System

Abstract

An object of a system according to an embodiment is to reduce burdens in terms of money and labor in preparation for a wedding.SOLUTION: A system according to an embodiment includes a reception unit, a proposal unit, a reservation unit, a creation support unit, a coordination unit, and a production unit. The reception unit receives an input of the number of persons or a desired budget. The proposal unit proposes an appropriate venue on the basis of the information received by the reception unit. The reservation unit reserves the venue proposed by the proposal unit. The creation support unit supports creation of an invitation card, a seating chart, or a speech script. The coordination part coordinates the site design or orders necessary small articles. The production unit produces a movie.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, wedding preparations were a major financial and labor-intensive burden.

[0005] The system according to the embodiment aims to reduce the financial and labor burden involved in preparing for a wedding ceremony. [Means for solving the problem]

[0006] The system according to the embodiment comprises a reception unit, a proposal unit, a reservation unit, a creation support unit, a coordination unit, and a production unit. The reception unit accepts input of the number of people or desired budget. The proposal unit proposes an appropriate venue based on the information accepted by the reception unit. The reservation unit makes reservations for the venue proposed by the proposal unit. The creation support unit supports the creation of invitations, seating charts, and speech manuscripts. The coordination unit coordinates the venue design or orders necessary accessories. The production unit produces the movie. [Effects of the Invention]

[0007] The system according to the embodiment can reduce the financial and labor burden involved in preparing for a wedding ceremony. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) A wedding preparation support system according to an embodiment of the present invention uses generative AI and AI to support wedding preparations. The system accepts inputs of the number of guests and desired budget, proposes an optimal venue, and reserves the venue. It also assists in the creation of invitations, seating charts, and speech scripts, coordinates the venue design, and orders necessary accessories. It also produces videos. For example, in a wedding preparation support system, a couple inputs their desired budget and number of guests, and the generative AI searches for and proposes the optimal venue based on that information. Furthermore, the proposed venue can be automatically reserved. Next, the system uses generative AI to assist in the creation of invitations, seating charts, speech scripts, and other items. For example, when a couple inputs their desired design and content, the generative AI generates invitations, seating charts, and speech scripts based on that information. This allows couples to create high-quality items without hassle. Furthermore, the generative AI is used to coordinate the venue design and order necessary accessories. For example, when a couple inputs their desired theme and style, the generative AI coordinates the venue design based on that information and orders necessary accessories. This allows couples to realize their ideal venue without hassle. Finally, the generative AI is used to produce videos and other content. For example, if a couple inputs their desired content and theme, the AI ​​will generate a movie based on that. This allows couples to create high-quality movies without much effort. As a result, the wedding preparation support system reduces the burden of wedding preparations for dual-income couples and enables them to have a more enjoyable wedding. For example, the system can quickly and accurately create invitations, seating charts, and speech scripts written by the couple, reducing the burden on the couple. Couples can also easily create venue designs and movies that suit their wishes, allowing them to efficiently proceed with wedding preparations.

[0029] A wedding preparation support system according to an embodiment includes a reception unit, a proposal unit, a reservation unit, a creation support unit, a coordination unit, and a production unit. The reception unit accepts input of the number of guests or desired budget. For example, when a couple inputs their desired budget and number of guests, the reception unit can accept the information. The proposal unit proposes an appropriate venue based on the information accepted by the reception unit. For example, the proposal unit can search for and propose an optimal venue based on the couple's desired budget and number of guests. The reservation unit makes reservations for the venue proposed by the proposal unit. For example, the reservation unit can automatically make reservations for the proposed venue. The creation support unit assists in the creation of invitations, seating charts, and speech manuscripts. For example, when a couple inputs their desired design and content, the creation support unit can generate invitations, seating charts, and speech manuscripts based on the input. The coordination unit coordinates the venue design or orders necessary accessories. For example, when a couple inputs their desired theme and style, the coordination unit can coordinate the venue design and order necessary accessories based on the input. The production unit produces videos. For example, when a couple inputs desired content or theme, the production department can generate a movie based on that. As a result, the wedding preparation support system according to the embodiment can efficiently support each stage of wedding preparation and reduce the burden on the couple.

[0030] The proposal unit can propose an appropriate venue based on the couple's desired budget or number of people. The proposal unit, for example, searches for and proposes the optimal venue based on the couple's desired budget and number of people. For example, the proposal unit can select the optimal venue based on the budget and number of people entered by the couple, taking into consideration the capacity, facilities, location, and other conditions. The proposal unit can also propose multiple venues according to the couple's wishes. For example, the proposal unit searches for multiple venues within the couple's desired budget, compares the features of each venue, and makes a proposal. This makes it possible to efficiently prepare for a wedding by proposing the optimal venue according to the couple's wishes.

[0031] The reservation unit can make a reservation for the proposed venue. The reservation unit, for example, automatically makes a reservation for the proposed venue. For example, the reservation unit can check the availability of the venue proposed by the proposal unit and make a reservation. The reservation unit can also make the optimal reservation based on the couple's desired date and time. For example, the reservation unit compares the availability of multiple venues based on the couple's desired date and time and reserves the optimal venue. This can reduce the couple's effort by automating the reservation of the proposed venue.

[0032] The creation support unit can generate invitations, seating charts, and speech manuscripts based on the couple's desired design or content. For example, when the couple inputs their desired design and content, the creation support unit generates invitations, seating charts, and speech manuscripts based on the input. For example, the creation support unit can automatically generate invitations, seating charts, and speech manuscripts by selecting a design template desired by the couple and inputting the required information items. The creation support unit can also provide multiple design templates according to the couple's wishes. For example, the creation support unit can propose multiple design templates based on the couple's desired theme and style and generate items based on each template. This reduces the effort required by automatically generating high-quality items according to the couple's wishes.

[0033] The coordinating unit can coordinate the venue design based on the couple's desired theme or style and order the necessary accessories. For example, when the couple inputs their desired theme or style, the coordinating unit coordinates the venue design based on that and orders the necessary accessories. For example, the coordinating unit can select the couple's desired theme color and decorative items and coordinate the venue design based on those. The coordinating unit can also provide multiple design options according to the couple's wishes. For example, the coordinating unit can propose multiple design options based on the couple's desired theme and order accessories based on each option. This reduces the effort required by automating the venue design and ordering accessories according to the couple's wishes.

[0034] The production department can generate a movie based on the content and theme desired by the couple. For example, when the couple inputs the content and theme desired by the couple, the production department generates a movie based on that. For example, the production department can automatically generate a movie by inputting the length and content structure desired by the couple. The production department can also provide multiple video templates according to the couple's wishes. For example, the production department can propose multiple video templates based on the theme desired by the couple and generate a movie based on each template. This reduces the effort required by automatically generating a high-quality movie according to the couple's wishes.

[0035] The reception unit can analyze the couple's past wedding preparation history and suggest the optimal input method. For example, the reception unit prioritizes suggesting input methods (voice, text, etc.) that the couple has used in the past. The reception unit can also automatically display information that the couple has frequently input in the past as candidates. Furthermore, the reception unit can predict and suggest the input method that will be used during a specific time period based on the couple's past input history. This makes it possible to streamline input work by suggesting the optimal input method based on past history.

[0036] The reception unit can customize the input items based on the couple's current living situation and areas of interest when inputting information. For example, if a couple is busy because both partners work, the reception unit can provide simplified input items. Furthermore, if a couple is interested in a particular topic, the reception unit can preferentially display input items related to that topic. Furthermore, the reception unit can customize the order and content of the input items according to the couple's living situation. This can make input work more efficient by providing input items according to the couple's living situation and areas of interest.

[0037] The reception unit can select the optimal input means depending on the input method of the couple when inputting. For example, if the couple prefers voice input, the reception unit can provide voice input preferentially. Furthermore, if the couple prefers text input, the reception unit can provide text input preferentially. Furthermore, if the couple prefers image input, the reception unit can provide image input preferentially. This makes it possible to streamline input work by providing the optimal means depending on the couple's input method.

