System

Abstract

An object of a system according to an embodiment is to propose an optimal travel plan on the basis of preferences and interests of a user and cause the user to experience the travel plan in a virtual space.SOLUTION: A system according to an embodiment includes a preference analysis unit, a travel plan suggestion unit, a virtual experience providing unit, and a shared experience unit. The preference analysis unit analyzes preferences and interests of the user. The travel plan suggestion unit suggests an optimal travel plan based on the information analyzed by the preference analysis unit. The virtual experience providing portion causes the user to experience the travel plan suggested by the travel plan suggestion portion in the virtual space. The shared experience unit shares the virtual travel experience provided by the virtual experience providing unit with other users.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 not adequately proposed optimal travel plans based on users' preferences and interests and allowed them to experience them in virtual spaces, so there is room for improvement.

[0005] The system according to the embodiment aims to propose an optimal travel plan based on the user's preferences and interests and allow the user to experience it in a virtual space. [Means for solving the problem]

[0006] The system according to the embodiment includes a preference analysis unit, a travel plan proposal unit, a virtual experience provision unit, and a shared experience unit. The preference analysis unit analyzes a user's preferences and interests. The travel plan proposal unit proposes an optimal travel plan based on the information analyzed by the preference analysis unit. The virtual experience provision unit allows the user to experience the travel plan proposed by the travel plan proposal unit in a virtual space. The shared experience unit shares the virtual travel experience provided by the virtual experience provision unit with other users. [Effects of the Invention]

[0007] The system according to the embodiment can propose an optimal travel plan based on the user's preferences and interests, and allow the user to experience it in a virtual space. [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) The travel experience system according to the embodiment of the present invention is a system that allows users to enjoy traveling anywhere, anytime, with anyone, regardless of location or time. This allows users to enjoy a realistic travel experience without actually traveling.

[0029] A travel experience system according to an embodiment includes a preference analysis unit, a travel plan proposal unit, a virtual experience provision unit, and a shared experience unit. The preference analysis unit analyzes a user's preferences and interests. For example, the preference analysis unit analyzes the user's past travel history, interests, and preferences. The preference analysis unit can also analyze public information such as the user's social media accounts and blogs. The preference analysis unit can also analyze the user's daily behavioral patterns and hobbies and preferences. The travel plan proposal unit proposes an optimal travel plan based on the information analyzed by the preference analysis unit. For example, the travel plan proposal unit proposes an optimal travel plan based on the user's past travel history, interests, and preferences. The travel plan proposal unit can also propose a customized travel plan based on user feedback and new interests. The travel plan proposal unit can also use a user emotion estimation function to consider the user's emotional state when proposing a travel plan and generate a plan that elicits the most positive response. The virtual experience provision unit allows the user to experience the travel plan proposed by the travel plan proposal unit in a virtual space. For example, the virtual experience providing unit allows a user to wear a VR headset and visit tourist spots or enjoy activities in a virtual space. The virtual experience providing unit can also use an emotion estimation function to analyze the user's emotions during the virtual trip in real time and dynamically change the experience content. The virtual experience providing unit can also monitor the user's physical reactions (heart rate, body temperature, etc.) during the virtual trip to enhance the realism of the experience. The virtual experience providing unit can also introduce a haptic feedback device that the user can actually touch to the virtual trip experience, providing a more realistic experience. The shared experience unit shares the virtual trip experience provided by the virtual experience providing unit with other users. For example, the shared experience unit allows a user to enjoy a trip in a virtual space with friends or family. The shared experience unit can also use the emotion estimation function to analyze the emotional synchronization rate between users during the shared experience, providing a more unified experience. The shared experience unit can also analyze communication between users using natural language processing technology to suggest appropriate topics and activities during the shared experience.The shared experience unit can also add a real-time translation function to enable smooth communication between users who speak different languages ​​during the shared experience. This allows the travel experience system according to the embodiment to allow users to enjoy traveling with anyone, anywhere, anytime, regardless of location or time. For example, a busy businessman can enjoy a virtual trip to refresh himself during work, or he can enjoy a trip with family members who live far away. Furthermore, new discoveries and learning can be made through interactions with people of different cultures and languages.

[0030] The preference analysis unit can analyze the user's past travel history, interests, and preferences to propose optimal travel plans. The preference analysis unit, for example, analyzes the user's past travel history to propose optimal travel plans. For example, it proposes optimal travel destinations and plans based on data such as places the user has visited in the past, favorite activities, and foods. The preference analysis unit also analyzes the user's interests and preferences and proposes travel plans based on the analysis. For example, it proposes plans that include tourist spots and activities that the user is interested in. The preference analysis unit can also use a user emotion estimation function to consider the user's emotional state when proposing travel plans and generate plans that elicit the most positive response. This makes it possible to propose optimal travel plans based on the user's past travel history, interests, and preferences.

[0031] The virtual experience providing unit allows a user to visit tourist spots and enjoy activities in a virtual space by wearing a VR headset. For example, the virtual experience providing unit allows a user to visit tourist spots in a virtual space by wearing a VR headset. For example, the user can visit famous tourist spots in the virtual space by wearing a VR headset. Furthermore, the virtual experience providing unit allows a user to enjoy activities in the virtual space by wearing a VR headset. For example, the user can enjoy activities such as skydiving and scuba diving in the virtual space by wearing a VR headset. Furthermore, the virtual experience providing unit allows a user to enjoy traveling with friends and family in the virtual space by wearing a VR headset. For example, the user can visit tourist spots and enjoy activities with friends and family in the virtual space by wearing a VR headset. This allows a user to visit tourist spots and enjoy activities in the virtual space by wearing a VR headset.

