System

Abstract

An object of a system according to an embodiment is to reduce erroneous registration of data at the time of registration of an individual number card.SOLUTION: A system includes an automatic input support unit and a registration support unit. The automatic input support unit analyzes information input by the user and supports automatic input of accurate data. The registration support unit provides interactive support when the user performs a registration procedure.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, there was a problem that many data errors occurred when manually registering My Number cards.

[0005] The system according to the embodiment aims to reduce erroneous data registration when registering a My Number card. [Means for solving the problem]

[0006] The system according to the embodiment includes an automatic input support unit and a registration support unit. The automatic input support unit analyzes information entered by a user and supports the user in automatically entering accurate data. The registration support unit interactively supports the user when performing the registration procedure. [Effects of the Invention]

[0007] The system according to the embodiment can reduce erroneous data registration when registering a My Number card. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The My Number Card registration support system according to an embodiment of the present invention is a system that combines automatic input support using generation AI with registration support by an AI chatbot. As a result, the My Number Card registration support system can reduce manual registration errors and improve data accuracy.

[0029] The My Number Card registration support system according to the embodiment includes an automatic input support unit and a registration support unit. The automatic input support unit analyzes information entered by a user and automatically supports the user in entering accurate data. For example, the generation AI checks the information entered by the user in real time to ensure there are no errors. The generation AI can also generate accurate data based on the information entered by the user. For example, if the generation AI instructs the user to "enter your name," and the user enters "Yamada Taro," the AI ​​checks whether the data is correct and suggests corrections as necessary. The registration support unit provides interactive support to the user during the registration process. For example, if the user has questions during the registration process, the AI ​​chatbot can answer questions in real time and provide appropriate advice. The AI ​​chatbot can also provide specific instructions in response to user questions. For example, in response to a question such as "I don't know how to enter my address," the AI ​​chatbot can provide specific instructions such as "Please enter the address starting with the city, ward, town, or village name." This allows the My Number Card registration support system according to the embodiment to reduce manual registration errors and improve data accuracy.

[0030] The automatic input assistance unit can refer to the user's past input history, learn input error patterns, and predict and correct them. For example, the generation AI in the automatic input assistance unit analyzes the user's past input history and learns frequently occurring input error patterns. For example, it identifies trends in specific character strings and typos and automatically suggests corrections as the user inputs. The automatic input assistance unit also predicts input errors based on data previously entered by the user. For example, if a user who previously entered "Yamada Taro" mistakenly enters "Yamada Taro" when attempting to enter "Yamada Taro," the generation AI automatically suggests a correction. The automatic input assistance unit also predicts and corrects future input errors by referring to the user's input history and learning input error patterns. For example, if a user mistakenly enters "Tokyo" when attempting to enter "Tokyo," the generation AI automatically suggests a correction. This improves data accuracy by predicting and correcting input errors based on past input history.

[0031] The automatic input assistance unit can detect a user's input speed and typing habits, identify areas where input errors are likely to occur, and issue a warning. For example, the automatic input assistance unit uses a generation AI to analyze a user's input speed and identify areas where input speed changes suddenly. For example, it can detect areas where input is made faster than normal, determine that there is a high possibility of an input error, and display a warning. The automatic input assistance unit can also learn a user's typing habits and detect specific key combinations and input patterns. For example, if a user has a habit of pressing specific keys repeatedly, it can identify areas where there is a high possibility of an input error based on that pattern and issue a warning. The automatic input assistance unit can also analyze a user's input speed and typing habits in real time and identify areas where there is a high possibility of an input error. For example, it can detect areas where input is made slower than normal, determine that there is a high possibility of an input error, and issue a warning. This allows for improved data accuracy by identifying and warning about potential input errors based on input speed and typing habits.

[0032] The automatic input support unit supports voice input and handwriting input, thereby improving user convenience. In the automatic input support unit, for example, a generation AI supports voice input and automatically converts what the user inputs by voice into text. For example, if a user inputs "Yamada Taro" by voice, the generation AI converts the voice into text and inputs it. The automatic input support unit also supports handwriting input and automatically converts what the user inputs by hand into text. For example, if a user inputs "Yamada Taro" by hand, the generation AI converts the handwritten characters into text and inputs it. The automatic input support unit also supports voice input and handwriting input, thereby improving user convenience. For example, it converts what the user inputs by voice or handwriting into text in real time, reducing input errors. This supports voice input and handwriting input, thereby improving user convenience.

[0033] The automatic input support unit can link with other public databases to cross-check the accuracy of the input content. For example, the generation AI in the automatic input support unit links with other public databases to cross-check the accuracy of the input name and address. For example, it verifies whether the input content is correct by comparing it with the Basic Resident Register or family register database. The automatic input support unit also cross-checks the accuracy of the input content in real time by linking with other public databases. For example, it verifies whether the address entered by the user actually exists. The automatic input support unit also prevents incorrect input by cross-checking the accuracy of the input content with other public databases. For example, it verifies whether the name entered by the user is correct. In this way, incorrect input can be prevented by cross-checking the accuracy of the input content in linkage with other public databases.

