System

Abstract

An object of a system according to an embodiment is to provide information necessary for a user to smoothly proceed with a procedure and to track a progress status of the procedure in real time.SOLUTION: A system includes a reception unit, a generation unit, a tracking unit, a notification unit, and an information providing unit. The reception unit inputs information for a user to start a procedure. The generation unit generates a list of necessary procedures based on the information input by the reception unit. The tracking unit tracks the progress of the procedure in real time based on the list generated by the generation unit. The notification unit notifies the user of the progress tracked by the tracking unit. The information providing unit collects data from a reliable information source and provides the data to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, it was difficult to keep track of the necessary procedures and their progress when it came to procedures such as moving, studying abroad, marriage, childbirth, and bereavement, and there was the issue of the time-consuming need to contact each institution.

[0005] The system according to the embodiment aims to provide the user with the information necessary to smoothly proceed with the procedure and to track the progress of the procedure in real time. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, a generation unit, a tracking unit, a notification unit, and an information provision unit. The reception unit inputs information for a user to start a procedure. The generation unit generates a list of required procedures based on the information input by the reception unit. The tracking unit tracks the progress of the procedures in real time based on the list generated by the generation unit. The notification unit notifies the user of the progress tracked by the tracking unit. The information provision unit collects data from reliable information sources and provides it to the user. [Effects of the Invention]

[0007] The system according to the embodiment provides the user with the information necessary to smoothly proceed with the procedure and can track the progress of the procedure in real time. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) A procedure support system according to an embodiment of the present invention allows users to efficiently complete procedures and eliminates the need to contact various institutions. The procedure support system includes a reception unit through which a user inputs information to begin a procedure; a generation unit that generates a list of required procedures based on the information input by the reception unit; a tracking unit that tracks the progress of the procedures in real time based on the list generated by the generation unit; a notification unit that notifies the user of the progress tracked by the tracking unit; and an information provision unit that collects data from reliable sources and provides it to the user. For example, when a user begins a procedure, the procedure support system generates a list of required procedures. For example, in the case of moving, this list includes procedures for changing address and changing electricity, gas, and water contracts. The procedure support system then tracks the progress of each procedure in real time and notifies the user. For example, when the address change procedure is completed, the system sends a notification to the user. Furthermore, the procedure support system provides various information about Japan and overseas. For example, this includes information about the university the user is studying at and information about marriage laws and procedures. This allows the user to understand the progress of the procedure in real time, thereby preventing delays and errors. It also saves time and effort by eliminating the need to contact each institution. This allows the procedure support system to allow users to proceed with the procedure efficiently and eliminates the need to contact each institution. For example, when a user enters information to start a procedure, the system can automatically generate a list of required procedures, track the progress of each procedure in real time, and notify the user, preventing delays and errors in the procedure. In addition, by collecting data from reliable sources and providing it to the user, the user can obtain the information they need in a centralized location.

[0029] A procedure assistance system according to an embodiment includes a reception unit, a generation unit, a tracking unit, a notification unit, and an information providing unit. The reception unit inputs information required for a user to start a procedure. The information required for a user to start a procedure includes, but is not limited to, personal information, the type of procedure, and required documents. The reception unit allows the user to input information using, for example, a web form. The reception unit also allows the user to input information using a mobile app. The reception unit also allows the user to input information using voice input. The generation unit generates a list of required procedures based on the information input by the reception unit. The list of required procedures includes, for example, the name of the procedure, procedure steps, and required documents, but is not limited to, for example. The generation unit generates the list according to, for example, the type of procedure. The generation unit can also improve the accuracy of the list by referring to the user's past procedure history. The tracking unit tracks the progress of the procedure in real time based on the list generated by the generation unit. To track the progress in real time, for example, information may be obtained in cooperation with various institutions. The tracking unit cooperates with, for example, government agencies, local governments, private companies, etc. to obtain the progress of procedures. The notification unit notifies the user of the progress tracked by the tracking unit. The progress of procedures includes, for example, but is not limited to, the status of the procedures, the expected completion date, and required actions. The notification unit notifies the user using, for example, email or push notification. The notification unit can also estimate the user's emotions and adjust the notification method based on the estimated user emotions. The information providing unit collects data from reliable sources and provides it to the user. Reliable sources include, for example, government agencies, official databases, certified information providers, etc., but are not limited to these examples. The information providing unit, for example, periodically updates data to provide the latest information. The information providing unit also has an interface that allows the user to search for information of interest. As a result, the procedure support system according to the embodiment allows the user to efficiently proceed with procedures and eliminates the need to inquire at each institution.

[0030] The reception unit may include an interface through which a user inputs information to start a procedure. Examples of interfaces include, but are not limited to, a web form, a mobile app, and voice input. The reception unit may, for example, allow a user to input information using a web form. The reception unit may also allow a user to input information using a mobile app. For example, a mobile app is designed to allow a user to easily input information. The reception unit may also allow a user to input information using voice input. For example, speech recognition technology may be used to convert a user's voice into text and input information. This allows a user to easily input information to start a procedure.

[0031] The generation unit can generate a list of required procedures based on the information input by the reception unit. The list of required procedures includes, for example, the name of the procedure, the steps of the procedure, and the necessary documents, but is not limited to these examples. The generation unit generates the list according to the type of procedure, for example. For example, in the case of a moving procedure, procedures for address change and contract change are included in the list. The generation unit can also improve the accuracy of the list by referring to the user's past procedure history. For example, the accuracy of the list can be improved based on procedures the user has performed in the past. This allows the user to understand the required procedures at a glance.

[0032] The tracking unit can obtain the progress status of the procedure in real time by cooperating with a specific institution. Examples of specific institutions include, but are not limited to, government institutions, local governments, and private companies. For example, the tracking unit can obtain the progress status of the procedure in cooperation with a government institution. For example, the tracking unit can obtain the progress status of the procedure from a government institution's database. The tracking unit can also obtain the progress status of the procedure in cooperation with a local government. For example, the tracking unit can obtain the progress status of the procedure from a local government's system. The tracking unit can also obtain the progress status of the procedure in cooperation with a private company. For example, the tracking unit can obtain the progress status of the procedure from a private company's system. This allows the user to grasp the progress status of the procedure in real time.

[0033] The notification unit can notify the user of the progress of the procedure. The progress of the procedure includes, but is not limited to, for example, the status of the procedure, the expected completion date, and any necessary actions. The notification unit notifies the user, for example, by email or push notification. For example, if the status of the procedure changes, the system sends the user an email. The notification unit can also notify the user of the progress of the procedure by push notification. For example, if the expected completion date of the procedure approaches, the system sends the user a push notification. This allows the user to immediately know the progress of the procedure.

[0034] The information providing unit can collect data from reliable sources and update it regularly. Examples of reliable sources include, but are not limited to, government agencies, official databases, and certified information providers. The information providing unit, for example, collects data from government agencies. For example, it obtains the latest information from the official database of a government agency. The information providing unit can also collect data from official databases. For example, it collects data from certified information providers. Furthermore, the information providing unit regularly updates the data to provide the latest information. For example, it updates the data daily to provide the user with the latest information. This allows the user to always obtain the latest information.

