System

Abstract

To provide a system according to an embodiment which can automatically and efficiently generate a video of a wedding.SOLUTION: The system according to an embodiment includes a reception unit, an analysis unit, and a generation unit. The reception unit inputs data of a bride and a groom. The analysis unit analyzes the data input by the reception unit, and determines the configuration of the video. The generation unit generates the movie on the basis of the configuration determined by the analysis 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 posed the problem that manually creating wedding videos requires a lot of time and effort, making it difficult to create them efficiently.

[0005] The system according to the embodiment aims to efficiently and automatically generate wedding movies. [Means for solving the problem]

[0006] The system according to the embodiment includes a reception unit, an analysis unit, and a generation unit. The reception unit inputs data of the bride and groom. The analysis unit analyzes the data input by the reception unit and determines the structure of the movie. The generation unit generates the movie based on the structure determined by the analysis unit. [Effects of the Invention]

[0007] The system according to the embodiment can automatically generate wedding movies efficiently. [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 movie generation system according to an embodiment of the present invention automatically generates opening and profile introduction videos to be played at weddings. This movie generation system automatically generates movies using AI by simply registering specific data about the bride and groom (such as their hometowns and hobbies), photos, and videos. It is also possible to specify detailed conditions. For example, first, basic information about the bride and groom (such as their names, hometowns, and hobbies) is entered. Next, photos and videos to be used at the wedding are uploaded. This information is then input into the AI. The AI ​​analyzes the input information and determines the optimal movie structure. For example, a unique movie can be created by incorporating scenery related to the bride and groom's hometown or scenes related to their hobbies. The AI ​​can also adjust the order and timing of the photos and videos to create a movie with a natural flow. Furthermore, users can specify detailed conditions. For example, customization is possible according to user requests, such as emphasizing specific scenes or using specific music. The generated movie is provided to the user and can be used at the wedding. This system allows for the creation of high-quality movies without hassle, creating a memorable wedding for the bride and groom and their guests. This allows the movie generation system to automatically generate movies based on the bride and groom's data.

[0029] A movie generation system according to an embodiment includes a reception unit, an analysis unit, and a generation unit. The reception unit inputs data of the bride and groom. The data includes, but is not limited to, names, photos, video clips, and messages. The reception unit provides an interface for inputting basic information, such as names, hometowns, and hobbies. The reception unit also includes a function for uploading photos and videos to be used at the wedding. For example, the reception unit may provide a drag-and-drop function so that users can easily upload photos and videos. The analysis unit analyzes the data input by the reception unit and determines the structure of the movie. For example, the analysis unit classifies the data using AI and considers the optimal structure of the movie. For example, the analysis unit creates a unique movie by incorporating scenery related to the bride and groom's hometown or scenes related to their hobbies. The analysis unit also adjusts the order and timing of the photos and videos to generate a movie with a natural flow. The generation unit generates the movie based on the structure determined by the analysis unit. For example, the generation unit automatically generates the movie using AI. For example, the generation unit may combine photos and videos, adjust the order and timing of scenes, and generate a movie with a natural flow. This allows the movie generation system according to the embodiment to automatically generate a movie based on data on the bride and groom.

[0030] The reception unit inputs data of the bride and groom. The bride and groom data may include, but is not limited to, names, photos, video clips, and messages. The reception unit provides an interface for inputting basic information, such as names, hometowns, and hobbies. The reception unit also has a function for uploading photos and videos to be used at the wedding. For example, the reception unit provides a drag-and-drop function to enable users to easily upload photos and videos. Furthermore, the reception unit is connected to a database for centrally managing data entered by users, and the entered information is instantly saved and made accessible to the analysis unit and generation unit. The reception unit's interface is designed to be user-friendly and intuitive. For example, the input form has an auto-complete function that displays suggestions when the user enters their name or hometown. Furthermore, when uploading photos and videos, a preview function allows the user to check the contents of the uploaded files. The reception unit also has a function for checking the consistency of the data entered by the user, displaying a warning if, for example, there is a typo in the name or the photo has low resolution. This allows the reception unit to enable users to input data about the bride and groom easily and accurately, improving the data quality of the entire system.

[0031] The analysis unit analyzes the data entered by the reception unit and determines the movie's composition. For example, the analysis unit uses AI to classify the data and determine the optimal movie composition. Specifically, the AI ​​analyzes basic information such as the bride and groom's names, hometowns, and hobbies, and then determines the movie's theme and scenes based on that information. For example, incorporating scenery related to their hometowns or scenes related to their hobbies creates a unique movie. The analysis unit also adjusts the order and timing of photos and videos to create a movie with a natural flow. The AI ​​uses image recognition technology to analyze the content of photos and videos and identify important scenes and moving moments. Furthermore, the AI ​​uses voice recognition technology to analyze the audio in video clips and extract moving messages and speeches. This allows the analysis unit to make the most of the data entered by the user and generate a moving and unique movie. Furthermore, the analysis unit continues to learn the optimal movie composition using past data and statistical information. For example, based on the evaluation data of previously generated movies, it analyzes which scenes and compositions received high ratings and reflects this information in the generation of new movies. This allows the analysis unit to always generate movies that reflect the latest trends and user preferences.

[0032] The generation unit generates a movie based on the structure determined by the analysis unit. The generation unit automatically generates the movie using, for example, AI. Specifically, the generation unit combines photos and videos and adjusts the order and timing of scenes to create a movie with a natural flow. AI uses image processing technology to adjust the color tone and brightness of the photos and videos to create a sense of overall unity. AI also uses audio processing technology to adjust the audio of video clips and optimize volume and sound quality. Furthermore, the generation unit automatically selects background music and sound effects and inserts them into the movie. For example, adding emotional background music to moving scenes and cheerful background music to happy scenes enhances the overall atmosphere of the movie. The generation unit can also automatically apply movie designs and effects based on themes and styles specified by the user. For example, it generates movies based on the user's preferences, such as a classic style or a modern style. This allows the generation unit to automatically generate high-quality movies that meet the user's expectations. Furthermore, the generation unit also has a function that allows the user to preview the generated movie, allowing them to check the content of the movie and request corrections if necessary. This allows the generator to provide an optimal movie that reflects the user's feedback.

[0033] The movie generation system may include an adjustment unit that adjusts the order or timing of photos or videos. The adjustment unit, for example, adjusts the order or timing of photos or videos. For example, the adjustment unit can determine the order of photos or videos based on a timeline. The adjustment unit can also determine the order based on the importance of events. For example, the adjustment unit prioritizes important scenes of a wedding to generate a movie with a natural flow. The adjustment unit can also adjust the start time or length of a scene. For example, the adjustment unit optimizes the flow of the movie by adjusting the start time or length of a scene. In this way, the adjustment unit can generate a movie with a more natural flow by adjusting the order and timing of photos or videos. Some or all of the above-described processing in the adjustment unit may be performed using, for example, AI, or may be performed without using AI. For example, the adjustment unit can determine the optimal order and timing using an AI model for determining the order and timing of photos and videos.

[0034] The movie generation system may include a customization unit that performs customization according to a user's request. The customization unit customizes a movie according to, for example, a user's request. For example, the customization unit may change colors, add text, select music, and the like. For example, the customization unit may change the color of the movie based on a color specified by the user. The customization unit may also add text specified by the user to the movie. The customization unit may also add music specified by the user to the movie. This allows the customization unit to customize the movie according to the user's request. Some or all of the above-described processing in the customization unit may be performed using, for example, AI, or may be performed without using AI. For example, the customization unit may determine an optimal customization method using an AI model for customization based on the user's request.

[0035] The movie generation system may include a providing unit that provides the generated movie to a user. The providing unit, for example, provides the generated movie to a user. For example, the providing unit may distribute the generated movie online, create a DVD, provide a download link, or the like. For example, the providing unit may distribute the generated movie online so that the user can access it at any time. The providing unit may also burn the generated movie onto a DVD and provide it. Furthermore, the providing unit may provide a download link for the generated movie so that the user can download the movie. In this way, the providing unit can provide the generated movie to the user. Some or all of the above-described processing in the providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the providing unit may determine the optimal distribution method using an AI model for providing the generated movie.