[0034] The registration support unit can provide more accurate advice by referring to the user's past question history. For example, the registration support unit allows an AI chatbot to analyze a user's past question history and learn frequently asked questions. For example, if a user who previously asked, "I don't know how to enter my address," asks a similar question again, the registration support unit can provide more accurate advice. The registration support unit also allows the AI ​​chatbot to provide accurate advice based on the user's past question history. For example, if a user who previously asked, "I don't know how to enter my name," asks the same question again, the registration support unit can provide specific input methods. The registration support unit also allows the AI ​​chatbot to provide accurate advice by referring to the user's past question history, quickly resolving the user's questions. For example, if a user who previously asked, "I don't know how to enter my date of birth," asks the same question again, the registration support unit can provide specific input methods. This allows the AI ​​chatbot to provide accurate advice based on the user's past question history, quickly resolving the user's questions.

[0035] The registration support unit can provide answers using appropriate expressions, taking into account the user's language and cultural background. The registration support unit, for example, has an AI chatbot analyze the user's language and cultural background and respond using appropriate expressions. For example, for a user whose native language is English, the AI ​​chatbot provides answers in English. The registration support unit also takes into account the user's cultural background and has the AI ​​chatbot respond using appropriate expressions. For example, for a user who is familiar with Japanese culture, the AI ​​chatbot provides answers using specific examples related to Japanese culture. The registration support unit also deepens the user's understanding by having the AI ​​chatbot respond using appropriate expressions, taking into account the user's language and cultural background. For example, for a user from a different cultural sphere, the AI ​​chatbot provides answers using expressions that are appropriate for that culture. This allows the user's understanding to be deepened by providing answers using appropriate expressions, taking into account the user's language and cultural background.

[0036] The registration support unit can add video calling and screen sharing functions to provide visual support. For example, the registration support unit adds a video calling function to the AI ​​chatbot to provide visual support when the user asks a question. For example, the user can ask a question while sharing their screen, and the AI ​​chatbot can show specific operation procedures. The registration support unit also adds a screen sharing function, and the AI ​​chatbot can provide support by checking the user's screen in real time. For example, when a user asks how to operate an input form, the AI ​​chatbot can share the screen and show specific operation procedures. The registration support unit also adds a video calling and screen sharing function to the AI ​​chatbot to provide visual support and quickly resolve user questions. For example, when a user asks a question about input content, the AI ​​chatbot can share the screen and show specific input procedures. In this way, adding the video calling and screen sharing functions can provide visual support and quickly resolve user questions.

[0037] The registration support unit can create a database of questions and answers from other users and provide it as an FAQ. For example, the registration support unit may use an AI chatbot to create a database of questions and answers from other users and provide it as an FAQ. For example, the registration support unit may compile questions asked by many users in the past and display them as an FAQ. The registration support unit may also create a database of questions and answers from other users, allowing the AI ​​chatbot to quickly provide answers. For example, when a user asks, "I don't know how to enter my address," an appropriate answer may be provided from past FAQs. The registration support unit may also create a database of questions and answers from other users and provide it as an FAQ, allowing the AI ​​chatbot to quickly resolve user questions. For example, when a user asks, "I don't know how to enter my name," an appropriate answer may be provided from past FAQs. In this way, the AI ​​chatbot may create a database of questions and answers from other users and provide it as an FAQ, thereby quickly resolving user questions.

[0038] The automatic input support unit can refer to multiple data sources and check the consistency of the data. In the automatic input support unit, for example, the generation AI refers to multiple data sources and checks the consistency of the entered data. For example, it checks whether the input content is correct by comparing it with the Basic Resident Register or family register database. In addition, the automatic input support unit refers to multiple data sources in real time when checking the accuracy of data. For example, it checks whether the address entered by the user actually exists. In addition, the automatic input support unit prevents incorrect input by having the generation AI refer to multiple data sources and check the consistency of the data. For example, it checks whether the name entered by the user is correct. In this way, by checking the consistency of the data by referring to multiple data sources, the accuracy of the data can be improved.

[0039] The automatic input assistance unit can track the history of data changes and record the reasons for the changes. In the automatic input assistance unit, for example, the generation AI tracks the history of data changes and records the reasons for the changes. For example, when a user changes their address, the reason is recorded and saved in a database. Furthermore, when checking the accuracy of data, the automatic input assistance unit tracks the history of changes and records the reasons for the changes, thereby improving the reliability of the data. For example, when a user changes their name, the reason is recorded. Furthermore, the automatic input assistance unit maintains the accuracy of the data by tracking the history of data changes and recording the reasons for the changes. For example, when a user changes their date of birth, the reason is recorded. In this way, by tracking the history of data changes and recording the reasons for the changes, the reliability of the data can be improved.

[0040] The automatic input assistance unit can detect outliers by comparing with other users' data. For example, the generation AI of the automatic input assistance unit compares data with other users' data and detects outliers. For example, it compares data with data from other users living in the same area to detect abnormal address entries. The automatic input assistance unit also detects outliers by comparing with data from other users when checking the accuracy of data. For example, it compares with data from other users in the same age group to detect abnormal date of birth entries. The automatic input assistance unit also prevents incorrect input by comparing with data from other users and detecting outliers. For example, it compares with data from other users with the same surname to detect abnormal name entries. In this way, incorrect input can be prevented by comparing with data from other users to detect abnormal values.

[0041] The automatic input support unit can automatically standardize the data input format and format. For example, the generation AI automatically standardizes the data input format and format. For example, the input format for addresses is standardized to the order of "prefecture, city, ward, town, village, street address." The automatic input support unit also prevents incorrect input by automatically standardizing the input format and format when checking the accuracy of data. For example, the input format for names is standardized to the order of "last name, first name." The automatic input support unit also maintains the accuracy of data by having the generation AI automatically standardize the data input format and format. For example, the input format for dates of birth is standardized to the order of "year, month, day." This automatically standardizes the data input format and format, thereby maintaining the accuracy of data.

