System

Abstract

An object of a system according to an embodiment is to enable anyone to easily create project mapping and use the project mapping in an event.SOLUTION: A system includes a reception unit, a generation unit, and a control unit. The reception unit inputs detailed information of an event. The generation unit analyzes the information input by the reception unit and generates a plan of project mapping. The control unit controls video and music in real time on the basis of the plan generated by the generation unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional techniques have had the problem that creating project mapping requires specialized knowledge and is difficult for general users to use easily.

[0005] The system according to the embodiment aims to enable anyone to easily create project mapping and use it at events. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, a generation unit, and a control unit. The reception unit inputs detailed information about the event. The generation unit analyzes the information input by the reception unit and generates a plan for project mapping. The control unit controls video and music in real time based on the plan generated by the generation unit. [Effects of the Invention]

[0007] The system according to the embodiment allows anyone to easily create project mapping and use it at an event. [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 project mapping generation system according to an embodiment of the present invention is a system in which detailed event information is input, and a generation AI generates an optimal project mapping plan and controls video and music in real time. The project mapping generation system allows anyone to easily create project mapping for any event, regardless of its type or scale. This system allows a user to input detailed event information, and a generation AI analyzes the input information to generate an optimal project mapping plan. For example, for a wedding, the generation AI creates an impressive video using photos and videos of the bride and groom. Based on the generated plan, the user sets up a projector and sound equipment and holds the event. The generation AI controls video and music in real time, creating project mapping in accordance with the progress of the event. For example, for a fireworks display, the AI ​​controls the video and music to change in sync with the fireworks launch. This system allows anyone to easily create project mapping and liven up an event. Even without special skills or knowledge, the generation AI automatically generates an optimal plan and controls it in real time, allowing users to enjoy the event with peace of mind. This allows the project mapping generation system to input detailed event information, and the generation AI generates an optimal project mapping plan and controls video and music in real time. For example, users simply need to enter detailed information about the event, and the generation AI will automatically generate the optimal plan and control it in real time, allowing users to enjoy the event with peace of mind.

[0029] A project mapping generation system according to an embodiment includes a reception unit, a generation unit, and a control unit. The reception unit inputs detailed event information. The detailed event information includes, but is not limited to, the type of event, location, date and time, number of participants, location layout, and type of projector to be used. The reception unit, for example, stores the information input by the user in a database and provides the information to the generation unit. The generation unit analyzes the information input by the reception unit and generates an optimal project mapping plan using a generation AI. The generation AI automatically selects images and music that match the theme and atmosphere of the event using technologies such as deep learning and neural networks to create a project mapping scenario. For example, in the case of a wedding, the generation unit creates a moving image using photos and videos of the bride and groom. In the case of a fireworks display, the generation unit can also create a scenario in which the images change and the music plays in sync with the fireworks launch. The control unit controls the images and music in real time based on the plan generated by the generation unit. The control unit controls, for example, a projector and audio equipment to perform project mapping in accordance with the progress of the event. The control unit can control the video to change and the music to play in sync with the launch of fireworks, for example. This allows the project mapping generation system according to the embodiment to input detailed event information, have the generation AI generate an optimal project mapping plan, and control the video and music in real time.

[0030] The reception unit can input information such as the type of event, location, date and time, number of participants, location layout, and type of projector to be used. Examples of event types include, but are not limited to, weddings, concerts, and conferences. Examples of location layouts include, but are not limited to, seating arrangements and stage positions. Examples of projector types include, but are not limited to, DLP projectors and LCD projectors. The reception unit, for example, stores the information input by the user in a database and provides it to the generation unit. This allows detailed event information to be accurately input.

[0031] The generation unit can use generation AI to automatically select images and music that match the event theme and create a project mapping scenario. The generation AI uses technologies such as deep learning and neural networks to automatically select images and music that match the event theme and atmosphere. For example, in the case of a wedding, the generation AI can create a moving image using photos and videos of the bride and groom. In the case of a fireworks display, the generation AI can also create a scenario that controls the images and music to change in sync with the fireworks launch. The generation AI selects images and music based on criteria such as genre, atmosphere, and tempo. This makes it possible to automatically create the optimal project mapping scenario that matches the event theme and atmosphere.

[0032] The control unit can control the video and music in real time based on the generated plan. The control unit, for example, controls a projector and audio equipment and performs project mapping in accordance with the progress of the event. The control unit can, for example, control the video so that it changes and the music plays in accordance with the launch of fireworks. The control unit performs control in real time based on, for example, the timing of control and the technology used. This allows the video and music to be controlled in real time based on the generated plan.

[0033] The control unit can control the video to change and the music to play in sync with the launch of fireworks. The control unit controls the video to change and the music to play in sync with the timing of the launch of fireworks, for example. The control unit performs control based on a synchronization method for the video and the music, for example. This allows the video and the music to be controlled in sync with the launch of fireworks.

[0034] In the case of a wedding, the generation unit can create a video using photos and videos of the bride and groom. For example, in the case of a wedding, the generation unit creates a moving video using photos and videos of the bride and groom. The generation unit creates the video based on, for example, selection criteria and editing methods for the photos and videos to be used. In this way, a moving video can be created for the wedding.