[0038] The reception unit can prioritize inputting highly relevant information by taking into consideration the geographical location information of the couple when inputting information. For example, if the couple lives in a specific area, the reception unit can prioritize inputting information related to that area. Also, if the couple plans to hold a wedding ceremony in a specific area, the reception unit can prioritize inputting information related to that area. Furthermore, the reception unit can suggest optimal input items based on the geographical location information of the couple. This can make input work more efficient by providing highly relevant information based on the geographical location information.

[0039] The reception unit can analyze the couple's social media activity at the time of input and input relevant information. The reception unit can suggest relevant input items based on, for example, information shared by the couple on social media. The reception unit can also analyze the couple's social media activity and automatically input relevant information. Furthermore, the reception unit can input relevant information by referring to the activity of the couple's friends on social media. This makes it possible to streamline input work by providing relevant information based on social media activity.

[0040] The reception unit can customize the input method by reflecting the couple's past feedback when inputting information. The reception unit can, for example, suggest the optimal input method based on feedback provided by the couple in the past. The reception unit can also improve the input interface by reflecting the couple's past feedback. Furthermore, the reception unit can customize the order and content of input items based on the couple's past feedback. This can make input work more efficient by providing the optimal input method based on past feedback.

[0041] The suggestion unit can adjust the level of detail of the proposal based on the importance of the venue when making the proposal. For example, in the case of an important venue, the suggestion unit can provide a proposal including detailed information. In addition, in the case of a venue that is not so important, the suggestion unit can provide a simplified proposal. Furthermore, the suggestion unit can adjust the level of detail of the proposal depending on the importance of the venue. In this way, by providing the level of detail of the proposal according to the importance of the venue, it is possible to improve the likelihood of the proposal being accepted.

[0042] The suggestion unit can apply different suggestion algorithms depending on the category of the venue when making a suggestion. For example, in the case of a hotel venue, the suggestion unit can provide a suggestion that emphasizes the features of the hotel. In addition, in the case of a garden venue, the suggestion unit can provide a suggestion that emphasizes the features of the garden. In addition, in the case of a restaurant venue, the suggestion unit can provide a suggestion that emphasizes the features of the restaurant. This makes it possible to provide optimal suggestions according to the category of the venue, thereby increasing the likelihood of the suggestions being accepted.

[0043] The proposal unit can improve the accuracy of the proposal by referring to the couple's past proposal results when making a proposal. For example, the proposal unit proposes the most suitable venue based on the features of venues selected by the couple in the past. The proposal unit can also analyze the couple's past proposal results and improve the accuracy of the proposal. Furthermore, the proposal unit can customize the content of the proposal by referring to the couple's past proposal results. This makes it possible to improve the accuracy of the proposal by providing the most suitable proposal based on the past proposal results.

[0044] The proposal unit can determine the priority of proposals based on the reservation status of the venues at the time of proposal. For example, the proposal unit can prioritize proposals based on venues that are easily booked. The proposal unit can also postpone proposals based on venues that are easily booked. Furthermore, the proposal unit can adjust the priority of proposals based on the reservation status of the venues. This can improve the likelihood of proposals being accepted by providing a priority of proposals based on the reservation status of the venues.

[0045] The suggestion unit may adjust the order of suggestions based on the relevance of the venues when making suggestions. For example, the suggestion unit may prioritize suggesting venues that are most relevant to the couple's wishes. Also, the suggestion unit may postpone suggesting venues that are less relevant to the couple's wishes. Furthermore, the suggestion unit may adjust the order of suggestions based on the relevance of the venues. This may increase the likelihood of suggestions being accepted by providing an order of suggestions based on the relevance of the venues.

[0046] The suggestion unit can adjust the use of technical terms in the suggestion depending on the expertise level of the couple when making the suggestion. For example, if the couple has specialized knowledge, the suggestion unit can provide a suggestion that uses a lot of technical terms. Also, if the couple does not have specialized knowledge, the suggestion unit can provide a suggestion that is explained in simple language. Furthermore, the suggestion unit can adjust the content of the suggestion depending on the expertise level of the couple. This can increase the likelihood of the suggestion being accepted by providing a suggestion that is appropriate for the expertise level of the couple.

[0047] The reservation unit can analyze the couple's past reservation history at the time of reservation and select the optimal reservation method. For example, the reservation unit can suggest the optimal reservation method based on the reservation methods used by the couple in the past. The reservation unit can also analyze the couple's past reservation history and suggest the most efficient reservation method. Furthermore, the reservation unit can customize the reservation method by referring to the couple's past reservation history. This makes it possible to streamline the reservation process by providing the optimal reservation method based on the past reservation history.

[0048] The reservation unit can customize the reservation method based on the couple's current living situation at the time of reservation. For example, if a couple is busy because both partners work, the reservation unit can provide a simplified reservation method. Also, if a couple is interested in a particular theme, the reservation unit can provide reservation methods related to that theme preferentially. Furthermore, the reservation unit can customize the order and content of the reservation methods according to the couple's living situation. This can streamline the reservation process by providing reservation methods that suit the couple's living situation.

[0049] The reservation unit can improve the reservation method by reflecting the couple's feedback at the time of reservation. For example, the reservation unit can suggest the optimal reservation method based on feedback provided by the couple in the past. The reservation unit can also improve the reservation interface by reflecting the couple's past feedback. Furthermore, the reservation unit can customize the order and content of the reservation methods based on the couple's past feedback. This can make the reservation process more efficient by providing the optimal reservation method based on past feedback.

[0050] The reservation unit can select the optimal reservation method by taking into consideration the geographical location information of the couple when making a reservation. For example, if the couple lives in a specific area, the reservation unit can preferentially provide reservation methods related to that area. Also, if the couple plans to hold a wedding in a specific area, the reservation unit can preferentially provide reservation methods related to that area. Furthermore, the reservation unit can suggest the optimal reservation method based on the geographical location information of the couple. This makes it possible to streamline the reservation process by providing the optimal reservation method based on the geographical location information.

[0051] The reservation unit can analyze the couple's social media activity at the time of reservation to suggest a reservation method. For example, the reservation unit can suggest a relevant reservation method based on information shared by the couple on social media. The reservation unit can also analyze the couple's social media activity and automatically suggest a relevant reservation method. Furthermore, the reservation unit can suggest a relevant reservation method based on the activity of the couple's friends on social media. This makes it possible to streamline the reservation process by providing the optimal reservation method based on social media activity.

[0052] The reservation unit can customize the reservation method by reflecting the couple's past feedback when making a reservation. For example, the reservation unit can suggest the optimal reservation method based on the couple's past feedback. The reservation unit can also improve the reservation interface by reflecting the couple's past feedback. Furthermore, the reservation unit can customize the order and content of the reservation methods based on the couple's past feedback. This can make the reservation process more efficient by providing the optimal reservation method based on the couple's past feedback.

[0053] The creation support unit can analyze the couple's past creation history and select the optimal creation method when providing creation support. For example, the creation support unit can suggest the optimal creation method based on the creation methods used by the couple in the past. The creation support unit can also analyze the couple's past creation history and suggest the most efficient creation method. Furthermore, the creation support unit can customize the creation method by referring to the couple's past creation history. This makes it possible to streamline the creation process by providing the optimal creation method based on the past creation history.

[0054] The creation support unit can customize the creation support means based on the couple's current living situation when providing creation support. For example, if a couple is busy because both partners work, the creation support unit can provide simplified creation support means. Also, if a couple is interested in a specific theme, the creation support unit can provide creation support means related to that theme preferentially. Furthermore, the creation support unit can customize the order and content of the creation support means according to the couple's living situation. This makes it possible to streamline the creation work by providing creation support means that suit the couple's living situation.

[0055] The creation support unit can improve the creation support method by reflecting the couple's feedback during creation support. For example, the creation support unit can propose an optimal creation support method based on feedback previously provided by the couple. The creation support unit can also improve the creation support interface by reflecting the couple's past feedback. Furthermore, the creation support unit can customize the order and content of the creation support means based on the couple's past feedback. This can make the creation work more efficient by providing an optimal creation support method based on past feedback.

