The input unit can add a function that allows sharing with other family members and educational institutions to support cooperative parenting. The input unit, for example, builds a system that allows information about the situation of the home and children to be shared with other family members and educational institutions. For example, it provides a shared platform that all family members can access. The input unit can also develop a system that supports cooperative parenting by working with educational institutions to share the situation of children. For example, school teachers and parents can share information to support children's development. The input unit can also add a function that allows family members and educational institutions to share information in real time to promote cooperative parenting. For example, information can be shared using a chat function or notification function. This can support cooperative parenting.

[0037] The input unit can automatically generate a child's growth record and album, allowing parents to easily look back on their child's growth. The input unit, for example, builds a system that automatically generates a child's growth record and album based on input information. For example, it automatically organizes photos and videos and creates a growth album. The input unit can also display a child's growth record in chronological order, allowing parents to easily look back on their child's growth. For example, it displays a monthly growth record in a graph or chart. The input unit can also add functions that parents can customize when automatically generating growth records and albums. For example, it provides a function to highlight specific events or memories. This allows parents to easily look back on their child's growth.

[0038] The suggestion unit can include specific examples of practice and success stories to make it easier for parents to put the child-rearing methods into practice. For example, the suggestion unit builds a system that includes specific examples of practice in the child-rearing methods it proposes to make it easier for parents to put the methods into practice. For example, it presents success stories and specific steps. The suggestion unit can also provide practical examples and success stories visually in the form of videos or illustrations to make it easier for parents to understand. For example, it can provide videos that recreate actual child-rearing scenes. The suggestion unit can also include success stories and advice from other parents in the child-rearing methods it proposes to make it easier for parents to put the methods into practice. For example, it can share success stories within the community. This makes it possible to propose child-rearing methods that are easy for parents to put into practice.

[0039] The suggestion unit can customize the suggestions to suit the parent's lifestyle and daily schedule, increasing feasibility. The suggestion unit, for example, builds a system that customizes child-rearing methods to suit the parent's lifestyle and daily schedule. For example, the suggestion unit makes suggestions that suit the parent's work hours and home routine. The suggestion unit can also adjust the suggested child-rearing methods so that they are easy to incorporate into the parent's schedule. For example, the suggestion unit can suggest methods that can be carried out in a short amount of time or methods that are suitable for a specific time period. The suggestion unit can also adjust the suggested content based on user input information to provide a child-rearing method that is customized to suit the parent's lifestyle. For example, the suggestion unit can suggest methods that suit the parent's hobbies and interests. This makes it possible to suggest child-rearing methods that suit the parent's lifestyle.

[0040] The suggestion unit can incorporate activities and games that parents and children can enjoy together to make parenting more enjoyable. For example, the suggestion unit builds a system that incorporates activities and activities that parents and children can enjoy together into the parenting methods it proposes. For example, it proposes games and activities that parents and children can play together. The suggestion unit can also provide activities and games that parents and children can enjoy visually using videos and illustrations to make them easier for parents to understand. For example, it can provide videos that recreate actual activity scenes. The suggestion unit can also make the parenting methods it proposes easier for parents to put into practice by including success stories and advice from other parents. For example, it can share success stories within the community. This makes it possible to propose parenting methods that parents and children can enjoy together.

[0041] The suggestion unit can provide visual content such as videos and animations to make it easier for parents to understand. For example, the suggestion unit builds a system that visually provides suggested child-rearing methods using videos and animations. For example, it provides videos that recreate actual child-rearing scenes. The suggestion unit can also use visual content to explain child-rearing methods in a way that is easy for parents to understand. For example, it can use animations to show specific steps. The suggestion unit can also use videos and animations to visually provide success stories and advice from other parents. For example, it can share success stories within the community in the form of videos. This makes it possible to suggest child-rearing methods that are easy for parents to understand.

[0042] The progress management unit can record in diary format, allowing parents to easily look back on their progress. For example, the progress management unit can build a system for recording parenting progress in diary format, allowing parents to easily look back on their progress. For example, daily parenting activities can be recorded using text and photos. The progress management unit can also display diary-format records in chronological order, allowing parents to intuitively understand their parenting progress. For example, it can display them in calendar format. The progress management unit can also automatically organize diary-format records, allowing parents to easily look back on specific periods or events. For example, a search function can be added. This allows parents to easily look back on their parenting progress.

[0043] The progress management unit can provide feedback together with positive messages to increase parents' motivation. For example, the progress management unit builds a system that provides feedback on parenting progress management together with positive messages to increase parents' motivation. For example, it displays messages of praise for achieved goals. The progress management unit can also incorporate positive messages into the feedback to help parents gain confidence in their parenting. For example, it provides success stories and words of encouragement. The progress management unit can also provide visual feedback to increase parents' motivation. For example, it displays achieved goals in graphs or charts. This can increase parents' motivation.

[0044] The progress management unit can visualize the results of progress management in graphs and charts, allowing parents to intuitively understand. For example, the progress management unit builds a system that visualizes the results of child-rearing progress management in graphs and charts, allowing parents to intuitively understand. For example, it displays achieved goals and progress in graphs. The progress management unit can also provide visual feedback so that parents can intuitively understand their child-rearing progress. For example, it displays progress in charts and infographics. The progress management unit can also add functions that parents can customize when visualizing the results of progress management. For example, it can create graphs that focus on specific periods or goals. This allows parents to intuitively understand their child-rearing progress.