[0036] The reception unit can analyze the bride and groom's past event data and suggest the optimal data input method. The reception unit can, for example, analyze the bride and groom's past event data and suggest the optimal data input method. For example, the reception unit can suggest the optimal input method based on data on events the bride and groom have previously attended. The reception unit can also prioritize and suggest frequently used input methods (voice, text, etc.) based on the bride and groom's past event data. Furthermore, the reception unit can analyze the bride and groom's past event data and predict and suggest the input method to be used during a specific time period. This allows the reception unit to suggest the optimal data input method based on the past event data, enabling efficient data entry. Some or all of the above-described processing in the reception unit may be performed using, for example, AI, or may be performed without AI. For example, the reception unit can suggest the optimal data input method using an AI model for analyzing past event data.

[0037] The reception unit can check the consistency of the input data when data is entered and perform automatic completion as necessary. For example, the reception unit can check the consistency of the input data when data is entered and perform automatic completion as necessary. For example, the reception unit can check the consistency of the data entered by the bride and groom and automatically complete missing information. Furthermore, if there is an inconsistency in the data entered by the bride and groom, the reception unit can automatically suggest corrections using AI. Furthermore, the reception unit can automatically complete related information based on the data entered by the bride and groom, simplifying the input work. This allows the reception unit to maintain the consistency of data entry and perform automatic completion as necessary, thereby improving the accuracy of data entry. Some or all of the above-described processing in the reception unit may be performed using AI, for example, or may be performed without AI. For example, the reception unit can use an AI model to check the consistency of the input data and perform automatic completion as necessary.

[0038] The reception unit can prioritize inputting highly relevant data by taking into account the geographical location information of the bride and groom when inputting data. For example, the reception unit prioritizes inputting highly relevant data by taking into account the geographical location information of the bride and groom when inputting data. For example, the reception unit prioritizes inputting highly relevant data based on the current locations of the bride and groom. The reception unit can also prioritize inputting highly relevant data based on the hometowns of the bride and groom. Furthermore, the reception unit can prioritize inputting highly relevant data based on the location of the bride and groom's wedding ceremony. This allows the reception unit to prioritize inputting highly relevant data by taking into account the geographical location information, thereby enabling more appropriate data input. Some or all of the above-described processing by the reception unit may be performed using, for example, AI, or may be performed without using AI. For example, the reception unit can determine the optimal data input method using an AI model for preferentially inputting highly relevant data by taking into account the geographical location information.

[0039] The reception unit can analyze the social media activities of the bride and groom when data is entered and automatically acquire related data. For example, the reception unit can automatically acquire related photos and videos from the bride and groom's social media accounts when data is entered and automatically acquire related data. For example, the reception unit can automatically acquire related photos and videos from the bride and groom's social media accounts. The reception unit can also analyze the content of the bride and groom's social media posts and automatically acquire related data. Furthermore, the reception unit can automatically acquire related data based on the bride and groom's social media friend lists. By analyzing social media activities and automatically acquiring related data, the reception unit can thereby reduce the effort of data entry. Some or all of the above-described processing in the reception unit may be performed using, for example, AI, or may be performed without using AI. For example, the reception unit can automatically acquire related data using an AI model for analyzing social media activities.

[0040] The analysis unit can propose an optimal structure by referring to past wedding movie data during analysis. For example, the analysis unit can propose an optimal structure by referring to past wedding movie data during analysis. For example, the analysis unit can propose an optimal structure based on past wedding movie data. The analysis unit can also extract and propose popular elements from past wedding movie data. Furthermore, the analysis unit can analyze past wedding movie data and propose a structure based on trends. This allows the analysis unit to propose an optimal structure by referring to past wedding movie data. Some or all of the above-described processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can propose an optimal structure using an AI model for analyzing past wedding movie data.

[0041] During analysis, the analysis unit can emphasize specific scenes based on the hobbies and interests of the bride and groom. For example, during analysis, the analysis unit can emphasize specific scenes based on the hobbies and interests of the bride and groom. For example, the analysis unit can emphasize scenes related to the hobbies of the bride and groom. The analysis unit can also emphasize specific scenes based on the interests of the bride and groom. Furthermore, the analysis unit can add related scenes based on the hobbies and interests of the bride and groom. This allows the analysis unit to generate a more unique movie by emphasizing specific scenes based on the hobbies and interests of the bride and groom. Some or all of the above-described processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can emphasize specific scenes using an AI model for analyzing the hobbies and interests of the bride and groom.

[0042] The analysis unit can select movie scenes taking into account the geographical background of the bride and groom during analysis. For example, the analysis unit selects movie scenes taking into account the geographical background of the bride and groom during analysis. For example, the analysis unit selects scenes related to the hometown of the bride and groom. The analysis unit can also select scenes related to the location of the bride and groom's wedding. Furthermore, the analysis unit can select scenes related to the current location of the bride and groom. In this way, the analysis unit can incorporate more relevant scenes by selecting movie scenes taking into account the geographical background. Some or all of the above-described processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can select optimal scenes using an AI model for selecting movie scenes taking into account the geographical background.

[0043] The analysis unit can analyze the social media activities of the bride and groom during analysis and incorporate relevant scenes into the movie. For example, the analysis unit can analyze the social media activities of the bride and groom during analysis and incorporate relevant scenes into the movie. For example, the analysis unit can analyze the social media posts of the bride and groom and incorporate relevant scenes into the movie. The analysis unit can also analyze the social media photos and videos of the bride and groom and incorporate relevant scenes into the movie. Furthermore, the analysis unit can incorporate relevant scenes into the movie based on the bride and groom's social media friend list. This allows the analysis unit to analyze social media activities and incorporate relevant scenes into the movie, thereby generating a more unique movie. Some or all of the above-described processing by the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can incorporate relevant scenes into the movie using an AI model for analyzing social media activities.

[0044] The generation unit can apply an optimal generation algorithm by referring to past generation data at the time of generation. For example, the generation unit can apply an optimal generation algorithm by referring to past generation data at the time of generation. For example, the generation unit can apply an optimal generation algorithm based on past generation data. The generation unit can also extract and apply a popular generation algorithm from past generation data. Furthermore, the generation unit can analyze past generation data and apply a generation algorithm based on trends. In this way, the generation unit can apply an optimal generation algorithm by referring to past generation data. Some or all of the above-described processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can apply an optimal generation algorithm using an AI model for analyzing past generation data.

[0045] The generation unit can generate a movie customized based on the specific requests of the bride and groom at the time of generation. For example, the generation unit can generate a movie customized based on the specific requests of the bride and groom at the time of generation. For example, the generation unit can generate a movie that emphasizes specific scenes based on the requests of the bride and groom. The generation unit can also generate a movie using specific music based on the requests of the bride and groom. Furthermore, the generation unit can generate a movie with specific effects added based on the requests of the bride and groom. In this way, the generation unit can provide a more unique movie by generating a movie customized based on the requests of the bride and groom. Some or all of the above-described processing in the generation unit can be performed using AI, for example, or without AI. For example, the generation unit can generate a customized movie using an AI model for analyzing the requests of the bride and groom.

[0046] The generation unit can select movie scenes taking into account the geographical background of the bride and groom when generating the video. For example, the generation unit selects movie scenes taking into account the geographical background of the bride and groom when generating the video. For example, the generation unit selects scenes related to the hometown of the bride and groom. The generation unit can also select scenes related to the location of the bride and groom's wedding. Furthermore, the generation unit can select scenes related to the current location of the bride and groom. In this way, the generation unit can incorporate more relevant scenes by selecting movie scenes taking into account the geographical background. Some or all of the above-described processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can select optimal scenes using an AI model for selecting movie scenes taking into account the geographical background.

[0047] The generation unit can analyze the social media activities of the bride and groom during generation and incorporate related scenes into the movie. For example, the generation unit can analyze the social media activities of the bride and groom during generation and incorporate related scenes into the movie. For example, the generation unit can analyze the social media posts of the bride and groom and incorporate related scenes into the movie. The generation unit can also analyze social media photos and videos of the bride and groom and incorporate related scenes into the movie. Furthermore, the generation unit can incorporate related scenes into the movie based on the bride and groom's social media friend list. In this way, the generation unit can generate a more unique movie by analyzing social media activities and incorporating related scenes into the movie. Some or all of the above-described processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can incorporate related scenes into the movie using an AI model for analyzing social media activities.