[0056] The creation support unit can select the optimal creation support method by taking into consideration the geographical location information of the couple when providing creation support. For example, if the couple lives in a specific area, the creation support unit can preferentially provide creation support methods related to that area. Also, if the couple plans to hold their wedding in a specific area, the creation support unit can preferentially provide creation support methods related to that area. Furthermore, the creation support unit can suggest the optimal creation support method based on the geographical location information of the couple. This makes it possible to streamline the creation work by providing the optimal creation support method based on the geographical location information.

[0057] The creation support unit can analyze the couple's social media activity and suggest creation support means when providing creation support. For example, the creation support unit can suggest relevant creation support means based on information shared by the couple on social media. The creation support unit can also analyze the couple's social media activity and automatically suggest relevant creation support means. Furthermore, the creation support unit can suggest relevant creation support means by referring to the activity of the couple's friends on social media. This makes it possible to streamline the creation process by providing optimal creation support means based on social media activity.

[0058] The creation support unit can customize the creation support method by reflecting the couple's past feedback when providing creation support. For example, the creation support unit can suggest the optimal creation support method based on feedback provided by the couple in the past. The creation support unit can also improve the creation support interface by reflecting the couple's past feedback. Furthermore, the creation support unit can customize the order and content of the creation support means based on the couple's past feedback. This can make the creation work more efficient by providing the optimal creation support method based on past feedback.

[0059] The coordination unit can analyze the past coordination history of the couple when coordinating and select the optimal coordination method. For example, the coordination unit can suggest the optimal coordination method based on the coordination methods used by the couple in the past. The coordination unit can also analyze the past coordination history of the couple and suggest the most efficient coordination method. Furthermore, the coordination unit can customize the coordination method by referring to the past coordination history of the couple. This makes it possible to improve the efficiency of the coordination work by providing the optimal coordination method based on the past coordination history.

[0060] The coordination unit can customize coordination methods based on the couple's current living situation when coordinating. For example, if a couple is busy because both partners work, the coordination unit can provide simplified coordination methods. Also, if a couple is interested in a particular theme, the coordination unit can provide coordination methods related to that theme preferentially. Furthermore, the coordination unit can customize the order and content of coordination methods according to the couple's living situation. This can make the coordination process more efficient by providing coordination methods that suit the couple's living situation.

[0061] The coordination unit can improve the coordination method by reflecting the couple's feedback during coordination. For example, the coordination unit can suggest an optimal coordination method based on feedback provided by the couple in the past. The coordination unit can also improve the coordination interface by reflecting the couple's past feedback. Furthermore, the coordination unit can customize the order and content of coordination methods based on the couple's past feedback. This can make the coordination work more efficient by providing an optimal coordination method based on past feedback.

[0062] The coordination unit can select the optimal coordination method by taking into consideration the geographical location information of the couple when coordinating. For example, if the couple lives in a specific area, the coordination unit can preferentially provide coordination methods related to that area. Also, if the couple plans to hold a wedding in a specific area, the coordination unit can preferentially provide coordination methods related to that area. Furthermore, the coordination unit can suggest the optimal coordination method based on the geographical location information of the couple. This makes it possible to streamline coordination work by providing the optimal coordination method based on the geographical location information.

[0063] The coordination unit can analyze the couple's social media activity when coordinating outfits and suggest coordination methods. The coordination unit can suggest related coordination methods, for example, based on information shared by the couple on social media. The coordination unit can also analyze the couple's social media activity and automatically suggest related coordination methods. Furthermore, the coordination unit can suggest related coordination methods by referring to the activity of the couple's friends on social media. This makes it possible to streamline coordination work by providing optimal coordination methods based on social media activity.

[0064] The coordination unit can customize the coordination method by reflecting the couple's past feedback when coordinating. For example, the coordination unit can suggest an optimal coordination method based on feedback provided by the couple in the past. The coordination unit can also improve the coordination interface by reflecting the couple's past feedback. Furthermore, the coordination unit can customize the order and content of coordination methods based on the couple's past feedback. This can make the coordination work more efficient by providing an optimal coordination method based on past feedback.

[0065] The production department can analyze the couple's past production history during production to select the optimal production method. For example, the production department can propose the optimal production method based on the production methods the couple has used in the past. The production department can also analyze the couple's past production history to propose the most efficient production method. Furthermore, the production department can customize the production method by referring to the couple's past production history. This makes it possible to streamline production work by providing the optimal production method based on the couple's past production history.

[0066] The production department can customize the production methods based on the couple's current living situation during production. For example, if a couple is busy because both partners work, the production department can provide simplified production methods. Also, if a couple is interested in a particular theme, the production department can prioritize providing production methods related to that theme. Furthermore, the production department can customize the order and content of the production methods according to the couple's living situation. This allows the production work to be made more efficient by providing production methods that suit the couple's living situation.

[0067] The production department can improve the production method by reflecting the couple's feedback during production. For example, the production department can suggest the optimal production method based on feedback provided by the couple in the past. The production department can also improve the production interface by reflecting the couple's past feedback. Furthermore, the production department can customize the order and content of the production methods based on the couple's past feedback. This makes it possible to streamline the production work by providing the optimal production method based on past feedback.

[0068] The production department can select the optimal production method by taking into consideration the geographical location information of the couple during production. For example, if the couple lives in a specific area, the production department can prioritize providing production methods related to that area. Also, if the couple plans to hold their wedding in a specific area, the production department can prioritize providing production methods related to that area. Furthermore, the production department can suggest the optimal production method based on the geographical location information of the couple. This allows for the efficiency of production work by providing the optimal production method based on the geographical location information.

[0069] The production department can analyze the couple's social media activity during production to suggest production methods. For example, the production department can suggest relevant production methods based on information shared by the couple on social media. The production department can also analyze the couple's social media activity and automatically suggest relevant production methods. Furthermore, the production department can suggest relevant production methods based on the activity of the couple's friends on social media. This makes it possible to streamline production work by providing optimal production methods based on social media activity.

[0070] The production department can customize the production method by reflecting the couple's past feedback during production. For example, the production department can suggest the optimal production method based on the couple's past feedback. The production department can also improve the production interface by reflecting the couple's past feedback. Furthermore, the production department can customize the order and content of the production methods based on the couple's past feedback. This makes it possible to streamline the production work by providing the optimal production method based on the past feedback.

[0071] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0072] The suggestion unit can adjust the level of detail of the proposal based on the importance of the venue when making the proposal. For example, for an important venue, a proposal including detailed information can be provided. For a less important venue, a simplified proposal can be provided. Furthermore, the level of detail of the proposal can be adjusted according to the importance of the venue. This can improve the likelihood of the proposal being accepted by providing a level of detail of the proposal according to the importance of the venue.

[0073] The suggestion unit can apply different suggestion algorithms depending on the category of the venue when making a suggestion. For example, in the case of a hotel venue, a suggestion that emphasizes the hotel's features can be provided. In addition, in the case of a garden venue, a suggestion that emphasizes the garden's features can be provided. Furthermore, in the case of a restaurant venue, a suggestion that emphasizes the restaurant's features can be provided. This makes it possible to provide optimal suggestions according to the venue category, thereby increasing the likelihood of the suggestions being accepted.

[0074] The suggestion unit can improve the accuracy of the suggestion by referring to the couple's past suggestion results when making a suggestion. For example, the suggestion unit can suggest the most suitable venue based on the features of venues selected by the couple in the past. The suggestion unit can also improve the accuracy of the suggestion by analyzing the couple's past suggestion results. Furthermore, the suggestion unit can customize the content of the suggestion by referring to the couple's past suggestion results. This allows the suggestion unit to improve the accuracy of the suggestion by providing the most suitable suggestion based on the past suggestion results.

[0075] The reservation unit can analyze the couple's past reservation history when making a reservation and select the optimal reservation method. For example, it can suggest the optimal reservation method based on the reservation methods the couple has used in the past. It can also analyze the couple's past reservation history and suggest the most efficient reservation method. Furthermore, it can customize the reservation method by referring to the couple's past reservation history. This makes it possible to streamline the reservation process by providing the optimal reservation method based on the past reservation history.

