system

Abstract

The system according to this embodiment aims to efficiently manage and optimize the wide range of tasks involved in wedding preparations. [Solution] The system according to the embodiment comprises a schedule management unit, an action proposal unit, and a task optimization unit. The schedule management unit manages the couple's schedule. The action proposal unit predicts and proposes necessary actions based on the schedule managed by the schedule management unit. The task optimization unit optimizes each task based on the actions proposed by the action proposal unit.

Description

Technical Field

[0006] , ,

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0005] The system according to the embodiment aims to efficiently manage and optimize various tasks in wedding preparations.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a schedule management unit, an action proposal unit, and a task optimization unit. The schedule management unit manages the couple's schedule. The action proposal unit predicts and proposes necessary actions based on the schedule managed by the schedule management unit. The task optimization unit optimizes each task based on the actions proposed by the action proposal unit. [Effects of the Invention]

[0007] The system according to this embodiment can efficiently manage and optimize the wide range of tasks involved in wedding preparations. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

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

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

[0014] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between a plurality of 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), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

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

[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, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are 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 comprises a computer 36, a receiving device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

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

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction 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 a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also 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 processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The AI ​​concierge service according to an embodiment of the present invention is a system that centrally manages and seamlessly supports all steps of wedding preparation. This system autonomously manages the couple's schedule and predicts and suggests the necessary actions at each step of wedding preparation. For example, the AI ​​concierge service automatically optimizes the schedule for venue visits and also automates the timing of invitation mailings and the scheduling of rehearsals. It also optimizes a wide range of tasks, such as wedding preparations, moving, purchasing furniture and appliances, meeting with venues, choosing attire, and deciding on wedding performances, thereby reducing the burden on the couple. For example, the AI ​​concierge service automatically optimizes the schedule simply by inputting the couple's wishes and plans. When the couple inputs their desired dates for venue visits, the AI ​​suggests the optimal dates. Next, the AI ​​predicts and suggests the necessary actions at each step of wedding preparation. For example, it automates the timing of invitation mailings and the scheduling of rehearsals. This allows the couple to proceed with wedding preparations without hassle. Furthermore, the AI ​​optimizes a wide range of tasks, such as wedding preparations, moving, purchasing furniture and appliances, meeting with venues, choosing attire, and deciding on wedding performances. For example, AI can suggest the most suitable furniture and appliances based on a couple's preferences and support them through the purchase process. It can also automatically adjust schedules for meetings with wedding venues and selecting wedding attire. This reduces the burden of wedding preparations for couples and allows them to proceed smoothly. For instance, by having AI manage a couple's schedule and suggest necessary actions, couples can proceed with wedding preparations without stress. Furthermore, by having AI optimize a wide range of tasks, couples can proceed with preparations efficiently. In this way, AI concierge services can efficiently support couples in their wedding preparations and reduce their burden.

[0029] The AI ​​concierge service according to this embodiment comprises a schedule management unit, an action suggestion unit, and a task optimization unit. The schedule management unit manages the couple's schedule. For example, the schedule management unit optimizes the schedule simply by inputting the couple's wishes and plans. The schedule management unit can suggest the optimal dates when the couple inputs their desired dates for visiting wedding venues. The schedule management unit autonomously manages the couple's schedule and predicts and suggests the necessary actions at each step of wedding preparation. The action suggestion unit predicts and suggests the necessary actions based on the schedule managed by the schedule management unit. For example, the action suggestion unit automates the timing of sending invitations and scheduling rehearsals. The action suggestion unit suggests the necessary actions so that the couple can proceed with wedding preparations without hassle. The action suggestion unit can suggest the optimal actions based on the couple's wishes and plans. The task optimization unit optimizes each task based on the actions suggested by the action suggestion unit. For example, the task optimization unit optimizes tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with wedding venues, choosing attire, and deciding on performances. The task optimization unit proposes the most suitable furniture and home appliances based on the couple's wishes and supports the purchase process. The task optimization unit can automatically adjust the schedule for meetings with the wedding venue and for selecting wedding attire. As a result, the AI ​​concierge service according to this embodiment can efficiently support the couple's wedding preparations and reduce their burden. Some or all of the above-mentioned processes in the schedule management unit, action proposal unit, and task optimization unit may be performed using AI, for example, or not using AI. For example, the schedule management unit can input the couple's wishes and plans into the AI ​​and have the AI ​​perform schedule optimization. The action proposal unit can predict and propose necessary actions using AI. The task optimization unit can optimize each task using AI. As a result, the AI ​​concierge service can efficiently support the couple's wedding preparations and reduce their burden.

[0030] The Schedule Management Department manages the couple's schedule. For example, the Schedule Management Department optimizes the schedule simply by having the couple input their wishes and plans. Specifically, when the couple inputs their desired dates for visiting wedding venues, the Schedule Management Department uses AI to consider the couple's other plans and venue availability to suggest the optimal dates. The AI ​​learns the couple's past schedule data and patterns to generate the most efficient and stress-free schedule. For example, if the couple has work or other important appointments, the AI ​​will suggest venue visit dates that avoid those appointments. The Schedule Management Department also autonomously manages the couple's schedule and predicts and suggests necessary actions at each step of wedding preparation. For example, it lists the tasks and events necessary for wedding preparation and suggests the optimal timing for each task. This makes it easier for the couple to grasp the overall picture of wedding preparation and proceed with preparations systematically. Furthermore, the Schedule Management Department has a function to update the couple's schedule in real time and immediately notify them of any changes. This allows the couple to always know the latest schedule and respond flexibly. The schedule management department allows couples to input their wishes and plans into an AI, which then optimizes the schedule. This enables the schedule management department to efficiently support couples in their wedding preparations and reduce their burden.

[0031] The Action Proposal Department predicts and proposes necessary actions based on the schedule managed by the Schedule Management Department. Specifically, it automates tasks such as sending out invitations and scheduling rehearsals. The Action Proposal Department proposes necessary actions so that couples can proceed with wedding preparations without hassle. For example, the AI ​​analyzes the couple's schedule and calculates the optimal time to send out invitations. This takes into account factors such as the guests' addresses, the time it takes to mail them, and the time required for designing and printing the invitations. Similarly, when scheduling rehearsals, the AI ​​considers the schedules of the couple and those involved and proposes the optimal date that everyone can attend. Furthermore, the Action Proposal Department can propose optimal actions based on the couple's wishes and plans. For example, if the couple wants a wedding with a specific theme or style, the AI ​​will suggest decoration and performance ideas that match that theme. Also, if the couple has set a budget, the AI ​​can suggest the best options within that budget. The Action Proposal Department can predict and propose necessary actions using AI. This allows the Action Proposal Department to efficiently support couples in their wedding preparations and reduce their burden.