[0045] The progress management unit can provide this information along with success stories and advice from other parents, thereby promoting information sharing between parents. For example, the progress management unit can build a system that provides feedback on child-rearing progress management along with success stories and advice from other parents. For example, success stories within a community can be shared. The progress management unit can also incorporate advice from other parents into the feedback to promote information sharing between parents. For example, advice from parents with the same concerns can be provided. The progress management unit can also provide other parents' success stories and advice visually to make it easier for parents to understand. For example, success stories can be provided as videos or illustrations. This can promote information sharing between parents.

[0046] Furthermore, the child-rearing support system is equipped with a community formation unit in which AI automatically organizes information exchanges, allowing parents to easily find the information they need. The community formation unit, for example, builds a system in which AI automatically organizes information exchanges within the community, allowing parents to easily find the information they need. For example, it analyzes the content of posts and tags related information. The community formation unit can also develop a system in which AI automatically classifies information so that parents can easily find the information they need. For example, it can organize questions and advice by category. The community formation unit can also automatically organize information within the community using AI, allowing parents to intuitively access it. For example, it can enhance the search function and quickly provide related information, allowing parents to easily find the information they need.

[0047] The Community Formation Department can use AI to moderate discussions and promote constructive debate. For example, the Community Formation Department can build a system in which AI moderates discussions within a community and promotes constructive discussions. For example, AI can automatically filter inappropriate comments. The Community Formation Department can also use AI to support the progress of discussions, allowing parents to have meaningful discussions. For example, it can organize the topics of discussion and provide related information. The Community Formation Department can also use AI to moderate discussions within a community, providing an environment in which parents can exchange opinions with peace of mind. For example, AI can monitor the rules of discussion and prevent violations. This can promote constructive discussions.

[0048] The community formation unit can subdivide communities by region or interest, allowing parents to join groups that they can more easily relate to. For example, the community formation unit can subdivide communities by region or interest, and build a system that allows parents to join groups that they can more easily relate to. For example, it can create groups by region or groups based on specific interests. The community formation unit can also develop a system that automatically recommends groups using AI so that parents can join groups that they can more easily relate to. For example, it can suggest appropriate groups based on information entered by parents. The community formation unit can also subdivide groups within a community so that parents can join groups that suit them. For example, it can provide groups based on specific child-rearing theories or groups that focus on specific issues. This allows parents to join groups that they can more easily relate to.

[0049] The community formation department can hold events and workshops regularly to deepen interactions between parents. For example, the community formation department can build a system to hold events and workshops regularly within the community to deepen interactions between parents. For example, it can plan online seminars and offline social gatherings. The community formation department can also develop a system that automatically provides information about events and workshops to promote interactions between parents. For example, it can recommend events based on parents' interests. The community formation department can also provide an environment where parents can exchange information and receive support through events and workshops. For example, it can host lectures by inviting experts and provide a forum for discussions between parents. This can deepen interactions between parents.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The suggestion unit can customize the suggestions to suit the parent's lifestyle and daily schedule, increasing feasibility. For example, the suggestion unit can make suggestions that are tailored to the parent's work hours and home routine. The suggestion unit can also adjust the suggested child-rearing methods to make them easier to incorporate into the parent's schedule. For example, the suggestion unit can suggest methods that can be done in a short amount of time or methods that are suitable for a specific time period. The suggestion unit can also adjust the suggested content based on information input by the user to provide a child-rearing method that is customized to suit the parent's lifestyle. For example, the suggestion unit can suggest methods that are tailored to the parent's hobbies and interests. This makes it possible to suggest child-rearing methods that suit the parent's lifestyle.

[0052] The database construction unit can be expanded to create a global database that includes parenting theories from different cultures and regions. For example, parenting books and papers from various countries can be translated and registered in the database. The database construction unit can also integrate global parenting theories into the database, allowing users to select parenting methods that suit their region or culture. For example, a filtering function for each region can be added. The database construction unit can also build a system that compares parenting theories from different cultures and analyzes similarities and differences. For example, it can propose parenting methods that take cultural background into account. This allows global parenting theories to be reflected.

[0053] The input unit can automatically collect information using voice input or image recognition technology, reducing the effort required for input. For example, a system can be built using voice input technology to automatically convert what parents say into text and collect information about the situation at home and their children. For example, information can be input using a smart speaker. The input unit can also use image recognition technology to develop a system that analyzes photos of the home and children and automatically grasps the situation. For example, a child's growth record can be extracted from the photos. The input unit can also combine voice input and image recognition to build a system that comprehensively collects information about the situation at home and their children. For example, it can simultaneously analyze what parents say and photos and integrate the information. This reduces the effort required for input.