[0035] The information providing unit may have an interface that allows a user to search for information of interest. Examples of interfaces include, but are not limited to, a web form, a mobile app, and voice input. For example, the information providing unit allows a user to search for information using a web form. The information providing unit may also allow a user to search for information using a mobile app. For example, a mobile app is designed to allow a user to easily search for information. The information providing unit may also allow a user to search for information using voice input. For example, speech recognition technology may be used to convert a user's voice into text and search for information. This allows a user to easily search for required information.

[0036] The reception unit can analyze the user's past procedure history and suggest the optimal input method. For example, the reception unit can automatically display procedures that the user has frequently performed in the past as candidates. The reception unit can also preferentially suggest input methods (voice, text, etc.) that the user has used in the past. Furthermore, the reception unit can predict and suggest procedures to be performed during a specific time period based on the user's past procedure history. This makes input work more efficient by suggesting the optimal input method based on the user's past history.

[0037] The reception unit can dynamically change the layout of the input interface depending on the type of procedure. For example, in the case of moving procedures, the reception unit may prioritize displaying input fields for address changes and contract changes. In addition, in the case of marriage procedures, the reception unit may prioritize displaying input fields for marriage registration and related documents. Furthermore, in the case of study abroad procedures, the reception unit may prioritize displaying input fields for visa applications and university information. This provides an interface according to the type of procedure, making input work more efficient.

[0038] The reception unit can add a function that analyzes the user's input in real time and automatically completes the necessary information. For example, when the user inputs an address, the reception unit can automatically complete the address when the user inputs a postal code. The reception unit can also display names that the user has previously input as candidates when the user inputs a name. Furthermore, the reception unit can automatically complete related information when the user selects a type of procedure. This makes the user's input work more efficient.

[0039] The reception unit can prioritize displaying region-specific procedure information by taking into account the user's geographical location information. For example, if the user lives in a specific region, the reception unit can prioritize displaying region-specific procedure information. Also, if the user lives overseas, the reception unit can prioritize displaying country-specific procedure information. Furthermore, the reception unit can prioritize displaying procedure information related to the region to which the user has moved. This allows the user to quickly obtain the information they need by providing region-specific procedure information.

[0040] The reception unit can analyze the user's social media activity and automatically suggest related procedural information. For example, if a user announces their marriage on social media, the reception unit automatically suggests information about marriage procedures. In addition, if a user announces their move on social media, the reception unit can automatically suggest information about moving procedures. Furthermore, if a user announces their study abroad on social media, the reception unit can automatically suggest information about study abroad procedures. This makes procedures more efficient by providing related procedural information based on the user's social media activity.

[0041] The reception unit can customize the input interface by reflecting the user's past feedback. For example, the reception unit improves the input interface based on feedback provided by the user in the past. The reception unit can also adjust the input interface to resolve problems pointed out by the user in the past. Furthermore, the reception unit can provide an easier-to-use input interface by referring to the user's past feedback. In this way, usability is improved by improving the interface based on the user's feedback.

[0042] The generation unit can dynamically change the priority of the list based on the importance of the procedure. For example, the generation unit displays important procedures at the top of the list. The generation unit can also display procedures with high urgency at the top of the list. Furthermore, the generation unit can dynamically change the priority of procedures depending on the user's situation. This allows important procedures to be displayed preferentially, thereby making procedures more efficient.

[0043] The generation unit can apply different generation algorithms depending on the procedure category. For example, in the case of moving procedures, the generation unit applies an algorithm that prioritizes displaying procedures for address change and contract change. In addition, in the case of marriage procedures, the generation unit can also apply an algorithm that prioritizes displaying procedures for marriage registration and related documents. Furthermore, in the case of study abroad procedures, the generation unit can also apply an algorithm that prioritizes displaying procedures for visa application and university information. This makes procedures more efficient by providing a list according to the procedure category.

[0044] The generation unit can improve the accuracy of the list by referring to the user's past procedure history. The generation unit improves the accuracy of the list, for example, based on procedures that the user has performed in the past. The generation unit can also add related procedures to the list from the user's past procedure history. Furthermore, the generation unit can analyze the user's past procedure history and display the most appropriate procedures in the list. This improves the accuracy of the list based on the user's past procedure history, thereby making procedures more efficient.

[0045] The generation unit can determine the priority of the list based on the submission date of the procedure. For example, the generation unit displays procedures with an upcoming submission deadline at the top of the list. The generation unit can also display procedures whose submission date has passed at the bottom of the list. Furthermore, the generation unit can dynamically change the priority of the list based on the submission date depending on the user's situation. This makes procedures more efficient by providing a list based on the submission date.

[0046] The generation unit can adjust the order of the list based on the relevance of the procedures. For example, the generation unit displays related procedures at the top of the list. The generation unit can also display highly related procedures preferentially depending on the user's situation. Furthermore, the generation unit can dynamically change the order of the list based on the relevance of the procedures. This makes the procedures more efficient by providing a list based on the relevance of the procedures.

[0047] The generator can adjust the use of technical terms in the list according to the user's level of expertise. For example, if the user has technical expertise, the generator can provide a list using technical terms. Alternatively, if the user does not have technical expertise, the generator can provide a list that explains things in simple terms. Furthermore, the generator can dynamically adjust the use of technical terms in the list according to the user's level of expertise. This can streamline the process by providing a list that is appropriate for the user's level of expertise.

[0048] The tracking unit can improve the accuracy of the progress status by taking into account the interrelationships between procedures. For example, the tracking unit displays the progress status of related procedures all at once. The tracking unit can also adjust the display order of the progress status by taking into account the interrelationships between procedures. Furthermore, the tracking unit can improve the accuracy of the progress status based on the interrelationships between procedures. In this way, the accuracy of the progress status is improved by taking into account the interrelationships between procedures.

[0049] The tracking unit can customize the progress status taking into account attribute information of the person who submitted the procedure. The tracking unit customizes the display method of the progress status according to, for example, the age and gender of the person who submitted the procedure. The tracking unit can also customize the display method of the progress status according to the occupation and expertise of the person who submitted the procedure. Furthermore, the tracking unit can dynamically adjust the display method of the progress status based on the attribute information of the person who submitted the procedure. This makes the procedure more efficient by providing the progress status based on the attribute information of the person who submitted the procedure.

[0050] The tracking unit can weight the progress status based on the frequency of submission of the procedure. For example, the tracking unit can prioritize and display procedures that are submitted more frequently. The tracking unit can also display procedures that are submitted less frequently lower in the list. Furthermore, the tracking unit can dynamically adjust the weighting of the progress status based on the frequency of submission. This allows for the efficiency of procedures by providing progress based on the frequency of submission.

[0051] The tracking unit can display the progress status taking into account the geographical distribution of procedures. For example, the tracking unit can prioritize displaying the progress status of procedures in the area where the user lives. The tracking unit can also prioritize displaying the progress status of procedures in the area where the user is moving. Furthermore, the tracking unit can also prioritize displaying the progress status of procedures in areas in which the user is interested. This makes procedures more efficient by providing progress status based on geographical distribution.