[0032] The Task Optimization Department optimizes each task based on actions proposed by the Action Proposal Department. Specifically, it optimizes tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on wedding entertainment. The Task Optimization Department proposes the most suitable furniture and appliances based on the couple's wishes and supports the purchase process. For example, AI considers the couple's preferences, budget, and necessary functions to propose the most suitable furniture and appliances. It also integrates with online shopping sites to simplify the purchase process. Furthermore, the Task Optimization Department can automatically adjust the schedule for meetings with the venue and attire selection. AI considers the schedules of the couple and the venue staff to propose the most suitable meeting dates. In addition, for attire selection, AI proposes outfits that suit the couple's preferences and body type and adjusts the fitting schedule. This allows the couple to proceed with the attire selection efficiently. The Task Optimization Department can optimize each task using AI. As a result, the Task Optimization Department can efficiently support the couple's wedding preparations and reduce their burden.

[0033] The schedule management system can optimize a couple's schedule simply by inputting their preferences and plans. For example, if a couple inputs their desired date locations or planned events, the system will suggest the optimal schedule. The schedule management system can optimize the schedule based on the couple's preferences and plans. The schedule management system allows the couple's preferences and plans to be input into an AI, which then performs the schedule optimization. This enables the schedule to be optimized based on the couple's preferences and plans.

[0034] The Action Proposal Department can automate the timing of invitation mailing and rehearsal scheduling. For example, the Action Proposal Department can propose a mailing date calculated backward from the event date. The Action Proposal Department can automate the timing of invitation mailing. The Action Proposal Department can automate the scheduling of rehearsals. The Action Proposal Department can adjust participants' schedules and optimize rehearsal dates. The Action Proposal Department can use AI to automate the timing of invitation mailing and rehearsal scheduling. This automates the timing of invitation mailing and rehearsal scheduling.

[0035] The Task Optimization Unit can optimize tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on wedding entertainment. For example, for wedding preparations, the Task Optimization Unit optimizes tasks such as creating invitations, booking the venue, and preparing decorations. For moving tasks, the Task Optimization Unit optimizes tasks such as arranging moving companies, packing belongings, and changing addresses. For purchasing furniture and appliances, the Task Optimization Unit optimizes tasks such as creating a list of items to purchase, setting a budget, and selecting suppliers. For meetings with the venue, the Task Optimization Unit optimizes tasks such as setting meeting dates and times, preparing agendas, and creating lists of items to be confirmed. For choosing attire, the Task Optimization Unit optimizes tasks such as booking fittings, selecting designs, and confirming sizes. For deciding on wedding entertainment, the Task Optimization Unit optimizes tasks such as brainstorming ideas for entertainment, planning rehearsals, and preparing necessary equipment. The Task Optimization Unit can use AI to optimize tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on wedding entertainment. This optimizes tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on the wedding's presentation.

[0036] The Task Optimization Unit can suggest the most suitable furniture and appliances based on a couple's preferences and support the purchase process. For example, the Task Optimization Unit suggests the most suitable furniture and appliances based on the couple's tastes and budget. The Task Optimization Unit evaluates functionality and design to suggest the most suitable furniture and appliances. To support the purchase process, the Task Optimization Unit assists with selecting suppliers and guiding the purchase process. Using AI, the Task Optimization Unit can suggest the most suitable furniture and appliances based on a couple's preferences and support the purchase process. This allows the Unit to suggest the most suitable furniture and appliances based on a couple's preferences and support the purchase process.

[0037] The task optimization unit can automatically adjust the schedule for meetings with the wedding venue and for selecting wedding attire. For example, the task optimization unit optimizes the frequency and agenda setting of meetings. The task optimization unit creates a list of items to be confirmed and adjusts the meeting schedule. The task optimization unit optimizes the booking of fittings and the selection of designs. The task optimization unit adjusts the schedule for size confirmation and fittings. The task optimization unit can use AI to automatically adjust the schedule for meetings with the wedding venue and for selecting wedding attire. As a result, the schedule for meetings with the wedding venue and for selecting wedding attire is automatically adjusted.

[0038] The schedule management department can analyze a couple's past schedule history and select the optimal schedule management method. For example, the schedule management department can propose the optimal schedule based on the couple's past successful schedule patterns. The schedule management department selects an efficient schedule management method from the couple's past schedule history. The schedule management department analyzes the couple's past schedule history and proposes ways to reduce wasted time. The schedule management department can use AI to analyze the couple's past schedule history and select the optimal schedule management method. This allows the department to analyze the couple's past schedule history and select the optimal schedule management method.

[0039] The schedule management department can optimize schedules by taking into account the couple's lifestyle and work schedules. For example, the schedule management department can propose an optimal schedule that matches the couple's lifestyle. The schedule management department can create a manageable schedule by considering the couple's work schedules. The schedule management department can integrate the couple's lifestyle and work schedules to propose a balanced schedule. The schedule management department can use AI to optimize schedules by taking into account the couple's lifestyle and work schedules. This allows for schedule optimization that takes into account the couple's lifestyle and work schedules.

[0040] The schedule management system can prioritize highly relevant schedules by considering the couple's geographical location. For example, if the couple is nearby, the system prioritizes tasks they can do together. If the couple is far apart, the system prioritizes tasks that can be done online. The system proposes an efficient schedule based on the couple's geographical location. The schedule management system uses AI to prioritize highly relevant schedules by considering the couple's geographical location. This allows the system to prioritize highly relevant schedules by considering the couple's geographical location.

[0041] The schedule management department can analyze a couple's social media activity and manage related schedules during the scheduling process. For example, the schedule management department analyzes a couple's social media activity and incorporates important events into the schedule. The schedule management department reflects plans with friends and family based on the couple's social media activity into the schedule. The schedule management department proposes an efficient schedule based on the couple's social media activity. The schedule management department can use AI to analyze a couple's social media activity and manage related schedules during the scheduling process. This allows for the analysis of a couple's social media activity and the management of related schedules.