[0035] When inputting detailed event information, the reception unit can complement the input by referring to the user's past event history. For example, the reception unit automatically displays event types and locations previously input by the user as candidates. For example, the reception unit preferentially suggests projector types and audio equipment previously used by the user. For example, the reception unit predicts and suggests specific dates and times and the number of participants from the user's past event history. This allows the input to be complemented by referring to the user's past event history.

[0036] The reception unit can automatically acquire the user's current location information to complement the location information when entering detailed event information. For example, when the user opens the app, the reception unit automatically acquires the user's current location and sets it as the event location. For example, when the user enters the event location, the reception unit suggests the most suitable candidate location taking into account the distance from the user's current location. For example, when the user uses the app while on the move, the reception unit updates the user's current location in real time and reflects it as the event location. This allows the user's current location information to be automatically acquired to complement the location information.

[0037] The reception unit can provide a function for analyzing a user's voice input and converting it into text when entering detailed event information. For example, the reception unit automatically sets the location information when the user simply voice-inputs, "The wedding location is ____." For example, the reception unit automatically sets the number of participants when the user simply voice-inputs, "The number of participants is 50." For example, the reception unit automatically sets the type of projector to be used when the user simply voice-inputs, "We will use ____ projector." This allows the user's voice input to be analyzed and converted into text.

[0038] When inputting detailed information about an event, the reception unit can automatically input related information by referring to the user's social media activity. For example, the reception unit automatically sets the location where the user checked in on social media as the location of the event. For example, the reception unit analyzes the content of the user's social media posts and automatically inputs the type and date and time of the related event. For example, the reception unit automatically inputs detailed information about the related event by referring to the activity of the user's friends on social media. In this way, it is possible to automatically input related information by referring to the user's social media activity.

[0039] The reception unit can customize the input interface by reflecting the user's past feedback when entering detailed event information. The reception unit provides an easy-to-use interface, for example, based on feedback previously entered by the user. The reception unit, for example, preferentially displays specific input items based on the user's past feedback. The reception unit, for example, analyzes the user's past feedback and suggests an optimal input method. This allows the input interface to be customized by reflecting the user's past feedback.

[0040] When entering detailed event information, the reception unit can provide an input method based on the user's device information. For example, if the user is using a smartphone, the reception unit provides an input method that matches the screen size. For example, if the user is using a tablet, the reception unit provides an input method that is optimized for a large screen. For example, if the user is using a desktop, the reception unit provides an input method that prioritizes keyboard input. This makes it possible to provide the optimal input method in consideration of the user's device information.

[0041] The generation unit can refer to past event data to generate an optimal project mapping plan that matches the theme and atmosphere of the event. For example, the generation unit references data from past weddings to generate an impressive project mapping plan. For example, the generation unit references data from past fireworks displays to generate a visually beautiful project mapping plan. For example, the generation unit references data from past music events to generate a project mapping plan that matches the music. In this way, it is possible to generate an optimal project mapping plan by referencing past event data.

[0042] The generation unit can generate multiple different scenarios based on detailed event information and provide the user with options. For example, in the case of a wedding, the generation unit can generate an emotional scenario and an enjoyable scenario and provide the user with options. For example, in the case of a fireworks display, the generation unit can generate a visually beautiful scenario and a scenario that matches music and provide the user with options. For example, in the case of a music event, the generation unit can generate scenarios that match music of different genres and provide the user with options. In this way, multiple different scenarios can be generated and the user can be provided with options.

[0043] The generation unit can automatically adjust the length and timing of the video and music to be generated based on detailed information about the event. For example, in the case of a wedding, the generation unit automatically adjusts the length of the video and music to match the progress of the ceremony. For example, in the case of a fireworks display, the generation unit automatically adjusts the timing of the video and music to match the launch of the fireworks. For example, in the case of a music event, the generation unit automatically adjusts the length and timing of the video and music to match the progress of the performance. This makes it possible to automatically adjust the length and timing of the video and music to be generated.

[0044] The generation unit can generate a project mapping plan that incorporates elements of different cultures and regions to match the theme and atmosphere of the event. For example, in the case of a wedding, the generation unit generates a project mapping plan that incorporates wedding elements of different cultures. For example, in the case of a fireworks display, the generation unit generates a project mapping plan that incorporates elements of fireworks displays of different regions. For example, in the case of a music event, the generation unit generates a project mapping plan that incorporates music elements of different cultures. In this way, it is possible to generate project mapping plans that incorporate elements of different cultures and regions.

[0045] The generation unit can add interactive elements to the generated video and music based on detailed information about the event. For example, in the case of a wedding, the generation unit generates interactive video and music in which guests can participate. For example, in the case of a fireworks display, the generation unit adds interactive elements that allow spectators to affect the video and music in real time. For example, in the case of a music event, the generation unit adds interactive elements that allow spectators to manipulate the video and music in time with the performance. In this way, by adding interactive elements to the generated video and music, it is possible to provide a performance that is more enjoyable for participants.