[0076] The reservation unit can customize the reservation method based on the couple's current living situation when making a reservation. For example, if a couple is busy because both partners work, a simplified reservation method can be provided. Also, if a couple is interested in a specific theme, reservation methods related to that theme can be provided preferentially. Furthermore, the order and content of the reservation methods can be customized according to the couple's living situation. This makes it possible to streamline the reservation process by providing reservation methods that suit the couple's living situation.

[0077] The creation support unit can analyze the couple's past creation history when providing creation support and select the optimal creation method. For example, it can suggest the optimal creation method based on the creation methods the couple has used in the past. It can also analyze the couple's past creation history and suggest the most efficient creation method. Furthermore, it can customize the creation method by referring to the couple's past creation history. This makes it possible to streamline the creation process by providing the optimal creation method based on the past creation history.

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

[0079] Step 1: The reception unit accepts input of the number of people or desired budget. For example, when a couple enters their desired budget and number of people, the reception unit can accept that information. Step 2: The proposal unit proposes an appropriate venue based on the information received by the reception unit. For example, the proposal unit can search for and propose the optimal venue based on the couple's desired budget and number of guests. Step 3: The reservation unit makes a reservation for the venue proposed by the proposal unit. For example, the reservation unit can automatically make a reservation for the proposed venue. Step 4: The creation support unit supports the creation of invitations, seating charts, and speech manuscripts. For example, when the couple inputs their desired design and content, the creation support unit can generate invitations, seating charts, and speech manuscripts based on that. Step 5: The coordination department coordinates the venue design and orders the necessary accessories. For example, if the couple inputs the theme and style they want, the coordination department can coordinate the venue design based on that and order the necessary accessories. Step 6: The production team creates the movie. For example, the production team can generate a movie based on the couple's desired content or theme.

[0080] (Example 2) A wedding preparation support system according to an embodiment of the present invention uses generative AI and AI to support wedding preparations. The system accepts inputs of the number of guests and desired budget, proposes an optimal venue, and reserves the venue. It also assists in the creation of invitations, seating charts, and speech scripts, coordinates the venue design, and orders necessary accessories. It also produces videos. For example, in a wedding preparation support system, a couple inputs their desired budget and number of guests, and the generative AI searches for and proposes the optimal venue based on that information. Furthermore, the proposed venue can be automatically reserved. Next, the system uses generative AI to assist in the creation of invitations, seating charts, speech scripts, and other items. For example, when a couple inputs their desired design and content, the generative AI generates invitations, seating charts, and speech scripts based on that information. This allows couples to create high-quality items without hassle. Furthermore, the generative AI is used to coordinate the venue design and order necessary accessories. For example, when a couple inputs their desired theme and style, the generative AI coordinates the venue design based on that information and orders necessary accessories. This allows couples to realize their ideal venue without hassle. Finally, the generative AI is used to produce videos and other content. For example, if a couple inputs their desired content and theme, the AI ​​will generate a movie based on that. This allows couples to create high-quality movies without much effort. As a result, the wedding preparation support system reduces the burden of wedding preparations for dual-income couples and enables them to have a more enjoyable wedding. For example, the system can quickly and accurately create invitations, seating charts, and speech scripts written by the couple, reducing the burden on the couple. Couples can also easily create venue designs and movies that suit their wishes, allowing them to efficiently proceed with wedding preparations.

[0081] A wedding preparation support system according to an embodiment includes a reception unit, a proposal unit, a reservation unit, a creation support unit, a coordination unit, and a production unit. The reception unit accepts input of the number of guests or desired budget. For example, when a couple inputs their desired budget and number of guests, the reception unit can accept the information. The proposal unit proposes an appropriate venue based on the information accepted by the reception unit. For example, the proposal unit can search for and propose an optimal venue based on the couple's desired budget and number of guests. The reservation unit makes reservations for the venue proposed by the proposal unit. For example, the reservation unit can automatically make reservations for the proposed venue. The creation support unit assists in the creation of invitations, seating charts, and speech manuscripts. For example, when a couple inputs their desired design and content, the creation support unit can generate invitations, seating charts, and speech manuscripts based on the input. The coordination unit coordinates the venue design or orders necessary accessories. For example, when a couple inputs their desired theme and style, the coordination unit can coordinate the venue design and order necessary accessories based on the input. The production unit produces videos. For example, when a couple inputs desired content or theme, the production department can generate a movie based on that. As a result, the wedding preparation support system according to the embodiment can efficiently support each stage of wedding preparation and reduce the burden on the couple.

[0082] The proposal unit can propose an appropriate venue based on the couple's desired budget or number of people. The proposal unit, for example, searches for and proposes the optimal venue based on the couple's desired budget and number of people. For example, the proposal unit can select the optimal venue based on the budget and number of people entered by the couple, taking into consideration the capacity, facilities, location, and other conditions. The proposal unit can also propose multiple venues according to the couple's wishes. For example, the proposal unit searches for multiple venues within the couple's desired budget, compares the features of each venue, and makes a proposal. This makes it possible to efficiently prepare for a wedding by proposing the optimal venue according to the couple's wishes.

[0083] The reservation unit can make a reservation for the proposed venue. The reservation unit, for example, automatically makes a reservation for the proposed venue. For example, the reservation unit can check the availability of the venue proposed by the proposal unit and make a reservation. The reservation unit can also make the optimal reservation based on the couple's desired date and time. For example, the reservation unit compares the availability of multiple venues based on the couple's desired date and time and reserves the optimal venue. This can reduce the couple's effort by automating the reservation of the proposed venue.

[0084] The creation support unit can generate invitations, seating charts, and speech manuscripts based on the couple's desired design or content. For example, when the couple inputs their desired design and content, the creation support unit generates invitations, seating charts, and speech manuscripts based on the input. For example, the creation support unit can automatically generate invitations, seating charts, and speech manuscripts by selecting a design template desired by the couple and inputting the required information items. The creation support unit can also provide multiple design templates according to the couple's wishes. For example, the creation support unit can propose multiple design templates based on the couple's desired theme and style and generate items based on each template. This reduces the effort required by automatically generating high-quality items according to the couple's wishes.

[0085] The coordinating unit can coordinate the venue design based on the couple's desired theme or style and order the necessary accessories. For example, when the couple inputs their desired theme or style, the coordinating unit coordinates the venue design based on that and orders the necessary accessories. For example, the coordinating unit can select the couple's desired theme color and decorative items and coordinate the venue design based on those. The coordinating unit can also provide multiple design options according to the couple's wishes. For example, the coordinating unit can propose multiple design options based on the couple's desired theme and order accessories based on each option. This reduces the effort required by automating the venue design and ordering accessories according to the couple's wishes.

[0086] The production department can generate a movie based on the content and theme desired by the couple. For example, when the couple inputs the content and theme desired by the couple, the production department generates a movie based on that. For example, the production department can automatically generate a movie by inputting the length and content structure desired by the couple. The production department can also provide multiple video templates according to the couple's wishes. For example, the production department can propose multiple video templates based on the theme desired by the couple and generate a movie based on each template. This reduces the effort required by automatically generating a high-quality movie according to the couple's wishes.

[0087] The reception unit can estimate the couple's emotions and adjust the design of the input interface based on the estimated emotions. For example, if the couple is nervous, the reception unit can provide an interface with subdued colors to reduce visual stress. Furthermore, if the couple is having fun, the reception unit can provide an interface with bright colors to make input work more enjoyable. Furthermore, if the couple is tired, the reception unit can provide a simple, highly visible interface to make input work easier. This can reduce the stress of input work by providing an interface that corresponds to the couple's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI.

[0088] The reception unit can analyze the couple's past wedding preparation history and suggest the optimal input method. For example, the reception unit prioritizes suggesting input methods (voice, text, etc.) that the couple has used in the past. The reception unit can also automatically display information that the couple has frequently input in the past as candidates. Furthermore, the reception unit can predict and suggest the input method that will be used during a specific time period based on the couple's past input history. This makes it possible to streamline input work by suggesting the optimal input method based on past history.