[0032] The shared experience unit allows a user to enjoy a trip in a virtual space with friends and family. The shared experience unit allows a user to enjoy a trip in a virtual space with friends and family. For example, a user can visit tourist spots and enjoy activities in the virtual space with friends and family. Furthermore, when a user enjoys a trip in a virtual space with friends and family, the shared experience unit can use an emotion estimation function to analyze the emotional synchronization rate between users and provide a more unified experience. For example, if the emotional synchronization rate between users is high, the shared experience unit can provide an experience that users can easily empathize with. Furthermore, when a user enjoys a trip in a virtual space with friends and family, the shared experience unit can use natural language processing technology to analyze communication between users and suggest appropriate topics and activities. For example, the shared experience unit can suggest topics and activities of common interest based on the content of the users' conversations. This allows a user to enjoy a trip in a virtual space with friends and family.

[0033] The preference analysis unit can propose a customized travel plan based on the user's feedback and new interests. The preference analysis unit, for example, analyzes the user's feedback and proposes a customized travel plan. For example, if the user expresses interest in a particular tourist destination or activity, the preference analysis unit generates and proposes a new travel plan based on that information. The preference analysis unit also analyzes the user's new interests and proposes a customized travel plan based on them. For example, the preference analysis unit proposes a plan that includes tourist destinations or activities that the user has newly become interested in. The preference analysis unit can also dynamically adjust the travel plan based on the user's feedback and new interests. For example, if the user wants to change part of the travel plan, the entire plan is reconstructed according to the change. In this way, a customized travel plan can be proposed based on the user's feedback and new interests.

[0034] The preference analysis unit analyzes public information such as the user's social media accounts and blogs, and can propose travel plans that reflect more detailed interests and preferences. The preference analysis unit, for example, analyzes the user's social media posts to extract travel interests and preferences. For example, it generates travel plans based on tourist spots and activities frequently posted about by the user. The preference analysis unit also analyzes the user's blog posts to propose plans that reflect the user's past travel experiences and interests. For example, it generates plans that include tourist spots and restaurants introduced by the user in their blogs. The preference analysis unit also analyzes the user's interests and preferences in detail based on the public information and provides customized travel plans. For example, it adjusts the plan based on photos and comments shared by the user on social media. This makes it possible to analyze public information such as the user's social media accounts and blogs, and propose travel plans that reflect more detailed interests and preferences.

[0035] The preference analysis unit analyzes not only the user's past travel history but also their daily behavioral patterns and hobbies and preferences, allowing it to generate more personalized travel plans. For example, the preference analysis unit analyzes the user's daily behavioral patterns and reflects them in the travel plan. For example, if the user enjoys outdoor activities on weekends, it will suggest a plan to enjoy nature. The preference analysis unit also customizes the travel plan based on the user's hobbies and preferences. For example, if the user is interested in music festivals, it will generate a plan that includes music events in that area. The preference analysis unit also integrates the user's past travel history and daily behavioral data to suggest the optimal travel plan. For example, it will provide a plan that combines places the user has visited in the past with their daily hobbies. This allows it to generate more personalized travel plans by analyzing not only the user's past travel history but also their daily behavioral patterns and hobbies and preferences.

[0036] The preference analysis unit can provide a more intuitive interface using voice and gesture input when analyzing a user's preferences and interests. For example, when a user expresses their travel preferences through voice input, the AI ​​analyzes the information and proposes the optimal travel plan. For example, if the user says, "I want to go to a beach resort," a beach resort plan is generated. The preference analysis unit also uses gesture input to provide an interface that allows the user to intuitively communicate their travel preferences. For example, if the user points to a place they want to go on a map, a plan that includes that place is generated. The preference analysis unit also develops an interface that combines voice and gesture, allowing the user to communicate their travel preferences more naturally. For example, the user can express their preferences through voice while specifying details with gestures. This makes it possible to provide a more intuitive interface using voice and gesture input when analyzing a user's preferences and interests.

[0037] The preference analysis unit can analyze data of users of different age groups and cultural backgrounds and propose travel plans appropriate for each generation and culture. The preference analysis unit, for example, analyzes data of users of different age groups and proposes travel plans appropriate for each generation. For example, it provides plans including active activities for younger users and relaxing plans for seniors. The preference analysis unit also analyzes the cultural interests and habits of users to propose travel plans that take cultural backgrounds into consideration. For example, it generates plans that include festivals and events related to a particular culture. The preference analysis unit also analyzes user data in detail to provide customized travel plans appropriate for each age group and cultural background. For example, it proposes plans that include food and tourist spots from different cultures. This makes it possible to analyze data of users of different age groups and cultural backgrounds and propose travel plans appropriate for each generation and culture.

[0038] The virtual experience providing unit can monitor the user's physical reactions (heart rate, body temperature, etc.) during the virtual travel experience to improve the realism of the experience. The virtual experience providing unit can, for example, monitor the user's heart rate to improve the realism of the experience. For example, if the heart rate increases, the difficulty of the activity can be adjusted. The virtual experience providing unit can also monitor the user's body temperature to dynamically change the experience content. For example, if the body temperature increases, a scene of moving to a cooler place can be added. The virtual experience providing unit can also personalize the virtual travel experience based on the physical reaction data to improve the realism. For example, the experience content can be adjusted according to the user's physical reactions. This makes it possible to monitor the user's physical reactions and improve the realism of the experience.

[0039] The virtual experience providing unit can provide a more realistic experience by introducing a haptic feedback device that the user can actually touch during the virtual travel experience. The virtual experience providing unit, for example, uses the haptic feedback device to provide the user with the sensation of actually touching something during the virtual travel. For example, the sensation of walking on a sandy beach or touching water is reproduced. The virtual experience providing unit also introduces the haptic feedback device to enable the user to experience the sensation of touching an object during the virtual travel. For example, the sensation of touching an object in a virtual space is provided. The virtual experience providing unit also uses the haptic feedback device to realistically reproduce the sensations the user feels during the virtual travel. For example, the user can feel changes in wind and temperature through touch. This allows the introduction of a haptic feedback device that the user can actually touch to provide a more realistic experience.

