system

Abstract

We provide the system. [Solution] A device for acquiring location information, A means of searching for relevant tourist destination information based on the location information, A means for obtaining user interest and preference information and filtering the search results based on said interest and preference information, A generative model that generates guide content using filtered tourist destination information, A means of translating the generated guide content into the user's specified language, A means for delivering the translated guide content to the user's terminal, 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, and includes 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 that responds 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] When visiting a tourist destination, users may not fully understand the information and historical background of the place. This problem is caused by the lack of knowledge of users and language barriers, and conventional guide services often include information that does not match the interests, and it is required to solve the problem that it is difficult to provide information according to individual needs.

Means for Solving the Problems

[0005] The present invention includes a device for acquiring location information and information search means considering the interests and preferences of users, and generates personalized guide content by a generation model based on the filtered tourist destination information. Further, it uses a translation means into multiple languages to provide information in an appropriate language for the user, thereby realizing a guide specialized for the needs of the user.

[0006] "Location information" is digital data that indicates the user's current location, and is usually composed of latitude and longitude values.

[0007] "Tourist destination information" refers to detailed data about a tourist destination, including various information related to that place, such as its history, culture, works of art, and an overview of its facilities.

[0008] "User interest and preference information" refers to information that indicates the categories and themes that users are particularly interested in, and is data used for personalizing tourist guides.

[0009] A "generative model" refers to an algorithm or system that creates new content or information based on specific input data, and in particular, uses AI to generate user-friendly guide content.

[0010] "Translation means" refers to a device or software that has the function of converting information written in a specific language into another language, and is a process for providing information in a language that the user can understand.

[0011] A "user terminal" is an electronic device that a user directly operates to receive and display information, and includes smartphones and tablets. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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 Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0013] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0014] First, the language used in the following description will be explained.

[0015] 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.

[0016] 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.

[0017] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs, various parameters, and the like. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0018] In the following embodiments, the numbered communication I / F (Interface) is an interface that includes a communication processor, an antenna, and the like. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0019] 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."

[0020] [First Embodiment]

[0021] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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".

[0033] This invention is a system that provides tourist destination information related to a user's location using that location information. Specifically, location information is acquired from sensors such as GPS through a device such as a smartphone or tablet used by the user. This location information is transmitted to a server in the cloud.

[0034] The server uses location information received from the user, along with pre-registered user interest and preference information, to query the database and search for relevant tourist destination information. Based on these search results, it filters tourist information that matches the user's interests and preferences, and automatically generates guide content using a generative model.

[0035] The generated guide content is translated based on the language set on the user's device. The server performs this multilingual translation, providing the information in the format that is easiest for the user to understand. This translated guide data is delivered to the user's device, which can then play it as audio or display it as text.

[0036] As a concrete example, consider a scenario where a user visits a historical art museum. In this case, the device detects the user's current location, and the server retrieves information about the museum from a database. Furthermore, based on categories the user has shown particular interest in (e.g., "medieval paintings" or "a specific painter"), the generative model generates a detailed description, translates it into the user's language, and sends it to the device.

[0037] Ultimately, users can choose and listen to only the information that interests them at their own pace, making their travel experience more enriching. This system is designed to individually optimize the user experience and effectively deliver travel information.

[0038] The following describes the processing flow.

[0039] Step 1:

[0040] The device activates its GPS sensor and performs the operation of acquiring its own location information (latitude and longitude).

[0041] Step 2:

[0042] The device transmits its acquired location information to the server in real time. This process involves data communication.

[0043] Step 3:

[0044] The server receives the transmitted location information and searches the database for tourist destination information related to that location.

[0045] Step 4:

[0046] The server refers to the user's pre-registered interests and preferences and filters the searched tourist destination information to include relevant results.

[0047] Step 5:

[0048] Based on the filtered information, the server uses a generative model to generate user guidance content.

[0049] Step 6:

[0050] The server translates the generated guide content according to the user's device language settings and prepares multilingual data.

[0051] Step 7:

[0052] The server sends the translated guide data to the terminal and provides it in a format that the user can access.

[0053] Step 8:

[0054] The device processes the received guide data and either plays the audio guide or displays the text.

[0055] Step 9:

[0056] If a user requests more details about information they are interested in on their device, the device sends a request to the server, and additional information is provided.

[0057] (Example 1)

[0058] 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."

[0059] In tourist destination information search systems, there is a need to efficiently provide information tailored to the user's current location and individual interests. However, conventional systems have the problem that location-based search results are not personalized, and useful information is not provided to users in a timely manner. Furthermore, information provision in different languages ​​is insufficient, making it difficult to effectively generate and provide multilingual guides.

[0060] 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.

[0061] In this invention, the server includes means for acquiring user preference information and selecting search results based on said preference information, a generation model for generating explanatory content using the selected regional information, and means for converting the generated explanatory content into the user's specified language. This makes it possible to efficiently provide customized tourist information in multiple languages ​​that is tailored to the user's location and individual preferences.

[0062] "Location" refers to information indicating the user's current location, and is usually expressed as latitude and longitude on Earth.

[0063] "Device" refers to a device used to acquire location information, such as a mobile terminal with GPS functionality.

[0064] "Means of searching" refers to methods and technologies for finding relevant regional information by searching a database based on acquired location information.

[0065] "User preference information" refers to data about users' interests and preferences, and is used to select the information provided.

[0066] "Selection methods" refer to the processes and technologies used to select items that match the user's preferences based on the acquired information.

[0067] A "generative model" refers to an algorithm or program used to create relevant descriptions or instructions based on specific input conditions.

[0068] "Means of converting into language" refers to translation technologies and systems used to display the generated explanatory content in multiple languages.

[0069] "User device" refers to a device that the user directly uses, and includes smartphones and tablets.

[0070] "Means of customization" refers to technologies and methods that adaptively adjust information according to the individual needs and requirements of the user.

[0071] This system provides relevant tourist destination information based on the user's location. Specifically, it requires a smartphone or tablet as the user's device. The device uses its built-in GPS sensor to obtain the user's current location and sends it to a server in the cloud. The device securely transmits data packets, including the obtained location information, to the server using the HTTPS protocol.

[0072] The server uses this location information and pre-registered user interest and preference information to search the database. Database query techniques such as SQL are used to extract regional information relevant to the user's location. Next, the user's preference information is referenced to filter the relevant regional information based on the search results. The filtered data is analyzed by a generative AI model to generate customized guide content. This generative model utilizes algorithms employing natural language processing techniques to automatically create contextually appropriate explanations.

[0073] The generated guide content is processed by a multilingual translation service and translated into the user's specified language. For multilingual support, a cloud-based translation API is used to translate the generated text in real time. This translated guide information is then delivered to the user's device using HTTPS. The device stores the received information and either displays it as text on the application screen or plays it back as audio using TTS (Text-to-Speech) functionality.

[0074] As a concrete example, consider a scenario where a user visits a museum that is a historical cultural asset. The terminal confirms the location of this museum, and the server uses a generative model to generate information about the museum from its database, along with detailed descriptions of medieval paintings that the user is particularly interested in. This generation process utilizes prompts such as, "Tell me more about the exhibits at the museum at my current location."

[0075] This allows users to obtain detailed information in multiple languages ​​on the spot, tailored to their interests, making their travel experience deeper and more personalized.

[0076] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0077] Step 1:

[0078] The device obtains location information using a GPS sensor. During this process, the device updates its location every few seconds, acquiring latitude and longitude data. This information is prepared as packet data and sent to the server as location information. The input is location data from the device's GPS sensor, and the output is structured location information data for transmission to the server.

[0079] Step 2:

[0080] The server receives location data sent from the terminal. The server then sends an SQL query to the database to retrieve regional data related to this location. The input here is the location data, and the output is the relevant tourist destination data and related information. The server extracts the relevant regional information from the database.

[0081] Step 3:

[0082] The server retrieves the user's preferences from the database and filters the retrieved tourist destination data. The input consists of tourist destination data from the database and the user's preferences, while the output is a filtered list of tourist destinations that match the user's interests. Through this filtering process, the server selects the data best suited to the user.

[0083] Step 4:

[0084] The server uses a generative AI model to generate guide content based on filtered tourist destination information. Here, the generative model is activated based on prompt text to create a customized text description for the user. The input is filtered data and prompt text, and the output is the generated text guide.

[0085] Step 5:

[0086] The server sends the generated guide content to a multilingual translation API, which translates it into the language set on the user's device. The input is the generated text guide in the target language, and the output is the translated multilingual text. The server performs the translation using the appropriate translation service.

[0087] Step 6:

[0088] The server sends the translated guide content to the terminal using the HTTPS protocol. The input is the translated multilingual text, and the output is delivery to the terminal. The server verifies that the data is transmitted securely during transmission.

[0089] Step 7:

[0090] The terminal receives the distributed translated guide information and displays or plays it as audio within the application. Input is data received from the server, and output is display on the user interface or audio output. The terminal presents the information in an appropriate format according to the user's selection.

[0091] (Application Example 1)

[0092] 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."

[0093] Modern tourists require real-time, effective access to information tailored to their individual interests and preferences. However, traditional tourist guide systems can only provide general information, making it difficult to adequately address users' specific needs. Furthermore, even multilingual and practical information delivery methods have limitations in terms of efficiency and accuracy. Therefore, a system was needed that could flexibly respond to diverse user needs and further personalize and optimize the tourist experience.

[0094] 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.

[0095] In this invention, the server includes means for acquiring location data, means for filtering tourist destination data based on user interest and preference data, and means for generating and translating explanatory content using a generation device. This allows users to receive detailed and personalized tourist information in real time according to their current location and interests. Furthermore, voice output enables intuitive information provision to users of various languages.

[0096] "Location data" refers to geographical information indicating the user's current location, and is measured using GPS or other location information acquisition methods.

[0097] "Tourist destination data" refers to a collection of information about a tourist destination, including detailed information about its history, culture, and notable landmarks.

[0098] "User interest and preference data" refers to information about specific genres or themes that users are interested in, and is collected based on the user's past behavior and choices.

[0099] A "generation device" is a system that has the function of creating explanatory content based on input data, and uses an AI model to generate content that is suitable for the user.

[0100] "Description content" refers to text or audio data containing specific information related to tourist destinations, and is guide information generated based on the user's interests.

[0101] "Translation" is the process of converting generated explanatory content into the user's chosen language, and is a process for accurately conveying information between different languages.

[0102] To implement this invention, first, the user's terminal acquires location data using GPS. The acquired location data is transmitted to a server via the network. The server receives this location data and the user's already registered interest and preference data. Using this, it searches for relevant tourist destination data in a database.

[0103] The server filters search results based on the user's interests and preferences. Based on the filtered tourist destination data, a generator automatically produces appropriate descriptions. This generation uses the latest AI model. The generated descriptions are then translated into the user's specified language. High-precision language conversion software is used for the translation.

[0104] The translated explanations are delivered to the user's device. This allows the device to play the explanations as audio in real time using its audio output device. As a result, users can obtain the necessary information on the spot and enjoy a sightseeing experience that doesn't rely on visual cues.

[0105] As a concrete example, when a user visits a museum, the server retrieves the museum's exhibition data and generates a detailed description of "medieval paintings" that the user is interested in. This content is then translated into the user's chosen language, for example, Japanese, and delivered to the user's device. In this case, an example of a prompt message to the generating AI model would be in text format: "The user has expressed interest in 'medieval paintings.' Please generate a detailed description of the relevant paintings in the museum."

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The user's device uses its GPS function to obtain current location data. This location data includes latitude and longitude information. The obtained location data is prepared for transmission to the server. The input is GPS data, and the output is location data ready for transmission to the server.

[0109] Step 2:

[0110] The server receives location data from the user's device. Using this location data as input, the server searches a relevant tourist destination database and extracts tourist destination data for the corresponding location. The output is the corresponding tourist destination data.

[0111] Step 3:

[0112] The server retrieves user interest and preference data from the database and filters it in combination with tourist destination data. In this process, highly relevant information is selected based on the user's past interests. The input is tourist destination data and interest and preference data, and the output is filtered tourist destination data.

[0113] Step 4:

[0114] The server uses a generative AI model to generate detailed descriptions based on filtered tourist destination data. In this step, a prompt is created, and the AI ​​model generates text based on the prompt. The input is the filtered tourist destination data, and the output is the generated description.

[0115] Step 5:

[0116] The server translates the generated description into the language specified by the user. This translation process uses multilingual translation software. The input is the generated description, and the output is the translated description.