[0089] The reception unit can customize the input items based on the couple's current living situation and areas of interest when inputting information. For example, if a couple is busy because both partners work, the reception unit can provide simplified input items. Furthermore, if a couple is interested in a particular topic, the reception unit can preferentially display input items related to that topic. Furthermore, the reception unit can customize the order and content of the input items according to the couple's living situation. This can make input work more efficient by providing input items according to the couple's living situation and areas of interest.

[0090] The reception unit can select the optimal input means depending on the input method of the couple when inputting. For example, if the couple prefers voice input, the reception unit can provide voice input preferentially. Furthermore, if the couple prefers text input, the reception unit can provide text input preferentially. Furthermore, if the couple prefers image input, the reception unit can provide image input preferentially. This makes it possible to streamline input work by providing the optimal means depending on the couple's input method.

[0091] The reception unit can estimate the couple's emotions and prioritize input content based on the estimated emotions of the couple. For example, if the couple is nervous, the reception unit can prioritize displaying important input items and postpone other items. Furthermore, if the couple is relaxed, the reception unit can prioritize displaying detailed input items. Furthermore, if the couple is in a hurry, the reception unit can prioritize displaying the most important input items, allowing the couple to complete input quickly. This allows input work to be made more efficient by prioritizing input content according to the couple's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI.

[0092] The reception unit can prioritize inputting highly relevant information by taking into consideration the geographical location information of the couple when inputting information. For example, if the couple lives in a specific area, the reception unit can prioritize inputting information related to that area. Also, if the couple plans to hold a wedding ceremony in a specific area, the reception unit can prioritize inputting information related to that area. Furthermore, the reception unit can suggest optimal input items based on the geographical location information of the couple. This can make input work more efficient by providing highly relevant information based on the geographical location information.

[0093] The reception unit can analyze the couple's social media activity at the time of input and input relevant information. The reception unit can suggest relevant input items based on, for example, information shared by the couple on social media. The reception unit can also analyze the couple's social media activity and automatically input relevant information. Furthermore, the reception unit can input relevant information by referring to the activity of the couple's friends on social media. This makes it possible to streamline input work by providing relevant information based on social media activity.

[0094] The reception unit can customize the input method by reflecting the couple's past feedback when inputting information. The reception unit can, for example, suggest the optimal input method based on feedback provided by the couple in the past. The reception unit can also improve the input interface by reflecting the couple's past feedback. Furthermore, the reception unit can customize the order and content of input items based on the couple's past feedback. This can make input work more efficient by providing the optimal input method based on past feedback.

[0095] The suggestion unit can estimate the couple's emotions and adjust the way the suggestion is expressed based on the estimated emotions of the couple. For example, if the couple is nervous, the suggestion unit can provide a simple, highly visible suggestion. Furthermore, if the couple is relaxed, the suggestion unit can provide a suggestion that includes detailed information. Furthermore, if the couple is in a hurry, the suggestion unit can provide a suggestion that focuses on the main points. This can improve the likelihood of the suggestion being accepted by providing a way to express the suggestion according to the couple's emotions. The emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to these examples.

[0096] The suggestion unit can adjust the level of detail of the proposal based on the importance of the venue when making the proposal. For example, in the case of an important venue, the suggestion unit can provide a proposal including detailed information. In addition, in the case of a venue that is not so important, the suggestion unit can provide a simplified proposal. Furthermore, the suggestion unit can adjust the level of detail of the proposal depending on the importance of the venue. In this way, by providing the level of detail of the proposal according to the importance of the venue, it is possible to improve the likelihood of the proposal being accepted.

[0097] The suggestion unit can apply different suggestion algorithms depending on the category of the venue when making a suggestion. For example, in the case of a hotel venue, the suggestion unit can provide a suggestion that emphasizes the features of the hotel. In addition, in the case of a garden venue, the suggestion unit can provide a suggestion that emphasizes the features of the garden. In addition, in the case of a restaurant venue, the suggestion unit can provide a suggestion that emphasizes the features of the restaurant. This makes it possible to provide optimal suggestions according to the category of the venue, thereby increasing the likelihood of the suggestions being accepted.

[0098] The proposal unit can improve the accuracy of the proposal by referring to the couple's past proposal results when making a proposal. For example, the proposal unit proposes the most suitable venue based on the features of venues selected by the couple in the past. The proposal unit can also analyze the couple's past proposal results and improve the accuracy of the proposal. Furthermore, the proposal unit can customize the content of the proposal by referring to the couple's past proposal results. This makes it possible to improve the accuracy of the proposal by providing the most suitable proposal based on the past proposal results.

[0099] The suggestion unit can estimate the couple's emotions and adjust the length of the suggestion based on the estimated couple's emotions. For example, if the couple is nervous, the suggestion unit can provide a short and to-the-point suggestion. Also, if the couple is relaxed, the suggestion unit can provide a longer suggestion with detailed explanations. Furthermore, if the couple is in a hurry, the suggestion unit can provide a quick and concise suggestion. This can improve the likelihood of the suggestion being accepted by providing a suggestion length that corresponds to the couple's emotions. The emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples.

[0100] The proposal unit can determine the priority of proposals based on the reservation status of the venues at the time of proposal. For example, the proposal unit can prioritize proposals based on venues that are easily booked. The proposal unit can also postpone proposals based on venues that are easily booked. Furthermore, the proposal unit can adjust the priority of proposals based on the reservation status of the venues. This can improve the likelihood of proposals being accepted by providing a priority of proposals based on the reservation status of the venues.

[0101] The suggestion unit may adjust the order of suggestions based on the relevance of the venues when making suggestions. For example, the suggestion unit may prioritize suggesting venues that are most relevant to the couple's wishes. Also, the suggestion unit may postpone suggesting venues that are less relevant to the couple's wishes. Furthermore, the suggestion unit may adjust the order of suggestions based on the relevance of the venues. This may increase the likelihood of suggestions being accepted by providing an order of suggestions based on the relevance of the venues.

[0102] The suggestion unit can adjust the use of technical terms in the suggestion depending on the expertise level of the couple when making the suggestion. For example, if the couple has specialized knowledge, the suggestion unit can provide a suggestion that uses a lot of technical terms. Also, if the couple does not have specialized knowledge, the suggestion unit can provide a suggestion that is explained in simple language. Furthermore, the suggestion unit can adjust the content of the suggestion depending on the expertise level of the couple. This can increase the likelihood of the suggestion being accepted by providing a suggestion that is appropriate for the expertise level of the couple.

[0103] The reservation unit can estimate the couple's emotions and adjust the reservation method based on the estimated couple's emotions. For example, if the couple is nervous, the reservation unit can provide a simple and highly visible reservation method. Furthermore, if the couple is relaxed, the reservation unit can provide a reservation method that includes detailed information. Furthermore, if the couple is in a hurry, the reservation unit can provide a quick and concise reservation method. This can reduce the stress of the reservation process by providing a reservation method that corresponds to the couple's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI can be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0104] The reservation unit can analyze the couple's past reservation history at the time of reservation and select the optimal reservation method. For example, the reservation unit can suggest the optimal reservation method based on the reservation methods used by the couple in the past. The reservation unit can also analyze the couple's past reservation history and suggest the most efficient reservation method. Furthermore, the reservation unit can customize the reservation method by referring to the couple's past reservation history. This makes it possible to streamline the reservation process by providing the optimal reservation method based on the past reservation history.

[0105] The reservation unit can customize the reservation method based on the couple's current living situation at the time of reservation. For example, if a couple is busy because both partners work, the reservation unit can provide a simplified reservation method. Also, if a couple is interested in a particular theme, the reservation unit can provide reservation methods related to that theme preferentially. Furthermore, the reservation unit can customize the order and content of the reservation methods according to the couple's living situation. This can streamline the reservation process by providing reservation methods that suit the couple's living situation.