[0048] The adjustment unit can apply an optimal adjustment method by referring to past adjustment data during adjustment. For example, the adjustment unit can apply an optimal adjustment method by referring to past adjustment data during adjustment. For example, the adjustment unit can adjust an optimal order or timing based on past adjustment data. The adjustment unit can also extract and apply a popular adjustment method from past adjustment data. Furthermore, the adjustment unit can analyze past adjustment data and apply an adjustment method based on trends. In this way, the adjustment unit can adjust an optimal order or timing by referring to past adjustment data. Some or all of the above-described processing in the adjustment unit may be performed using, for example, AI, or may be performed without using AI. For example, the adjustment unit can apply an optimal adjustment method using an AI model for analyzing past adjustment data.

[0049] During adjustment, the adjustment unit can adjust the order and timing of photos and videos taking into account the geographical background of the bride and groom. For example, during adjustment, the adjustment unit can adjust the order and timing of photos and videos taking into account the geographical background of the bride and groom. For example, the adjustment unit can prioritize arranging photos and videos related to the bride and groom's hometown. The adjustment unit can also prioritize arranging photos and videos related to the bride and groom's wedding location. Furthermore, the adjustment unit can prioritize arranging photos and videos related to the bride and groom's current location. This allows the adjustment unit to incorporate more relevant scenes by adjusting the order and timing of photos and videos taking into account the geographical background. Some or all of the above-described processing by the adjustment unit may be performed using, for example, AI, or may be performed without using AI. For example, the adjustment unit can determine the optimal order and timing using an AI model for adjusting the order and timing of photos and videos taking into account the geographical background.

[0050] The customization unit can suggest an optimal customization method by referring to past customization data during customization. For example, the customization unit can suggest an optimal customization method by referring to past customization data during customization. For example, the customization unit can suggest an optimal customization method based on past customization data. The customization unit can also extract and suggest popular customization methods from past customization data. Furthermore, the customization unit can analyze past customization data and suggest a customization method based on trends. In this way, the customization unit can suggest an optimal customization method by referring to past customization data. Some or all of the above-described processing in the customization unit may be performed using, for example, AI, or may be performed without using AI. For example, the customization unit can suggest an optimal customization method using an AI model for analyzing past customization data.

[0051] The customization unit can determine the customization content taking into account the geographical background of the bride and groom when customizing. For example, the customization unit can perform customization related to the bride and groom's hometown. The customization unit can also perform customization related to the location of the bride and groom's wedding. Furthermore, the customization unit can perform customization related to the bride and groom's current location. In this way, the customization unit can incorporate more relevant scenes by determining the customization content taking into account the geographical background. Some or all of the above-described processing in the customization unit can be performed using, for example, AI, or can be performed without using AI. For example, the customization unit can determine the optimal customization method using an AI model for determining the customization content taking into account the geographical background.

[0052] The providing unit can propose an optimal provision method by referring to past provision data at the time of provision. For example, the providing unit can propose an optimal provision method by referring to past provision data at the time of provision. For example, the providing unit proposes an optimal provision method based on past provision data. The providing unit can also extract and propose popular provision methods from past provision data. Furthermore, the providing unit can analyze past provision data and propose a provision method based on trends. In this way, the providing unit can propose an optimal provision method by referring to past provision data. Some or all of the above-described processing in the providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the providing unit can propose an optimal provision method using an AI model for analyzing past provision data.

[0053] The providing unit can select the optimal providing method by taking into consideration the geographical background of the bride and groom when providing the video. For example, the providing unit can select the optimal providing method by taking into consideration the geographical background of the bride and groom when providing the video. For example, the providing unit can prioritize providing movies related to the hometown of the bride and groom. The providing unit can also prioritize providing movies related to the location of the bride and groom's wedding. Furthermore, the providing unit can prioritize providing movies related to the current location of the bride and groom. In this way, the providing unit can incorporate more relevant scenes by selecting the optimal providing method by taking into consideration the geographical background. Some or all of the above-described processing by the providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the providing unit can determine the optimal providing method by using an AI model for selecting the optimal providing method by taking into consideration the geographical background.

[0054] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0055] The movie generation system can also analyze the bride and groom's past travel data and incorporate photos and videos from their travel destinations into the movie. For example, the analysis unit can add scenes of the bride and groom's travel destinations and tourist attractions to the movie based on data on the destinations they have visited in the past. The analysis unit can also prioritize photos and videos taken at the travel destination to highlight travel memories. Furthermore, the analysis unit can generate a more unique movie by incorporating scenes related to the culture and customs of the travel destination. This allows the movie generation system to provide a movie that reflects the bride and groom's travel memories.

[0056] The movie generation system can further collect messages from the bride and groom's family and friends and incorporate them into the movie. For example, the reception unit provides an interface for uploading video messages from family and friends. The analysis unit can analyze the collected messages and place them in appropriate positions in the movie. Furthermore, the generation unit can emphasize touching or humorous scenes based on the content of the messages. This allows the movie generation system to provide a more touching movie that includes warm messages from family and friends.

[0057] The movie generation system can also incorporate scenes from the bride and groom's favorite movies and TV shows. For example, the analysis unit can add related scenes to the movie based on data on the bride and groom's favorite movies and TV shows. The generation unit can also recreate famous scenes from movies and TV shows and combine them with photos and videos of the bride and groom. Furthermore, the customization unit can add music and effects that match the theme of the movie or TV show. This allows the movie generation system to provide a more personalized movie that matches the hobbies and preferences of the bride and groom.

[0058] The movie generation system can also incorporate live video of the bride and groom on their wedding day in real time. For example, the providing unit provides an interface for streaming live video of the wedding day. The generating unit can also analyze the live video in real time and incorporate it into the movie. Furthermore, the adjusting unit can adjust the timing and order of the live video to generate a movie with a natural flow. This allows the movie generation system to provide a more realistic movie that incorporates moving moments from the wedding day in real time.

[0059] The processing flow of the first embodiment will be briefly explained below.

[0060] Step 1: The reception unit inputs the bride and groom's data. The bride and groom's data includes names, photos, video clips, messages, etc. The reception unit provides an interface for inputting basic information such as names, hometowns, and hobbies, and has a function for uploading photos and videos to be used at the wedding. For example, it provides a drag-and-drop function so that users can easily upload photos and videos. Step 2: The analysis unit analyzes the data entered by the reception unit and determines the composition of the movie. The analysis unit uses AI to classify the data and consider the optimal composition of the movie. For example, by incorporating scenery related to the person's hometown or scenes related to their hobbies, a unique movie can be created. The order and timing of the photos and videos can also be adjusted to create a movie with a natural flow. Step 3: The generator generates a movie based on the structure determined by the analyzer. The generator uses AI to automatically generate the movie. For example, it combines photos and videos, adjusts the order and timing of scenes, and creates a movie with a natural flow.

[0061] (Example 2) A movie generation system according to an embodiment of the present invention automatically generates opening and profile introduction videos to be played at weddings. This movie generation system automatically generates movies using AI by simply registering specific data about the bride and groom (such as their hometowns and hobbies), photos, and videos. It is also possible to specify detailed conditions. For example, first, basic information about the bride and groom (such as their names, hometowns, and hobbies) is entered. Next, photos and videos to be used at the wedding are uploaded. This information is then input into the AI. The AI ​​analyzes the input information and determines the optimal movie structure. For example, a unique movie can be created by incorporating scenery related to the bride and groom's hometown or scenes related to their hobbies. The AI ​​can also adjust the order and timing of the photos and videos to create a movie with a natural flow. Furthermore, users can specify detailed conditions. For example, customization is possible according to user requests, such as emphasizing specific scenes or using specific music. The generated movie is provided to the user and can be used at the wedding. This system allows for the creation of high-quality movies without hassle, creating a memorable wedding for the bride and groom and their guests. This allows the movie generation system to automatically generate movies based on the bride and groom's data.

[0062] A movie generation system according to an embodiment includes a reception unit, an analysis unit, and a generation unit. The reception unit inputs data of the bride and groom. The data includes, but is not limited to, names, photos, video clips, and messages. The reception unit provides an interface for inputting basic information, such as names, hometowns, and hobbies. The reception unit also includes a function for uploading photos and videos to be used at the wedding. For example, the reception unit may provide a drag-and-drop function so that users can easily upload photos and videos. The analysis unit analyzes the data input by the reception unit and determines the structure of the movie. For example, the analysis unit classifies the data using AI and considers the optimal structure of the movie. For example, the analysis unit creates a unique movie by incorporating scenery related to the bride and groom's hometown or scenes related to their hobbies. The analysis unit also adjusts the order and timing of the photos and videos to generate a movie with a natural flow. The generation unit generates the movie based on the structure determined by the analysis unit. For example, the generation unit automatically generates the movie using AI. For example, the generation unit may combine photos and videos, adjust the order and timing of scenes, and generate a movie with a natural flow. This allows the movie generation system according to the embodiment to automatically generate a movie based on data on the bride and groom.