[0117] Step 6:

[0118] The server delivers the translated explanation to the user's terminal. The terminal receives this and plays the audio in real time using an audio output unit. The input is the translated explanation, and the output is the audio information provided to the user through the audio output device.

[0119] 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.

[0120] This invention is a system that recognizes a user's emotions and provides a personalized tourist guide based on those emotions. First, the terminal uses GPS to obtain the user's precise location information. This location information is sent to a server, which searches a database for information on relevant tourist destinations.

[0121] The server utilizes user interest and preference information to filter information in the database and select information that is highly relevant to the user. Furthermore, it uses a generative model to dynamically generate guide content that aligns with the user's preferences.

[0122] The emotion engine uses sensors such as cameras and microphones to analyze the user's voice tone and facial expressions, recognizing their emotions in real time. Based on this, the server adjusts the guide information provided according to the user's emotional state. For example, if the user is excited, the server might emphasize particularly interesting content.

[0123] The translation tool converts the generated guide content into the language set on the user's device. The translated content is sent to the device, which then provides the information in audio or text format.

[0124] For example, when a user visits a historical castle, if the emotion engine detects the user's surprise, the server can provide additional interesting anecdotes. In this way, the present invention enables flexible information delivery based on emotions, thereby improving the user experience.

[0125] The following describes the processing flow.

[0126] Step 1:

[0127] The device uses GPS to obtain the user's current location information. The obtained location information is recorded as latitude and longitude.

[0128] Step 2:

[0129] The device sends location information to the server. The server receives this information and searches its database for information on the corresponding tourist destination.

[0130] Step 3:

[0131] The server references the user's interests and preferences and filters the tourist destination information in the database to provide the most relevant information for the user.

[0132] Step 4:

[0133] Based on filtered tourist destination information, the server uses a generative model to generate guide content. This guide content is designed to be as relevant as possible to the user's interests.

[0134] Step 5:

[0135] The device uses its camera and microphone to analyze the user's facial expressions and voice using an emotion engine, acquiring emotional data in real time.

[0136] Step 6:

[0137] The server analyzes the user's current emotional state based on data from the emotion engine. The guide content provided is then adjusted according to the analysis results.

[0138] Step 7:

[0139] The server translates the adjusted guide content into the language set on the user's device. Once the translation is complete through multilingual support, the guide content is sent to the device.

[0140] Step 8:

[0141] The device can either play the received guide content as audio or display it as text on the screen. This allows users to acquire information at their own pace.

[0142] Step 9:

[0143] If the user shows further interest in the guide content, the device requests additional information from the server. Based on this request, the server retrieves more detailed information and sends it to the device.

[0144] (Example 2)

[0145] 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".

[0146] In modern tourism systems, providing information based on user location and basic interests is common, but personalized information that takes user emotions into account is not provided. As a result, tourism experiences become uniform, making it difficult to improve user satisfaction and interest. Furthermore, there are still challenges in the flexibility of providing information in multiple languages. This invention aims to solve these problems and provide flexible tourism guidance that is attentive to the user's emotions.

[0147] 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.

[0148] In this invention, the server includes means for acquiring location information, means for dynamically generating personalized guide content from filtered tourist destination information using a generative model, and means for recognizing the user's emotions using sensors. This enables flexible adjustment of tourist information according to the user's emotional state and multilingual guide guidance.

[0149] "Devices for acquiring location information" refers to any hardware or software used to determine the latitude and longitude of a user's current location.

[0150] "Means for searching tourist destination information" refers to a system that retrieves data about relevant tourist destinations from a database based on the user's location information.

[0151] "User interest and preference information" refers to information that represents an individual's preferences and interests, estimated based on a user's past behavior and explicit choices.

[0152] "Filtering methods" refer to methods that utilize user interest and preference information to select important or relevant information from acquired tourist destination data.

[0153] A "generative model" is an AI algorithm that automatically generates appropriate tourist guide information based on the user's preferences and emotions.

[0154] "Means of recognizing user emotions using sensors" refers to devices and programs that detect a user's facial expressions and voice tone, and evaluate and judge their emotions from there.

[0155] "Means of adjusting guide content based on emotional information" refers to methods of dynamically changing the content and expression of tourist information provided in accordance with the user's emotions.

[0156] "Means of translating into a specified language" refers to technology for converting the generated guide content into a language that the user can understand.

[0157] "Means of delivering to user terminals" refers to methods of transferring the customized tourism information to devices available to the user.

[0158] This invention relates to a system that recognizes a user's emotions and provides a personalized tourist guide tailored to those emotions. This system primarily consists of a terminal, a server, and user interaction.

[0159] First, the device accurately acquires the user's location information using GPS technology. This utilizes the GPS module in the smartphone or dedicated device. The acquired location information is transmitted to the server in real time via the internet connection.

[0160] The server searches the database for relevant tourist destination information based on the received location data. A generative AI model is used to filter and select information, taking into account the user's interests and preferences. This generative AI model, for example, utilizes a large-scale neural network to dynamically generate optimal guide content for the user.

[0161] Next, the system uses sensors such as the camera and microphone built into the device to acquire data on the user's voice tone and facial expressions. Based on this data, the server activates an emotion engine to analyze the user's emotions. Based on this analysis, the server can adjust the guide content to match the user's emotional state. For example, if the user is surprised, the system will provide information that emphasizes interesting facts or anecdotes.

[0162] Furthermore, the guide content generated by the translation system is converted into the user's chosen language. Automatic translation software is used for this translation, enabling multilingual support. The translated guide is provided to the user via the device in either audio or text format.

[0163] As a concrete example, imagine a user using this system while touring a historical castle. When the emotion engine detects the user's surprise, the server can provide additional, particularly interesting anecdotes related to the castle's history. This flexible, emotion-responsive information delivery enriches the user's sightseeing experience.

[0164] An example of a prompt might be, "How can we provide relevant anecdotes based on the user's excitement level when visiting a historical site?" This system enables the provision of advanced information based on individual user experiences.

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] The device obtains the user's current location using a GPS module. It receives location data from the user's device as input and outputs it in the form of latitude and longitude. This process makes it possible to pinpoint the user's exact location.

[0168] Step 2:

[0169] The device transmits the acquired location information to the server. The input is location data, which is sent to the server via the internet connection. The server receives the location information as output and prepares it for subsequent processing.

[0170] Step 3:

[0171] The server searches its database for relevant tourist destination information based on the received location data. The input is location data, and it retrieves information about nearby tourist spots through database queries. The output is tourist destination information related to the location. This information is then filtered in the next step, combined with the user's interests and preferences.

[0172] Step 4:

[0173] The server uses user interest and preference information to filter the acquired tourist destination information. The input consists of tourist destination information and user preference data. A generative AI model is used to select the most relevant tourist destination information for each individual user. The output is personalized tourist destination information.

[0174] Step 5:

[0175] The device acquires the user's facial expressions and voice tone through its camera and microphone. Input consists of data collected by sensors, which is then sent to a server. Output is the data necessary for analyzing the user's emotions.

[0176] Step 6:

[0177] The server performs emotion analysis based on the user's facial expressions and voice data received. The input is sensor data, which is analyzed by the emotion engine. The output is a determination of the user's emotional state.

[0178] Step 7:

[0179] The server adjusts personalized tourist information based on the user's emotional state. The input consists of filtered tourist information and emotional data, and a generative AI model is used to highlight interesting information and add new information. The output is emotionally responsive tourist guide information.

[0180] Step 8:

[0181] The server translates the generated guide information into the user-specified language. The input is the guide information, which is automatically translated into each user's native language using natural language processing technology. The output is the translated guide information.

[0182] Step 9:

[0183] The device receives translated guide information and provides it to the user in audio or text format. The input is the translated information, presented to the user visually and aurally using speech synthesis technology and a display. The output is the actual guide information provided to enhance the user experience.

[0184] (Application Example 2)

[0185] 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".

[0186] Traditional tourist information systems are limited to providing information based on users' interests and preferences, making it difficult to flexibly adjust guide content to respond to users' emotions. Furthermore, the inability to provide emotion-based information in real time sometimes resulted in insufficient optimization of the user experience.

[0187] 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.

[0188] In this invention, the server includes a device for acquiring location information, means for searching for relevant tourist destination information based on said location information, means for acquiring user interest and preference information and filtering the search results based on said interest and preference information, and means for recognizing the user's emotions and adjusting the guide content based on said emotions. This makes it possible to provide personalized guide information in response to the user's emotions in real time.

[0189] A "device for acquiring location information" is a device that uses location information technology such as GPS to collect geographical data in order to determine the user's current location.

[0190] "Means for searching for relevant tourist destination information" refers to a method or device for retrieving detailed information about tourist destinations related to a given region from a database or other source, based on acquired location information.

[0191] "Means for acquiring user interest and preference information and filtering search results based on said interest and preference information" refers to a method or function for acquiring information that the user is interested in and then narrowing down tourist destination information based on that information.

[0192] A "generative model for generating guide content" is a model that uses AI and other technologies to generate guide information to present to users, using filtered tourist destination information.

[0193] "Means for recognizing user emotions and adjusting guide content based on those emotions" refers to a method or apparatus for analyzing a user's facial expressions and voice using a camera or microphone, and optimizing the guide information provided according to the detected user emotions.

[0194] "Means for translating generated guide content into a user-specified language" refers to a method or technology for converting generated guide information into the language used by the user.

[0195] "Means for delivering the translated guide content to the user's terminal" refers to a method or technology for transmitting translated guidance information to the user's terminal and providing it through display or audio, etc.

[0196] This system provides personalized tourist information based on the user's emotions. First, the user's device is equipped with a GPS module to acquire location information, and accurate location data is sent to the server. Based on this location information, the server searches its database for information on relevant tourist destinations.

[0197] Search results are filtered based on the user's interests and preferences. Personalized guide information is generated by extracting information that matches the user's hobbies and interests. The server then uses a generative AI model to create user-specific guide content based on the filtered tourist destination information.

[0198] Furthermore, the device uses its built-in camera and microphone to analyze the user's facial expressions and voice in real time and recognize their emotions. This analysis utilizes emotion recognition software (e.g., OpenFace, Google® Cloud Speech-to-Text). Once the user's emotions are recognized, the guide content is dynamically adjusted accordingly.

[0199] The generated guide content is translated into the user's specified language, and the translated information is delivered to the user's device. Translation software (e.g., Google Translate API) is used for the translation. Finally, the user's device provides the guide content in audio or text format through its speaker or display.

[0200] As a concrete example, if a foreign tourist visiting an ancient Japanese capital shows signs of excitement, emotion recognition technology can detect this excitement. Based on this information, the server provides a guide that highlights the interesting historical background and anecdotes of the temple they are visiting.

[0201] An example of a prompt message would be: "Please provide additional information about what surprised the user. The tourist spot is a temple in Kyoto. Please provide an anecdote or information that would interest the user."

[0202] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0203] Step 1:

[0204] The device uses a GPS module to obtain the user's location information. The input is a signal from the GPS, and the output is latitude and longitude location data. This allows the user's current location to be determined.

[0205] Step 2:

[0206] The server receives location information and uses it to search for relevant tourist destination information in the database. The input is location data received from the device, and the output is a list of tourist spots associated with that location. SQL queries are used in this process to retrieve information from the database.

[0207] Step 3:

[0208] The server retrieves the user's interests and preferences and filters the aforementioned list of tourist destinations. The input consists of the user's interests and preferences data and the list of tourist destinations, and the output is a selection of tourist destinations that match the user's interests. A data filtering algorithm is applied to perform the selection.

[0209] Step 4:

[0210] The server utilizes a generated AI model to create guide content based on selected tourist destination information. The input is filtered tourist destination information, and the output is the guide content. In this process, a language model is used to construct the explanation in natural language.

[0211] Step 5:

[0212] The device uses its camera and microphone to analyze the user's voice and facial expressions, and recognizes their emotions. The input is real-time data from the camera and microphone, and the output is the user's emotional state. Emotion recognition software is used to analyze facial expressions and voice tone.

[0213] Step 6:

[0214] The server adjusts the pre-generated guide content based on the user's emotions. The input is the user's emotional state, and the output is the adjusted guide content. An adjustment algorithm is used to emphasize or add information.

[0215] Step 7:

[0216] The server translates the generated guide content into the user's specified language. The input is the guide content, and the output is the translated guide content. Language conversion is performed using translation software.