[0042] The automatic input support unit can strengthen data encryption and access control. In the automatic input support unit, for example, the generation AI encrypts data to reduce the risk of information leakage. For example, the user's personal information is encrypted and stored. The automatic input support unit also strengthens access control, and the generation AI reduces the risk of information leakage. For example, it ensures that only specific users can access the data. The automatic input support unit also reduces the risk of information leakage by having the generation AI strengthen data encryption and access control. For example, it periodically changes the data encryption key. This strengthens data encryption and access control, thereby reducing the risk of information leakage.

[0043] The automatic input support unit can monitor data usage history and detect unauthorized access. In the automatic input support unit, for example, the generation AI monitors data usage history and detects unauthorized access. For example, it detects abnormal access patterns and issues a warning. The automatic input support unit also monitors data usage history in real time, and the generation AI detects unauthorized access. For example, it detects access outside of normal access hours. The automatic input support unit also reduces the risk of information leakage by having the generation AI monitor data usage history and detect unauthorized access. For example, it detects abnormal frequency of access by the same user. In this way, the risk of information leakage can be reduced by monitoring data usage history and detecting unauthorized access.

[0044] The automatic input support unit can automate the data backup and recovery process. In the automatic input support unit, for example, the generation AI automates data backup, reducing the risk of information leakage. For example, data is backed up regularly and quickly recovered if an abnormality occurs. The automatic input support unit also automates the recovery process, reducing the risk of information leakage. For example, a process is built to automatically restore data from backups. The automatic input support unit also reduces the risk of information leakage by having the generation AI automate the data backup and recovery process. For example, backup data is encrypted and stored, and automatically restored upon recovery. In this way, the risk of information leakage can be reduced by automating the data backup and recovery process.

[0045] The automatic input support unit monitors data access logs in real time and can immediately block abnormal access. In the automatic input support unit, for example, the generation AI monitors data access logs in real time and immediately blocks abnormal access. For example, it detects access that differs from normal access patterns and immediately blocks it. The automatic input support unit also monitors access logs in real time and immediately blocks abnormal access if the generation AI detects it. For example, it detects and blocks abnormal access from the same IP address. The automatic input support unit also reduces the risk of information leakage by having the generation AI monitor data access logs in real time and immediately blocks abnormal access. For example, it detects and blocks access outside of normal access hours. In this way, the risk of information leakage can be reduced by monitoring data access logs in real time and immediately blocking abnormal access.

[0046] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0047] The automatic input assistance unit can analyze the user's input and automatically suggest related information based on the input. For example, when a user inputs an address, information on nearby public facilities and transportation can be automatically displayed. Also, when a user inputs an occupation, related industry news and job information can be provided. Furthermore, when a user inputs a specific keyword, FAQs and help articles related to that keyword can be automatically displayed. This improves user convenience by providing related information based on the user's input.

[0048] The auto-input assistant can analyze user input and automatically apply the appropriate format based on the input. For example, when a user enters a date, it can automatically convert it to a specified format (such as YYYY / MM / DD). It can also automatically convert a user's phone number into an international format when the user enters it. It can also automatically complete the postal code and prefecture name when the user enters an address. This unifies the format of input data, improving data consistency and accuracy.

[0049] The automatic input assistance unit can analyze the user's input and automatically execute appropriate actions based on the input. For example, when a user enters an address, a map can be automatically displayed. Also, when a user enters an email address, a confirmation email can be automatically sent to that address. Furthermore, when a user enters credit card information, a payment process can be automatically initiated. By automatically executing appropriate actions based on the input, it is possible to simplify user operations and improve convenience.

[0050] The automatic input support unit supports voice input and handwriting input, improving user convenience. For example, the generation AI supports voice input and automatically converts what the user inputs by voice into text. For example, if a user inputs "Yamada Taro" by voice, the generation AI converts that voice into text and inputs it. It can also support handwriting input and automatically convert what the user inputs by hand into text. For example, if a user inputs "Yamada Taro" by hand, the generation AI converts the handwritten characters into text and inputs it. In this way, by supporting voice input and handwriting input, user convenience can be improved.

[0051] The automatic input assistance unit can link with other public databases to cross-check the accuracy of input content. For example, the generation AI can link with other public databases to cross-check the accuracy of input names and addresses. For example, it can verify that the input content is correct by comparing it with the Basic Resident Register or family register database. In addition, by linking with other public databases, it is possible to cross-check the accuracy of input content in real time. For example, it can verify whether the address entered by the user actually exists. This cross-checks the accuracy of input content by linking with other public databases, making it possible to prevent input errors.

[0052] The registration support unit can refer to the user's past question history to provide more accurate advice. For example, an AI chatbot can analyze a user's past question history and learn the frequently asked questions. For example, if a user who previously asked "I don't know how to enter my address" asks the same question again, more accurate advice can be provided. The AI ​​chatbot can also provide accurate advice based on the user's past question history. For example, if a user who previously asked "I don't know how to enter my name" asks the same question again, the AI ​​chatbot can provide specific input instructions. This allows the user's questions to be resolved quickly by providing accurate advice based on the user's past question history.

[0053] The registration support unit can provide answers in appropriate language, taking into account the user's language and cultural background. For example, an AI chatbot can analyze the user's language and cultural background and provide answers in appropriate language. For example, answers can be provided in English for a user whose native language is English. The AI ​​chatbot can also provide answers in appropriate language, taking into account the user's cultural background. For example, answers can be provided using specific examples related to Japanese culture for a user who is knowledgeable about Japanese culture. This allows the user's understanding to be deepened by providing answers in appropriate language, taking into account the user's language and cultural background.