[0040] The virtual experience providing unit applies the virtual travel experience to educational and training situations, allowing students to experience historical places and scientific phenomena. The virtual experience providing unit applies the virtual travel experience to educational situations, for example, allowing students to experience historical places. For example, an ancient Roman city could be recreated in a virtual space, allowing students to experience life in that era. The virtual experience providing unit also recreates scientific phenomena through virtual travel experiences, applying them to education. For example, a volcanic eruption or space exploration could be experienced in a virtual space. The virtual experience providing unit also applies the virtual travel experience to training situations, simulating real situations. For example, medical professionals could simulate surgery in a virtual space. In this way, the virtual travel experience can be applied to educational and training situations, allowing students to experience historical places and scientific phenomena.

[0041] The virtual experience providing unit can add a social function that allows the user to interact with other virtual travelers during the virtual travel experience. The virtual experience providing unit adds, for example, a social function that allows the user to chat with other virtual travelers in real time during the virtual travel experience. For example, they can talk while exploring tourist spots together. The virtual experience providing unit also provides a function that allows the user to enjoy activities collaboratively with other virtual travelers during the virtual travel experience. For example, they can play games together in a virtual space. The virtual experience providing unit also uses the social function to allow the user to share information with other travelers during the virtual travel. For example, they can share recommended spots in tourist spots. This makes it possible to add a social function that allows the user to interact with other virtual travelers during the virtual travel experience.

[0042] The shared experience unit can analyze communication between users during a shared experience using natural language processing technology and suggest appropriate topics and activities. For example, the shared experience unit can analyze conversations between users during a shared experience using natural language processing technology and suggest appropriate topics. For example, it can present topics of common interest. The shared experience unit can also use natural language processing technology to analyze communication between users and suggest related activities. For example, it can suggest tourist spots based on the content of the conversation. The shared experience unit can also analyze communication between users in real time during a shared experience and provide appropriate feedback. For example, it can adjust activities according to the flow of the conversation. In this way, it can analyze communication between users during a shared experience using natural language processing technology and suggest appropriate topics and activities.

[0043] The shared experience unit can analyze the user's behavioral patterns during the shared experience and promote interaction at the optimal timing. The shared experience unit, for example, analyzes the user's behavioral patterns during the shared experience and builds a system that promotes interaction at the optimal timing. For example, the shared experience unit suggests the next activity when the user finishes an activity. The shared experience unit also dynamically adjusts the content of the shared experience based on the user's behavioral patterns. For example, it prioritizes suggesting activities in which the user has shown interest. The shared experience unit also uses behavioral pattern analysis to provide feedback to promote interaction between users. For example, it suggests activities for users to engage in together. In this way, the user's behavioral patterns can be analyzed during the shared experience and promotion of interaction at the optimal timing.

[0044] The shared experience unit can apply the shared experience to business meetings and conferences, enabling real-time collaboration in a virtual space. The shared experience unit, for example, applies the shared experience to business meetings, building a system that enables real-time collaboration in a virtual space. For example, it supports presentations and discussions in a virtual conference room. The shared experience unit also applies the shared experience to conferences, providing a function that allows participants to interact in real time in a virtual space. For example, it supports exhibitions and networking in virtual booths. The shared experience unit also provides collaborative tools in the virtual space to enhance the shared experience in business meetings and conferences. For example, it adds a virtual whiteboard and collaborative editing function. This makes it possible to apply the shared experience to business meetings and conferences, enabling real-time collaboration in a virtual space.

[0045] The shared experience unit can add a real-time translation function so that users who speak different languages ​​can communicate smoothly during a shared experience. The shared experience unit, for example, provides a real-time translation function so that users who speak different languages ​​can communicate smoothly during a shared experience. For example, the content of a conversation can be automatically translated and displayed. The shared experience unit also uses the real-time translation function to support chats between users who speak different languages. For example, text messages can be translated in real time. The shared experience unit also adds a real-time translation function so that users who speak different languages ​​can enjoy an activity together during a shared experience. For example, instructions for a collaborative task can be translated and displayed. In this way, the real-time translation function can be added so that users who speak different languages ​​can communicate smoothly during a shared experience.

[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 may further include a health management unit. The health management unit monitors the user's health status and adjusts the travel plan. For example, the health management unit may monitor the user's heart rate and blood pressure and suggest a relaxation plan to avoid excessive stress. The health management unit may also consider the user's dietary restrictions and allergy information to suggest appropriate restaurants and meal plans. Furthermore, the health management unit may analyze the user's exercise habits and provide a plan that incorporates appropriate exercise during the trip. This allows the user to enjoy their trip while maintaining their health.

[0048] The travel experience system may further include an environmental consideration unit. The environmental consideration unit may evaluate the environmental impact of a travel plan and suggest eco-friendly plans. For example, the environmental consideration unit may suggest plans using public transportation or plans including local eco-tours. The environmental consideration unit may also provide information to raise the user's awareness of environmental protection. Furthermore, the environmental consideration unit may calculate the carbon footprint generated during the trip and suggest ways to offset it. This allows the user to enjoy a trip while being environmentally conscious.

[0049] The travel experience system may further include a cultural exchange section. The cultural exchange section provides information for the user to learn about the culture and customs of the region they are visiting. For example, it may suggest plans to participate in local festivals and events. The cultural exchange section may also provide opportunities for the user to interact with local people. For example, it may suggest plans for homestays or sightseeing with local guides. The cultural exchange section may also provide workshops and tours for the user to learn about the history and traditions of the region they are visiting. This allows the user to enjoy their trip through a deeper cultural experience.