[0217] Step 8:

[0218] The device delivers translated guide content to the user and presents the information. The input is the translated guide content, and the output is information provided in audio or text format. The information is presented to the user through the device's speaker or display.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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".

[0235] This invention is a system that provides tourist destination information related to a user's location using that location information. Specifically, location information is acquired from sensors such as GPS through a device such as a smartphone or tablet used by the user. This location information is transmitted to a server in the cloud.

[0236] The server uses location information received from the user, along with pre-registered user interest and preference information, to query the database and search for relevant tourist destination information. Based on these search results, it filters tourist information that matches the user's interests and preferences, and automatically generates guide content using a generative model.

[0237] The generated guide content is translated based on the language set on the user's device. The server performs this multilingual translation, providing the information in the format that is easiest for the user to understand. This translated guide data is delivered to the user's device, which can then play it as audio or display it as text.

[0238] As a concrete example, consider a scenario where a user visits a historical art museum. In this case, the device detects the user's current location, and the server retrieves information about the museum from a database. Furthermore, based on categories the user has shown particular interest in (e.g., "medieval paintings" or "a specific painter"), the generative model generates a detailed description, translates it into the user's language, and sends it to the device.

[0239] Ultimately, users can choose and listen to only the information that interests them at their own pace, making their travel experience more enriching. This system is designed to individually optimize the user experience and effectively deliver travel information.

[0240] The following describes the processing flow.

[0241] Step 1:

[0242] The device activates its GPS sensor and performs the operation of acquiring its own location information (latitude and longitude).

[0243] Step 2:

[0244] The device transmits its acquired location information to the server in real time. This process involves data communication.

[0245] Step 3:

[0246] The server receives the transmitted location information and searches the database for tourist destination information related to that location.

[0247] Step 4:

[0248] The server refers to the user's pre-registered interests and preferences and filters the searched tourist destination information to include relevant results.

[0249] Step 5:

[0250] Based on the filtered information, the server uses a generative model to generate user guidance content.

[0251] Step 6:

[0252] The server translates the generated guide content according to the user's device language settings and prepares multilingual data.

[0253] Step 7:

[0254] The server sends the translated guide data to the terminal and provides it in a format that the user can access.

[0255] Step 8:

[0256] The device processes the received guide data and either plays the audio guide or displays the text.

[0257] Step 9:

[0258] If a user requests more details about information they are interested in on their device, the device sends a request to the server, and additional information is provided.

[0259] (Example 1)

[0260] 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."

[0261] In tourist destination information search systems, there is a need to efficiently provide information tailored to the user's current location and individual interests. However, conventional systems have the problem that location-based search results are not personalized, and useful information is not provided to users in a timely manner. Furthermore, information provision in different languages ​​is insufficient, making it difficult to effectively generate and provide multilingual guides.

[0262] 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.

[0263] In this invention, the server includes means for acquiring user preference information and selecting search results based on said preference information, a generation model for generating explanatory content using the selected regional information, and means for converting the generated explanatory content into the user's specified language. This makes it possible to efficiently provide customized tourist information in multiple languages ​​that is tailored to the user's location and individual preferences.

[0264] "Location" refers to information indicating the user's current location, and is usually expressed as latitude and longitude on Earth.

[0265] "Device" refers to a device used to acquire location information, such as a mobile terminal with GPS functionality.

[0266] "Means of searching" refers to methods and technologies for finding relevant regional information by searching a database based on acquired location information.

[0267] "User preference information" refers to data about users' interests and preferences, and is used to select the information provided.

[0268] "Selection methods" refer to the processes and technologies used to select items that match the user's preferences based on the acquired information.

[0269] A "generative model" refers to an algorithm or program used to create relevant descriptions or instructions based on specific input conditions.

[0270] "Means of converting into language" refers to translation technologies and systems used to display the generated explanatory content in multiple languages.

[0271] "User device" refers to a device that the user directly uses, and includes smartphones and tablets.

[0272] "Means of customization" refers to technologies and methods that adaptively adjust information according to the individual needs and requirements of the user.

[0273] This system provides relevant tourist destination information based on the user's location. Specifically, it requires a smartphone or tablet as the user's device. The device uses its built-in GPS sensor to obtain the user's current location and sends it to a server in the cloud. The device securely transmits data packets, including the obtained location information, to the server using the HTTPS protocol.

[0274] The server uses this location information and pre-registered user interest and preference information to search the database. Database query techniques such as SQL are used to extract regional information relevant to the user's location. Next, the user's preference information is referenced to filter the relevant regional information based on the search results. The filtered data is analyzed by a generative AI model to generate customized guide content. This generative model utilizes algorithms employing natural language processing techniques to automatically create contextually appropriate explanations.

[0275] The generated guide content is processed by a multilingual translation service and translated into the user's specified language. For multilingual support, a cloud-based translation API is used to translate the generated text in real time. This translated guide information is then delivered to the user's device using HTTPS. The device stores the received information and either displays it as text on the application screen or plays it back as audio using TTS (Text-to-Speech) functionality.

[0276] As a concrete example, consider a scenario where a user visits a museum that is a historical cultural asset. The terminal confirms the location of this museum, and the server uses a generative model to generate information about the museum from its database, along with detailed descriptions of medieval paintings that the user is particularly interested in. This generation process utilizes prompts such as, "Tell me more about the exhibits at the museum at my current location."

[0277] This allows users to obtain detailed information in multiple languages ​​on the spot, tailored to their interests, making their travel experience deeper and more personalized.

[0278] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0279] Step 1:

[0280] The device obtains location information using a GPS sensor. During this process, the device updates its location every few seconds, acquiring latitude and longitude data. This information is prepared as packet data and sent to the server as location information. The input is location data from the device's GPS sensor, and the output is structured location information data for transmission to the server.

[0281] Step 2:

[0282] The server receives the location information data sent from the terminal. The server then sends an SQL query to the database to search for the regional data related to this location information. Here, the input is the location information data, and the output is the corresponding tourist destination data and related information. The server extracts the corresponding regional information from the database.

[0283] Step 3:

[0284] The server retrieves the preference information of its user from the database and filters the obtained tourist destination data. The input is the tourist destination data from the database and the user's preference information, and the output is a filtered list of tourist destinations that match the user's interests. The server selects the most suitable data for the user through this filtering process.

[0285] Step 4:

[0286] The server uses a generative AI model to generate guide content based on the filtered tourist destination information. Here, the generation model is operated based on the prompt text to create a customized text description for the user. The input is the filtered data and the prompt text, and the output is the generated text guide.

[0287] Step 5:

[0288] The server sends the generated guide content to a multilingual translation API for translation into the language set on the user's terminal. The input is the generated text guide and the target language, and the output is the translated multilingual text. The server performs the translation operation using an appropriate translation service.

[0289] Step 6:

[0290] The server sends the translated guide content to the terminal using the HTTPS protocol. The input is the translated multilingual text, and the output is the delivery to the terminal. The server confirms that the data is transmitted securely during the sending process.

[0291] Step 7:

[0292] The terminal receives the distributed translated guide information and displays or plays it as audio within the application. Input is data received from the server, and output is display on the user interface or audio output. The terminal presents the information in an appropriate format according to the user's selection.

[0293] (Application Example 1)

[0294] 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."

[0295] Modern tourists require real-time, effective access to information tailored to their individual interests and preferences. However, traditional tourist guide systems can only provide general information, making it difficult to adequately address users' specific needs. Furthermore, even multilingual and practical information delivery methods have limitations in terms of efficiency and accuracy. Therefore, a system was needed that could flexibly respond to diverse user needs and further personalize and optimize the tourist experience.

[0296] 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.

[0297] In this invention, the server includes means for acquiring location data, means for filtering tourist destination data based on user interest and preference data, and means for generating and translating explanatory content using a generation device. This allows users to receive detailed and personalized tourist information in real time according to their current location and interests. Furthermore, voice output enables intuitive information provision to users of various languages.

[0298] "Location data" refers to geographical information indicating the user's current location, and is measured using GPS or other location information acquisition methods.

[0299] "Tourist destination data" refers to a collection of information about a tourist destination, including detailed information about its history, culture, and notable landmarks.

[0300] "User interest and preference data" refers to information about specific genres or themes that users are interested in, and is collected based on the user's past behavior and choices.

[0301] A "generation device" is a system that has the function of creating explanatory content based on input data, and uses an AI model to generate content that is suitable for the user.

[0302] "Description content" refers to text or audio data containing specific information related to tourist destinations, and is guide information generated based on the user's interests.

[0303] "Translation" is the process of converting generated explanatory content into the user's chosen language, and is a process for accurately conveying information between different languages.

[0304] To implement this invention, first, the user's terminal acquires location data using GPS. The acquired location data is transmitted to a server via the network. The server receives this location data and the user's already registered interest and preference data. Using this, it searches for relevant tourist destination data in a database.

[0305] The server filters search results based on the user's interests and preferences. Based on the filtered tourist destination data, a generator automatically produces appropriate descriptions. This generation uses the latest AI model. The generated descriptions are then translated into the user's specified language. High-precision language conversion software is used for the translation.

[0306] The translated explanatory content is distributed to the user's terminal. As a result, the terminal can reproduce the explanatory content as audio in real time using the audio output device. Thus, the user can obtain the necessary information on-site and enjoy a tourism experience that does not rely on vision.

[0307] As a specific example, when a user visits an art museum, the server acquires the exhibition data of the art museum and generates a detailed explanation about "medieval paintings" that the user is interested in. These contents are translated into the language selected by the user, for example, Japanese, and distributed to the user's terminal. At this time, as an example of the prompt sentence to the generation AI model, a text form such as "The user shows interest in'medieval paintings'. Please generate a detailed explanation about related paintings in the art museum." is used.

[0308] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0309] Step 1:

[0310] The user's terminal uses the GPS function to acquire the current position data. This position data includes latitude and longitude information. The acquired position data is prepared to be transmitted to the server. The input is GPS data, and the output is the position data ready to be transmitted to the server.

[0311] Step 2:

[0312] The server receives the position data from the user's terminal. Using this position data as input, the server searches the relevant tourist destination database and extracts the tourist destination data regarding the corresponding place. The output is the corresponding tourist destination data.

[0313] Step 3:

[0314] The server retrieves user interest and preference data from the database and filters it in combination with tourist destination data. In this process, highly relevant information is selected based on the user's past interests. The input is tourist destination data and interest and preference data, and the output is filtered tourist destination data.

[0315] Step 4:

[0316] The server uses a generative AI model to generate detailed descriptions based on filtered tourist destination data. In this step, a prompt is created, and the AI ​​model generates text based on the prompt. The input is the filtered tourist destination data, and the output is the generated description.

[0317] Step 5:

[0318] The server translates the generated description into the language specified by the user. This translation process uses multilingual translation software. The input is the generated description, and the output is the translated description.

[0319] Step 6:

[0320] The server delivers the translated explanation to the user's terminal. The terminal receives this and plays the audio in real time using an audio output unit. The input is the translated explanation, and the output is the audio information provided to the user through the audio output device.

[0321] 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.

[0322] This invention is a system that recognizes a user's emotions and provides a personalized tourist guide based on those emotions. First, the terminal uses GPS to obtain the user's precise location information. This location information is sent to a server, which searches a database for information on relevant tourist destinations.

[0323] The server utilizes user interest and preference information to filter information in the database and select information that is highly relevant to the user. Furthermore, it uses a generative model to dynamically generate guide content that aligns with the user's preferences.

[0324] The emotion engine uses sensors such as cameras and microphones to analyze the user's voice tone and facial expressions, recognizing their emotions in real time. Based on this, the server adjusts the guide information provided according to the user's emotional state. For example, if the user is excited, the server might emphasize particularly interesting content.

[0325] The translation tool converts the generated guide content into the language set on the user's device. The translated content is sent to the device, which then provides the information in audio or text format.

[0326] For example, when a user visits a historical castle, if the emotion engine detects the user's surprise, the server can provide additional interesting anecdotes. In this way, the present invention enables flexible information delivery based on emotions, thereby improving the user experience.

[0327] The following describes the processing flow.

[0328] Step 1:

[0329] The device uses GPS to obtain the user's current location information. The obtained location information is recorded as latitude and longitude.

[0330] Step 2:

[0331] The device sends location information to the server. The server receives this information and searches its database for information on the corresponding tourist destination.

[0332] Step 3:

[0333] The server references the user's interests and preferences and filters the tourist destination information in the database to provide the most relevant information for the user.