[0054] The processing flow of the first embodiment will be briefly explained below.

[0055] Step 1: The automatic input assistance unit analyzes the information entered by the user and assists in automatically entering accurate data. For example, the generation AI checks the information entered by the user in real time to ensure there are no errors. The generation AI can also generate accurate data based on the information entered by the user. For example, if the generation AI is instructed to "enter your name," and the user enters "Yamada Taro," the AI ​​will check whether the data is correct and suggest corrections if necessary. Step 2: The registration support unit provides interactive support as the user goes through the registration process. For example, if the user has questions during the registration process, the AI ​​chatbot can answer the questions in real time and provide appropriate advice. The AI ​​chatbot can also provide specific instructions in response to user questions. For example, in response to the question, "I don't know how to enter my address," it can provide specific instructions such as, "Please enter the address starting with the city, ward, town, or village name."

[0056] (Example 2) The My Number Card registration support system according to an embodiment of the present invention is a system that combines automatic input support using generation AI with registration support by an AI chatbot. As a result, the My Number Card registration support system can reduce manual registration errors and improve data accuracy.

[0057] The My Number Card registration support system according to the embodiment includes an automatic input support unit and a registration support unit. The automatic input support unit analyzes information entered by a user and automatically supports the user in entering accurate data. For example, the generation AI checks the information entered by the user in real time to ensure there are no errors. The generation AI can also generate accurate data based on the information entered by the user. For example, if the generation AI instructs the user to "enter your name," and the user enters "Yamada Taro," the AI ​​checks whether the data is correct and suggests corrections as necessary. The registration support unit provides interactive support to the user during the registration process. For example, if the user has questions during the registration process, the AI ​​chatbot can answer questions in real time and provide appropriate advice. The AI ​​chatbot can also provide specific instructions in response to user questions. For example, in response to a question such as "I don't know how to enter my address," the AI ​​chatbot can provide specific instructions such as "Please enter the address starting with the city, ward, town, or village name." This allows the My Number Card registration support system according to the embodiment to reduce manual registration errors and improve data accuracy.

[0058] The automatic input assistance unit can refer to the user's past input history, learn input error patterns, and predict and correct them. For example, the generation AI in the automatic input assistance unit analyzes the user's past input history and learns frequently occurring input error patterns. For example, it identifies trends in specific character strings and typos and automatically suggests corrections as the user inputs. The automatic input assistance unit also predicts input errors based on data previously entered by the user. For example, if a user who previously entered "Yamada Taro" mistakenly enters "Yamada Taro" when attempting to enter "Yamada Taro," the generation AI automatically suggests a correction. The automatic input assistance unit also predicts and corrects future input errors by referring to the user's input history and learning input error patterns. For example, if a user mistakenly enters "Tokyo" when attempting to enter "Tokyo," the generation AI automatically suggests a correction. This improves data accuracy by predicting and correcting input errors based on past input history.

[0059] The automatic input assistance unit can detect a user's input speed and typing habits, identify areas where input errors are likely to occur, and issue a warning. For example, the automatic input assistance unit uses a generation AI to analyze a user's input speed and identify areas where input speed changes suddenly. For example, it can detect areas where input is made faster than normal, determine that there is a high possibility of an input error, and display a warning. The automatic input assistance unit can also learn a user's typing habits and detect specific key combinations and input patterns. For example, if a user has a habit of pressing specific keys repeatedly, it can identify areas where there is a high possibility of an input error based on that pattern and issue a warning. The automatic input assistance unit can also analyze a user's input speed and typing habits in real time and identify areas where there is a high possibility of an input error. For example, it can detect areas where input is made slower than normal, determine that there is a high possibility of an input error, and issue a warning. This allows for improved data accuracy by identifying and warning about potential input errors based on input speed and typing habits.

[0060] The automatic input support unit can use an emotion estimation function to detect stress or anxiety felt by the user while inputting data and display a message to help the user relax. The automatic input support unit, for example, uses the emotion estimation function to detect stress or anxiety felt by the user while inputting data in real time. For example, the automatic input support unit analyzes the user's facial expressions and voice to detect signs of stress or anxiety. Furthermore, if the automatic input support unit detects stress or anxiety felt by the user while inputting data, it displays a message to help the user relax. For example, it displays a message such as "Please relax when inputting data." Furthermore, the automatic input support unit can use the emotion estimation function to detect stress or anxiety felt by the user while inputting data and provide music or video to help the user relax. For example, it plays music with a relaxing effect. In this way, the automatic input support unit can detect the user's stress or anxiety and display a relaxing message, making input work more comfortable.

[0061] The automatic input support unit supports voice input and handwriting input, thereby improving user convenience. In the automatic input support unit, for example, a generation AI supports voice input and automatically converts what the user inputs by voice into text. For example, if a user inputs "Yamada Taro" by voice, the generation AI converts the voice into text and inputs it. The automatic input support unit also supports handwriting input and automatically converts what the user inputs by hand into text. For example, if a user inputs "Yamada Taro" by hand, the generation AI converts the handwritten characters into text and inputs it. The automatic input support unit also supports voice input and handwriting input, thereby improving user convenience. For example, it converts what the user inputs by voice or handwriting into text in real time, reducing input errors. This supports voice input and handwriting input, thereby improving user convenience.