[0054] The progress management unit can record in diary format, allowing parents to easily review their progress. For example, a system can be built that records parenting progress in diary format, allowing parents to easily review their progress. For example, daily parenting activities can be recorded using text and photos. The progress management unit can also display diary-format records in chronological order, allowing parents to intuitively understand their parenting progress. For example, they can be displayed in calendar format. The progress management unit can also automatically organize diary-format records, allowing parents to easily review specific periods or events. For example, a search function can be added. This allows parents to easily review their parenting progress.

[0055] The community formation department can use AI to moderate discussions and promote constructive debate. For example, a system can be built in which AI moderates discussions within a community and promotes constructive debate. For example, AI can automatically filter inappropriate comments. The community formation department can also use AI to support the progress of discussions and enable parents to have meaningful discussions. For example, it can organize the discussion topics and provide related information. The community formation department can also use AI to moderate discussions within a community, providing an environment in which parents can exchange opinions with peace of mind. For example, AI can monitor the rules of the discussion and prevent violations. This can promote constructive discussion.

[0056] The suggestion unit can incorporate activities and games that parents and children can enjoy together to make parenting more enjoyable. For example, a system can be constructed that incorporates activities and games that parents and children can enjoy together into the parenting methods it proposes. For example, it can propose games and activities that parents and children can play together. The suggestion unit can also provide activities and games that parents and children can enjoy together visually using videos and illustrations to make them easier for parents to understand. For example, it can provide videos that recreate actual activity scenes. The suggestion unit can also include success stories and advice from other parents in the parenting methods it proposes to make them easier for parents to put into practice. For example, it can share success stories within the community. This makes it possible to propose parenting methods that parents and children can enjoy together.

[0057] The processing flow of the first embodiment will be briefly explained below.

[0058] Step 1: The database construction department builds a database of parenting theories. For example, it builds a database containing parenting theories and practical examples collected from fields such as psychology, education, and sociology. It can also build a database that includes theories such as Montessori education, Piaget's developmental theory, and attachment theory. Step 2: The input section inputs information about the family and the child, such as the child's age, personality, interests, home environment, and parental educational policy. The user can also input prompts containing instructions on what they want the AI ​​to do. Step 3: The suggestion unit suggests optimal child-rearing methods based on the information entered by the input unit. For example, if a child is introverted, it can suggest methods to deepen the parent-child bond based on attachment theory. Or, if a child is curious, it can suggest methods to respect autonomy based on Montessori education.

[0059] (Example 2) A child-rearing support system according to an embodiment of the present invention is a system that uses AI technology to provide advice and support on child-rearing methods based on various child-rearing theories. As a result, the child-rearing support system can propose optimal child-rearing methods according to the circumstances of each family and child, manage progress, and provide feedback.

[0060] A child-rearing support system according to an embodiment includes a database construction unit, an input unit, and a suggestion unit. The database construction unit constructs a database of child-rearing theories. For example, the database constructs a database containing child-rearing theories and practical examples collected from fields such as psychology, pedagogy, and sociology. The database construction unit can also construct a database containing theories such as Montessori education, Piaget's developmental theory, and attachment theory. The input unit inputs information about the family and child. For example, the input information includes the child's age, personality, interests, home environment, and parental educational philosophy. The input unit can also input prompts containing instructions on what the user wants the AI ​​to do. The suggestion unit suggests optimal child-rearing methods based on the information input by the input unit. For example, if a child is introverted, the suggestion unit can suggest methods to deepen the parent-child bond based on attachment theory. Alternatively, if a child is curious, the suggestion unit can suggest methods to respect the child's independence based on Montessori education. This allows the child-rearing support system according to an embodiment to use AI to suggest optimal child-rearing methods based on child-rearing theories.

[0061] The database construction unit can add the latest research papers and academic presentations in real time, ensuring that the database always reflects the latest information. For example, the database construction unit could build a system that automatically collects the latest research papers and academic presentations and adds them to the database. For example, it could periodically crawl academic databases and automatically import new papers. The database construction unit could also analyze live streaming and recorded data from academic conferences to extract important information, so that the content of academic presentations can be updated in real time in the database. Furthermore, when adding the latest research results to the database, the database construction unit could automatically generate summaries using AI to make them easy to understand for users. For example, it could extract the key points of a paper and provide a concise summary. This would ensure that the latest parenting theories are always reflected.

[0062] The database construction unit can collect experimental data and statistical data to verify the effectiveness of each theory and evaluate the reliability of the theory. For example, the database construction unit collects experimental data and statistical data to verify the effectiveness of each parenting theory and registers it in a database. For example, it analyzes experimental results and survey data to evaluate the reliability of the theory. The database construction unit can also develop an algorithm to evaluate the effectiveness of each parenting theory based on the experimental data and statistical data. For example, it can build a system that prioritizes and proposes highly effective theories. The database construction unit can also visualize the empirical data to allow users to intuitively understand the effectiveness of each theory. For example, it can show the effects using graphs and charts. This makes it possible to evaluate the reliability of parenting theories.