[0106] The reservation unit can improve the reservation method by reflecting the couple's feedback at the time of reservation. For example, the reservation unit can suggest the optimal reservation method based on feedback provided by the couple in the past. The reservation unit can also improve the reservation interface by reflecting the couple's past feedback. Furthermore, the reservation unit can customize the order and content of the reservation methods based on the couple's past feedback. This can make the reservation process more efficient by providing the optimal reservation method based on past feedback.

[0107] The reservation unit can estimate the couple's emotions and prioritize reservations based on the estimated couple's emotions. For example, if the couple is nervous, the reservation unit can prioritize important reservations. Furthermore, if the couple is relaxed, the reservation unit can prioritize reservations that include detailed information. Furthermore, if the couple is in a hurry, the reservation unit can prioritize quick and concise reservations. This can streamline reservation work by providing reservation priorities according to the couple's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI can be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0108] The reservation unit can select the optimal reservation method by taking into consideration the geographical location information of the couple when making a reservation. For example, if the couple lives in a specific area, the reservation unit can preferentially provide reservation methods related to that area. Also, if the couple plans to hold a wedding in a specific area, the reservation unit can preferentially provide reservation methods related to that area. Furthermore, the reservation unit can suggest the optimal reservation method based on the geographical location information of the couple. This makes it possible to streamline the reservation process by providing the optimal reservation method based on the geographical location information.

[0109] The reservation unit can analyze the couple's social media activity at the time of reservation to suggest a reservation method. For example, the reservation unit can suggest a relevant reservation method based on information shared by the couple on social media. The reservation unit can also analyze the couple's social media activity and automatically suggest a relevant reservation method. Furthermore, the reservation unit can suggest a relevant reservation method based on the activity of the couple's friends on social media. This makes it possible to streamline the reservation process by providing the optimal reservation method based on social media activity.

[0110] The reservation unit can customize the reservation method by reflecting the couple's past feedback when making a reservation. For example, the reservation unit can suggest the optimal reservation method based on the couple's past feedback. The reservation unit can also improve the reservation interface by reflecting the couple's past feedback. Furthermore, the reservation unit can customize the order and content of the reservation methods based on the couple's past feedback. This can make the reservation process more efficient by providing the optimal reservation method based on the couple's past feedback.

[0111] The creation support unit can estimate the couple's emotions and adjust the creation support method based on the estimated couple's emotions. For example, if the couple is nervous, the creation support unit can provide a simple and highly visible creation support method. Furthermore, if the couple is relaxed, the creation support unit can provide a creation support method that includes detailed information. Furthermore, if the couple is in a hurry, the creation support unit can provide a quick and concise creation support method. This can reduce the stress of the creation work by providing a creation support method that corresponds to the couple's emotions. Emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples.

[0112] The creation support unit can analyze the couple's past creation history and select the optimal creation method when providing creation support. For example, the creation support unit can suggest the optimal creation method based on the creation methods used by the couple in the past. The creation support unit can also analyze the couple's past creation history and suggest the most efficient creation method. Furthermore, the creation support unit can customize the creation method by referring to the couple's past creation history. This makes it possible to streamline the creation process by providing the optimal creation method based on the past creation history.

[0113] The creation support unit can customize the creation support means based on the couple's current living situation when providing creation support. For example, if a couple is busy because both partners work, the creation support unit can provide simplified creation support means. Also, if a couple is interested in a specific theme, the creation support unit can provide creation support means related to that theme preferentially. Furthermore, the creation support unit can customize the order and content of the creation support means according to the couple's living situation. This makes it possible to streamline the creation work by providing creation support means that suit the couple's living situation.

[0114] The creation support unit can improve the creation support method by reflecting the couple's feedback during creation support. For example, the creation support unit can propose an optimal creation support method based on feedback previously provided by the couple. The creation support unit can also improve the creation support interface by reflecting the couple's past feedback. Furthermore, the creation support unit can customize the order and content of the creation support means based on the couple's past feedback. This can make the creation work more efficient by providing an optimal creation support method based on past feedback.

[0115] The creation support unit can estimate the couple's emotions and determine the priority of creation support based on the estimated couple's emotions. For example, if the couple is nervous, the creation support unit can prioritize important creation support. Also, if the couple is relaxed, the creation support unit can prioritize creation support that includes detailed information. Furthermore, if the couple is in a hurry, the creation support unit can prioritize quick and concise creation support. This allows for efficient creation work by providing a priority order for creation support according to the couple's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI.

[0116] The creation support unit can select the optimal creation support method by taking into consideration the geographical location information of the couple when providing creation support. For example, if the couple lives in a specific area, the creation support unit can preferentially provide creation support methods related to that area. Also, if the couple plans to hold their wedding in a specific area, the creation support unit can preferentially provide creation support methods related to that area. Furthermore, the creation support unit can suggest the optimal creation support method based on the geographical location information of the couple. This makes it possible to streamline the creation work by providing the optimal creation support method based on the geographical location information.

[0117] The creation support unit can analyze the couple's social media activity and suggest creation support means when providing creation support. For example, the creation support unit can suggest relevant creation support means based on information shared by the couple on social media. The creation support unit can also analyze the couple's social media activity and automatically suggest relevant creation support means. Furthermore, the creation support unit can suggest relevant creation support means by referring to the activity of the couple's friends on social media. This makes it possible to streamline the creation process by providing optimal creation support means based on social media activity.

[0118] The creation support unit can customize the creation support method by reflecting the couple's past feedback when providing creation support. For example, the creation support unit can suggest the optimal creation support method based on feedback provided by the couple in the past. The creation support unit can also improve the creation support interface by reflecting the couple's past feedback. Furthermore, the creation support unit can customize the order and content of the creation support means based on the couple's past feedback. This can make the creation work more efficient by providing the optimal creation support method based on past feedback.

[0119] The coordination unit can estimate the couple's emotions and adjust the coordination method based on the estimated couple's emotions. For example, if the couple is nervous, the coordination unit can provide a simple and highly visible coordination method. Furthermore, if the couple is relaxed, the coordination unit can provide a coordination method that includes detailed information. Furthermore, if the couple is in a hurry, the coordination unit can provide a quick and concise coordination method. This can reduce the stress of coordination work by providing a coordination method that corresponds to the couple's emotions. Emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to these examples.

[0120] The coordination unit can analyze the past coordination history of the couple when coordinating and select the optimal coordination method. For example, the coordination unit can suggest the optimal coordination method based on the coordination methods used by the couple in the past. The coordination unit can also analyze the past coordination history of the couple and suggest the most efficient coordination method. Furthermore, the coordination unit can customize the coordination method by referring to the past coordination history of the couple. This makes it possible to improve the efficiency of the coordination work by providing the optimal coordination method based on the past coordination history.

[0121] The coordination unit can customize coordination methods based on the couple's current living situation when coordinating. For example, if a couple is busy because both partners work, the coordination unit can provide simplified coordination methods. Also, if a couple is interested in a particular theme, the coordination unit can provide coordination methods related to that theme preferentially. Furthermore, the coordination unit can customize the order and content of coordination methods according to the couple's living situation. This can make the coordination process more efficient by providing coordination methods that suit the couple's living situation.

[0122] The coordination unit can improve the coordination method by reflecting the couple's feedback during coordination. For example, the coordination unit can suggest an optimal coordination method based on feedback provided by the couple in the past. The coordination unit can also improve the coordination interface by reflecting the couple's past feedback. Furthermore, the coordination unit can customize the order and content of coordination methods based on the couple's past feedback. This can make the coordination work more efficient by providing an optimal coordination method based on past feedback.

[0123] The coordination unit can estimate the couple's emotions and determine the priority of coordination based on the estimated emotions of the couple. For example, if the couple is nervous, the coordination unit can prioritize important coordination. Furthermore, if the couple is relaxed, the coordination unit can prioritize coordination that includes detailed information. Furthermore, if the couple is in a hurry, the coordination unit can prioritize quick and concise coordination. This can improve the efficiency of coordination work by providing coordination priorities according to the couple's emotions. Emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI.