[0052] The tracking unit can improve the accuracy of the progress status by referring to related literature of the procedure. The tracking unit can improve the accuracy of the progress status by referring to, for example, related laws and guidelines. The tracking unit can also improve the accuracy of the progress status by referring to related research papers and reports. Furthermore, the tracking unit can improve the accuracy of the progress status by referring to related news articles and blogs. This makes the procedure more efficient by providing progress status based on related literature.

[0053] The tracking unit can display the progress status taking into account the market value of the procedure. For example, the tracking unit can prioritize displaying procedures with high market value. The tracking unit can also display procedures with low market value lower in the list. Furthermore, the tracking unit can dynamically adjust the display order of the progress status based on market value. This allows for the efficiency of procedures by providing progress status based on market value.

[0054] The notification unit can adjust the level of detail of the notification based on the importance of the procedure when notifying. For example, the notification unit provides detailed notification for important procedures. The notification unit can also provide detailed notification for highly urgent procedures. Furthermore, the notification unit can dynamically adjust the level of detail of the notification based on the importance of the procedure depending on the user's situation. This allows the procedure to be performed more efficiently by providing notifications based on the importance of the procedure.

[0055] The notification unit can apply different notification algorithms depending on the procedure category when sending notifications. For example, in the case of moving procedures, the notification unit applies an algorithm that prioritizes notifications of address changes and contract changes. In addition, in the case of marriage procedures, the notification unit can also apply an algorithm that prioritizes notifications of marriage registration forms and related documents. Furthermore, in the case of study abroad procedures, the notification unit can also apply an algorithm that prioritizes notifications of visa applications and university information. This makes procedures more efficient by providing notifications according to the procedure category.

[0056] The notification unit can improve the accuracy of notifications by referring to the user's past notification history when providing notifications. The notification unit can improve the accuracy of notifications, for example, based on notifications received by the user in the past. The notification unit can also provide relevant notifications from the user's past notification history. Furthermore, the notification unit can analyze the user's past notification history and provide optimal notifications. This makes procedures more efficient by providing notifications based on the user's past notification history.

[0057] The notification unit can determine the priority of notifications based on the submission time of the procedure when notifying. For example, the notification unit prioritizes notifications for procedures with an approaching submission deadline. The notification unit can also display notifications for procedures whose submission time has passed lower in the notification hierarchy. Furthermore, the notification unit can dynamically change the priority of notifications based on the submission time depending on the user's situation. This makes procedures more efficient by providing notifications based on the submission time.

[0058] The notification unit can adjust the order of notifications based on the relevance of the procedures when notifying. For example, the notification unit prioritizes notifications of related procedures. The notification unit can also prioritize notifications of highly relevant procedures depending on the user's situation. Furthermore, the notification unit can dynamically change the order of notifications based on the relevance of the procedures. This allows for more efficient procedures by providing notifications based on the relevance of the procedures.

[0059] The notification unit can adjust the use of technical terms in the notification depending on the user's level of expertise when providing a notification. For example, if the user has technical expertise, the notification unit provides a notification using technical terms. Also, if the user does not have technical expertise, the notification unit can provide a notification that explains the notification in simple language. Furthermore, the notification unit can dynamically adjust the use of technical terms in the notification depending on the user's level of expertise. This allows for efficient procedures by providing notifications that are tailored to the user's level of expertise.

[0060] The information providing unit can adjust the level of detail of the display based on the importance of the information when providing the information. For example, the information providing unit provides a detailed display in the case of important information. The information providing unit can also provide a detailed display in the case of highly urgent information. Furthermore, the information providing unit can dynamically adjust the level of detail of the display based on the importance of the information according to the user's situation. This allows for a deeper understanding of the information by providing a display based on the importance of the information.

[0061] When providing information, the information providing unit can apply different display algorithms depending on the category of information. For example, in the case of moving information, the information providing unit applies an algorithm that prioritizes displaying information about address changes and contract changes. In addition, in the case of marriage information, the information providing unit can also apply an algorithm that prioritizes displaying information about marriage registration forms and related documents. Furthermore, in the case of study abroad information, the information providing unit can also apply an algorithm that prioritizes displaying information about visa applications and university information. This allows for a deeper understanding of the information by providing a display according to the category of information.

[0062] When providing information, the information providing unit can improve the accuracy of the display by referring to the user's past information search history. The information providing unit improves the accuracy of the display, for example, based on information searched for by the user in the past. The information providing unit can also display related information from the user's past information search history. Furthermore, the information providing unit can analyze the user's past information search history and display optimal information. This allows for a deeper understanding of the information by providing a display based on the user's past information search history.

[0063] When providing information, the information providing unit can determine the display priority based on the time of submission of the information. For example, the information providing unit can preferentially display information whose submission deadline is approaching. The information providing unit can also display information whose submission deadline has passed at a lower level. Furthermore, the information providing unit can dynamically change the display priority based on the time of submission depending on the user's situation. This allows for a deeper understanding of the information by providing information display based on the time of submission.

[0064] The information providing unit can adjust the display order based on the relevance of the information when providing the information. For example, the information providing unit can prioritize displaying related information. The information providing unit can also prioritize displaying highly relevant information according to the user's situation. Furthermore, the information providing unit can dynamically change the display order based on the relevance of the information. This allows for a deeper understanding of the information by providing a display based on the relevance of the information.

[0065] The information providing unit can adjust the use of technical terms in the display according to the user's level of expertise when providing information. For example, if the user has technical knowledge, the information providing unit can provide a display using technical terms. Also, if the user does not have technical knowledge, the information providing unit can provide a display that explains the information in simple terms. Furthermore, the information providing unit can dynamically adjust the use of technical terms in the display according to the user's level of expertise. This allows the user to deepen their understanding of the information by providing a display that suits the user's level of expertise.

[0066] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0067] The reception unit can add a function that analyzes the user's input in real time and automatically completes the necessary information. For example, when a user enters an address, the address is automatically completed when the user enters a postal code. The reception unit can also display names that the user has entered in the past as candidates when the user enters a name. Furthermore, the reception unit can automatically complete related information when the user selects a type of procedure. This makes the user's input work more efficient.

[0068] The generation unit can dynamically change the priority of the list based on the importance of the procedure. For example, important procedures can be displayed at the top of the list. The generation unit can also display procedures with high urgency at the top of the list. Furthermore, the generation unit can dynamically change the priority of procedures depending on the user's situation. This allows important procedures to be displayed preferentially, thereby making procedures more efficient.

[0069] The tracking unit can improve the accuracy of the progress status by taking into account the interrelationships between procedures. For example, the progress status of related procedures is displayed all at once. The tracking unit can also adjust the display order of the progress status by taking into account the interrelationships between procedures. Furthermore, the tracking unit can improve the accuracy of the progress status based on the interrelationships between procedures. In this way, the accuracy of the progress status is improved by taking into account the interrelationships between procedures.