[0050] The travel experience system may further include a safety management unit. The safety management unit provides information to ensure the user's safety. For example, the safety management unit provides security information for the area to be visited and emergency contact information. The safety management unit may also evaluate risks the user may encounter during the trip and suggest preventive measures. Furthermore, the safety management unit may provide first aid instructions and evacuation routes so that the user can respond to emergencies. This allows the user to enjoy their trip with peace of mind.

[0051] The travel experience system may further include a language support unit. The language support unit provides support for learning the language of the region the user is visiting. For example, the language support unit may provide online lessons for learning basic greetings and phrases. The language support unit may also provide translation apps and guidebooks to help the user communicate locally. The language support unit may also suggest language exchange programs to help the user interact smoothly with local people. This allows the user to enjoy traveling without language barriers.

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

[0053] Step 1: The preference analysis unit analyzes the user's preferences and interests. For example, it can analyze the user's past travel history, interests, and preferences, as well as public information on social media and blogs. It can also analyze the user's daily behavior patterns and hobbies and preferences. Step 2: The travel plan suggestion unit proposes optimal travel plans based on the information analyzed by the preference analysis unit. For example, it can propose optimal travel plans based on the user's past travel history, interests, and preferences, and can also propose customized travel plans based on the user's feedback and new interests. It can also use emotion estimation functionality to consider the user's emotional state when proposing travel plans, generating plans that will elicit the most positive response. Step 3: The virtual experience provider allows the user to experience the travel plan proposed by the travel plan suggestor in a virtual space. For example, by wearing a VR headset, the user can visit tourist spots and enjoy activities in the virtual space. The emotion estimation function can also be used to analyze the emotions the user feels during the virtual trip in real time and dynamically change the content of the experience. Furthermore, the system can monitor the user's physical reactions (heart rate, body temperature, etc.) to enhance the realism of the experience. A haptic feedback device can also be introduced to provide a more realistic experience. Step 4: The shared experience unit shares the virtual travel experience provided by the virtual experience provider with other users. For example, a user can enjoy traveling in a virtual space with friends and family. The emotion estimation function can also be used to analyze the emotional synchronization rate between users during the shared experience, providing a more unified experience. Furthermore, natural language processing technology can be used to analyze communication between users, suggesting appropriate topics and activities. A real-time translation function can also be added to enable smooth communication between users who speak different languages.

[0054] (Example 2) The travel experience system according to the embodiment of the present invention is a system that allows users to enjoy traveling anywhere, anytime, with anyone, regardless of location or time. This allows users to enjoy a realistic travel experience without actually traveling.

[0055] A travel experience system according to an embodiment includes a preference analysis unit, a travel plan proposal unit, a virtual experience provision unit, and a shared experience unit. The preference analysis unit analyzes a user's preferences and interests. For example, the preference analysis unit analyzes the user's past travel history, interests, and preferences. The preference analysis unit can also analyze public information such as the user's social media accounts and blogs. The preference analysis unit can also analyze the user's daily behavioral patterns and hobbies and preferences. The travel plan proposal unit proposes an optimal travel plan based on the information analyzed by the preference analysis unit. For example, the travel plan proposal unit proposes an optimal travel plan based on the user's past travel history, interests, and preferences. The travel plan proposal unit can also propose a customized travel plan based on user feedback and new interests. The travel plan proposal unit can also use a user emotion estimation function to consider the user's emotional state when proposing a travel plan and generate a plan that elicits the most positive response. The virtual experience provision unit allows the user to experience the travel plan proposed by the travel plan proposal unit in a virtual space. For example, the virtual experience providing unit allows a user to wear a VR headset and visit tourist spots or enjoy activities in a virtual space. The virtual experience providing unit can also use an emotion estimation function to analyze the user's emotions during the virtual trip in real time and dynamically change the experience content. The virtual experience providing unit can also monitor the user's physical reactions (heart rate, body temperature, etc.) during the virtual trip to enhance the realism of the experience. The virtual experience providing unit can also introduce a haptic feedback device that the user can actually touch to the virtual trip experience, providing a more realistic experience. The shared experience unit shares the virtual trip experience provided by the virtual experience providing unit with other users. For example, the shared experience unit allows a user to enjoy a trip in a virtual space with friends or family. The shared experience unit can also use the emotion estimation function to analyze the emotional synchronization rate between users during the shared experience, providing a more unified experience. The shared experience unit can also analyze communication between users using natural language processing technology to suggest appropriate topics and activities during the shared experience.The shared experience unit can also add a real-time translation function to enable smooth communication between users who speak different languages ​​during the shared experience. This allows the travel experience system according to the embodiment to allow users to enjoy traveling with anyone, anywhere, anytime, regardless of location or time. For example, a busy businessman can enjoy a virtual trip to refresh himself during work, or he can enjoy a trip with family members who live far away. Furthermore, new discoveries and learning can be made through interactions with people of different cultures and languages.

[0056] The preference analysis unit can analyze the user's past travel history, interests, and preferences to propose optimal travel plans. The preference analysis unit, for example, analyzes the user's past travel history to propose optimal travel plans. For example, it proposes optimal travel destinations and plans based on data such as places the user has visited in the past, favorite activities, and foods. The preference analysis unit also analyzes the user's interests and preferences and proposes travel plans based on the analysis. For example, it proposes plans that include tourist spots and activities that the user is interested in. The preference analysis unit can also use a user emotion estimation function to consider the user's emotional state when proposing travel plans and generate plans that elicit the most positive response. This makes it possible to propose optimal travel plans based on the user's past travel history, interests, and preferences.

