system

Abstract

We provide the system. [Solution] A means for receiving travel preference information from users in natural language, and for analyzing that information to identify the traveler's preferences, A means of selecting and presenting the optimal travel destination and related activities to the user based on the analysis results, A means of generating reservation information and linking with an external reservation system based on the travel plan selected by the user, A means of providing additional information and support in real time based on the user's location information during travel, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] Modern travelers have diverse and individualized needs, and there are problems that the overall travel planning is time-consuming and laborious. In particular, the selection of travel destinations and the determination of activities are complicated, and multiple steps are required for reservation procedures. Also, it is difficult to quickly respond to changes and new requests during travel. These are major obstacles for travelers to enjoy their trips without stress.

Means for Solving the Problems

[0005] This invention provides a system that uses natural language processing technology to analyze a user's travel preferences and automatically suggests travel destinations and activities tailored to their tastes. This system generates appropriate booking information based on user feedback and automatically processes bookings in conjunction with external booking systems. Furthermore, it can provide real-time information and support based on the user's location during their trip. As a result, travelers can consistently enjoy a convenient and personalized travel experience.

[0006] A "user" refers to an individual who uses the system to plan or book a trip.

[0007] "Natural language" refers to the language that humans use on a daily basis, and computers analyze it to understand the user's intentions.

[0008] "Travel preference information" refers to information about the expectations and desired travel experiences that users communicate to the system.

[0009] "Analysis" refers to the process by which a system thoroughly analyzes information received from a user to identify its meaning and intent.

[0010] "Preferences" refer to the user's tendencies, likes, and areas of interest, and are used to customize the travel experience.

[0011] A "travel destination" refers to a geographical place that a traveler would like to visit.

[0012] "Activities" refer to the activities, events, and experiences undertaken during a trip, and are an important element of the travel experience.

[0013] "Reservation information" refers to data showing the status of prior arrangements for services necessary for travel, such as transportation and accommodation.

[0014] The "external reservation system" refers to an external mechanism that provides various travel-related services and accepts reservations in cooperation with the system.

[0015] "Location information" is data indicating the current geographical location of the user and is used for real-time information provision.

[0016] "Real-time" indicates a situation where information processing and provision are performed immediately, meaning there is almost no time lag.

Brief Explanation of Drawings

[0017] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Modes for Carrying Out the Invention

[0018] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), and the like.

[0021] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0022] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0023] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0025] [First Embodiment]

[0026] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0027] As shown in Figure 1, the 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.

[0028] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0030] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0033] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0037] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0038] This invention is a system that allows travelers to easily plan trips and enjoy personalized travel experiences. Based on user input, the system suggests optimal destinations and activities, automatically makes reservations, and provides real-time support during the trip.

[0039] First, the user inputs their travel preferences and specific requests in natural language via their device. This information includes the regions they wish to visit, activities of interest, and their purpose. The device then formats this information and sends it to the server.

[0040] Next, the server analyzes the received information using natural language processing technology. This analysis extracts keywords and travel purposes, identifying the user's preferences. Furthermore, past travel history and profile information are also used to perform a more refined preference analysis.

[0041] Once the analysis is complete, the server selects the most suitable travel destinations and activities from the database and generates several options. This takes into account various factors such as weather, budget, and popularity. The selected information is sent to the terminal and displayed to the user.

[0042] Once the user has selected their preferred option, the server proceeds with the booking process based on the chosen plan. Flight and accommodation bookings are handled automatically through integration with external booking systems. This results in a smooth booking process that requires no multiple steps.

[0043] Once the trip begins, the device monitors the user's location and can send inquiries to the server requesting additional information or support as needed. Examples include requests to change restaurant reservations or receive information about local events. The server responds quickly to these requests, ensuring a stress-free travel experience for the user.

[0044] This system allows users to consistently enjoy a personalized travel experience and eliminates complex procedures. Furthermore, its multilingual interface enables service delivery that transcends language barriers. Specifically, if a user requires a sudden change of plans during their stay, the system can immediately propose a new schedule and implement it quickly.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user enters travel preferences via a terminal. This includes destination, purpose of travel, and activities of interest. The terminal receives this input and sends it to the server as formatted data.

[0048] Step 2:

[0049] The server analyzes the received data using a natural language processing engine. It extracts keywords and recognizes intent to systematically identify the user's preferences and travel objectives. It also refers to the user's past travel history and profile data to perform a more detailed preference analysis.

[0050] Step 3:

[0051] Based on the analysis results, the server selects the most suitable travel destinations and activities for the user from the database. The selected candidates include information that takes into account current weather, budget, popularity, etc. The generated candidates are then sent directly to the terminal and displayed to the user.

[0052] Step 4:

[0053] The user selects their preferred travel plan from the presented destinations and activities. Once the selection is complete, the device returns that information to the server.

[0054] Step 5:

[0055] The server automatically processes flight and accommodation reservations based on the user's chosen plan. It integrates with external reservation systems via APIs to complete the necessary reservation procedures.

[0056] Step 6:

[0057] The device continuously monitors the user's location while they are traveling. It can send any new inquiries or requests to the server, such as requests for information about local restaurants.

[0058] Step 7:

[0059] The server responds to user requests in real time. It not only provides supplementary information but also responds quickly to changes in travel plans, sending necessary support to the user's device.

[0060] Through these steps, the user's travel experience is personalized, and the process from planning to execution becomes consistently seamless.

[0061] (Example 1)

[0062] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0063] In recent years, travel planning has diversified, and there is a growing demand for customization to suit individual preferences. However, conventional systems have struggled to understand travel preferences and provide the most suitable travel experience for each individual. Furthermore, providing real-time support during travel has been difficult, creating a need for a stress-free travel experience for users.

[0064] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0065] This invention includes a server that receives travel preference information from a user in natural language, analyzes that information using a generative model to identify the traveler's preferences, selects the optimal travel destination and related activities based on the analysis results and the user's past data, and presents them to the user's terminal, and generates reservation information based on the selected travel plan and automatically links with an external reservation system. This allows the user to easily create a personalized travel plan and receive real-time support during their trip.

[0066] "Natural language" is a means of communication composed of the human language that users use on a daily basis, and which can be converted into a format that the system can analyze.

[0067] A "generative model" is an algorithm or technology used to analyze and generate useful information based on input natural language, in order to identify user preferences and intentions.

[0068] "Preferences" refer to a user's personal likes and tendencies regarding travel destinations and activities, and are an important factor that should be considered when planning a trip.

[0069] A "travel destination" refers to the region or tourist spot that the user wishes to visit, and is included in the suggested travel plan.

[0070] "Related activities" refer to entertainment, learning, and experiential programs and events that users can participate in at their travel destination.

[0071] "Reservation information" refers to information about transportation and accommodations obtained based on the travel plan selected by the user, and is managed in conjunction with an external reservation system.

[0072] "Dynamic information" refers to variable data that is acquired and used in real time, such as the user's current location and changes in their behavior.

[0073] This system is designed to provide users with personalized experiences when planning and executing their trips. First, users input their travel preferences and requests in natural language via a device such as a smartphone or computer. An example of such input might be, "I'm interested in visiting museums in Paris."

[0074] The natural language input is converted into digital data by the terminal and sent to the server. The server utilizes a generative AI model to process this information and analyzes the user's preferences using natural language processing technology. This analysis identifies important keywords and travel objectives.

[0075] Next, the server references the user's past usage records and profile information, performing data analysis based on their preferences. This allows it to extract and suggest the most suitable travel destinations and related activities from the database for each individual user. This information is then sent back to the terminal and presented to the user.

[0076] When a user selects a specific option from the suggested travel plans, the server integrates with an external booking system to generate booking information based on the selected plan. For example, flight and accommodation bookings are made automatically, eliminating the need for complex manual procedures.

[0077] Furthermore, once the trip begins, the device tracks the user's location and queries the server for additional information and support as needed. For example, if the user needs to make a last-minute change to a restaurant reservation while at their destination, they can send a prompt message to the server saying "Find nearby restaurants." The server responds quickly to this request and provides the user with the appropriate information.

[0078] In this way, the system enables users to have a seamless and personalized travel experience.

[0079] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0080] Step 1:

[0081] Users use devices such as smartphones or computers to input their travel preferences and specific requests in natural language. For example, they might input "I want to visit museums in Paris." The device then converts this natural language data into a digital format and prepares to send it to the server. The input is the user's request in natural language, and the output is the data converted into a digital format.

[0082] Step 2:

[0083] The device sends the converted digital data to the server. The receiving server utilizes a generative AI model and natural language processing techniques to analyze the user's input. Specifically, it extracts important keywords from the text (e.g., "museum," "Paris") to understand the purpose of the trip. In this process, the input is digital data, and the output is the analysis results regarding the user's preferences.

[0084] Step 3:

[0085] The server uses the analysis results to cross-reference the user's profile information and past travel history to perform a more detailed preference analysis. This allows for a deeper understanding of the user's personal preferences and tendencies. The input for this process is the analysis results and the user's historical data, and the output is even more refined user preference information.

[0086] Step 4:

[0087] The server selects suitable travel destinations and activities from the database based on refined preference information, generating several travel options. Factors such as weather, budget, and popularity are also considered to form the final travel plan. Inputs are user preference information and various factor data, and output are optimal travel plan candidates.

[0088] Step 5:

[0089] The server sends generated travel plan options to the terminal and presents them to the user. The user reviews the presented options and chooses the plan that best suits their preferences. The input is the travel plan options, and the output is the plan selected by the user.

[0090] Step 6:

[0091] Once the user has selected a travel plan, the server integrates with an external booking system and automatically completes the booking process for the chosen plan. Specific steps include booking flights and accommodations. The input is the user's selected plan, and the output is the completed booking information.

[0092] Step 7:

[0093] From the moment the trip begins, the device monitors the user's dynamic information in real time and sends data to the server as needed. For example, if the user needs to make a new restaurant reservation locally, the device will send a prompt saying "Find nearby restaurants." The server will then provide appropriate information in response to this request, immediately addressing the user's needs. The input is the user's dynamic information and additional requests, and the output is real-time information and support.

[0094] (Application Example 1)

[0095] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0096] In recent years, there has been a growing demand for personalized travel planning, and travelers are finding it difficult to select the best destinations and activities from the vast amount of information available. Furthermore, there is a need for real-time information and updates during travel, but existing systems are insufficient to cover these needs. Additionally, there is a growing need to visually and aurally confirm detailed information about destinations and local experiences in advance. This invention aims to solve these problems and provide travelers with a more convenient and enriching travel experience.

[0097] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0098] In this invention, the server includes means for receiving travel preference information from a user in natural language, analyzing the information to identify the traveler's preferences, selecting and presenting the optimal travel destination and related activities to the user based on the analysis results, generating reservation information and coordinating with an external reservation system based on the travel plan selected by the user, and delivering audiovisual content related to the travel destination to the user. As a result, the user can obtain detailed information about their destination before traveling, and can also acquire information as needed during their trip, enabling them to enjoy a more fulfilling travel experience.

[0099] A "user" refers to a traveler who uses this system to plan their trip.

[0100] "Natural language" refers to the language that users normally use in conversation or text, which is converted into a form that can be processed by machines.

[0101] "Travel preference information" refers to information in which a user describes their desired destination, activities, budget, and other requirements for their trip.

[0102] "Traveler preferences" refer to the travel preferences and tendencies identified from a user's past preferences and interests.

[0103] "Audiovisual content" refers to content, including video and audio, that allows users to obtain information about their destination through visual and auditory means.

[0104] "Providing information in real time" means providing users with the latest information and support in real time while they are traveling.

[0105] An "external booking system" is a system used to automate the travel booking process in cooperation with other providers.

[0106] "Means of analysis" refers to functions that mechanically process natural language information received from users and extract and identify necessary data.

[0107] "Selection methods" refer to functions that select and present the most suitable travel destinations and activities to the user based on the analyzed information.

[0108] "Means of distribution" refers to functions that transmit audiovisual content to users, enabling them to view and listen to it.

[0109] To realize this application, it is crucial to build a system that includes servers, terminals, and user-deployed components.

[0110] The server receives travel preference information entered by the user via their device in natural language. This information is analyzed using natural language processing technology (e.g., Google® Cloud Natural Language API) to extract keywords and intents and identify the traveler's preferences. Furthermore, the server utilizes the user's past travel history and profile information to identify preferences more precisely. Based on the analysis results, the server then generates the necessary data to present to the user, such as selecting travel destinations and activities from a database.

[0111] The terminal is responsible for displaying travel destination recommendations and related audiovisual content provided by the server to the user. Smartphones and tablets fall into this category, providing an interface that allows users to enjoy audiovisual content. In addition, during travel, location services (e.g., Google Maps API) are used to display additional information based on the user's current location in real time. This enables smooth provision of information at the destination.

[0112] Users can select a travel destination and activities from the presented options and proceed with the booking process. Based on the selected travel plan, the server integrates with an external booking system and automatically confirms the reservation based on that information. Furthermore, users can understand the appeal of their destination in advance through audiovisual content, allowing them to prepare visually and aurally.

[0113] For example, if a user enters "I'm interested in visiting shrines in Kyoto," the server will select information on major shrines in Kyoto and related video content, and provide it to the user through their device. The user can then watch the related videos and make concrete plans for their visit.

[0114] An example of a prompt to input into a generative AI model is: "The user has entered 'I am interested in visiting shrines in Kyoto.' Please recommend content that is suitable for this user."

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The server receives travel preference information entered by the user via the terminal in natural language. This input consists of descriptions of the user's destination and interests. The server receives this information for processing and prepares for the next step.