[0062] The automatic input support unit can link with other public databases to cross-check the accuracy of the input content. For example, the generation AI in the automatic input support unit links with other public databases to cross-check the accuracy of the input name and address. For example, it verifies whether the input content is correct by comparing it with the Basic Resident Register or family register database. The automatic input support unit also cross-checks the accuracy of the input content in real time by linking with other public databases. For example, it verifies whether the address entered by the user actually exists. The automatic input support unit also prevents incorrect input by cross-checking the accuracy of the input content with other public databases. For example, it verifies whether the name entered by the user is correct. In this way, incorrect input can be prevented by cross-checking the accuracy of the input content in linkage with other public databases.

[0063] The automatic input assistance unit uses an emotion estimation function to evaluate the user's satisfaction with the input content in real time, thereby improving the accuracy of the input assistance. The automatic input assistance unit, for example, uses the emotion estimation function to evaluate the user's satisfaction with the input content in real time. For example, the automatic input assistance unit analyzes the user's facial expressions and voice to calculate a satisfaction score. The automatic input assistance unit also evaluates the user's satisfaction in real time and improves the accuracy of the input assistance based on the result. For example, if the satisfaction level is low, the input assistance method is improved. The automatic input assistance unit also uses the emotion estimation function to evaluate the user's satisfaction with the input content and improves the accuracy of the input assistance. For example, if the satisfaction level is high, the method is continued to be used. In this way, the user's satisfaction can be evaluated in real time and the accuracy of the input assistance can be improved.

[0064] The registration support unit can provide more accurate advice by referring to the user's past question history. For example, the registration support unit allows an AI chatbot to analyze a user's past question history and learn frequently asked questions. For example, if a user who previously asked, "I don't know how to enter my address," asks a similar question again, the registration support unit can provide more accurate advice. The registration support unit also allows the AI ​​chatbot to provide accurate advice based on the user's past question history. For example, if a user who previously asked, "I don't know how to enter my name," asks the same question again, the registration support unit can provide specific input methods. The registration support unit also allows the AI ​​chatbot to provide accurate advice by referring to the user's past question history, quickly resolving the user's questions. For example, if a user who previously asked, "I don't know how to enter my date of birth," asks the same question again, the registration support unit can provide specific input methods. This allows the AI ​​chatbot to provide accurate advice based on the user's past question history, quickly resolving the user's questions.

[0065] The registration support unit can provide answers using appropriate expressions, taking into account the user's language and cultural background. The registration support unit, for example, has an AI chatbot analyze the user's language and cultural background and respond using appropriate expressions. For example, for a user whose native language is English, the AI ​​chatbot provides answers in English. The registration support unit also takes into account the user's cultural background and has the AI ​​chatbot respond using appropriate expressions. For example, for a user who is familiar with Japanese culture, the AI ​​chatbot provides answers using specific examples related to Japanese culture. The registration support unit also deepens the user's understanding by having the AI ​​chatbot respond using appropriate expressions, taking into account the user's language and cultural background. For example, for a user from a different cultural sphere, the AI ​​chatbot provides answers using expressions that are appropriate for that culture. This allows the user's understanding to be deepened by providing answers using appropriate expressions, taking into account the user's language and cultural background.

[0066] The registration support unit uses the emotion estimation function to analyze the emotion a user expresses when asking a question and can respond in accordance with the user's emotion. The registration support unit, for example, uses the emotion estimation function to analyze the emotion a user expresses when asking a question in real time. For example, it analyzes the user's facial expressions and voice to detect changes in emotion. The registration support unit also analyzes the user's emotion, and the AI ​​chatbot responds appropriately based on the results. For example, if the user is feeling anxious, it provides a message that gives a sense of security. The registration support unit also uses the emotion estimation function to analyze the emotion a user expresses when asking a question and responds in accordance with the emotion, thereby improving user satisfaction. For example, if the user is feeling stressed, it provides a message to help them relax. In this way, by analyzing the user's emotion and responding in accordance with the emotion, it is possible to improve user satisfaction.

[0067] The registration support unit can add video calling and screen sharing functions to provide visual support. For example, the registration support unit adds a video calling function to the AI ​​chatbot to provide visual support when the user asks a question. For example, the user can ask a question while sharing their screen, and the AI ​​chatbot can show specific operation procedures. The registration support unit also adds a screen sharing function, and the AI ​​chatbot can provide support by checking the user's screen in real time. For example, when a user asks how to operate an input form, the AI ​​chatbot can share the screen and show specific operation procedures. The registration support unit also adds a video calling and screen sharing function to the AI ​​chatbot to provide visual support and quickly resolve user questions. For example, when a user asks a question about input content, the AI ​​chatbot can share the screen and show specific input procedures. In this way, adding the video calling and screen sharing functions can provide visual support and quickly resolve user questions.

[0068] The registration support unit can create a database of questions and answers from other users and provide it as an FAQ. For example, the registration support unit may use an AI chatbot to create a database of questions and answers from other users and provide it as an FAQ. For example, the registration support unit may compile questions asked by many users in the past and display them as an FAQ. The registration support unit may also create a database of questions and answers from other users, allowing the AI ​​chatbot to quickly provide answers. For example, when a user asks, "I don't know how to enter my address," an appropriate answer may be provided from past FAQs. The registration support unit may also create a database of questions and answers from other users and provide it as an FAQ, allowing the AI ​​chatbot to quickly resolve user questions. For example, when a user asks, "I don't know how to enter my name," an appropriate answer may be provided from past FAQs. In this way, the AI ​​chatbot may create a database of questions and answers from other users and provide it as an FAQ, thereby quickly resolving user questions.

