System

Abstract

An object of a system according to an embodiment is to provide details of a trip without giving a prejudice to a user.SOLUTION: A system includes a user input unit, an analysis unit, and a generation unit. The user input unit allows a user to input a departure place and the number of staying days. The analysis unit analyzes the information input by the user input unit. The generation unit generates details of the trip using only words on the basis of the information analyzed by the analysis unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology provides travel details through images and detailed descriptions, which can create preconceived notions and diminish the excitement of the trip.

[0005] The system according to the embodiment aims to provide the user with travel details without preconceived ideas. [Means for solving the problem]

[0006] The system according to the embodiment includes a user input unit, an analysis unit, and a generation unit. The user input unit inputs the departure point and the number of days of stay. The analysis unit analyzes the information input by the user input unit. The generation unit generates travel details using only words based on the information analyzed by the analysis unit. [Effects of the Invention]

[0007] The system according to the embodiment can provide the travel details to the user without preconceived ideas. [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 an embodiment of the present invention allows users to simply input their departure point and number of days of stay, and the AI ​​generator will then create a travel plan using only words, evoking an unknown adventure. This allows the travel experience system to stimulate the user's imagination and provide an inspiring travel experience that is free from preconceptions.

[0029] A travel experience system according to an embodiment includes a user input unit, an analysis unit, and a generation unit. The user input unit allows a user to input a departure point and length of stay. For example, the user can specify the departure point and length of stay using text input, a drop-down menu, a calendar selection, or other methods. The analysis unit analyzes the information input by the user input unit. For example, the analysis unit may use natural language processing technology to analyze the user's input information and narrow down potential travel destinations. The analysis unit may also use data mining technology to analyze past travel data and propose optimal travel plans. Furthermore, the analysis unit may use machine learning algorithms to learn the user's preferences and trends and provide a more personalized travel experience. The generation unit generates travel details using only words based on the information analyzed by the analysis unit. For example, the generation AI may use text generation AI (e.g., LLM) to describe the scenery and experiences of the travel destination in words. The generation AI may also use multimodal generation AI to integrate data obtained from multiple sources to generate a more detailed description. For example, the generation AI generates a description in the form of, "You depart from Tokyo and arrive at a quiet village surrounded by beautiful mountains. In the center of the village there is an old church, surrounded by colorful flowers." This allows the travel experience system according to the embodiment to easily make travel plans and provide a travel experience that is free from preconceptions.

[0030] The user input unit can accept voice input and analyze the input using voice recognition technology. For example, when a user uses a smartphone or microphone to voice-input "a three-day trip from Tokyo," the voice recognition technology converts the input into text and the system analyzes it. If a user speaks, "A two-night, three-day trip to Kyoto next weekend," the voice recognition technology accurately recognizes the input and allows the system to create a travel plan. If a user speaks, "A five-day trip to Hokkaido at the beginning of next month," the voice recognition technology analyzes the input and the system generates an appropriate travel plan. This allows users to easily plan their travel plans using their voice.

[0031] The analysis unit can learn the user's past travel history and preferences and suggest the optimal departure point and length of stay. For example, the analysis unit stores the user's past travel destinations and length of stay in a database and suggests the next travel plan based on that information. For example, if a user has previously visited hot spring resorts, a new hot spring resort will be suggested. The analysis unit also analyzes the user's past travel history and automatically learns the user's preferred travel destinations and length of stay. For example, if a user likes places rich in nature, a natural destination will be suggested for the next trip. Furthermore, the analysis unit suggests the optimal departure point and length of stay based on the user's preferences and past travel history. For example, if a user has preferred short trips in the past, a short trip will be suggested for the next trip as well. This makes it possible to suggest optimal travel plans based on the user's preferences.

[0032] The user input unit may be equipped with a collaboration function that allows users to jointly plan trips with friends and family. The user input unit provides, for example, a collaboration function that allows users to jointly plan trips with friends and family. For example, multiple users can input information simultaneously and share plans in real time. The user input unit also uses the collaboration function to allow users to jointly plan trips with friends and family. For example, each user can input their own preferences and generate an optimal trip plan based on those preferences. Furthermore, the user input unit may add a function for jointly planning trips with friends and family, allowing users to easily share plans. For example, a function that allows users to check the progress of the plan in real time can be provided. This allows users to jointly plan trips with friends and family.

[0033] The user input unit may provide an option for the user to select activities or themes that interest them in addition to inputting the departure point and number of days of stay. The user input unit may provide an option for the user to select activities or themes that interest them in addition to inputting the departure point and number of days of stay. For example, themes such as adventure, relaxation, and cultural experience may be selected. The user input unit may also add a function for the user to select activities that interest them in addition to inputting the departure point and number of days of stay. For example, activities such as hiking, hot springs, and shopping may be selected. Furthermore, the user input unit may provide an option for the user to select themes and activities that interest them, thereby enabling more personalized travel plans to be created. For example, themes such as nature experiences, historical explorations, and gourmet tours may be selected. This allows travel plans to be created based on the user's interests.

[0034] The generation unit can provide personalized depictions that reflect the user's past travel experiences and preferences. For example, the generation AI learns the user's past travel experiences and preferences and provides personalized journey depictions based on them. For example, a user who has previously visited beach resorts is provided with a depiction of beach resorts. The generation unit also analyzes the user's past travel history, and the generation AI generates personalized journey depictions based on that information. For example, a user who has previously visited historical places is provided with a depiction of historical places. Furthermore, the generation unit provides depictions that reflect the user's preferences and past travel experiences through the generation AI. For example, a user who likes nature is provided with a depiction of a place rich in nature. This makes it possible to provide personalized depictions based on the user's past travel experiences and preferences.