[0118] Step 2:

[0119] The server analyzes the received natural language information using natural language processing technology. The input is the user's travel preference information received in step 1, and the output is keywords and the identified user's preferences. This analysis extracts the intentions and interests necessary for selecting a travel destination.

[0120] Step 3:

[0121] The server selects the most suitable travel destination and related activities based on the analysis results, the user's past travel history, and profile information. The input consists of analyzed keywords and user history data, while the output is a list of selected travel destinations and activities. It gathers a variety of options from the database and prioritizes those best suited to the user.

[0122] Step 4:

[0123] The terminal displays travel destination recommendations sent from the server to the user. The input is recommendation data from the server, and the output is a travel guide that the user can visually confirm. The terminal provides information to the user in an intuitive and easy-to-understand manner through its display interface.

[0124] Step 5:

[0125] The user uses a device to select a travel destination and activities from the provided options. The input is the information displayed in step 4, and the output is the user's selection. The options based on the user's selection are finalized, and the user is ready to proceed to the next step, booking.

[0126] Step 6:

[0127] The server confirms the reservation in conjunction with an external reservation system based on the user's selection results. The input is the user's selection results, and the output is a reservation confirmation notification and related information. The server communicates quickly with the external system and makes arrangements according to the user's schedule.

[0128] Step 7:

[0129] The device collects the user's location information during travel and sends it to the server to obtain additional information in real time. The input is data from the device's location sensor, and the output is additional local information and support information received by the user. It works in conjunction with the server to dynamically provide map information and event information as needed.

[0130] Step 8:

[0131] The server delivers audiovisual content related to the selected travel destination to the user. The input is content data from the server's media library, and the output is the video and audio that the user views. The server selects content that matches the user's interests and provides added value as entertainment.

[0132] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0133] This invention is a system that provides a personalized travel experience that takes into account the emotions of travelers. By using an emotion engine to analyze natural language input from users, it recognizes the user's emotional state and provides appropriate suggestions and support. The system receives travel preference information entered by the user, analyzes their preferences and emotions, and then presents the optimal travel destination and activities, and automates the booking process. Furthermore, it provides real-time support during the trip, enabling appropriate responses based on the user's emotions.

[0134] First, the user inputs their travel-related wishes and opinions in natural language via their device. This information may include not only the purpose and interests of the trip, but also emotional expressions. The device then formats this input data and sends it to the server.

[0135] The server utilizes natural language processing and an emotion engine to analyze the received data. Natural language processing identifies keywords and intentions, while the emotion engine analyzes the user's emotional state. This allows the server to identify the emotional nuances and psychological state hidden within the user's statements. For example, if a user emphasizes relaxation during travel, that emotion is recognized along with the intention of "seeking stress reduction."

[0136] Based on the analysis results, the server suggests the most suitable travel destinations and activities for the user. By considering the output of the emotion engine and adjusting the suggestions accordingly, for example, if the user's emotion shifts from "excitement" to "peace," destinations such as quiet resorts or spas will be suggested. These suggestions are presented to the user via their device.

[0137] Once the user has made their selection, the server integrates with an external booking system to automatically complete the associated booking process. During the trip, the device continuously monitors the user's location and promptly communicates with the server if any changes or new requests are needed.

[0138] The server provides real-time support, offering appropriate information and responses based on the user's emotional state during their trip. For example, if the user's emotional state changes to "anxiety," it will provide reassuring suggestions and encouraging messages.

[0139] Thus, the present invention realizes a travel management system that incorporates emotion recognition technology, making it possible to provide users with a richer and more customized travel experience.

[0140] The following describes the processing flow.

[0141] Step 1:

[0142] Users input their travel preferences and feelings into the device using natural language. This input may include not only information about the region they want to visit, but also their psychological state and emotions at the time. The device formats the user's input data and sends it to the server.

[0143] Step 2:

[0144] The server analyzes the user's input data. First, it uses a natural language processing engine to extract keywords and themes and identify the user's travel intentions. Next, it uses an emotion engine to determine the user's emotional state. The emotion engine detects emotional nuances and tones in the text and estimates the user's psychological state.

[0145] Step 3:

[0146] Based on the analysis results, the server selects the most suitable travel destination and activities for the user. For example, if the emotion engine extracts the emotion of "wanting to relax," a quiet and relaxing resort destination might be selected. These suggestions are sent to the device as an optimized travel plan and displayed to the user.

[0147] Step 4:

[0148] Users review the suggested travel plans and select the one that best suits their preferences. During the selection process, they can also provide feedback on the suggestions on their device, and their responses are analyzed by an emotion engine.

[0149] Step 5:

[0150] The server generates booking information according to the travel plan selected by the user. It automatically connects with external booking systems via API for necessary flights and accommodations, and completes the booking process. During this process, details such as booking confirmations are also generated and sent to the terminal.

[0151] Step 6:

[0152] During travel, the device constantly acquires the user's location information and provides support based on their travel status and schedule. For example, if there are delays in travel to the destination, the server is notified, and appropriate information and support are provided in real time.

[0153] Step 7:

[0154] The server uses an emotion engine to analyze the user's emotions based on inquiries and requests from users during their trip. For example, it provides guidance that shifts the user's emotions from "anxiety" to "reassurance," and sends alternatives and additional information to the device in real time as needed.

[0155] This entire process allows users to enjoy a more fulfilling travel experience that also addresses their emotional needs.

[0156] (Example 2)

[0157] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0158] Modern travel experiences demand personalized services tailored to the individual traveler's preferences and emotional state. However, traditional systems have struggled to adequately consider travelers' emotions when providing suggestions and support, making it difficult to increase traveler satisfaction. Furthermore, real-time support during travel is insufficient, making it challenging to respond quickly to travelers' evolving needs.

[0159] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0160] This invention includes a server that receives travel preference information from a user in natural language, analyzes the information to identify the traveler's preferences and emotional state, selects and presents the optimal travel destination and related activities to the user using an AI model generated based on the analysis results, and performs an automated process of generating reservation information and making external reservations based on the travel plan selected by the user. This enables the provision of a personalized travel experience tailored to the user's preferences and emotions, as well as real-time support.

[0161] "Natural language" refers to the language that people use on a daily basis, and it is a format from which data can be extracted through machine analysis.

[0162] "Travel preference information" refers to data that indicates travelers' preferences regarding their itinerary, such as places they want to visit and activities they are interested in.

[0163] "Preferences" refer to individual users' interests, tastes, and specific tendencies.

[0164] "Emotional state" refers to the psychological and emotional state a user is experiencing at a particular moment.

[0165] An "AI model" is a computational model that uses machine learning algorithms to solve specific problems.

[0166] "Reservation information" refers to detailed data regarding arrangements such as transportation and accommodation necessary for planning a trip.

[0167] An "automated process" is a work procedure that eliminates the need for manual operation through mechanical or computer programs.

[0168] A "multilingual interface" is a function of a computer system that enables accurate transmission and reception of information to users who use different languages.

[0169] This invention provides an emotion recognition system to make the user's travel experience more personalized. The user uses a device to input their travel preferences and opinions in natural language. The input may include the purpose and interests of the trip, as well as expressions of emotions. For example, the user might input a preference such as "I'm looking for a place where I can relax to relieve stress."

[0170] The terminal uses a text analysis library (e.g., NLTK or spaCy) to convert this natural language data into structured data. The converted data is then sent to the server.

[0171] The server uses a generative AI model to analyze the received data. The natural language processing engine identifies keywords from the input data, and the emotion engine analyzes the user's emotional state. As an example of this analysis, the keyword "relax" is identified as the emotion "desire for stress reduction."

[0172] Based on the analysis results, the server uses an AI model to suggest travel destinations and activities tailored to the user's emotional state. For example, a user seeking relaxation might be suggested a quiet seaside resort or spa. These suggestions are optimized by considering the user's past behavioral history and preferences.

[0173] Once a user selects a suggestion, the server integrates with an external booking system and automatically proceeds with the booking process. Furthermore, the device continuously monitors the user's location during their trip, and if there are any changes in the user's emotional state, it communicates with the server to provide optimal support in real time.

[0174] As a concrete example, the prompt message is as follows: "For my next vacation, I would like to go somewhere relaxing to relieve stress. A place with lots of nature would be ideal."

[0175] This invention allows users to enjoy a travel experience tailored to their emotions and preferences, and to receive optimal services that respond to real-time changes in their emotions.

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] Users input their travel preferences and opinions in natural language using their devices. This information includes travel destinations, activities of interest, and emotional preferences. This natural language data is recorded on the device and processed in the next step.

[0179] Step 2:

[0180] The terminal converts natural language data entered by the user into structured data. This process uses text analysis libraries (e.g., NLTK or spaCy). It analyzes the input natural language text and extracts keywords and important phrases. As output, a structured dataset is generated and sent to the server.

[0181] Step 3:

[0182] The server performs natural language processing using a generative AI model based on the received structured data. Specifically, the AI ​​model analyzes the intent behind the data to identify the traveler's purpose and desires. The server also uses an emotion engine to analyze the user's emotional state to understand the traveler's psychological state and needs. The output is the identified intent and emotional state.

[0183] Step 4:

[0184] The server uses an AI model generated based on the analysis results to select the optimal travel destination and activities. This process considers the user's preferences and emotional state, and generates personalized suggestions by comparing them with past data. The output is a list of customized travel destinations and activities.

[0185] Step 5:

[0186] The device displays suggestions received from the server to the user. The user selects their preferred travel destination or activity from the presented list. This selection information is recorded on the device and sent back to the server.

[0187] Step 6:

[0188] The server generates booking information based on the user's selection. It then integrates with an external booking system to automate the travel booking process. The output includes confirmation and details of the confirmed booking.

[0189] Step 7:

[0190] During travel, the device continuously monitors the user's location and communicates with a server if real-time support is needed based on this information. The server monitors changes in the user's emotional state and provides new suggestions and support as necessary. As output, real-time support information is provided to help the user enjoy their trip with peace of mind.

[0191] (Application Example 2)

[0192] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0193] Users traveling often find themselves in a variety of environments and situations, making it difficult to have a safe travel experience that takes their emotions into account in real time. In particular, changes in emotions can increase anxiety and tension at the travel destination, so there is a need for a system that can immediately detect this and provide appropriate instructions, including safety information.

[0194] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0195] In this invention, the server includes means for analyzing the user's travel preference information in natural language, means for suggesting travel destinations based on preferences, and means for analyzing the user's emotional state and presenting safety information. This enables a safe and comfortable travel experience in real time that is tailored to the user's emotions.

[0196] A "user" is an entity that uses the system to provide travel preference information and receive suggestions for travel experiences.

[0197] "Travel preference information in natural language" refers to a means by which users express their travel intentions, including their purpose and interests, either verbally or in text.

[0198] "Analysis" is the process of analyzing information received from the user to determine their preferences and emotional state.

[0199] "Preferences" refer to the individual preferences of users regarding their preferred travel style and destinations.

[0200] A "travel destination" is a place to visit or stay that is selected based on the user's preferences and emotional state.

[0201] "Activities" refer to specific actions or events that can be taken at a destination during a trip.

[0202] "Emotional state" refers to the user's psychological state, and the system uses changes in this state as a basis for providing suggestions and support.

[0203] "Real-time" refers to processing that provides information and support almost instantly during your trip.

[0204] "Safety information" refers to information provided based on the user's emotional state to ensure their safety during travel.

[0205] The main components of the system are the user's terminal, a central server that processes information, and software for data analysis. Users input their travel preferences in natural language via the terminal, which can be a smartphone or smart glasses.

[0206] The device temporarily stores the input and sends it to a cloud-based server. The server analyzes the data using natural language processing libraries and an emotion engine. Software used in this process includes SpeechRecognition and EmotionEngine. Based on the analysis results, it identifies travel destinations and activities that match the user's preferences and emotional state, and generates suggestions.

[0207] Furthermore, during travel, the system continuously monitors the user's emotional state through real-time emotion analysis, providing safety information that adapts to changes. For example, if the system analyzes that the user is feeling anxious, the server can immediately send that information to the device and provide instructions such as safe route guidance.

[0208] For example, if a user says, "I'm worried about traveling in an unfamiliar city," this information is sent to the server via the device, and the server recognizes the emotion as "anxiety." In response, it provides specific safety information in real time, such as, "Here are some safer routes from nearby stations."

[0209] An example of a prompt message is, "When a traveler feels anxious in a place they are visiting, please provide appropriate support to alleviate those feelings." In this way, the system aims to provide travelers with an emotionally personalized, safe, and comfortable travel experience.

[0210] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0211] Step 1:

[0212] Users input travel preferences in natural language via their devices. This input includes travel destinations, purposes, and emotional states. The device digitizes this information using voice recognition and text input functions and stores it temporarily.

[0213] Step 2:

[0214] The terminal sends the user's saved travel preference information to the server. The data is transmitted using a secure protocol. The server stores the received natural language data in a waiting list for processing.

[0215] Step 3:

[0216] The server uses a natural language processing library to extract keywords and perform intent analysis on the received natural language data. User text data is used as input, and the output consists of analyzed keywords and user intent.

[0217] Step 4:

[0218] Next, the server uses an emotion engine to detect the user's emotional state from their utterances. The input is the parsed text data obtained in step 3, and the output is an emotion tag (e.g., anxious, excited, relaxed).

[0219] Step 5:

[0220] The server considers the user's preferences and emotional state based on the analysis results and suggests appropriate travel destinations and activities. A generative AI model is used to formulate the suggestions. The output at this stage is a list of destinations and activities that perfectly match the user's preferences.

[0221] Step 6:

[0222] When a user selects a suggested travel destination and activities, the device sends this selection information to the server. The server uses this data to integrate with an external booking system and automatically makes the travel reservation.