[0046] The generation unit can incorporate a user's personal message into the generated video and music based on detailed information about the event. For example, in the case of a wedding, the generation unit incorporates a message from the bride and groom into the video and music. For example, in the case of a fireworks display, the generation unit incorporates a message from the organizer into the video and music. For example, in the case of a music event, the generation unit incorporates a message from the artist into the video and music. In this way, by incorporating a user's personal message into the generated video and music, a more personalized performance can be provided.

[0047] The control unit can automatically adjust the timing of the video and music according to the progress of the event. For example, in the case of a wedding, the control unit automatically adjusts the timing of the video and music to match the progress of the ceremony. For example, in the case of a fireworks display, the control unit automatically adjusts the timing of the video and music to match the launch of the fireworks. For example, in the case of a music event, the control unit automatically adjusts the timing of the video and music to match the progress of the performance. In this way, the timing of the video and music can be automatically adjusted according to the progress of the event.

[0048] The control unit can adjust the volume and effects of the video and music in real time according to the progress of the event. For example, in the case of a wedding, the control unit adjusts the music volume in real time to match the progress of the ceremony. For example, in the case of a fireworks display, the control unit adjusts the video effects in real time to match the launch of the fireworks. For example, in the case of a music event, the control unit adjusts the music volume and effects in real time to match the progress of the performance. This makes it possible to adjust the volume and effects of the video and music in real time according to the progress of the event.

[0049] The control unit can apply an algorithm for smoothly switching between video and music in accordance with the progress of the event. For example, in the case of a wedding, the control unit applies an algorithm for smoothly switching between video and music in accordance with the progress of the ceremony. For example, in the case of a fireworks display, the control unit applies an algorithm for smoothly switching between video and music in accordance with the launch of the fireworks. For example, in the case of a music event, the control unit applies an algorithm for smoothly switching between video and music in accordance with the progress of the performance. This allows for smooth switching between video and music in accordance with the progress of the event.

[0050] The control unit can add interactive elements to the video and music production according to the progress of the event. For example, in the case of a wedding, the control unit adds an interactive production in which guests can participate. For example, in the case of a fireworks display, the control unit adds an interactive element that allows spectators to affect the video and music in real time. For example, in the case of a music event, the control unit adds an interactive element that allows spectators to manipulate the video and music in time with the performance. This makes it possible to provide interactive production according to the progress of the event.

[0051] The control unit can reflect user feedback in the video and music production according to the progress of the event. For example, in the case of a wedding, the control unit adjusts the video and music production in real time based on feedback from guests. For example, in the case of a fireworks display, the control unit adjusts the video and music production in real time based on feedback from spectators. For example, in the case of a music event, the control unit adjusts the video and music production in real time based on feedback from spectators. This makes it possible to provide a production that reflects user feedback according to the progress of the event.

[0052] The control unit can link different devices to produce video and music depending on the progress of the event. For example, in the case of a wedding, the control unit links smartphones and tablets to produce video and music. For example, in the case of a fireworks display, the control unit links drones and lights to produce video and music. For example, in the case of a music event, the control unit links projectors and speakers to produce video and music. This makes it possible to provide a performance that links different devices depending on the progress of the event.

[0053] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0054] The reception unit can automatically search for data on related past events based on the event details entered by the user and provide it as reference information. For example, if the user enters details about a wedding, project mapping plans and video samples from past weddings can be displayed. If the user enters details about a concert, video and music samples from past concerts can be provided. Furthermore, if the user enters details about a meeting, sample layouts and audio settings from past meetings can be displayed. This allows the user to create the optimal project mapping plan while referring to past success stories.

[0055] The generation unit can generate multiple project mapping plans with different themes and styles based on the event details entered by the user, and provide the user with options. For example, for a wedding, plans with a romantic theme, a classical theme, and a modern theme can be generated to provide the user with options. For a concert, plans tailored to different music genres such as rock, pop, and classical can be generated. For a conference, plans with a formal style, a casual style, and an interactive style can be generated to provide the user with options. This allows the user to select the optimal plan that matches the theme and style of the event.

[0056] The control unit can add interactive elements to video and music productions depending on the progress of the event. For example, at a wedding, an interactive production can be added that allows guests to affect the video and music in real time using their smartphones. At a concert, an interactive production can be added that allows audience members to change the color and pattern of lights using their smartphones. Furthermore, at a conference, an interactive production can be added that allows participants to control the content of the presentation using tablets. This allows participants to more actively participate in and enjoy the event.

[0057] The generation unit can incorporate a user's personal message into the generated video and music based on detailed information about the event. For example, in the case of a wedding, a message from the bride and groom can be incorporated into the video and music. In the case of a concert, a message from the artist can be incorporated into the video and music. Furthermore, in the case of a conference, a message from the organizer can be incorporated into the video and music. In this way, by incorporating a user's personal message into the generated video and music, a more personalized performance can be provided.

