System

Abstract

An object of a system according to an embodiment is to provide a travel space with a sense of immersion according to a user's preference.SOLUTION: A system according to an embodiment includes a preference hearing unit, a travel space generation unit, a real-time preference grasping unit, and a metaverse providing unit. The preference hearing unit may hear a user's preference. The travel space generation unit generates a travel space based on the information heard by the preference hearing unit. The real-time preference recognition unit measures brain waves and facial expressions of the user during the trip and recognizes preferences in real time. The Metaverse providing unit provides the created travel space in a Metaverse space.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 technologies have difficulty providing travel experiences that meet users' preferences, and there is room for improvement in creating immersive travel spaces.

[0005] The system according to the embodiment aims to provide an immersive travel space that meets the user's preferences. [Means for solving the problem]

[0006] The system according to the embodiment includes a preference hearing unit, a travel space generation unit, a real-time preference understanding unit, and a metaverse providing unit. The preference hearing unit hears the user's preferences. The travel space generation unit generates a travel space based on the information heard by the preference hearing unit. The real-time preference understanding unit measures the user's brain waves and facial expressions during the trip and understands the preferences in real time. The metaverse providing unit provides the generated travel space in the metaverse space. [Effects of the Invention]

[0007] The system according to the embodiment can provide an immersive travel space that meets the user's preferences. [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 travel experience system according to an embodiment of the present invention is a system that generates a fictional travel space based on a user's preferences and provides it in a metaverse space. By generating a travel space based on a user's preferences and providing it in a metaverse space, the travel experience system can provide an immersive travel experience.

[0029] A travel experience system according to an embodiment includes a preference hearing unit, a travel space generation unit, a real-time preference understanding unit, and a metaverse provision unit. The preference hearing unit hears user preferences. For example, it conducts a survey of the user and asks about their favorite travel destinations and experiences. The preference hearing unit can also analyze the user's past travel history and social media posts to automatically extract preference trends. The preference hearing unit can also analyze the user's music and movie preferences and generate travel destination images based on the analysis. The travel space generation unit generates a travel space based on the information gathered by the preference hearing unit. For example, the generation AI generates images and sounds of the travel destination based on survey information collected from the user. The travel space generation unit can also provide information about the history and culture of the travel destination in the form of images and audio, depending on the user's preferences. The travel space generation unit can also provide a more personalized experience by incorporating the user's name and personal elements into the generated images and sounds. The real-time preference understanding unit measures the user's brain waves and facial expressions during the trip to understand the user's preferences in real time. For example, the real-time preference understanding unit measures the user's brain waves and facial expressions to understand the user's preferences in real time. The real-time preference understanding unit can also measure the user's heart rate and electrodermal activity to perform more detailed emotional analysis. Furthermore, the real-time preference understanding unit can dynamically change the scenario of the travel space based on the user's real-time reactions. The metaverse providing unit provides the generated travel space in the metaverse space. For example, the generated travel space is provided to the user in a metaverse (VR) space. As a result, the travel experience system according to the embodiment can provide an immersive travel experience by generating a travel space based on the user's preferences and providing it in the metaverse space.

[0030] The preference hearing unit can analyze a user's past travel history and social media posts to automatically extract preference trends. For example, the preference hearing unit analyzes the user's past travel history to extract preference trends based on places visited, length of stay, type of activity, etc. For example, it collects data on cities and natural landscapes visited in the past to identify the characteristics of the user's favorite travel destinations. The preference hearing unit also analyzes the user's social media posts to extract preference trends from travel-related photos and comments. For example, it analyzes Instagram and Facebook posts to identify travel destinations and activities frequently shared by the user. The preference hearing unit also integrates the user's past travel history and social media posts to automatically extract overall preference trends. For example, it combines travel history data and social media post data to identify patterns of the user's favorite travel destinations and experiences. This allows for the generation of more accurate travel spaces by automatically extracting preferences based on the user's past data.

[0031] The preference hearing unit can analyze the user's music and movie preferences and generate travel destination images based on them. For example, the preference hearing unit can analyze the user's music streaming service history to identify the user's favorite music genres and artists. For example, a user who likes relaxing music can be suggested tranquil beaches or natural scenery. The preference hearing unit can also analyze the user's movie viewing history to identify the user's favorite movie genres and themes. For example, a user who likes adventure movies can be suggested travel destinations that offer adventure experiences. The preference hearing unit can also integrate music and movie preference data to generate travel destination images based on the user's overall preferences. For example, it can suggest travel destinations with themes that match the user's music and movie preferences. This allows the system to provide a more personalized travel experience by generating travel destination images based on the user's music and movie preferences.

[0032] The preference hearing unit can simultaneously hear the preferences of the user's friends and family and generate a group travel plan. For example, the preference hearing unit may also conduct a survey of the user's friends and family to collect their respective preferences. For example, the preference hearing unit may suggest travel destinations that everyone can enjoy based on the preferences of all family members. The preference hearing unit may also analyze social media posts from friends and family to extract the preferences of the entire group. For example, the preference hearing unit may suggest travel destinations that the entire group can enjoy based on data on travel destinations and activities shared by friends and family. The preference hearing unit may also integrate the preferences of the user and their friends and family to generate a group travel plan. For example, the unit may suggest travel destinations and activities that reflect the preferences of everyone. This makes it possible to generate a group travel plan that takes into account the preferences of the user's friends and family.

[0033] The preference hearing unit can suggest optimal travel destinations according to the season and weather based on the user's preferences. For example, the preference hearing unit suggests optimal travel destinations for each season based on the user's preferences. For example, a snowy mountain resort is suggested for a user who wants to enjoy skiing in winter. The preference hearing unit also suggests optimal travel destinations according to the weather based on the user's preferences. For example, a city with plenty of indoor activities is suggested for a rainy day. The preference hearing unit also integrates season and weather data to suggest travel destinations that are optimal for the user's preferences. For example, a beach resort is suggested for a sunny day, and a museum or art galleries are suggested for a rainy day. In this way, the optimal travel destinations according to the season and weather can be suggested, thereby providing the user with the optimal travel experience.

[0034] The travel space generation unit can provide video and audio information about the history and culture of the travel destination according to the user's preferences. For example, if the user is interested in historical buildings, the travel space generation unit provides video and audio information about the history and culture of those buildings. For example, it generates video of ancient ruins or castles along with audio explaining the history of the place. Furthermore, if the user is interested in a particular culture, the travel space generation unit provides video and audio information about that culture. For example, it generates video of traditional festivals and ceremonies along with audio explaining the background of those festivals and ceremonies. Furthermore, the travel space generation unit generates documentary-style video and audio about the history and culture of the travel destination according to the user's preferences. For example, it generates video and narration introducing the history and culture of a particular region. This makes it possible to provide a deeper travel experience by providing historical and cultural information according to the user's preferences.