[0042] The action proposal unit can adjust the level of detail in its proposals based on the importance of each action. For example, it adds detailed explanations to important actions and concise explanations to less important actions. The action proposal unit adjusts the level of detail in its proposals according to the importance of each action. The action proposal unit can use AI to adjust the level of detail in its proposals based on the importance of each action. This allows it to adjust the level of detail in its proposals based on the importance of each action.

[0043] The action suggestion unit can apply different suggestion algorithms depending on the category of each action when suggesting actions. For example, for the action of visiting a wedding venue, the action suggestion unit applies an algorithm that suggests the optimal date for visiting. For the action of sending invitations, the action suggestion unit applies an algorithm that suggests the optimal timing for sending invitations. For the action of scheduling a rehearsal, the action suggestion unit applies an algorithm that suggests the optimal date for a rehearsal. The action suggestion unit can use AI to apply different suggestion algorithms depending on the category of each action when suggesting actions. This allows for the application of different suggestion algorithms depending on the category of each action.

[0044] The action proposal department can determine the priority of proposals based on the implementation timing of each action when proposing actions. For example, the action proposal department will prioritize proposing actions that should be implemented urgently. The action proposal department will postpone actions that are far in the future. The action proposal department will determine the priority of proposals based on the implementation timing of each action. The action proposal department can use AI to determine the priority of proposals based on the implementation timing of each action when proposing actions. This allows the priority of proposals to be determined based on the implementation timing of each action.

[0045] The action proposal unit can adjust the order of proposed actions based on the relevance of each action when proposing actions. For example, the action proposal unit proposes highly relevant actions consecutively. The action proposal unit postpones actions with low relevance. The action proposal unit adjusts the order of proposed actions based on the relevance of each action. The action proposal unit can use AI to adjust the order of proposed actions based on the relevance of each action when proposing actions. This allows the order of proposed actions to be adjusted based on the relevance of each action.

[0046] The task optimization unit can analyze a couple's past task history to select the optimal optimization method during task optimization. For example, the task optimization unit proposes the optimal task based on the couple's past successful task patterns. The task optimization unit selects an efficient task optimization method from the couple's past task history. The task optimization unit analyzes the couple's past task history and proposes ways to reduce wasted time. The task optimization unit can use AI to analyze a couple's past task history to select the optimal optimization method during task optimization. This allows the system to analyze the couple's past task history and select the optimal optimization method.

[0047] The task optimization unit can customize the task optimization method based on the couple's current lifestyle during task optimization. For example, the task optimization unit proposes the most suitable tasks based on the couple's current lifestyle. The task optimization unit creates manageable tasks considering the couple's lifestyle. The task optimization unit integrates the couple's lifestyle and work schedule to propose well-balanced tasks. The task optimization unit can use AI to customize the task optimization method based on the couple's current lifestyle during task optimization. This allows the task optimization method to be customized based on the couple's current lifestyle.

[0048] The task optimization unit can select the optimal task optimization method by considering the couple's geographical location information during task optimization. For example, if the couple is nearby, the task optimization unit prioritizes tasks that can be done together. If the couple is far apart, the task optimization unit prioritizes tasks that can be done online. The task optimization unit proposes efficient tasks based on the couple's geographical location information. The task optimization unit can select the optimal task optimization method by considering the couple's geographical location information during task optimization using AI. This allows the system to select the optimal task optimization method by considering the couple's geographical location information.

[0049] The task optimization unit can analyze a couple's social media activity during task optimization and propose methods for optimizing the task. For example, the task optimization unit analyzes the couple's social media activity and incorporates important events into the task. The task optimization unit reflects the couple's plans with friends and family into the task based on their social media activity. The task optimization unit proposes efficient tasks based on the couple's social media activity. The task optimization unit can use AI to analyze a couple's social media activity during task optimization and propose methods for optimizing the task. This allows it to analyze a couple's social media activity and propose methods for optimizing the task.

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

[0051] The scheduling department can monitor the couple's health and adjust their schedule based on that health status. For example, if one partner is unwell, important tasks can be postponed, and rest time can be increased. It can also analyze the couple's health data and incorporate health-maintaining activities into their schedule. Furthermore, it can offer suggestions for diet and exercise based on their health status, providing support for a healthy lifestyle. This allows for schedule adjustments based on the couple's health, supporting a healthy wedding preparation.

[0052] The Action Proposal Department can suggest wedding preparation actions based on the couple's hobbies and interests. For example, if the couple enjoys the outdoors, they can suggest an outdoor wedding idea. If the couple enjoys cooking, they can suggest wedding preparation actions that incorporate cooking classes. Furthermore, if the couple loves music, they can suggest wedding arrangements that include music events or live performances. In this way, they can propose wedding preparation actions based on the couple's hobbies and interests, supporting them in creating a more unique and enjoyable wedding.

[0053] The task optimization unit supports couples in managing their budget and can propose the most suitable tasks based on that budget. For example, it can suggest the best venue and attire according to the couple's budget. It can also suggest cost-saving methods to maximize effectiveness within the budget. Furthermore, it can suggest decorations and staging that meet the couple's wishes within the budget. In this way, it can propose the most suitable tasks based on the couple's budget and support them in making economical wedding preparations.

[0054] The scheduling department can adjust the wedding preparation schedule, taking into account the schedules of the couple's family and friends. For example, they can prioritize dates when family and friends can attend when scheduling venue visits and rehearsals. They can also determine the timing of invitation mailings and event dates to match the schedules of family and friends. Furthermore, they can adjust the division of roles and the order of speeches on the wedding day, taking into account the schedules of family and friends. In this way, they can adjust the wedding preparation schedule, taking into account the schedules of the couple's family and friends, and support smooth wedding preparations.

[0055] The following briefly describes the processing flow for example form 1.

[0056] Step 1: The schedule management unit manages the couple's schedule. For example, simply by entering the couple's wishes and plans, the unit optimizes the schedule, and if the couple enters their desired venue visit dates, it can suggest the best dates. The schedule management unit autonomously manages the couple's schedule and predicts and suggests the necessary actions at each step of wedding preparation. Step 2: The Action Proposal Department predicts and proposes necessary actions based on the schedule managed by the Schedule Management Department. For example, it proposes actions such as automating the timing of sending out invitations and scheduling rehearsals, so that couples can proceed with wedding preparations without hassle. Step 3: The Task Optimization Unit optimizes each task based on the actions proposed by the Action Proposal Unit. For example, it optimizes tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on the wedding's presentation. It also proposes the most suitable furniture and appliances based on the couple's wishes and supports the purchase process. Furthermore, it can automatically adjust the schedule for meetings with the venue and choosing attire.