[0223] Step 7:

[0224] During travel, the device continuously collects the user's location and speech information and sends it to a server. The server processes this information in real time and provides safety information and support tailored to the user's emotional state. Examples include guidance on safe routes and recommended facilities. In this process, prompts are used to drive a generative AI model, which generates recommendation messages for the user.

[0225] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0226] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0227] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0228] [Second Embodiment]

[0229] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0230] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0231] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0232] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0233] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0234] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0235] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0236] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0237] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0238] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0239] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0240] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0241] This invention is a system that allows travelers to easily plan trips and enjoy personalized travel experiences. Based on user input, the system suggests optimal destinations and activities, automatically makes reservations, and provides real-time support during the trip.

[0242] First, the user inputs their travel preferences and specific requests in natural language via their device. This information includes the regions they wish to visit, activities of interest, and their purpose. The device then formats this information and sends it to the server.

[0243] Next, the server analyzes the received information using natural language processing technology. This analysis extracts keywords and travel purposes, identifying the user's preferences. Furthermore, past travel history and profile information are also used to perform a more refined preference analysis.

[0244] Once the analysis is complete, the server selects the most suitable travel destinations and activities from the database and generates several options. This takes into account various factors such as weather, budget, and popularity. The selected information is sent to the terminal and displayed to the user.

[0245] Once the user has selected their preferred option, the server proceeds with the booking process based on the chosen plan. Flight and accommodation bookings are handled automatically through integration with external booking systems. This results in a smooth booking process that requires no multiple steps.

[0246] Once the trip begins, the device monitors the user's location and can send inquiries to the server requesting additional information or support as needed. Examples include requests to change restaurant reservations or receive information about local events. The server responds quickly to these requests, ensuring a stress-free travel experience for the user.

[0247] This system allows users to consistently enjoy a personalized travel experience and eliminates complex procedures. Furthermore, its multilingual interface enables service delivery that transcends language barriers. Specifically, if a user requires a sudden change of plans during their stay, the system can immediately propose a new schedule and implement it quickly.

[0248] The following describes the processing flow.

[0249] Step 1:

[0250] The user enters travel preferences via a terminal. This includes destination, purpose of travel, and activities of interest. The terminal receives this input and sends it to the server as formatted data.

[0251] Step 2:

[0252] The server analyzes the received data using a natural language processing engine. It extracts keywords and recognizes intent to systematically identify the user's preferences and travel objectives. It also refers to the user's past travel history and profile data to perform a more detailed preference analysis.

[0253] Step 3:

[0254] Based on the analysis results, the server selects the most suitable travel destinations and activities for the user from the database. The selected candidates include information that takes into account current weather, budget, popularity, etc. The generated candidates are then sent directly to the terminal and displayed to the user.

[0255] Step 4:

[0256] The user selects their preferred travel plan from the presented destinations and activities. Once the selection is complete, the device returns that information to the server.

[0257] Step 5:

[0258] The server automatically processes flight and accommodation reservations based on the user's chosen plan. It integrates with external reservation systems via APIs to complete the necessary reservation procedures.

[0259] Step 6:

[0260] The device continuously monitors the user's location while they are traveling. It can send any new inquiries or requests to the server, such as requests for information about local restaurants.

[0261] Step 7:

[0262] The server responds to user requests in real time. It not only provides supplementary information but also responds quickly to changes in travel plans, sending necessary support to the user's device.

[0263] Through these steps, the user's travel experience is personalized, and the process from planning to execution becomes consistently seamless.

[0264] (Example 1)

[0265] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0266] In recent years, travel planning has diversified, and there is a growing demand for customization to suit individual preferences. However, conventional systems have struggled to understand travel preferences and provide the most suitable travel experience for each individual. Furthermore, providing real-time support during travel has been difficult, creating a need for a stress-free travel experience for users.

[0267] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0268] This invention includes a server that receives travel preference information from a user in natural language, analyzes that information using a generative model to identify the traveler's preferences, selects the optimal travel destination and related activities based on the analysis results and the user's past data, and presents them to the user's terminal, and generates reservation information based on the selected travel plan and automatically links with an external reservation system. This allows the user to easily create a personalized travel plan and receive real-time support during their trip.

[0269] "Natural language" is a means of communication composed of the human language that users use on a daily basis, and which can be converted into a format that the system can analyze.

[0270] A "generative model" is an algorithm or technology used to analyze and generate useful information based on input natural language, in order to identify user preferences and intentions.

[0271] "Preferences" refer to a user's personal likes and tendencies regarding travel destinations and activities, and are an important factor that should be considered when planning a trip.

[0272] A "travel destination" refers to the region or tourist spot that the user wishes to visit, and is included in the suggested travel plan.

[0273] "Related activities" refer to entertainment, learning, and experiential programs and events that users can participate in at their travel destination.

[0274] "Reservation information" refers to information about transportation and accommodations obtained based on the travel plan selected by the user, and is managed in conjunction with an external reservation system.

[0275] "Dynamic information" refers to variable data that is acquired and used in real time, such as the user's current location and changes in their behavior.

[0276] This system is designed to provide users with personalized experiences when planning and executing their trips. First, users input their travel preferences and requests in natural language via a device such as a smartphone or computer. An example of such input might be, "I'm interested in visiting museums in Paris."

[0277] The natural language input is converted into digital data by the terminal and sent to the server. The server utilizes a generative AI model to process this information and analyzes the user's preferences using natural language processing technology. This analysis identifies important keywords and travel objectives.

[0278] Next, the server references the user's past usage records and profile information, performing data analysis based on their preferences. This allows it to extract and suggest the most suitable travel destinations and related activities from the database for each individual user. This information is then sent back to the terminal and presented to the user.

[0279] When a user selects a specific option from the suggested travel plans, the server integrates with an external booking system to generate booking information based on the selected plan. For example, flight and accommodation bookings are made automatically, eliminating the need for complex manual procedures.

[0280] Furthermore, once the trip begins, the device tracks the user's location and queries the server for additional information and support as needed. For example, if the user needs to make a last-minute change to a restaurant reservation while at their destination, they can send a prompt message to the server saying "Find nearby restaurants." The server responds quickly to this request and provides the user with the appropriate information.

[0281] In this way, the system enables users to have a seamless and personalized travel experience.

[0282] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0283] Step 1:

[0284] The user uses a terminal such as a smartphone or a computer to input their travel wishes and specific requirements in natural language. For example, information such as "want to visit museums in Paris" is input. The terminal converts this natural language data into digital format and prepares to send it to the server. The input is the user's request in natural language, and the output is the data converted into digital format.

[0285] Step 2:

[0286] The terminal sends the converted digital data to the server. On the receiving server, the generated AI model is utilized, and natural language processing technology is used to analyze the user's input. Specifically, important keywords (e.g., "museum", "Paris") are extracted from the text to understand the purpose of the trip. In this process, the input is digital data, and the output is the analysis result regarding the user's preferences.

[0287] Step 3:

[0288] Based on the analysis result, the server matches the user's profile information and past travel history to conduct a more detailed preference analysis. This enables a deeper understanding of the user's personal preferences and tendencies. The input for this process is the analysis result and the user's history data, and the output is more refined user preference information.

[0289] Step 4:

[0290] Based on the refined preference information, the server selects appropriate travel destinations and activities from the database and generates several travel candidates. Factors such as weather, budget, popularity, etc. are also considered to form the final travel plan. The input is the user preference information and various factor data, and the output is the candidate for the optimal travel plan.

[0291] Step 5:

[0292] The server sends generated travel plan options to the terminal and presents them to the user. The user reviews the presented options and chooses the plan that best suits their preferences. The input is the travel plan options, and the output is the plan selected by the user.

[0293] Step 6:

[0294] Once the user has selected a travel plan, the server integrates with an external booking system and automatically completes the booking process for the chosen plan. Specific steps include booking flights and accommodations. The input is the user's selected plan, and the output is the completed booking information.

[0295] Step 7:

[0296] From the moment the trip begins, the device monitors the user's dynamic information in real time and sends data to the server as needed. For example, if the user needs to make a new restaurant reservation locally, the device will send a prompt saying "Find nearby restaurants." The server will then provide appropriate information in response to this request, immediately addressing the user's needs. The input is the user's dynamic information and additional requests, and the output is real-time information and support.

[0297] (Application Example 1)

[0298] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0299] In recent years, there has been a growing demand for personalized travel planning, and travelers are finding it difficult to select the best destinations and activities from the vast amount of information available. Furthermore, there is a need for real-time information and updates during travel, but existing systems are insufficient to cover these needs. Additionally, there is a growing need to visually and aurally confirm detailed information about destinations and local experiences in advance. This invention aims to solve these problems and provide travelers with a more convenient and enriching travel experience.

[0300] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following means.

[0301] In this invention, the server includes means for receiving travel wish information in natural language from a user, analyzing the information to identify the preferences of the traveler, selecting an optimal travel destination and related activities based on the analysis result and presenting them to the user, generating reservation information and coordinating with an external reservation system based on the travel plan selected by the user, and distributing visual content related to the travel destination to the user. As a result, the user can obtain detailed information about the destination before the trip, obtain information flexibly during the trip, and enjoy a more fulfilling travel experience.

[0302] The "user" refers to a traveler who makes a travel plan using this system.

[0303] "Natural language" means the language that the user uses in normal conversations or texts, and is converted into a form that can be processed by a machine.

[0304] "Travel wish information" is information that describes the user's requests regarding the destination, activities, budget, etc. that the user wishes for travel.

[0305] "Traveler's preferences" refers to the preferences and tendencies in travel that are identified from the user's past preferences and interests.

[0306] "Visual content" includes videos and sounds, and is content for the user to obtain information about the visited destination through vision and hearing.

[0307] "Providing information in real time" means providing the user with the latest information and support in real time during the trip.

[0308] "External reservation system" is a system used to automatically perform travel reservation operations in cooperation with other providers.

[0309] "Means of analysis" refers to functions that mechanically process natural language information received from users and extract and identify necessary data.

[0310] "Selection methods" refer to functions that select and present the most suitable travel destinations and activities to the user based on the analyzed information.

[0311] "Means of distribution" refers to functions that transmit audiovisual content to users, enabling them to view and listen to it.

[0312] To realize this application, it is crucial to build a system that includes servers, terminals, and user-deployed components.

[0313] The server receives travel preference information entered by the user via their device in natural language. This information is analyzed using natural language processing technology (e.g., Google Cloud Natural Language API) to extract keywords and intents and identify the traveler's preferences. Furthermore, the server utilizes the user's past travel history and profile information to identify preferences more precisely. Based on the analysis results, the server then generates the necessary data to present to the user, such as selecting travel destinations and activities from a database.

[0314] The terminal is responsible for displaying travel destination recommendations and related audiovisual content provided by the server to the user. Smartphones and tablets fall into this category, providing an interface that allows users to enjoy audiovisual content. In addition, during travel, location services (e.g., Google Maps API) are used to display additional information based on the user's current location in real time. This enables smooth provision of information at the destination.

[0315] Users can select a travel destination and activities from the presented options and proceed with the booking process. Based on the selected travel plan, the server integrates with an external booking system and automatically confirms the reservation based on that information. Furthermore, users can understand the appeal of their destination in advance through audiovisual content, allowing them to prepare visually and aurally.

[0316] For example, if a user enters "I'm interested in visiting shrines in Kyoto," the server will select information on major shrines in Kyoto and related video content, and provide it to the user through their device. The user can then watch the related videos and make concrete plans for their visit.

[0317] An example of a prompt to input into a generative AI model is: "The user has entered 'I am interested in visiting shrines in Kyoto.' Please recommend content that is suitable for this user."

[0318] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0319] Step 1:

[0320] The server receives travel preference information entered by the user via the terminal in natural language. This input consists of descriptions of the user's destination and interests. The server receives this information for processing and prepares for the next step.

[0321] Step 2:

[0322] The server analyzes the received natural language information using natural language processing technology. The input is the user's travel preference information received in step 1, and the output is keywords and the identified user's preferences. This analysis extracts the intentions and interests necessary for selecting a travel destination.

[0323] Step 3:

[0324] The server selects the most suitable travel destination and related activities based on the analysis results, the user's past travel history, and profile information. The input consists of analyzed keywords and user history data, while the output is a list of selected travel destinations and activities. It gathers a variety of options from the database and prioritizes those best suited to the user.

[0325] Step 4:

[0326] The terminal displays travel destination recommendations sent from the server to the user. The input is recommendation data from the server, and the output is a travel guide that the user can visually confirm. The terminal provides information to the user in an intuitive and easy-to-understand manner through its display interface.

[0327] Step 5:

[0328] The user uses a device to select a travel destination and activities from the provided options. The input is the information displayed in step 4, and the output is the user's selection. The options based on the user's selection are finalized, and the user is ready to proceed to the next step, booking.

[0329] Step 6:

[0330] The server confirms the reservation in conjunction with an external reservation system based on the user's selection results. The input is the user's selection results, and the output is a reservation confirmation notification and related information. The server communicates quickly with the external system and makes arrangements according to the user's schedule.

[0331] Step 7:

[0332] The device collects the user's location information during travel and sends it to the server to obtain additional information in real time. The input is data from the device's location sensor, and the output is additional local information and support information received by the user. It works in conjunction with the server to dynamically provide map information and event information as needed.

[0333] Step 8:

[0334] The server delivers audiovisual content related to the selected travel destination to the user. The input is content data from the server's media library, and the output is the video and audio that the user views. The server selects content that matches the user's interests and provides added value as entertainment.