[0058] When inputting detailed event information, the reception unit can complement the input by referring to the user's past event history. For example, the reception unit can automatically display the event types and locations previously input by the user as candidates. It can also preferentially suggest the types of projectors and audio equipment that the user has used in the past. Furthermore, it can predict and suggest specific dates and times and the number of participants from the user's past event history. This makes it possible to complement the input by referring to the user's past event history.

[0059] The generation unit can generate multiple different scenarios based on detailed event information and provide the user with options. For example, in the case of a wedding, an emotional scenario and a fun scenario can be generated to provide the user with options. In addition, in the case of a concert, a visually beautiful scenario and a scenario that matches the music can be generated to provide the user with options. Furthermore, in the case of a meeting, a formal scenario and a casual scenario can be generated to provide the user with options. In this way, multiple different scenarios can be generated to provide the user with options.

[0060] The control unit can adjust the volume and effects of the video and music in real time according to the progress of the event. For example, in the case of a wedding, the volume of the music can be adjusted in real time according to the progress of the ceremony. In the case of a concert, the music effects can be adjusted in real time according to the progress of the performance. Furthermore, in the case of a conference, the volume and effects of the video and music can be adjusted in real time according to the progress of the presentation. This makes it possible to adjust the volume and effects of the video and music in real time according to the progress of the event.

[0061] The processing flow of the first embodiment will be briefly explained below.

[0062] Step 1: The reception unit inputs detailed information about the event. The detailed information about the event includes, for example, the type of event, location, date and time, number of participants, location layout, and type of projector to be used. The reception unit stores the information input by the user in a database and provides it to the generation unit. Step 2: The generation unit analyzes the information entered by the reception unit and generates the optimal project mapping plan. Using generative AI and technologies such as deep learning and neural networks, the generation unit automatically selects images and music that match the theme and atmosphere of the event and creates a project mapping scenario. For example, in the case of a wedding, it creates a moving image using photos and videos of the bride and groom, and in the case of a fireworks display, it creates a scenario that controls the images and music to change in sync with the fireworks launch. Step 3: The control unit controls the video and music in real time based on the plan generated by the generation unit. The control unit controls the projector and audio equipment, and performs project mapping in accordance with the progress of the event. For example, it can control the video to change and the music to play in accordance with the launch of fireworks.

[0063] (Example 2) A project mapping generation system according to an embodiment of the present invention is a system in which detailed event information is input, and a generation AI generates an optimal project mapping plan and controls video and music in real time. The project mapping generation system allows anyone to easily create project mapping for any event, regardless of its type or scale. This system allows a user to input detailed event information, and a generation AI analyzes the input information to generate an optimal project mapping plan. For example, for a wedding, the generation AI creates an impressive video using photos and videos of the bride and groom. Based on the generated plan, the user sets up a projector and sound equipment and holds the event. The generation AI controls video and music in real time, creating project mapping in accordance with the progress of the event. For example, for a fireworks display, the AI ​​controls the video and music to change in sync with the fireworks launch. This system allows anyone to easily create project mapping and liven up an event. Even without special skills or knowledge, the generation AI automatically generates an optimal plan and controls it in real time, allowing users to enjoy the event with peace of mind. This allows the project mapping generation system to input detailed event information, and the generation AI generates an optimal project mapping plan and controls video and music in real time. For example, users simply need to enter detailed information about the event, and the generation AI will automatically generate the optimal plan and control it in real time, allowing users to enjoy the event with peace of mind.

[0064] A project mapping generation system according to an embodiment includes a reception unit, a generation unit, and a control unit. The reception unit inputs detailed event information. The detailed event information includes, but is not limited to, the type of event, location, date and time, number of participants, location layout, and type of projector to be used. The reception unit, for example, stores the information input by the user in a database and provides the information to the generation unit. The generation unit analyzes the information input by the reception unit and generates an optimal project mapping plan using a generation AI. The generation AI automatically selects images and music that match the theme and atmosphere of the event using technologies such as deep learning and neural networks to create a project mapping scenario. For example, in the case of a wedding, the generation unit creates a moving image using photos and videos of the bride and groom. In the case of a fireworks display, the generation unit can also create a scenario in which the images change and the music plays in sync with the fireworks launch. The control unit controls the images and music in real time based on the plan generated by the generation unit. The control unit controls, for example, a projector and audio equipment to perform project mapping in accordance with the progress of the event. The control unit can control the video to change and the music to play in sync with the launch of fireworks, for example. This allows the project mapping generation system according to the embodiment to input detailed event information, have the generation AI generate an optimal project mapping plan, and control the video and music in real time.

[0065] The reception unit can input information such as the type of event, location, date and time, number of participants, location layout, and type of projector to be used. Examples of event types include, but are not limited to, weddings, concerts, and conferences. Examples of location layouts include, but are not limited to, seating arrangements and stage positions. Examples of projector types include, but are not limited to, DLP projectors and LCD projectors. The reception unit, for example, stores the information input by the user in a database and provides it to the generation unit. This allows detailed event information to be accurately input.