[0057] (Example of form 2) The AI ​​concierge service according to an embodiment of the present invention is a system that centrally manages and seamlessly supports all steps of wedding preparation. This system autonomously manages the couple's schedule and predicts and suggests the necessary actions at each step of wedding preparation. For example, the AI ​​concierge service automatically optimizes the schedule for venue visits and also automates the timing of invitation mailings and the scheduling of rehearsals. It also optimizes a wide range of tasks, such as wedding preparations, moving, purchasing furniture and appliances, meeting with venues, choosing attire, and deciding on wedding performances, thereby reducing the burden on the couple. For example, the AI ​​concierge service automatically optimizes the schedule simply by inputting the couple's wishes and plans. When the couple inputs their desired dates for venue visits, the AI ​​suggests the optimal dates. Next, the AI ​​predicts and suggests the necessary actions at each step of wedding preparation. For example, it automates the timing of invitation mailings and the scheduling of rehearsals. This allows the couple to proceed with wedding preparations without hassle. Furthermore, the AI ​​optimizes a wide range of tasks, such as wedding preparations, moving, purchasing furniture and appliances, meeting with venues, choosing attire, and deciding on wedding performances. For example, AI can suggest the most suitable furniture and appliances based on a couple's preferences and support them through the purchase process. It can also automatically adjust schedules for meetings with wedding venues and selecting wedding attire. This reduces the burden of wedding preparations for couples and allows them to proceed smoothly. For instance, by having AI manage a couple's schedule and suggest necessary actions, couples can proceed with wedding preparations without stress. Furthermore, by having AI optimize a wide range of tasks, couples can proceed with preparations efficiently. In this way, AI concierge services can efficiently support couples in their wedding preparations and reduce their burden.

[0058] The AI ​​concierge service according to this embodiment comprises a schedule management unit, an action suggestion unit, and a task optimization unit. The schedule management unit manages the couple's schedule. For example, the schedule management unit optimizes the schedule simply by inputting the couple's wishes and plans. The schedule management unit can suggest the optimal dates when the couple inputs their desired dates for visiting wedding venues. The schedule management unit autonomously manages the couple's schedule and predicts and suggests the necessary actions at each step of wedding preparation. The action suggestion unit predicts and suggests the necessary actions based on the schedule managed by the schedule management unit. For example, the action suggestion unit automates the timing of sending invitations and scheduling rehearsals. The action suggestion unit suggests the necessary actions so that the couple can proceed with wedding preparations without hassle. The action suggestion unit can suggest the optimal actions based on the couple's wishes and plans. The task optimization unit optimizes each task based on the actions suggested by the action suggestion unit. For example, the task optimization unit optimizes tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with wedding venues, choosing attire, and deciding on performances. The task optimization unit proposes the most suitable furniture and home appliances based on the couple's wishes and supports the purchase process. The task optimization unit can automatically adjust the schedule for meetings with the wedding venue and for selecting wedding attire. As a result, the AI ​​concierge service according to this embodiment can efficiently support the couple's wedding preparations and reduce their burden. Some or all of the above-mentioned processes in the schedule management unit, action proposal unit, and task optimization unit may be performed using AI, for example, or not using AI. For example, the schedule management unit can input the couple's wishes and plans into the AI ​​and have the AI ​​perform schedule optimization. The action proposal unit can predict and propose necessary actions using AI. The task optimization unit can optimize each task using AI. As a result, the AI ​​concierge service can efficiently support the couple's wedding preparations and reduce their burden.

[0059] The Schedule Management Department manages the couple's schedule. For example, the Schedule Management Department optimizes the schedule simply by having the couple input their wishes and plans. Specifically, when the couple inputs their desired dates for visiting wedding venues, the Schedule Management Department uses AI to consider the couple's other plans and venue availability to suggest the optimal dates. The AI ​​learns the couple's past schedule data and patterns to generate the most efficient and stress-free schedule. For example, if the couple has work or other important appointments, the AI ​​will suggest venue visit dates that avoid those appointments. The Schedule Management Department also autonomously manages the couple's schedule and predicts and suggests necessary actions at each step of wedding preparation. For example, it lists the tasks and events necessary for wedding preparation and suggests the optimal timing for each task. This makes it easier for the couple to grasp the overall picture of wedding preparation and proceed with preparations systematically. Furthermore, the Schedule Management Department has a function to update the couple's schedule in real time and immediately notify them of any changes. This allows the couple to always know the latest schedule and respond flexibly. The schedule management department allows couples to input their wishes and plans into an AI, which then optimizes the schedule. This enables the schedule management department to efficiently support couples in their wedding preparations and reduce their burden.

[0060] The Action Proposal Department predicts and proposes necessary actions based on the schedule managed by the Schedule Management Department. Specifically, it automates tasks such as sending out invitations and scheduling rehearsals. The Action Proposal Department proposes necessary actions so that couples can proceed with wedding preparations without hassle. For example, the AI ​​analyzes the couple's schedule and calculates the optimal time to send out invitations. This takes into account factors such as the guests' addresses, the time it takes to mail them, and the time required for designing and printing the invitations. Similarly, when scheduling rehearsals, the AI ​​considers the schedules of the couple and those involved and proposes the optimal date that everyone can attend. Furthermore, the Action Proposal Department can propose optimal actions based on the couple's wishes and plans. For example, if the couple wants a wedding with a specific theme or style, the AI ​​will suggest decoration and performance ideas that match that theme. Also, if the couple has set a budget, the AI ​​can suggest the best options within that budget. The Action Proposal Department can predict and propose necessary actions using AI. This allows the Action Proposal Department to efficiently support couples in their wedding preparations and reduce their burden.