[0063] The database construction unit can use the emotion estimation function to collect parents' emotional reactions to practical examples of parenting theories and reflect this in the selection of theories. For example, the database construction unit introduces the emotion estimation function to collect parents' emotional reactions to practical examples of parenting theories. For example, it analyzes parents' facial expressions and voices and calculates an emotion score. The database construction unit can also build a system that preferentially suggests parenting theories that parents have positive emotions about, based on the emotion estimation data. For example, it extracts theories with high emotion scores from the database. The database construction unit can also analyze parents' emotional reaction data and reflect this in the selection of parenting theories. For example, it adds a filtering function to exclude theories with a high number of negative emotions. This makes it possible to select parenting theories taking parents' emotional reactions into consideration.

[0064] The database construction unit can be expanded to create a global database that includes parenting theories from different cultural spheres and regions. For example, the database construction unit collects parenting theories from different cultural spheres and regions and adds them to the database. For example, it translates parenting books and papers from various countries and registers them in the database. The database construction unit can also integrate global parenting theories into the database, allowing users to select parenting methods that suit their region or culture. For example, it can add a filtering function by region. The database construction unit can also build a system that compares parenting theories from different cultural spheres and analyzes similarities and differences. For example, it can propose parenting methods that take cultural background into account. This makes it possible to reflect global parenting theories.

[0065] The database construction unit can integrate not only parenting theory but also information on children's health and nutrition to provide comprehensive parenting support. For example, the database construction unit can integrate information on children's health and nutrition in addition to parenting theory into the database. For example, it can collect information by referring to specialized books on nutrition and pediatrics. The database construction unit can also build a system that provides comprehensive parenting support based on the health and nutrition information. For example, it can propose meal plans and health management advice. The database construction unit can also integrate parenting theory and health and nutrition information to build a database that users can access centrally. For example, it can enhance the search function to quickly provide necessary information. This makes it possible to provide comprehensive parenting support.

[0066] The database construction unit can use the emotion estimation function to take parents' emotions into consideration when selecting a parenting theory, and prioritize suggesting theories that give parents the most sense of security. The database construction unit, for example, uses the emotion estimation function to analyze parents' emotions in real time when selecting a parenting theory. For example, it calculates an emotion score based on the parents' facial expressions and voice. The database construction unit can also build a system that prioritizes suggesting parenting theories that give parents the most sense of security. For example, it extracts and suggests theories with high emotion scores from the database. The database construction unit can also propose parenting theories customized to match the parents' emotions based on the emotion estimation data. For example, it adjusts the content of the proposal according to the parents' emotional state. This makes it possible to prioritize suggesting parenting theories that give parents a sense of security.

[0067] The input unit can automatically collect information using voice input or image recognition technology, reducing the effort required for input. For example, the input unit can use voice input technology to automatically convert what parents say into text and build a system that collects information about the home and their children. For example, a smart speaker can be used to input information. The input unit can also use image recognition technology to develop a system that analyzes photos of the home and children and automatically grasps the situation. For example, a child's growth record can be extracted from the photos. The input unit can also combine voice input and image recognition to build a system that comprehensively collects information about the home and children. For example, the input unit can simultaneously analyze what parents say and photos and integrate the information. This reduces the effort required for input.

[0068] The input unit can add a reminder function for periodic updates, so that the latest information can always be maintained. For example, the input unit can add a reminder function for periodically updating the status of the home and child, so that parents do not forget to enter information. For example, the notification function of a smartphone can be used. The input unit can also use the reminder function to build a system in which parents periodically report on their child's growth and changes in the home. For example, a reminder can be set to enter monthly growth records. The input unit can also enhance the reminder function and develop a system that automatically analyzes the information entered by parents and suggests necessary updates. For example, the next update content can be suggested based on the input content. This allows the latest information to always be maintained.

[0069] The input unit can use the emotion estimation function to analyze the parent's emotions at the time of input and provide advice to reduce stress and anxiety. The input unit, for example, uses the emotion estimation function to build a system that analyzes the parent's emotions at the time of input in real time and provides advice to reduce stress and anxiety. For example, the input unit analyzes the parent's facial expressions and voice and calculates an emotion score. The input unit can also develop a system that provides customized advice according to the parent's emotional state. For example, if stress is high, the input unit can suggest relaxation methods. The input unit can also build a system that analyzes the parent's emotions based on the emotion estimation data and provides long-term stress management and mental health support. For example, the input unit performs regular emotion checks and advice. This makes it possible to provide advice to reduce the parent's stress and anxiety.

[0070] The input unit can add a function that allows sharing with other family members and educational institutions to support cooperative parenting. The input unit, for example, builds a system that allows information about the situation of the home and children to be shared with other family members and educational institutions. For example, it provides a shared platform that all family members can access. The input unit can also develop a system that supports cooperative parenting by working with educational institutions to share the situation of children. For example, school teachers and parents can share information to support children's development. The input unit can also add a function that allows family members and educational institutions to share information in real time to promote cooperative parenting. For example, information can be shared using a chat function or notification function. This can support cooperative parenting.

[0071] The input unit can automatically generate a child's growth record and album, allowing parents to easily look back on their child's growth. The input unit, for example, builds a system that automatically generates a child's growth record and album based on input information. For example, it automatically organizes photos and videos and creates a growth album. The input unit can also display a child's growth record in chronological order, allowing parents to easily look back on their child's growth. For example, it displays a monthly growth record in a graph or chart. The input unit can also add functions that parents can customize when automatically generating growth records and albums. For example, it provides a function to highlight specific events or memories. This allows parents to easily look back on their child's growth.