[0035] The travel space generation unit can provide a more personalized experience by incorporating the user's name and personal elements into the generated images and sounds. The travel space generation unit can provide a more personalized experience by, for example, incorporating the user's name into the generated images and sounds. For example, the user's name may be displayed on signs or guide boards in the images. The travel space generation unit also incorporates the user's personal elements (for example, favorite colors or symbols) into the images and sounds. For example, a landscape based on the user's favorite color or symbols that the user likes may be placed in the images. The travel space generation unit can also provide a more personalized experience by incorporating the user's past travel photos and videos into the images and sounds. For example, photos of places the user has visited in the past may be displayed in the images. In this way, by incorporating the user's name and personal elements, a more personalized travel experience may be provided.

[0036] The travel space generation unit can add social functions to the generated travel space that allow users to interact with other users in real time. The travel space generation unit adds, for example, social functions that allow users to chat or make voice calls with other users within the generated travel space. For example, users visiting the same travel destination can interact with each other in real time. The travel space generation unit also adds a function that allows users to enjoy activities with other users within the travel space. For example, virtual tours and joint missions can be carried out. The travel space generation unit also adds a function that allows users to interact with other users' avatars in real time within the travel space. For example, users can stroll around or take photos together with other users. By adding social functions that allow users to interact with other users in real time, a more interactive travel experience can be provided.

[0037] The travel space generation unit can add elements to the travel space that the user can customize themselves. For example, the travel space generation unit adds a function that allows the user to play their favorite music in the travel space. For example, the user plays their own playlist in the travel space. The travel space generation unit also adds a function that allows the user to add their favorite decorations in the travel space. For example, the user selects decorations with their favorite colors and designs. The travel space generation unit also adds a function that allows the user to customize their own avatar and clothing in the travel space. For example, the user changes the appearance and clothing of their avatar. In this way, by adding elements that the user can customize themselves, a more personalized travel experience can be provided.

[0038] The metaverse providing unit can analyze the user's movements and behavior within the VR space and automatically suggest places and activities of interest. For example, the metaverse providing unit tracks the user's gaze within the VR space and automatically suggests places and activities of interest. For example, it suggests activities related to places where the user has looked for a long time. The metaverse providing unit also analyzes the user's movement patterns within the VR space and automatically suggests places and activities of interest. For example, it suggests activities related to places the user frequently visits. The metaverse providing unit also analyzes the user's behavioral data within the VR space and automatically suggests places and activities of interest. For example, if the user repeatedly performs a particular activity, it makes new suggestions related to that activity. This allows the system to provide a more personalized travel experience by analyzing the user's movements and behavior and automatically suggesting places and activities of interest.

[0039] The metaverse provider can track the user's gaze within the VR space and automatically provide information about what is in their line of sight. For example, the metaverse provider can track the user's gaze within the VR space and automatically provide information about tourist spots and activities in their line of sight. For example, it can display the history and background information of a building the user is looking at. The metaverse provider can also track the user's gaze and automatically provide information related to the object in their line of sight. For example, it can display an explanation of an artwork the user is looking at. The metaverse provider can also build a system that provides information of interest to the user in real time based on the gaze tracking data. For example, it can display information about events and activities related to the place the user is looking at. This allows the user to track their gaze and automatically provide information about what is in their line of sight, providing a more interactive travel experience.

[0040] The metaverse provider can collect user behavior data within the VR space and reflect it in the user's next travel experience. For example, the metaverse provider can collect the user's movement patterns and gaze data within the VR space and reflect it in the user's next travel experience. For example, the metaverse provider can reflect the user's frequently visited places and activities of interest in the next travel experience suggestions. The metaverse provider can also analyze the user's behavior data and build a system that makes optimal suggestions for the user's next travel experience. For example, the metaverse provider can suggest the user's next travel destination based on the user's preferred theme or style. The metaverse provider can also collect user behavior data within the VR space over the long term and track changes in the user's preferences and interests. For example, the metaverse provider can identify user preference trends based on past data and reflect them in the user's next travel experience. This allows the user to provide a more personalized travel experience by collecting user behavior data and reflecting it in the user's next travel experience.

[0041] The metaverse providing unit can provide a function that records a user's experience in a VR space and allows them to re-experience it later. The metaverse providing unit provides, for example, a function that records a user's experience in a VR space and allows them to re-experience it later. For example, it can record places a user has visited or activities a user has performed and allow them to play them back later. The metaverse providing unit also provides a function that edits the recorded experience and allows the user to re-experience their favorite parts. For example, it can select and play specific places or activities. The metaverse providing unit also provides a function that allows the user to share the recorded experience with other users. For example, it can allow the user to share their experience on a social networking site and allow other users to play that experience. This allows the user to record their experience and re-experience it later, thereby providing a deeper travel experience.

[0042] The metaverse provider can provide the wealthy with experiences of specific luxury resorts and private tours. For example, the metaverse provider provides virtual tours of specific luxury resorts for the wealthy. For example, it recreates the experience of a private beach or luxury spa in a VR space. The metaverse provider also provides private tour experiences for the wealthy. For example, it recreates special tourist spots and activities guided by a dedicated guide in a VR space. The metaverse provider also provides a function that allows the wealthy to customize the experience of specific luxury resorts and private tours. For example, the user can select the tour content according to their preferences. This makes it possible to provide a more luxurious travel experience by providing the wealthy with experiences of specific luxury resorts and private tours.

[0043] The metaverse providing unit can automatically generate special videos and photos for users who want to share on social media. The metaverse providing unit provides, for example, a function to automatically generate special videos and photos for users who want to share on social media. For example, it can compile videos and photos that highlight the places the user has visited or the activities they have performed. The metaverse providing unit also provides a function to add the user's name and message to the videos and photos to be shared. For example, the user can insert their name and message into the video or photo. The metaverse providing unit also provides a function to directly post videos and photos to be shared to social media. For example, the user can share the generated videos and photos on social media with one click. This makes it possible to provide a travel experience that is easier to share by automatically generating special videos and photos for users who want to share on social media.