[0057] The virtual experience providing unit allows a user to visit tourist spots and enjoy activities in a virtual space by wearing a VR headset. For example, the virtual experience providing unit allows a user to visit tourist spots in a virtual space by wearing a VR headset. For example, the user can visit famous tourist spots in the virtual space by wearing a VR headset. Furthermore, the virtual experience providing unit allows a user to enjoy activities in the virtual space by wearing a VR headset. For example, the user can enjoy activities such as skydiving and scuba diving in the virtual space by wearing a VR headset. Furthermore, the virtual experience providing unit allows a user to enjoy traveling with friends and family in the virtual space by wearing a VR headset. For example, the user can visit tourist spots and enjoy activities with friends and family in the virtual space by wearing a VR headset. This allows a user to visit tourist spots and enjoy activities in the virtual space by wearing a VR headset.

[0058] The shared experience unit allows a user to enjoy a trip in a virtual space with friends and family. The shared experience unit allows a user to enjoy a trip in a virtual space with friends and family. For example, a user can visit tourist spots and enjoy activities in the virtual space with friends and family. Furthermore, when a user enjoys a trip in a virtual space with friends and family, the shared experience unit can use an emotion estimation function to analyze the emotional synchronization rate between users and provide a more unified experience. For example, if the emotional synchronization rate between users is high, the shared experience unit can provide an experience that users can easily empathize with. Furthermore, when a user enjoys a trip in a virtual space with friends and family, the shared experience unit can use natural language processing technology to analyze communication between users and suggest appropriate topics and activities. For example, the shared experience unit can suggest topics and activities of common interest based on the content of the users' conversations. This allows a user to enjoy a trip in a virtual space with friends and family.

[0059] The preference analysis unit can propose a customized travel plan based on the user's feedback and new interests. The preference analysis unit, for example, analyzes the user's feedback and proposes a customized travel plan. For example, if the user expresses interest in a particular tourist destination or activity, the preference analysis unit generates and proposes a new travel plan based on that information. The preference analysis unit also analyzes the user's new interests and proposes a customized travel plan based on them. For example, the preference analysis unit proposes a plan that includes tourist destinations or activities that the user has newly become interested in. The preference analysis unit can also dynamically adjust the travel plan based on the user's feedback and new interests. For example, if the user wants to change part of the travel plan, the entire plan is reconstructed according to the change. In this way, a customized travel plan can be proposed based on the user's feedback and new interests.

[0060] The preference analysis unit uses the user's emotion estimation function to consider the user's emotional state when proposing a travel plan and generate a plan that elicits the most positive response. The preference analysis unit, for example, analyzes the user's emotional state in real time and proposes a travel plan that strongly reflects positive emotions. For example, if the user feels like relaxing, it generates a plan that includes resorts and spas. The preference analysis unit also uses the emotion estimation function to identify travel destinations and activities that the user has previously felt positive about and proposes a new travel plan based on that. For example, it generates a plan that includes activities that the user has previously enjoyed. The preference analysis unit also dynamically adjusts travel plan options based on the user's emotion data and provides a plan that elicits the most positive response. For example, it analyzes the emotion data each time the user changes an option and presents the optimal plan. This makes it possible to generate a plan that elicits the most positive response by considering the user's emotional state.

[0061] The preference analysis unit analyzes public information such as the user's social media accounts and blogs, and can propose travel plans that reflect more detailed interests and preferences. The preference analysis unit, for example, analyzes the user's social media posts to extract travel interests and preferences. For example, it generates travel plans based on tourist spots and activities frequently posted about by the user. The preference analysis unit also analyzes the user's blog posts to propose plans that reflect the user's past travel experiences and interests. For example, it generates plans that include tourist spots and restaurants introduced by the user in their blogs. The preference analysis unit also analyzes the user's interests and preferences in detail based on the public information and provides customized travel plans. For example, it adjusts the plan based on photos and comments shared by the user on social media. This makes it possible to analyze public information such as the user's social media accounts and blogs, and propose travel plans that reflect more detailed interests and preferences.

[0062] The preference analysis unit analyzes not only the user's past travel history but also their daily behavioral patterns and hobbies and preferences, allowing it to generate more personalized travel plans. For example, the preference analysis unit analyzes the user's daily behavioral patterns and reflects them in the travel plan. For example, if the user enjoys outdoor activities on weekends, it will suggest a plan to enjoy nature. The preference analysis unit also customizes the travel plan based on the user's hobbies and preferences. For example, if the user is interested in music festivals, it will generate a plan that includes music events in that area. The preference analysis unit also integrates the user's past travel history and daily behavioral data to suggest the optimal travel plan. For example, it will provide a plan that combines places the user has visited in the past with their daily hobbies. This allows it to generate more personalized travel plans by analyzing not only the user's past travel history but also their daily behavioral patterns and hobbies and preferences.

[0063] The preference analysis unit can provide a more intuitive interface using voice and gesture input when analyzing a user's preferences and interests. For example, when a user expresses their travel preferences through voice input, the AI ​​analyzes the information and proposes the optimal travel plan. For example, if the user says, "I want to go to a beach resort," a beach resort plan is generated. The preference analysis unit also uses gesture input to provide an interface that allows the user to intuitively communicate their travel preferences. For example, if the user points to a place they want to go on a map, a plan that includes that place is generated. The preference analysis unit also develops an interface that combines voice and gesture, allowing the user to communicate their travel preferences more naturally. For example, the user can express their preferences through voice while specifying details with gestures. This makes it possible to provide a more intuitive interface using voice and gesture input when analyzing a user's preferences and interests.

[0064] The preference analysis unit can analyze data of users of different age groups and cultural backgrounds and propose travel plans appropriate for each generation and culture. The preference analysis unit, for example, analyzes data of users of different age groups and proposes travel plans appropriate for each generation. For example, it provides plans including active activities for younger users and relaxing plans for seniors. The preference analysis unit also analyzes the cultural interests and habits of users to propose travel plans that take cultural backgrounds into consideration. For example, it generates plans that include festivals and events related to a particular culture. The preference analysis unit also analyzes user data in detail to provide customized travel plans appropriate for each age group and cultural background. For example, it proposes plans that include food and tourist spots from different cultures. This makes it possible to analyze data of users of different age groups and cultural backgrounds and propose travel plans appropriate for each generation and culture.