[0072] The input unit can use the emotion estimation function to analyze the parent's emotions based on the input information and provide customized parenting advice according to the emotions. The input unit, for example, uses the emotion estimation function to analyze the parent's emotions based on the input information in real time and build a system that provides customized parenting advice. For example, the input unit analyzes the parent's facial expressions and voice and calculates an emotion score. The input unit can also develop a system that provides parenting advice according to the parent's emotional state. For example, if stress is high, the input unit can suggest relaxation methods. The input unit can also build a system that analyzes the parent's emotions based on the emotion estimation data and provides long-term parenting support. For example, the input unit performs regular emotion checks and advice. This makes it possible to provide customized parenting advice according to the parent's emotions.

[0073] The suggestion unit can include specific examples of practice and success stories to make it easier for parents to put the child-rearing methods into practice. For example, the suggestion unit builds a system that includes specific examples of practice in the child-rearing methods it proposes to make it easier for parents to put the methods into practice. For example, it presents success stories and specific steps. The suggestion unit can also provide practical examples and success stories visually in the form of videos or illustrations to make it easier for parents to understand. For example, it can provide videos that recreate actual child-rearing scenes. The suggestion unit can also include success stories and advice from other parents in the child-rearing methods it proposes to make it easier for parents to put the methods into practice. For example, it can share success stories within the community. This makes it possible to propose child-rearing methods that are easy for parents to put into practice.

[0074] The suggestion unit can customize the suggestions to suit the parent's lifestyle and daily schedule, increasing feasibility. The suggestion unit, for example, builds a system that customizes child-rearing methods to suit the parent's lifestyle and daily schedule. For example, the suggestion unit makes suggestions that suit the parent's work hours and home routine. The suggestion unit can also adjust the suggested child-rearing methods so that they are easy to incorporate into the parent's schedule. For example, the suggestion unit can suggest methods that can be carried out in a short amount of time or methods that are suitable for a specific time period. The suggestion unit can also adjust the suggested content based on user input information to provide a child-rearing method that is customized to suit the parent's lifestyle. For example, the suggestion unit can suggest methods that suit the parent's hobbies and interests. This makes it possible to suggest child-rearing methods that suit the parent's lifestyle.

[0075] The suggestion unit can use the emotion estimation function to collect parents' emotional reactions to the proposed parenting methods and continuously improve the content of the suggestions. For example, the suggestion unit uses the emotion estimation function to build a system that collects parents' emotional reactions to the proposed parenting methods in real time. For example, the suggestion unit analyzes parents' facial expressions and voices and calculates an emotion score. The suggestion unit can also develop a system that continuously improves the content of the suggestions based on the parents' emotional reaction data. For example, the suggestion unit can modify suggestions that contain a lot of negative emotions and strengthen suggestions that contain a lot of positive emotions. The suggestion unit can also build a system that provides customized parenting methods based on the emotion estimation data. For example, the suggestion content can be adjusted to match the parents' emotional state. This allows the content of the suggestions to be continuously improved based on the parents' emotional reactions.

[0076] The suggestion unit can incorporate activities and games that parents and children can enjoy together to make parenting more enjoyable. For example, the suggestion unit builds a system that incorporates activities and activities that parents and children can enjoy together into the parenting methods it proposes. For example, it proposes games and activities that parents and children can play together. The suggestion unit can also provide activities and games that parents and children can enjoy visually using videos and illustrations to make them easier for parents to understand. For example, it can provide videos that recreate actual activity scenes. The suggestion unit can also make the parenting methods it proposes easier for parents to put into practice by including success stories and advice from other parents. For example, it can share success stories within the community. This makes it possible to propose parenting methods that parents and children can enjoy together.

[0077] The suggestion unit can provide visual content such as videos and animations to make it easier for parents to understand. For example, the suggestion unit builds a system that visually provides suggested child-rearing methods using videos and animations. For example, it provides videos that recreate actual child-rearing scenes. The suggestion unit can also use visual content to explain child-rearing methods in a way that is easy for parents to understand. For example, it can use animations to show specific steps. The suggestion unit can also use videos and animations to visually provide success stories and advice from other parents. For example, it can share success stories within the community in the form of videos. This makes it possible to suggest child-rearing methods that are easy for parents to understand.

[0078] The suggestion unit can use the emotion estimation function to monitor parents' emotions regarding the proposed parenting methods in real time and instantly revise the suggestions as necessary. For example, the suggestion unit can use the emotion estimation function to build a system that monitors parents' emotions regarding the proposed parenting methods in real time. For example, the suggestion unit can analyze the parents' facial expressions and voices and calculate an emotion score. The suggestion unit can also develop a system that instantly revises the suggestions based on the parents' emotional response data. For example, the suggestion unit can revise suggestions that contain a lot of negative emotions and strengthen suggestions that contain a lot of positive emotions. The suggestion unit can also build a system that provides customized parenting methods based on the parents' emotions based on the emotion estimation data. For example, the suggestion unit can adjust the suggestions to match the parents' emotional state. This makes it possible to monitor parents' emotions in real time and instantly revise the suggestions.