[0063] The reception unit inputs data of the bride and groom. The bride and groom data may include, but is not limited to, names, photos, video clips, and messages. The reception unit provides an interface for inputting basic information, such as names, hometowns, and hobbies. The reception unit also has a function for uploading photos and videos to be used at the wedding. For example, the reception unit provides a drag-and-drop function to enable users to easily upload photos and videos. Furthermore, the reception unit is connected to a database for centrally managing data entered by users, and the entered information is instantly saved and made accessible to the analysis unit and generation unit. The reception unit's interface is designed to be user-friendly and intuitive. For example, the input form has an auto-complete function that displays suggestions when the user enters their name or hometown. Furthermore, when uploading photos and videos, a preview function allows the user to check the contents of the uploaded files. The reception unit also has a function for checking the consistency of the data entered by the user, displaying a warning if, for example, there is a typo in the name or the photo has low resolution. This allows the reception unit to enable users to input data about the bride and groom easily and accurately, improving the data quality of the entire system.

[0064] The analysis unit analyzes the data entered by the reception unit and determines the movie's composition. For example, the analysis unit uses AI to classify the data and determine the optimal movie composition. Specifically, the AI ​​analyzes basic information such as the bride and groom's names, hometowns, and hobbies, and then determines the movie's theme and scenes based on that information. For example, incorporating scenery related to their hometowns or scenes related to their hobbies creates a unique movie. The analysis unit also adjusts the order and timing of photos and videos to create a movie with a natural flow. The AI ​​uses image recognition technology to analyze the content of photos and videos and identify important scenes and moving moments. Furthermore, the AI ​​uses voice recognition technology to analyze the audio in video clips and extract moving messages and speeches. This allows the analysis unit to make the most of the data entered by the user and generate a moving and unique movie. Furthermore, the analysis unit continues to learn the optimal movie composition using past data and statistical information. For example, based on the evaluation data of previously generated movies, it analyzes which scenes and compositions received high ratings and reflects this information in the generation of new movies. This allows the analysis unit to always generate movies that reflect the latest trends and user preferences.

[0065] The generation unit generates a movie based on the structure determined by the analysis unit. The generation unit automatically generates the movie using, for example, AI. Specifically, the generation unit combines photos and videos and adjusts the order and timing of scenes to create a movie with a natural flow. AI uses image processing technology to adjust the color tone and brightness of the photos and videos to create a sense of overall unity. AI also uses audio processing technology to adjust the audio of video clips and optimize volume and sound quality. Furthermore, the generation unit automatically selects background music and sound effects and inserts them into the movie. For example, adding emotional background music to moving scenes and cheerful background music to happy scenes enhances the overall atmosphere of the movie. The generation unit can also automatically apply movie designs and effects based on themes and styles specified by the user. For example, it generates movies based on the user's preferences, such as a classic style or a modern style. This allows the generation unit to automatically generate high-quality movies that meet the user's expectations. Furthermore, the generation unit also has a function that allows the user to preview the generated movie, allowing them to check the content of the movie and request corrections if necessary. This allows the generator to provide an optimal movie that reflects the user's feedback.

[0066] The movie generation system may include an adjustment unit that adjusts the order or timing of photos or videos. The adjustment unit, for example, adjusts the order or timing of photos or videos. For example, the adjustment unit can determine the order of photos or videos based on a timeline. The adjustment unit can also determine the order based on the importance of events. For example, the adjustment unit prioritizes important scenes of a wedding to generate a movie with a natural flow. The adjustment unit can also adjust the start time or length of a scene. For example, the adjustment unit optimizes the flow of the movie by adjusting the start time or length of a scene. In this way, the adjustment unit can generate a movie with a more natural flow by adjusting the order and timing of photos or videos. Some or all of the above-described processing in the adjustment unit may be performed using, for example, AI, or may be performed without using AI. For example, the adjustment unit can determine the optimal order and timing using an AI model for determining the order and timing of photos and videos.

[0067] The movie generation system may include a customization unit that performs customization according to a user's request. The customization unit customizes a movie according to, for example, a user's request. For example, the customization unit may change colors, add text, select music, and the like. For example, the customization unit may change the color of the movie based on a color specified by the user. The customization unit may also add text specified by the user to the movie. The customization unit may also add music specified by the user to the movie. This allows the customization unit to customize the movie according to the user's request. Some or all of the above-described processing in the customization unit may be performed using, for example, AI, or may be performed without using AI. For example, the customization unit may determine an optimal customization method using an AI model for customization based on the user's request.

[0068] The movie generation system may include a providing unit that provides the generated movie to a user. The providing unit, for example, provides the generated movie to a user. For example, the providing unit may distribute the generated movie online, create a DVD, provide a download link, or the like. For example, the providing unit may distribute the generated movie online so that the user can access it at any time. The providing unit may also burn the generated movie onto a DVD and provide it. Furthermore, the providing unit may provide a download link for the generated movie so that the user can download the movie. In this way, the providing unit can provide the generated movie to the user. Some or all of the above-described processing in the providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the providing unit may determine the optimal distribution method using an AI model for providing the generated movie.

[0069] The reception unit can estimate the emotions of the bride and groom and adjust the data input interface based on the estimated emotions. For example, the reception unit can estimate the emotions of the bride and groom and adjust the data input interface based on the estimated emotions. For example, if the bride and groom are nervous, the reception unit can provide a simple and intuitive interface and minimize input steps. Furthermore, if the bride and groom are relaxed, the reception unit can provide detailed input options and suggest customizable input methods. Furthermore, if the bride and groom are in a hurry, the reception unit can prioritize voice input to allow quick data entry. This allows the reception unit to adjust the data input interface according to the emotions of the bride and groom, thereby providing a more user-friendly system. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the reception unit can be performed using, for example, AI, or without AI. For example, the reception department can use an AI model to estimate the emotions of the bride and groom and adjust the interface based on their emotions.

[0070] The reception unit can analyze the bride and groom's past event data and suggest the optimal data input method. The reception unit can, for example, analyze the bride and groom's past event data and suggest the optimal data input method. For example, the reception unit can suggest the optimal input method based on data on events the bride and groom have previously attended. The reception unit can also prioritize and suggest frequently used input methods (voice, text, etc.) based on the bride and groom's past event data. Furthermore, the reception unit can analyze the bride and groom's past event data and predict and suggest the input method to be used during a specific time period. This allows the reception unit to suggest the optimal data input method based on the past event data, enabling efficient data entry. Some or all of the above-described processing in the reception unit may be performed using, for example, AI, or may be performed without AI. For example, the reception unit can suggest the optimal data input method using an AI model for analyzing past event data.

[0071] The reception unit can check the consistency of the input data when data is entered and perform automatic completion as necessary. For example, the reception unit can check the consistency of the input data when data is entered and perform automatic completion as necessary. For example, the reception unit can check the consistency of the data entered by the bride and groom and automatically complete missing information. Furthermore, if there is an inconsistency in the data entered by the bride and groom, the reception unit can automatically suggest corrections using AI. Furthermore, the reception unit can automatically complete related information based on the data entered by the bride and groom, simplifying the input work. This allows the reception unit to maintain the consistency of data entry and perform automatic completion as necessary, thereby improving the accuracy of data entry. Some or all of the above-described processing in the reception unit may be performed using AI, for example, or may be performed without AI. For example, the reception unit can use an AI model to check the consistency of the input data and perform automatic completion as necessary.

[0072] The reception unit can estimate the emotions of the bride and groom and prioritize the input data based on the estimated emotions. For example, the reception unit can estimate the emotions of the bride and groom and prioritize the input data based on the estimated emotions. For example, if the bride and groom are nervous, the reception unit can adjust the interface so that important data is input first. Furthermore, if the bride and groom are relaxed, the reception unit can adjust the interface so that detailed data is input first. Furthermore, if the bride and groom are in a hurry, the reception unit can adjust the interface so that the most important data is input first. Thus, the reception unit can prioritize the input data based on the emotions of the bride and groom, thereby allowing important data to be input first. The emotion estimation is realized using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the reception unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the reception unit can use an AI model to estimate the emotions of the bride and groom and prioritize input data based on their emotions.