[0335] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0336] This invention is a system that provides a personalized travel experience that takes into account the emotions of travelers. By using an emotion engine to analyze natural language input from users, it recognizes the user's emotional state and provides appropriate suggestions and support. The system receives travel preference information entered by the user, analyzes their preferences and emotions, and then presents the optimal travel destination and activities, and automates the booking process. Furthermore, it provides real-time support during the trip, enabling appropriate responses based on the user's emotions.

[0337] First, the user inputs their travel-related wishes and opinions in natural language via their device. This information may include not only the purpose and interests of the trip, but also emotional expressions. The device then formats this input data and sends it to the server.

[0338] The server utilizes natural language processing and an emotion engine to analyze the received data. Natural language processing identifies keywords and intentions, while the emotion engine analyzes the user's emotional state. This allows the server to identify the emotional nuances and psychological state hidden within the user's statements. For example, if a user emphasizes relaxation during travel, that emotion is recognized along with the intention of "seeking stress reduction."

[0339] Based on the analysis results, the server suggests the most suitable travel destinations and activities for the user. By considering the output of the emotion engine and adjusting the suggestions accordingly, for example, if the user's emotion shifts from "excitement" to "peace," destinations such as quiet resorts or spas will be suggested. These suggestions are presented to the user via their device.

[0340] Once the user has made their selection, the server integrates with an external booking system to automatically complete the associated booking process. During the trip, the device continuously monitors the user's location and promptly communicates with the server if any changes or new requests are needed.

[0341] The server provides real-time support, offering appropriate information and responses based on the user's emotional state during their trip. For example, if the user's emotional state changes to "anxiety," it will provide reassuring suggestions and encouraging messages.

[0342] Thus, the present invention realizes a travel management system that incorporates emotion recognition technology, making it possible to provide users with a richer and more customized travel experience.

[0343] The following describes the processing flow.

[0344] Step 1:

[0345] Users input their travel preferences and feelings into the device using natural language. This input may include not only information about the region they want to visit, but also their psychological state and emotions at the time. The device formats the user's input data and sends it to the server.

[0346] Step 2:

[0347] The server analyzes the user's input data. First, it uses a natural language processing engine to extract keywords and themes and identify the user's travel intentions. Next, it uses an emotion engine to determine the user's emotional state. The emotion engine detects emotional nuances and tones in the text and estimates the user's psychological state.

[0348] Step 3:

[0349] Based on the analysis results, the server selects the most suitable travel destination and activities for the user. For example, if the emotion engine extracts the emotion of "wanting to relax," a quiet and relaxing resort destination might be selected. These suggestions are sent to the device as an optimized travel plan and displayed to the user.

[0350] Step 4:

[0351] Users review the suggested travel plans and select the one that best suits their preferences. During the selection process, they can also provide feedback on the suggestions on their device, and their responses are analyzed by an emotion engine.

[0352] Step 5:

[0353] The server generates booking information according to the travel plan selected by the user. It automatically connects with external booking systems via API for necessary flights and accommodations, and completes the booking process. During this process, details such as booking confirmations are also generated and sent to the terminal.

[0354] Step 6:

[0355] During travel, the device constantly acquires the user's location information and provides support based on their travel status and schedule. For example, if there are delays in travel to the destination, the server is notified, and appropriate information and support are provided in real time.

[0356] Step 7:

[0357] The server uses an emotion engine to analyze the user's emotions based on inquiries and requests from users during their trip. For example, it provides guidance that shifts the user's emotions from "anxiety" to "reassurance," and sends alternatives and additional information to the device in real time as needed.

[0358] This entire process allows users to enjoy a more fulfilling travel experience that also addresses their emotional needs.

[0359] (Example 2)

[0360] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0361] Modern travel experiences demand personalized services tailored to the individual traveler's preferences and emotional state. However, traditional systems have struggled to adequately consider travelers' emotions when providing suggestions and support, making it difficult to increase traveler satisfaction. Furthermore, real-time support during travel is insufficient, making it challenging to respond quickly to travelers' evolving needs.

[0362] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0363] This invention includes a server that receives travel preference information from a user in natural language, analyzes the information to identify the traveler's preferences and emotional state, selects and presents the optimal travel destination and related activities to the user using an AI model generated based on the analysis results, and performs an automated process of generating reservation information and making external reservations based on the travel plan selected by the user. This enables the provision of a personalized travel experience tailored to the user's preferences and emotions, as well as real-time support.

[0364] "Natural language" refers to the language that people use on a daily basis, and it is a format from which data can be extracted through machine analysis.

[0365] "Travel preference information" refers to data that indicates travelers' preferences regarding their itinerary, such as places they want to visit and activities they are interested in.

[0366] "Preferences" refer to individual users' interests, tastes, and specific tendencies.

[0367] "Emotional state" refers to the psychological and emotional state a user is experiencing at a particular moment.

[0368] An "AI model" is a computational model that uses machine learning algorithms to solve specific problems.

[0369] "Reservation information" refers to detailed data regarding arrangements such as transportation and accommodation necessary for planning a trip.

[0370] An "automated process" is a work procedure that eliminates the need for manual operation through mechanical or computer programs.

[0371] A "multilingual interface" is a function of a computer system that enables accurate transmission and reception of information to users who use different languages.

[0372] This invention provides an emotion recognition system to make the user's travel experience more personalized. The user uses a device to input their travel preferences and opinions in natural language. The input may include the purpose and interests of the trip, as well as expressions of emotions. For example, the user might input a preference such as "I'm looking for a place where I can relax to relieve stress."

[0373] The terminal uses a text analysis library (e.g., NLTK or spaCy) to convert this natural language data into structured data. The converted data is then sent to the server.

[0374] The server uses a generative AI model to analyze the received data. The natural language processing engine identifies keywords from the input data, and the emotion engine analyzes the user's emotional state. As an example of this analysis, the keyword "relax" is identified as the emotion "desire for stress reduction."

[0375] Based on the analysis results, the server uses an AI model to suggest travel destinations and activities tailored to the user's emotional state. For example, a user seeking relaxation might be suggested a quiet seaside resort or spa. These suggestions are optimized by considering the user's past behavioral history and preferences.

[0376] Once a user selects a suggestion, the server integrates with an external booking system and automatically proceeds with the booking process. Furthermore, the device continuously monitors the user's location during their trip, and if there are any changes in the user's emotional state, it communicates with the server to provide optimal support in real time.

[0377] As a concrete example, the prompt message is as follows: "For my next vacation, I would like to go somewhere relaxing to relieve stress. A place with lots of nature would be ideal."

[0378] This invention allows users to enjoy a travel experience tailored to their emotions and preferences, and to receive optimal services that respond to real-time changes in their emotions.

[0379] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0380] Step 1:

[0381] Users input their travel preferences and opinions in natural language using their devices. This information includes travel destinations, activities of interest, and emotional preferences. This natural language data is recorded on the device and processed in the next step.

[0382] Step 2:

[0383] The terminal converts natural language data entered by the user into structured data. This process uses text analysis libraries (e.g., NLTK or spaCy). It analyzes the input natural language text and extracts keywords and important phrases. As output, a structured dataset is generated and sent to the server.

[0384] Step 3:

[0385] The server performs natural language processing using a generative AI model based on the received structured data. Specifically, the AI ​​model analyzes the intent behind the data to identify the traveler's purpose and desires. The server also uses an emotion engine to analyze the user's emotional state to understand the traveler's psychological state and needs. The output is the identified intent and emotional state.

[0386] Step 4:

[0387] The server uses an AI model generated based on the analysis results to select the optimal travel destination and activities. This process considers the user's preferences and emotional state, and generates personalized suggestions by comparing them with past data. The output is a list of customized travel destinations and activities.

[0388] Step 5:

[0389] The device displays suggestions received from the server to the user. The user selects their preferred travel destination or activity from the presented list. This selection information is recorded on the device and sent back to the server.

[0390] Step 6:

[0391] The server generates booking information based on the user's selection. It then integrates with an external booking system to automate the travel booking process. The output includes confirmation and details of the confirmed booking.

[0392] Step 7:

[0393] During travel, the device continuously monitors the user's location and communicates with a server if real-time support is needed based on this information. The server monitors changes in the user's emotional state and provides new suggestions and support as necessary. As output, real-time support information is provided to help the user enjoy their trip with peace of mind.

[0394] (Application Example 2)

[0395] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0396] Users traveling often find themselves in a variety of environments and situations, making it difficult to have a safe travel experience that takes their emotions into account in real time. In particular, changes in emotions can increase anxiety and tension at the travel destination, so there is a need for a system that can immediately detect this and provide appropriate instructions, including safety information.

[0397] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0398] In this invention, the server includes means for analyzing the user's travel preference information in natural language, means for suggesting travel destinations based on preferences, and means for analyzing the user's emotional state and presenting safety information. This enables a safe and comfortable travel experience in real time that is tailored to the user's emotions.

[0399] A "user" is an entity that uses the system to provide travel preference information and receive suggestions for travel experiences.

[0400] "Travel preference information in natural language" refers to a means by which users express their travel intentions, including their purpose and interests, either verbally or in text.

[0401] "Analysis" is the process of analyzing information received from the user to determine their preferences and emotional state.

[0402] "Preferences" refer to the individual preferences of users regarding their preferred travel style and destinations.

[0403] A "travel destination" is a place to visit or stay that is selected based on the user's preferences and emotional state.

[0404] "Activities" refer to specific actions or events that can be taken at a destination during a trip.

[0405] "Emotional state" refers to the user's psychological state, and the system uses changes in this state as a basis for providing suggestions and support.

[0406] "Real-time" refers to processing that provides information and support almost instantly during your trip.

[0407] "Safety information" refers to information provided based on the user's emotional state to ensure their safety during travel.

[0408] The main components of the system are the user's terminal, a central server that processes information, and software for data analysis. Users input their travel preferences in natural language via the terminal, which can be a smartphone or smart glasses.

[0409] The device temporarily stores the input and sends it to a cloud-based server. The server analyzes the data using natural language processing libraries and an emotion engine. Software used in this process includes SpeechRecognition and EmotionEngine. Based on the analysis results, it identifies travel destinations and activities that match the user's preferences and emotional state, and generates suggestions.

[0410] Furthermore, during travel, the system continuously monitors the user's emotional state through real-time emotion analysis, providing safety information that adapts to changes. For example, if the system analyzes that the user is feeling anxious, the server can immediately send that information to the device and provide instructions such as safe route guidance.

[0411] For example, if a user says, "I'm worried about traveling in an unfamiliar city," this information is sent to the server via the device, and the server recognizes the emotion as "anxiety." In response, it provides specific safety information in real time, such as, "Here are some safer routes from nearby stations."

[0412] An example of a prompt message is, "When a traveler feels anxious in a place they are visiting, please provide appropriate support to alleviate those feelings." In this way, the system aims to provide travelers with an emotionally personalized, safe, and comfortable travel experience.

[0413] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0414] Step 1:

[0415] Users input travel preferences in natural language via their devices. This input includes travel destinations, purposes, and emotional states. The device digitizes this information using voice recognition and text input functions and stores it temporarily.

[0416] Step 2:

[0417] The terminal sends the user's saved travel preference information to the server. The data is transmitted using a secure protocol. The server stores the received natural language data in a waiting list for processing.

[0418] Step 3:

[0419] The server uses a natural language processing library to extract keywords and perform intent analysis on the received natural language data. User text data is used as input, and the output consists of analyzed keywords and user intent.

[0420] Step 4:

[0421] Next, the server uses an emotion engine to detect the user's emotional state from their utterances. The input is the parsed text data obtained in step 3, and the output is an emotion tag (e.g., anxious, excited, relaxed).

[0422] Step 5:

[0423] The server considers the user's preferences and emotional state based on the analysis results and suggests appropriate travel destinations and activities. A generative AI model is used to formulate the suggestions. The output at this stage is a list of destinations and activities that perfectly match the user's preferences.

[0424] Step 6:

[0425] When a user selects a suggested travel destination and activities, the device sends this selection information to the server. The server uses this data to integrate with an external booking system and automatically makes the travel reservation.

[0426] Step 7:

[0427] During travel, the device continuously collects the user's location and speech information and sends it to a server. The server processes this information in real time and provides safety information and support tailored to the user's emotional state. Examples include guidance on safe routes and recommended facilities. In this process, prompts are used to drive a generative AI model, which generates recommendation messages for the user.

[0428] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0429] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0430] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0431] [Third Embodiment]

[0432] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0433] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0434] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0435] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0436] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0437] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0438] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0439] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0440] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0441] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0442] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0443] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0444] This invention is a system that allows travelers to easily plan trips and enjoy personalized travel experiences. Based on user input, the system suggests optimal destinations and activities, automatically makes reservations, and provides real-time support during the trip.

[0445] First, the user inputs their travel preferences and specific requests in natural language via their device. This information includes the regions they wish to visit, activities of interest, and their purpose. The device then formats this information and sends it to the server.

[0446] Next, the server analyzes the received information using natural language processing technology. This analysis extracts keywords and travel purposes, identifying the user's preferences. Furthermore, past travel history and profile information are also used to perform a more refined preference analysis.

[0447] Once the analysis is complete, the server selects the most suitable travel destinations and activities from the database and generates several options. This takes into account various factors such as weather, budget, and popularity. The selected information is sent to the terminal and displayed to the user.

[0448] Once the user has selected their preferred option, the server proceeds with the booking process based on the chosen plan. Flight and accommodation bookings are handled automatically through integration with external booking systems. This results in a smooth booking process that requires no multiple steps.