[0069] The registration support unit uses the emotion estimation function to monitor the emotion of a user when asking a question in real time and can provide a customized answer based on the emotion. The registration support unit, for example, uses the emotion estimation function to monitor the emotion of a user when asking a question in real time. For example, it analyzes the user's facial expressions and voice to detect changes in emotion. The registration support unit also monitors the user's emotion in real time, and the AI ​​chatbot provides a customized answer based on the results. For example, if the user is feeling anxious, it provides a message that gives a sense of security. The registration support unit also uses the emotion estimation function to monitor the emotion of a user when asking a question and provides a customized answer based on the emotion, thereby improving user satisfaction. For example, if the user is feeling stressed, it provides a message to help them relax. In this way, the registration support unit can monitor the user's emotion in real time and provide a customized answer based on the emotion, thereby improving user satisfaction.

[0070] The automatic input support unit can refer to multiple data sources and check the consistency of the data. In the automatic input support unit, for example, the generation AI refers to multiple data sources and checks the consistency of the entered data. For example, it checks whether the input content is correct by comparing it with the Basic Resident Register or family register database. In addition, the automatic input support unit refers to multiple data sources in real time when checking the accuracy of data. For example, it checks whether the address entered by the user actually exists. In addition, the automatic input support unit prevents incorrect input by having the generation AI refer to multiple data sources and check the consistency of the data. For example, it checks whether the name entered by the user is correct. In this way, by checking the consistency of the data by referring to multiple data sources, the accuracy of the data can be improved.

[0071] The automatic input assistance unit can track the history of data changes and record the reasons for the changes. In the automatic input assistance unit, for example, the generation AI tracks the history of data changes and records the reasons for the changes. For example, when a user changes their address, the reason is recorded and saved in a database. Furthermore, when checking the accuracy of data, the automatic input assistance unit tracks the history of changes and records the reasons for the changes, thereby improving the reliability of the data. For example, when a user changes their name, the reason is recorded. Furthermore, the automatic input assistance unit maintains the accuracy of the data by tracking the history of data changes and recording the reasons for the changes. For example, when a user changes their date of birth, the reason is recorded. In this way, by tracking the history of data changes and recording the reasons for the changes, the reliability of the data can be improved.

[0072] The automatic input support unit can use an emotion estimation function to detect anxiety or doubts the user feels when entering data and provide appropriate support. The automatic input support unit, for example, uses the emotion estimation function to detect anxiety or doubts the user feels when entering data in real time. For example, it analyzes the user's facial expressions and voice to detect signs of anxiety or doubt. Furthermore, if the automatic input support unit detects anxiety or doubts the user feels when entering data, it provides appropriate support. For example, it displays a message such as "Are you feeling anxious about what you are entering?" to provide support. Furthermore, the automatic input support unit can use the emotion estimation function to detect anxiety or doubts the user feels when entering data and provide appropriate support, thereby improving the accuracy of the data. For example, if the user has doubts, it provides specific input methods. In this way, it is possible to detect the user's anxiety or doubts and provide appropriate support, thereby improving the accuracy of the data.

[0073] The automatic input assistance unit can detect outliers by comparing with other users' data. For example, the generation AI of the automatic input assistance unit compares data with other users' data and detects outliers. For example, it compares data with data from other users living in the same area to detect abnormal address entries. The automatic input assistance unit also detects outliers by comparing with data from other users when checking the accuracy of data. For example, it compares with data from other users in the same age group to detect abnormal date of birth entries. The automatic input assistance unit also prevents incorrect input by comparing with data from other users and detecting outliers. For example, it compares with data from other users with the same surname to detect abnormal name entries. In this way, incorrect input can be prevented by comparing with data from other users to detect abnormal values.

[0074] The automatic input support unit can automatically standardize the data input format and format. For example, the generation AI automatically standardizes the data input format and format. For example, the input format for addresses is standardized to the order of "prefecture, city, ward, town, village, street address." The automatic input support unit also prevents incorrect input by automatically standardizing the input format and format when checking the accuracy of data. For example, the input format for names is standardized to the order of "last name, first name." The automatic input support unit also maintains the accuracy of data by having the generation AI automatically standardize the data input format and format. For example, the input format for dates of birth is standardized to the order of "year, month, day." This automatically standardizes the data input format and format, thereby maintaining the accuracy of data.

[0075] The automatic input assistance unit uses an emotion estimation function to evaluate in real time the level of satisfaction a user feels when entering data, thereby improving the accuracy of input assistance. The automatic input assistance unit, for example, uses the emotion estimation function to evaluate in real time the level of satisfaction a user feels when entering data. For example, the automatic input assistance unit analyzes the user's facial expressions and voice to calculate a satisfaction score. The automatic input assistance unit also evaluates the user's satisfaction in real time and improves the accuracy of input assistance based on the result. For example, if satisfaction is low, the input assistance method is improved. The automatic input assistance unit also uses the emotion estimation function to evaluate the level of satisfaction a user feels when entering data, thereby improving the accuracy of input assistance. For example, if satisfaction is high, the method is continued to be used. In this way, the user's satisfaction can be evaluated in real time and the accuracy of input assistance can be improved.