[0079] The progress management unit can record in diary format, allowing parents to easily look back on their progress. For example, the progress management unit can build a system for recording parenting progress in diary format, allowing parents to easily look back on their progress. For example, daily parenting activities can be recorded using text and photos. The progress management unit can also display diary-format records in chronological order, allowing parents to intuitively understand their parenting progress. For example, it can display them in calendar format. The progress management unit can also automatically organize diary-format records, allowing parents to easily look back on specific periods or events. For example, a search function can be added. This allows parents to easily look back on their parenting progress.

[0080] The progress management unit can provide feedback together with positive messages to increase parents' motivation. For example, the progress management unit builds a system that provides feedback on parenting progress management together with positive messages to increase parents' motivation. For example, it displays messages of praise for achieved goals. The progress management unit can also incorporate positive messages into the feedback to help parents gain confidence in their parenting. For example, it provides success stories and words of encouragement. The progress management unit can also provide visual feedback to increase parents' motivation. For example, it displays achieved goals in graphs or charts. This can increase parents' motivation.

[0081] The progress management unit can use the emotion estimation function to analyze the parent's emotions during progress management and provide support to reduce stress and anxiety. The progress management unit, for example, uses the emotion estimation function to analyze the parent's emotions during progress management in real time and build a system that provides support to reduce stress and anxiety. For example, the progress management unit analyzes the parent's facial expressions and voice and calculates an emotion score. The progress management unit can also develop a system that provides customized support according to the parent's emotional state. For example, if stress is high, the system can suggest relaxation methods. The progress management unit can also analyze the parent's emotions based on the emotion estimation data and build a system that provides long-term stress management and mental health support. For example, the system can perform regular emotion checks and advice. This can provide support to reduce the parent's stress and anxiety.

[0082] The progress management unit can visualize the results of progress management in graphs and charts, allowing parents to intuitively understand. For example, the progress management unit builds a system that visualizes the results of child-rearing progress management in graphs and charts, allowing parents to intuitively understand. For example, it displays achieved goals and progress in graphs. The progress management unit can also provide visual feedback so that parents can intuitively understand their child-rearing progress. For example, it displays progress in charts and infographics. The progress management unit can also add functions that parents can customize when visualizing the results of progress management. For example, it can create graphs that focus on specific periods or goals. This allows parents to intuitively understand their child-rearing progress.

[0083] The progress management unit can provide this information along with success stories and advice from other parents, thereby promoting information sharing between parents. For example, the progress management unit can build a system that provides feedback on child-rearing progress management along with success stories and advice from other parents. For example, success stories within a community can be shared. The progress management unit can also incorporate advice from other parents into the feedback to promote information sharing between parents. For example, advice from parents with the same concerns can be provided. The progress management unit can also provide other parents' success stories and advice visually to make it easier for parents to understand. For example, success stories can be provided as videos or illustrations. This can promote information sharing between parents.

[0084] The progress management unit can use the emotion estimation function to monitor the parent's emotions during progress management in real time and provide feedback according to the emotions. The progress management unit, for example, uses the emotion estimation function to build a system that monitors the parent's emotions during progress management in real time. For example, it analyzes the parent's facial expressions and voice and calculates an emotion score. The progress management unit can also develop a system that provides feedback according to the parent's emotions based on the parent's emotional response data. For example, it can suggest relaxation methods if the parent is under high stress. The progress management unit can also build a system that analyzes the parent's emotions based on the emotion estimation data and provides long-term stress management and mental health support. For example, it can perform regular emotion checks and advice. This makes it possible to provide feedback according to the parent's emotions.

[0085] Furthermore, the child-rearing support system is equipped with a community formation unit in which AI automatically organizes information exchanges, allowing parents to easily find the information they need. The community formation unit, for example, builds a system in which AI automatically organizes information exchanges within the community, allowing parents to easily find the information they need. For example, it analyzes the content of posts and tags related information. The community formation unit can also develop a system in which AI automatically classifies information so that parents can easily find the information they need. For example, it can organize questions and advice by category. The community formation unit can also automatically organize information within the community using AI, allowing parents to intuitively access it. For example, it can enhance the search function and quickly provide related information, allowing parents to easily find the information they need.

[0086] The Community Formation Department can use AI to moderate discussions and promote constructive debate. For example, the Community Formation Department can build a system in which AI moderates discussions within a community and promotes constructive discussions. For example, AI can automatically filter inappropriate comments. The Community Formation Department can also use AI to support the progress of discussions, allowing parents to have meaningful discussions. For example, it can organize the topics of discussion and provide related information. The Community Formation Department can also use AI to moderate discussions within a community, providing an environment in which parents can exchange opinions with peace of mind. For example, AI can monitor the rules of discussion and prevent violations. This can promote constructive discussions.

[0087] The community formation unit can use the emotion estimation function to analyze the emotions of parents in the community and provide support and advice according to those emotions. For example, the community formation unit uses the emotion estimation function to analyze the emotions of parents in the community in real time and build a system that provides support and advice according to those emotions. For example, the community formation unit analyzes the parents' facial expressions and voices and calculates an emotion score. The community formation unit can also develop a system that provides customized support and advice according to the parents' emotional state. For example, it can suggest relaxation methods when stress is high. The community formation unit can also build a system that analyzes parents' emotions based on the emotion estimation data and provides long-term mental health support. For example, it can perform regular emotion checks and advice. This makes it possible to provide support and advice according to the parents' emotions.