[0334] Step 4:

[0335] Based on filtered tourist destination information, the server uses a generative model to generate guide content. This guide content is designed to be as relevant as possible to the user's interests.

[0336] Step 5:

[0337] The device uses its camera and microphone to analyze the user's facial expressions and voice using an emotion engine, acquiring emotional data in real time.

[0338] Step 6:

[0339] The server analyzes the user's current emotional state based on data from the emotion engine. The guide content provided is then adjusted according to the analysis results.

[0340] Step 7:

[0341] The server translates the adjusted guide content into the language set on the user's device. Once the translation is complete through multilingual support, the guide content is sent to the device.

[0342] Step 8:

[0343] The device can either play the received guide content as audio or display it as text on the screen. This allows users to acquire information at their own pace.

[0344] Step 9:

[0345] If the user shows further interest in the guide content, the device requests additional information from the server. Based on this request, the server retrieves more detailed information and sends it to the device.

[0346] (Example 2)

[0347] 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".

[0348] In modern tourism systems, providing information based on user location and basic interests is common, but personalized information that takes user emotions into account is not provided. As a result, tourism experiences become uniform, making it difficult to improve user satisfaction and interest. Furthermore, there are still challenges in the flexibility of providing information in multiple languages. This invention aims to solve these problems and provide flexible tourism guidance that is attentive to the user's emotions.

[0349] 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.

[0350] In this invention, the server includes means for acquiring location information, means for dynamically generating personalized guide content from filtered tourist destination information using a generative model, and means for recognizing the user's emotions using sensors. This enables flexible adjustment of tourist information according to the user's emotional state and multilingual guide guidance.

[0351] "Devices for acquiring location information" refers to any hardware or software used to determine the latitude and longitude of a user's current location.

[0352] "Means for searching tourist destination information" refers to a system that retrieves data about relevant tourist destinations from a database based on the user's location information.

[0353] "User interest and preference information" refers to information that represents an individual's preferences and interests, estimated based on a user's past behavior and explicit choices.

[0354] "Filtering methods" refer to methods that utilize user interest and preference information to select important or relevant information from acquired tourist destination data.

[0355] A "generative model" is an AI algorithm that automatically generates appropriate tourist guide information based on the user's preferences and emotions.

[0356] "Means of recognizing user emotions using sensors" refers to devices and programs that detect a user's facial expressions and voice tone, and evaluate and judge their emotions from there.

[0357] "Means of adjusting guide content based on emotional information" refers to methods of dynamically changing the content and expression of tourist information provided in accordance with the user's emotions.

[0358] "Means of translating into a specified language" refers to technology for converting the generated guide content into a language that the user can understand.

[0359] "Means of delivering to user terminals" refers to methods of transferring the customized tourism information to devices available to the user.

[0360] This invention relates to a system that recognizes a user's emotions and provides a personalized tourist guide tailored to those emotions. This system primarily consists of a terminal, a server, and user interaction.

[0361] First, the device accurately acquires the user's location information using GPS technology. This utilizes the GPS module in the smartphone or dedicated device. The acquired location information is transmitted to the server in real time via the internet connection.

[0362] The server searches the database for relevant tourist destination information based on the received location data. A generative AI model is used to filter and select information, taking into account the user's interests and preferences. This generative AI model, for example, utilizes a large-scale neural network to dynamically generate optimal guide content for the user.

[0363] Next, the system uses sensors such as the camera and microphone built into the device to acquire data on the user's voice tone and facial expressions. Based on this data, the server activates an emotion engine to analyze the user's emotions. Based on this analysis, the server can adjust the guide content to match the user's emotional state. For example, if the user is surprised, the system will provide information that emphasizes interesting facts or anecdotes.

[0364] Furthermore, the guide content generated by the translation system is converted into the user's chosen language. Automatic translation software is used for this translation, enabling multilingual support. The translated guide is provided to the user via the device in either audio or text format.

[0365] As a concrete example, imagine a user using this system while touring a historical castle. When the emotion engine detects the user's surprise, the server can provide additional, particularly interesting anecdotes related to the castle's history. This flexible, emotion-responsive information delivery enriches the user's sightseeing experience.

[0366] An example of a prompt might be, "How can we provide relevant anecdotes based on the user's excitement level when visiting a historical site?" This system enables the provision of advanced information based on individual user experiences.

[0367] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0368] Step 1:

[0369] The device obtains the user's current location using a GPS module. It receives location data from the user's device as input and outputs it in the form of latitude and longitude. This process makes it possible to pinpoint the user's exact location.

[0370] Step 2:

[0371] The device transmits the acquired location information to the server. The input is location data, which is sent to the server via the internet connection. The server receives the location information as output and prepares it for subsequent processing.

[0372] Step 3:

[0373] The server searches its database for relevant tourist destination information based on the received location data. The input is location data, and it retrieves information about nearby tourist spots through database queries. The output is tourist destination information related to the location. This information is then filtered in the next step, combined with the user's interests and preferences.

[0374] Step 4:

[0375] The server uses user interest and preference information to filter the acquired tourist destination information. The input consists of tourist destination information and user preference data. A generative AI model is used to select the most relevant tourist destination information for each individual user. The output is personalized tourist destination information.

[0376] Step 5:

[0377] The device acquires the user's facial expressions and voice tone through its camera and microphone. Input consists of data collected by sensors, which is then sent to a server. Output is the data necessary for analyzing the user's emotions.

[0378] Step 6:

[0379] The server performs emotion analysis based on the user's facial expressions and voice data received. The input is sensor data, which is analyzed by the emotion engine. The output is a determination of the user's emotional state.

[0380] Step 7:

[0381] The server adjusts personalized tourist information based on the user's emotional state. The input consists of filtered tourist information and emotional data, and a generative AI model is used to highlight interesting information and add new information. The output is emotionally responsive tourist guide information.

[0382] Step 8:

[0383] The server translates the generated guide information into the user-specified language. The input is the guide information, which is automatically translated into each user's native language using natural language processing technology. The output is the translated guide information.

[0384] Step 9:

[0385] The device receives translated guide information and provides it to the user in audio or text format. The input is the translated information, presented to the user visually and aurally using speech synthesis technology and a display. The output is the actual guide information provided to enhance the user experience.

[0386] (Application Example 2)

[0387] 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."

[0388] Traditional tourist information systems are limited to providing information based on users' interests and preferences, making it difficult to flexibly adjust guide content to respond to users' emotions. Furthermore, the inability to provide emotion-based information in real time sometimes resulted in insufficient optimization of the user experience.

[0389] 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.

[0390] In this invention, the server includes a device for acquiring location information, means for searching for relevant tourist destination information based on said location information, means for acquiring user interest and preference information and filtering the search results based on said interest and preference information, and means for recognizing the user's emotions and adjusting the guide content based on said emotions. This makes it possible to provide personalized guide information in response to the user's emotions in real time.

[0391] A "device for acquiring location information" is a device that uses location information technology such as GPS to collect geographical data in order to determine the user's current location.

[0392] "Means for searching for relevant tourist destination information" refers to a method or device for retrieving detailed information about tourist destinations related to a given region from a database or other source, based on acquired location information.

[0393] "Means for acquiring user interest and preference information and filtering search results based on said interest and preference information" refers to a method or function for acquiring information that the user is interested in and then narrowing down tourist destination information based on that information.

[0394] A "generative model for generating guide content" is a model that uses AI and other technologies to generate guide information to present to users, using filtered tourist destination information.

[0395] "Means for recognizing user emotions and adjusting guide content based on those emotions" refers to a method or apparatus for analyzing a user's facial expressions and voice using a camera or microphone, and optimizing the guide information provided according to the detected user emotions.

[0396] "Means for translating generated guide content into a user-specified language" refers to a method or technology for converting generated guide information into the language used by the user.

[0397] "Means for delivering the translated guide content to the user's terminal" refers to a method or technology for transmitting translated guidance information to the user's terminal and providing it through display or audio, etc.

[0398] This system provides personalized tourist information based on the user's emotions. First, the user's device is equipped with a GPS module to acquire location information, and accurate location data is sent to the server. Based on this location information, the server searches its database for information on relevant tourist destinations.

[0399] Search results are filtered based on the user's interests and preferences. Personalized guide information is generated by extracting information that matches the user's hobbies and interests. The server then uses a generative AI model to create user-specific guide content based on the filtered tourist destination information.

[0400] Furthermore, the device uses its built-in camera and microphone to analyze the user's facial expressions and voice in real time and recognize their emotions. This analysis utilizes emotion recognition software (e.g., OpenFace, Google Cloud Speech-to-Text). Once the user's emotions are recognized, the guide content is dynamically adjusted accordingly.

[0401] The generated guide content is translated into the user's specified language, and the translated information is delivered to the user's device. Translation software (e.g., Google Translate API) is used for the translation. Finally, the user's device provides the guide content in audio or text format through its speaker or display.

[0402] As a concrete example, if a foreign tourist visiting an ancient Japanese capital shows signs of excitement, emotion recognition technology can detect this excitement. Based on this information, the server provides a guide that highlights the interesting historical background and anecdotes of the temple they are visiting.

[0403] An example of a prompt message would be: "Please provide additional information about what surprised the user. The tourist spot is a temple in Kyoto. Please provide an anecdote or information that would interest the user."

[0404] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0405] Step 1:

[0406] The device uses a GPS module to obtain the user's location information. The input is a signal from the GPS, and the output is latitude and longitude location data. This allows the user's current location to be determined.

[0407] Step 2:

[0408] The server receives location information and uses it to search for relevant tourist destination information in the database. The input is location data received from the device, and the output is a list of tourist spots associated with that location. SQL queries are used in this process to retrieve information from the database.

[0409] Step 3:

[0410] The server retrieves the user's interests and preferences and filters the aforementioned list of tourist destinations. The input consists of the user's interests and preferences data and the list of tourist destinations, and the output is a selection of tourist destinations that match the user's interests. A data filtering algorithm is applied to perform the selection.

[0411] Step 4:

[0412] The server utilizes a generated AI model to create guide content based on selected tourist destination information. The input is filtered tourist destination information, and the output is the guide content. In this process, a language model is used to construct the explanation in natural language.

[0413] Step 5:

[0414] The device uses its camera and microphone to analyze the user's voice and facial expressions, and recognizes their emotions. The input is real-time data from the camera and microphone, and the output is the user's emotional state. Emotion recognition software is used to analyze facial expressions and voice tone.

[0415] Step 6:

[0416] The server adjusts the pre-generated guide content based on the user's emotions. The input is the user's emotional state, and the output is the adjusted guide content. An adjustment algorithm is used to emphasize or add information.

[0417] Step 7:

[0418] The server translates the generated guide content into the user's specified language. The input is the guide content, and the output is the translated guide content. Language conversion is performed using translation software.

[0419] Step 8:

[0420] The device delivers translated guide content to the user and presents the information. The input is the translated guide content, and the output is information provided in audio or text format. The information is presented to the user through the device's speaker or display.

[0421] 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.

[0422] 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.

[0423] 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.

[0424] [Third Embodiment]

[0425] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0426] 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.

[0427] 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).

[0428] 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.

[0429] 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.

[0430] 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).

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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".

[0437] This invention is a system that provides tourist destination information related to a user's location using that location information. Specifically, location information is acquired from sensors such as GPS through a device such as a smartphone or tablet used by the user. This location information is transmitted to a server in the cloud.

[0438] The server uses location information received from the user, along with pre-registered user interest and preference information, to query the database and search for relevant tourist destination information. Based on these search results, it filters tourist information that matches the user's interests and preferences, and automatically generates guide content using a generative model.

[0439] The generated guide content is translated based on the language set on the user's device. The server performs this multilingual translation, providing the information in the format that is easiest for the user to understand. This translated guide data is delivered to the user's device, which can then play it as audio or display it as text.

[0440] As a concrete example, consider a scenario where a user visits a historical art museum. In this case, the device detects the user's current location, and the server retrieves information about the museum from a database. Furthermore, based on categories the user has shown particular interest in (e.g., "medieval paintings" or "a specific painter"), the generative model generates a detailed description, translates it into the user's language, and sends it to the device.

[0441] Ultimately, users can choose and listen to only the information that interests them at their own pace, making their travel experience more enriching. This system is designed to individually optimize the user experience and effectively deliver travel information.

[0442] The following describes the processing flow.

[0443] Step 1:

[0444] The device activates its GPS sensor and performs the operation of acquiring its own location information (latitude and longitude).