[0070] The notification unit can adjust the level of detail of the notification based on the importance of the procedure when notifying. For example, for important procedures, detailed notifications are provided. The notification unit can also provide detailed notifications for procedures with high urgency. Furthermore, the notification unit can dynamically adjust the level of detail of the notification based on the importance of the procedure depending on the user's situation. This allows the procedure to be performed more efficiently by providing notifications based on the importance of the procedure.

[0071] The information providing unit can adjust the level of detail of the display based on the importance of the information when providing the information. For example, if the information is important, a detailed display is provided. The information providing unit can also provide a detailed display if the information is highly urgent. Furthermore, the information providing unit can dynamically adjust the level of detail of the display based on the importance of the information according to the user's situation. This allows for a deeper understanding of the information by providing a display based on the importance of the information.

[0072] The processing flow of the first embodiment will be briefly explained below.

[0073] Step 1: The reception unit inputs information for the user to start the procedure. The information for the user to start the procedure includes, for example, personal information, the type of procedure, and required documents. The reception unit allows the user to input information using a web form, a mobile app, voice input, etc. Step 2: The generator generates a list of required procedures based on the information input by the reception unit. The list of required procedures includes the name of the procedure, procedure steps, required documents, etc. The generator generates the list according to the type of procedure and can also improve the accuracy of the list by referring to the user's past procedure history. Step 3: The tracking unit tracks the progress of the procedures in real time based on the list generated by the generation unit. To track the progress in real time, the tracking unit cooperates with each institution to obtain information. The tracking unit cooperates with government agencies, local governments, private companies, etc. to obtain the progress of the procedures. Step 4: The notification unit notifies the user of the progress tracked by the tracking unit. The progress of the procedure includes the procedure status, expected completion date, required actions, etc. The notification unit notifies the user via email or push notification, and can also adjust the notification method by estimating the user's emotions. Step 5: The information provider collects data from reliable sources and provides it to users. Reliable sources include government agencies, official databases, and certified information providers. The information provider updates the data regularly to provide the latest information. It also provides an interface that allows users to search for information of interest.

[0074] (Example 2) A procedure support system according to an embodiment of the present invention allows users to efficiently complete procedures and eliminates the need to contact various institutions. The procedure support system includes a reception unit through which a user inputs information to begin a procedure; a generation unit that generates a list of required procedures based on the information input by the reception unit; a tracking unit that tracks the progress of the procedures in real time based on the list generated by the generation unit; a notification unit that notifies the user of the progress tracked by the tracking unit; and an information provision unit that collects data from reliable sources and provides it to the user. For example, when a user begins a procedure, the procedure support system generates a list of required procedures. For example, in the case of moving, this list includes procedures for changing address and changing electricity, gas, and water contracts. The procedure support system then tracks the progress of each procedure in real time and notifies the user. For example, when the address change procedure is completed, the system sends a notification to the user. Furthermore, the procedure support system provides various information about Japan and overseas. For example, this includes information about the university the user is studying at and information about marriage laws and procedures. This allows the user to understand the progress of the procedure in real time, thereby preventing delays and errors. It also saves time and effort by eliminating the need to contact each institution. This allows the procedure support system to allow users to proceed with the procedure efficiently and eliminates the need to contact each institution. For example, when a user enters information to start a procedure, the system can automatically generate a list of required procedures, track the progress of each procedure in real time, and notify the user, preventing delays and errors in the procedure. In addition, by collecting data from reliable sources and providing it to the user, the user can obtain the information they need in a centralized location.

[0075] A procedure assistance system according to an embodiment includes a reception unit, a generation unit, a tracking unit, a notification unit, and an information providing unit. The reception unit inputs information required for a user to start a procedure. The information required for a user to start a procedure includes, but is not limited to, personal information, the type of procedure, and required documents. The reception unit allows the user to input information using, for example, a web form. The reception unit also allows the user to input information using a mobile app. The reception unit also allows the user to input information using voice input. The generation unit generates a list of required procedures based on the information input by the reception unit. The list of required procedures includes, for example, the name of the procedure, procedure steps, and required documents, but is not limited to, for example. The generation unit generates the list according to, for example, the type of procedure. The generation unit can also improve the accuracy of the list by referring to the user's past procedure history. The tracking unit tracks the progress of the procedure in real time based on the list generated by the generation unit. To track the progress in real time, for example, information may be obtained in cooperation with various institutions. The tracking unit cooperates with, for example, government agencies, local governments, private companies, etc. to obtain the progress of procedures. The notification unit notifies the user of the progress tracked by the tracking unit. The progress of procedures includes, for example, but is not limited to, the status of the procedures, the expected completion date, and required actions. The notification unit notifies the user using, for example, email or push notification. The notification unit can also estimate the user's emotions and adjust the notification method based on the estimated user emotions. The information providing unit collects data from reliable sources and provides it to the user. Reliable sources include, for example, government agencies, official databases, certified information providers, etc., but are not limited to these examples. The information providing unit, for example, periodically updates data to provide the latest information. The information providing unit also has an interface that allows the user to search for information of interest. As a result, the procedure support system according to the embodiment allows the user to efficiently proceed with procedures and eliminates the need to inquire at each institution.

[0076] The reception unit may include an interface through which a user inputs information to start a procedure. Examples of interfaces include, but are not limited to, a web form, a mobile app, and voice input. The reception unit may, for example, allow a user to input information using a web form. The reception unit may also allow a user to input information using a mobile app. For example, a mobile app is designed to allow a user to easily input information. The reception unit may also allow a user to input information using voice input. For example, speech recognition technology may be used to convert a user's voice into text and input information. This allows a user to easily input information to start a procedure.

[0077] The generation unit can generate a list of required procedures based on the information input by the reception unit. The list of required procedures includes, for example, the name of the procedure, the steps of the procedure, and the necessary documents, but is not limited to these examples. The generation unit generates the list according to the type of procedure, for example. For example, in the case of a moving procedure, procedures for address change and contract change are included in the list. The generation unit can also improve the accuracy of the list by referring to the user's past procedure history. For example, the accuracy of the list can be improved based on procedures the user has performed in the past. This allows the user to understand the required procedures at a glance.

[0078] The tracking unit can obtain the progress status of the procedure in real time by cooperating with a specific institution. Examples of specific institutions include, but are not limited to, government institutions, local governments, and private companies. For example, the tracking unit can obtain the progress status of the procedure in cooperation with a government institution. For example, the tracking unit can obtain the progress status of the procedure from a government institution's database. The tracking unit can also obtain the progress status of the procedure in cooperation with a local government. For example, the tracking unit can obtain the progress status of the procedure from a local government's system. The tracking unit can also obtain the progress status of the procedure in cooperation with a private company. For example, the tracking unit can obtain the progress status of the procedure from a private company's system. This allows the user to grasp the progress status of the procedure in real time.

[0079] The notification unit can notify the user of the progress of the procedure. The progress of the procedure includes, but is not limited to, for example, the status of the procedure, the expected completion date, and any necessary actions. The notification unit notifies the user, for example, by email or push notification. For example, if the status of the procedure changes, the system sends the user an email. The notification unit can also notify the user of the progress of the procedure by push notification. For example, if the expected completion date of the procedure approaches, the system sends the user a push notification. This allows the user to immediately know the progress of the procedure.