[0044] The metaverse providing unit can provide travel experiences with different themes and styles for each target. For example, the metaverse providing unit provides travel experiences with different themes for each target. For example, it might suggest luxury resorts for the wealthy, or unique tourist spots for those who like to share on social media. The metaverse providing unit also provides travel experiences with different styles for each target. For example, it might suggest adventure experiences for adventure lovers, or relaxation experiences for those who want to relax. The metaverse providing unit also provides a function that allows the theme and style of the travel experience to be customized according to the preferences of each target. For example, users can select the theme and style to suit their preferences. This makes it possible to provide a more personalized travel experience by providing travel experiences with different themes and styles for each target.

[0045] The metaverse providing unit can provide customization options according to the needs of each target. For example, the metaverse providing unit provides customization options according to the needs of each target. For example, it provides private tour options for wealthy customers and special video and photo options for those who like to share on social media. The metaverse providing unit also provides a function that allows the content of the travel experience to be customized according to the needs of each target. For example, users can select activities and tourist spots according to their preferences. The metaverse providing unit also builds a system that provides customization options according to the needs of each target in real time. For example, it dynamically adjusts customization options according to the user's emotions and preferences. This makes it possible to provide a more personalized travel experience by providing customization options according to the needs of each target.

[0046] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0047] The travel experience system can further include a health management unit that monitors the user's health condition. For example, the system can monitor the user's heart rate and blood pressure in real time and provide a travel plan that matches the user's health condition. For example, if the user's heart rate is high, the system can suggest relaxing activities, and if the user's blood pressure is stable, the system can suggest active activities. The health management unit can also provide a travel plan that takes into account the user's dietary restrictions and allergy information. For example, the health management unit can suggest restaurants and meal plans that avoid certain ingredients. Furthermore, the health management unit can provide a travel plan that includes an appropriate amount of exercise based on the user's exercise history. For example, the system can suggest activities such as walking and hiking. This makes it possible to provide a travel experience that takes the user's health condition into consideration.

[0048] The travel experience system can further include a learning analysis unit that analyzes the user's learning history. For example, the system can suggest related travel destinations based on information about history and culture that the user has previously studied. For example, if the user has studied the history of ancient Egypt, the system can suggest Egyptian pyramids and museums. The learning analysis unit can also suggest travel destinations based on the user's academic field of interest. For example, if a user is interested in astronomy, the system can suggest observatories and places where they can observe the stars. Furthermore, the learning analysis unit can combine the user's learning history with their travel experience to provide travel plans that are both educational and enjoyable. For example, the system can suggest plans that incorporate local guided tours and workshops. This makes it possible to provide a travel experience that takes the user's learning history into consideration.

[0049] The travel experience system can further include a hobby and special skill analysis unit that takes into account the user's hobbies and special skills. For example, if the user's hobby is photography, the system can suggest photogenic spots. For example, it can suggest places with beautiful scenery and architecture. If the user's special skill is cooking, the hobby and special skill analysis unit can also suggest local cooking classes and food markets. For example, it can provide an experience of cooking with a local chef. Furthermore, the hobby and special skill analysis unit can also suggest special events and workshops based on the user's hobbies and special skills. For example, if a user is interested in art, it can suggest local art galleries and art workshops. This makes it possible to provide a travel experience that takes the user's hobbies and special skills into consideration.

[0050] The travel experience system can further include a travel history analysis unit that suggests the user's next travel destination based on the user's past travel experiences. For example, the system analyzes the places the user has visited in the past and the activities they have experienced, and suggests similar travel destinations. For example, if a user has visited a beach resort in the past, other beach resorts will be suggested. The travel history analysis unit can also suggest the user's next travel destination based on the user's ratings and impressions of places they have visited in the past. For example, it can suggest travel destinations similar to places that the user has given high ratings in the past. Furthermore, the travel history analysis unit can combine the user's past travel experiences with their current preferences to provide an optimal travel plan. For example, it can suggest travel destinations that take into account the places the user has visited in the past and their current preferences. This makes it possible to provide a travel experience that takes into account the user's past travel experiences.

[0051] The travel experience system can further include a theme travel unit that provides travel plans based on specific themes based on the user's preferences. For example, if the user is interested in history, the theme travel unit can suggest a plan to visit historical tourist sites. For example, a plan to visit ancient ruins and historical buildings can be provided. If the user likes nature, the theme travel unit can also suggest a plan to fully enjoy nature. For example, a plan to visit national parks and nature reserves can be provided. Furthermore, the theme travel unit can also provide plans that incorporate events and activities based on specific themes based on the user's preferences. For example, a plan to visit music festivals and art exhibitions can be provided. In this way, a theme travel experience can be provided that suits the user's preferences.

[0052] The processing flow of the first embodiment will be briefly explained below.

[0053] Step 1: The preference hearing unit hears about the user's preferences. For example, it can conduct a survey of the user and ask about their favorite travel destinations and experiences. It can also analyze the user's past travel history and social media posts to automatically extract preference trends. It can also analyze the user's music and movie preferences and generate travel destination images based on them. Step 2: The travel space generation unit generates a travel space based on the information gathered by the preference hearing unit. For example, the generation AI generates images and sounds of travel destinations based on questionnaire information collected from users. It can also provide information about the history and culture of the travel destination in the form of images and sounds, depending on the user's preferences. Furthermore, by incorporating the user's name and personal elements into the generated images and sounds, it is possible to provide a more personalized experience. Step 3: The real-time preference understanding unit measures the user's brain waves and facial expressions during the trip to understand their preferences in real time. For example, it measures the user's brain waves and facial expressions to understand their preferences in real time. It can also measure the user's heart rate and electrodermal activity to perform more detailed emotional analysis. Furthermore, it can dynamically change the travel space scenario based on the user's real-time reactions. Step 4: The metaverse provider provides the generated travel space in the metaverse space. For example, the generated travel space is provided to the user in the metaverse (VR) space. This allows a travel space based on the user's preferences to be generated and provided in the metaverse space, providing an immersive travel experience.

[0054] (Example 2) A travel experience system according to an embodiment of the present invention is a system that generates a fictional travel space based on a user's preferences and provides it in a metaverse space. By generating a travel space based on a user's preferences and providing it in a metaverse space, the travel experience system can provide an immersive travel experience.