[0066] The generation unit can use generation AI to automatically select images and music that match the event theme and create a project mapping scenario. The generation AI uses technologies such as deep learning and neural networks to automatically select images and music that match the event theme and atmosphere. For example, in the case of a wedding, the generation AI can create a moving image using photos and videos of the bride and groom. In the case of a fireworks display, the generation AI can also create a scenario that controls the images and music to change in sync with the fireworks launch. The generation AI selects images and music based on criteria such as genre, atmosphere, and tempo. This makes it possible to automatically create the optimal project mapping scenario that matches the event theme and atmosphere.

[0067] The control unit can control the video and music in real time based on the generated plan. The control unit, for example, controls a projector and audio equipment and performs project mapping in accordance with the progress of the event. The control unit can, for example, control the video so that it changes and the music plays in accordance with the launch of fireworks. The control unit performs control in real time based on, for example, the timing of control and the technology used. This allows the video and music to be controlled in real time based on the generated plan.

[0068] The control unit can control the video to change and the music to play in sync with the launch of fireworks. The control unit controls the video to change and the music to play in sync with the timing of the launch of fireworks, for example. The control unit performs control based on a synchronization method for the video and the music, for example. This allows the video and the music to be controlled in sync with the launch of fireworks.

[0069] In the case of a wedding, the generation unit can create a video using photos and videos of the bride and groom. For example, in the case of a wedding, the generation unit creates a moving video using photos and videos of the bride and groom. The generation unit creates the video based on, for example, selection criteria and editing methods for the photos and videos to be used. In this way, a moving video can be created for the wedding.

[0070] The reception unit can estimate the user's emotions and adjust the display method of the input interface based on the estimated user emotions. For example, if the user is nervous, the reception unit provides an interface with subdued colors to reduce visual stress. For example, if the user is having fun, the reception unit provides an interface with bright colors to make input work more enjoyable. For example, if the user is tired, the reception unit provides a simple, highly visible interface to make input work easier. This makes it possible to provide an input interface that corresponds to the user'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.

[0071] When inputting detailed event information, the reception unit can complement the input by referring to the user's past event history. For example, the reception unit automatically displays event types and locations previously input by the user as candidates. For example, the reception unit preferentially suggests projector types and audio equipment previously used by the user. For example, the reception unit predicts and suggests specific dates and times and the number of participants from the user's past event history. This allows the input to be complemented by referring to the user's past event history.

[0072] The reception unit can automatically acquire the user's current location information to complement the location information when entering detailed event information. For example, when the user opens the app, the reception unit automatically acquires the user's current location and sets it as the event location. For example, when the user enters the event location, the reception unit suggests the most suitable candidate location taking into account the distance from the user's current location. For example, when the user uses the app while on the move, the reception unit updates the user's current location in real time and reflects it as the event location. This allows the user's current location information to be automatically acquired to complement the location information.

[0073] The reception unit can provide a function for analyzing a user's voice input and converting it into text when entering detailed event information. For example, the reception unit automatically sets the location information when the user simply voice-inputs, "The wedding location is ____." For example, the reception unit automatically sets the number of participants when the user simply voice-inputs, "The number of participants is 50." For example, the reception unit automatically sets the type of projector to be used when the user simply voice-inputs, "We will use ____ projector." This allows the user's voice input to be analyzed and converted into text.

[0074] The reception unit can estimate the user's emotions and adjust the priority of input items based on the estimated user emotions. For example, if the user is nervous, the reception unit prioritizes displaying important input items to simplify the input procedure. For example, if the user is having fun, the reception unit provides detailed input options and suggests a customizable input method. For example, if the user is in a hurry, the reception unit prioritizes voice input to allow the user to quickly enter detailed event information. This makes it possible to provide a priority of input items according to the user'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.

[0075] When inputting detailed information about an event, the reception unit can automatically input related information by referring to the user's social media activity. For example, the reception unit automatically sets the location where the user checked in on social media as the location of the event. For example, the reception unit analyzes the content of the user's social media posts and automatically inputs the type and date and time of the related event. For example, the reception unit automatically inputs detailed information about the related event by referring to the activity of the user's friends on social media. In this way, it is possible to automatically input related information by referring to the user's social media activity.

[0076] The reception unit can customize the input interface by reflecting the user's past feedback when entering detailed event information. The reception unit provides an easy-to-use interface, for example, based on feedback previously entered by the user. The reception unit, for example, preferentially displays specific input items based on the user's past feedback. The reception unit, for example, analyzes the user's past feedback and suggests an optimal input method. This allows the input interface to be customized by reflecting the user's past feedback.

[0077] When entering detailed event information, the reception unit can provide an input method based on the user's device information. For example, if the user is using a smartphone, the reception unit provides an input method that matches the screen size. For example, if the user is using a tablet, the reception unit provides an input method that is optimized for a large screen. For example, if the user is using a desktop, the reception unit provides an input method that prioritizes keyboard input. This makes it possible to provide the optimal input method in consideration of the user's device information.

[0078] The generation unit can estimate the user's emotions and adjust the atmosphere of the generated video and music based on the estimated user emotions. For example, if the user is relaxed, the generation unit generates video and music with a relaxed atmosphere. For example, if the user is excited, the generation unit generates visually stimulating video and music. For example, if the user is moved, the generation unit generates moving video and music. This makes it possible to provide the atmosphere of video and music according to the user'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.