[0449] Once the trip begins, the device monitors the user's location and can send inquiries to the server requesting additional information or support as needed. Examples include requests to change restaurant reservations or receive information about local events. The server responds quickly to these requests, ensuring a stress-free travel experience for the user.

[0450] This system allows users to consistently enjoy a personalized travel experience and eliminates complex procedures. Furthermore, its multilingual interface enables service delivery that transcends language barriers. Specifically, if a user requires a sudden change of plans during their stay, the system can immediately propose a new schedule and implement it quickly.

[0451] The following describes the processing flow.

[0452] Step 1:

[0453] The user enters travel preferences via a terminal. This includes destination, purpose of travel, and activities of interest. The terminal receives this input and sends it to the server as formatted data.

[0454] Step 2:

[0455] The server analyzes the received data using a natural language processing engine. It extracts keywords and recognizes intent to systematically identify the user's preferences and travel objectives. It also refers to the user's past travel history and profile data to perform a more detailed preference analysis.

[0456] Step 3:

[0457] Based on the analysis results, the server selects the most suitable travel destinations and activities for the user from the database. The selected candidates include information that takes into account current weather, budget, popularity, etc. The generated candidates are then sent directly to the terminal and displayed to the user.

[0458] Step 4:

[0459] The user selects their preferred travel plan from the presented destinations and activities. Once the selection is complete, the device returns that information to the server.

[0460] Step 5:

[0461] The server automatically processes flight and accommodation reservations based on the user's chosen plan. It integrates with external reservation systems via APIs to complete the necessary reservation procedures.

[0462] Step 6:

[0463] The device continuously monitors the user's location while they are traveling. It can send any new inquiries or requests to the server, such as requests for information about local restaurants.

[0464] Step 7:

[0465] The server responds to user requests in real time. It not only provides supplementary information but also responds quickly to changes in travel plans, sending necessary support to the user's device.

[0466] Through these steps, the user's travel experience is personalized, and the process from planning to execution becomes consistently seamless.

[0467] (Example 1)

[0468] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0469] In recent years, travel planning has diversified, and there is a growing demand for customization to suit individual preferences. However, conventional systems have struggled to understand travel preferences and provide the most suitable travel experience for each individual. Furthermore, providing real-time support during travel has been difficult, creating a need for a stress-free travel experience for users.

[0470] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0471] This invention includes a server that receives travel preference information from a user in natural language, analyzes that information using a generative model to identify the traveler's preferences, selects the optimal travel destination and related activities based on the analysis results and the user's past data, and presents them to the user's terminal, and generates reservation information based on the selected travel plan and automatically links with an external reservation system. This allows the user to easily create a personalized travel plan and receive real-time support during their trip.

[0472] "Natural language" is a means of communication composed of the human language that users use on a daily basis, and which can be converted into a format that the system can analyze.

[0473] A "generative model" is an algorithm or technology used to analyze and generate useful information based on input natural language, in order to identify user preferences and intentions.

[0474] "Preferences" refer to a user's personal likes and tendencies regarding travel destinations and activities, and are an important factor that should be considered when planning a trip.

[0475] A "travel destination" refers to the region or tourist spot that the user wishes to visit, and is included in the suggested travel plan.

[0476] "Related activities" refer to entertainment, learning, and experiential programs and events that users can participate in at their travel destination.

[0477] "Reservation information" refers to information about transportation and accommodations obtained based on the travel plan selected by the user, and is managed in conjunction with an external reservation system.

[0478] "Dynamic information" refers to variable data that is acquired and used in real time, such as the user's current location and changes in their behavior.

[0479] This system is designed to provide users with personalized experiences when planning and executing their trips. First, users input their travel preferences and requests in natural language via a device such as a smartphone or computer. An example of such input might be, "I'm interested in visiting museums in Paris."

[0480] The natural language input is converted into digital data by the terminal and sent to the server. The server utilizes a generative AI model to process this information and analyzes the user's preferences using natural language processing technology. This analysis identifies important keywords and travel objectives.

[0481] Next, the server references the user's past usage records and profile information, performing data analysis based on their preferences. This allows it to extract and suggest the most suitable travel destinations and related activities from the database for each individual user. This information is then sent back to the terminal and presented to the user.

[0482] When a user selects a specific option from the suggested travel plans, the server integrates with an external booking system to generate booking information based on the selected plan. For example, flight and accommodation bookings are made automatically, eliminating the need for complex manual procedures.

[0483] Furthermore, once the trip begins, the device tracks the user's location and queries the server for additional information and support as needed. For example, if the user needs to make a last-minute change to a restaurant reservation while at their destination, they can send a prompt message to the server saying "Find nearby restaurants." The server responds quickly to this request and provides the user with the appropriate information.

[0484] In this way, the system enables users to have a seamless and personalized travel experience.

[0485] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0486] Step 1:

[0487] Users use devices such as smartphones or computers to input their travel preferences and specific requests in natural language. For example, they might input "I want to visit museums in Paris." The device then converts this natural language data into a digital format and prepares to send it to the server. The input is the user's request in natural language, and the output is the data converted into a digital format.

[0488] Step 2:

[0489] The device sends the converted digital data to the server. The receiving server utilizes a generative AI model and natural language processing techniques to analyze the user's input. Specifically, it extracts important keywords from the text (e.g., "museum," "Paris") to understand the purpose of the trip. In this process, the input is digital data, and the output is the analysis results regarding the user's preferences.

[0490] Step 3:

[0491] The server uses the analysis results to cross-reference the user's profile information and past travel history to perform a more detailed preference analysis. This allows for a deeper understanding of the user's personal preferences and tendencies. The input for this process is the analysis results and the user's historical data, and the output is even more refined user preference information.

[0492] Step 4:

[0493] The server selects suitable travel destinations and activities from the database based on refined preference information, generating several travel options. Factors such as weather, budget, and popularity are also considered to form the final travel plan. Inputs are user preference information and various factor data, and output are optimal travel plan candidates.

[0494] Step 5:

[0495] The server sends generated travel plan options to the terminal and presents them to the user. The user reviews the presented options and chooses the plan that best suits their preferences. The input is the travel plan options, and the output is the plan selected by the user.

[0496] Step 6:

[0497] Once the user has selected a travel plan, the server integrates with an external booking system and automatically completes the booking process for the chosen plan. Specific steps include booking flights and accommodations. The input is the user's selected plan, and the output is the completed booking information.

[0498] Step 7:

[0499] From the moment the trip begins, the device monitors the user's dynamic information in real time and sends data to the server as needed. For example, if the user needs to make a new restaurant reservation locally, the device will send a prompt saying "Find nearby restaurants." The server will then provide appropriate information in response to this request, immediately addressing the user's needs. The input is the user's dynamic information and additional requests, and the output is real-time information and support.

[0500] (Application Example 1)

[0501] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0502] In recent years, there has been a growing demand for personalized travel planning, and travelers are finding it difficult to select the best destinations and activities from the vast amount of information available. Furthermore, there is a need for real-time information and updates during travel, but existing systems are insufficient to cover these needs. Additionally, there is a growing need to visually and aurally confirm detailed information about destinations and local experiences in advance. This invention aims to solve these problems and provide travelers with a more convenient and enriching travel experience.

[0503] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0504] In this invention, the server includes means for receiving travel preference information from a user in natural language, analyzing the information to identify the traveler's preferences, selecting and presenting the optimal travel destination and related activities to the user based on the analysis results, generating reservation information and coordinating with an external reservation system based on the travel plan selected by the user, and delivering audiovisual content related to the travel destination to the user. As a result, the user can obtain detailed information about their destination before traveling, and can also acquire information as needed during their trip, enabling them to enjoy a more fulfilling travel experience.

[0505] A "user" refers to a traveler who uses this system to plan their trip.

[0506] "Natural language" refers to the language that users normally use in conversation or text, which is converted into a form that can be processed by machines.

[0507] "Travel preference information" refers to information in which a user describes their desired destination, activities, budget, and other requirements for their trip.

[0508] "Traveler preferences" refer to the travel preferences and tendencies identified from a user's past preferences and interests.

[0509] "Audiovisual content" refers to content, including video and audio, that allows users to obtain information about their destination through visual and auditory means.

[0510] "Providing information in real time" means providing users with the latest information and support in real time while they are traveling.

[0511] An "external booking system" is a system used to automate the travel booking process in cooperation with other providers.

[0512] "Means of analysis" refers to functions that mechanically process natural language information received from users and extract and identify necessary data.

[0513] "Selection methods" refer to functions that select and present the most suitable travel destinations and activities to the user based on the analyzed information.

[0514] "Means of distribution" refers to functions that transmit audiovisual content to users, enabling them to view and listen to it.

[0515] To realize this application, it is crucial to build a system that includes servers, terminals, and user-deployed components.

[0516] The server receives travel preference information entered by the user via their device in natural language. This information is analyzed using natural language processing technology (e.g., Google Cloud Natural Language API) to extract keywords and intents and identify the traveler's preferences. Furthermore, the server utilizes the user's past travel history and profile information to identify preferences more precisely. Based on the analysis results, the server then generates the necessary data to present to the user, such as selecting travel destinations and activities from a database.

[0517] The terminal is responsible for displaying travel destination recommendations and related audiovisual content provided by the server to the user. Smartphones and tablets fall into this category, providing an interface that allows users to enjoy audiovisual content. In addition, during travel, location services (e.g., Google Maps API) are used to display additional information based on the user's current location in real time. This enables smooth provision of information at the destination.

[0518] Users can select a travel destination and activities from the presented options and proceed with the booking process. Based on the selected travel plan, the server integrates with an external booking system and automatically confirms the reservation based on that information. Furthermore, users can understand the appeal of their destination in advance through audiovisual content, allowing them to prepare visually and aurally.

[0519] For example, if a user enters "I'm interested in visiting shrines in Kyoto," the server will select information on major shrines in Kyoto and related video content, and provide it to the user through their device. The user can then watch the related videos and make concrete plans for their visit.

[0520] An example of a prompt to input into a generative AI model is: "The user has entered 'I am interested in visiting shrines in Kyoto.' Please recommend content that is suitable for this user."

[0521] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0522] Step 1:

[0523] The server receives travel preference information entered by the user via the terminal in natural language. This input consists of descriptions of the user's destination and interests. The server receives this information for processing and prepares for the next step.

[0524] Step 2:

[0525] The server analyzes the received natural language information using natural language processing technology. The input is the user's travel preference information received in step 1, and the output is keywords and the identified user's preferences. This analysis extracts the intentions and interests necessary for selecting a travel destination.

[0526] Step 3:

[0527] The server selects the most suitable travel destination and related activities based on the analysis results, the user's past travel history, and profile information. The input consists of analyzed keywords and user history data, while the output is a list of selected travel destinations and activities. It gathers a variety of options from the database and prioritizes those best suited to the user.

[0528] Step 4:

[0529] The terminal displays travel destination recommendations sent from the server to the user. The input is recommendation data from the server, and the output is a travel guide that the user can visually confirm. The terminal provides information to the user in an intuitive and easy-to-understand manner through its display interface.

[0530] Step 5:

[0531] The user uses a device to select a travel destination and activities from the provided options. The input is the information displayed in step 4, and the output is the user's selection. The options based on the user's selection are finalized, and the user is ready to proceed to the next step, booking.

[0532] Step 6:

[0533] The server confirms the reservation in conjunction with an external reservation system based on the user's selection results. The input is the user's selection results, and the output is a reservation confirmation notification and related information. The server communicates quickly with the external system and makes arrangements according to the user's schedule.

[0534] Step 7:

[0535] The device collects the user's location information during travel and sends it to the server to obtain additional information in real time. The input is data from the device's location sensor, and the output is additional local information and support information received by the user. It works in conjunction with the server to dynamically provide map information and event information as needed.

[0536] Step 8:

[0537] The server delivers audiovisual content related to the selected travel destination to the user. The input is content data from the server's media library, and the output is the video and audio that the user views. The server selects content that matches the user's interests and provides added value as entertainment.

[0538] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0539] This invention is a system that provides a personalized travel experience that takes into account the emotions of travelers. By using an emotion engine to analyze natural language input from users, it recognizes the user's emotional state and provides appropriate suggestions and support. The system receives travel preference information entered by the user, analyzes their preferences and emotions, and then presents the optimal travel destination and activities, and automates the booking process. Furthermore, it provides real-time support during the trip, enabling appropriate responses based on the user's emotions.

[0540] First, the user inputs their travel-related wishes and opinions in natural language via their device. This information may include not only the purpose and interests of the trip, but also emotional expressions. The device then formats this input data and sends it to the server.

[0541] The server utilizes natural language processing and an emotion engine to analyze the received data. Natural language processing identifies keywords and intentions, while the emotion engine analyzes the user's emotional state. This allows the server to identify the emotional nuances and psychological state hidden within the user's statements. For example, if a user emphasizes relaxation during travel, that emotion is recognized along with the intention of "seeking stress reduction."

[0542] Based on the analysis results, the server suggests the most suitable travel destinations and activities for the user. By considering the output of the emotion engine and adjusting the suggestions accordingly, for example, if the user's emotion shifts from "excitement" to "peace," destinations such as quiet resorts or spas will be suggested. These suggestions are presented to the user via their device.

[0543] Once the user has made their selection, the server integrates with an external booking system to automatically complete the associated booking process. During the trip, the device continuously monitors the user's location and promptly communicates with the server if any changes or new requests are needed.

[0544] The server provides real-time support, offering appropriate information and responses based on the user's emotional state during their trip. For example, if the user's emotional state changes to "anxiety," it will provide reassuring suggestions and encouraging messages.

[0545] Thus, the present invention realizes a travel management system that incorporates emotion recognition technology, making it possible to provide users with a richer and more customized travel experience.