[0080] The information providing unit can collect data from reliable sources and update it regularly. Examples of reliable sources include, but are not limited to, government agencies, official databases, and certified information providers. The information providing unit, for example, collects data from government agencies. For example, it obtains the latest information from the official database of a government agency. The information providing unit can also collect data from official databases. For example, it collects data from certified information providers. Furthermore, the information providing unit regularly updates the data to provide the latest information. For example, it updates the data daily to provide the user with the latest information. This allows the user to always obtain the latest information.

[0081] The information providing unit may have an interface that allows a user to search for information of interest. Examples of interfaces include, but are not limited to, a web form, a mobile app, and voice input. For example, the information providing unit allows a user to search for information using a web form. The information providing unit may also allow a user to search for information using a mobile app. For example, a mobile app is designed to allow a user to easily search for information. The information providing unit may also allow a user to search for information using voice input. For example, speech recognition technology may be used to convert a user's voice into text and search for information. This allows a user to easily search for required information.

[0082] The reception unit can estimate the user's emotions and adjust the design of the input interface based on the estimated user emotions. For example, if the user is nervous, the reception unit can provide an interface with subdued colors to reduce visual stress. Furthermore, if the user is having fun, the reception unit can provide an interface with bright colors to make input work more enjoyable. Furthermore, if the user is tired, the reception unit can provide a simple, highly visible interface to make input work easier. This provides an interface that corresponds to the user's emotions, making input work more comfortable. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the reception unit can be performed using, for example, AI, or without AI. For example, the reception unit can input the user's facial expression data into the generation AI and have the generation AI perform emotion estimation.

[0083] The reception unit can analyze the user's past procedure history and suggest the optimal input method. For example, the reception unit can automatically display procedures that the user has frequently performed in the past as candidates. The reception unit can also preferentially suggest input methods (voice, text, etc.) that the user has used in the past. Furthermore, the reception unit can predict and suggest procedures to be performed during a specific time period based on the user's past procedure history. This makes input work more efficient by suggesting the optimal input method based on the user's past history.

[0084] The reception unit can dynamically change the layout of the input interface depending on the type of procedure. For example, in the case of moving procedures, the reception unit may prioritize displaying input fields for address changes and contract changes. In addition, in the case of marriage procedures, the reception unit may prioritize displaying input fields for marriage registration and related documents. Furthermore, in the case of study abroad procedures, the reception unit may prioritize displaying input fields for visa applications and university information. This provides an interface according to the type of procedure, making input work more efficient.

[0085] The reception unit can add a function that analyzes the user's input in real time and automatically completes the necessary information. For example, when the user inputs an address, the reception unit can automatically complete the address when the user inputs a postal code. The reception unit can also display names that the user has previously input as candidates when the user inputs a name. Furthermore, the reception unit can automatically complete related information when the user selects a type of procedure. This makes the user's input work more efficient.

[0086] The reception unit can estimate the user's emotions and prioritize input based on the estimated user emotions. For example, if the user is in a hurry, the reception unit can prioritize important procedures. The reception unit can also provide detailed input options if the user is relaxed. Furthermore, the reception unit can provide a simple input interface if the user is stressed. This streamlines input work by providing priorities according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the reception unit can be performed using, for example, AI, or without AI. For example, the reception unit can input the user's facial expression data into the generation AI and have the generation AI perform emotion estimation.

[0087] The reception unit can prioritize displaying region-specific procedure information by taking into account the user's geographical location information. For example, if the user lives in a specific region, the reception unit can prioritize displaying region-specific procedure information. Also, if the user lives overseas, the reception unit can prioritize displaying country-specific procedure information. Furthermore, the reception unit can prioritize displaying procedure information related to the region to which the user has moved. This allows the user to quickly obtain the information they need by providing region-specific procedure information.

[0088] The reception unit can analyze the user's social media activity and automatically suggest related procedural information. For example, if a user announces their marriage on social media, the reception unit automatically suggests information about marriage procedures. In addition, if a user announces their move on social media, the reception unit can automatically suggest information about moving procedures. Furthermore, if a user announces their study abroad on social media, the reception unit can automatically suggest information about study abroad procedures. This makes procedures more efficient by providing related procedural information based on the user's social media activity.

[0089] The reception unit can customize the input interface by reflecting the user's past feedback. For example, the reception unit improves the input interface based on feedback provided by the user in the past. The reception unit can also adjust the input interface to resolve problems pointed out by the user in the past. Furthermore, the reception unit can provide an easier-to-use input interface by referring to the user's past feedback. In this way, usability is improved by improving the interface based on the user's feedback.

[0090] The generation unit can estimate the user's emotions and adjust the display method of the procedure list based on the estimated user emotions. For example, if the user is nervous, the generation unit can provide a simple, highly visible list. Furthermore, if the user is relaxed, the generation unit can also provide a list including detailed information. Furthermore, if the user is in a hurry, the generation unit can prioritize the display of important procedures. This provides a list display that corresponds to the user's emotions, thereby streamlining procedures. The emotion estimation is realized using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the generation unit can be performed using, for example, AI, or without AI. For example, the generation unit can input the user's facial expression data into the generation AI and have the generation AI perform emotion estimation.

[0091] The generation unit can dynamically change the priority of the list based on the importance of the procedure. For example, the generation unit displays important procedures at the top of the list. The generation unit can also display procedures with high urgency at the top of the list. Furthermore, the generation unit can dynamically change the priority of procedures depending on the user's situation. This allows important procedures to be displayed preferentially, thereby making procedures more efficient.

[0092] The generation unit can apply different generation algorithms depending on the procedure category. For example, in the case of moving procedures, the generation unit applies an algorithm that prioritizes displaying procedures for address change and contract change. In addition, in the case of marriage procedures, the generation unit can also apply an algorithm that prioritizes displaying procedures for marriage registration and related documents. Furthermore, in the case of study abroad procedures, the generation unit can also apply an algorithm that prioritizes displaying procedures for visa application and university information. This makes procedures more efficient by providing a list according to the procedure category.

[0093] The generation unit can improve the accuracy of the list by referring to the user's past procedure history. The generation unit improves the accuracy of the list, for example, based on procedures that the user has performed in the past. The generation unit can also add related procedures to the list from the user's past procedure history. Furthermore, the generation unit can analyze the user's past procedure history and display the most appropriate procedures in the list. This improves the accuracy of the list based on the user's past procedure history, thereby making procedures more efficient.

[0094] The generation unit can estimate the user's emotions and adjust the length of the list based on the estimated user emotions. For example, if the user is nervous, the generation unit can provide a short list. Furthermore, if the user is relaxed, the generation unit can provide a long list containing detailed information. Furthermore, if the user is in a hurry, the generation unit can provide a short list that prioritizes important procedures. This provides a list length that corresponds to the user's emotions, thereby streamlining procedures. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the generation unit can be performed using, for example, AI, or without AI. For example, the generation unit can input the user's facial expression data into the generation AI and have the generation AI perform emotion estimation.