[0076] The automatic input support unit can strengthen data encryption and access control. In the automatic input support unit, for example, the generation AI encrypts data to reduce the risk of information leakage. For example, the user's personal information is encrypted and stored. The automatic input support unit also strengthens access control, and the generation AI reduces the risk of information leakage. For example, it ensures that only specific users can access the data. The automatic input support unit also reduces the risk of information leakage by having the generation AI strengthen data encryption and access control. For example, it periodically changes the data encryption key. This strengthens data encryption and access control, thereby reducing the risk of information leakage.

[0077] The automatic input support unit can monitor data usage history and detect unauthorized access. In the automatic input support unit, for example, the generation AI monitors data usage history and detects unauthorized access. For example, it detects abnormal access patterns and issues a warning. The automatic input support unit also monitors data usage history in real time, and the generation AI detects unauthorized access. For example, it detects access outside of normal access hours. The automatic input support unit also reduces the risk of information leakage by having the generation AI monitor data usage history and detect unauthorized access. For example, it detects abnormal frequency of access by the same user. In this way, the risk of information leakage can be reduced by monitoring data usage history and detecting unauthorized access.

[0078] The automatic input support unit can use an emotion estimation function to detect anxiety felt by the user when entering data and display a message that provides a sense of security. The automatic input support unit, for example, uses the emotion estimation function to detect anxiety felt by the user when entering data in real time. For example, the automatic input support unit analyzes the user's facial expressions and voice to detect signs of anxiety. Furthermore, if the automatic input support unit detects anxiety felt by the user when entering data, it displays a message that provides a sense of security. For example, it displays a message such as "Your data is stored safely." Furthermore, the automatic input support unit can use the emotion estimation function to detect anxiety felt by the user when entering data and display a message that provides a sense of security, thereby reducing the risk of information leakage. For example, it displays a message such as "Your data is encrypted." In this way, by detecting the user's anxiety and displaying a message that provides a sense of security, it is possible to reduce the risk of information leakage.

[0079] The automatic input support unit can automate the data backup and recovery process. In the automatic input support unit, for example, the generation AI automates data backup, reducing the risk of information leakage. For example, data is backed up regularly and quickly recovered if an abnormality occurs. The automatic input support unit also automates the recovery process, reducing the risk of information leakage. For example, a process is built to automatically restore data from backups. The automatic input support unit also reduces the risk of information leakage by having the generation AI automate the data backup and recovery process. For example, backup data is encrypted and stored, and automatically restored upon recovery. In this way, the risk of information leakage can be reduced by automating the data backup and recovery process.

[0080] The automatic input support unit monitors data access logs in real time and can immediately block abnormal access. In the automatic input support unit, for example, the generation AI monitors data access logs in real time and immediately blocks abnormal access. For example, it detects access that differs from normal access patterns and immediately blocks it. The automatic input support unit also monitors access logs in real time and immediately blocks abnormal access if the generation AI detects it. For example, it detects and blocks abnormal access from the same IP address. The automatic input support unit also reduces the risk of information leakage by having the generation AI monitor data access logs in real time and immediately blocks abnormal access. For example, it detects and blocks access outside of normal access hours. In this way, the risk of information leakage can be reduced by monitoring data access logs in real time and immediately blocking abnormal access.

[0081] The automatic input support unit uses an emotion estimation function to evaluate in real time the sense of security felt by the user when entering data, thereby improving the effectiveness of security measures. The automatic input support unit, for example, uses the emotion estimation function to evaluate in real time the sense of security felt by the user when entering data. For example, it analyzes the user's facial expressions and voice to calculate a score for the sense of security. The automatic input support unit also evaluates the user's sense of security in real time and improves the effectiveness of security measures based on the evaluation result. For example, if the sense of security is low, it strengthens the security measures. The automatic input support unit also uses the emotion estimation function to evaluate in real time the sense of security felt by the user when entering data, thereby improving the effectiveness of security measures. For example, if the sense of security is high, it continues to use the security measures. In this way, the user's sense of security can be evaluated in real time and the effectiveness of security measures can be improved.

[0082] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0083] The automatic input assistance unit can analyze the user's input and automatically suggest related information based on the input. For example, when a user inputs an address, information on nearby public facilities and transportation can be automatically displayed. Also, when a user inputs an occupation, related industry news and job information can be provided. Furthermore, when a user inputs a specific keyword, FAQs and help articles related to that keyword can be automatically displayed. This improves user convenience by providing related information based on the user's input.

[0084] The auto-input assistant can analyze user input and automatically apply the appropriate format based on the input. For example, when a user enters a date, it can automatically convert it to a specified format (such as YYYY / MM / DD). It can also automatically convert a user's phone number into an international format when the user enters it. It can also automatically complete the postal code and prefecture name when the user enters an address. This unifies the format of input data, improving data consistency and accuracy.

[0085] The automatic input assistance unit can analyze the user's input and automatically execute appropriate actions based on the input. For example, when a user enters an address, a map can be automatically displayed. Also, when a user enters an email address, a confirmation email can be automatically sent to that address. Furthermore, when a user enters credit card information, a payment process can be automatically initiated. By automatically executing appropriate actions based on the input, it is possible to simplify user operations and improve convenience.

[0086] The automatic input assistance unit can use the emotion estimation function to detect stress or anxiety felt by the user while typing and display a message to help them relax. For example, it can analyze the user's facial expressions and voice to detect signs of stress or anxiety. If it detects stress or anxiety felt by the user while typing, it can display a message to help them relax. For example, it can display a message such as "Please relax when typing." It can also use the emotion estimation function to detect stress or anxiety felt by the user while typing and provide music or images to help them relax. This makes typing more comfortable by detecting the user's stress or anxiety and displaying a message to help them relax.