[0546] The following describes the processing flow.

[0547] Step 1:

[0548] Users input their travel preferences and feelings into the device using natural language. This input may include not only information about the region they want to visit, but also their psychological state and emotions at the time. The device formats the user's input data and sends it to the server.

[0549] Step 2:

[0550] The server analyzes the user's input data. First, it uses a natural language processing engine to extract keywords and themes and identify the user's travel intentions. Next, it uses an emotion engine to determine the user's emotional state. The emotion engine detects emotional nuances and tones in the text and estimates the user's psychological state.

[0551] Step 3:

[0552] Based on the analysis results, the server selects the most suitable travel destination and activities for the user. For example, if the emotion engine extracts the emotion of "wanting to relax," a quiet and relaxing resort destination might be selected. These suggestions are sent to the device as an optimized travel plan and displayed to the user.

[0553] Step 4:

[0554] Users review the suggested travel plans and select the one that best suits their preferences. During the selection process, they can also provide feedback on the suggestions on their device, and their responses are analyzed by an emotion engine.

[0555] Step 5:

[0556] The server generates booking information according to the travel plan selected by the user. It automatically connects with external booking systems via API for necessary flights and accommodations, and completes the booking process. During this process, details such as booking confirmations are also generated and sent to the terminal.

[0557] Step 6:

[0558] During travel, the device constantly acquires the user's location information and provides support based on their travel status and schedule. For example, if there are delays in travel to the destination, the server is notified, and appropriate information and support are provided in real time.

[0559] Step 7:

[0560] The server uses an emotion engine to analyze the user's emotions based on inquiries and requests from users during their trip. For example, it provides guidance that shifts the user's emotions from "anxiety" to "reassurance," and sends alternatives and additional information to the device in real time as needed.

[0561] This entire process allows users to enjoy a more fulfilling travel experience that also addresses their emotional needs.

[0562] (Example 2)

[0563] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0564] Modern travel experiences demand personalized services tailored to the individual traveler's preferences and emotional state. However, traditional systems have struggled to adequately consider travelers' emotions when providing suggestions and support, making it difficult to increase traveler satisfaction. Furthermore, real-time support during travel is insufficient, making it challenging to respond quickly to travelers' evolving needs.

[0565] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0566] This invention includes a server that receives travel preference information from a user in natural language, analyzes the information to identify the traveler's preferences and emotional state, selects and presents the optimal travel destination and related activities to the user using an AI model generated based on the analysis results, and performs an automated process of generating reservation information and making external reservations based on the travel plan selected by the user. This enables the provision of a personalized travel experience tailored to the user's preferences and emotions, as well as real-time support.

[0567] "Natural language" refers to the language that people use on a daily basis, and it is a format from which data can be extracted through machine analysis.

[0568] "Travel preference information" refers to data that indicates travelers' preferences regarding their itinerary, such as places they want to visit and activities they are interested in.

[0569] "Preferences" refer to individual users' interests, tastes, and specific tendencies.

[0570] "Emotional state" refers to the psychological and emotional state a user is experiencing at a particular moment.

[0571] An "AI model" is a computational model that uses machine learning algorithms to solve specific problems.

[0572] "Reservation information" refers to detailed data regarding arrangements such as transportation and accommodation necessary for planning a trip.

[0573] An "automated process" is a work procedure that eliminates the need for manual operation through mechanical or computer programs.

[0574] A "multilingual interface" is a function of a computer system that enables accurate transmission and reception of information to users who use different languages.

[0575] This invention provides an emotion recognition system to make the user's travel experience more personalized. The user uses a device to input their travel preferences and opinions in natural language. The input may include the purpose and interests of the trip, as well as expressions of emotions. For example, the user might input a preference such as "I'm looking for a place where I can relax to relieve stress."

[0576] The terminal uses a text analysis library (e.g., NLTK or spaCy) to convert this natural language data into structured data. The converted data is then sent to the server.

[0577] The server uses a generative AI model to analyze the received data. The natural language processing engine identifies keywords from the input data, and the emotion engine analyzes the user's emotional state. As an example of this analysis, the keyword "relax" is identified as the emotion "desire for stress reduction."

[0578] Based on the analysis results, the server uses an AI model to suggest travel destinations and activities tailored to the user's emotional state. For example, a user seeking relaxation might be suggested a quiet seaside resort or spa. These suggestions are optimized by considering the user's past behavioral history and preferences.

[0579] Once a user selects a suggestion, the server integrates with an external booking system and automatically proceeds with the booking process. Furthermore, the device continuously monitors the user's location during their trip, and if there are any changes in the user's emotional state, it communicates with the server to provide optimal support in real time.

[0580] As a concrete example, the prompt message is as follows: "For my next vacation, I would like to go somewhere relaxing to relieve stress. A place with lots of nature would be ideal."

[0581] This invention allows users to enjoy a travel experience tailored to their emotions and preferences, and to receive optimal services that respond to real-time changes in their emotions.

[0582] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0583] Step 1:

[0584] Users input their travel preferences and opinions in natural language using their devices. This information includes travel destinations, activities of interest, and emotional preferences. This natural language data is recorded on the device and processed in the next step.

[0585] Step 2:

[0586] The terminal converts natural language data entered by the user into structured data. This process uses text analysis libraries (e.g., NLTK or spaCy). It analyzes the input natural language text and extracts keywords and important phrases. As output, a structured dataset is generated and sent to the server.

[0587] Step 3:

[0588] The server performs natural language processing using a generative AI model based on the received structured data. Specifically, the AI ​​model analyzes the intent behind the data to identify the traveler's purpose and desires. The server also uses an emotion engine to analyze the user's emotional state to understand the traveler's psychological state and needs. The output is the identified intent and emotional state.

[0589] Step 4:

[0590] The server uses an AI model generated based on the analysis results to select the optimal travel destination and activities. This process considers the user's preferences and emotional state, and generates personalized suggestions by comparing them with past data. The output is a list of customized travel destinations and activities.

[0591] Step 5:

[0592] The device displays suggestions received from the server to the user. The user selects their preferred travel destination or activity from the presented list. This selection information is recorded on the device and sent back to the server.

[0593] Step 6:

[0594] The server generates booking information based on the user's selection. It then integrates with an external booking system to automate the travel booking process. The output includes confirmation and details of the confirmed booking.

[0595] Step 7:

[0596] During travel, the device continuously monitors the user's location and communicates with a server if real-time support is needed based on this information. The server monitors changes in the user's emotional state and provides new suggestions and support as necessary. As output, real-time support information is provided to help the user enjoy their trip with peace of mind.

[0597] (Application Example 2)

[0598] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0599] Users traveling often find themselves in a variety of environments and situations, making it difficult to have a safe travel experience that takes their emotions into account in real time. In particular, changes in emotions can increase anxiety and tension at the travel destination, so there is a need for a system that can immediately detect this and provide appropriate instructions, including safety information.

[0600] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0601] In this invention, the server includes means for analyzing the user's travel preference information in natural language, means for suggesting travel destinations based on preferences, and means for analyzing the user's emotional state and presenting safety information. This enables a safe and comfortable travel experience in real time that is tailored to the user's emotions.

[0602] A "user" is an entity that uses the system to provide travel preference information and receive suggestions for travel experiences.

[0603] "Travel preference information in natural language" refers to a means by which users express their travel intentions, including their purpose and interests, either verbally or in text.

[0604] "Analysis" is the process of analyzing information received from the user to determine their preferences and emotional state.

[0605] "Preferences" refer to the individual preferences of users regarding their preferred travel style and destinations.

[0606] A "travel destination" is a place to visit or stay that is selected based on the user's preferences and emotional state.

[0607] "Activities" refer to specific actions or events that can be taken at a destination during a trip.

[0608] "Emotional state" refers to the user's psychological state, and the system uses changes in this state as a basis for providing suggestions and support.

[0609] "Real-time" refers to processing that provides information and support almost instantly during your trip.

[0610] "Safety information" refers to information provided based on the user's emotional state to ensure their safety during travel.

[0611] The main components of the system are the user's terminal, a central server that processes information, and software for data analysis. Users input their travel preferences in natural language via the terminal, which can be a smartphone or smart glasses.

[0612] The device temporarily stores the input and sends it to a cloud-based server. The server analyzes the data using natural language processing libraries and an emotion engine. Software used in this process includes SpeechRecognition and EmotionEngine. Based on the analysis results, it identifies travel destinations and activities that match the user's preferences and emotional state, and generates suggestions.

[0613] Furthermore, during travel, the system continuously monitors the user's emotional state through real-time emotion analysis, providing safety information that adapts to changes. For example, if the system analyzes that the user is feeling anxious, the server can immediately send that information to the device and provide instructions such as safe route guidance.

[0614] For example, if a user says, "I'm worried about traveling in an unfamiliar city," this information is sent to the server via the device, and the server recognizes the emotion as "anxiety." In response, it provides specific safety information in real time, such as, "Here are some safer routes from nearby stations."

[0615] An example of a prompt message is, "When a traveler feels anxious in a place they are visiting, please provide appropriate support to alleviate those feelings." In this way, the system aims to provide travelers with an emotionally personalized, safe, and comfortable travel experience.

[0616] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0617] Step 1:

[0618] Users input travel preferences in natural language via their devices. This input includes travel destinations, purposes, and emotional states. The device digitizes this information using voice recognition and text input functions and stores it temporarily.

[0619] Step 2:

[0620] The terminal sends the user's saved travel preference information to the server. The data is transmitted using a secure protocol. The server stores the received natural language data in a waiting list for processing.

[0621] Step 3:

[0622] The server uses a natural language processing library to extract keywords and perform intent analysis on the received natural language data. User text data is used as input, and the output consists of analyzed keywords and user intent.

[0623] Step 4:

[0624] Next, the server uses an emotion engine to detect the user's emotional state from their utterances. The input is the parsed text data obtained in step 3, and the output is an emotion tag (e.g., anxious, excited, relaxed).

[0625] Step 5:

[0626] The server considers the user's preferences and emotional state based on the analysis results and suggests appropriate travel destinations and activities. A generative AI model is used to formulate the suggestions. The output at this stage is a list of destinations and activities that perfectly match the user's preferences.

[0627] Step 6:

[0628] When a user selects a suggested travel destination and activities, the device sends this selection information to the server. The server uses this data to integrate with an external booking system and automatically makes the travel reservation.

[0629] Step 7:

[0630] During travel, the device continuously collects the user's location and speech information and sends it to a server. The server processes this information in real time and provides safety information and support tailored to the user's emotional state. Examples include guidance on safe routes and recommended facilities. In this process, prompts are used to drive a generative AI model, which generates recommendation messages for the user.

[0631] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0632] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0633] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0634] [Fourth Embodiment]

[0635] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0636] As shown in Figure 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.

[0637] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0638] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0639] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0640] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0641] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0642] The controlled 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0643] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0644] The specific processing program 56 is an example of a "program" relating to the technology of this 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 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.

[0645] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0646] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0647] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0648] This invention is a system that allows travelers to easily plan trips and enjoy personalized travel experiences. Based on user input, the system suggests optimal destinations and activities, automatically makes reservations, and provides real-time support during the trip.

[0649] First, the user inputs their travel preferences and specific requests in natural language via their device. This information includes the regions they wish to visit, activities of interest, and their purpose. The device then formats this information and sends it to the server.

[0650] Next, the server analyzes the received information using natural language processing technology. This analysis extracts keywords and travel purposes, identifying the user's preferences. Furthermore, past travel history and profile information are also used to perform a more refined preference analysis.

[0651] Once the analysis is complete, the server selects the most suitable travel destinations and activities from the database and generates several options. This takes into account various factors such as weather, budget, and popularity. The selected information is sent to the terminal and displayed to the user.

[0652] Once the user has selected their preferred option, the server proceeds with the booking process based on the chosen plan. Flight and accommodation bookings are handled automatically through integration with external booking systems. This results in a smooth booking process that requires no multiple steps.

[0653] Once the trip begins, the device monitors the user's location and can send inquiries to the server requesting additional information or support as needed. Examples include requests to change restaurant reservations or receive information about local events. The server responds quickly to these requests, ensuring a stress-free travel experience for the user.

[0654] This system allows users to consistently enjoy a personalized travel experience and eliminates complex procedures. Furthermore, its multilingual interface enables service delivery that transcends language barriers. Specifically, if a user requires a sudden change of plans during their stay, the system can immediately propose a new schedule and implement it quickly.

[0655] The following describes the processing flow.

[0656] Step 1:

[0657] The user enters travel preferences via a terminal. This includes destination, purpose of travel, and activities of interest. The terminal receives this input and sends it to the server as formatted data.

[0658] Step 2:

[0659] The server analyzes the received data using a natural language processing engine. It extracts keywords and recognizes intent to systematically identify the user's preferences and travel objectives. It also refers to the user's past travel history and profile data to perform a more detailed preference analysis.

[0660] Step 3:

[0661] Based on the analysis results, the server selects the most suitable travel destinations and activities for the user from the database. The selected candidates include information that takes into account current weather, budget, popularity, etc. The generated candidates are then sent directly to the terminal and displayed to the user.

[0662] Step 4:

[0663] The user selects their preferred travel plan from the presented destinations and activities. Once the selection is complete, the device returns that information to the server.

[0664] Step 5:

[0665] The server automatically processes flight and accommodation reservations based on the user's chosen plan. It integrates with external reservation systems via APIs to complete the necessary reservation procedures.

[0666] Step 6:

[0667] The device continuously monitors the user's location while they are traveling. It can send any new inquiries or requests to the server, such as requests for information about local restaurants.