[0055] A travel experience system according to an embodiment includes a preference hearing unit, a travel space generation unit, a real-time preference understanding unit, and a metaverse provision unit. The preference hearing unit hears user preferences. For example, it conducts a survey of the user and asks about their favorite travel destinations and experiences. The preference hearing unit can also analyze the user's past travel history and social media posts to automatically extract preference trends. The preference hearing unit can also analyze the user's music and movie preferences and generate travel destination images based on the analysis. The travel space generation unit generates a travel space based on the information gathered by the preference hearing unit. For example, the generation AI generates images and sounds of the travel destination based on survey information collected from the user. The travel space generation unit can also provide information about the history and culture of the travel destination in the form of images and audio, depending on the user's preferences. The travel space generation unit can also provide a more personalized experience by incorporating the user's name and personal elements into the generated images and sounds. The real-time preference understanding unit measures the user's brain waves and facial expressions during the trip to understand the user's preferences in real time. For example, the real-time preference understanding unit measures the user's brain waves and facial expressions to understand the user's preferences in real time. The real-time preference understanding unit can also measure the user's heart rate and electrodermal activity to perform more detailed emotional analysis. Furthermore, the real-time preference understanding unit can dynamically change the scenario of the travel space based on the user's real-time reactions. The metaverse providing unit provides the generated travel space in the metaverse space. For example, the generated travel space is provided to the user in a metaverse (VR) space. As a result, the travel experience system according to the embodiment can provide an immersive travel experience by generating a travel space based on the user's preferences and providing it in the metaverse space.

[0056] The preference hearing unit can analyze a user's past travel history and social media posts to automatically extract preference trends. For example, the preference hearing unit analyzes the user's past travel history to extract preference trends based on places visited, length of stay, type of activity, etc. For example, it collects data on cities and natural landscapes visited in the past to identify the characteristics of the user's favorite travel destinations. The preference hearing unit also analyzes the user's social media posts to extract preference trends from travel-related photos and comments. For example, it analyzes Instagram and Facebook posts to identify travel destinations and activities frequently shared by the user. The preference hearing unit also integrates the user's past travel history and social media posts to automatically extract overall preference trends. For example, it combines travel history data and social media post data to identify patterns of the user's favorite travel destinations and experiences. This allows for the generation of more accurate travel spaces by automatically extracting preferences based on the user's past data.

[0057] The preference hearing unit can analyze the user's music and movie preferences and generate travel destination images based on them. For example, the preference hearing unit can analyze the user's music streaming service history to identify the user's favorite music genres and artists. For example, a user who likes relaxing music can be suggested tranquil beaches or natural scenery. The preference hearing unit can also analyze the user's movie viewing history to identify the user's favorite movie genres and themes. For example, a user who likes adventure movies can be suggested travel destinations that offer adventure experiences. The preference hearing unit can also integrate music and movie preference data to generate travel destination images based on the user's overall preferences. For example, it can suggest travel destinations with themes that match the user's music and movie preferences. This allows the system to provide a more personalized travel experience by generating travel destination images based on the user's music and movie preferences.

[0058] The preference hearing unit can use the emotion estimation function to analyze the user's emotions when answering a questionnaire and add questions that elicit positive emotions. For example, the preference hearing unit analyzes the user's facial expressions when answering a questionnaire and generates additional questions based on answers that indicate positive emotions. For example, if a smile or facial expression indicating excitement is detected, questions related to that theme are added. The preference hearing unit also analyzes the user's voice tone and generates additional questions based on answers that indicate positive emotions. For example, if the voice tone rises, questions related to that theme are added. The preference hearing unit also integrates facial expression and voice data to comprehensively analyze the user's emotions and generate questions that elicit positive emotions. For example, if both the facial expression and voice are positive, questions related to that theme are added. In this way, a better travel experience can be provided by analyzing the user's emotions and adding questions that elicit positive emotions.

[0059] The preference hearing unit can simultaneously hear the preferences of the user's friends and family and generate a group travel plan. For example, the preference hearing unit may also conduct a survey of the user's friends and family to collect their respective preferences. For example, the preference hearing unit may suggest travel destinations that everyone can enjoy based on the preferences of all family members. The preference hearing unit may also analyze social media posts from friends and family to extract the preferences of the entire group. For example, the preference hearing unit may suggest travel destinations that the entire group can enjoy based on data on travel destinations and activities shared by friends and family. The preference hearing unit may also integrate the preferences of the user and their friends and family to generate a group travel plan. For example, the unit may suggest travel destinations and activities that reflect the preferences of everyone. This makes it possible to generate a group travel plan that takes into account the preferences of the user's friends and family.

[0060] The preference hearing unit can suggest optimal travel destinations according to the season and weather based on the user's preferences. For example, the preference hearing unit suggests optimal travel destinations for each season based on the user's preferences. For example, a snowy mountain resort is suggested for a user who wants to enjoy skiing in winter. The preference hearing unit also suggests optimal travel destinations according to the weather based on the user's preferences. For example, a city with plenty of indoor activities is suggested for a rainy day. The preference hearing unit also integrates season and weather data to suggest travel destinations that are optimal for the user's preferences. For example, a beach resort is suggested for a sunny day, and a museum or art galleries are suggested for a rainy day. In this way, the optimal travel destinations according to the season and weather can be suggested, thereby providing the user with the optimal travel experience.

[0061] The preference hearing unit can use the emotion estimation function to analyze the emotions of the user when answering a questionnaire in real time and dynamically adjust the answers. For example, the preference hearing unit analyzes the user's facial expression in real time when answering a questionnaire and adjusts the questions according to the emotions. For example, if the user is excited, it adds questions about adventure experiences. The preference hearing unit also analyzes the user's voice tone in real time and adjusts the questions according to the emotions. For example, if the user is relaxed, it adds questions about relaxing travel destinations. The preference hearing unit also integrates facial expression and voice data, analyzes the user's emotions in real time, and dynamically adjusts the questions. For example, the questions are updated every time the user's emotions change. In this way, the user's emotions can be analyzed in real time and the answers dynamically adjusted, making it possible to more accurately grasp the user's preferences.

[0062] The travel space generation unit can provide video and audio information about the history and culture of the travel destination according to the user's preferences. For example, if the user is interested in historical buildings, the travel space generation unit provides video and audio information about the history and culture of those buildings. For example, it generates video of ancient ruins or castles along with audio explaining the history of the place. Furthermore, if the user is interested in a particular culture, the travel space generation unit provides video and audio information about that culture. For example, it generates video of traditional festivals and ceremonies along with audio explaining the background of those festivals and ceremonies. Furthermore, the travel space generation unit generates documentary-style video and audio about the history and culture of the travel destination according to the user's preferences. For example, it generates video and narration introducing the history and culture of a particular region. This makes it possible to provide a deeper travel experience by providing historical and cultural information according to the user's preferences.