[0088] The community formation unit can subdivide communities by region or interest, allowing parents to join groups that they can more easily relate to. For example, the community formation unit can subdivide communities by region or interest, and build a system that allows parents to join groups that they can more easily relate to. For example, it can create groups by region or groups based on specific interests. The community formation unit can also develop a system that automatically recommends groups using AI so that parents can join groups that they can more easily relate to. For example, it can suggest appropriate groups based on information entered by parents. The community formation unit can also subdivide groups within a community so that parents can join groups that suit them. For example, it can provide groups based on specific child-rearing theories or groups that focus on specific issues. This allows parents to join groups that they can more easily relate to.

[0089] The community formation department can hold events and workshops regularly to deepen interactions between parents. For example, the community formation department can build a system to hold events and workshops regularly within the community to deepen interactions between parents. For example, it can plan online seminars and offline social gatherings. The community formation department can also develop a system that automatically provides information about events and workshops to promote interactions between parents. For example, it can recommend events based on parents' interests. The community formation department can also provide an environment where parents can exchange information and receive support through events and workshops. For example, it can host lectures by inviting experts and provide a forum for discussions between parents. This can deepen interactions between parents.

[0090] The community formation unit can use the emotion estimation function to monitor the emotions of parents in the community in real time and provide events and support according to their emotions. For example, the community formation unit can use the emotion estimation function to build a system that monitors the emotions of parents in the community in real time. For example, it can analyze the parents' facial expressions and voices and calculate an emotion score. The community formation unit can also develop a system that provides events and support according to their emotions based on the parents' emotional response data. For example, it can suggest a relaxation event if the parents are highly stressed. The community formation unit can also build a system that analyzes the parents' emotions based on the emotion estimation data and provides long-term mental health support. For example, it can perform regular emotion checks and advice. This makes it possible to provide events and support according to the parents' emotions.

[0091] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0092] The suggestion unit can customize the suggestions to suit the parent's lifestyle and daily schedule, increasing feasibility. For example, the suggestion unit can make suggestions that are tailored to the parent's work hours and home routine. The suggestion unit can also adjust the suggested child-rearing methods to make them easier to incorporate into the parent's schedule. For example, the suggestion unit can suggest methods that can be done in a short amount of time or methods that are suitable for a specific time period. The suggestion unit can also adjust the suggested content based on information input by the user to provide a child-rearing method that is customized to suit the parent's lifestyle. For example, the suggestion unit can suggest methods that are tailored to the parent's hobbies and interests. This makes it possible to suggest child-rearing methods that suit the parent's lifestyle.

[0093] The database construction unit can be expanded to create a global database that includes parenting theories from different cultures and regions. For example, parenting books and papers from various countries can be translated and registered in the database. The database construction unit can also integrate global parenting theories into the database, allowing users to select parenting methods that suit their region or culture. For example, a filtering function for each region can be added. The database construction unit can also build a system that compares parenting theories from different cultures and analyzes similarities and differences. For example, it can propose parenting methods that take cultural background into account. This allows global parenting theories to be reflected.

[0094] The input unit can automatically collect information using voice input or image recognition technology, reducing the effort required for input. For example, a system can be built using voice input technology to automatically convert what parents say into text and collect information about the situation at home and their children. For example, information can be input using a smart speaker. The input unit can also use image recognition technology to develop a system that analyzes photos of the home and children and automatically grasps the situation. For example, a child's growth record can be extracted from the photos. The input unit can also combine voice input and image recognition to build a system that comprehensively collects information about the situation at home and their children. For example, it can simultaneously analyze what parents say and photos and integrate the information. This reduces the effort required for input.

[0095] The progress management unit can record in diary format, allowing parents to easily review their progress. For example, a system can be built that records parenting progress in diary format, allowing parents to easily review their progress. For example, daily parenting activities can be recorded using text and photos. The progress management unit can also display diary-format records in chronological order, allowing parents to intuitively understand their parenting progress. For example, they can be displayed in calendar format. The progress management unit can also automatically organize diary-format records, allowing parents to easily review specific periods or events. For example, a search function can be added. This allows parents to easily review their parenting progress.

[0096] The community formation department can use AI to moderate discussions and promote constructive debate. For example, a system can be built in which AI moderates discussions within a community and promotes constructive debate. For example, AI can automatically filter inappropriate comments. The community formation department can also use AI to support the progress of discussions and enable parents to have meaningful discussions. For example, it can organize the discussion topics and provide related information. The community formation department can also use AI to moderate discussions within a community, providing an environment in which parents can exchange opinions with peace of mind. For example, AI can monitor the rules of the discussion and prevent violations. This can promote constructive discussion.