[0124] The coordination unit can select the optimal coordination method by taking into consideration the geographical location information of the couple when coordinating. For example, if the couple lives in a specific area, the coordination unit can preferentially provide coordination methods related to that area. Also, if the couple plans to hold a wedding in a specific area, the coordination unit can preferentially provide coordination methods related to that area. Furthermore, the coordination unit can suggest the optimal coordination method based on the geographical location information of the couple. This makes it possible to streamline coordination work by providing the optimal coordination method based on the geographical location information.

[0125] The coordination unit can analyze the couple's social media activity when coordinating outfits and suggest coordination methods. The coordination unit can suggest related coordination methods, for example, based on information shared by the couple on social media. The coordination unit can also analyze the couple's social media activity and automatically suggest related coordination methods. Furthermore, the coordination unit can suggest related coordination methods by referring to the activity of the couple's friends on social media. This makes it possible to streamline coordination work by providing optimal coordination methods based on social media activity.

[0126] The coordination unit can customize the coordination method by reflecting the couple's past feedback when coordinating. For example, the coordination unit can suggest an optimal coordination method based on feedback provided by the couple in the past. The coordination unit can also improve the coordination interface by reflecting the couple's past feedback. Furthermore, the coordination unit can customize the order and content of coordination methods based on the couple's past feedback. This can make the coordination work more efficient by providing an optimal coordination method based on past feedback.

[0127] The production department can estimate the couple's emotions and adjust the production method based on the estimated couple's emotions. For example, if the couple is nervous, the production department can provide a simple, highly visible production method. Furthermore, if the couple is relaxed, the production department can provide a production method that includes detailed information. Furthermore, if the couple is in a hurry, the production department can provide a quick and concise production method. This can reduce the stress of production work by providing a production method that corresponds to the couple's emotions. Emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples.

[0128] The production department can analyze the couple's past production history during production to select the optimal production method. For example, the production department can propose the optimal production method based on the production methods the couple has used in the past. The production department can also analyze the couple's past production history to propose the most efficient production method. Furthermore, the production department can customize the production method by referring to the couple's past production history. This makes it possible to streamline production work by providing the optimal production method based on the couple's past production history.

[0129] The production department can customize the production methods based on the couple's current living situation during production. For example, if a couple is busy because both partners work, the production department can provide simplified production methods. Also, if a couple is interested in a particular theme, the production department can prioritize providing production methods related to that theme. Furthermore, the production department can customize the order and content of the production methods according to the couple's living situation. This allows the production work to be made more efficient by providing production methods that suit the couple's living situation.

[0130] The production department can improve the production method by reflecting the couple's feedback during production. For example, the production department can suggest the optimal production method based on feedback provided by the couple in the past. The production department can also improve the production interface by reflecting the couple's past feedback. Furthermore, the production department can customize the order and content of the production methods based on the couple's past feedback. This makes it possible to streamline the production work by providing the optimal production method based on past feedback.

[0131] The production department can estimate the couple's emotions and determine production priorities based on the estimated couple's emotions. For example, if the couple is nervous, the production department can prioritize important productions. Also, if the couple is relaxed, the production department can prioritize productions that include detailed information. Furthermore, if the couple is in a hurry, the production department can prioritize quick and concise productions. This allows for production prioritization according to the couple's emotions, thereby streamlining production work. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generation AI. Generation AI can be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0132] The production department can select the optimal production method by taking into consideration the geographical location information of the couple during production. For example, if the couple lives in a specific area, the production department can prioritize providing production methods related to that area. Also, if the couple plans to hold their wedding in a specific area, the production department can prioritize providing production methods related to that area. Furthermore, the production department can suggest the optimal production method based on the geographical location information of the couple. This allows for the efficiency of production work by providing the optimal production method based on the geographical location information.

[0133] The production department can analyze the couple's social media activity during production to suggest production methods. For example, the production department can suggest relevant production methods based on information shared by the couple on social media. The production department can also analyze the couple's social media activity and automatically suggest relevant production methods. Furthermore, the production department can suggest relevant production methods based on the activity of the couple's friends on social media. This makes it possible to streamline production work by providing optimal production methods based on social media activity.

[0134] The production department can customize the production method by reflecting the couple's past feedback during production. For example, the production department can suggest the optimal production method based on the couple's past feedback. The production department can also improve the production interface by reflecting the couple's past feedback. Furthermore, the production department can customize the order and content of the production methods based on the couple's past feedback. This makes it possible to streamline the production work by providing the optimal production method based on the past feedback. === Hard Collateral 1-1 === Each of the above-described elements, including the reception unit, proposal unit, reservation unit, creation support unit, coordination unit, and production unit, is implemented, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit can accept input of the number of guests and desired budget via the reception device 38 of the smart device 14 or the communication I / F 26 of the data processing device 12. The proposal unit, implemented by the specific processing unit 290 of the data processing device 12, proposes an optimal venue based on the couple's preferences. The reservation unit makes reservations for the proposed venue via the specific processing unit 290 of the data processing device 12. The creation support unit supports the creation of invitations, seating charts, and speech manuscripts via the control unit 46A of the smart device 14 and the specific processing unit 290 of the data processing device 12. The coordination unit coordinates the venue design and orders necessary accessories via the control unit 46A of the smart device 14 and the specific processing unit 290 of the data processing device 12. The production unit produces a movie via the control unit 46A of the smart device 14 and the specific processing unit 290 of the data processing device 12. === Hard Collateral 1-2 === Each of the multiple elements, including the reception unit, proposal unit, reservation unit, creation support unit, coordination unit, and production unit, described above, is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit can accept input of the number of guests and desired budget via the microphone 238 of the smart glasses 214 or the communication I / F 26 of the data processing device 12. The proposal unit is realized by the specific processing unit 290 of the data processing device 12 and proposes the optimal venue based on the couple's preferences. The reservation unit makes reservations for the venue proposed by the specific processing unit 290 of the data processing device 12. The creation support unit supports the creation of invitations, seating charts, and speech manuscripts using the control unit 46A of the smart glasses 214 and the specific processing unit 290 of the data processing device 12. The coordination unit coordinates the venue design and orders necessary accessories using the control unit 46A of the smart glasses 214 and the specific processing unit 290 of the data processing device 12. The production unit produces movies using the control unit 46A of the smart glasses 214 and the specific processing unit 290 of the data processing device 12. === Hard Collateral 1-3 === Each of the multiple elements, including the reception unit, proposal unit, reservation unit, creation support unit, coordination unit, and production unit, described above, is realized, for example, by at least one of the headset terminal 314 and the data processing device 12. For example, the reception unit can accept input of the number of guests and desired budget via the microphone 238 of the headset terminal 314 or the communication I / F 26 of the data processing device 12. The proposal unit is realized by the specific processing unit 290 of the data processing device 12 and proposes the optimal venue based on the couple's preferences. The reservation unit makes reservations for the venue proposed by the specific processing unit 290 of the data processing device 12. The creation support unit supports the creation of invitations, seating charts, and speech manuscripts using the control unit 46A of the headset terminal 314 and the specific processing unit 290 of the data processing device 12. The coordination unit coordinates the venue design and orders necessary accessories using the control unit 46A of the headset terminal 314 and the specific processing unit 290 of the data processing device 12. The production unit produces a movie using the control unit 46A of the headset type terminal 314 and the specific processing unit 290 of the data processing device 12. === Hard Collateral 1-4 === Each of the multiple elements, including the reception unit, proposal unit, reservation unit, creation support unit, coordination unit, and production unit, is realized, for example, by at least one of the headset-type terminal 314 and the data processing device 12. For example, the reception unit can accept input of the number of guests and desired budget via the microphone 238 of the robot 414 or the communication I / F 26 of the data processing device 12. The proposal unit is realized by the specific processing unit 290 of the data processing device 12 and proposes the optimal venue based on the couple's preferences. The reservation unit makes reservations for the venue proposed by the specific processing unit 290 of the data processing device 12. The creation support unit supports the creation of invitations, seating charts, and speech manuscripts using the control unit 46A of the robot 414 and the specific processing unit 290 of the data processing device 12. The coordination unit coordinates the venue design and orders necessary accessories using the control unit 46A of the robot 414 and the specific processing unit 290 of the data processing device 12. The production unit produces a movie using the control unit 46A of the robot 414 and the specific processing unit 290 of the data processing device 12.