[0073] The reception unit can prioritize inputting highly relevant data by taking into account the geographical location information of the bride and groom when inputting data. For example, the reception unit prioritizes inputting highly relevant data by taking into account the geographical location information of the bride and groom when inputting data. For example, the reception unit prioritizes inputting highly relevant data based on the current locations of the bride and groom. The reception unit can also prioritize inputting highly relevant data based on the hometowns of the bride and groom. Furthermore, the reception unit can prioritize inputting highly relevant data based on the location of the bride and groom's wedding ceremony. This allows the reception unit to prioritize inputting highly relevant data by taking into account the geographical location information, thereby enabling more appropriate data input. Some or all of the above-described processing by the reception unit may be performed using, for example, AI, or may be performed without using AI. For example, the reception unit can determine the optimal data input method using an AI model for preferentially inputting highly relevant data by taking into account the geographical location information.

[0074] The reception unit can analyze the social media activities of the bride and groom when data is entered and automatically acquire related data. For example, the reception unit can automatically acquire related photos and videos from the bride and groom's social media accounts when data is entered and automatically acquire related data. For example, the reception unit can automatically acquire related photos and videos from the bride and groom's social media accounts. The reception unit can also analyze the content of the bride and groom's social media posts and automatically acquire related data. Furthermore, the reception unit can automatically acquire related data based on the bride and groom's social media friend lists. By analyzing social media activities and automatically acquiring related data, the reception unit can thereby reduce the effort of data entry. Some or all of the above-described processing in the reception unit may be performed using, for example, AI, or may be performed without using AI. For example, the reception unit can automatically acquire related data using an AI model for analyzing social media activities.

[0075] The analysis unit can estimate the emotions of the bride and groom and adjust the composition of the movie based on the estimated emotions. For example, the analysis unit estimates the emotions of the bride and groom and adjusts the composition of the movie based on the estimated emotions. For example, if the bride and groom are relaxed, the analysis unit can create a movie that progresses at a leisurely pace. Furthermore, if the bride and groom are in a hurry, the analysis unit can create a movie that emphasizes the shortest route. Furthermore, if the bride and groom are excited, the analysis unit can create a movie that adds visually stimulating effects. This allows the analysis unit to adjust the composition of the movie according to the emotions of the bride and groom, thereby generating a movie that is more in tune with their emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to these examples. Some or all of the above-described processing in the analysis unit may be performed using, for example, AI, or without AI. For example, the analysis unit can use an AI model to estimate the emotions of the bride and groom and adjust the composition of the movie based on their emotions.

[0076] The analysis unit can propose an optimal structure by referring to past wedding movie data during analysis. For example, the analysis unit can propose an optimal structure by referring to past wedding movie data during analysis. For example, the analysis unit can propose an optimal structure based on past wedding movie data. The analysis unit can also extract and propose popular elements from past wedding movie data. Furthermore, the analysis unit can analyze past wedding movie data and propose a structure based on trends. This allows the analysis unit to propose an optimal structure by referring to past wedding movie data. Some or all of the above-described processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can propose an optimal structure using an AI model for analyzing past wedding movie data.

[0077] During analysis, the analysis unit can emphasize specific scenes based on the hobbies and interests of the bride and groom. For example, during analysis, the analysis unit can emphasize specific scenes based on the hobbies and interests of the bride and groom. For example, the analysis unit can emphasize scenes related to the hobbies of the bride and groom. The analysis unit can also emphasize specific scenes based on the interests of the bride and groom. Furthermore, the analysis unit can add related scenes based on the hobbies and interests of the bride and groom. This allows the analysis unit to generate a more unique movie by emphasizing specific scenes based on the hobbies and interests of the bride and groom. Some or all of the above-described processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can emphasize specific scenes using an AI model for analyzing the hobbies and interests of the bride and groom.

[0078] The analysis unit can estimate the emotions of the bride and groom and determine the priority of the movie components based on the estimated emotions. For example, the analysis unit can estimate the emotions of the bride and groom and determine the priority of the movie components based on the estimated emotions. For example, if the bride and groom are nervous, the analysis unit can prioritize constructing important scenes. Furthermore, if the bride and groom are relaxed, the analysis unit can prioritize constructing detailed scenes. Furthermore, if the bride and groom are in a hurry, the analysis unit can prioritize constructing the most important scenes. Thus, the analysis unit can prioritize constructing important scenes by determining the priority of the movie components according to the emotions of the bride and groom. Emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the analysis unit can be performed using, for example, AI, or without AI. For example, the analysis unit can use an AI model to estimate the emotions of the bride and groom and prioritize movie elements based on their emotions.

[0079] The analysis unit can select movie scenes taking into account the geographical background of the bride and groom during analysis. For example, the analysis unit selects movie scenes taking into account the geographical background of the bride and groom during analysis. For example, the analysis unit selects scenes related to the hometown of the bride and groom. The analysis unit can also select scenes related to the location of the bride and groom's wedding. Furthermore, the analysis unit can select scenes related to the current location of the bride and groom. In this way, the analysis unit can incorporate more relevant scenes by selecting movie scenes taking into account the geographical background. Some or all of the above-described processing in the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can select optimal scenes using an AI model for selecting movie scenes taking into account the geographical background.

[0080] The analysis unit can analyze the social media activities of the bride and groom during analysis and incorporate relevant scenes into the movie. For example, the analysis unit can analyze the social media activities of the bride and groom during analysis and incorporate relevant scenes into the movie. For example, the analysis unit can analyze the social media posts of the bride and groom and incorporate relevant scenes into the movie. The analysis unit can also analyze the social media photos and videos of the bride and groom and incorporate relevant scenes into the movie. Furthermore, the analysis unit can incorporate relevant scenes into the movie based on the bride and groom's social media friend list. This allows the analysis unit to analyze social media activities and incorporate relevant scenes into the movie, thereby generating a more unique movie. Some or all of the above-described processing by the analysis unit may be performed using, for example, AI, or may be performed without using AI. For example, the analysis unit can incorporate relevant scenes into the movie using an AI model for analyzing social media activities.

[0081] The generation unit can estimate the emotions of the bride and groom and adjust the movie generation method based on the estimated emotions. For example, the generation unit can estimate the emotions of the bride and groom and adjust the movie generation method based on the estimated emotions. For example, if the bride and groom are relaxed, the generation unit can generate a movie that progresses at a leisurely pace. Furthermore, if the bride and groom are in a hurry, the generation unit can generate a movie that emphasizes the shortest route. Furthermore, if the bride and groom are excited, the generation unit can generate a movie that adds visually stimulating effects. Thus, the generation unit can adjust the movie generation method according to the emotions of the bride and groom, thereby generating a movie that is more in line with their emotions. Emotion estimation is realized using an emotion estimation function, for example, 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. Some or all of the above-described processing in the generation unit may be performed using, for example, AI, or without AI. For example, the generator can use an AI model to estimate the emotions of the bride and groom and adjust how the movie is generated based on their emotions.

[0082] The generation unit can apply an optimal generation algorithm by referring to past generation data at the time of generation. For example, the generation unit can apply an optimal generation algorithm by referring to past generation data at the time of generation. For example, the generation unit can apply an optimal generation algorithm based on past generation data. The generation unit can also extract and apply a popular generation algorithm from past generation data. Furthermore, the generation unit can analyze past generation data and apply a generation algorithm based on trends. In this way, the generation unit can apply an optimal generation algorithm by referring to past generation data. Some or all of the above-described processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can apply an optimal generation algorithm using an AI model for analyzing past generation data.

[0083] The generation unit can generate a movie customized based on the specific requests of the bride and groom at the time of generation. For example, the generation unit can generate a movie customized based on the specific requests of the bride and groom at the time of generation. For example, the generation unit can generate a movie that emphasizes specific scenes based on the requests of the bride and groom. The generation unit can also generate a movie using specific music based on the requests of the bride and groom. Furthermore, the generation unit can generate a movie with specific effects added based on the requests of the bride and groom. In this way, the generation unit can provide a more unique movie by generating a movie customized based on the requests of the bride and groom. Some or all of the above-described processing in the generation unit can be performed using AI, for example, or without AI. For example, the generation unit can generate a customized movie using an AI model for analyzing the requests of the bride and groom.