[0668] Step 7:

[0669] The server responds to user requests in real time. It not only provides supplementary information but also responds quickly to changes in travel plans, sending necessary support to the user's device.

[0670] Through these steps, the user's travel experience is personalized, and the process from planning to execution becomes consistently seamless.

[0671] (Example 1)

[0672] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0673] In recent years, travel planning has diversified, and there is a growing demand for customization to suit individual preferences. However, conventional systems have struggled to understand travel preferences and provide the most suitable travel experience for each individual. Furthermore, providing real-time support during travel has been difficult, creating a need for a stress-free travel experience for users.

[0674] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0675] This invention includes a server that receives travel preference information from a user in natural language, analyzes that information using a generative model to identify the traveler's preferences, selects the optimal travel destination and related activities based on the analysis results and the user's past data, and presents them to the user's terminal, and generates reservation information based on the selected travel plan and automatically links with an external reservation system. This allows the user to easily create a personalized travel plan and receive real-time support during their trip.

[0676] "Natural language" is a means of communication composed of the human language that users use on a daily basis, and which can be converted into a format that the system can analyze.

[0677] A "generative model" is an algorithm or technology used to analyze and generate useful information based on input natural language, in order to identify user preferences and intentions.

[0678] "Preferences" refer to a user's personal likes and tendencies regarding travel destinations and activities, and are an important factor that should be considered when planning a trip.

[0679] A "travel destination" refers to the region or tourist spot that the user wishes to visit, and is included in the suggested travel plan.

[0680] "Related activities" refer to entertainment, learning, and experiential programs and events that users can participate in at their travel destination.

[0681] "Reservation information" refers to information about transportation and accommodations obtained based on the travel plan selected by the user, and is managed in conjunction with an external reservation system.

[0682] "Dynamic information" refers to variable data that is acquired and used in real time, such as the user's current location and changes in their behavior.

[0683] This system is designed to provide users with personalized experiences when planning and executing their trips. First, users input their travel preferences and requests in natural language via a device such as a smartphone or computer. An example of such input might be, "I'm interested in visiting museums in Paris."

[0684] The natural language input is converted into digital data by the terminal and sent to the server. The server utilizes a generative AI model to process this information and analyzes the user's preferences using natural language processing technology. This analysis identifies important keywords and travel objectives.

[0685] Next, the server references the user's past usage records and profile information, performing data analysis based on their preferences. This allows it to extract and suggest the most suitable travel destinations and related activities from the database for each individual user. This information is then sent back to the terminal and presented to the user.

[0686] When a user selects a specific option from the suggested travel plans, the server integrates with an external booking system to generate booking information based on the selected plan. For example, flight and accommodation bookings are made automatically, eliminating the need for complex manual procedures.

[0687] Furthermore, once the trip begins, the device tracks the user's location and queries the server for additional information and support as needed. For example, if the user needs to make a last-minute change to a restaurant reservation while at their destination, they can send a prompt message to the server saying "Find nearby restaurants." The server responds quickly to this request and provides the user with the appropriate information.

[0688] In this way, the system enables users to have a seamless and personalized travel experience.

[0689] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0690] Step 1:

[0691] Users use devices such as smartphones or computers to input their travel preferences and specific requests in natural language. For example, they might input "I want to visit museums in Paris." The device then converts this natural language data into a digital format and prepares to send it to the server. The input is the user's request in natural language, and the output is the data converted into a digital format.

[0692] Step 2:

[0693] The device sends the converted digital data to the server. The receiving server utilizes a generative AI model and natural language processing techniques to analyze the user's input. Specifically, it extracts important keywords from the text (e.g., "museum," "Paris") to understand the purpose of the trip. In this process, the input is digital data, and the output is the analysis results regarding the user's preferences.

[0694] Step 3:

[0695] The server uses the analysis results to cross-reference the user's profile information and past travel history to perform a more detailed preference analysis. This allows for a deeper understanding of the user's personal preferences and tendencies. The input for this process is the analysis results and the user's historical data, and the output is even more refined user preference information.

[0696] Step 4:

[0697] The server selects suitable travel destinations and activities from the database based on refined preference information, generating several travel options. Factors such as weather, budget, and popularity are also considered to form the final travel plan. Inputs are user preference information and various factor data, and output are optimal travel plan candidates.

[0698] Step 5:

[0699] The server sends generated travel plan options to the terminal and presents them to the user. The user reviews the presented options and chooses the plan that best suits their preferences. The input is the travel plan options, and the output is the plan selected by the user.

[0700] Step 6:

[0701] Once the user has selected a travel plan, the server integrates with an external booking system and automatically completes the booking process for the chosen plan. Specific steps include booking flights and accommodations. The input is the user's selected plan, and the output is the completed booking information.

[0702] Step 7:

[0703] From the moment the trip begins, the device monitors the user's dynamic information in real time and sends data to the server as needed. For example, if the user needs to make a new restaurant reservation locally, the device will send a prompt saying "Find nearby restaurants." The server will then provide appropriate information in response to this request, immediately addressing the user's needs. The input is the user's dynamic information and additional requests, and the output is real-time information and support.

[0704] (Application Example 1)

[0705] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0706] In recent years, there has been a growing demand for personalized travel planning, and travelers are finding it difficult to select the best destinations and activities from the vast amount of information available. Furthermore, there is a need for real-time information and updates during travel, but existing systems are insufficient to cover these needs. Additionally, there is a growing need to visually and aurally confirm detailed information about destinations and local experiences in advance. This invention aims to solve these problems and provide travelers with a more convenient and enriching travel experience.

[0707] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0708] In this invention, the server includes means for receiving travel preference information from a user in natural language, analyzing the information to identify the traveler's preferences, selecting and presenting the optimal travel destination and related activities to the user based on the analysis results, generating reservation information and coordinating with an external reservation system based on the travel plan selected by the user, and delivering audiovisual content related to the travel destination to the user. As a result, the user can obtain detailed information about their destination before traveling, and can also acquire information as needed during their trip, enabling them to enjoy a more fulfilling travel experience.

[0709] A "user" refers to a traveler who uses this system to plan their trip.

[0710] "Natural language" refers to the language that users normally use in conversation or text, which is converted into a form that can be processed by machines.

[0711] "Travel preference information" refers to information in which a user describes their desired destination, activities, budget, and other requirements for their trip.

[0712] "Traveler preferences" refer to the travel preferences and tendencies identified from a user's past preferences and interests.

[0713] "Audiovisual content" refers to content, including video and audio, that allows users to obtain information about their destination through visual and auditory means.

[0714] "Providing information in real time" means providing users with the latest information and support in real time while they are traveling.

[0715] An "external booking system" is a system used to automate the travel booking process in cooperation with other providers.

[0716] "Means of analysis" refers to functions that mechanically process natural language information received from users and extract and identify necessary data.

[0717] "Selection methods" refer to functions that select and present the most suitable travel destinations and activities to the user based on the analyzed information.

[0718] "Means of distribution" refers to functions that transmit audiovisual content to users, enabling them to view and listen to it.

[0719] To realize this application, it is crucial to build a system that includes servers, terminals, and user-deployed components.

[0720] The server receives travel preference information entered by the user via their device in natural language. This information is analyzed using natural language processing technology (e.g., Google Cloud Natural Language API) to extract keywords and intents and identify the traveler's preferences. Furthermore, the server utilizes the user's past travel history and profile information to identify preferences more precisely. Based on the analysis results, the server then generates the necessary data to present to the user, such as selecting travel destinations and activities from a database.

[0721] The terminal is responsible for displaying travel destination recommendations and related audiovisual content provided by the server to the user. Smartphones and tablets fall into this category, providing an interface that allows users to enjoy audiovisual content. In addition, during travel, location services (e.g., Google Maps API) are used to display additional information based on the user's current location in real time. This enables smooth provision of information at the destination.

[0722] Users can select a travel destination and activities from the presented options and proceed with the booking process. Based on the selected travel plan, the server integrates with an external booking system and automatically confirms the reservation based on that information. Furthermore, users can understand the appeal of their destination in advance through audiovisual content, allowing them to prepare visually and aurally.

[0723] For example, if a user enters "I'm interested in visiting shrines in Kyoto," the server will select information on major shrines in Kyoto and related video content, and provide it to the user through their device. The user can then watch the related videos and make concrete plans for their visit.

[0724] An example of a prompt to input into a generative AI model is: "The user has entered 'I am interested in visiting shrines in Kyoto.' Please recommend content that is suitable for this user."

[0725] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0726] Step 1:

[0727] The server receives travel preference information entered by the user via the terminal in natural language. This input consists of descriptions of the user's destination and interests. The server receives this information for processing and prepares for the next step.

[0728] Step 2:

[0729] The server analyzes the received natural language information using natural language processing technology. The input is the user's travel preference information received in step 1, and the output is keywords and the identified user's preferences. This analysis extracts the intentions and interests necessary for selecting a travel destination.

[0730] Step 3:

[0731] The server selects the most suitable travel destination and related activities based on the analysis results, the user's past travel history, and profile information. The input consists of analyzed keywords and user history data, while the output is a list of selected travel destinations and activities. It gathers a variety of options from the database and prioritizes those best suited to the user.

[0732] Step 4:

[0733] The terminal displays travel destination recommendations sent from the server to the user. The input is recommendation data from the server, and the output is a travel guide that the user can visually confirm. The terminal provides information to the user in an intuitive and easy-to-understand manner through its display interface.

[0734] Step 5:

[0735] The user uses a device to select a travel destination and activities from the provided options. The input is the information displayed in step 4, and the output is the user's selection. The options based on the user's selection are finalized, and the user is ready to proceed to the next step, booking.

[0736] Step 6:

[0737] The server confirms the reservation in conjunction with an external reservation system based on the user's selection results. The input is the user's selection results, and the output is a reservation confirmation notification and related information. The server communicates quickly with the external system and makes arrangements according to the user's schedule.

[0738] Step 7:

[0739] The device collects the user's location information during travel and sends it to the server to obtain additional information in real time. The input is data from the device's location sensor, and the output is additional local information and support information received by the user. It works in conjunction with the server to dynamically provide map information and event information as needed.

[0740] Step 8:

[0741] The server delivers audiovisual content related to the selected travel destination to the user. The input is content data from the server's media library, and the output is the video and audio that the user views. The server selects content that matches the user's interests and provides added value as entertainment.

[0742] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0743] This invention is a system that provides a personalized travel experience that takes into account the emotions of travelers. By using an emotion engine to analyze natural language input from users, it recognizes the user's emotional state and provides appropriate suggestions and support. The system receives travel preference information entered by the user, analyzes their preferences and emotions, and then presents the optimal travel destination and activities, and automates the booking process. Furthermore, it provides real-time support during the trip, enabling appropriate responses based on the user's emotions.

[0744] First, the user inputs their travel-related wishes and opinions in natural language via their device. This information may include not only the purpose and interests of the trip, but also emotional expressions. The device then formats this input data and sends it to the server.

[0745] The server utilizes natural language processing and an emotion engine to analyze the received data. Natural language processing identifies keywords and intentions, while the emotion engine analyzes the user's emotional state. This allows the server to identify the emotional nuances and psychological state hidden within the user's statements. For example, if a user emphasizes relaxation during travel, that emotion is recognized along with the intention of "seeking stress reduction."

[0746] Based on the analysis results, the server suggests the most suitable travel destinations and activities for the user. By considering the output of the emotion engine and adjusting the suggestions accordingly, for example, if the user's emotion shifts from "excitement" to "peace," destinations such as quiet resorts or spas will be suggested. These suggestions are presented to the user via their device.

[0747] Once the user has made their selection, the server integrates with an external booking system to automatically complete the associated booking process. During the trip, the device continuously monitors the user's location and promptly communicates with the server if any changes or new requests are needed.

[0748] The server provides real-time support, offering appropriate information and responses based on the user's emotional state during their trip. For example, if the user's emotional state changes to "anxiety," it will provide reassuring suggestions and encouraging messages.

[0749] Thus, the present invention realizes a travel management system that incorporates emotion recognition technology, making it possible to provide users with a richer and more customized travel experience.

[0750] The following describes the processing flow.

[0751] Step 1:

[0752] Users input their travel preferences and feelings into the device using natural language. This input may include not only information about the region they want to visit, but also their psychological state and emotions at the time. The device formats the user's input data and sends it to the server.

[0753] Step 2:

[0754] The server analyzes the user's input data. First, it uses a natural language processing engine to extract keywords and themes and identify the user's travel intentions. Next, it uses an emotion engine to determine the user's emotional state. The emotion engine detects emotional nuances and tones in the text and estimates the user's psychological state.

[0755] Step 3:

[0756] Based on the analysis results, the server selects the most suitable travel destination and activities for the user. For example, if the emotion engine extracts the emotion of "wanting to relax," a quiet and relaxing resort destination might be selected. These suggestions are sent to the device as an optimized travel plan and displayed to the user.

[0757] Step 4:

[0758] Users review the suggested travel plans and select the one that best suits their preferences. During the selection process, they can also provide feedback on the suggestions on their device, and their responses are analyzed by an emotion engine.

[0759] Step 5:

[0760] The server generates booking information according to the travel plan selected by the user. It automatically connects with external booking systems via API for necessary flights and accommodations, and completes the booking process. During this process, details such as booking confirmations are also generated and sent to the terminal.

[0761] Step 6:

[0762] During travel, the device constantly acquires the user's location information and provides support based on their travel status and schedule. For example, if there are delays in travel to the destination, the server is notified, and appropriate information and support are provided in real time.