[0063] The travel space generation unit can provide a more personalized experience by incorporating the user's name and personal elements into the generated images and sounds. The travel space generation unit can provide a more personalized experience by, for example, incorporating the user's name into the generated images and sounds. For example, the user's name may be displayed on signs or guide boards in the images. The travel space generation unit also incorporates the user's personal elements (for example, favorite colors or symbols) into the images and sounds. For example, a landscape based on the user's favorite color or symbols that the user likes may be placed in the images. The travel space generation unit can also provide a more personalized experience by incorporating the user's past travel photos and videos into the images and sounds. For example, photos of places the user has visited in the past may be displayed in the images. In this way, by incorporating the user's name and personal elements, a more personalized travel experience may be provided.

[0064] The travel space generation unit can use the emotion estimation function to analyze the user's emotional response to the generated travel space and strengthen elements that elicit a positive response. The travel space generation unit, for example, analyzes the user's facial expression in response to the generated travel space and strengthens elements that indicate a positive emotional response. For example, it highlights places and activities where the user smiled. The travel space generation unit also analyzes the user's vocal tone and strengthens elements that indicate a positive emotional response. For example, it highlights places and activities where the user made an excited voice. The travel space generation unit also integrates facial expression and voice data to comprehensively analyze the user's emotional response and strengthen elements that elicit a positive response. For example, it highlights places and activities that the user enjoyed the most. In this way, a better travel experience can be provided by analyzing the user's emotional response and strengthening elements that elicit a positive response.

[0065] The travel space generation unit can add social functions to the generated travel space that allow users to interact with other users in real time. The travel space generation unit adds, for example, social functions that allow users to chat or make voice calls with other users within the generated travel space. For example, users visiting the same travel destination can interact with each other in real time. The travel space generation unit also adds a function that allows users to enjoy activities with other users within the travel space. For example, virtual tours and joint missions can be carried out. The travel space generation unit also adds a function that allows users to interact with other users' avatars in real time within the travel space. For example, users can stroll around or take photos together with other users. By adding social functions that allow users to interact with other users in real time, a more interactive travel experience can be provided.

[0066] The travel space generation unit can add elements to the travel space that the user can customize themselves. For example, the travel space generation unit adds a function that allows the user to play their favorite music in the travel space. For example, the user plays their own playlist in the travel space. The travel space generation unit also adds a function that allows the user to add their favorite decorations in the travel space. For example, the user selects decorations with their favorite colors and designs. The travel space generation unit also adds a function that allows the user to customize their own avatar and clothing in the travel space. For example, the user changes the appearance and clothing of their avatar. In this way, by adding elements that the user can customize themselves, a more personalized travel experience can be provided.

[0067] The travel space generation unit can use the emotion estimation function to analyze the user's emotions regarding the generated travel space in real time and dynamically adjust the space elements. For example, the travel space generation unit analyzes the user's facial expressions regarding the generated travel space in real time and adjusts the space elements according to the emotions. For example, if the user is relaxed, quiet scenery and sounds are emphasized. The travel space generation unit also analyzes the user's voice tone in real time and adjusts the space elements according to the emotions. For example, if the user is excited, active activities are added. The travel space generation unit also integrates facial expression and voice data, analyzes the user's emotions in real time, and dynamically adjusts the space elements. For example, the space elements are updated every time the user's emotions change. In this way, a better travel experience can be provided by analyzing the user's emotions in real time and dynamically adjusting the space elements.

[0068] The real-time preference grasping unit measures not only the user's brain waves and facial expressions, but also their heart rate and electrodermal activity, enabling more detailed emotional analysis. The real-time preference grasping unit, for example, measures the user's brain waves and analyzes their emotional state, such as relaxation or excitement. For example, emotions are identified based on fluctuations in alpha and beta brain waves. The real-time preference grasping unit also measures the user's heart rate and analyzes their state of stress or relaxation. For example, the user's emotional state is identified based on fluctuations in heart rate. The real-time preference grasping unit also measures the user's electrodermal activity and analyzes changes in emotions. For example, the user's emotional state is identified based on fluctuations in the skin's electrical resistance. In this way, more detailed emotional analysis is possible by also measuring the heart rate and electrodermal activity.

[0069] The real-time preference understanding unit can dynamically change the scenario of the travel space based on the user's real-time reaction. For example, the real-time preference understanding unit analyzes the user's brain waves and facial expressions in real time and changes the scenario of the travel space according to the user's emotions. For example, if the user is relaxed, the scenario is changed to one that emphasizes tranquil scenery. The real-time preference understanding unit also analyzes the user's heart rate and electrodermal activity in real time and changes the scenario of the travel space according to the user's emotions. For example, if the user is excited, the scenario is changed to one that adds active activities. The real-time preference understanding unit also integrates data on the brain waves, facial expressions, heart rate, and electrodermal activity and dynamically changes the scenario of the travel space according to the user's emotions. For example, the scenario is updated every time the user's emotions change. This makes it possible to provide a more adaptive travel experience by dynamically changing the scenario based on the user's real-time reaction.

[0070] The real-time preference understanding unit can use the emotion estimation function to analyze changes in the user's emotions in real time and enhance elements that elicit positive emotions. The real-time preference understanding unit, for example, analyzes the user's brain waves and facial expressions in real time and enhances elements that elicit positive emotions. For example, it emphasizes places and activities where the user smiles. The real-time preference understanding unit also analyzes the user's heart rate and electrodermal activity in real time and enhances elements that elicit positive emotions. For example, if the user is relaxed, it emphasizes quiet scenery and sounds. The real-time preference understanding unit also integrates data on brain waves, facial expressions, heart rate, and electrodermal activity to analyze the user's emotions in real time and enhance elements that elicit positive emotions. For example, it emphasizes places and activities that the user enjoyed most. In this way, by analyzing changes in the user's emotions in real time and enhancing elements that elicit positive emotions, a better travel experience can be provided.

[0071] The real-time preference understanding unit can add new activities and events to the travel space based on the user's real-time reactions. For example, the real-time preference understanding unit analyzes the user's brain waves and facial expressions in real time and adds new activities according to the user's emotions. For example, if the user is excited, it adds an adventure experience. The real-time preference understanding unit also analyzes the user's heart rate and electrodermal activity in real time and adds new events according to the user's emotions. For example, if the user is relaxed, it adds a relaxation event. The real-time preference understanding unit also integrates data on the brain waves, facial expressions, heart rate, and electrodermal activity and adds new activities and events according to the user's emotions. For example, it adds new activities and events every time the user's emotions change. This makes it possible to provide a more dynamic travel experience by adding new activities and events based on the user's real-time reactions.