[0065] The preference analysis unit uses the emotion estimation function to monitor the emotional reactions of the user when selecting a travel plan in real time and dynamically adjust the optimal plan. For example, the preference analysis unit monitors the emotional reactions of the user when selecting a travel plan in real time and preferentially displays plans that elicit a strong positive reaction. For example, it recommends plans that elicit a smile from the user. The preference analysis unit also uses the emotion estimation function to analyze emotional data each time the user changes their options and dynamically adjust the optimal plan. For example, it highlights plans that the user is interested in. The preference analysis unit also builds a system that optimizes travel plan options in real time based on the user's emotional reactions. For example, it automatically suggests plans that elicit positive emotions from the user. This makes it possible to monitor the emotional reactions of the user when selecting a travel plan in real time and dynamically adjust the optimal plan.

[0066] The virtual experience providing unit can use the emotion estimation function to analyze the emotions felt by the user during the virtual trip in real time and dynamically change the experience content. For example, the virtual experience providing unit can analyze the emotions felt by the user during the virtual trip in real time and dynamically change the experience content to one that emphasizes more positive emotions. For example, if the user is enjoying themselves, the activity can be extended. Furthermore, the virtual experience providing unit can use the emotion estimation function to identify the cause of negative emotions felt by the user during the virtual trip and adjust the experience content. For example, if the user feels fear, the scene can be switched to one that is relaxing. Furthermore, the virtual experience providing unit can personalize the virtual travel experience based on the user's emotion data and provide optimal experience content. For example, if the user is excited, an active activity can be added. This allows the emotions felt by the user during the virtual trip to be analyzed in real time and the experience content to be dynamically changed.

[0067] The virtual experience providing unit can monitor the user's physical reactions (heart rate, body temperature, etc.) during the virtual travel experience to improve the realism of the experience. The virtual experience providing unit can, for example, monitor the user's heart rate to improve the realism of the experience. For example, if the heart rate increases, the difficulty of the activity can be adjusted. The virtual experience providing unit can also monitor the user's body temperature to dynamically change the experience content. For example, if the body temperature increases, a scene of moving to a cooler place can be added. The virtual experience providing unit can also personalize the virtual travel experience based on the physical reaction data to improve the realism. For example, the experience content can be adjusted according to the user's physical reactions. This makes it possible to monitor the user's physical reactions and improve the realism of the experience.

[0068] The virtual experience providing unit can provide a more realistic experience by introducing a haptic feedback device that the user can actually touch during the virtual travel experience. The virtual experience providing unit, for example, uses the haptic feedback device to provide the user with the sensation of actually touching something during the virtual travel. For example, the sensation of walking on a sandy beach or touching water is reproduced. The virtual experience providing unit also introduces the haptic feedback device to enable the user to experience the sensation of touching an object during the virtual travel. For example, the sensation of touching an object in a virtual space is provided. The virtual experience providing unit also uses the haptic feedback device to realistically reproduce the sensations the user feels during the virtual travel. For example, the user can feel changes in wind and temperature through touch. This allows the introduction of a haptic feedback device that the user can actually touch to provide a more realistic experience.

[0069] The virtual experience providing unit applies the virtual travel experience to educational and training situations, allowing students to experience historical places and scientific phenomena. The virtual experience providing unit applies the virtual travel experience to educational situations, for example, allowing students to experience historical places. For example, an ancient Roman city could be recreated in a virtual space, allowing students to experience life in that era. The virtual experience providing unit also recreates scientific phenomena through virtual travel experiences, applying them to education. For example, a volcanic eruption or space exploration could be experienced in a virtual space. The virtual experience providing unit also applies the virtual travel experience to training situations, simulating real situations. For example, medical professionals could simulate surgery in a virtual space. In this way, the virtual travel experience can be applied to educational and training situations, allowing students to experience historical places and scientific phenomena.

[0070] The virtual experience providing unit can add a social function that allows the user to interact with other virtual travelers during the virtual travel experience. The virtual experience providing unit adds, for example, a social function that allows the user to chat with other virtual travelers in real time during the virtual travel experience. For example, they can talk while exploring tourist spots together. The virtual experience providing unit also provides a function that allows the user to enjoy activities collaboratively with other virtual travelers during the virtual travel experience. For example, they can play games together in a virtual space. The virtual experience providing unit also uses the social function to allow the user to share information with other travelers during the virtual travel. For example, they can share recommended spots in tourist spots. This makes it possible to add a social function that allows the user to interact with other virtual travelers during the virtual travel experience.

[0071] The virtual experience providing unit can use the emotion estimation function to provide a function that allows a user to share emotions felt during a virtual trip and form an emotional connection with other users. For example, the virtual experience providing unit uses the emotion estimation function to build a system that allows a user to share emotions felt during a virtual trip in real time. For example, the user communicates the emotions that the user is enjoying to other users. The virtual experience providing unit also provides a function that allows a user to form an emotional connection with other users during a virtual trip based on the user's emotion data. For example, the virtual experience providing unit matches users who share the same emotions. The virtual experience providing unit also uses the emotion estimation function to visualize the emotions felt by the user during the virtual trip and strengthen the emotional connection with other users. For example, the emotion estimation function displays an emotion score to encourage empathy. In this way, the emotion estimation function can be used to provide a function that allows a user to share emotions felt during a virtual trip and form an emotional connection with other users.