[0079] The generation unit can refer to past event data to generate an optimal project mapping plan that matches the theme and atmosphere of the event. For example, the generation unit references data from past weddings to generate an impressive project mapping plan. For example, the generation unit references data from past fireworks displays to generate a visually beautiful project mapping plan. For example, the generation unit references data from past music events to generate a project mapping plan that matches the music. In this way, it is possible to generate an optimal project mapping plan by referencing past event data.

[0080] The generation unit can generate multiple different scenarios based on detailed event information and provide the user with options. For example, in the case of a wedding, the generation unit can generate an emotional scenario and an enjoyable scenario and provide the user with options. For example, in the case of a fireworks display, the generation unit can generate a visually beautiful scenario and a scenario that matches music and provide the user with options. For example, in the case of a music event, the generation unit can generate scenarios that match music of different genres and provide the user with options. In this way, multiple different scenarios can be generated and the user can be provided with options.

[0081] The generation unit can automatically adjust the length and timing of the video and music to be generated based on detailed information about the event. For example, in the case of a wedding, the generation unit automatically adjusts the length of the video and music to match the progress of the ceremony. For example, in the case of a fireworks display, the generation unit automatically adjusts the timing of the video and music to match the launch of the fireworks. For example, in the case of a music event, the generation unit automatically adjusts the length and timing of the video and music to match the progress of the performance. This makes it possible to automatically adjust the length and timing of the video and music to be generated.

[0082] The generation unit can estimate the user's emotions and adjust the tempo of the generated video and music based on the estimated user's emotions. For example, if the user is relaxed, the generation unit generates video and music with a slow tempo. For example, if the user is excited, the generation unit generates video and music with a fast tempo. For example, if the user is moved, the generation unit generates video and music with an emotional tempo. This makes it possible to provide video and music with tempos that correspond to the user'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.

[0083] The generation unit can generate a project mapping plan that incorporates elements of different cultures and regions to match the theme and atmosphere of the event. For example, in the case of a wedding, the generation unit generates a project mapping plan that incorporates wedding elements of different cultures. For example, in the case of a fireworks display, the generation unit generates a project mapping plan that incorporates elements of fireworks displays of different regions. For example, in the case of a music event, the generation unit generates a project mapping plan that incorporates music elements of different cultures. In this way, it is possible to generate project mapping plans that incorporate elements of different cultures and regions.

[0084] The generation unit can add interactive elements to the generated video and music based on detailed information about the event. For example, in the case of a wedding, the generation unit generates interactive video and music in which guests can participate. For example, in the case of a fireworks display, the generation unit adds interactive elements that allow spectators to affect the video and music in real time. For example, in the case of a music event, the generation unit adds interactive elements that allow spectators to manipulate the video and music in time with the performance. In this way, by adding interactive elements to the generated video and music, it is possible to provide a performance that is more enjoyable for participants.

[0085] The generation unit can incorporate a user's personal message into the generated video and music based on detailed information about the event. For example, in the case of a wedding, the generation unit incorporates a message from the bride and groom into the video and music. For example, in the case of a fireworks display, the generation unit incorporates a message from the organizer into the video and music. For example, in the case of a music event, the generation unit incorporates a message from the artist into the video and music. In this way, by incorporating a user's personal message into the generated video and music, a more personalized performance can be provided.

[0086] The control unit can estimate the user's emotions and adjust the visual and musical presentation in real time based on the estimated user emotions. For example, if the user is relaxed, the control unit adjusts a relaxed presentation in real time. For example, if the user is excited, the control unit adjusts a visually stimulating presentation in real time. For example, if the user is moved, the control unit adjusts an emotional presentation in real time. This makes it possible to provide a real-time presentation according to the user'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 a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to these examples.

[0087] The control unit can automatically adjust the timing of the video and music according to the progress of the event. For example, in the case of a wedding, the control unit automatically adjusts the timing of the video and music to match the progress of the ceremony. For example, in the case of a fireworks display, the control unit automatically adjusts the timing of the video and music to match the launch of the fireworks. For example, in the case of a music event, the control unit automatically adjusts the timing of the video and music to match the progress of the performance. In this way, the timing of the video and music can be automatically adjusted according to the progress of the event.

[0088] The control unit can adjust the volume and effects of the video and music in real time according to the progress of the event. For example, in the case of a wedding, the control unit adjusts the music volume in real time to match the progress of the ceremony. For example, in the case of a fireworks display, the control unit adjusts the video effects in real time to match the launch of the fireworks. For example, in the case of a music event, the control unit adjusts the music volume and effects in real time to match the progress of the performance. This makes it possible to adjust the volume and effects of the video and music in real time according to the progress of the event.

[0089] The control unit can apply an algorithm for smoothly switching between video and music in accordance with the progress of the event. For example, in the case of a wedding, the control unit applies an algorithm for smoothly switching between video and music in accordance with the progress of the ceremony. For example, in the case of a fireworks display, the control unit applies an algorithm for smoothly switching between video and music in accordance with the launch of the fireworks. For example, in the case of a music event, the control unit applies an algorithm for smoothly switching between video and music in accordance with the progress of the performance. This allows for smooth switching between video and music in accordance with the progress of the event.