[0035] The generation unit can provide descriptions that include the local culture and historical background. For example, the generation unit can provide the user with a deeper understanding and excitement by including the local culture and historical background in the content depicted by the generation AI. For example, information about the history and culture of the place to be visited is included in the description. The generation unit also provides the generation AI with descriptions that reflect the local culture and historical background. For example, information about the traditions and customs of the place to be visited is included in the description. Furthermore, the generation unit can provide the user with new discoveries and excitement by providing the generation AI with descriptions that include the local culture and historical background. For example, historical events and cultural features of the place to be visited are included in the description. This can provide the user with a deeper understanding and excitement that includes the local culture and historical background.

[0036] The generation unit can provide a depiction that combines music or poetry selected by the user. For example, the generation unit can provide a more moving experience by combining music selected by the user with the content depicted by the generation AI. For example, background music can be played in sync with the depiction. The generation unit can also provide a more moving experience by combining poetry selected by the user with the depiction by the generation AI. For example, a passage of poetry can be inserted into the depiction. The generation unit can also provide a moving experience by combining music or poetry selected by the user with the content depicted by the generation AI. For example, a reading of the poem can be played in sync with the depiction. This can provide a moving experience for the user.

[0037] The generation unit can provide a description in a language selected by the user. For example, the generation unit provides the content described by the generation AI in a language selected by the user. For example, multiple languages ​​such as English, French, and Chinese are supported. Furthermore, the generation unit provides the description in a language selected by the user, thereby accommodating users from different cultural backgrounds. For example, the generation unit generates a description in a language selected by the user. Furthermore, the generation unit provides the content described by the generation AI in a language selected by the user, thereby accommodating users from different cultural backgrounds. For example, the generation unit translates the description into a language selected by the user. This allows accommodating users from different cultural backgrounds.

[0038] The generation unit can provide a depiction that prioritizes places and experiences that the user has not visited before. For example, the generation AI analyzes the user's past travel history and prioritizes depicting places and experiences that the user has not visited. For example, countries and cities that the user has not visited are included in the depiction. The generation unit also includes activities that the user has not experienced before in the depiction. For example, sports and cultural experiences that the user has not experienced are included in the depiction. Furthermore, the generation unit eliminates preconceptions by having the generation AI prioritize depicting places and experiences that the user has not visited based on the user's past travel history. For example, natural landscapes and historical buildings that the user has not visited are included in the depiction. This can provide the user with a new perspective and eliminate preconceptions.

[0039] The generation unit can provide depictions that include themes and activities that the user is not normally interested in. For example, the generation AI includes themes and activities that are not of interest to the user in the depiction. For example, art or music events that the user is not normally interested in are included in the depiction. The generation unit also provides a new perspective by having the generation AI include themes that the user is not normally interested in in the depiction. For example, science museums or historical ruins that the user is not normally interested in are included in the depiction. Furthermore, the generation unit includes activities that are not of interest to the user in the depiction. For example, outdoor activities or sporting events that the user does not normally experience are included in the depiction. This can provide a new perspective to the user and eliminate preconceptions.

[0040] The generation unit can provide a depiction to which random elements based on a theme selected by the user have been added. For example, the generation unit may include a surprise event related to the theme selected by the user in the depiction. The generation unit may also provide an unpredictable experience by having the generation AI add random elements to the depiction based on the theme selected by the user. For example, the generation unit may include an unexplored activity related to the theme selected by the user in the depiction. The generation unit may also provide new discoveries and surprises by having the generation AI add random elements to the depiction based on the theme selected by the user. For example, the generation unit may include a hidden attraction related to the theme selected by the user in the depiction. This provides an unpredictable experience for the user and eliminates preconceptions.

[0041] The generation unit can provide depictions that change according to the time of day and season selected by the user. For example, the generation AI changes the depiction according to the time of day and season selected by the user. For example, different scenery and experiences are included in the depiction during summer daytime and winter nighttime. The generation unit also eliminates preconceptions by having the generation AI change the depiction based on the time of day and season selected by the user. For example, cherry blossom viewing in spring and autumn leaves are included in the depiction. Furthermore, the generation unit provides new perspectives by having the generation AI change the depiction according to the time of day and season selected by the user. For example, a morning walk or stargazing at night is included in the depiction. This allows the user to have a new perspective and eliminate preconceptions.

[0042] The generation unit can provide a depiction that prioritizes activities and places that the user has not experienced before. For example, the generation AI analyzes the user's past travel history and prioritizes depicting activities and places that the user has not experienced before. For example, adventure sports and exotic places that the user has not experienced before are included in the depiction. The generation unit also includes activities that the user has not experienced before in the depiction. For example, cultural experiences and nature explorations that the user has not experienced before are included in the depiction. Furthermore, the generation unit evokes unknown adventures by having the generation AI prioritize depicting activities and places that the user has not experienced before based on the user's past travel history. For example, countries and cities that the user has not visited are included in the depiction. This can provide the user with new adventures and evoke unknown experiences.

[0043] The generation unit can provide descriptions that include local traditions and customs. For example, the generation unit provides the user with a new cultural experience by including local traditions and customs in the content depicted by the generation AI. For example, festivals and traditional events of the places visited are included in the description. The generation unit also provides descriptions that reflect local traditions and customs by the generation AI. For example, information about traditional cuisine and clothing of the places visited is included in the description. Furthermore, the generation unit provides the user with a new cultural experience by providing descriptions that include local traditions and customs by the generation AI. For example, information about traditional dance and music of the places visited is included in the description. This can provide the user with a new cultural experience and inspire unknown adventures.