[0061] The Task Optimization Department optimizes each task based on actions proposed by the Action Proposal Department. Specifically, it optimizes tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on wedding entertainment. The Task Optimization Department proposes the most suitable furniture and appliances based on the couple's wishes and supports the purchase process. For example, AI considers the couple's preferences, budget, and necessary functions to propose the most suitable furniture and appliances. It also integrates with online shopping sites to simplify the purchase process. Furthermore, the Task Optimization Department can automatically adjust the schedule for meetings with the venue and attire selection. AI considers the schedules of the couple and the venue staff to propose the most suitable meeting dates. In addition, for attire selection, AI proposes outfits that suit the couple's preferences and body type and adjusts the fitting schedule. This allows the couple to proceed with the attire selection efficiently. The Task Optimization Department can optimize each task using AI. As a result, the Task Optimization Department can efficiently support the couple's wedding preparations and reduce their burden.

[0062] The schedule management system can optimize a couple's schedule simply by inputting their preferences and plans. For example, if a couple inputs their desired date locations or planned events, the system will suggest the optimal schedule. The schedule management system can optimize the schedule based on the couple's preferences and plans. The schedule management system allows the couple's preferences and plans to be input into an AI, which then performs the schedule optimization. This enables the schedule to be optimized based on the couple's preferences and plans.

[0063] The Action Proposal Department can automate the timing of invitation mailing and rehearsal scheduling. For example, the Action Proposal Department can propose a mailing date calculated backward from the event date. The Action Proposal Department can automate the timing of invitation mailing. The Action Proposal Department can automate the scheduling of rehearsals. The Action Proposal Department can adjust participants' schedules and optimize rehearsal dates. The Action Proposal Department can use AI to automate the timing of invitation mailing and rehearsal scheduling. This automates the timing of invitation mailing and rehearsal scheduling.

[0064] The Task Optimization Unit can optimize tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on wedding entertainment. For example, for wedding preparations, the Task Optimization Unit optimizes tasks such as creating invitations, booking the venue, and preparing decorations. For moving tasks, the Task Optimization Unit optimizes tasks such as arranging moving companies, packing belongings, and changing addresses. For purchasing furniture and appliances, the Task Optimization Unit optimizes tasks such as creating a list of items to purchase, setting a budget, and selecting suppliers. For meetings with the venue, the Task Optimization Unit optimizes tasks such as setting meeting dates and times, preparing agendas, and creating lists of items to be confirmed. For choosing attire, the Task Optimization Unit optimizes tasks such as booking fittings, selecting designs, and confirming sizes. For deciding on wedding entertainment, the Task Optimization Unit optimizes tasks such as brainstorming ideas for entertainment, planning rehearsals, and preparing necessary equipment. The Task Optimization Unit can use AI to optimize tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on wedding entertainment. This optimizes tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on the wedding's presentation.

[0065] The Task Optimization Unit can suggest the most suitable furniture and appliances based on a couple's preferences and support the purchase process. For example, the Task Optimization Unit suggests the most suitable furniture and appliances based on the couple's tastes and budget. The Task Optimization Unit evaluates functionality and design to suggest the most suitable furniture and appliances. To support the purchase process, the Task Optimization Unit assists with selecting suppliers and guiding the purchase process. Using AI, the Task Optimization Unit can suggest the most suitable furniture and appliances based on a couple's preferences and support the purchase process. This allows the Unit to suggest the most suitable furniture and appliances based on a couple's preferences and support the purchase process.

[0066] The task optimization unit can automatically adjust the schedule for meetings with the wedding venue and for selecting wedding attire. For example, the task optimization unit optimizes the frequency and agenda setting of meetings. The task optimization unit creates a list of items to be confirmed and adjusts the meeting schedule. The task optimization unit optimizes the booking of fittings and the selection of designs. The task optimization unit adjusts the schedule for size confirmation and fittings. The task optimization unit can use AI to automatically adjust the schedule for meetings with the wedding venue and for selecting wedding attire. As a result, the schedule for meetings with the wedding venue and for selecting wedding attire is automatically adjusted.

[0067] The schedule management unit can estimate the couple's emotions and adjust the schedule based on those estimates. For example, if the couple is stressed, the schedule management unit will incorporate relaxation time into the schedule. If the couple is excited, the schedule management unit will prioritize important tasks in the schedule. If the couple is tired, the schedule management unit will allocate more rest time. The schedule management unit can estimate the couple's emotions using an emotion estimation function, such as an emotion engine or generative AI, and adjust the schedule based on those estimates. Generative AI can be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. This allows for schedule adjustments based on the couple's emotions.

[0068] The schedule management department can analyze a couple's past schedule history and select the optimal schedule management method. For example, the schedule management department can propose the optimal schedule based on the couple's past successful schedule patterns. The schedule management department selects an efficient schedule management method from the couple's past schedule history. The schedule management department analyzes the couple's past schedule history and proposes ways to reduce wasted time. The schedule management department can use AI to analyze the couple's past schedule history and select the optimal schedule management method. This allows the department to analyze the couple's past schedule history and select the optimal schedule management method.

[0069] The schedule management department can optimize schedules by taking into account the couple's lifestyle and work schedules. For example, the schedule management department can propose an optimal schedule that matches the couple's lifestyle. The schedule management department can create a manageable schedule by considering the couple's work schedules. The schedule management department can integrate the couple's lifestyle and work schedules to propose a balanced schedule. The schedule management department can use AI to optimize schedules by taking into account the couple's lifestyle and work schedules. This allows for schedule optimization that takes into account the couple's lifestyle and work schedules.

[0070] The schedule management unit can estimate the couple's emotions and determine schedule priorities based on those estimated emotions. For example, if the couple is stressed, the schedule management unit will prioritize relaxing tasks. If the couple is excited, the schedule management unit will prioritize important tasks. If the couple is tired, the schedule management unit will prioritize rest. The schedule management unit can estimate the couple's emotions using an emotion estimation function, such as an emotion engine or generative AI, and determine schedule priorities based on those estimated emotions. Generative AI may include, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. This allows for schedule priorities to be determined based on the couple's emotions.

[0071] The schedule management system can prioritize highly relevant schedules by considering the couple's geographical location. For example, if the couple is nearby, the system prioritizes tasks they can do together. If the couple is far apart, the system prioritizes tasks that can be done online. The system proposes an efficient schedule based on the couple's geographical location. The schedule management system uses AI to prioritize highly relevant schedules by considering the couple's geographical location. This allows the system to prioritize highly relevant schedules by considering the couple's geographical location.