[0090] The control unit can estimate the user's emotions and change the video and music content in real time based on the estimated user emotions. For example, if the user is relaxed, the control unit changes the video and music to more relaxed content in real time. For example, if the user is excited, the control unit changes the video and music to more visually stimulating content in real time. For example, if the user is moved, the control unit changes the video and music to more moving content in real time. This makes it possible to provide real-time content changes according to the user'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 a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to these examples.

[0091] The control unit can add interactive elements to the video and music production according to the progress of the event. For example, in the case of a wedding, the control unit adds an interactive production in which guests can participate. For example, in the case of a fireworks display, the control unit adds an interactive element that allows spectators to affect the video and music in real time. For example, in the case of a music event, the control unit adds an interactive element that allows spectators to manipulate the video and music in time with the performance. This makes it possible to provide interactive production according to the progress of the event.

[0092] The control unit can reflect user feedback in the video and music production according to the progress of the event. For example, in the case of a wedding, the control unit adjusts the video and music production in real time based on feedback from guests. For example, in the case of a fireworks display, the control unit adjusts the video and music production in real time based on feedback from spectators. For example, in the case of a music event, the control unit adjusts the video and music production in real time based on feedback from spectators. This makes it possible to provide a production that reflects user feedback according to the progress of the event.

[0093] The control unit can link different devices to produce video and music depending on the progress of the event. For example, in the case of a wedding, the control unit links smartphones and tablets to produce video and music. For example, in the case of a fireworks display, the control unit links drones and lights to produce video and music. For example, in the case of a music event, the control unit links projectors and speakers to produce video and music. This makes it possible to provide a performance that links different devices depending on the progress of the event. === Hard Collateral 1-1 === Each of the multiple elements including the above-mentioned reception unit, generation unit, and control unit is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is realized by the reception device 38 of the smart device 14, and a user inputs detailed information about an event. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12, and generates an optimal project mapping plan using a generation AI. For example, the control unit is realized by the control unit 46A of the smart device 14, and controls video and music in real time. === Hard Collateral 1-2 === Each of the multiple elements including the above-mentioned reception unit, generation unit, and control unit is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is realized by the microphone 238 of the smart glasses 214, and the user inputs detailed event information. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12, and generates an optimal project mapping plan using a generation AI. For example, the control unit is realized by the control unit 46A of the smart glasses 214, and controls video and music in real time. === Hard Collateral 1-3 === Each of the multiple elements including the above-mentioned reception unit, generation unit, and control unit is realized, for example, by at least one of the headset type terminal 314 and the data processing device 12. For example, the reception unit is realized by the microphone 238 of the headset type terminal 314, and the user inputs detailed information about the event. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12, and generates an optimal project mapping plan using a generation AI. For example, the control unit is realized by the control unit 46A of the headset type terminal 314, and controls video and music in real time. === Hard Collateral 1-4 === Each of the multiple elements including the above-mentioned reception unit, generation unit, and control unit is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is realized by the microphone 238 of the robot 414, and the user inputs detailed information about the event. For example, the generation unit is realized by the specific processing unit 290 of the data processing device 12, and generates an optimal project mapping plan using a generation AI. For example, the control unit is realized by the control unit 46A of the robot 414, and controls video and music in real time.

[0094] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0095] The reception unit can automatically search for data on related past events based on the event details entered by the user and provide it as reference information. For example, if the user enters details about a wedding, project mapping plans and video samples from past weddings can be displayed. If the user enters details about a concert, video and music samples from past concerts can be provided. Furthermore, if the user enters details about a meeting, sample layouts and audio settings from past meetings can be displayed. This allows the user to create the optimal project mapping plan while referring to past success stories.

[0096] The generation unit can generate multiple project mapping plans with different themes and styles based on the event details entered by the user, and provide the user with options. For example, for a wedding, plans with a romantic theme, a classical theme, and a modern theme can be generated to provide the user with options. For a concert, plans tailored to different music genres such as rock, pop, and classical can be generated. For a conference, plans with a formal style, a casual style, and an interactive style can be generated to provide the user with options. This allows the user to select the optimal plan that matches the theme and style of the event.

[0097] The control unit can add interactive elements to video and music productions depending on the progress of the event. For example, at a wedding, an interactive production can be added that allows guests to affect the video and music in real time using their smartphones. At a concert, an interactive production can be added that allows audience members to change the color and pattern of lights using their smartphones. Furthermore, at a conference, an interactive production can be added that allows participants to control the content of the presentation using tablets. This allows participants to more actively participate in and enjoy the event.

[0098] The generation unit can estimate the user's emotions and adjust the atmosphere of the generated images and music based on the estimated user's emotions. For example, if the user is relaxed, the generation unit can generate images and music with a relaxed atmosphere. If the user is excited, the generation unit can generate visually stimulating images and music. If the user is moved, the generation unit can generate moving images and music. This makes it possible to provide optimal images and music according to the user's emotions.