[0044] The generation unit can provide a depiction that adds a surprise element based on a theme selected by the user. For example, the generation unit causes the generation AI to add a surprise element based on the theme selected by the user to the depiction. For example, the generation unit includes an unexpected event related to the theme selected by the user in the depiction. The generation unit also provides an unpredictable experience by having the generation AI add a surprise element to the depiction based on the theme selected by the user. For example, the generation unit includes a hidden attraction related to the theme selected by the user in the depiction. The generation unit also provides new discoveries and surprises by having the generation AI add a surprise element based on the theme selected by the user to the depiction. For example, the generation unit includes a special experience related to the theme selected by the user in the depiction. This can provide an unpredictable experience for the user and inspire unknown adventures.

[0045] The generation unit can provide depictions that change according to the time of day and season selected by the user. For example, the generation AI changes the depiction according to the time of day and season selected by the user. For example, different scenery and experiences are included in the depiction during summer daytime and winter nighttime. The generation unit also provides new adventures by having the generation AI change the depiction based on the time of day and season selected by the user. For example, cherry blossom viewing in spring and autumn leaves are included in the depiction. Furthermore, the generation unit provides new perspectives by having the generation AI change the depiction according to the time of day and season selected by the user. For example, a morning walk or stargazing at night is included in the depiction. This provides the user with new perspectives and inspires unknown adventures.

[0046] The generation unit learns the user's past travel history and preferences, and can suggest optimal travel destinations and experiences based on that. For example, the generation AI of the generation unit learns the user's past travel history and preferences, and suggests optimal travel destinations and experiences based on that. For example, a new beach resort is suggested for a user who has previously visited beach resorts. The generation unit also analyzes the user's past travel history, and the generation AI suggests optimal travel destinations and experiences based on that information. For example, a historical place is suggested for a user who has previously visited historical places. Furthermore, the generation unit uses the generation AI to suggest travel destinations and experiences that reflect the user's preferences and past travel history. For example, a user who likes nature is suggested travel destinations rich in nature. This makes it possible to suggest optimal travel destinations and experiences for the user.

[0047] The generation unit can analyze the user's current mood and physical condition and provide a travel experience that suits them. For example, the generation AI in the generation unit analyzes the user's current mood and physical condition and provides a travel experience that suits them. For example, if the user feels like relaxing, the generation AI will suggest a relaxing travel destination. The generation unit also analyzes the user's current mood and physical condition and the generation AI will provide the optimal travel experience based on that information. For example, if the user feels active, the generation AI will suggest an active activity. Furthermore, the generation unit can provide a travel experience that reflects the user's mood and physical condition. For example, if the user is tired, the generation AI will suggest a refreshing travel destination. This makes it possible to provide a travel experience that suits the user's current mood and physical condition.

[0048] The generation unit is able to suggest the best experiences for group trips by taking into account the travel history and preferences of the user's friends and family. For example, the generation AI learns the travel history and preferences of the user's friends and family and suggests the best experiences for group trips based on that information. For example, it suggests activities that everyone can enjoy. The generation unit also analyzes the travel history of the user's friends and family and the generation AI suggests the best experiences for group trips based on that information. For example, it suggests travel destinations that everyone will be interested in. Furthermore, the generation unit is able to suggest group trip experiences that reflect the preferences and past travel history of the user's friends and family through the generation AI. For example, it suggests travel destinations where everyone can relax. This makes it possible to suggest the best experiences for group trips.

[0049] The generation unit can provide travel experiences in different cultural spheres based on themes and interests selected by the user. For example, the generation AI provides travel experiences in different cultural spheres based on themes and interests selected by the user. For example, it includes in the description intercultural experiences related to the theme selected by the user. The generation unit also provides travel experiences in different cultural spheres based on themes and interests selected by the user. For example, it includes in the description information about cultures and history in which the user is interested. Furthermore, the generation unit provides intercultural experiences that reflect the themes and interests selected by the user. For example, it includes in the description traditions and customs of regions in which the user is interested. This makes it possible to provide the user with travel experiences in different cultural spheres.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The user input unit can provide an option for the user to input the purpose and budget of the trip. For example, the user can input a purpose such as "I want to relax" or "I want to be adventurous," and a travel plan can be suggested based on that. Also, if the user inputs a budget, the optimal travel plan within that range can be suggested. Furthermore, the user input unit can provide a more personalized travel experience by allowing the user to input the purpose and budget of the trip. For example, if the user inputs "I want to relax," hot springs and resorts can be suggested.

[0052] The generator can provide a depiction that adds random elements based on a theme selected by the user. For example, the depiction can include a surprise event related to the theme selected by the user. The generator can also provide an unpredictable experience by having the generator AI add random elements to the depiction based on the theme selected by the user. The generator can also provide new discoveries and surprises by having the generator AI add random elements to the depiction based on the theme selected by the user. For example, the depiction can include a hidden attraction related to the theme selected by the user.

[0053] The generation unit can provide a depiction that combines music or poetry selected by the user. For example, by combining music selected by the user with the content depicted by the generation AI, a more moving experience can be provided. For example, background music can be played in sync with the depiction. The generation AI can also provide a more moving experience by combining poetry selected by the user with the depiction. For example, a passage of poetry can be inserted into the depiction. The generation unit can also provide a moving experience by combining music or poetry selected by the user with the content depicted by the generation AI. For example, a recitation of the poem can be played in sync with the depiction.

[0054] The analysis unit can learn the user's past travel history and preferences and suggest the optimal departure point and length of stay. For example, the system can store the user's past travel destinations and length of stay in a database and suggest the next travel plan based on that information. The system can also analyze the user's past travel history and automatically learn the user's preferred travel destinations and length of stay. Furthermore, the analysis unit can suggest the optimal departure point and length of stay based on the user's preferences and past travel history. For example, if a user has preferred short trips in the past, the system can suggest a short trip next time as well.