[0072] The real-time preference grasping unit can dynamically change the theme and style of the travel space in response to changes in the user's preferences. For example, the real-time preference grasping unit analyzes the user's brain waves and facial expressions in real time and changes the theme of the travel space in response to emotions. For example, if the user is relaxed, the theme is changed to a quiet beach theme. The real-time preference grasping unit also analyzes the user's heart rate and electrodermal activity in real time and changes the style of the travel space in response to emotions. For example, if the user is excited, the style is changed to an adventure style. The real-time preference grasping unit also integrates data on the brain waves, facial expressions, heart rate, and electrodermal activity and dynamically changes the theme and style of the travel space in response to the user's emotions. For example, the theme and style are updated every time the user's emotions change. This allows the theme and style to be dynamically changed in response to changes in the user's preferences, thereby providing a more adaptive travel experience.

[0073] The real-time preference understanding unit can use the emotion estimation function to analyze changes in the user's emotions in real time and dynamically adjust elements of the travel space. For example, the real-time preference understanding unit analyzes the user's brain waves and facial expressions in real time and adjusts elements of the travel space according to the user's emotions. For example, if the user is relaxed, it emphasizes quiet scenery and sounds. The real-time preference understanding unit also analyzes the user's heart rate and electrodermal activity in real time and adjusts elements of the travel space according to the user's emotions. For example, if the user is excited, it adds active activities. The real-time preference understanding unit also integrates data on brain waves, facial expressions, heart rate, and electrodermal activity to analyze the user's emotions in real time and dynamically adjust elements of the travel space. For example, the space elements are updated every time the user's emotions change. This allows the user to analyze changes in the user's emotions in real time and dynamically adjust elements of the travel space to provide a more adaptive travel experience.

[0074] The metaverse providing unit can analyze the user's movements and behavior within the VR space and automatically suggest places and activities of interest. For example, the metaverse providing unit tracks the user's gaze within the VR space and automatically suggests places and activities of interest. For example, it suggests activities related to places where the user has looked for a long time. The metaverse providing unit also analyzes the user's movement patterns within the VR space and automatically suggests places and activities of interest. For example, it suggests activities related to places the user frequently visits. The metaverse providing unit also analyzes the user's behavioral data within the VR space and automatically suggests places and activities of interest. For example, if the user repeatedly performs a particular activity, it makes new suggestions related to that activity. This allows the system to provide a more personalized travel experience by analyzing the user's movements and behavior and automatically suggesting places and activities of interest.

[0075] The metaverse provider can track the user's gaze within the VR space and automatically provide information about what is in their line of sight. For example, the metaverse provider can track the user's gaze within the VR space and automatically provide information about tourist spots and activities in their line of sight. For example, it can display the history and background information of a building the user is looking at. The metaverse provider can also track the user's gaze and automatically provide information related to the object in their line of sight. For example, it can display an explanation of an artwork the user is looking at. The metaverse provider can also build a system that provides information of interest to the user in real time based on the gaze tracking data. For example, it can display information about events and activities related to the place the user is looking at. This allows the user to track their gaze and automatically provide information about what is in their line of sight, providing a more interactive travel experience.

[0076] The metaverse providing unit can use the emotion estimation function to analyze the user's emotions in the VR space in real time and enhance elements that elicit positive emotions. For example, the metaverse providing unit analyzes the user's facial expressions in the VR space in real time and enhances elements that elicit positive emotions. For example, it highlights places and activities where the user smiles. The metaverse providing unit also analyzes the user's vocal tone in real time and enhances elements that elicit positive emotions. For example, it highlights places and activities where the user makes an excited voice. The metaverse providing unit also integrates facial expression and voice data to analyze the user's emotions in real time and enhance elements that elicit positive emotions. For example, it highlights places and activities that the user enjoyed the most. In this way, a better travel experience can be provided by analyzing the user's emotions in real time and enhancing elements that elicit positive emotions.

[0077] The metaverse provider can collect user behavior data within the VR space and reflect it in the user's next travel experience. For example, the metaverse provider can collect the user's movement patterns and gaze data within the VR space and reflect it in the user's next travel experience. For example, the metaverse provider can reflect the user's frequently visited places and activities of interest in the next travel experience suggestions. The metaverse provider can also analyze the user's behavior data and build a system that makes optimal suggestions for the user's next travel experience. For example, the metaverse provider can suggest the user's next travel destination based on the user's preferred theme or style. The metaverse provider can also collect user behavior data within the VR space over the long term and track changes in the user's preferences and interests. For example, the metaverse provider can identify user preference trends based on past data and reflect them in the user's next travel experience. This allows the user to provide a more personalized travel experience by collecting user behavior data and reflecting it in the user's next travel experience.

[0078] The metaverse providing unit can provide a function that records a user's experience in a VR space and allows them to re-experience it later. The metaverse providing unit provides, for example, a function that records a user's experience in a VR space and allows them to re-experience it later. For example, it can record places a user has visited or activities a user has performed and allow them to play them back later. The metaverse providing unit also provides a function that edits the recorded experience and allows the user to re-experience their favorite parts. For example, it can select and play specific places or activities. The metaverse providing unit also provides a function that allows the user to share the recorded experience with other users. For example, it can allow the user to share their experience on a social networking site and allow other users to play that experience. This allows the user to record their experience and re-experience it later, thereby providing a deeper travel experience.

[0079] The metaverse provider can use the emotion estimation function to analyze the user's emotions in the VR space in real time and dynamically adjust the elements of the experience. For example, the metaverse provider can analyze the user's facial expressions in the VR space in real time and adjust the elements of the experience according to the emotions. For example, if the user is relaxed, it can emphasize quiet scenery and sounds. The metaverse provider can also analyze the user's voice tone in real time and adjust the elements of the experience according to the emotions. For example, if the user is excited, it can add active activities. The metaverse provider can also integrate facial and voice data, analyze the user's emotions in real time, and dynamically adjust the elements of the experience. For example, it can update the elements of the experience whenever the user's emotions change. This allows the user's emotions to be analyzed in real time and the elements of the experience to be dynamically adjusted, providing a more adaptive travel experience.

[0080] The metaverse provider can provide the wealthy with experiences of specific luxury resorts and private tours. For example, the metaverse provider provides virtual tours of specific luxury resorts for the wealthy. For example, it recreates the experience of a private beach or luxury spa in a VR space. The metaverse provider also provides private tour experiences for the wealthy. For example, it recreates special tourist spots and activities guided by a dedicated guide in a VR space. The metaverse provider also provides a function that allows the wealthy to customize the experience of specific luxury resorts and private tours. For example, the user can select the tour content according to their preferences. This makes it possible to provide a more luxurious travel experience by providing the wealthy with experiences of specific luxury resorts and private tours.