[0095] The generation unit can determine the priority of the list based on the submission date of the procedure. For example, the generation unit displays procedures with an upcoming submission deadline at the top of the list. The generation unit can also display procedures whose submission date has passed at the bottom of the list. Furthermore, the generation unit can dynamically change the priority of the list based on the submission date depending on the user's situation. This makes procedures more efficient by providing a list based on the submission date.

[0096] The generation unit can adjust the order of the list based on the relevance of the procedures. For example, the generation unit displays related procedures at the top of the list. The generation unit can also display highly related procedures preferentially depending on the user's situation. Furthermore, the generation unit can dynamically change the order of the list based on the relevance of the procedures. This makes the procedures more efficient by providing a list based on the relevance of the procedures.

[0097] The generator can adjust the use of technical terms in the list according to the user's level of expertise. For example, if the user has technical expertise, the generator can provide a list using technical terms. Alternatively, if the user does not have technical expertise, the generator can provide a list that explains things in simple terms. Furthermore, the generator can dynamically adjust the use of technical terms in the list according to the user's level of expertise. This can streamline the process by providing a list that is appropriate for the user's level of expertise.

[0098] The tracking unit can estimate the user's emotions and adjust the progress display method based on the estimated user emotions. For example, if the user is nervous, the tracking unit can provide a simple, highly visible display method. Furthermore, if the user is relaxed, the tracking unit can provide a display method that includes detailed information. Furthermore, if the user is in a hurry, the tracking unit can provide a display method that focuses on the main points. This streamlines the process by providing a progress display method that corresponds to the user's emotions. The emotion estimation is realized using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, for example, a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the tracking unit can be performed using, for example, an AI, or without an AI. For example, the tracking unit can input the user's facial expression data into the generation AI and have the generation AI perform emotion estimation.

[0099] The tracking unit can improve the accuracy of the progress status by taking into account the interrelationships between procedures. For example, the tracking unit displays the progress status of related procedures all at once. The tracking unit can also adjust the display order of the progress status by taking into account the interrelationships between procedures. Furthermore, the tracking unit can improve the accuracy of the progress status based on the interrelationships between procedures. In this way, the accuracy of the progress status is improved by taking into account the interrelationships between procedures.

[0100] The tracking unit can customize the progress status taking into account attribute information of the person who submitted the procedure. The tracking unit customizes the display method of the progress status according to, for example, the age and gender of the person who submitted the procedure. The tracking unit can also customize the display method of the progress status according to the occupation and expertise of the person who submitted the procedure. Furthermore, the tracking unit can dynamically adjust the display method of the progress status based on the attribute information of the person who submitted the procedure. This makes the procedure more efficient by providing the progress status based on the attribute information of the person who submitted the procedure.

[0101] The tracking unit can weight the progress status based on the frequency of submission of the procedure. For example, the tracking unit can prioritize and display procedures that are submitted more frequently. The tracking unit can also display procedures that are submitted less frequently lower in the list. Furthermore, the tracking unit can dynamically adjust the weighting of the progress status based on the frequency of submission. This allows for the efficiency of procedures by providing progress based on the frequency of submission.

[0102] The tracking unit can estimate the user's emotions and adjust the display order of the progress status based on the estimated user emotions. For example, if the user is nervous, the tracking unit can prioritize displaying important procedures. Furthermore, if the user is relaxed, the tracking unit can provide a display order that includes detailed information. Furthermore, if the user is in a hurry, the tracking unit can provide a display order that focuses on the main points. This provides a display order of the progress status according to the user's emotions, thereby streamlining the procedures. The emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the tracking unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the tracking unit can input the user's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0103] The tracking unit can display the progress status taking into account the geographical distribution of procedures. For example, the tracking unit can prioritize displaying the progress status of procedures in the area where the user lives. The tracking unit can also prioritize displaying the progress status of procedures in the area where the user is moving. Furthermore, the tracking unit can also prioritize displaying the progress status of procedures in areas in which the user is interested. This makes procedures more efficient by providing progress status based on geographical distribution.

[0104] The tracking unit can improve the accuracy of the progress status by referring to related literature of the procedure. The tracking unit can improve the accuracy of the progress status by referring to, for example, related laws and guidelines. The tracking unit can also improve the accuracy of the progress status by referring to related research papers and reports. Furthermore, the tracking unit can improve the accuracy of the progress status by referring to related news articles and blogs. This makes the procedure more efficient by providing progress status based on related literature.

[0105] The tracking unit can display the progress status taking into account the market value of the procedure. For example, the tracking unit can prioritize displaying procedures with high market value. The tracking unit can also display procedures with low market value lower in the list. Furthermore, the tracking unit can dynamically adjust the display order of the progress status based on market value. This allows for the efficiency of procedures by providing progress status based on market value.

[0106] The notification unit can estimate the user's emotions and adjust the notification method based on the estimated user emotions. For example, if the user is nervous, the notification unit can provide a simple, highly visible notification method. Furthermore, if the user is relaxed, the notification unit can provide a notification method that includes detailed information. Furthermore, if the user is in a hurry, the notification unit can provide a notification method that focuses on the main points. This streamlines the process by providing a notification method that matches the user's emotions. The emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the notification unit can be performed using AI, or without AI. For example, the notification unit can input the user's facial expression data into the generation AI and have the generation AI perform emotion estimation.

[0107] The notification unit can adjust the level of detail of the notification based on the importance of the procedure when notifying. For example, the notification unit provides detailed notification for important procedures. The notification unit can also provide detailed notification for highly urgent procedures. Furthermore, the notification unit can dynamically adjust the level of detail of the notification based on the importance of the procedure depending on the user's situation. This allows the procedure to be performed more efficiently by providing notifications based on the importance of the procedure.

[0108] The notification unit can apply different notification algorithms depending on the procedure category when sending notifications. For example, in the case of moving procedures, the notification unit applies an algorithm that prioritizes notifications of address changes and contract changes. In addition, in the case of marriage procedures, the notification unit can also apply an algorithm that prioritizes notifications of marriage registration forms and related documents. Furthermore, in the case of study abroad procedures, the notification unit can also apply an algorithm that prioritizes notifications of visa applications and university information. This makes procedures more efficient by providing notifications according to the procedure category.

[0109] The notification unit can improve the accuracy of notifications by referring to the user's past notification history when providing notifications. The notification unit can improve the accuracy of notifications, for example, based on notifications received by the user in the past. The notification unit can also provide relevant notifications from the user's past notification history. Furthermore, the notification unit can analyze the user's past notification history and provide optimal notifications. This makes procedures more efficient by providing notifications based on the user's past notification history.

[0110] The notification unit can estimate the user's emotions and adjust the timing of notifications based on the estimated user emotions. For example, if the user is nervous, the notification unit can prioritize notifications for important procedures. The notification unit can also provide notifications containing detailed information if the user is relaxed. Furthermore, if the user is in a hurry, the notification unit can provide notifications that focus on the main points. This improves the efficiency of procedures by providing notifications at a timing appropriate to the user's emotions. The emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the notification unit can be performed using, for example, an AI, or can be performed without using an AI. For example, the notification unit can input the user's facial expression data into the generation AI and have the generation AI perform emotion estimation.