[0055] The generation unit can provide a depiction that prioritizes places and experiences that the user has not visited before. For example, the generation AI can analyze the user's past travel history and prioritize depicting places and experiences that the user has not visited before. For example, countries and cities that the user has not visited can be included in the depiction. The generation AI can also include activities that the user has not experienced before. For example, sports and cultural experiences that the user has not experienced can be included in the depiction. Furthermore, the generation unit can eliminate preconceptions by having the generation AI prioritize depicting places and experiences that the user has not visited before based on the user's past travel history. For example, natural landscapes and historical buildings that the user has not visited can be included in the depiction.

[0056] The generation unit can provide a depiction that includes themes and activities that the user is not normally interested in. For example, the generation AI can include themes and activities that are not of interest to the user in the depiction. For example, art or music events that the user is not normally interested in can be included in the depiction. The generation AI can also provide a new perspective by including themes that the user is not normally interested in in the depiction. For example, science museums or historical ruins that the user is not normally interested in can be included in the depiction. Furthermore, the generation unit can include activities that the user is not normally interested in in the depiction. For example, outdoor activities or sporting events that the user does not normally experience can be included in the depiction.

[0057] The generation unit can provide depictions that change depending on the time of day and season selected by the user. For example, the generation AI can change the depiction depending on the time of day and season selected by the user. For example, different scenery and experiences can be included in the depiction during the daytime in summer and at night in winter. The generation AI can also eliminate preconceptions by changing the depiction based on the time of day and season selected by the user. For example, cherry blossom viewing in spring and autumn leaves can be included in the depiction. Furthermore, the generation unit can provide new perspectives by changing the depiction depending on the time of day and season selected by the user. For example, a morning walk or stargazing at night can be included in the depiction.

[0058] The processing flow of the first embodiment will be briefly explained below.

[0059] Step 1: In the user input section, the user inputs the departure point and the number of days of stay. For example, the user can specify the departure point and the number of days of stay by text input, drop-down menu, calendar selection, etc. Step 2: The analysis unit analyzes the information entered by the user input unit. For example, the analysis unit uses natural language processing technology to analyze the user's input information and narrow down the list of travel destination candidates. The analysis unit can also use data mining technology to analyze past travel data and propose optimal travel plans. Furthermore, the analysis unit uses machine learning algorithms to learn the user's preferences and tendencies, providing a more personalized travel experience. Step 3: The generator generates verbal details of the journey based on the information analyzed by the analyzer. For example, the generator uses text generation AI (e.g., LLM) to describe the scenery and experiences of the travel destination in words. The generator can also use multimodal generation AI to integrate data obtained from multiple sources to generate a more detailed description. For example, the generator might generate a description such as, "You depart from Tokyo and arrive in a quiet village surrounded by beautiful mountains. In the center of the village is an old church, surrounded by colorful flowers."

[0060] (Example 2) The travel experience system according to an embodiment of the present invention allows users to simply input their departure point and number of days of stay, and the AI ​​generator will then create a travel plan using only words, evoking an unknown adventure. This allows the travel experience system to stimulate the user's imagination and provide an inspiring travel experience that is free from preconceptions.

[0061] A travel experience system according to an embodiment includes a user input unit, an analysis unit, and a generation unit. The user input unit allows a user to input a departure point and length of stay. For example, the user can specify the departure point and length of stay using text input, a drop-down menu, a calendar selection, or other methods. The analysis unit analyzes the information input by the user input unit. For example, the analysis unit may use natural language processing technology to analyze the user's input information and narrow down potential travel destinations. The analysis unit may also use data mining technology to analyze past travel data and propose optimal travel plans. Furthermore, the analysis unit may use machine learning algorithms to learn the user's preferences and trends and provide a more personalized travel experience. The generation unit generates travel details using only words based on the information analyzed by the analysis unit. For example, the generation AI may use text generation AI (e.g., LLM) to describe the scenery and experiences of the travel destination in words. The generation AI may also use multimodal generation AI to integrate data obtained from multiple sources to generate a more detailed description. For example, the generation AI generates a description in the form of, "You depart from Tokyo and arrive at a quiet village surrounded by beautiful mountains. In the center of the village there is an old church, surrounded by colorful flowers." This allows the travel experience system according to the embodiment to easily make travel plans and provide a travel experience that is free from preconceptions.

[0062] The user input unit can accept voice input and analyze the input using voice recognition technology. For example, when a user uses a smartphone or microphone to voice-input "a three-day trip from Tokyo," the voice recognition technology converts the input into text and the system analyzes it. If a user speaks, "A two-night, three-day trip to Kyoto next weekend," the voice recognition technology accurately recognizes the input and allows the system to create a travel plan. If a user speaks, "A five-day trip to Hokkaido at the beginning of next month," the voice recognition technology analyzes the input and the system generates an appropriate travel plan. This allows users to easily plan their travel plans using their voice.

[0063] The analysis unit can learn the user's past travel history and preferences and suggest the optimal departure point and length of stay. For example, the analysis unit stores the user's past travel destinations and length of stay in a database and suggests the next travel plan based on that information. For example, if a user has previously visited hot spring resorts, a new hot spring resort will be suggested. The analysis unit also analyzes the user's past travel history and automatically learns the user's preferred travel destinations and length of stay. For example, if a user likes places rich in nature, a natural destination will be suggested for the next trip. Furthermore, the analysis unit suggests the optimal departure point and length of stay based on the user's preferences and past travel history. For example, if a user has preferred short trips in the past, a short trip will be suggested for the next trip as well. This makes it possible to suggest optimal travel plans based on the user's preferences.