[0072] The schedule management department can analyze a couple's social media activity and manage related schedules during the scheduling process. For example, the schedule management department analyzes a couple's social media activity and incorporates important events into the schedule. The schedule management department reflects plans with friends and family based on the couple's social media activity into the schedule. The schedule management department proposes an efficient schedule based on the couple's social media activity. The schedule management department can use AI to analyze a couple's social media activity and manage related schedules during the scheduling process. This allows for the analysis of a couple's social media activity and the management of related schedules.

[0073] The action suggestion unit can estimate the couple's emotions and adjust the way it expresses actions based on those emotions. For example, if the couple is relaxed, the action suggestion unit will suggest actions using calm language. If the couple is excited, the action suggestion unit will suggest actions using energetic language. If the couple is stressed, the action suggestion unit will suggest actions using simple and easy-to-understand language. The action suggestion unit can estimate the couple's emotions using an emotion estimation function, such as an emotion engine or generative AI, and adjust the way it expresses actions based on those emotions. Generative AI can be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. This allows the action to be expressed in a way that reflects the couple's emotions.

[0074] The action proposal unit can adjust the level of detail in its proposals based on the importance of each action. For example, it adds detailed explanations to important actions and concise explanations to less important actions. The action proposal unit adjusts the level of detail in its proposals according to the importance of each action. The action proposal unit can use AI to adjust the level of detail in its proposals based on the importance of each action. This allows it to adjust the level of detail in its proposals based on the importance of each action.

[0075] The action suggestion unit can apply different suggestion algorithms depending on the category of each action when suggesting actions. For example, for the action of visiting a wedding venue, the action suggestion unit applies an algorithm that suggests the optimal date for visiting. For the action of sending invitations, the action suggestion unit applies an algorithm that suggests the optimal timing for sending invitations. For the action of scheduling a rehearsal, the action suggestion unit applies an algorithm that suggests the optimal date for a rehearsal. The action suggestion unit can use AI to apply different suggestion algorithms depending on the category of each action when suggesting actions. This allows for the application of different suggestion algorithms depending on the category of each action.

[0076] The action suggestion unit can estimate the couple's emotions and determine the priority of actions based on those estimated emotions. For example, if the couple is stressed, the action suggestion unit will prioritize relaxing actions. If the couple is excited, the action suggestion unit will prioritize important actions. If the couple is tired, the action suggestion unit will suggest actions that prioritize rest. The action suggestion unit can estimate the couple's emotions using an emotion estimation function, such as an emotion engine or generative AI, and determine the priority of actions based on those estimated emotions. Generative AI can be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. This allows for the prioritization of actions based on the couple's emotions.

[0077] The action proposal department can determine the priority of proposals based on the implementation timing of each action when proposing actions. For example, the action proposal department will prioritize proposing actions that should be implemented urgently. The action proposal department will postpone actions that are far in the future. The action proposal department will determine the priority of proposals based on the implementation timing of each action. The action proposal department can use AI to determine the priority of proposals based on the implementation timing of each action when proposing actions. This allows the priority of proposals to be determined based on the implementation timing of each action.

[0078] The action proposal unit can adjust the order of proposed actions based on the relevance of each action when proposing actions. For example, the action proposal unit proposes highly relevant actions consecutively. The action proposal unit postpones actions with low relevance. The action proposal unit adjusts the order of proposed actions based on the relevance of each action. The action proposal unit can use AI to adjust the order of proposed actions based on the relevance of each action when proposing actions. This allows the order of proposed actions to be adjusted based on the relevance of each action.

[0079] The task optimization unit can estimate the couple's emotions and adjust the task optimization method based on the estimated emotions. For example, if the couple is relaxed, the task optimization unit will suggest tasks that proceed at a relaxed pace. If the couple is in a hurry, the task optimization unit will suggest tasks that can be completed quickly. If the couple is stressed, the task optimization unit will suggest simple and easy-to-understand tasks. The task optimization unit can estimate the couple's emotions using an emotion estimation function, such as an emotion engine or generative AI, and adjust the task optimization method based on the estimated emotions. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. This allows the task optimization method to be adjusted based on the couple's emotions.

[0080] The task optimization unit can analyze a couple's past task history to select the optimal optimization method during task optimization. For example, the task optimization unit proposes the optimal task based on the couple's past successful task patterns. The task optimization unit selects an efficient task optimization method from the couple's past task history. The task optimization unit analyzes the couple's past task history and proposes ways to reduce wasted time. The task optimization unit can use AI to analyze a couple's past task history to select the optimal optimization method during task optimization. This allows the system to analyze the couple's past task history and select the optimal optimization method.

[0081] The task optimization unit can customize the task optimization method based on the couple's current lifestyle during task optimization. For example, the task optimization unit proposes the most suitable tasks based on the couple's current lifestyle. The task optimization unit creates manageable tasks considering the couple's lifestyle. The task optimization unit integrates the couple's lifestyle and work schedule to propose well-balanced tasks. The task optimization unit can use AI to customize the task optimization method based on the couple's current lifestyle during task optimization. This allows the task optimization method to be customized based on the couple's current lifestyle.

[0082] The task optimization unit can estimate the couple's emotions and determine task priorities based on those estimated emotions. For example, if the couple is stressed, the task optimization unit will prioritize relaxing tasks. If the couple is excited, the task optimization unit will prioritize important tasks. If the couple is tired, the task optimization unit will suggest tasks that prioritize rest. The task optimization unit can estimate the couple's emotions using an emotion estimation function, such as an emotion engine or generative AI, and determine task priorities based on those estimated emotions. Generative AI can be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. This allows for task prioritization based on the couple's emotions.

[0083] The task optimization unit can select the optimal task optimization method by considering the couple's geographical location information during task optimization. For example, if the couple is nearby, the task optimization unit prioritizes tasks that can be done together. If the couple is far apart, the task optimization unit prioritizes tasks that can be done online. The task optimization unit proposes efficient tasks based on the couple's geographical location information. The task optimization unit can select the optimal task optimization method by considering the couple's geographical location information during task optimization using AI. This allows the system to select the optimal task optimization method by considering the couple's geographical location information.

[0084] The task optimization unit can analyze a couple's social media activity during task optimization and propose methods for optimizing the task. For example, the task optimization unit analyzes the couple's social media activity and incorporates important events into the task. The task optimization unit reflects the couple's plans with friends and family into the task based on their social media activity. The task optimization unit proposes efficient tasks based on the couple's social media activity. The task optimization unit can use AI to analyze a couple's social media activity during task optimization and propose methods for optimizing the task. This allows it to analyze a couple's social media activity and propose methods for optimizing the task.