[0072] The shared experience unit uses the emotion estimation function to analyze the emotional synchronization rate between users during a shared experience, thereby providing a more unified experience. The shared experience unit, for example, uses the emotion estimation function to analyze the emotional synchronization rate between users in real time during a shared experience. For example, the shared experience unit enhances the experience between users who share the same emotion. The shared experience unit also builds a system that dynamically adjusts the content of the shared experience based on the emotional synchronization rate between users. For example, the shared experience unit suggests a joint activity to users whose emotions are synchronized. The shared experience unit also analyzes the emotional synchronization rate and provides feedback to enhance the sense of unity between users. For example, the shared experience unit notifies users that their emotions are synchronized to encourage empathy. In this way, the emotion estimation function can be used to analyze the emotional synchronization rate between users during a shared experience, thereby providing a more unified experience.

[0073] The shared experience unit can analyze communication between users during a shared experience using natural language processing technology and suggest appropriate topics and activities. For example, the shared experience unit can analyze conversations between users during a shared experience using natural language processing technology and suggest appropriate topics. For example, it can present topics of common interest. The shared experience unit can also use natural language processing technology to analyze communication between users and suggest related activities. For example, it can suggest tourist spots based on the content of the conversation. The shared experience unit can also analyze communication between users in real time during a shared experience and provide appropriate feedback. For example, it can adjust activities according to the flow of the conversation. In this way, it can analyze communication between users during a shared experience using natural language processing technology and suggest appropriate topics and activities.

[0074] The shared experience unit can analyze the user's behavioral patterns during the shared experience and promote interaction at the optimal timing. The shared experience unit, for example, analyzes the user's behavioral patterns during the shared experience and builds a system that promotes interaction at the optimal timing. For example, the shared experience unit suggests the next activity when the user finishes an activity. The shared experience unit also dynamically adjusts the content of the shared experience based on the user's behavioral patterns. For example, it prioritizes suggesting activities in which the user has shown interest. The shared experience unit also uses behavioral pattern analysis to provide feedback to promote interaction between users. For example, it suggests activities for users to engage in together. In this way, the user's behavioral patterns can be analyzed during the shared experience and promotion of interaction at the optimal timing.

[0075] The shared experience unit can apply the shared experience to business meetings and conferences, enabling real-time collaboration in a virtual space. The shared experience unit, for example, applies the shared experience to business meetings, building a system that enables real-time collaboration in a virtual space. For example, it supports presentations and discussions in a virtual conference room. The shared experience unit also applies the shared experience to conferences, providing a function that allows participants to interact in real time in a virtual space. For example, it supports exhibitions and networking in virtual booths. The shared experience unit also provides collaborative tools in the virtual space to enhance the shared experience in business meetings and conferences. For example, it adds a virtual whiteboard and collaborative editing function. This makes it possible to apply the shared experience to business meetings and conferences, enabling real-time collaboration in a virtual space.

[0076] The shared experience unit can add a real-time translation function so that users who speak different languages ​​can communicate smoothly during a shared experience. The shared experience unit, for example, provides a real-time translation function so that users who speak different languages ​​can communicate smoothly during a shared experience. For example, the content of a conversation can be automatically translated and displayed. The shared experience unit also uses the real-time translation function to support chats between users who speak different languages. For example, text messages can be translated in real time. The shared experience unit also adds a real-time translation function so that users who speak different languages ​​can enjoy an activity together during a shared experience. For example, instructions for a collaborative task can be translated and displayed. In this way, the real-time translation function can be added so that users who speak different languages ​​can communicate smoothly during a shared experience.

[0077] The shared experience unit uses the emotion estimation function to visualize emotions felt by the user during the shared experience, thereby strengthening the emotional connection with other users. The shared experience unit, for example, uses the emotion estimation function to build a system that visualizes the emotions felt by the user during the shared experience in real time. For example, the emotion estimation function displays an emotion score and shares it with other users. The shared experience unit also provides feedback to strengthen the emotional connection during the shared experience based on the user's emotion data. For example, it displays a message encouraging empathy. The shared experience unit also uses the emotion estimation function to visualize the emotions felt by the user during the shared experience, thereby strengthening the emotional connection with other users. For example, it matches users with high emotion scores. In this way, the emotion estimation function can be used to visualize the emotions felt by the user during the shared experience, thereby strengthening the emotional connection with other users.

[0078] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0079] The travel experience system may further include a health management unit. The health management unit monitors the user's health status and adjusts the travel plan. For example, the health management unit may monitor the user's heart rate and blood pressure and suggest a relaxation plan to avoid excessive stress. The health management unit may also consider the user's dietary restrictions and allergy information to suggest appropriate restaurants and meal plans. Furthermore, the health management unit may analyze the user's exercise habits and provide a plan that incorporates appropriate exercise during the trip. This allows the user to enjoy their trip while maintaining their health.

[0080] The travel experience system may further include an environmental consideration unit. The environmental consideration unit may evaluate the environmental impact of a travel plan and suggest eco-friendly plans. For example, the environmental consideration unit may suggest plans using public transportation or plans including local eco-tours. The environmental consideration unit may also provide information to raise the user's awareness of environmental protection. Furthermore, the environmental consideration unit may calculate the carbon footprint generated during the trip and suggest ways to offset it. This allows the user to enjoy a trip while being environmentally conscious.

[0081] The travel experience system may further include a cultural exchange section. The cultural exchange section provides information for the user to learn about the culture and customs of the region they are visiting. For example, it may suggest plans to participate in local festivals and events. The cultural exchange section may also provide opportunities for the user to interact with local people. For example, it may suggest plans for homestays or sightseeing with local guides. The cultural exchange section may also provide workshops and tours for the user to learn about the history and traditions of the region they are visiting. This allows the user to enjoy their trip through a deeper cultural experience.