[0064] The analysis unit can use the emotion estimation function to analyze the expectations and anxieties the user feels when entering data and provide input assistance based on the results. For example, the analysis unit uses the emotion estimation function to analyze the expectations and anxieties the user feels when entering data and makes suggestions to elicit positive emotions. For example, if the user feels anxious, the analysis unit makes suggestions to give the user a sense of security. The analysis unit also uses the emotion estimation function to analyze the emotions the user feels when entering data in real time and provide appropriate input assistance. For example, if the user feels expectations, the analysis unit makes suggestions to further increase those expectations. Furthermore, the analysis unit analyzes the user's emotions and provides assistance according to the expectations and anxieties the user feels when entering data. For example, if the user feels anxious, the analysis unit provides information to alleviate that anxiety. This makes it possible to provide input assistance according to the user's emotions and provide better travel plans.

[0065] The user input unit may be equipped with a collaboration function that allows users to jointly plan trips with friends and family. The user input unit provides, for example, a collaboration function that allows users to jointly plan trips with friends and family. For example, multiple users can input information simultaneously and share plans in real time. The user input unit also uses the collaboration function to allow users to jointly plan trips with friends and family. For example, each user can input their own preferences and generate an optimal trip plan based on those preferences. Furthermore, the user input unit may add a function for jointly planning trips with friends and family, allowing users to easily share plans. For example, a function that allows users to check the progress of the plan in real time can be provided. This allows users to jointly plan trips with friends and family.

[0066] The user input unit may provide an option for the user to select activities or themes that interest them in addition to inputting the departure point and number of days of stay. The user input unit may provide an option for the user to select activities or themes that interest them in addition to inputting the departure point and number of days of stay. For example, themes such as adventure, relaxation, and cultural experience may be selected. The user input unit may also add a function for the user to select activities that interest them in addition to inputting the departure point and number of days of stay. For example, activities such as hiking, hot springs, and shopping may be selected. Furthermore, the user input unit may provide an option for the user to select themes and activities that interest them, thereby enabling more personalized travel plans to be created. For example, themes such as nature experiences, historical explorations, and gourmet tours may be selected. This allows travel plans to be created based on the user's interests.

[0067] The analysis unit can use the emotion estimation function to analyze the emotional response of the user when reading a description and generate a description that elicits positive emotions. For example, the analysis unit uses the emotion estimation function to analyze the emotional response of the user when reading a description and generate a description that elicits positive emotions. For example, it provides a description that makes the user feel moved. The analysis unit also analyzes the user's emotional response in real time and generates a description that elicits positive emotions. For example, it provides a description that makes the user feel happy. Furthermore, the analysis unit uses the emotion estimation function to analyze the emotions of the user when reading a description and provides an interface that elicits positive emotions. For example, it provides a description that makes the user feel excited. This makes it possible to provide a positive description that matches the user's emotions.

[0068] The generation unit can provide personalized depictions that reflect the user's past travel experiences and preferences. For example, the generation AI learns the user's past travel experiences and preferences and provides personalized journey depictions based on them. For example, a user who has previously visited beach resorts is provided with a depiction of beach resorts. The generation unit also analyzes the user's past travel history, and the generation AI generates personalized journey depictions based on that information. For example, a user who has previously visited historical places is provided with a depiction of historical places. Furthermore, the generation unit provides depictions that reflect the user's preferences and past travel experiences through the generation AI. For example, a user who likes nature is provided with a depiction of a place rich in nature. This makes it possible to provide personalized depictions based on the user's past travel experiences and preferences.

[0069] The generation unit can provide descriptions that include the local culture and historical background. For example, the generation unit can provide the user with a deeper understanding and excitement by including the local culture and historical background in the content depicted by the generation AI. For example, information about the history and culture of the place to be visited is included in the description. The generation unit also provides the generation AI with descriptions that reflect the local culture and historical background. For example, information about the traditions and customs of the place to be visited is included in the description. Furthermore, the generation unit can provide the user with new discoveries and excitement by providing the generation AI with descriptions that include the local culture and historical background. For example, historical events and cultural features of the place to be visited are included in the description. This can provide the user with a deeper understanding and excitement that includes the local culture and historical background.

[0070] The generation unit can provide a depiction that combines music or poetry selected by the user. For example, the generation unit can provide a more moving experience by combining music selected by the user with the content depicted by the generation AI. For example, background music can be played in sync with the depiction. The generation unit can also provide a more moving experience by combining poetry selected by the user with the depiction by the generation AI. For example, a passage of poetry can be inserted into the depiction. The generation unit can also provide a moving experience by combining music or poetry selected by the user with the content depicted by the generation AI. For example, a reading of the poem can be played in sync with the depiction. This can provide a moving experience for the user.

[0071] The generation unit can provide a description in a language selected by the user. For example, the generation unit provides the content described by the generation AI in a language selected by the user. For example, multiple languages ​​such as English, French, and Chinese are supported. Furthermore, the generation unit provides the description in a language selected by the user, thereby accommodating users from different cultural backgrounds. For example, the generation unit generates a description in a language selected by the user. Furthermore, the generation unit provides the content described by the generation AI in a language selected by the user, thereby accommodating users from different cultural backgrounds. For example, the generation unit translates the description into a language selected by the user. This allows accommodating users from different cultural backgrounds.

[0072] The generation unit can provide a depiction that prioritizes places and experiences that the user has not visited before. For example, the generation AI analyzes the user's past travel history and prioritizes depicting places and experiences that the user has not visited. For example, countries and cities that the user has not visited are included in the depiction. The generation unit also includes activities that the user has not experienced before in the depiction. For example, sports and cultural experiences that the user has not experienced are included in the depiction. Furthermore, the generation unit eliminates preconceptions by having the generation AI prioritize depicting places and experiences that the user has not visited based on the user's past travel history. For example, natural landscapes and historical buildings that the user has not visited are included in the depiction. This can provide the user with a new perspective and eliminate preconceptions.