[0763] Step 7:

[0764] The server uses an emotion engine to analyze the user's emotions based on inquiries and requests from users during their trip. For example, it provides guidance that shifts the user's emotions from "anxiety" to "reassurance," and sends alternatives and additional information to the device in real time as needed.

[0765] This entire process allows users to enjoy a more fulfilling travel experience that also addresses their emotional needs.

[0766] (Example 2)

[0767] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0768] Modern travel experiences demand personalized services tailored to the individual traveler's preferences and emotional state. However, traditional systems have struggled to adequately consider travelers' emotions when providing suggestions and support, making it difficult to increase traveler satisfaction. Furthermore, real-time support during travel is insufficient, making it challenging to respond quickly to travelers' evolving needs.

[0769] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0770] This invention includes a server that receives travel preference information from a user in natural language, analyzes the information to identify the traveler's preferences and emotional state, selects and presents the optimal travel destination and related activities to the user using an AI model generated based on the analysis results, and performs an automated process of generating reservation information and making external reservations based on the travel plan selected by the user. This enables the provision of a personalized travel experience tailored to the user's preferences and emotions, as well as real-time support.

[0771] "Natural language" refers to the language that people use on a daily basis, and it is a format from which data can be extracted through machine analysis.

[0772] "Travel preference information" refers to data that indicates travelers' preferences regarding their itinerary, such as places they want to visit and activities they are interested in.

[0773] "Preferences" refer to individual users' interests, tastes, and specific tendencies.

[0774] "Emotional state" refers to the psychological and emotional state a user is experiencing at a particular moment.

[0775] An "AI model" is a computational model that uses machine learning algorithms to solve specific problems.

[0776] "Reservation information" refers to detailed data regarding arrangements such as transportation and accommodation necessary for planning a trip.

[0777] An "automated process" is a work procedure that eliminates the need for manual operation through mechanical or computer programs.

[0778] A "multilingual interface" is a function of a computer system that enables accurate transmission and reception of information to users who use different languages.

[0779] This invention provides an emotion recognition system to make the user's travel experience more personalized. The user uses a device to input their travel preferences and opinions in natural language. The input may include the purpose and interests of the trip, as well as expressions of emotions. For example, the user might input a preference such as "I'm looking for a place where I can relax to relieve stress."

[0780] The terminal uses a text analysis library (e.g., NLTK or spaCy) to convert this natural language data into structured data. The converted data is then sent to the server.

[0781] The server uses a generative AI model to analyze the received data. The natural language processing engine identifies keywords from the input data, and the emotion engine analyzes the user's emotional state. As an example of this analysis, the keyword "relax" is identified as the emotion "desire for stress reduction."

[0782] Based on the analysis results, the server uses an AI model to suggest travel destinations and activities tailored to the user's emotional state. For example, a user seeking relaxation might be suggested a quiet seaside resort or spa. These suggestions are optimized by considering the user's past behavioral history and preferences.

[0783] Once a user selects a suggestion, the server integrates with an external booking system and automatically proceeds with the booking process. Furthermore, the device continuously monitors the user's location during their trip, and if there are any changes in the user's emotional state, it communicates with the server to provide optimal support in real time.

[0784] As a concrete example, the prompt message is as follows: "For my next vacation, I would like to go somewhere relaxing to relieve stress. A place with lots of nature would be ideal."

[0785] This invention allows users to enjoy a travel experience tailored to their emotions and preferences, and to receive optimal services that respond to real-time changes in their emotions.

[0786] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0787] Step 1:

[0788] Users input their travel preferences and opinions in natural language using their devices. This information includes travel destinations, activities of interest, and emotional preferences. This natural language data is recorded on the device and processed in the next step.

[0789] Step 2:

[0790] The terminal converts natural language data entered by the user into structured data. This process uses text analysis libraries (e.g., NLTK or spaCy). It analyzes the input natural language text and extracts keywords and important phrases. As output, a structured dataset is generated and sent to the server.

[0791] Step 3:

[0792] The server performs natural language processing using a generative AI model based on the received structured data. Specifically, the AI ​​model analyzes the intent behind the data to identify the traveler's purpose and desires. The server also uses an emotion engine to analyze the user's emotional state to understand the traveler's psychological state and needs. The output is the identified intent and emotional state.

[0793] Step 4:

[0794] The server uses an AI model generated based on the analysis results to select the optimal travel destination and activities. This process considers the user's preferences and emotional state, and generates personalized suggestions by comparing them with past data. The output is a list of customized travel destinations and activities.

[0795] Step 5:

[0796] The device displays suggestions received from the server to the user. The user selects their preferred travel destination or activity from the presented list. This selection information is recorded on the device and sent back to the server.

[0797] Step 6:

[0798] The server generates booking information based on the user's selection. It then integrates with an external booking system to automate the travel booking process. The output includes confirmation and details of the confirmed booking.

[0799] Step 7:

[0800] During travel, the device continuously monitors the user's location and communicates with a server if real-time support is needed based on this information. The server monitors changes in the user's emotional state and provides new suggestions and support as necessary. As output, real-time support information is provided to help the user enjoy their trip with peace of mind.

[0801] (Application Example 2)

[0802] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0803] Users traveling often find themselves in a variety of environments and situations, making it difficult to have a safe travel experience that takes their emotions into account in real time. In particular, changes in emotions can increase anxiety and tension at the travel destination, so there is a need for a system that can immediately detect this and provide appropriate instructions, including safety information.

[0804] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0805] In this invention, the server includes means for analyzing the user's travel preference information in natural language, means for suggesting travel destinations based on preferences, and means for analyzing the user's emotional state and presenting safety information. This enables a safe and comfortable travel experience in real time that is tailored to the user's emotions.

[0806] A "user" is an entity that uses the system to provide travel preference information and receive suggestions for travel experiences.

[0807] "Travel preference information in natural language" refers to a means by which users express their travel intentions, including their purpose and interests, either verbally or in text.

[0808] "Analysis" is the process of analyzing information received from the user to determine their preferences and emotional state.

[0809] "Preferences" refer to the individual preferences of users regarding their preferred travel style and destinations.

[0810] A "travel destination" is a place to visit or stay that is selected based on the user's preferences and emotional state.

[0811] "Activities" refer to specific actions or events that can be taken at a destination during a trip.

[0812] "Emotional state" refers to the user's psychological state, and the system uses changes in this state as a basis for providing suggestions and support.

[0813] "Real-time" refers to processing that provides information and support almost instantly during your trip.

[0814] "Safety information" refers to information provided based on the user's emotional state to ensure their safety during travel.

[0815] The main components of the system are the user's terminal, a central server that processes information, and software for data analysis. Users input their travel preferences in natural language via the terminal, which can be a smartphone or smart glasses.

[0816] The device temporarily stores the input and sends it to a cloud-based server. The server analyzes the data using natural language processing libraries and an emotion engine. Software used in this process includes SpeechRecognition and EmotionEngine. Based on the analysis results, it identifies travel destinations and activities that match the user's preferences and emotional state, and generates suggestions.

[0817] Furthermore, during travel, the system continuously monitors the user's emotional state through real-time emotion analysis, providing safety information that adapts to changes. For example, if the system analyzes that the user is feeling anxious, the server can immediately send that information to the device and provide instructions such as safe route guidance.

[0818] For example, if a user says, "I'm worried about traveling in an unfamiliar city," this information is sent to the server via the device, and the server recognizes the emotion as "anxiety." In response, it provides specific safety information in real time, such as, "Here are some safer routes from nearby stations."

[0819] An example of a prompt message is, "When a traveler feels anxious in a place they are visiting, please provide appropriate support to alleviate those feelings." In this way, the system aims to provide travelers with an emotionally personalized, safe, and comfortable travel experience.

[0820] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0821] Step 1:

[0822] Users input travel preferences in natural language via their devices. This input includes travel destinations, purposes, and emotional states. The device digitizes this information using voice recognition and text input functions and stores it temporarily.

[0823] Step 2:

[0824] The terminal sends the user's saved travel preference information to the server. The data is transmitted using a secure protocol. The server stores the received natural language data in a waiting list for processing.

[0825] Step 3:

[0826] The server uses a natural language processing library to extract keywords and perform intent analysis on the received natural language data. User text data is used as input, and the output consists of analyzed keywords and user intent.

[0827] Step 4:

[0828] Next, the server uses an emotion engine to detect the user's emotional state from their utterances. The input is the parsed text data obtained in step 3, and the output is an emotion tag (e.g., anxious, excited, relaxed).

[0829] Step 5:

[0830] The server considers the user's preferences and emotional state based on the analysis results and suggests appropriate travel destinations and activities. A generative AI model is used to formulate the suggestions. The output at this stage is a list of destinations and activities that perfectly match the user's preferences.

[0831] Step 6:

[0832] When a user selects a suggested travel destination and activities, the device sends this selection information to the server. The server uses this data to integrate with an external booking system and automatically makes the travel reservation.

[0833] Step 7:

[0834] During travel, the device continuously collects the user's location and speech information and sends it to a server. The server processes this information in real time and provides safety information and support tailored to the user's emotional state. Examples include guidance on safe routes and recommended facilities. In this process, prompts are used to drive a generative AI model, which generates recommendation messages for the user.

[0835] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0836] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0837] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0838] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0839] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0840] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0841] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0842] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0843] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0844] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0845] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0846] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0847] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0848] 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.

[0849] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0850] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0851] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0852] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0853] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0854] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0855] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0856] The following is further disclosed regarding the embodiments described above.

[0857] (Claim 1)

[0858] A means for receiving travel preference information from users in natural language, and for analyzing that information to identify the traveler's preferences,

[0859] A means of selecting and presenting the optimal travel destination and related activities to the user based on the analysis results,

[0860] A means of generating reservation information and linking with an external reservation system based on the travel plan selected by the user,

[0861] A means of providing additional information and support in real time based on the user's location information during travel,

[0862] A system that includes this.

[0863] (Claim 2)

[0864] The system according to claim 1, which uses the user's past travel history and profile information to analyze and identify their preferences.

[0865] (Claim 3)

[0866] The system according to claim 1, which uses a multilingual interface to respond to user inquiries in real time.

[0867] "Example 1"

[0868] (Claim 1)

[0869] A means of receiving travel preference information from users in natural language, and analyzing that information using a generative model to identify travelers' preferences,

[0870] A means for selecting and presenting the optimal travel destination and related activities to the user's terminal based on analysis results and the user's past data,

[0871] A means of generating reservation information based on the selected travel plan and automatically linking it with an external reservation system,

[0872] A means of providing additional information and support in real time based on the user's dynamic information during travel,

[0873] A system that includes this.

[0874] (Claim 2)

[0875] The system according to claim 1, which uses past usage records and user profiles to analyze and identify preferences.

[0876] (Claim 3)

[0877] The system according to claim 1, which responds to user inquiries in real time using a multilingual user interface.

[0878] "Application Example 1"

[0879] (Claim 1)

[0880] A means for receiving travel preference information from users in natural language, and for analyzing that information to identify the traveler's preferences,

[0881] A means of selecting and presenting the optimal travel destination and related activities to the user based on the analysis results,

[0882] A means of generating reservation information and linking with an external reservation system based on the travel plan selected by the user,

[0883] A means of providing additional information and support in real time based on the user's location information during travel,

[0884] A means of delivering audiovisual content related to travel destinations to users,

[0885] A system that includes this.

[0886] (Claim 2)

[0887] The system according to claim 1, which uses the user's past travel history and profile information to analyze and identify their preferences.

[0888] (Claim 3)

[0889] The system according to claim 1, which uses a multilingual interface to respond to user inquiries in real time.

[0890] "Example 2 of combining an emotion engine"

[0891] (Claim 1)

[0892] A means for receiving travel preference information from users in natural language, and for analyzing said information to identify the traveler's preferences and emotional state,

[0893] A means of selecting and presenting the optimal travel destination and related activities to the user using an AI model generated based on the analysis results,

[0894] A means for generating booking information and automating the process of making external bookings based on the travel plan selected by the user,

[0895] A means of providing additional information and personalized responses in real time based on the user's location and emotional state during travel,

[0896] A system that includes this.

[0897] (Claim 2)

[0898] The system according to claim 1, which uses the user's past behavioral history and profile information to identify preferences and emotional patterns.

[0899] (Claim 3)

[0900] The system according to claim 1, which uses a multilingual interface and provides real-time customized responses to user inquiries based on emotion recognition.

[0901] "Application example 2 when combining with an emotional engine"

[0902] (Claim 1)

[0903] A means for receiving travel preference information from users in natural language, and for analyzing that information to identify the traveler's preferences,

[0904] A means of selecting and presenting the optimal travel destination and related activities to the user based on the analysis results,

[0905] A means of generating reservation information and linking with an external reservation system based on the travel plan selected by the user,

[0906] A means of providing additional information and support in real time based on the user's location information during travel,

[0907] A means of analyzing travelers' emotional states and presenting safety information,

[0908] A system that includes this.

[0909] (Claim 2)

[0910] The system according to claim 1, which uses the user's past travel history and profile information to analyze and identify their preferences.

[0911] (Claim 3)

[0912] The system according to claim 1, which uses a multilingual interface to respond to user inquiries in real time. [Explanation of symbols]

[0913] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving travel preference information from users in natural language, and for analyzing that information to identify the traveler's preferences, A means of selecting and presenting the optimal travel destination and related activities to the user based on the analysis results, A means of generating reservation information and linking with an external reservation system based on the travel plan selected by the user, A means of providing additional information and support in real time based on the user's location information during travel, A system that includes this.

2. The system according to claim 1, which uses the user's past travel history and profile information to analyze and identify their preferences.

3. The system according to claim 1, which uses a multilingual interface to respond to user inquiries in real time.

Images