[0097] The suggestion unit can use the emotion estimation function to collect parents' emotional reactions to the proposed parenting methods and continuously improve the content of the suggestions. For example, the emotion estimation function can be used to build a system that collects parents' emotional reactions to proposed parenting methods in real time. For example, the emotion estimation function can analyze parents' facial expressions and voices to calculate an emotion score. The suggestion unit can also develop a system that continuously improves the content of the suggestions based on the parents' emotional reaction data. For example, it can modify suggestions that contain a lot of negative emotions and strengthen suggestions that contain a lot of positive emotions. The suggestion unit can also build a system that provides parenting methods customized according to the parents' emotions based on the emotion estimation data. For example, it can adjust the content of the suggestions to match the parents' emotional state. This allows the content of the suggestions to be continuously improved based on the parents' emotional reactions.

[0098] The input unit can use the emotion estimation function to analyze the parent's emotions at the time of input and provide advice to reduce stress and anxiety. For example, a system can be built using the emotion estimation function to analyze the parent's emotions at the time of input in real time and provide advice to reduce stress and anxiety. For example, the emotion estimation function can analyze the parent's facial expressions and voice and calculate an emotion score. The input unit can also develop a system that provides customized advice according to the parent's emotional state. For example, if stress is high, it can suggest relaxation methods. The input unit can also build a system that analyzes the parent's emotions based on the emotion estimation data and provides long-term stress management and mental health support. For example, it can perform regular emotion checks and advice. This can provide advice to reduce the parent's stress and anxiety.

[0099] The progress management unit can use the emotion estimation function to analyze the parent's emotions during progress management and provide support to reduce stress and anxiety. For example, a system can be built using the emotion estimation function to analyze the parent's emotions during progress management in real time and provide support to reduce stress and anxiety. For example, the emotion estimation function can analyze the parent's facial expressions and voice and calculate an emotion score. The progress management unit can also develop a system that provides customized support according to the parent's emotional state. For example, if stress is high, it can suggest relaxation methods. The progress management unit can also build a system that analyzes the parent's emotions based on the emotion estimation data and provides long-term stress management and mental health support. For example, it can perform regular emotion checks and advice. This can provide support to reduce the parent's stress and anxiety.

[0100] The community building unit can use the emotion estimation function to analyze the emotions of parents in the community and provide support and advice according to their emotions. For example, the emotion estimation function can be used to build a system that analyzes the emotions of parents in the community in real time and provides support and advice according to their emotions. For example, the emotion estimation function can analyze the parents' facial expressions and voices and calculate an emotion score. The community building unit can also develop a system that provides customized support and advice according to the parents' emotional state. For example, it can suggest relaxation methods when stress is high. The community building unit can also build a system that analyzes parents' emotions based on the emotion estimation data and provides long-term mental health support. For example, it can perform periodic emotion checks and advice. This makes it possible to provide support and advice according to the parents' emotions.

[0101] The suggestion unit can incorporate activities and games that parents and children can enjoy together to make parenting more enjoyable. For example, a system can be constructed that incorporates activities and games that parents and children can enjoy together into the parenting methods it proposes. For example, it can propose games and activities that parents and children can play together. The suggestion unit can also provide activities and games that parents and children can enjoy together visually using videos and illustrations to make them easier for parents to understand. For example, it can provide videos that recreate actual activity scenes. The suggestion unit can also include success stories and advice from other parents in the parenting methods it proposes to make them easier for parents to put into practice. For example, it can share success stories within the community. This makes it possible to propose parenting methods that parents and children can enjoy together.

[0102] The processing flow of the second embodiment will be briefly explained below.

[0103] Step 1: The database construction department builds a database of parenting theories. For example, it builds a database containing parenting theories and practical examples collected from fields such as psychology, education, and sociology. It can also build a database that includes theories such as Montessori education, Piaget's developmental theory, and attachment theory. Step 2: The input section inputs information about the family and the child, such as the child's age, personality, interests, home environment, and parental educational policy. The user can also input prompts containing instructions on what they want the AI ​​to do. Step 3: The suggestion unit suggests optimal child-rearing methods based on the information entered by the input unit. For example, if a child is introverted, it can suggest methods to deepen the parent-child bond based on attachment theory. Or, if a child is curious, it can suggest methods to respect autonomy based on Montessori education.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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).

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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 AI 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.

[0121] 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.

[0122] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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).

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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 AI 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.

[0136] 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.

[0137] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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).

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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 also 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 perform processing similar to that of the specific processing unit 290 using these models.

[0149] 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.

[0150] 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.

[0151] 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 AI 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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).

[0157] 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.

[0158] 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."

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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]

[0171] 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. A database construction department that builds a database of child-rearing theories; An input section for inputting the situation of the family and children; a suggestion unit that suggests an optimal child-rearing method based on the information input by the input unit. A system characterized by:

2. The database construction unit Add the latest research papers and conference presentations in real time to keep the information up to date.

2. The system of claim 1.

3. The database construction unit Collect experimental and statistical data to verify the effectiveness of each theory and evaluate its reliability.

2. The system of claim 1.

4. The database construction unit Collecting parents' emotional responses to examples of child-rearing theories in practice and reflecting them in the selection of theories 2. The system of claim 1.

5. The database construction unit Expanding the database to a global one that includes child-rearing theories from different cultures and regions 2. The system of claim 1.

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