[0073] The generation unit can provide depictions that include themes and activities that the user is not normally interested in. For example, the generation AI includes themes and activities that are not of interest to the user in the depiction. For example, art or music events that the user is not normally interested in are included in the depiction. The generation unit also provides a new perspective by having the generation AI include themes that the user is not normally interested in in the depiction. For example, science museums or historical ruins that the user is not normally interested in are included in the depiction. Furthermore, the generation unit includes activities that are not of interest to the user in the depiction. For example, outdoor activities or sporting events that the user does not normally experience are included in the depiction. This can provide a new perspective to the user and eliminate preconceptions.

[0074] The generation unit can provide a depiction to which random elements based on a theme selected by the user have been added. For example, the generation unit may include a surprise event related to the theme selected by the user in the depiction. The generation unit may also provide an unpredictable experience by having the generation AI add random elements to the depiction based on the theme selected by the user. For example, the generation unit may include an unexplored activity related to the theme selected by the user in the depiction. The generation unit may also provide new discoveries and surprises by having the generation AI add random elements to the depiction based on the theme selected by the user. For example, the generation unit may include a hidden attraction related to the theme selected by the user in the depiction. This provides an unpredictable experience for the user and eliminates preconceptions.

[0075] The generation unit can provide depictions that change according to the time of day and season selected by the user. For example, the generation AI changes the depiction according to the time of day and season selected by the user. For example, different scenery and experiences are included in the depiction during summer daytime and winter nighttime. The generation unit also eliminates preconceptions by having the generation AI change the depiction based on the time of day and season selected by the user. For example, cherry blossom viewing in spring and autumn leaves are included in the depiction. Furthermore, the generation unit provides new perspectives by having the generation AI change the depiction according to the time of day and season selected by the user. For example, a morning walk or stargazing at night is included in the depiction. This allows the user to have a new perspective and eliminate preconceptions.

[0076] The generation unit can provide a depiction that prioritizes activities and places that the user has not experienced before. For example, the generation AI analyzes the user's past travel history and prioritizes depicting activities and places that the user has not experienced before. For example, adventure sports and exotic places that the user has not experienced before are included in the depiction. The generation unit also includes activities that the user has not experienced before in the depiction. For example, cultural experiences and nature explorations that the user has not experienced before are included in the depiction. Furthermore, the generation unit evokes unknown adventures by having the generation AI prioritize depicting activities and places that the user has not experienced before based on the user's past travel history. For example, countries and cities that the user has not visited are included in the depiction. This can provide the user with new adventures and evoke unknown experiences.

[0077] The generation unit can provide descriptions that include local traditions and customs. For example, the generation unit provides the user with a new cultural experience by including local traditions and customs in the content depicted by the generation AI. For example, festivals and traditional events of the places visited are included in the description. The generation unit also provides descriptions that reflect local traditions and customs by the generation AI. For example, information about traditional cuisine and clothing of the places visited is included in the description. Furthermore, the generation unit provides the user with a new cultural experience by providing descriptions that include local traditions and customs by the generation AI. For example, information about traditional dance and music of the places visited is included in the description. This can provide the user with a new cultural experience and inspire unknown adventures.

[0078] The generation unit can provide a depiction that adds a surprise element based on a theme selected by the user. For example, the generation unit causes the generation AI to add a surprise element based on the theme selected by the user to the depiction. For example, the generation unit includes an unexpected event related to the theme selected by the user in the depiction. The generation unit also provides an unpredictable experience by having the generation AI add a surprise element to the depiction based on the theme selected by the user. For example, the generation unit includes a hidden attraction related to the theme selected by the user in the depiction. The generation unit also provides new discoveries and surprises by having the generation AI add a surprise element based on the theme selected by the user to the depiction. For example, the generation unit includes a special experience related to the theme selected by the user in the depiction. This can provide an unpredictable experience for the user and inspire unknown adventures.

[0079] The generation unit can provide depictions that change according to the time of day and season selected by the user. For example, the generation AI changes the depiction according to the time of day and season selected by the user. For example, different scenery and experiences are included in the depiction during summer daytime and winter nighttime. The generation unit also provides new adventures by having the generation AI change the depiction based on the time of day and season selected by the user. For example, cherry blossom viewing in spring and autumn leaves are included in the depiction. Furthermore, the generation unit provides new perspectives by having the generation AI change the depiction according to the time of day and season selected by the user. For example, a morning walk or stargazing at night is included in the depiction. This provides the user with new perspectives and inspires unknown adventures.

[0080] The generation unit can use the emotion estimation function to analyze the emotional reaction of the user when reading a description, and generate a description that stimulates a sense of adventure. For example, the generation unit uses the emotion estimation function to analyze the emotional reaction of the user when reading a description, and generate a description that stimulates a sense of adventure. For example, it provides a description that makes the user feel excited. The generation unit also analyzes the user's emotional reaction in real time, and generates a description that stimulates a sense of adventure. For example, it provides a description that excites the user. Furthermore, the generation unit uses the emotion estimation function to analyze the emotion of the user when reading a description, and provides an interface that stimulates a sense of adventure. For example, it provides a description that makes the user feel a sense of challenge. This stimulates the user's sense of adventure and inspires them to take on unknown adventures.