[0085] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0086] The scheduling department can monitor the couple's health and adjust their schedule based on that health status. For example, if one partner is unwell, important tasks can be postponed, and rest time can be increased. It can also analyze the couple's health data and incorporate health-maintaining activities into their schedule. Furthermore, it can offer suggestions for diet and exercise based on their health status, providing support for a healthy lifestyle. This allows for schedule adjustments based on the couple's health, supporting a healthy wedding preparation.

[0087] The Action Proposal Department can suggest wedding preparation actions based on the couple's hobbies and interests. For example, if the couple enjoys the outdoors, they can suggest an outdoor wedding idea. If the couple enjoys cooking, they can suggest wedding preparation actions that incorporate cooking classes. Furthermore, if the couple loves music, they can suggest wedding arrangements that include music events or live performances. In this way, they can propose wedding preparation actions based on the couple's hobbies and interests, supporting them in creating a more unique and enjoyable wedding.

[0088] The task optimization unit supports couples in managing their budget and can propose the most suitable tasks based on that budget. For example, it can suggest the best venue and attire according to the couple's budget. It can also suggest cost-saving methods to maximize effectiveness within the budget. Furthermore, it can suggest decorations and staging that meet the couple's wishes within the budget. In this way, it can propose the most suitable tasks based on the couple's budget and support them in making economical wedding preparations.

[0089] The scheduling department can adjust the wedding preparation schedule, taking into account the schedules of the couple's family and friends. For example, they can prioritize dates when family and friends can attend when scheduling venue visits and rehearsals. They can also determine the timing of invitation mailings and event dates to match the schedules of family and friends. Furthermore, they can adjust the division of roles and the order of speeches on the wedding day, taking into account the schedules of family and friends. In this way, they can adjust the wedding preparation schedule, taking into account the schedules of the couple's family and friends, and support smooth wedding preparations.

[0090] The action suggestion function can estimate the couple's emotions and adjust the timing of actions based on those emotions. For example, if the couple is relaxed, it can suggest actions that can be done in a relaxed state. If the couple is stressed, it can prioritize suggesting actions that will reduce stress. Furthermore, if the couple is excited, it can suggest energetic actions. This allows the system to adjust the timing of actions based on the couple's emotions, supporting more effective wedding preparations.

[0091] The task optimization unit can estimate the couple's emotions and adjust the pace of tasks based on those emotions. For example, if the couple is relaxed, it can suggest tasks that proceed at a leisurely pace. If the couple is in a hurry, it can suggest tasks that can be completed quickly. Furthermore, if the couple is stressed, it can suggest simple and easy-to-understand tasks. This allows the system to adjust the pace of tasks based on the couple's emotions, supporting more effective wedding preparations.

[0092] The scheduling system can estimate a couple's emotions and prioritize their schedule based on those emotions. For example, if a couple is feeling stressed, relaxing tasks can be prioritized. If a couple is excited, important tasks can be prioritized. Furthermore, if a couple is tired, rest can be prioritized. This allows for scheduling prioritization based on the couple's emotions, supporting more effective wedding preparations.

[0093] The action suggestion unit can estimate the couple's emotions and adjust the way actions are expressed based on those emotions. For example, if the couple is relaxed, it can suggest actions using calm language. If the couple is excited, it can suggest actions using energetic language. Furthermore, if the couple is stressed, it can suggest actions using simple and easy-to-understand language. This allows the system to adjust the way actions are expressed based on the couple's emotions, supporting more effective wedding preparations.

[0094] The task optimization unit can estimate the couple's emotions and prioritize tasks based on those emotions. For example, if the couple is stressed, it can prioritize relaxing tasks. If the couple is excited, it can prioritize important tasks. Furthermore, if the couple is tired, it can suggest tasks that prioritize rest. This allows for task prioritization based on the couple's emotions, supporting more effective wedding preparations.

[0095] The scheduling department can estimate a couple's emotions and adjust their schedule based on those estimates. For example, if a couple is feeling stressed, relaxation time can be incorporated into their schedule. If a couple is excited, important tasks can be prioritized. Furthermore, if a couple is tired, more rest time can be allocated. This allows for schedule adjustments based on the couple's emotions, supporting more effective wedding preparations.

[0096] The following briefly describes the processing flow for example form 2.

[0097] Step 1: The schedule management unit manages the couple's schedule. For example, simply by entering the couple's wishes and plans, the unit optimizes the schedule, and if the couple enters their desired venue visit dates, it can suggest the best dates. The schedule management unit autonomously manages the couple's schedule and predicts and suggests the necessary actions at each step of wedding preparation. Step 2: The Action Proposal Department predicts and proposes necessary actions based on the schedule managed by the Schedule Management Department. For example, it proposes actions such as automating the timing of sending out invitations and scheduling rehearsals, so that couples can proceed with wedding preparations without hassle. Step 3: The Task Optimization Unit optimizes each task based on the actions proposed by the Action Proposal Unit. For example, it optimizes tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on the wedding's presentation. It also proposes the most suitable furniture and appliances based on the couple's wishes and supports the purchase process. Furthermore, it can automatically adjust the schedule for meetings with the venue and choosing attire.

[0098] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0099] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0100] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, 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.

[0101] Each of the multiple elements described above, including the schedule management unit, action proposal unit, and task optimization unit, is implemented in at least one of the smart device 14 and the data processing unit 12. For example, the schedule management unit is implemented by the control unit 46A of the smart device 14 and optimizes the schedule by inputting the couple's wishes and plans. The action proposal unit is implemented by the specific processing unit 290 of the data processing unit 12 and automates the timing of sending invitations and scheduling rehearsals. The task optimization unit is implemented by the control unit 46A of the smart device 14 and optimizes tasks such as wedding preparations and purchasing furniture and appliances. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be changed in various ways.

[0102] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0103] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0104] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0105] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0106] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0107] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0108] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0109] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0110] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0111] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0112] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. 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 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0113] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0114] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0115] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0116] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0117] Each of the multiple elements described above, including the schedule management unit, action proposal unit, and task optimization unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the schedule management unit is implemented by the control unit 46A of the smart glasses 214 and optimizes the schedule by inputting the couple's wishes and plans. The action proposal unit is implemented by the specific processing unit 290 of the data processing unit 12 and automates the timing of sending invitations and scheduling rehearsals. The task optimization unit is implemented by the control unit 46A of the smart glasses 214 and optimizes tasks such as wedding preparations and purchasing furniture and appliances. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be changed in various ways.