[0445] Step 2:

[0446] The device transmits its acquired location information to the server in real time. This process involves data communication.

[0447] Step 3:

[0448] The server receives the transmitted location information and searches the database for tourist destination information related to that location.

[0449] Step 4:

[0450] The server refers to the user's pre-registered interests and preferences and filters the searched tourist destination information to include relevant results.

[0451] Step 5:

[0452] Based on the filtered information, the server uses a generative model to generate user guidance content.

[0453] Step 6:

[0454] The server translates the generated guide content according to the user's device language settings and prepares multilingual data.

[0455] Step 7:

[0456] The server sends the translated guide data to the terminal and provides it in a format that the user can access.

[0457] Step 8:

[0458] The device processes the received guide data and either plays the audio guide or displays the text.

[0459] Step 9:

[0460] If a user requests more details about information they are interested in on their device, the device sends a request to the server, and additional information is provided.

[0461] (Example 1)

[0462] 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."

[0463] In tourist destination information search systems, there is a need to efficiently provide information tailored to the user's current location and individual interests. However, conventional systems have the problem that location-based search results are not personalized, and useful information is not provided to users in a timely manner. Furthermore, information provision in different languages ​​is insufficient, making it difficult to effectively generate and provide multilingual guides.

[0464] 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.

[0465] In this invention, the server includes means for acquiring user preference information and selecting search results based on said preference information, a generation model for generating explanatory content using the selected regional information, and means for converting the generated explanatory content into the user's specified language. This makes it possible to efficiently provide customized tourist information in multiple languages ​​that is tailored to the user's location and individual preferences.

[0466] "Location" refers to information indicating the user's current location, and is usually expressed as latitude and longitude on Earth.

[0467] "Device" refers to a device used to acquire location information, such as a mobile terminal with GPS functionality.

[0468] "Means of searching" refers to methods and technologies for finding relevant regional information by searching a database based on acquired location information.

[0469] "User preference information" refers to data about users' interests and preferences, and is used to select the information provided.

[0470] "Selection methods" refer to the processes and technologies used to select items that match the user's preferences based on the acquired information.

[0471] A "generative model" refers to an algorithm or program used to create relevant descriptions or instructions based on specific input conditions.

[0472] "Means of converting into language" refers to translation technologies and systems used to display the generated explanatory content in multiple languages.

[0473] "User device" refers to a device that the user directly uses, and includes smartphones and tablets.

[0474] "Means of customization" refers to technologies and methods that adaptively adjust information according to the individual needs and requirements of the user.

[0475] This system provides relevant tourist destination information based on the user's location. Specifically, it requires a smartphone or tablet as the user's device. The device uses its built-in GPS sensor to obtain the user's current location and sends it to a server in the cloud. The device securely transmits data packets, including the obtained location information, to the server using the HTTPS protocol.

[0476] The server uses this location information and pre-registered user interest and preference information to search the database. Database query techniques such as SQL are used to extract regional information relevant to the user's location. Next, the user's preference information is referenced to filter the relevant regional information based on the search results. The filtered data is analyzed by a generative AI model to generate customized guide content. This generative model utilizes algorithms employing natural language processing techniques to automatically create contextually appropriate explanations.

[0477] The generated guide content is processed by a multilingual translation service and translated into the user's specified language. For multilingual support, a cloud-based translation API is used to translate the generated text in real time. This translated guide information is then delivered to the user's device using HTTPS. The device stores the received information and either displays it as text on the application screen or plays it back as audio using TTS (Text-to-Speech) functionality.

[0478] As a concrete example, consider a scenario where a user visits a museum that is a historical cultural asset. The terminal confirms the location of this museum, and the server uses a generative model to generate information about the museum from its database, along with detailed descriptions of medieval paintings that the user is particularly interested in. This generation process utilizes prompts such as, "Tell me more about the exhibits at the museum at my current location."

[0479] This allows users to obtain detailed information in multiple languages ​​on the spot, tailored to their interests, making their travel experience deeper and more personalized.

[0480] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0481] Step 1:

[0482] The device obtains location information using a GPS sensor. During this process, the device updates its location every few seconds, acquiring latitude and longitude data. This information is prepared as packet data and sent to the server as location information. The input is location data from the device's GPS sensor, and the output is structured location information data for transmission to the server.

[0483] Step 2:

[0484] The server receives location data sent from the terminal. The server then sends an SQL query to the database to retrieve regional data related to this location. The input here is the location data, and the output is the relevant tourist destination data and related information. The server extracts the relevant regional information from the database.

[0485] Step 3:

[0486] The server retrieves the user's preferences from the database and filters the retrieved tourist destination data. The input consists of tourist destination data from the database and the user's preferences, while the output is a filtered list of tourist destinations that match the user's interests. Through this filtering process, the server selects the data best suited to the user.

[0487] Step 4:

[0488] The server uses a generative AI model to generate guide content based on filtered tourist destination information. Here, the generative model is activated based on prompt text to create a customized text description for the user. The input is filtered data and prompt text, and the output is the generated text guide.

[0489] Step 5:

[0490] The server sends the generated guide content to a multilingual translation API, which translates it into the language set on the user's device. The input is the generated text guide in the target language, and the output is the translated multilingual text. The server performs the translation using the appropriate translation service.

[0491] Step 6:

[0492] The server sends the translated guide content to the terminal using the HTTPS protocol. The input is the translated multilingual text, and the output is delivery to the terminal. The server verifies that the data is transmitted securely during transmission.

[0493] Step 7:

[0494] The terminal receives the distributed translated guide information and displays or plays it as audio within the application. Input is data received from the server, and output is display on the user interface or audio output. The terminal presents the information in an appropriate format according to the user's selection.

[0495] (Application Example 1)

[0496] 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."

[0497] Modern tourists require real-time, effective access to information tailored to their individual interests and preferences. However, traditional tourist guide systems can only provide general information, making it difficult to adequately address users' specific needs. Furthermore, even multilingual and practical information delivery methods have limitations in terms of efficiency and accuracy. Therefore, a system was needed that could flexibly respond to diverse user needs and further personalize and optimize the tourist experience.

[0498] 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.

[0499] In this invention, the server includes means for acquiring location data, means for filtering tourist destination data based on user interest and preference data, and means for generating and translating explanatory content using a generation device. This allows users to receive detailed and personalized tourist information in real time according to their current location and interests. Furthermore, voice output enables intuitive information provision to users of various languages.

[0500] "Location data" refers to geographical information indicating the user's current location, and is measured using GPS or other location information acquisition methods.

[0501] "Tourist destination data" refers to a collection of information about a tourist destination, including detailed information about its history, culture, and notable landmarks.

[0502] "User interest and preference data" refers to information about specific genres or themes that users are interested in, and is collected based on the user's past behavior and choices.

[0503] A "generation device" is a system that has the function of creating explanatory content based on input data, and uses an AI model to generate content that is suitable for the user.

[0504] "Description content" refers to text or audio data containing specific information related to tourist destinations, and is guide information generated based on the user's interests.

[0505] "Translation" is the process of converting generated explanatory content into the user's chosen language, and is a process for accurately conveying information between different languages.

[0506] To implement this invention, first, the user's terminal acquires location data using GPS. The acquired location data is transmitted to a server via the network. The server receives this location data and the user's already registered interest and preference data. Using this, it searches for relevant tourist destination data in a database.

[0507] The server filters search results based on the user's interests and preferences. Based on the filtered tourist destination data, a generator automatically produces appropriate descriptions. This generation uses the latest AI model. The generated descriptions are then translated into the user's specified language. High-precision language conversion software is used for the translation.

[0508] The translated explanations are delivered to the user's device. This allows the device to play the explanations as audio in real time using its audio output device. As a result, users can obtain the necessary information on the spot and enjoy a sightseeing experience that doesn't rely on visual cues.

[0509] As a concrete example, when a user visits a museum, the server retrieves the museum's exhibition data and generates a detailed description of "medieval paintings" that the user is interested in. This content is then translated into the user's chosen language, for example, Japanese, and delivered to the user's device. In this case, an example of a prompt message to the generating AI model would be in text format: "The user has expressed interest in 'medieval paintings.' Please generate a detailed description of the relevant paintings in the museum."

[0510] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0511] Step 1:

[0512] The user's device uses its GPS function to obtain current location data. This location data includes latitude and longitude information. The obtained location data is prepared for transmission to the server. The input is GPS data, and the output is location data ready for transmission to the server.

[0513] Step 2:

[0514] The server receives location data from the user's device. Using this location data as input, the server searches a relevant tourist destination database and extracts tourist destination data for the corresponding location. The output is the corresponding tourist destination data.

[0515] Step 3:

[0516] The server retrieves user interest and preference data from the database and filters it in combination with tourist destination data. In this process, highly relevant information is selected based on the user's past interests. The input is tourist destination data and interest and preference data, and the output is filtered tourist destination data.

[0517] Step 4:

[0518] The server uses a generative AI model to generate detailed descriptions based on filtered tourist destination data. In this step, a prompt is created, and the AI ​​model generates text based on the prompt. The input is the filtered tourist destination data, and the output is the generated description.

[0519] Step 5:

[0520] The server translates the generated description into the language specified by the user. This translation process uses multilingual translation software. The input is the generated description, and the output is the translated description.

[0521] Step 6:

[0522] The server delivers the translated explanation to the user's terminal. The terminal receives this and plays the audio in real time using an audio output unit. The input is the translated explanation, and the output is the audio information provided to the user through the audio output device.

[0523] 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.

[0524] This invention is a system that recognizes a user's emotions and provides a personalized tourist guide based on those emotions. First, the terminal uses GPS to obtain the user's precise location information. This location information is sent to a server, which searches a database for information on relevant tourist destinations.

[0525] The server utilizes user interest and preference information to filter information in the database and select information that is highly relevant to the user. Furthermore, it uses a generative model to dynamically generate guide content that aligns with the user's preferences.

[0526] The emotion engine uses sensors such as cameras and microphones to analyze the user's voice tone and facial expressions, recognizing their emotions in real time. Based on this, the server adjusts the guide information provided according to the user's emotional state. For example, if the user is excited, the server might emphasize particularly interesting content.

[0527] The translation tool converts the generated guide content into the language set on the user's device. The translated content is sent to the device, which then provides the information in audio or text format.

[0528] For example, when a user visits a historical castle, if the emotion engine detects the user's surprise, the server can provide additional interesting anecdotes. In this way, the present invention enables flexible information delivery based on emotions, thereby improving the user experience.

[0529] The following describes the processing flow.

[0530] Step 1:

[0531] The device uses GPS to obtain the user's current location information. The obtained location information is recorded as latitude and longitude.

[0532] Step 2:

[0533] The device sends location information to the server. The server receives this information and searches its database for information on the corresponding tourist destination.

[0534] Step 3:

[0535] The server references the user's interests and preferences and filters the tourist destination information in the database to provide the most relevant information for the user.

[0536] Step 4:

[0537] Based on filtered tourist destination information, the server uses a generative model to generate guide content. This guide content is designed to be as relevant as possible to the user's interests.

[0538] Step 5:

[0539] The device uses its camera and microphone to analyze the user's facial expressions and voice using an emotion engine, acquiring emotional data in real time.

[0540] Step 6:

[0541] The server analyzes the user's current emotional state based on data from the emotion engine. The guide content provided is then adjusted according to the analysis results.

[0542] Step 7:

[0543] The server translates the adjusted guide content into the language set on the user's device. Once the translation is complete through multilingual support, the guide content is sent to the device.

[0544] Step 8:

[0545] The device can either play the received guide content as audio or display it as text on the screen. This allows users to acquire information at their own pace.

[0546] Step 9:

[0547] If the user shows further interest in the guide content, the device requests additional information from the server. Based on this request, the server retrieves more detailed information and sends it to the device.

[0548] (Example 2)

[0549] 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."

[0550] In modern tourism systems, providing information based on user location and basic interests is common, but personalized information that takes user emotions into account is not provided. As a result, tourism experiences become uniform, making it difficult to improve user satisfaction and interest. Furthermore, there are still challenges in the flexibility of providing information in multiple languages. This invention aims to solve these problems and provide flexible tourism guidance that is attentive to the user's emotions.

[0551] 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.

[0552] In this invention, the server includes means for acquiring location information, means for dynamically generating personalized guide content from filtered tourist destination information using a generative model, and means for recognizing the user's emotions using sensors. This enables flexible adjustment of tourist information according to the user's emotional state and multilingual guide guidance.