[0081] The generation unit learns the user's past travel history and preferences, and can suggest optimal travel destinations and experiences based on that. For example, the generation AI of the generation unit learns the user's past travel history and preferences, and suggests optimal travel destinations and experiences based on that. For example, a new beach resort is suggested for a user who has previously visited beach resorts. The generation unit also analyzes the user's past travel history, and the generation AI suggests optimal travel destinations and experiences based on that information. For example, a historical place is suggested for a user who has previously visited historical places. Furthermore, the generation unit uses the generation AI to suggest travel destinations and experiences that reflect the user's preferences and past travel history. For example, a user who likes nature is suggested travel destinations rich in nature. This makes it possible to suggest optimal travel destinations and experiences for the user.

[0082] The generation unit can analyze the user's current mood and physical condition and provide a travel experience that suits them. For example, the generation AI in the generation unit analyzes the user's current mood and physical condition and provides a travel experience that suits them. For example, if the user feels like relaxing, the generation AI will suggest a relaxing travel destination. The generation unit also analyzes the user's current mood and physical condition and the generation AI will provide the optimal travel experience based on that information. For example, if the user feels active, the generation AI will suggest an active activity. Furthermore, the generation unit can provide a travel experience that reflects the user's mood and physical condition. For example, if the user is tired, the generation AI will suggest a refreshing travel destination. This makes it possible to provide a travel experience that suits the user's current mood and physical condition.

[0083] The generation unit can use the emotion estimation function to analyze the emotional response of the user when reading the description and generate a personalized description for eliciting positive emotions. For example, the generation unit uses the emotion estimation function to analyze the emotional response of the user when reading the description and generate a personalized description for eliciting positive emotions. For example, it provides a description that makes the user feel moved. The generation unit also analyzes the user's emotional response in real time and generates a personalized description for eliciting positive emotions. For example, it provides a description that makes the user feel happy. Furthermore, the generation unit uses the emotion estimation function to analyze the emotions of the user when reading the description and provides an interface for eliciting positive emotions. For example, it provides a description that makes the user feel excited. This makes it possible to provide a personalized description according to the user's emotions.

[0084] The generation unit is able to suggest the best experiences for group trips by taking into account the travel history and preferences of the user's friends and family. For example, the generation AI learns the travel history and preferences of the user's friends and family and suggests the best experiences for group trips based on that information. For example, it suggests activities that everyone can enjoy. The generation unit also analyzes the travel history of the user's friends and family and the generation AI suggests the best experiences for group trips based on that information. For example, it suggests travel destinations that everyone will be interested in. Furthermore, the generation unit is able to suggest group trip experiences that reflect the preferences and past travel history of the user's friends and family through the generation AI. For example, it suggests travel destinations where everyone can relax. This makes it possible to suggest the best experiences for group trips.

[0085] The generation unit can provide travel experiences in different cultural spheres based on themes and interests selected by the user. For example, the generation AI provides travel experiences in different cultural spheres based on themes and interests selected by the user. For example, it includes in the description intercultural experiences related to the theme selected by the user. The generation unit also provides travel experiences in different cultural spheres based on themes and interests selected by the user. For example, it includes in the description information about cultures and history in which the user is interested. Furthermore, the generation unit provides intercultural experiences that reflect the themes and interests selected by the user. For example, it includes in the description traditions and customs of regions in which the user is interested. This makes it possible to provide the user with travel experiences in different cultural spheres.

[0086] The generation unit uses the emotion estimation function to analyze the emotions of the user when reading the description in real time, and can continuously optimize the personalized travel experience. The generation unit, for example, uses the emotion estimation function to analyze the emotions of the user when reading the description in real time, and continuously optimize the personalized travel experience. For example, it provides a description that makes the user feel moved. The generation unit also analyzes the user's emotional reaction in real time, and continuously optimizes the personalized travel experience. For example, it provides a description that makes the user feel happy. Furthermore, the generation unit uses the emotion estimation function to analyze the emotions of the user when reading the description, and provides an interface that continuously optimizes the personalized travel experience. For example, it provides a description that makes the user feel excited. This makes it possible to continuously optimize the personalized travel experience according to the user's emotions.

[0087] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0088] The user input unit can provide an option for the user to input the purpose and budget of the trip. For example, the user can input a purpose such as "I want to relax" or "I want to be adventurous," and a travel plan can be suggested based on that. Also, if the user inputs a budget, the optimal travel plan within that range can be suggested. Furthermore, the user input unit can provide a more personalized travel experience by allowing the user to input the purpose and budget of the trip. For example, if the user inputs "I want to relax," hot springs and resorts can be suggested.

[0089] The analysis unit can analyze the user's current mood and physical condition and suggest travel plans accordingly. For example, if the user feels like relaxing, it can suggest relaxing travel destinations. If the user feels like being active, it can also suggest active activities. Furthermore, the analysis unit can analyze the user's mood and physical condition and suggest optimal travel plans based on that. For example, if the user is tired, it can suggest travel destinations that will refresh them.

[0090] The generator can provide a depiction that adds random elements based on a theme selected by the user. For example, the depiction can include a surprise event related to the theme selected by the user. The generator can also provide an unpredictable experience by having the generator AI add random elements to the depiction based on the theme selected by the user. The generator can also provide new discoveries and surprises by having the generator AI add random elements to the depiction based on the theme selected by the user. For example, the depiction can include a hidden attraction related to the theme selected by the user.

[0091] The analysis unit can use the emotion estimation function to analyze the emotional response of the user when reading a description and generate a description that elicits positive emotions. For example, it can provide a description that makes the user feel moved. It can also analyze the user's emotional response in real time and generate a description that elicits positive emotions. Furthermore, the analysis unit can use the emotion estimation function to analyze the emotion of the user when reading a description and provide an interface that elicits positive emotions. For example, it can provide a description that makes the user feel excited.