[0084] The generation unit can estimate the emotions of the bride and groom and determine the priority of the movies to be generated based on the estimated emotions. For example, the generation unit can estimate the emotions of the bride and groom and determine the priority of the movies to be generated based on the estimated emotions. For example, if the bride and groom are nervous, the generation unit can prioritize generating important scenes. Furthermore, if the bride and groom are relaxed, the generation unit can prioritize generating detailed scenes. Furthermore, if the bride and groom are in a hurry, the generation unit can prioritize generating the most important scenes. Thus, the generation unit can prioritize generating important scenes by determining the priority of movies according to the emotions of the bride and groom. The emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the generation unit may be performed using, for example, AI, or without AI. For example, the generator can use an AI model to estimate the emotions of the bride and groom and prioritize movies based on their emotions.

[0085] The generation unit can select movie scenes taking into account the geographical background of the bride and groom when generating the video. For example, the generation unit selects movie scenes taking into account the geographical background of the bride and groom when generating the video. For example, the generation unit selects scenes related to the hometown of the bride and groom. The generation unit can also select scenes related to the location of the bride and groom's wedding. Furthermore, the generation unit can select scenes related to the current location of the bride and groom. In this way, the generation unit can incorporate more relevant scenes by selecting movie scenes taking into account the geographical background. Some or all of the above-described processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can select optimal scenes using an AI model for selecting movie scenes taking into account the geographical background.

[0086] The generation unit can analyze the social media activities of the bride and groom during generation and incorporate related scenes into the movie. For example, the generation unit can analyze the social media activities of the bride and groom during generation and incorporate related scenes into the movie. For example, the generation unit can analyze the social media posts of the bride and groom and incorporate related scenes into the movie. The generation unit can also analyze social media photos and videos of the bride and groom and incorporate related scenes into the movie. Furthermore, the generation unit can incorporate related scenes into the movie based on the bride and groom's social media friend list. In this way, the generation unit can generate a more unique movie by analyzing social media activities and incorporating related scenes into the movie. Some or all of the above-described processing in the generation unit may be performed using, for example, AI, or may be performed without using AI. For example, the generation unit can incorporate related scenes into the movie using an AI model for analyzing social media activities.

[0087] The adjustment unit can estimate the emotions of the bride and groom and adjust the order and timing of photos and videos based on the estimated emotions. For example, the adjustment unit estimates the emotions of the bride and groom and adjusts the order and timing of photos and videos based on the estimated emotions. For example, if the bride and groom are relaxed, the adjustment unit adjusts the order and timing of photos and videos to a leisurely pace. Furthermore, if the bride and groom are in a hurry, the adjustment unit can prioritize important scenes and create an effective movie in a short amount of time. Furthermore, if the bride and groom are excited, the adjustment unit can adjust the order and timing of adding visually stimulating effects. In this way, the adjustment unit can generate a movie that is more in line with the emotions of the bride and groom by adjusting the order and timing of photos and videos according to their emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing by the adjustment unit may be performed using, for example, AI, or may be performed without AI. For example, the adjustment unit may use an AI model to estimate the emotions of the bride and groom and adjust the order and timing of photos and videos based on their emotions.

[0088] The adjustment unit can apply an optimal adjustment method by referring to past adjustment data during adjustment. For example, the adjustment unit can apply an optimal adjustment method by referring to past adjustment data during adjustment. For example, the adjustment unit can adjust an optimal order or timing based on past adjustment data. The adjustment unit can also extract and apply a popular adjustment method from past adjustment data. Furthermore, the adjustment unit can analyze past adjustment data and apply an adjustment method based on trends. In this way, the adjustment unit can adjust an optimal order or timing by referring to past adjustment data. Some or all of the above-described processing in the adjustment unit may be performed using, for example, AI, or may be performed without using AI. For example, the adjustment unit can apply an optimal adjustment method using an AI model for analyzing past adjustment data.

[0089] The adjustment unit can estimate the emotions of the bride and groom and determine the priority of adjustments based on the estimated emotions. For example, the adjustment unit can estimate the emotions of the bride and groom and determine the priority of adjustments based on the estimated emotions. For example, if the bride and groom are nervous, the adjustment unit can prioritize adjusting important scenes. Also, if the bride and groom are relaxed, the adjustment unit can prioritize adjusting detailed scenes. Furthermore, if the bride and groom are in a hurry, the adjustment unit can prioritize adjusting the most important scenes. In this way, the adjustment unit can prioritize adjusting important scenes by determining the priority of adjustments according to the emotions of the bride and groom. Emotion estimation is realized using an emotion estimation function using, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the adjustment unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the adjustment unit can use an AI model to estimate the emotions of the bride and groom and determine adjustment priorities based on their emotions.

[0090] During adjustment, the adjustment unit can adjust the order and timing of photos and videos taking into account the geographical background of the bride and groom. For example, during adjustment, the adjustment unit can adjust the order and timing of photos and videos taking into account the geographical background of the bride and groom. For example, the adjustment unit can prioritize arranging photos and videos related to the bride and groom's hometown. The adjustment unit can also prioritize arranging photos and videos related to the bride and groom's wedding location. Furthermore, the adjustment unit can prioritize arranging photos and videos related to the bride and groom's current location. This allows the adjustment unit to incorporate more relevant scenes by adjusting the order and timing of photos and videos taking into account the geographical background. Some or all of the above-described processing by the adjustment unit may be performed using, for example, AI, or may be performed without using AI. For example, the adjustment unit can determine the optimal order and timing using an AI model for adjusting the order and timing of photos and videos taking into account the geographical background.

[0091] The customization unit can estimate the emotions of the bride and groom and adjust the customization method based on the estimated emotions. For example, the customization unit estimates the emotions of the bride and groom and adjusts the customization method based on the estimated emotions. For example, if the bride and groom are relaxed, the customization unit can customize the video to proceed at a leisurely pace. Furthermore, if the bride and groom are in a hurry, the customization unit can customize the video to emphasize important scenes. Furthermore, if the bride and groom are excited, the customization unit can customize the video by adding visually stimulating effects. This allows the customization unit to adjust the customization method according to the emotions of the bride and groom, thereby generating a movie that is more in line with their emotions. Emotion estimation is achieved using an emotion estimation function, such as 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. Some or all of the above-described processing in the customization unit may be performed using, for example, AI, or without AI. For example, the customization department can use an AI model to estimate the emotions of the bride and groom and adjust the customization method based on their emotions.

[0092] The customization unit can suggest an optimal customization method by referring to past customization data during customization. For example, the customization unit can suggest an optimal customization method by referring to past customization data during customization. For example, the customization unit can suggest an optimal customization method based on past customization data. The customization unit can also extract and suggest popular customization methods from past customization data. Furthermore, the customization unit can analyze past customization data and suggest a customization method based on trends. In this way, the customization unit can suggest an optimal customization method by referring to past customization data. Some or all of the above-described processing in the customization unit may be performed using, for example, AI, or may be performed without using AI. For example, the customization unit can suggest an optimal customization method using an AI model for analyzing past customization data.

[0093] The customization unit can estimate the emotions of the bride and groom and determine the priorities of customization based on the estimated emotions. For example, the customization unit can estimate the emotions of the bride and groom and determine the priorities of customization based on the estimated emotions. For example, if the bride and groom are nervous, the customization unit can prioritize customizing important scenes. Also, if the bride and groom are relaxed, the customization unit can prioritize customizing detailed scenes. Furthermore, if the bride and groom are in a hurry, the customization unit can prioritize customizing the most important scenes. In this way, the customization unit can prioritize customization of important scenes by determining the priorities of customization according to the emotions of the bride and groom. Emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the customization unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the customization department can use an AI model to estimate the emotions of the bride and groom and prioritize customization based on their emotions.

[0094] The customization unit can determine the customization content taking into account the geographical background of the bride and groom when customizing. For example, the customization unit can perform customization related to the bride and groom's hometown. The customization unit can also perform customization related to the location of the bride and groom's wedding. Furthermore, the customization unit can perform customization related to the bride and groom's current location. In this way, the customization unit can incorporate more relevant scenes by determining the customization content taking into account the geographical background. Some or all of the above-described processing in the customization unit can be performed using, for example, AI, or can be performed without using AI. For example, the customization unit can determine the optimal customization method using an AI model for determining the customization content taking into account the geographical background.