[0081] The metaverse providing unit can automatically generate special videos and photos for users who want to share on social media. The metaverse providing unit provides, for example, a function to automatically generate special videos and photos for users who want to share on social media. For example, it can compile videos and photos that highlight the places the user has visited or the activities they have performed. The metaverse providing unit also provides a function to add the user's name and message to the videos and photos to be shared. For example, the user can insert their name and message into the video or photo. The metaverse providing unit also provides a function to directly post videos and photos to be shared to social media. For example, the user can share the generated videos and photos on social media with one click. This makes it possible to provide a travel experience that is easier to share by automatically generating special videos and photos for users who want to share on social media.

[0082] The metaverse providing unit can use the emotion estimation function to analyze the emotional response of each target and provide an optimal experience. The metaverse providing unit, for example, uses the emotion estimation function to analyze the emotional response of each target in real time and provide an optimal experience. For example, if the user is relaxed, it emphasizes quiet scenery and sounds. The metaverse providing unit also analyzes the emotional response of each target and enhances elements that elicit positive emotions. For example, if the user is excited, it adds active activities. The metaverse providing unit also analyzes the emotional response of each target based on the emotion estimation data and builds a system that provides an optimal experience. For example, it dynamically adjusts elements of the experience each time the user's emotions change. This makes it possible to provide a more personalized travel experience by analyzing the emotional response of each target and providing an optimal experience.

[0083] The metaverse providing unit can provide travel experiences with different themes and styles for each target. For example, the metaverse providing unit provides travel experiences with different themes for each target. For example, it might suggest luxury resorts for the wealthy, or unique tourist spots for those who like to share on social media. The metaverse providing unit also provides travel experiences with different styles for each target. For example, it might suggest adventure experiences for adventure lovers, or relaxation experiences for those who want to relax. The metaverse providing unit also provides a function that allows the theme and style of the travel experience to be customized according to the preferences of each target. For example, users can select the theme and style to suit their preferences. This makes it possible to provide a more personalized travel experience by providing travel experiences with different themes and styles for each target.

[0084] The metaverse providing unit can provide customization options according to the needs of each target. For example, the metaverse providing unit provides customization options according to the needs of each target. For example, it provides private tour options for wealthy customers and special video and photo options for those who like to share on social media. The metaverse providing unit also provides a function that allows the content of the travel experience to be customized according to the needs of each target. For example, users can select activities and tourist spots according to their preferences. The metaverse providing unit also builds a system that provides customization options according to the needs of each target in real time. For example, it dynamically adjusts customization options according to the user's emotions and preferences. This makes it possible to provide a more personalized travel experience by providing customization options according to the needs of each target.

[0085] The metaverse providing unit can use the emotion estimation function to analyze the emotional response of each target in real time and dynamically adjust the elements of the experience. The metaverse providing unit, for example, uses the emotion estimation function to analyze the emotional response of each target in real time and dynamically adjust the elements of the experience. For example, if the user is relaxed, it emphasizes quiet scenery and sounds. The metaverse providing unit also analyzes the emotional response of each target and strengthens elements that elicit positive emotions. For example, if the user is excited, it adds active activities. The metaverse providing unit also builds a system that analyzes the emotional response of each target based on the emotion estimation data and dynamically adjusts the elements of the experience. For example, the elements of the experience are updated every time the user's emotions change. In this way, a more personalized travel experience can be provided by analyzing the emotional response of each target in real time and dynamically adjusting the elements of the experience.

[0086] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0087] The travel experience system can further include a health management unit that monitors the user's health condition. For example, the system can monitor the user's heart rate and blood pressure in real time and provide a travel plan that matches the user's health condition. For example, if the user's heart rate is high, the system can suggest relaxing activities, and if the user's blood pressure is stable, the system can suggest active activities. The health management unit can also provide a travel plan that takes into account the user's dietary restrictions and allergy information. For example, the health management unit can suggest restaurants and meal plans that avoid certain ingredients. Furthermore, the health management unit can provide a travel plan that includes an appropriate amount of exercise based on the user's exercise history. For example, the system can suggest activities such as walking and hiking. This makes it possible to provide a travel experience that takes the user's health condition into consideration.

[0088] The travel experience system can further include a learning analysis unit that analyzes the user's learning history. For example, the system can suggest related travel destinations based on information about history and culture that the user has previously studied. For example, if the user has studied the history of ancient Egypt, the system can suggest Egyptian pyramids and museums. The learning analysis unit can also suggest travel destinations based on the user's academic field of interest. For example, if a user is interested in astronomy, the system can suggest observatories and places where they can observe the stars. Furthermore, the learning analysis unit can combine the user's learning history with their travel experience to provide travel plans that are both educational and enjoyable. For example, the system can suggest plans that incorporate local guided tours and workshops. This makes it possible to provide a travel experience that takes the user's learning history into consideration.

[0089] The travel experience system can further include a hobby and special skill analysis unit that takes into account the user's hobbies and special skills. For example, if the user's hobby is photography, the system can suggest photogenic spots. For example, it can suggest places with beautiful scenery and architecture. If the user's special skill is cooking, the hobby and special skill analysis unit can also suggest local cooking classes and food markets. For example, it can provide an experience of cooking with a local chef. Furthermore, the hobby and special skill analysis unit can also suggest special events and workshops based on the user's hobbies and special skills. For example, if a user is interested in art, it can suggest local art galleries and art workshops. This makes it possible to provide a travel experience that takes the user's hobbies and special skills into consideration.

[0090] The travel experience system can further include an emotion analysis unit that estimates the user's emotions and suggests travel destinations based on the estimated emotions. For example, if the user is feeling stressed, the emotion analysis unit can suggest travel destinations where the user can relax, such as hot spring resorts or places rich in nature. If the user is excited, the emotion analysis unit can also suggest travel destinations where the user can enjoy active activities, such as adventure parks or sporting events. Furthermore, the emotion analysis unit can dynamically adjust the travel plan according to changes in the user's emotions. For example, if the user is relaxing during the trip, the emotion analysis unit can add even more relaxing activities. This makes it possible to provide a travel experience that takes the user's emotions into consideration.