[0111] The notification unit can determine the priority of notifications based on the submission time of the procedure when notifying. For example, the notification unit prioritizes notifications for procedures with an approaching submission deadline. The notification unit can also display notifications for procedures whose submission time has passed lower in the notification hierarchy. Furthermore, the notification unit can dynamically change the priority of notifications based on the submission time depending on the user's situation. This makes procedures more efficient by providing notifications based on the submission time.

[0112] The notification unit can adjust the order of notifications based on the relevance of the procedures when notifying. For example, the notification unit prioritizes notifications of related procedures. The notification unit can also prioritize notifications of highly relevant procedures depending on the user's situation. Furthermore, the notification unit can dynamically change the order of notifications based on the relevance of the procedures. This allows for more efficient procedures by providing notifications based on the relevance of the procedures.

[0113] The notification unit can adjust the use of technical terms in the notification depending on the user's level of expertise when providing a notification. For example, if the user has technical expertise, the notification unit provides a notification using technical terms. Also, if the user does not have technical expertise, the notification unit can provide a notification that explains the notification in simple language. Furthermore, the notification unit can dynamically adjust the use of technical terms in the notification depending on the user's level of expertise. This allows for efficient procedures by providing notifications that are tailored to the user's level of expertise.

[0114] The information providing unit can estimate the user's emotions and adjust the information display method based on the estimated user's emotions. For example, if the user is nervous, the information providing unit can provide a simple, highly visible display method. Furthermore, if the user is relaxed, the information providing unit can provide a display method that includes detailed information. Furthermore, if the user is in a hurry, the information providing unit can provide a display method that focuses on the main points. This provides an information display method that corresponds to the user's emotions, thereby deepening the user's understanding of the information. The emotion estimation is realized using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the information providing unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the information providing unit can input the user's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0115] The information providing unit can adjust the level of detail of the display based on the importance of the information when providing the information. For example, the information providing unit provides a detailed display in the case of important information. The information providing unit can also provide a detailed display in the case of highly urgent information. Furthermore, the information providing unit can dynamically adjust the level of detail of the display based on the importance of the information according to the user's situation. This allows for a deeper understanding of the information by providing a display based on the importance of the information.

[0116] When providing information, the information providing unit can apply different display algorithms depending on the category of information. For example, in the case of moving information, the information providing unit applies an algorithm that prioritizes displaying information about address changes and contract changes. In addition, in the case of marriage information, the information providing unit can also apply an algorithm that prioritizes displaying information about marriage registration forms and related documents. Furthermore, in the case of study abroad information, the information providing unit can also apply an algorithm that prioritizes displaying information about visa applications and university information. This allows for a deeper understanding of the information by providing a display according to the category of information.

[0117] When providing information, the information providing unit can improve the accuracy of the display by referring to the user's past information search history. The information providing unit improves the accuracy of the display, for example, based on information searched for by the user in the past. The information providing unit can also display related information from the user's past information search history. Furthermore, the information providing unit can analyze the user's past information search history and display optimal information. This allows for a deeper understanding of the information by providing a display based on the user's past information search history.

[0118] The information providing unit can estimate the user's emotions and adjust the display order of information based on the estimated user emotions. For example, if the user is nervous, the information providing unit can prioritize displaying important information. Furthermore, if the user is relaxed, the information providing unit can provide a display order that includes detailed information. Furthermore, if the user is in a hurry, the information providing unit can provide a display order that focuses on the main points. This provides an information display order that corresponds to the user's emotions, thereby deepening the user's understanding of the information. The emotion estimation is realized using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI may be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the information providing unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the information providing unit can input the user's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0119] When providing information, the information providing unit can determine the display priority based on the time of submission of the information. For example, the information providing unit can preferentially display information whose submission deadline is approaching. The information providing unit can also display information whose submission deadline has passed at a lower level. Furthermore, the information providing unit can dynamically change the display priority based on the time of submission depending on the user's situation. This allows for a deeper understanding of the information by providing information display based on the time of submission.

[0120] The information providing unit can adjust the display order based on the relevance of the information when providing the information. For example, the information providing unit can prioritize displaying related information. The information providing unit can also prioritize displaying highly relevant information according to the user's situation. Furthermore, the information providing unit can dynamically change the display order based on the relevance of the information. This allows for a deeper understanding of the information by providing a display based on the relevance of the information.

[0121] The information providing unit can adjust the use of technical terms in the display according to the user's level of expertise when providing information. For example, if the user has technical knowledge, the information providing unit can provide a display using technical terms. Also, if the user does not have technical knowledge, the information providing unit can provide a display that explains the information in simple terms. Furthermore, the information providing unit can dynamically adjust the use of technical terms in the display according to the user's level of expertise. This allows the user to deepen their understanding of the information by providing a display that suits the user's level of expertise. === Hard Collateral 1-1 === Each of the multiple elements, including the above-mentioned reception unit, generation unit, tracking unit, notification unit, and information provision unit, is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart device 14, and the user inputs information to start a procedure. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and generates a list of required procedures. The tracking unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and tracks the progress of the procedures in real time. The notification unit is realized, for example, by the control unit 46A of the smart device 14, and notifies the user of the progress. The information provision unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and collects data from reliable information sources and provides it to the user. === Hard Collateral 1-2 === Each of the multiple elements, including the above-mentioned reception unit, generation unit, tracking unit, notification unit, and information provision unit, is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart glasses 214, and the user inputs information to start a procedure. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and generates a list of required procedures. The tracking unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and tracks the progress of the procedures in real time. The notification unit is realized, for example, by the control unit 46A of the smart glasses 214, and notifies the user of the progress. The information provision unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and collects data from reliable information sources and provides it to the user. === Hard Collateral 1-3 === Each of the multiple elements including the above-mentioned reception unit, generation unit, tracking unit, notification unit, and information provision unit is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the headset type terminal 314, and the user inputs information to start a procedure. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and generates a list of required procedures. The tracking unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and tracks the progress of the procedures in real time. The notification unit is realized, for example, by the control unit 46A of the headset type terminal 314, and notifies the user of the progress. The information provision unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and collects data from reliable information sources and provides it to the user. === Hard Collateral 1-4 === Each of the multiple elements including the above-mentioned reception unit, generation unit, tracking unit, notification unit, and information provision unit is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the robot 414, and the user inputs information to start a procedure. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and generates a list of required procedures. The tracking unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and tracks the progress of the procedures in real time. The notification unit is realized, for example, by the control unit 46A of the robot 414, and notifies the user of the progress. The information provision unit is realized, for example, by the specific processing unit 290 of the data processing device 12, and collects data from reliable information sources and provides it to the user.

[0122] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0123] The reception unit can add a function that analyzes the user's input in real time and automatically completes the necessary information. For example, when a user enters an address, the address is automatically completed when the user enters a postal code. The reception unit can also display names that the user has entered in the past as candidates when the user enters a name. Furthermore, the reception unit can automatically complete related information when the user selects a type of procedure. This makes the user's input work more efficient.