[0092] The generation unit can provide a depiction that combines music or poetry selected by the user. For example, by combining music selected by the user with the content depicted by the generation AI, a more moving experience can be provided. For example, background music can be played in sync with the depiction. The generation AI can also provide a more moving experience by combining poetry selected by the user with the depiction. For example, a passage of poetry can be inserted into the depiction. The generation unit can also provide a moving experience by combining music or poetry selected by the user with the content depicted by the generation AI. For example, a recitation of the poem can be played in sync with the depiction.

[0093] The analysis unit can learn the user's past travel history and preferences and suggest the optimal departure point and length of stay. For example, the system can store the user's past travel destinations and length of stay in a database and suggest the next travel plan based on that information. The system can also analyze the user's past travel history and automatically learn the user's preferred travel destinations and length of stay. Furthermore, the analysis unit can suggest the optimal departure point and length of stay based on the user's preferences and past travel history. For example, if a user has preferred short trips in the past, the system can suggest a short trip next time as well.

[0094] The generation unit can provide a depiction that prioritizes places and experiences that the user has not visited before. For example, the generation AI can analyze the user's past travel history and prioritize depicting places and experiences that the user has not visited before. For example, countries and cities that the user has not visited can be included in the depiction. The generation AI can also include activities that the user has not experienced before. For example, sports and cultural experiences that the user has not experienced can be included in the depiction. Furthermore, the generation unit can eliminate preconceptions by having the generation AI prioritize depicting places and experiences that the user has not visited before based on the user's past travel history. For example, natural landscapes and historical buildings that the user has not visited can be included in the depiction.

[0095] The analysis unit can use the emotion estimation function to analyze the expectations and anxieties the user feels when inputting data, and provide input assistance based on the results. For example, the emotion estimation function can analyze the expectations and anxieties the user feels when inputting data, and make suggestions to elicit positive emotions. For example, if the user feels anxious, suggestions can be made to give the user a sense of security. The emotion estimation function can also be used to analyze the emotions the user feels when inputting data in real time, and provide appropriate input assistance. For example, if the user feels expectations, suggestions can be made to further increase those expectations. Furthermore, the user's emotions can be analyzed, and assistance can be provided according to the expectations and anxieties the user feels when inputting data. For example, if the user feels anxious, information can be provided to alleviate that anxiety.

[0096] The generation unit can provide a depiction that includes themes and activities that the user is not normally interested in. For example, the generation AI can include themes and activities that are not of interest to the user in the depiction. For example, art or music events that the user is not normally interested in can be included in the depiction. The generation AI can also provide a new perspective by including themes that the user is not normally interested in in the depiction. For example, science museums or historical ruins that the user is not normally interested in can be included in the depiction. Furthermore, the generation unit can include activities that the user is not normally interested in in the depiction. For example, outdoor activities or sporting events that the user does not normally experience can be included in the depiction.

[0097] The generation unit can provide depictions that change depending on the time of day and season selected by the user. For example, the generation AI can change the depiction depending on the time of day and season selected by the user. For example, different scenery and experiences can be included in the depiction during the daytime in summer and at night in winter. The generation AI can also eliminate preconceptions by changing the depiction based on the time of day and season selected by the user. For example, cherry blossom viewing in spring and autumn leaves can be included in the depiction. Furthermore, the generation unit can provide new perspectives by changing the depiction depending on the time of day and season selected by the user. For example, a morning walk or stargazing at night can be included in the depiction.

[0098] The processing flow of the second embodiment will be briefly explained below.

[0099] Step 1: In the user input section, the user inputs the departure point and the number of days of stay. For example, the user can specify the departure point and the number of days of stay by text input, drop-down menu, calendar selection, etc. Step 2: The analysis unit analyzes the information entered by the user input unit. For example, the analysis unit uses natural language processing technology to analyze the user's input information and narrow down the list of travel destination candidates. The analysis unit can also use data mining technology to analyze past travel data and propose optimal travel plans. Furthermore, the analysis unit uses machine learning algorithms to learn the user's preferences and tendencies, providing a more personalized travel experience. Step 3: The generator generates verbal details of the journey based on the information analyzed by the analyzer. For example, the generator uses text generation AI (e.g., LLM) to describe the scenery and experiences of the travel destination in words. The generator can also use multimodal generation AI to integrate data obtained from multiple sources to generate a more detailed description. For example, the generator might generate a description such as, "You depart from Tokyo and arrive in a quiet village surrounded by beautiful mountains. In the center of the village is an old church, surrounded by colorful flowers."

[0100] 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.

[0101] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0102] 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.

[0103] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0104] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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).

[0109] 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.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0119] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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).

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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.

[0138] 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).

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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).

[0153] 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.

[0154] 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."

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] 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.

[0164] 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.

[0165] 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.

[0166] 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]

[0167] 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 user input section for inputting a departure point and length of stay by the user; an analysis unit that analyzes the information input by the user input unit; a generation unit that generates travel details using only words based on the information analyzed by the analysis unit. A system characterized by:

2. The user input unit Accepts voice input and analyzes the input using voice recognition technology 2. The system of claim 1.

3. The analysis unit Learn the user's past travel history and preferences to suggest the optimal departure point and length of stay 2. The system of claim 1.

4. The analysis unit Analyze the expectations and anxieties the user feels when entering data, and provide input support based on that.

2. The system of claim 1.

5. The user input unit Collaboration features allow you to plan trips together with friends and family 2. The system of claim 1.

6. The user input unit In addition to inputting the departure point and the length of stay, provide the user with the option to select activities or themes that interest them.

2. The system of claim 1.

7. The analysis unit Analyzing the emotional response of the user when reading the description and generating the description to elicit positive emotions.

2. The system of claim 1.

Images