[0553] "Devices for acquiring location information" refers to any hardware or software used to determine the latitude and longitude of a user's current location.

[0554] "Means for searching tourist destination information" refers to a system that retrieves data about relevant tourist destinations from a database based on the user's location information.

[0555] "User interest and preference information" refers to information that represents an individual's preferences and interests, estimated based on a user's past behavior and explicit choices.

[0556] "Filtering methods" refer to methods that utilize user interest and preference information to select important or relevant information from acquired tourist destination data.

[0557] A "generative model" is an AI algorithm that automatically generates appropriate tourist guide information based on the user's preferences and emotions.

[0558] "Means of recognizing user emotions using sensors" refers to devices and programs that detect a user's facial expressions and voice tone, and evaluate and judge their emotions from there.

[0559] "Means of adjusting guide content based on emotional information" refers to methods of dynamically changing the content and expression of tourist information provided in accordance with the user's emotions.

[0560] "Means of translating into a specified language" refers to technology for converting the generated guide content into a language that the user can understand.

[0561] "Means of delivering to user terminals" refers to methods of transferring the customized tourism information to devices available to the user.

[0562] This invention relates to a system that recognizes a user's emotions and provides a personalized tourist guide tailored to those emotions. This system primarily consists of a terminal, a server, and user interaction.

[0563] First, the device accurately acquires the user's location information using GPS technology. This utilizes the GPS module in the smartphone or dedicated device. The acquired location information is transmitted to the server in real time via the internet connection.

[0564] The server searches the database for relevant tourist destination information based on the received location data. A generative AI model is used to filter and select information, taking into account the user's interests and preferences. This generative AI model, for example, utilizes a large-scale neural network to dynamically generate optimal guide content for the user.

[0565] Next, the system uses sensors such as the camera and microphone built into the device to acquire data on the user's voice tone and facial expressions. Based on this data, the server activates an emotion engine to analyze the user's emotions. Based on this analysis, the server can adjust the guide content to match the user's emotional state. For example, if the user is surprised, the system will provide information that emphasizes interesting facts or anecdotes.

[0566] Furthermore, the guide content generated by the translation system is converted into the user's chosen language. Automatic translation software is used for this translation, enabling multilingual support. The translated guide is provided to the user via the device in either audio or text format.

[0567] As a concrete example, imagine a user using this system while touring a historical castle. When the emotion engine detects the user's surprise, the server can provide additional, particularly interesting anecdotes related to the castle's history. This flexible, emotion-responsive information delivery enriches the user's sightseeing experience.

[0568] An example of a prompt might be, "How can we provide relevant anecdotes based on the user's excitement level when visiting a historical site?" This system enables the provision of advanced information based on individual user experiences.

[0569] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0570] Step 1:

[0571] The device obtains the user's current location using a GPS module. It receives location data from the user's device as input and outputs it in the form of latitude and longitude. This process makes it possible to pinpoint the user's exact location.

[0572] Step 2:

[0573] The device transmits the acquired location information to the server. The input is location data, which is sent to the server via the internet connection. The server receives the location information as output and prepares it for subsequent processing.

[0574] Step 3:

[0575] The server searches its database for relevant tourist destination information based on the received location data. The input is location data, and it retrieves information about nearby tourist spots through database queries. The output is tourist destination information related to the location. This information is then filtered in the next step, combined with the user's interests and preferences.

[0576] Step 4:

[0577] The server uses user interest and preference information to filter the acquired tourist destination information. The input consists of tourist destination information and user preference data. A generative AI model is used to select the most relevant tourist destination information for each individual user. The output is personalized tourist destination information.

[0578] Step 5:

[0579] The device acquires the user's facial expressions and voice tone through its camera and microphone. Input consists of data collected by sensors, which is then sent to a server. Output is the data necessary for analyzing the user's emotions.

[0580] Step 6:

[0581] The server performs emotion analysis based on the user's facial expressions and voice data received. The input is sensor data, which is analyzed by the emotion engine. The output is a determination of the user's emotional state.

[0582] Step 7:

[0583] The server adjusts personalized tourist information based on the user's emotional state. The input consists of filtered tourist information and emotional data, and a generative AI model is used to highlight interesting information and add new information. The output is emotionally responsive tourist guide information.

[0584] Step 8:

[0585] The server translates the generated guide information into the user-specified language. The input is the guide information, which is automatically translated into each user's native language using natural language processing technology. The output is the translated guide information.

[0586] Step 9:

[0587] The device receives translated guide information and provides it to the user in audio or text format. The input is the translated information, presented to the user visually and aurally using speech synthesis technology and a display. The output is the actual guide information provided to enhance the user experience.

[0588] (Application Example 2)

[0589] 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."

[0590] Traditional tourist information systems are limited to providing information based on users' interests and preferences, making it difficult to flexibly adjust guide content to respond to users' emotions. Furthermore, the inability to provide emotion-based information in real time sometimes resulted in insufficient optimization of the user experience.

[0591] 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.

[0592] In this invention, the server includes a device for acquiring location information, means for searching for relevant tourist destination information based on said location information, means for acquiring user interest and preference information and filtering the search results based on said interest and preference information, and means for recognizing the user's emotions and adjusting the guide content based on said emotions. This makes it possible to provide personalized guide information in response to the user's emotions in real time.

[0593] A "device for acquiring location information" is a device that uses location information technology such as GPS to collect geographical data in order to determine the user's current location.

[0594] "Means for searching for relevant tourist destination information" refers to a method or device for retrieving detailed information about tourist destinations related to a given region from a database or other source, based on acquired location information.

[0595] "Means for acquiring user interest and preference information and filtering search results based on said interest and preference information" refers to a method or function for acquiring information that the user is interested in and then narrowing down tourist destination information based on that information.

[0596] A "generative model for generating guide content" is a model that uses AI and other technologies to generate guide information to present to users, using filtered tourist destination information.

[0597] "Means for recognizing user emotions and adjusting guide content based on those emotions" refers to a method or apparatus for analyzing a user's facial expressions and voice using a camera or microphone, and optimizing the guide information provided according to the detected user emotions.

[0598] "Means for translating generated guide content into a user-specified language" refers to a method or technology for converting generated guide information into the language used by the user.

[0599] "Means for delivering the translated guide content to the user's terminal" refers to a method or technology for transmitting translated guidance information to the user's terminal and providing it through display or audio, etc.

[0600] This system provides personalized tourist information based on the user's emotions. First, the user's device is equipped with a GPS module to acquire location information, and accurate location data is sent to the server. Based on this location information, the server searches its database for information on relevant tourist destinations.

[0601] Search results are filtered based on the user's interests and preferences. Personalized guide information is generated by extracting information that matches the user's hobbies and interests. The server then uses a generative AI model to create user-specific guide content based on the filtered tourist destination information.

[0602] Furthermore, the device uses its built-in camera and microphone to analyze the user's facial expressions and voice in real time and recognize their emotions. This analysis utilizes emotion recognition software (e.g., OpenFace, Google Cloud Speech-to-Text). Once the user's emotions are recognized, the guide content is dynamically adjusted accordingly.

[0603] The generated guide content is translated into the user's specified language, and the translated information is delivered to the user's device. Translation software (e.g., Google Translate API) is used for the translation. Finally, the user's device provides the guide content in audio or text format through its speaker or display.

[0604] As a concrete example, if a foreign tourist visiting an ancient Japanese capital shows signs of excitement, emotion recognition technology can detect this excitement. Based on this information, the server provides a guide that highlights the interesting historical background and anecdotes of the temple they are visiting.

[0605] An example of a prompt message would be: "Please provide additional information about what surprised the user. The tourist spot is a temple in Kyoto. Please provide an anecdote or information that would interest the user."

[0606] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0607] Step 1:

[0608] The device uses a GPS module to obtain the user's location information. The input is a signal from the GPS, and the output is latitude and longitude location data. This allows the user's current location to be determined.

[0609] Step 2:

[0610] The server receives location information and uses it to search for relevant tourist destination information in the database. The input is location data received from the device, and the output is a list of tourist spots associated with that location. SQL queries are used in this process to retrieve information from the database.

[0611] Step 3:

[0612] The server retrieves the user's interests and preferences and filters the aforementioned list of tourist destinations. The input consists of the user's interests and preferences data and the list of tourist destinations, and the output is a selection of tourist destinations that match the user's interests. A data filtering algorithm is applied to perform the selection.

[0613] Step 4:

[0614] The server utilizes a generated AI model to create guide content based on selected tourist destination information. The input is filtered tourist destination information, and the output is the guide content. In this process, a language model is used to construct the explanation in natural language.

[0615] Step 5:

[0616] The device uses its camera and microphone to analyze the user's voice and facial expressions, and recognizes their emotions. The input is real-time data from the camera and microphone, and the output is the user's emotional state. Emotion recognition software is used to analyze facial expressions and voice tone.

[0617] Step 6:

[0618] The server adjusts the pre-generated guide content based on the user's emotions. The input is the user's emotional state, and the output is the adjusted guide content. An adjustment algorithm is used to emphasize or add information.

[0619] Step 7:

[0620] The server translates the generated guide content into the user's specified language. The input is the guide content, and the output is the translated guide content. Language conversion is performed using translation software.

[0621] Step 8:

[0622] The device delivers translated guide content to the user and presents the information. The input is the translated guide content, and the output is information provided in audio or text format. The information is presented to the user through the device's speaker or display.

[0623] 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.

[0624] 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.

[0625] 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.

[0626] [Fourth Embodiment]

[0627] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0628] 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.

[0629] 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).

[0630] 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.

[0631] 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.

[0632] 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).

[0633] 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.

[0634] 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.

[0635] 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.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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".

[0640] This invention is a system that provides tourist destination information related to a user's location using that location information. Specifically, location information is acquired from sensors such as GPS through a device such as a smartphone or tablet used by the user. This location information is transmitted to a server in the cloud.

[0641] The server uses location information received from the user, along with pre-registered user interest and preference information, to query the database and search for relevant tourist destination information. Based on these search results, it filters tourist information that matches the user's interests and preferences, and automatically generates guide content using a generative model.

[0642] The generated guide content is translated based on the language set on the user's device. The server performs this multilingual translation, providing the information in the format that is easiest for the user to understand. This translated guide data is delivered to the user's device, which can then play it as audio or display it as text.

[0643] As a concrete example, consider a scenario where a user visits a historical art museum. In this case, the device detects the user's current location, and the server retrieves information about the museum from a database. Furthermore, based on categories the user has shown particular interest in (e.g., "medieval paintings" or "a specific painter"), the generative model generates a detailed description, translates it into the user's language, and sends it to the device.

[0644] Ultimately, users can choose and listen to only the information that interests them at their own pace, making their travel experience more enriching. This system is designed to individually optimize the user experience and effectively deliver travel information.

[0645] The following describes the processing flow.

[0646] Step 1:

[0647] The device activates its GPS sensor and performs the operation of acquiring its own location information (latitude and longitude).

[0648] Step 2:

[0649] The device transmits its acquired location information to the server in real time. This process involves data communication.

[0650] Step 3:

[0651] The server receives the transmitted location information and searches the database for tourist destination information related to that location.

[0652] Step 4:

[0653] The server refers to the user's pre-registered interests and preferences and filters the searched tourist destination information to include relevant results.

[0654] Step 5:

[0655] Based on the filtered information, the server uses a generative model to generate user guidance content.

[0656] Step 6:

[0657] The server translates the generated guide content according to the user's device language settings and prepares multilingual data.

[0658] Step 7:

[0659] The server sends the translated guide data to the terminal and provides it in a format that the user can access.

[0660] Step 8:

[0661] The device processes the received guide data and either plays the audio guide or displays the text.

[0662] Step 9:

[0663] If a user requests more details about information they are interested in on their device, the device sends a request to the server, and additional information is provided.

[0664] (Example 1)

[0665] 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".

[0666] In tourist destination information search systems, there is a need to efficiently provide information tailored to the user's current location and individual interests. However, conventional systems have the problem that location-based search results are not personalized, and useful information is not provided to users in a timely manner. Furthermore, information provision in different languages ​​is insufficient, making it difficult to effectively generate and provide multilingual guides.

[0667] 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.

[0668] In this invention, the server includes means for acquiring user preference information and selecting search results based on said preference information, a generation model for generating explanatory content using the selected regional information, and means for converting the generated explanatory content into the user's specified language. This makes it possible to efficiently provide customized tourist information in multiple languages ​​that is tailored to the user's location and individual preferences.