[0099] The reception unit can estimate the user's emotions and adjust the display method of the input interface based on the estimated user's emotions. For example, if the user is nervous, the reception unit can provide an interface with subdued colors to reduce visual stress. If the user is having fun, the reception unit can provide an interface with bright colors to make input work more enjoyable. Furthermore, if the user is tired, the reception unit can provide a simple, highly visible interface to make input work easier. In this way, an input interface can be provided that corresponds to the user's emotions.

[0100] The generation unit can incorporate a user's personal message into the generated video and music based on detailed information about the event. For example, in the case of a wedding, a message from the bride and groom can be incorporated into the video and music. In the case of a concert, a message from the artist can be incorporated into the video and music. Furthermore, in the case of a conference, a message from the organizer can be incorporated into the video and music. In this way, by incorporating a user's personal message into the generated video and music, a more personalized performance can be provided.

[0101] The control unit can estimate the user's emotions and adjust the visual and musical effects in real time based on the estimated user's emotions. For example, if the user is relaxed, the control unit can adjust a relaxed effect in real time. If the user is excited, the control unit can adjust a visually stimulating effect in real time. Furthermore, if the user is moved, the control unit can adjust an emotional effect in real time. This makes it possible to provide real-time effects according to the user's emotions.

[0102] When inputting detailed event information, the reception unit can complement the input by referring to the user's past event history. For example, the reception unit can automatically display the event types and locations previously input by the user as candidates. It can also preferentially suggest the types of projectors and audio equipment that the user has used in the past. Furthermore, it can predict and suggest specific dates and times and the number of participants from the user's past event history. This makes it possible to complement the input by referring to the user's past event history.

[0103] The generation unit can generate multiple different scenarios based on detailed event information and provide the user with options. For example, in the case of a wedding, an emotional scenario and a fun scenario can be generated to provide the user with options. In addition, in the case of a concert, a visually beautiful scenario and a scenario that matches the music can be generated to provide the user with options. Furthermore, in the case of a meeting, a formal scenario and a casual scenario can be generated to provide the user with options. In this way, multiple different scenarios can be generated to provide the user with options.

[0104] The control unit can adjust the volume and effects of the video and music in real time according to the progress of the event. For example, in the case of a wedding, the volume of the music can be adjusted in real time according to the progress of the ceremony. In the case of a concert, the music effects can be adjusted in real time according to the progress of the performance. Furthermore, in the case of a conference, the volume and effects of the video and music can be adjusted in real time according to the progress of the presentation. This makes it possible to adjust the volume and effects of the video and music in real time according to the progress of the event.

[0105] The processing flow of the second embodiment will be briefly explained below.

[0106] Step 1: The reception unit inputs detailed information about the event. The detailed information about the event includes, for example, the type of event, location, date and time, number of participants, location layout, and type of projector to be used. The reception unit stores the information input by the user in a database and provides it to the generation unit. Step 2: The generation unit analyzes the information entered by the reception unit and generates the optimal project mapping plan. Using generative AI and technologies such as deep learning and neural networks, the generation unit automatically selects images and music that match the theme and atmosphere of the event and creates a project mapping scenario. For example, in the case of a wedding, it creates a moving image using photos and videos of the bride and groom, and in the case of a fireworks display, it creates a scenario that controls the images and music to change in sync with the fireworks launch. Step 3: The control unit controls the video and music in real time based on the plan generated by the generation unit. The control unit controls the projector and audio equipment, and performs project mapping in accordance with the progress of the event. For example, it can control the video to change and the music to play in accordance with the launch of fireworks.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0111] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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).

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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.

[0124] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0125] 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.

[0126] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0127] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0128] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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).

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0141] 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.

[0142] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0143] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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).

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0158] 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.

[0159] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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).

[0164] 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 "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[0165] 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."

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] [Explanation of symbols]

[0179] 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 section for inputting detailed event information; a generation unit that analyzes the information input by the reception unit and generates a project mapping plan; a control unit that controls video and music in real time based on the plan generated by the generation unit. A system characterized by:

2. The reception unit Enter information about the type of event, location, date and time, number of participants, location layout, and type of projector you will be using.

2. The system of claim 1.

3. The generation unit Generative AI automatically selects images and music that match the event theme and creates a project mapping scenario.

2. The system of claim 1.

4. The control unit Control video and music in real time based on the generated plan 2. The system of claim 1.

5. The control unit The images change and music plays in sync with the fireworks.

2. The system of claim 1.

6. The generation unit For weddings, create a film using photos and videos of the bride and groom.

2. The system of claim 1.

7. The reception unit The system estimates the user's emotions and adjusts the display method of the input interface based on the estimated user emotions.

2. The system of claim 1.

8. The reception unit When entering event details, the user's past event history is referenced to complete the input.

2. The system of claim 1.

9. The reception unit Automatically captures your current location to complete location information when entering event details 2. The system of claim 1.

10. The reception unit Provides a function to analyze and convert user voice input into text when entering event details.

2. The system of claim 1.

Images