[0124] The generation unit can dynamically change the priority of the list based on the importance of the procedure. For example, important procedures can be displayed at the top of the list. The generation unit can also display procedures with high urgency at the top of the list. Furthermore, the generation unit can dynamically change the priority of procedures depending on the user's situation. This allows important procedures to be displayed preferentially, thereby making procedures more efficient.

[0125] The tracking unit can improve the accuracy of the progress status by taking into account the interrelationships between procedures. For example, the progress status of related procedures is displayed all at once. The tracking unit can also adjust the display order of the progress status by taking into account the interrelationships between procedures. Furthermore, the tracking unit can improve the accuracy of the progress status based on the interrelationships between procedures. In this way, the accuracy of the progress status is improved by taking into account the interrelationships between procedures.

[0126] The notification unit can adjust the level of detail of the notification based on the importance of the procedure when notifying. For example, for important procedures, detailed notifications are provided. The notification unit can also provide detailed notifications for procedures with high urgency. Furthermore, the notification unit can dynamically adjust the level of detail of the notification based on the importance of the procedure depending on the user's situation. This allows the procedure to be performed more efficiently by providing notifications based on the importance of the procedure.

[0127] The information providing unit can adjust the level of detail of the display based on the importance of the information when providing the information. For example, if the information is important, a detailed display is provided. The information providing unit can also provide a detailed display if the information is highly urgent. Furthermore, the information providing unit can dynamically adjust the level of detail of the display based on the importance of the information according to the user's situation. This allows for a deeper understanding of the information by providing a display based on the importance of the information.

[0128] The reception unit can estimate the user's emotions and adjust the design of the input interface based on the estimated user's emotions. For example, if the user is nervous, the reception unit can provide an interface with subdued colors to reduce visual stress. If the user is having fun, the reception unit can provide an interface with bright colors to make input work more enjoyable. If the user is tired, the reception unit can provide a simple, highly visible interface to make input work easier. Thus, by providing an interface that corresponds to the user's emotions, input work becomes more comfortable.

[0129] The generation unit can estimate the user's emotions and adjust the display method of the procedure list based on the estimated user emotions. For example, if the user is nervous, a simple, highly visible list is provided. The generation unit can also provide a list including detailed information if the user is relaxed. Furthermore, if the user is in a hurry, the generation unit can prioritize the display of important procedures. In this way, by providing a list display according to the user's emotions, procedures become more efficient.

[0130] The tracking unit can estimate the user's emotions and adjust the display method of the progress status based on the estimated user's emotions. For example, if the user is nervous, a simple, highly visible display method is provided. Alternatively, if the user is relaxed, the tracking unit can provide a display method including detailed information. Furthermore, if the user is in a hurry, the tracking unit can provide a display method that focuses on the main points. This makes the process more efficient by providing a display method of the progress status according to the user's emotions.

[0131] The notification unit can estimate the user's emotions and adjust the notification method based on the estimated user's emotions. For example, if the user is nervous, a simple, highly visible notification method is provided. If the user is relaxed, the notification unit can also provide a notification method that includes detailed information. Furthermore, if the user is in a hurry, the notification unit can also provide a notification method that focuses on the main points. In this way, by providing a notification method that corresponds to the user's emotions, procedures are made more efficient.

[0132] The information providing unit can estimate the user's emotions and adjust the information display method based on the estimated user's emotions. For example, if the user is nervous, a simple, highly visible display method is provided. The information providing unit can also provide a display method including detailed information if the user is relaxed. Furthermore, if the user is in a hurry, the information providing unit can also provide a display method that focuses on the main points. In this way, by providing an information display method that corresponds to the user's emotions, the user can better understand the information.

[0133] The processing flow of the second embodiment will be briefly explained below.

[0134] Step 1: The reception unit inputs information for the user to start the procedure. The information for the user to start the procedure includes, for example, personal information, the type of procedure, and required documents. The reception unit allows the user to input information using a web form, a mobile app, voice input, etc. Step 2: The generator generates a list of required procedures based on the information input by the reception unit. The list of required procedures includes the name of the procedure, procedure steps, required documents, etc. The generator generates the list according to the type of procedure and can also improve the accuracy of the list by referring to the user's past procedure history. Step 3: The tracking unit tracks the progress of the procedures in real time based on the list generated by the generation unit. To track the progress in real time, the tracking unit cooperates with each institution to obtain information. The tracking unit cooperates with government agencies, local governments, private companies, etc. to obtain the progress of the procedures. Step 4: The notification unit notifies the user of the progress tracked by the tracking unit. The progress of the procedure includes the procedure status, expected completion date, required actions, etc. The notification unit notifies the user via email or push notification, and can also adjust the notification method by estimating the user's emotions. Step 5: The information provider collects data from reliable sources and provides it to users. Reliable sources include government agencies, official databases, and certified information providers. The information provider updates the data regularly to provide the latest information. It also provides an interface that allows users to search for information of interest.

[0135] 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.

[0136] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<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.

[0137] 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.

[0138] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0139] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0140] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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).

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0153] 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.

[0154] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0155] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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).

[0161] 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.

[0162] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset 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.

[0163] 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.

[0164] 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.

[0165] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification 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 identification processing unit 290 using these models.

[0166] 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.

[0167] 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.

[0168] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0169] 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.

[0170] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0171] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0172] 7, a 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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).

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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.

[0182] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0183] 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.

[0184] 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.

[0185] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0186] 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.

[0187] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0188] 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.

[0189] 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.

[0190] 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.

[0191] 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).

[0192] 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.

[0193] 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."

[0194] 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.

[0195] 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.

[0196] 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.

[0197] 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.

[0198] 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.

[0199] 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.

[0200] 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.

[0201] 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.

[0202] 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.

[0203] 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.

[0204] 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, in order to avoid confusion and to 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.

[0205] 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.

[0206] [Explanation of symbols]

[0207] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a reception unit for inputting information for a user to start a procedure; a generating unit that generates a list of necessary procedures based on the information input by the receiving unit; a tracking unit that tracks the progress of the procedure in real time based on the list generated by the generating unit; a notification unit that notifies a user of the progress tracked by the tracking unit; an information providing unit that collects data from reliable information sources and provides it to the user; A system characterized by:

2. The reception unit Provides an interface for users to enter information to begin a procedure 2. The system of claim 1.

3. The generation unit A list of necessary procedures is generated based on the information input by the reception unit.

2. The system of claim 1.

4. The tracking unit Collaborate with specific agencies to get real-time progress updates on procedures 2. The system of claim 1.

5. The notification unit Notify the user of the progress of the procedure 2. The system of claim 1.

6. The information providing unit Collect data from reliable sources and update it regularly 2. The system of claim 1.

7. The information providing unit Provide an interface that allows users to search for information of interest 2. The system of claim 1.

8. The reception unit Estimate user emotions and adjust the design of the input interface based on the estimated user emotions.

2. The system of claim 1.

9. The reception unit Analyze the user's past procedure history and suggest the optimal input method 2. The system of claim 1.

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