[0669] "Location" refers to information indicating the user's current location, and is usually expressed as latitude and longitude on Earth.

[0670] "Device" refers to a device used to acquire location information, such as a mobile terminal with GPS functionality.

[0671] "Means of searching" refers to methods and technologies for finding relevant regional information by searching a database based on acquired location information.

[0672] "User preference information" refers to data about users' interests and preferences, and is used to select the information provided.

[0673] "Selection methods" refer to the processes and technologies used to select items that match the user's preferences based on the acquired information.

[0674] A "generative model" refers to an algorithm or program used to create relevant descriptions or instructions based on specific input conditions.

[0675] "Means of converting into language" refers to translation technologies and systems used to display the generated explanatory content in multiple languages.

[0676] "User device" refers to a device that the user directly uses, and includes smartphones and tablets.

[0677] "Means of customization" refers to technologies and methods that adaptively adjust information according to the individual needs and requirements of the user.

[0678] This system provides relevant tourist destination information based on the user's location. Specifically, it requires a smartphone or tablet as the user's device. The device uses its built-in GPS sensor to obtain the user's current location and sends it to a server in the cloud. The device securely transmits data packets, including the obtained location information, to the server using the HTTPS protocol.

[0679] The server uses this location information and pre-registered user interest and preference information to search the database. Database query techniques such as SQL are used to extract regional information relevant to the user's location. Next, the user's preference information is referenced to filter the relevant regional information based on the search results. The filtered data is analyzed by a generative AI model to generate customized guide content. This generative model utilizes algorithms employing natural language processing techniques to automatically create contextually appropriate explanations.

[0680] The generated guide content is processed by a multilingual translation service and translated into the user's specified language. For multilingual support, a cloud-based translation API is used to translate the generated text in real time. This translated guide information is then delivered to the user's device using HTTPS. The device stores the received information and either displays it as text on the application screen or plays it back as audio using TTS (Text-to-Speech) functionality.

[0681] As a concrete example, consider a scenario where a user visits a museum that is a historical cultural asset. The terminal confirms the location of this museum, and the server uses a generative model to generate information about the museum from its database, along with detailed descriptions of medieval paintings that the user is particularly interested in. This generation process utilizes prompts such as, "Tell me more about the exhibits at the museum at my current location."

[0682] This allows users to obtain detailed information in multiple languages ​​on the spot, tailored to their interests, making their travel experience deeper and more personalized.

[0683] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0684] Step 1:

[0685] The device obtains location information using a GPS sensor. During this process, the device updates its location every few seconds, acquiring latitude and longitude data. This information is prepared as packet data and sent to the server as location information. The input is location data from the device's GPS sensor, and the output is structured location information data for transmission to the server.

[0686] Step 2:

[0687] The server receives location data sent from the terminal. The server then sends an SQL query to the database to retrieve regional data related to this location. The input here is the location data, and the output is the relevant tourist destination data and related information. The server extracts the relevant regional information from the database.

[0688] Step 3:

[0689] The server retrieves the user's preferences from the database and filters the retrieved tourist destination data. The input consists of tourist destination data from the database and the user's preferences, while the output is a filtered list of tourist destinations that match the user's interests. Through this filtering process, the server selects the data best suited to the user.

[0690] Step 4:

[0691] The server uses a generative AI model to generate guide content based on filtered tourist destination information. Here, the generative model is activated based on prompt text to create a customized text description for the user. The input is filtered data and prompt text, and the output is the generated text guide.

[0692] Step 5:

[0693] The server sends the generated guide content to a multilingual translation API, which translates it into the language set on the user's device. The input is the generated text guide in the target language, and the output is the translated multilingual text. The server performs the translation using the appropriate translation service.

[0694] Step 6:

[0695] The server sends the translated guide content to the terminal using the HTTPS protocol. The input is the translated multilingual text, and the output is delivery to the terminal. The server verifies that the data is transmitted securely during transmission.

[0696] Step 7:

[0697] The terminal receives the distributed translated guide information and displays or plays it as audio within the application. Input is data received from the server, and output is display on the user interface or audio output. The terminal presents the information in an appropriate format according to the user's selection.

[0698] (Application Example 1)

[0699] 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".

[0700] Modern tourists require real-time, effective access to information tailored to their individual interests and preferences. However, traditional tourist guide systems can only provide general information, making it difficult to adequately address users' specific needs. Furthermore, even multilingual and practical information delivery methods have limitations in terms of efficiency and accuracy. Therefore, a system was needed that could flexibly respond to diverse user needs and further personalize and optimize the tourist experience.

[0701] 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.

[0702] In this invention, the server includes means for acquiring location data, means for filtering tourist destination data based on user interest and preference data, and means for generating and translating explanatory content using a generation device. This allows users to receive detailed and personalized tourist information in real time according to their current location and interests. Furthermore, voice output enables intuitive information provision to users of various languages.

[0703] "Location data" refers to geographical information indicating the user's current location, and is measured using GPS or other location information acquisition methods.

[0704] "Tourist destination data" refers to a collection of information about a tourist destination, including detailed information about its history, culture, and notable landmarks.

[0705] "User interest and preference data" refers to information about specific genres or themes that users are interested in, and is collected based on the user's past behavior and choices.

[0706] A "generation device" is a system that has the function of creating explanatory content based on input data, and uses an AI model to generate content that is suitable for the user.

[0707] "Description content" refers to text or audio data containing specific information related to tourist destinations, and is guide information generated based on the user's interests.

[0708] "Translation" is the process of converting generated explanatory content into the user's chosen language, and is a process for accurately conveying information between different languages.

[0709] To implement this invention, first, the user's terminal acquires location data using GPS. The acquired location data is transmitted to a server via the network. The server receives this location data and the user's already registered interest and preference data. Using this, it searches for relevant tourist destination data in a database.

[0710] The server filters search results based on the user's interests and preferences. Based on the filtered tourist destination data, a generator automatically produces appropriate descriptions. This generation uses the latest AI model. The generated descriptions are then translated into the user's specified language. High-precision language conversion software is used for the translation.

[0711] The translated explanations are delivered to the user's device. This allows the device to play the explanations as audio in real time using its audio output device. As a result, users can obtain the necessary information on the spot and enjoy a sightseeing experience that doesn't rely on visual cues.

[0712] As a concrete example, when a user visits a museum, the server retrieves the museum's exhibition data and generates a detailed description of "medieval paintings" that the user is interested in. This content is then translated into the user's chosen language, for example, Japanese, and delivered to the user's device. In this case, an example of a prompt message to the generating AI model would be in text format: "The user has expressed interest in 'medieval paintings.' Please generate a detailed description of the relevant paintings in the museum."

[0713] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0714] Step 1:

[0715] The user's device uses its GPS function to obtain current location data. This location data includes latitude and longitude information. The obtained location data is prepared for transmission to the server. The input is GPS data, and the output is location data ready for transmission to the server.

[0716] Step 2:

[0717] The server receives location data from the user's device. Using this location data as input, the server searches a relevant tourist destination database and extracts tourist destination data for the corresponding location. The output is the corresponding tourist destination data.

[0718] Step 3:

[0719] The server retrieves user interest and preference data from the database and filters it in combination with tourist destination data. In this process, highly relevant information is selected based on the user's past interests. The input is tourist destination data and interest and preference data, and the output is filtered tourist destination data.

[0720] Step 4:

[0721] The server uses a generative AI model to generate detailed descriptions based on filtered tourist destination data. In this step, a prompt is created, and the AI ​​model generates text based on the prompt. The input is the filtered tourist destination data, and the output is the generated description.

[0722] Step 5:

[0723] The server translates the generated description into the language specified by the user. This translation process uses multilingual translation software. The input is the generated description, and the output is the translated description.

[0724] Step 6:

[0725] The server delivers the translated explanation to the user's terminal. The terminal receives this and plays the audio in real time using an audio output unit. The input is the translated explanation, and the output is the audio information provided to the user through the audio output device.

[0726] 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.

[0727] This invention is a system that recognizes a user's emotions and provides a personalized tourist guide based on those emotions. First, the terminal uses GPS to obtain the user's precise location information. This location information is sent to a server, which searches a database for information on relevant tourist destinations.

[0728] The server utilizes user interest and preference information to filter information in the database and select information that is highly relevant to the user. Furthermore, it uses a generative model to dynamically generate guide content that aligns with the user's preferences.

[0729] The emotion engine uses sensors such as cameras and microphones to analyze the user's voice tone and facial expressions, recognizing their emotions in real time. Based on this, the server adjusts the guide information provided according to the user's emotional state. For example, if the user is excited, the server might emphasize particularly interesting content.

[0730] The translation tool converts the generated guide content into the language set on the user's device. The translated content is sent to the device, which then provides the information in audio or text format.

[0731] For example, when a user visits a historical castle, if the emotion engine detects the user's surprise, the server can provide additional interesting anecdotes. In this way, the present invention enables flexible information delivery based on emotions, thereby improving the user experience.

[0732] The following describes the processing flow.

[0733] Step 1:

[0734] The device uses GPS to obtain the user's current location information. The obtained location information is recorded as latitude and longitude.

[0735] Step 2:

[0736] The device sends location information to the server. The server receives this information and searches its database for information on the corresponding tourist destination.

[0737] Step 3:

[0738] The server references the user's interests and preferences and filters the tourist destination information in the database to provide the most relevant information for the user.

[0739] Step 4:

[0740] Based on filtered tourist destination information, the server uses a generative model to generate guide content. This guide content is designed to be as relevant as possible to the user's interests.

[0741] Step 5:

[0742] The device uses its camera and microphone to analyze the user's facial expressions and voice using an emotion engine, acquiring emotional data in real time.

[0743] Step 6:

[0744] The server analyzes the user's current emotional state based on data from the emotion engine. The guide content provided is then adjusted according to the analysis results.

[0745] Step 7:

[0746] The server translates the adjusted guide content into the language set on the user's device. Once the translation is complete through multilingual support, the guide content is sent to the device.

[0747] Step 8:

[0748] The device can either play the received guide content as audio or display it as text on the screen. This allows users to acquire information at their own pace.

[0749] Step 9:

[0750] If the user shows further interest in the guide content, the device requests additional information from the server. Based on this request, the server retrieves more detailed information and sends it to the device.

[0751] (Example 2)

[0752] 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".

[0753] In modern tourism systems, providing information based on user location and basic interests is common, but personalized information that takes user emotions into account is not provided. As a result, tourism experiences become uniform, making it difficult to improve user satisfaction and interest. Furthermore, there are still challenges in the flexibility of providing information in multiple languages. This invention aims to solve these problems and provide flexible tourism guidance that is attentive to the user's emotions.

[0754] 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.

[0755] In this invention, the server includes means for acquiring location information, means for dynamically generating personalized guide content from filtered tourist destination information using a generative model, and means for recognizing the user's emotions using sensors. This enables flexible adjustment of tourist information according to the user's emotional state and multilingual guide guidance.

[0756] "Devices for acquiring location information" refers to any hardware or software used to determine the latitude and longitude of a user's current location.

[0757] "Means for searching tourist destination information" refers to a system that retrieves data about relevant tourist destinations from a database based on the user's location information.

[0758] "User interest and preference information" refers to information that represents an individual's preferences and interests, estimated based on a user's past behavior and explicit choices.

[0759] "Filtering methods" refer to methods that utilize user interest and preference information to select important or relevant information from acquired tourist destination data.

[0760] A "generative model" is an AI algorithm that automatically generates appropriate tourist guide information based on the user's preferences and emotions.

[0761] "Means of recognizing user emotions using sensors" refers to devices and programs that detect a user's facial expressions and voice tone, and evaluate and judge their emotions from there.

[0762] "Means of adjusting guide content based on emotional information" refers to methods of dynamically changing the content and expression of tourist information provided in accordance with the user's emotions.

[0763] "Means of translating into a specified language" refers to technology for converting the generated guide content into a language that the user can understand.

[0764] "Means of delivering to user terminals" refers to methods of transferring the customized tourism information to devices available to the user.

[0765] This invention relates to a system that recognizes a user's emotions and provides a personalized tourist guide tailored to those emotions. This system primarily consists of a terminal, a server, and user interaction.

[0766] First, the device accurately acquires the user's location information using GPS technology. This utilizes the GPS module in the smartphone or dedicated device. The acquired location information is transmitted to the server in real time via the internet connection.