[0095] The providing unit can estimate the emotions of the bride and groom and adjust the way the movie is presented based on the estimated emotions. For example, the providing unit can estimate the emotions of the bride and groom and adjust the way the movie is presented based on the estimated emotions. For example, if the bride and groom are relaxed, the providing unit can present the movie at a leisurely pace. Furthermore, if the bride and groom are in a hurry, the providing unit can present a movie that emphasizes important scenes. Furthermore, if the bride and groom are excited, the providing unit can present a movie with visually stimulating effects. This allows the providing unit to adjust the way the movie is presented based on the emotions of the bride and groom, thereby providing a movie that is more in line with their emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the providing unit may be performed using, for example, AI, or without AI. For example, the presentation unit can use an AI model to estimate the emotions of the bride and groom and adjust how the movie is presented based on their emotions.

[0096] The providing unit can propose an optimal provision method by referring to past provision data at the time of provision. For example, the providing unit can propose an optimal provision method by referring to past provision data at the time of provision. For example, the providing unit proposes an optimal provision method based on past provision data. The providing unit can also extract and propose popular provision methods from past provision data. Furthermore, the providing unit can analyze past provision data and propose a provision method based on trends. In this way, the providing unit can propose an optimal provision method by referring to past provision data. Some or all of the above-described processing in the providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the providing unit can propose an optimal provision method using an AI model for analyzing past provision data.

[0097] The providing unit can estimate the emotions of the bride and groom and determine the priority of movie provision based on the estimated emotions. For example, the providing unit can estimate the emotions of the bride and groom and determine the priority of movie provision based on the estimated emotions. For example, if the bride and groom are nervous, the providing unit can prioritize providing important scenes. Also, if the bride and groom are relaxed, the providing unit can prioritize providing detailed scenes. Furthermore, if the bride and groom are in a hurry, the providing unit can prioritize providing the most important scenes. In this way, the providing unit can prioritize providing important scenes by determining the priority of movie provision according to the emotions of the bride and groom. Emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the providing unit may be performed using, for example, AI, or without AI. For example, the providing unit can use an AI model to estimate the emotions of the bride and groom and prioritize the provision of movies based on their emotions.

[0098] The providing unit can select the optimal providing method by taking into consideration the geographical background of the bride and groom when providing the video. For example, the providing unit can select the optimal providing method by taking into consideration the geographical background of the bride and groom when providing the video. For example, the providing unit can prioritize providing movies related to the hometown of the bride and groom. The providing unit can also prioritize providing movies related to the location of the bride and groom's wedding. Furthermore, the providing unit can prioritize providing movies related to the current location of the bride and groom. In this way, the providing unit can incorporate more relevant scenes by selecting the optimal providing method by taking into consideration the geographical background. Some or all of the above-described processing by the providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the providing unit can determine the optimal providing method by using an AI model for selecting the optimal providing method by taking into consideration the geographical background.

[0099] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0100] The movie generation system can also analyze the bride and groom's past travel data and incorporate photos and videos from their travel destinations into the movie. For example, the analysis unit can add scenes of the bride and groom's travel destinations and tourist attractions to the movie based on data on the destinations they have visited in the past. The analysis unit can also prioritize photos and videos taken at the travel destination to highlight travel memories. Furthermore, the analysis unit can generate a more unique movie by incorporating scenes related to the culture and customs of the travel destination. This allows the movie generation system to provide a movie that reflects the bride and groom's travel memories.

[0101] The movie generation system can further collect messages from the bride and groom's family and friends and incorporate them into the movie. For example, the reception unit provides an interface for uploading video messages from family and friends. The analysis unit can analyze the collected messages and place them in appropriate positions in the movie. Furthermore, the generation unit can emphasize touching or humorous scenes based on the content of the messages. This allows the movie generation system to provide a more touching movie that includes warm messages from family and friends.

[0102] The movie generation system can also incorporate scenes from the bride and groom's favorite movies and TV shows. For example, the analysis unit can add related scenes to the movie based on data on the bride and groom's favorite movies and TV shows. The generation unit can also recreate famous scenes from movies and TV shows and combine them with photos and videos of the bride and groom. Furthermore, the customization unit can add music and effects that match the theme of the movie or TV show. This allows the movie generation system to provide a more personalized movie that matches the hobbies and preferences of the bride and groom.

[0103] The movie generation system can also incorporate live video of the bride and groom on their wedding day in real time. For example, the providing unit provides an interface for streaming live video of the wedding day. The generating unit can also analyze the live video in real time and incorporate it into the movie. Furthermore, the adjusting unit can adjust the timing and order of the live video to generate a movie with a natural flow. This allows the movie generation system to provide a more realistic movie that incorporates moving moments from the wedding day in real time.

[0104] The movie generation system can further estimate the emotions of the bride and groom and adjust the movie effects based on the estimated emotions. For example, if the bride and groom are emotional, the generation unit can add soft lighting and slow-motion effects. If the bride and groom are happy, the generation unit can add bright colors and fast-paced effects. If the bride and groom are nervous, the generation unit can add muted colors and slow-paced effects. This allows the movie generation system to provide a more moving movie that is in tune with the emotions of the bride and groom.

[0105] The movie generation system can further estimate the emotions of the bride and groom and select music for the movie based on the estimated emotions. For example, if the bride and groom are relaxed, the generation unit can select calm music. If the bride and groom are excited, the generation unit can select upbeat music. If the bride and groom are moved, the generation unit can select music with an inspiring melody. This allows the movie generation system to provide a more emotional movie that incorporates music that matches the emotions of the bride and groom.

[0106] The movie generation system can further estimate the emotions of the bride and groom and adjust the narration of the movie based on the estimated emotions. For example, if the bride and groom are moved, the generation unit can add narration in an emotional tone. If the bride and groom are happy, the generation unit can add narration in a bright and cheerful tone. If the bride and groom are nervous, the generation unit can add narration in a calm tone. This allows the movie generation system to provide a more moving movie that incorporates narration that is in tune with the emotions of the bride and groom.

[0107] The movie generation system can further estimate the emotions of the bride and groom and adjust the scene transitions of the movie based on the estimated emotions. For example, if the bride and groom are relaxed, the generation unit can perform a relaxed scene transition. If the bride and groom are excited, the generation unit can perform a fast-paced scene transition. Furthermore, if the bride and groom are moved, the generation unit can perform a smooth and moving scene transition. This allows the movie generation system to provide a more emotional movie that incorporates scene transitions that match the emotions of the bride and groom.

[0108] The movie generation system can further estimate the emotions of the bride and groom and adjust the subtitles of the movie based on the estimated emotions. For example, if the bride and groom are moved, the generation unit can add an emotional message as subtitles. If the bride and groom are happy, the generation unit can add a humorous message as subtitles. If the bride and groom are nervous, the generation unit can add an encouraging message as subtitles. This allows the movie generation system to provide a more moving movie that incorporates subtitles that are in tune with the emotions of the bride and groom.

[0109] The movie generation system can further estimate the emotions of the bride and groom and adjust the movie filter based on the estimated emotions. For example, the generation unit can apply a soft filter if the bride and groom are relaxed. Alternatively, the generation unit can apply a vivid filter if the bride and groom are excited. Furthermore, the generation unit can apply a warm filter if the bride and groom are moved. This allows the movie generation system to provide a more emotional movie that incorporates filters that match the emotions of the bride and groom.

[0110] The processing flow of the second embodiment will be briefly explained below.

[0111] Step 1: The reception unit inputs the bride and groom's data. The bride and groom's data includes names, photos, video clips, messages, etc. The reception unit provides an interface for inputting basic information such as names, hometowns, and hobbies, and has a function for uploading photos and videos to be used at the wedding. For example, it provides a drag-and-drop function so that users can easily upload photos and videos. Step 2: The analysis unit analyzes the data entered by the reception unit and determines the composition of the movie. The analysis unit uses AI to classify the data and consider the optimal composition of the movie. For example, by incorporating scenery related to the person's hometown or scenes related to their hobbies, a unique movie can be created. The order and timing of the photos and videos can also be adjusted to create a movie with a natural flow. Step 3: The generator generates a movie based on the structure determined by the analyzer. The generator uses AI to automatically generate the movie. For example, it combines photos and videos, adjusts the order and timing of scenes, and creates a movie with a natural flow.

[0112] 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.

[0113] 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> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as voice data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats including voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. 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 models 58 include AIs other than the generation AI. The AIs other than the generation AI are, 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 are 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 in whole by AI, but are not limited to these examples.In addition, processing performed by AI including the generation AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI including the generation AI.