[0087] The automatic input support unit supports voice input and handwriting input, improving user convenience. For example, the generation AI supports voice input and automatically converts what the user inputs by voice into text. For example, if a user inputs "Yamada Taro" by voice, the generation AI converts that voice into text and inputs it. It can also support handwriting input and automatically convert what the user inputs by hand into text. For example, if a user inputs "Yamada Taro" by hand, the generation AI converts the handwritten characters into text and inputs it. In this way, by supporting voice input and handwriting input, user convenience can be improved.

[0088] The automatic input assistance unit can link with other public databases to cross-check the accuracy of input content. For example, the generation AI can link with other public databases to cross-check the accuracy of input names and addresses. For example, it can verify that the input content is correct by comparing it with the Basic Resident Register or family register database. In addition, by linking with other public databases, it is possible to cross-check the accuracy of input content in real time. For example, it can verify whether the address entered by the user actually exists. This cross-checks the accuracy of input content by linking with other public databases, making it possible to prevent input errors.

[0089] The automatic input assistance unit can use an emotion estimation function to evaluate the user's satisfaction with the input content in real time, thereby improving the accuracy of the input assistance. For example, the emotion estimation function is used to evaluate the user's satisfaction with the input content in real time. For example, the user's facial expression and voice are analyzed to calculate a satisfaction score. The automatic input assistance unit can also evaluate the user's satisfaction in real time and improve the accuracy of the input assistance based on the evaluation result. For example, if the satisfaction level is low, the input assistance method is improved. This allows the user's satisfaction to be evaluated in real time, thereby improving the accuracy of the input assistance.

[0090] The registration support unit can refer to the user's past question history to provide more accurate advice. For example, an AI chatbot can analyze a user's past question history and learn the frequently asked questions. For example, if a user who previously asked "I don't know how to enter my address" asks the same question again, more accurate advice can be provided. The AI ​​chatbot can also provide accurate advice based on the user's past question history. For example, if a user who previously asked "I don't know how to enter my name" asks the same question again, the AI ​​chatbot can provide specific input instructions. This allows the user's questions to be resolved quickly by providing accurate advice based on the user's past question history.

[0091] The registration support unit can provide answers in appropriate language, taking into account the user's language and cultural background. For example, an AI chatbot can analyze the user's language and cultural background and provide answers in appropriate language. For example, answers can be provided in English for a user whose native language is English. The AI ​​chatbot can also provide answers in appropriate language, taking into account the user's cultural background. For example, answers can be provided using specific examples related to Japanese culture for a user who is knowledgeable about Japanese culture. This allows the user's understanding to be deepened by providing answers in appropriate language, taking into account the user's language and cultural background.

[0092] The registration support unit uses the emotion estimation function to analyze the emotions expressed by the user when asking a question and can respond according to the user's emotions. For example, the emotion estimation function can be used to analyze the emotions expressed by the user when asking a question in real time. For example, the emotion estimation function can analyze the user's facial expressions and voice to detect changes in emotion. The AI ​​chatbot can also analyze the user's emotions and respond appropriately based on the results. For example, if the user is feeling anxious, it can provide a message that gives a sense of security. This makes it possible to analyze the user's emotions and respond according to their emotions, thereby improving user satisfaction.

[0093] The processing flow of the second embodiment will be briefly explained below.

[0094] Step 1: The automatic input assistance unit analyzes the information entered by the user and assists in automatically entering accurate data. For example, the generation AI checks the information entered by the user in real time to ensure there are no errors. The generation AI can also generate accurate data based on the information entered by the user. For example, if the generation AI is instructed to "enter your name," and the user enters "Yamada Taro," the AI ​​will check whether the data is correct and suggest corrections if necessary. Step 2: The registration support unit provides interactive support as the user goes through the registration process. For example, if the user has questions during the registration process, the AI ​​chatbot can answer the questions in real time and provide appropriate advice. The AI ​​chatbot can also provide specific instructions in response to user questions. For example, in response to the question, "I don't know how to enter my address," it can provide specific instructions such as, "Please enter the address starting with the city, ward, town, or village name."

[0095] 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.

[0096] 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.

[0097] 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.

[0098] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0099] 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.

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

[0101] The 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.

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

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

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

[0105] Fig. 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.

[0106] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

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

[0108] In the 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.

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

[0110] The specific processing unit 290 transmits the result of the specific processing to the 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.

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

[0112] The data processing system 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.

[0113] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0114] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

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

[0116] The 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.

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

[0118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (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).

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

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0127] 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.

[0128] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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).

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0140] 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.

[0141] 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.

[0142] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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).

[0148] 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.

[0149] 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."

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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]

[0162] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. An automatic input support section that utilizes generative AI, A registration support unit using an AI chatbot, The automatic input support unit It analyzes the information entered by the user and automatically assists in entering accurate data. The registration support unit Interactively assist users as they go through the registration process A system characterized by:

2. The automatic input support unit Refer to the user's past input history, learn input error patterns, and predict and correct them.

2. The system of claim 1.

3. The automatic input support unit Detects the user's input speed and typing habits, identifies areas where input errors are likely to occur, and issues a warning.

2. The system of claim 1.

4. The automatic input support unit Detects stress or anxiety felt by the user while typing and displays a message to help them relax 2. The system of claim 1.

5. The automatic input support unit Supports voice input and handwriting input, improving user convenience.

2. The system of claim 1.

Images