[0082] The travel experience system may further include a safety management unit. The safety management unit provides information to ensure the user's safety. For example, the safety management unit provides security information for the area to be visited and emergency contact information. The safety management unit may also evaluate risks the user may encounter during the trip and suggest preventive measures. Furthermore, the safety management unit may provide first aid instructions and evacuation routes so that the user can respond to emergencies. This allows the user to enjoy their trip with peace of mind.

[0083] The travel experience system may further include a language support unit. The language support unit provides support for learning the language of the region the user is visiting. For example, the language support unit may provide online lessons for learning basic greetings and phrases. The language support unit may also provide translation apps and guidebooks to help the user communicate locally. The language support unit may also suggest language exchange programs to help the user interact smoothly with local people. This allows the user to enjoy traveling without language barriers.

[0084] The travel experience system can further use emotion estimation to monitor a user's stress level and suggest relaxing activities. For example, if a user is feeling stressed, it can suggest a relaxing spa or yoga session. It can also use emotion estimation to identify activities the user enjoys and extend those activities. It can also use emotion estimation to identify the cause of anxiety if the user is feeling anxious and provide a reassuring environment. This allows the user to enjoy their trip while reducing stress.

[0085] The travel experience system can further use the emotion estimation function to adjust the timing of the trip based on the user's emotions. For example, if the user is tired, it can suggest a time to rest. Also, if the user is excited, it can use the emotion estimation function to add an activity to maintain that excitement. Furthermore, if the user is relaxed, it can use the emotion estimation function to provide an environment to maintain that state. This makes it possible to provide an optimal travel experience according to the user's emotions.

[0086] The travel experience system can further use the emotion estimation function to support the selection of a travel destination based on the user's emotions. For example, if the user feels like relaxing, a quiet resort can be suggested. If the user is seeking adventure, the emotion estimation function can also be used to suggest places where active activities can be enjoyed. Furthermore, if the user is seeking a cultural experience, the emotion estimation function can also be used to suggest historical tourist spots. This makes it possible to select the optimal travel destination based on the user's emotions.

[0087] The travel experience system can further use the emotion estimation function to adjust activities during the trip based on the user's emotions. For example, if the user is enjoying an activity, the activity can be extended. The emotion estimation function can also be used to suggest a time to rest if the user is tired. Furthermore, the emotion estimation function can also be used to identify the cause of anxiety if the user is feeling anxious and provide a reassuring environment. This makes it possible to provide the optimal activity according to the user's emotions.

[0088] The travel experience system can further use the emotion estimation function to collect travel feedback based on the user's emotions and reflect it in the next travel plan. For example, if the user expresses positive emotions toward a particular activity, the activity can be included in the next plan. Also, if the user expresses negative emotions, the emotion estimation function can be used to identify the cause and exclude it from the next plan. Furthermore, the emotion estimation function can be used to evaluate the user's overall satisfaction with the trip based on the user's emotion data and optimize the next plan. This allows feedback based on the user's emotions to be collected and reflected in the next travel plan.

[0089] The processing flow of the second embodiment will be briefly explained below.

[0090] Step 1: The preference analysis unit analyzes the user's preferences and interests. For example, it can analyze the user's past travel history, interests, and preferences, as well as public information on social media and blogs. It can also analyze the user's daily behavior patterns and hobbies and preferences. Step 2: The travel plan suggestion unit proposes optimal travel plans based on the information analyzed by the preference analysis unit. For example, it can propose optimal travel plans based on the user's past travel history, interests, and preferences, and can also propose customized travel plans based on the user's feedback and new interests. It can also use emotion estimation functionality to consider the user's emotional state when proposing travel plans, generating plans that will elicit the most positive response. Step 3: The virtual experience provider allows the user to experience the travel plan proposed by the travel plan suggestor in a virtual space. For example, by wearing a VR headset, the user can visit tourist spots and enjoy activities in the virtual space. The emotion estimation function can also be used to analyze the emotions the user feels during the virtual trip in real time and dynamically change the content of the experience. Furthermore, the system can monitor the user's physical reactions (heart rate, body temperature, etc.) to enhance the realism of the experience. A haptic feedback device can also be introduced to provide a more realistic experience. Step 4: The shared experience unit shares the virtual travel experience provided by the virtual experience provider with other users. For example, a user can enjoy traveling in a virtual space with friends and family. The emotion estimation function can also be used to analyze the emotional synchronization rate between users during the shared experience, providing a more unified experience. Furthermore, natural language processing technology can be used to analyze communication between users, suggesting appropriate topics and activities. A real-time translation function can also be added to enable smooth communication between users who speak different languages.

[0091] 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.

[0092] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0093] 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.

[0094] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0095] 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0096] 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.

[0097] 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.

[0098] 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.

[0099] 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).

[0100] 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.

[0101] 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.

[0102] 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.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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.

[0107] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0108] 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.

[0109] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0110] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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).

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] 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.

[0122] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0123] 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.

[0124] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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).

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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 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.

[0136] 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.

[0137] 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.

[0138] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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).

[0144] 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.

[0145] 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."

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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.

[0156] 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.

[0157] 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]

[0158] 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 analysis unit that analyzes user preferences and interests; a travel plan suggestion unit that suggests an optimal travel plan based on the information analyzed by the preference analysis unit; a virtual experience providing unit that allows the user to experience the travel plan proposed by the travel plan proposal unit in a virtual space; a shared experience unit that shares the virtual travel experience provided by the virtual experience providing unit with other users. A system characterized by:

2. The preference analysis unit Analyze the user's past travel history, interests, and preferences to propose optimal travel plans 2. The system of claim 1.

3. The virtual experience providing unit By wearing the VR headset, the user can visit tourist spots and enjoy activities in the virtual space.

2. The system of claim 1.

4. The shared experience unit includes: The user can enjoy traveling in the virtual space with friends and family.

2. The system of claim 1.

5. The preference analysis unit Suggesting customized travel plans based on the user's feedback and emerging interests 2. The system of claim 1.

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