[0114] 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.

[0115] Each of the multiple elements including the above-mentioned reception unit, analysis unit, and generation unit is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart device 14 and provides an interface for the user to input data of the bride and groom. The analysis unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and analyzes the input data and determines the configuration of the movie. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and generates the movie based on the configuration determined by the analysis unit. The correspondence between each unit and the device or control unit is not limited to the above example and various modifications are possible.

[0116] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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).

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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 including an instruction and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0130] 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.

[0131] Each of the multiple elements, including the above-mentioned reception unit, analysis unit, and generation unit, is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the smart glasses 214 and provides an interface for the user to input data on the bride and groom. The analysis unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and analyzes the input data and determines the configuration of the movie. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and generates the movie based on the configuration determined by the analysis unit. The correspondence between each unit and the device or control unit is not limited to the above example and various modifications are possible.

[0132] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0133] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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).

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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 including an instruction and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0146] 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.

[0147] Each of the multiple elements including the above-mentioned reception unit, analysis unit, and generation unit is realized, for example, by at least one of the headset-type terminal 314 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the headset-type terminal 314 and provides an interface through which a user inputs data about the bride and groom. The analysis unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and analyzes the input data and determines the configuration of the movie. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and generates a movie based on the configuration determined by the analysis unit. The correspondence between each unit and the device or control unit is not limited to the above example and various modifications are possible.

[0148] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0149] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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).

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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 including an instruction and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). 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 one or more data formats, such as voice data, text data, and image data. The data generation model 58 includes, for example, a text generation AI, an image generation AI, and a multimodal generation AI. 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 models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0163] 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.

[0164] Each of the multiple elements including the above-mentioned reception unit, analysis unit, and generation unit is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the reception unit is realized by the control unit 46A of the robot 414 and provides an interface through which a user inputs data about the bride and groom. The analysis unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and analyzes the input data and determines the configuration of the movie. The generation unit is realized, for example, by the specific processing unit 290 of the data processing device 12 and generates a movie based on the configuration determined by the analysis unit. The correspondence between each unit and the device or control unit is not limited to the above example and can be changed in various ways.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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).

[0169] 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.

[0170] 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."

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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.

[0177] 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.

[0178] 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.

[0179] 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.

[0180] 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.

[0181] 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.

[0182] 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.

[0183] (Appendix 1) A reception desk where the bride and groom's data is entered, an analysis unit that analyzes the data input by the reception unit and determines a configuration of the movie; a generator for generating a movie based on the structure determined by the analyzer; Equipped with A system characterized by: (Appendix 2) Equipped with an adjustment unit to adjust the order or timing of photos or videos 2. The system of claim 1. (Appendix 3) Equipped with a customization section that customizes the system according to user requests 2. The system of claim 1. (Appendix 4) A providing unit that provides the generated movie to the user 2. The system of claim 1. (Appendix 5) The reception unit Estimate the emotions of the bride and groom and adjust the data entry interface based on the estimated emotions. 2. The system of claim 1. (Appendix 6) The reception unit Analyze past event data for the bride and groom and suggest appropriate data entry methods 2. The system of claim 1. (Appendix 7) The reception unit During data entry, checks input data for consistency and auto-completes if necessary 2. The system of claim 1. (Appendix 8) The reception unit Estimate the emotions of the bride and groom and prioritize input data based on the estimated emotions 2. The system of claim 1. (Appendix 9) The reception unit When entering data, the geographic location of the bride and groom is taken into consideration to prioritize the most relevant data. 2. The system of claim 1. (Appendix 10) The reception unit When data is entered, the social media activity of the bride and groom is analyzed and relevant data is automatically retrieved. 2. The system of claim 1. (Appendix 11) The analysis unit Estimate the emotions of the bride and groom and adjust the composition of the movie based on the estimated emotions 2. The system of claim 1. (Appendix 12) The analysis unit During analysis, past wedding video data is referenced to suggest the optimal composition 2. The system of claim 1. (Appendix 13) The analysis unit During analysis, highlight specific scenes based on the bride and groom's hobbies and interests 2. The system of claim 1. (Appendix 14) The analysis unit Estimate the emotions of the bride and groom and prioritize the components of the movie based on the estimated emotions. 2. The system of claim 1. (Appendix 15) The analysis unit During analysis, movie scenes are selected taking into account the geographical background of the bride and groom. 2. The system of claim 1. (Appendix 16) The analysis unit During analysis, the social media activity of the bride and groom is analyzed and relevant scenes are incorporated into the movie. 2. The system of claim 1. (Appendix 17) The generation unit Estimate the emotions of the bride and groom and adjust the movie generation method based on the estimated emotions 2. The system of claim 1. (Appendix 18) The generation unit At the time of generation, the optimal generation algorithm is applied by referring to past generation data. 2. The system of claim 1. (Appendix 19) The generation unit Generate a customized movie based on the bride and groom's specific requests at the time of production 2. The system of claim 1. (Appendix 20) The generation unit Estimate the emotions of the bride and groom and prioritize the videos to be generated based on the estimated emotions. 2. The system of claim 1. (Appendix 21) The generation unit When generating the movie, select the scene taking into account the geographical background of the bride and groom. 2. The system of claim 1. (Appendix 22) The generation unit During production, the social media activity of the bride and groom is analyzed and relevant scenes are incorporated into the movie. 2. The system of claim 1. (Appendix 23) The adjustment unit Estimate the emotions of the bride and groom and adjust the order and timing of photos and videos based on those emotions 3. The system of claim 2. (Appendix 24) The adjustment unit When adjusting, refer to past adjustment data to apply the optimal adjustment method 3. The system of claim 2. (Appendix 25) The adjustment unit Estimate the emotions of the bride and groom and determine the priority of coordination based on the estimated emotions. 3. The system of claim 2. (Appendix 26) The adjustment unit When coordinating, adjust the order and timing of photos and videos to take into account the geographical location of the bride and groom. 3. The system of claim 2. (Appendix 27) The customization unit Estimate the emotions of the bride and groom and adjust the customization method based on the estimated emotions. 4. The system of claim 3. (Appendix 28) The customization unit When customizing, it refers to past customization data and suggests the best customization method. 4. The system of claim 3. (Appendix 29) The customization unit Estimate the emotions of the bride and groom and prioritize customization based on the estimated emotions 4. The system of claim 3. (Appendix 30) The customization unit When customizing, consider the geographical background of the bride and groom to determine the content of the customization. 4. The system of claim 3. (Appendix 31) The providing unit Estimate the emotions of the bride and groom and adjust the way the video is presented based on the estimated emotions 5. The system of claim 4. (Appendix 32) The providing unit When providing data, the system refers to past data provided to suggest the optimal method of providing the data. 5. The system of claim 4. (Appendix 33) The providing unit Estimate the emotions of the bride and groom and prioritize the movie presentation based on the estimated emotions. 5. The system of claim 4. (Appendix 34) The providing unit When serving, the most appropriate method of serving will be selected taking into consideration the geographical background of the bride and groom. 5. The system of claim 4. [Explanation of symbols]

[0184] 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 desk where the bride and groom's personal information is entered; an analysis unit that analyzes the data input by the reception unit and determines a configuration of the movie; a generator for generating a movie based on the configuration determined by the analyzer; Equipped A system characterized by:

2. Equipped with an adjustment section to adjust the order or timing of photos or videos 2. The system of claim 1 .

3. Equipped with a customization section that customizes the system according to user requests 2. The system of claim 1 .

4. A providing unit that provides the generated movie to the user 2. The system of claim 1 .

5. The reception unit is Estimate the emotions of the bride and groom and adjust the data entry interface based on the estimated emotions.

2. The system of claim 1 .

6. The reception unit is Analyze the bride and groom's past event data and suggest the appropriate data entry method 2. The system of claim 1 .

7. The reception unit is During data entry, checks input data for consistency and auto-completes if necessary 2. The system of claim 1 .

8. The reception unit is Estimate the emotions of the bride and groom and prioritize input data based on the estimated emotions 2. The system of claim 1 .

9. The reception unit is When entering data, the geographic location of the bride and groom is taken into consideration to prioritize the most relevant data.

2. The system of claim 1 .

10. The reception unit is When data is entered, the social media activity of the bride and groom is analyzed and relevant data is automatically retrieved.

2. The system of claim 1 .

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