[0135] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0136] The suggestion unit can estimate the couple's emotions and adjust the way the suggestion is expressed based on the estimated emotions of the couple. For example, if the couple is nervous, a simple and highly visible suggestion can be provided. If the couple is relaxed, a suggestion including detailed information can be provided. Furthermore, if the couple is in a hurry, a suggestion that focuses on the main points can be provided. In this way, by providing a way of expressing the suggestion according to the couple's emotions, it is possible to increase the likelihood of the suggestion being accepted.

[0137] The suggestion unit can adjust the level of detail of the proposal based on the importance of the venue when making the proposal. For example, for an important venue, a proposal including detailed information can be provided. For a less important venue, a simplified proposal can be provided. Furthermore, the level of detail of the proposal can be adjusted according to the importance of the venue. This can improve the likelihood of the proposal being accepted by providing a level of detail of the proposal according to the importance of the venue.

[0138] The suggestion unit can apply different suggestion algorithms depending on the category of the venue when making a suggestion. For example, in the case of a hotel venue, a suggestion that emphasizes the hotel's features can be provided. In addition, in the case of a garden venue, a suggestion that emphasizes the garden's features can be provided. Furthermore, in the case of a restaurant venue, a suggestion that emphasizes the restaurant's features can be provided. This makes it possible to provide optimal suggestions according to the venue category, thereby increasing the likelihood of the suggestions being accepted.

[0139] The suggestion unit can improve the accuracy of the suggestion by referring to the couple's past suggestion results when making a suggestion. For example, the suggestion unit can suggest the most suitable venue based on the features of venues selected by the couple in the past. The suggestion unit can also improve the accuracy of the suggestion by analyzing the couple's past suggestion results. Furthermore, the suggestion unit can customize the content of the suggestion by referring to the couple's past suggestion results. This allows the suggestion unit to improve the accuracy of the suggestion by providing the most suitable suggestion based on the past suggestion results.

[0140] The suggestion unit can estimate the couple's emotions and adjust the length of the suggestion based on the estimated couple's emotions. For example, if the couple is nervous, a short and to-the-point suggestion can be provided. If the couple is relaxed, a longer suggestion with detailed explanations can be provided. Furthermore, if the couple is in a hurry, a quick and concise suggestion can be provided. In this way, by providing the length of the suggestion according to the couple's emotions, it is possible to increase the likelihood of the suggestion being accepted.

[0141] The reservation unit can estimate the couple's emotions and adjust the reservation method based on the estimated couple's emotions. For example, if the couple is nervous, a simple and highly visible reservation method can be provided. If the couple is relaxed, a reservation method including detailed information can be provided. Furthermore, if the couple is in a hurry, a quick and concise reservation method can be provided. In this way, by providing a reservation method that corresponds to the couple's emotions, the stress of the reservation process can be reduced.

[0142] The reservation unit can analyze the couple's past reservation history when making a reservation and select the optimal reservation method. For example, it can suggest the optimal reservation method based on the reservation methods the couple has used in the past. It can also analyze the couple's past reservation history and suggest the most efficient reservation method. Furthermore, it can customize the reservation method by referring to the couple's past reservation history. This makes it possible to streamline the reservation process by providing the optimal reservation method based on the past reservation history.

[0143] The reservation unit can customize the reservation method based on the couple's current living situation when making a reservation. For example, if a couple is busy because both partners work, a simplified reservation method can be provided. Also, if a couple is interested in a specific theme, reservation methods related to that theme can be provided preferentially. Furthermore, the order and content of the reservation methods can be customized according to the couple's living situation. This makes it possible to streamline the reservation process by providing reservation methods that suit the couple's living situation.

[0144] The creation support unit can estimate the couple's emotions and adjust the creation support method based on the estimated couple's emotions. For example, if the couple is nervous, a simple and highly visible creation support method can be provided. If the couple is relaxed, a creation support method including detailed information can be provided. Furthermore, if the couple is in a hurry, a quick and concise creation support method can be provided. In this way, by providing a creation support method that corresponds to the couple's emotions, it is possible to reduce the stress of the creation work.

[0145] The creation support unit can analyze the couple's past creation history when providing creation support and select the optimal creation method. For example, it can suggest the optimal creation method based on the creation methods the couple has used in the past. It can also analyze the couple's past creation history and suggest the most efficient creation method. Furthermore, it can customize the creation method by referring to the couple's past creation history. This makes it possible to streamline the creation process by providing the optimal creation method based on the past creation history.

[0146] The processing flow of the second embodiment will be briefly explained below.

[0147] Step 1: The reception unit accepts input of the number of people or desired budget. For example, when a couple enters their desired budget and number of people, the reception unit can accept that information. Step 2: The proposal unit proposes an appropriate venue based on the information received by the reception unit. For example, the proposal unit can search for and propose the optimal venue based on the couple's desired budget and number of guests. Step 3: The reservation unit makes a reservation for the venue proposed by the proposal unit. For example, the reservation unit can automatically make a reservation for the proposed venue. Step 4: The creation support unit supports the creation of invitations, seating charts, and speech manuscripts. For example, when the couple inputs their desired design and content, the creation support unit can generate invitations, seating charts, and speech manuscripts based on that. Step 5: The coordination department coordinates the venue design and orders the necessary accessories. For example, if the couple inputs the theme and style they want, the coordination department can coordinate the venue design based on that and order the necessary accessories. Step 6: The production team creates the movie. For example, the production team can generate a movie based on the couple's desired content or theme.

[0148] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0149] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0150] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0151] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0152] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0153] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0154] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0155] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0156] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0157] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0158] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0159] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0160] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0161] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0162] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0163] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0164] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0165] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0166] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0167] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0168] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0169] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0170] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0171] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0172] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0173] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0174] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0175] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0176] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0177] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0178] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0179] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0180] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0181] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0182] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0183] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0184] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0185] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0186] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0187] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0188] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0189] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0190] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0191] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0192] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0193] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0194] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0195] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0196] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0197] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0198] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0199] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0200] The correspondence between each part and the device or control part is not limited to the above example, and various modifications are possible.

[0201] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0202] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0203] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0204] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0205] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0206] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0207] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0208] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0209] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0210] 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.

[0211] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0212] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0213] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0214] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0215] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0216] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0217] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0218] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0219] [Explanation of symbols]

[0220] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a reception unit for receiving input of the number of people or desired budget; a proposal unit that proposes an appropriate venue based on the information received by the reception unit; a reservation unit that makes reservations for the venue proposed by the proposal unit; A writing support department that assists with the creation of invitations, seating charts, and speech manuscripts; The Coordination Department coordinates the venue design and orders necessary accessories. A production department that produces movies. A system characterized by:

2. The proposal unit Suggest suitable venues based on the couple's desired budget or number of guests 2. The system of claim 1.

3. The reservation unit Make a reservation for the proposed venue 2. The system of claim 1.

4. The creation support unit Generate invitations, seating charts, and speech scripts based on the couple's desired design or content 2. The system of claim 1.

5. The coordinating unit Coordinate the venue design based on the couple's desired theme or style and order any necessary accessories 2. The system of claim 1.

6. The production department: Generate movies based on couples' desired content and themes 2. The system of claim 1.

7. The reception unit Estimate the couple's emotions and adjust the design of the input interface based on the estimated couple's emotions.

2. The system of claim 1.

8. The reception unit Analyzes the couple's past wedding preparation history and suggests the best way to enter information 2. The system of claim 1.

9. The reception unit Customize your input based on the couple's current life situation and interests as you enter it 2. The system of claim 1.

10. The reception unit Select the best input method according to the couple's input method when inputting 2. The system of claim 1.

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