[0118] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0119] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0120] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0121] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0122] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0123] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0124] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0125] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0126] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0127] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0128] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0129] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0130] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0131] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0132] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0133] Each of the multiple elements described above, including the schedule management unit, action proposal unit, and task optimization unit, is implemented by at least one of the headset terminal 314 and the data processing unit 12. For example, the schedule management unit is implemented by the control unit 46A of the headset terminal 314 and optimizes the schedule by inputting the couple's wishes and plans. The action proposal unit is implemented by the specific processing unit 290 of the data processing unit 12 and automates the timing of sending invitations and scheduling rehearsals. The task optimization unit is implemented by the control unit 46A of the headset terminal 314 and optimizes tasks such as wedding preparations and purchasing furniture and appliances. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be changed in various ways.

[0134] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0135] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0136] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0137] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0138] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0139] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0140] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0141] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0142] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0143] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0144] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0145] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0146] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0147] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0148] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0149] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0150] Each of the multiple elements described above, including the schedule management unit, action proposal unit, and task optimization unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the schedule management unit is implemented by the control unit 46A of the robot 414 and optimizes the schedule by inputting the couple's wishes and plans. The action proposal unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and automates the timing of sending invitations and scheduling rehearsals. The task optimization unit is implemented by, for example, the control unit 46A of the robot 414 and optimizes tasks such as wedding preparations and the purchase of furniture and appliances. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be changed in various ways.

[0151] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0152] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0153] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0154] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0155] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0156] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0157] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0158] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0159] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0160] 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.

[0161] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0162] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0163] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0164] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0165] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0166] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0167] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0168] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0169] (Note 1) The schedule management department manages the couple's schedule, An action proposal unit predicts and proposes necessary actions based on the schedule managed by the aforementioned schedule management unit, The system includes a task optimization unit that optimizes each task based on the actions proposed by the action proposal unit. A system characterized by the following features. (Note 2) The aforementioned schedule management unit, Simply enter your preferences and plans to optimize your schedule. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned Action Proposal Unit, Automate the process of sending out invitations and scheduling rehearsals. The system described in Appendix 1, characterized by the features described herein. (Note 4) The task optimization unit, Optimize tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with the venue, choosing attire, and deciding on the wedding's entertainment. The system described in Appendix 1, characterized by the features described herein. (Note 5) The task optimization unit, We propose the most suitable furniture and home appliances based on the couple's preferences and support them through the purchase process. The system described in Appendix 1, characterized by the features described herein. (Note 6) The task optimization unit, The system automatically adjusts the schedule for meetings with the wedding venue and for choosing wedding attire. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned schedule management unit, It estimates the couple's emotions and adjusts the schedule based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned schedule management unit, Analyze the couple's past schedule history to select the optimal schedule management method. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned schedule management unit, When managing schedules, optimize them by taking into account the couple's daily routines and work schedules. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned schedule management unit, It estimates the couple's emotions and prioritizes schedules based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned schedule management unit, When managing schedules, prioritize highly relevant schedules by considering the couple's geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned schedule management unit, When managing schedules, analyze the couple's social media activity and manage relevant schedules. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned Action Proposal Unit, It estimates the couple's emotions and adjusts the way actions are expressed based on the estimated emotions of the couple. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned Action Proposal Unit, When proposing actions, adjust the level of detail in the proposal based on the importance of each action. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned Action Proposal Unit, When proposing actions, different proposal algorithms are applied depending on the category of each action. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned Action Proposal Unit, It estimates the couple's emotions and determines the priority of actions based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned Action Proposal Unit, When proposing actions, prioritize the proposals based on the timing of each action's implementation. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned Action Proposal Unit, When proposing actions, adjust the order of the suggestions based on the relevance of each action. The system described in Appendix 1, characterized by the features described herein. (Note 19) The task optimization unit, The system estimates the couple's emotions and adjusts the task optimization method based on the estimated couple's emotions. The system described in Appendix 1, characterized by the features described herein. (Note 20) The task optimization unit, When optimizing tasks, the couple's past task history is analyzed to select the optimal optimization method. The system described in Appendix 1, characterized by the features described herein. (Note 21) The task optimization unit, When optimizing tasks, customize the task optimization method based on the couple's current living situation. The system described in Appendix 1, characterized by the features described herein. (Note 22) The task optimization unit, The system estimates the couple's emotions and prioritizes tasks based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 23) The task optimization unit, When optimizing tasks, the optimal task optimization method is selected by considering the couple's geographical location information. The system described in Appendix 1, characterized by the features described herein. (Note 24) The task optimization unit, When optimizing tasks, we analyze the couple's social media activity and propose methods for optimizing the tasks. The system described in Appendix 1, characterized by the features described herein. [Explanation of Symbols]

[0170] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The schedule management department manages the couple's schedule, An action proposal unit predicts and proposes necessary actions based on the schedule managed by the aforementioned schedule management unit, The system includes a task optimization unit that optimizes each task based on the actions proposed by the action proposal unit. A system characterized by the following features.

2. The aforementioned schedule management unit, Simply enter your preferences and plans to optimize your schedule. The system according to feature 1.

3. The aforementioned Action Proposal Unit, Automate the process of sending out invitations and scheduling rehearsals. The system according to feature 1.

4. The task optimization unit, Optimize tasks such as wedding preparations, moving, purchasing furniture and appliances, meeting with venues, choosing attire, and deciding on the wedding's presentation. The system according to feature 1.

5. The task optimization unit, We propose the most suitable furniture and appliances based on the couple's preferences and support them through the purchase process. The system according to feature 1.

6. The task optimization unit, The system automatically adjusts the schedule for meetings with the wedding venue and for choosing wedding attire. The system according to feature 1.

7. The aforementioned schedule management unit, It estimates the couple's emotions and adjusts the schedule based on those estimated emotions. The system according to feature 1.

8. The aforementioned schedule management unit, Analyze the couple's past schedule history to select the optimal schedule management method. The system according to feature 1.

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