[0767] The server searches the database for relevant tourist destination information based on the received location data. A generative AI model is used to filter and select information, taking into account the user's interests and preferences. This generative AI model, for example, utilizes a large-scale neural network to dynamically generate optimal guide content for the user.

[0768] Next, the system uses sensors such as the camera and microphone built into the device to acquire data on the user's voice tone and facial expressions. Based on this data, the server activates an emotion engine to analyze the user's emotions. Based on this analysis, the server can adjust the guide content to match the user's emotional state. For example, if the user is surprised, the system will provide information that emphasizes interesting facts or anecdotes.

[0769] Furthermore, the guide content generated by the translation system is converted into the user's chosen language. Automatic translation software is used for this translation, enabling multilingual support. The translated guide is provided to the user via the device in either audio or text format.

[0770] As a concrete example, imagine a user using this system while touring a historical castle. When the emotion engine detects the user's surprise, the server can provide additional, particularly interesting anecdotes related to the castle's history. This flexible, emotion-responsive information delivery enriches the user's sightseeing experience.

[0771] An example of a prompt might be, "How can we provide relevant anecdotes based on the user's excitement level when visiting a historical site?" This system enables the provision of advanced information based on individual user experiences.

[0772] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0773] Step 1:

[0774] The device obtains the user's current location using a GPS module. It receives location data from the user's device as input and outputs it in the form of latitude and longitude. This process makes it possible to pinpoint the user's exact location.

[0775] Step 2:

[0776] The device transmits the acquired location information to the server. The input is location data, which is sent to the server via the internet connection. The server receives the location information as output and prepares it for subsequent processing.

[0777] Step 3:

[0778] The server searches its database for relevant tourist destination information based on the received location data. The input is location data, and it retrieves information about nearby tourist spots through database queries. The output is tourist destination information related to the location. This information is then filtered in the next step, combined with the user's interests and preferences.

[0779] Step 4:

[0780] The server uses user interest and preference information to filter the acquired tourist destination information. The input consists of tourist destination information and user preference data. A generative AI model is used to select the most relevant tourist destination information for each individual user. The output is personalized tourist destination information.

[0781] Step 5:

[0782] The device acquires the user's facial expressions and voice tone through its camera and microphone. Input consists of data collected by sensors, which is then sent to a server. Output is the data necessary for analyzing the user's emotions.

[0783] Step 6:

[0784] The server performs emotion analysis based on the user's facial expressions and voice data received. The input is sensor data, which is analyzed by the emotion engine. The output is a determination of the user's emotional state.

[0785] Step 7:

[0786] The server adjusts personalized tourist information based on the user's emotional state. The input consists of filtered tourist information and emotional data, and a generative AI model is used to highlight interesting information and add new information. The output is emotionally responsive tourist guide information.

[0787] Step 8:

[0788] The server translates the generated guide information into the user-specified language. The input is the guide information, which is automatically translated into each user's native language using natural language processing technology. The output is the translated guide information.

[0789] Step 9:

[0790] The device receives translated guide information and provides it to the user in audio or text format. The input is the translated information, presented to the user visually and aurally using speech synthesis technology and a display. The output is the actual guide information provided to enhance the user experience.

[0791] (Application Example 2)

[0792] 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".

[0793] Traditional tourist information systems are limited to providing information based on users' interests and preferences, making it difficult to flexibly adjust guide content to respond to users' emotions. Furthermore, the inability to provide emotion-based information in real time sometimes resulted in insufficient optimization of the user experience.

[0794] 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.

[0795] In this invention, the server includes a device for acquiring location information, means for searching for relevant tourist destination information based on said location information, means for acquiring user interest and preference information and filtering the search results based on said interest and preference information, and means for recognizing the user's emotions and adjusting the guide content based on said emotions. This makes it possible to provide personalized guide information in response to the user's emotions in real time.

[0796] A "device for acquiring location information" is a device that uses location information technology such as GPS to collect geographical data in order to determine the user's current location.

[0797] "Means for searching for relevant tourist destination information" refers to a method or device for retrieving detailed information about tourist destinations related to a given region from a database or other source, based on acquired location information.

[0798] "Means for acquiring user interest and preference information and filtering search results based on said interest and preference information" refers to a method or function for acquiring information that the user is interested in and then narrowing down tourist destination information based on that information.

[0799] A "generative model for generating guide content" is a model that uses AI and other technologies to generate guide information to present to users, using filtered tourist destination information.

[0800] "Means for recognizing user emotions and adjusting guide content based on those emotions" refers to a method or apparatus for analyzing a user's facial expressions and voice using a camera or microphone, and optimizing the guide information provided according to the detected user emotions.

[0801] "Means for translating generated guide content into a user-specified language" refers to a method or technology for converting generated guide information into the language used by the user.

[0802] "Means for delivering the translated guide content to the user's terminal" refers to a method or technology for transmitting translated guidance information to the user's terminal and providing it through display or audio, etc.

[0803] This system provides personalized tourist information based on the user's emotions. First, the user's device is equipped with a GPS module to acquire location information, and accurate location data is sent to the server. Based on this location information, the server searches its database for information on relevant tourist destinations.

[0804] Search results are filtered based on the user's interests and preferences. Personalized guide information is generated by extracting information that matches the user's hobbies and interests. The server then uses a generative AI model to create user-specific guide content based on the filtered tourist destination information.

[0805] Furthermore, the device uses its built-in camera and microphone to analyze the user's facial expressions and voice in real time and recognize their emotions. This analysis utilizes emotion recognition software (e.g., OpenFace, Google Cloud Speech-to-Text). Once the user's emotions are recognized, the guide content is dynamically adjusted accordingly.

[0806] The generated guide content is translated into the user's specified language, and the translated information is delivered to the user's device. Translation software (e.g., Google Translate API) is used for the translation. Finally, the user's device provides the guide content in audio or text format through its speaker or display.

[0807] As a concrete example, if a foreign tourist visiting an ancient Japanese capital shows signs of excitement, emotion recognition technology can detect this excitement. Based on this information, the server provides a guide that highlights the interesting historical background and anecdotes of the temple they are visiting.

[0808] An example of a prompt message would be: "Please provide additional information about what surprised the user. The tourist spot is a temple in Kyoto. Please provide an anecdote or information that would interest the user."

[0809] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0810] Step 1:

[0811] The device uses a GPS module to obtain the user's location information. The input is a signal from the GPS, and the output is latitude and longitude location data. This allows the user's current location to be determined.

[0812] Step 2:

[0813] The server receives location information and uses it to search for relevant tourist destination information in the database. The input is location data received from the device, and the output is a list of tourist spots associated with that location. SQL queries are used in this process to retrieve information from the database.

[0814] Step 3:

[0815] The server retrieves the user's interests and preferences and filters the aforementioned list of tourist destinations. The input consists of the user's interests and preferences data and the list of tourist destinations, and the output is a selection of tourist destinations that match the user's interests. A data filtering algorithm is applied to perform the selection.

[0816] Step 4:

[0817] The server utilizes a generated AI model to create guide content based on selected tourist destination information. The input is filtered tourist destination information, and the output is the guide content. In this process, a language model is used to construct the explanation in natural language.

[0818] Step 5:

[0819] The device uses its camera and microphone to analyze the user's voice and facial expressions, and recognizes their emotions. The input is real-time data from the camera and microphone, and the output is the user's emotional state. Emotion recognition software is used to analyze facial expressions and voice tone.

[0820] Step 6:

[0821] The server adjusts the pre-generated guide content based on the user's emotions. The input is the user's emotional state, and the output is the adjusted guide content. An adjustment algorithm is used to emphasize or add information.

[0822] Step 7:

[0823] The server translates the generated guide content into the user's specified language. The input is the guide content, and the output is the translated guide content. Language conversion is performed using translation software.

[0824] Step 8:

[0825] The device delivers translated guide content to the user and presents the information. The input is the translated guide content, and the output is information provided in audio or text format. The information is presented to the user through the device's speaker or display.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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."

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] 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.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] The following is further disclosed regarding the embodiments described above.

[0848] (Claim 1)

[0849] A device for acquiring location information,

[0850] A means of searching for relevant tourist destination information based on the location information,

[0851] A means for obtaining user interest and preference information and filtering the search results based on said interest and preference information,

[0852] A generative model that generates guide content using filtered tourist destination information,

[0853] A means of translating the generated guide content into the user's specified language,

[0854] A means for delivering the translated guide content to the user's terminal,

[0855] A system that includes this.

[0856] (Claim 2)

[0857] The system according to claim 1, comprising means for dynamically obtaining additional detailed information based on information of interest to the user.

[0858] (Claim 3)

[0859] The system according to claim 1, comprising means for providing guide content that supports multiple languages.

[0860] "Example 1"

[0861] (Claim 1)

[0862] Equipment for determining location,

[0863] A means of searching for relevant regional information based on the location,

[0864] A means for acquiring user preference information and selecting the search results based on said preference information,

[0865] A generative model that generates explanatory content using selected regional information,

[0866] A means of converting the generated explanation into the user's specified language,

[0867] A means for transferring the converted explanation content to the user's device,

[0868] A means to customize the description based on the acquired location and user profile information,

[0869] A system that includes this.

[0870] (Claim 2)

[0871] The system according to claim 1, comprising means for dynamically acquiring additional detailed data based on information of interest to the user.

[0872] (Claim 3)

[0873] The system according to claim 1, comprising means for providing explanatory content in multiple languages.

[0874] "Application Example 1"

[0875] (Claim 1)

[0876] Means for obtaining location data,

[0877] A means for searching for related tourist destination data based on the location data,

[0878] A means for acquiring user interest and preference data and filtering the search results based on said interest and preference data,

[0879] A generation device that generates explanatory content using filtered tourist destination data,

[0880] A means of translating the generated explanation into the user's selected language,

[0881] A means for distributing the translated explanation content to the user's device,

[0882] A means of outputting the explanation content by voice on the user device,

[0883] A system that includes this.

[0884] (Claim 2)

[0885] The system according to claim 1, comprising means for dynamically acquiring additional detailed data based on the user's indicated interests.

[0886] (Claim 3)

[0887] The system according to claim 1, comprising means for providing explanatory content in multiple languages.

[0888] "Example 2 of combining an emotion engine"

[0889] (Claim 1)

[0890] A device for acquiring location information,

[0891] A means of searching for relevant tourist destination information based on the location information,

[0892] A means for obtaining user interest and preference information and filtering the search results based on said interest and preference information,

[0893] A means for dynamically generating filtered tourist destination information into further personalized guide content using a generative model,

[0894] A means of recognizing the user's emotions using sensors,

[0895] A means of adjusting the guide content based on recognized emotional information,

[0896] A means of translating the generated guide content into the user's specified language,

[0897] A means for delivering the translated guide content to the user's terminal,

[0898] A system that includes this.

[0899] (Claim 2)

[0900] The system according to claim 1, comprising means for highlighting information of interest and dynamically obtaining additional details based on the user's emotions.

[0901] (Claim 3)

[0902] The system according to claim 1, comprising means for providing multilingual guide content in audio and text.

[0903] "Application example 2 when combining with an emotional engine"

[0904] (Claim 1)

[0905] A device for acquiring location information,

[0906] A means of searching for relevant tourist destination information based on the location information,

[0907] A means for obtaining user interest and preference information and filtering the search results based on said interest and preference information,

[0908] A generative model that generates guide content using filtered tourist destination information,

[0909] A means for recognizing the user's emotions and adjusting the guide content based on those emotions,

[0910] A means of translating the generated guide content into the user's specified language,

[0911] A means for delivering the translated guide content to the user's terminal,

[0912] A system that includes this.

[0913] (Claim 2)

[0914] The system according to claim 1, comprising means for dynamically obtaining additional detailed information based on information of interest to the user.

[0915] (Claim 3)

[0916] The system according to claim 1, comprising means for providing guide content that supports multiple languages. [Explanation of symbols]

[0917] 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 device for acquiring location information, A means of searching for relevant tourist destination information based on the location information, A means for obtaining user interest and preference information and filtering the search results based on said interest and preference information, A generative model that generates guide content using filtered tourist destination information, A means of translating the generated guide content into the user's specified language, A means for delivering the translated guide content to the user's terminal, A system that includes this.

2. The system according to claim 1, comprising means for dynamically obtaining additional detailed information based on information of interest to the user.

3. The system according to claim 1, comprising means for providing guide content that supports multiple languages.

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