[0091] The travel experience system can further include a travel history analysis unit that suggests the user's next travel destination based on the user's past travel experiences. For example, the system analyzes the places the user has visited in the past and the activities they have experienced, and suggests similar travel destinations. For example, if a user has visited a beach resort in the past, other beach resorts will be suggested. The travel history analysis unit can also suggest the user's next travel destination based on the user's ratings and impressions of places they have visited in the past. For example, it can suggest travel destinations similar to places that the user has given high ratings in the past. Furthermore, the travel history analysis unit can combine the user's past travel experiences with their current preferences to provide an optimal travel plan. For example, it can suggest travel destinations that take into account the places the user has visited in the past and their current preferences. This makes it possible to provide a travel experience that takes into account the user's past travel experiences.

[0092] The travel experience system may further include an emotional activity analysis unit that estimates the user's emotions and suggests activities during the trip based on the estimated emotions. For example, if the user is relaxed, a relaxation activity may be suggested, such as a spa or yoga session. The emotional activity analysis unit may also suggest active activities, such as hiking or water sports, if the user is excited. Furthermore, the emotional activity analysis unit may dynamically adjust the order and content of activities according to changes in the user's emotions. For example, if the user is relaxed during the trip, a relaxation activity may be suggested first. This makes it possible to provide an activity experience that takes the user's emotions into consideration.

[0093] The travel experience system may further include an emotional meal analysis unit that estimates the user's emotions and suggests meal plans for the trip based on the estimated emotions. For example, if the user is relaxed, restaurants with a relaxing atmosphere may be suggested. For example, quiet cafes or restaurants surrounded by nature may be suggested. Furthermore, if the user is excited, the emotional meal analysis unit may suggest lively restaurants or bars. For example, restaurants or bars with live music may be suggested. Furthermore, the emotional meal analysis unit may dynamically adjust the meal plan according to changes in the user's emotions. For example, if the user is relaxed during the trip, a meal plan that allows for relaxation may be suggested preferentially. This allows for a meal experience that takes the user's emotions into consideration.

[0094] The travel experience system may further include an emotional accommodation analysis unit that estimates the user's emotions and suggests lodging options during the trip based on the estimated emotions. For example, if the user is relaxed, a quiet lodging option may be suggested. For example, a resort surrounded by nature or a quiet hotel may be suggested. The emotional accommodation analysis unit may also suggest a lively lodging option if the user is excited. For example, a hotel in the city center or a lodging option with a fun nightlife may be suggested. Furthermore, the emotional accommodation analysis unit may dynamically adjust the selection of lodging options according to changes in the user's emotions. For example, if the user is relaxing during the trip, relaxing lodging options may be suggested preferentially. This makes it possible to provide a lodging experience that takes the user's emotions into consideration.

[0095] The travel experience system may further include an emotional entertainment analysis unit that estimates the user's emotions and suggests entertainment during the trip based on the estimated emotions. For example, if the user is relaxed, relaxation entertainment may be suggested, such as a quiet music concert or a movie. The emotional entertainment analysis unit may also suggest active entertainment, such as a live performance or a sporting event, if the user is excited. Furthermore, the emotional entertainment analysis unit may dynamically adjust the content of the entertainment according to changes in the user's emotions. For example, if the user is relaxing during the trip, relaxation entertainment may be suggested first. This makes it possible to provide an entertainment experience that takes the user's emotions into consideration.

[0096] The travel experience system can further include a theme travel unit that provides travel plans based on specific themes based on the user's preferences. For example, if the user is interested in history, the theme travel unit can suggest a plan to visit historical tourist sites. For example, a plan to visit ancient ruins and historical buildings can be provided. If the user likes nature, the theme travel unit can also suggest a plan to fully enjoy nature. For example, a plan to visit national parks and nature reserves can be provided. Furthermore, the theme travel unit can also provide plans that incorporate events and activities based on specific themes based on the user's preferences. For example, a plan to visit music festivals and art exhibitions can be provided. In this way, a theme travel experience can be provided that suits the user's preferences.

[0097] The processing flow of the second embodiment will be briefly explained below.

[0098] Step 1: The preference hearing unit hears about the user's preferences. For example, it can conduct a survey of the user and ask about their favorite travel destinations and experiences. It can also analyze the user's past travel history and social media posts to automatically extract preference trends. It can also analyze the user's music and movie preferences and generate travel destination images based on them. Step 2: The travel space generation unit generates a travel space based on the information gathered by the preference hearing unit. For example, the generation AI generates images and sounds of travel destinations based on questionnaire information collected from users. It can also provide information about the history and culture of the travel destination in the form of images and sounds, depending on the user's preferences. Furthermore, by incorporating the user's name and personal elements into the generated images and sounds, it is possible to provide a more personalized experience. Step 3: The real-time preference understanding unit measures the user's brain waves and facial expressions during the trip to understand their preferences in real time. For example, it measures the user's brain waves and facial expressions to understand their preferences in real time. It can also measure the user's heart rate and electrodermal activity to perform more detailed emotional analysis. Furthermore, it can dynamically change the travel space scenario based on the user's real-time reactions. Step 4: The metaverse provider provides the generated travel space in the metaverse space. For example, the generated travel space is provided to the user in the metaverse (VR) space. This allows a travel space based on the user's preferences to be generated and provided in the metaverse space, providing an immersive travel experience.

[0099] 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.

[0100] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0101] 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.

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

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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).

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

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

[0115] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0116] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is 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.

[0117] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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).

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] In the headset type terminal 314, 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. 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 specific processing unit 290 using these models.

[0128] 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.

[0129] 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.

[0130] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0131] 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.

[0132] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0133] 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.

[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 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.

[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 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).

[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] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] In the robot 414, 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 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 processing similar to that of the specific processing unit 290 using these models.

[0144] 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.

[0145] 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.

[0146] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AI other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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).

[0152] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0153] 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."

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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. [Explanation of symbols]

[0166] 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 preference hearing unit that hears user preferences; a travel space generation unit that generates a travel space based on the information heard by the preference hearing unit; a real-time preference understanding unit that measures the user's brain waves and facial expressions during the trip and understands the user's preferences in real time; a metaverse providing unit that provides the generated travel space in a metaverse space; A system characterized by:

2. The preference hearing unit Analyze the user's past travel history and social media posts to automatically extract preference trends.

2. The system of claim 1.

3. The preference hearing unit Analyzing the user's music and movie preferences and generating travel destination images based on them 2. The system of claim 1.

4. The preference hearing unit Analyze the user's emotions when answering the survey and add questions that elicit positive emotions.

2. The system of claim 1.

5. The preference hearing unit The preferences of the user's friends and family are also collected at the same time to generate a group travel plan.

2. The system of claim 1.

Images