System

Abstract

An object of a system according to an embodiment is to provide information on a tourist spot or a destination in an easy-to-understand manner.SOLUTION: A system includes an input unit, an information acquisition unit, and an information conversion unit. The input unit receives an instruction from a user. The information acquisition unit collects information from the Internet based on the instruction received by the input unit. The information conversion part converts the information collected by the information acquisition part into a sightseeing guide style.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technology has had the problem of making it difficult to collect information about tourist spots and destinations and provide it in an easy-to-understand manner.

[0005] The system according to the embodiment aims to provide information about tourist spots and destinations in an easy-to-understand manner. [Means for solving the problem]

[0006] The system according to the embodiment includes an input unit, an information acquisition unit, and an information conversion unit. The input unit accepts user instructions. The information acquisition unit collects information from the Internet based on the instructions accepted by the input unit. The information conversion unit converts the information collected by the information acquisition unit into a tourist guide-style information. [Effects of the Invention]

[0007] The system according to the embodiment can provide information about tourist spots and destinations in an easy-to-understand manner. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The digital platform according to an embodiment of the present invention is a system that uses an AI tour conductor to create and provide customized guides for tourist spots and destinations specified by users, enabling the digital platform to meet various needs of travelers, from planning trips to guiding them during the actual trip.

[0029] A digital platform according to an embodiment includes an input unit, an information acquisition unit, and an information conversion unit. The input unit accepts user instructions. For example, the user inputs tourist spots or destinations they want to visit via text. Instructions can also be accepted using voice input. Furthermore, tourist spots can be selected using touch operations. The information acquisition unit collects information from the Internet based on the instructions accepted by the input unit. For example, the information acquisition unit collects information such as the history, highlights, access methods, and nearby restaurants of the tourist spot. The information acquisition unit can also acquire data from reliable sources. Furthermore, the information acquisition unit can collect the latest information using an API. The information conversion unit converts the information collected by the information acquisition unit into a tourist guide-style information. For example, the information acquisition unit analyzes the collected data, selects information useful to the user, and converts it into an easy-to-read format. The information conversion unit can also adjust the writing style and information structure and reorganize the information into a tourist guide-style text. Furthermore, the information conversion unit can provide information based on a template used. This allows the digital platform according to an embodiment to create and provide a tourist guide based on user instructions. For example, if a user types "Tell me about tourist spots in Tokyo," the system will collect information about tourist spots in Tokyo and provide it in a tourist guide format. If a user uses voice input to give instructions, the system will analyze the voice and similarly collect and provide information. Furthermore, if a user selects a tourist spot using touch operations, the system will also collect and provide information about the selected tourist spot.

[0030] The input unit can learn the user's past travel history and preferences and automatically generate suggestions for the next travel destination. The input unit, for example, stores the user's past travel history in a database and suggests the next travel destination based on that data. For example, it analyzes information on cities and tourist destinations visited in the past and suggests similar tourist destinations. The input unit can also learn the user's preferences and automatically generate suggestions for the next travel destination. For example, it makes suggestions based on the type of tourist destination the user likes and the activities they prefer. Furthermore, the input unit can make suggestions based on the user's past search history and survey results. This makes it possible to suggest the next travel destination based on the user's past travel history and preferences.

[0031] The input unit can suggest nearby tourist spots based on the user's real-time location information. The input unit, for example, uses the GPS function of the user's smartphone to obtain real-time location information and suggest nearby tourist spots. For example, the input unit may list tourist spots within walking distance of the current location. The input unit can also obtain location information using Wi-Fi location information or mobile base station information. For example, the input unit may identify the current location based on the location information of a Wi-Fi access point and suggest nearby tourist spots. Furthermore, the input unit can combine multiple data sources to improve the accuracy of the location information. This allows the input unit to suggest nearby tourist spots based on the user's real-time location information.

[0032] The information acquisition unit can automatically add event information and seasonal attractions related to the tourist destination entered by the user. The information acquisition unit, for example, builds a system that automatically collects event information related to the tourist destination entered by the user and adds it to the guide. For example, it provides information on festivals and concerts held at the tourist destination. The information acquisition unit can also automatically collect seasonal attractions and add them to the guide. For example, it provides seasonal natural scenery such as cherry blossoms in spring and autumn leaves. Furthermore, the information acquisition unit can collect event information and attractions from the official website of the tourist destination or from reliable information sources. This makes it possible to automatically add event information and seasonal attractions related to the tourist destination entered by the user.

[0033] The information acquisition unit can display reviews and ratings by other users for tourist destinations entered by the user. The information acquisition unit, for example, automatically collects reviews and ratings by other users for tourist destinations entered by the user and builds a system to display them in a guide. For example, the information acquisition unit acquires information from tourist destination review sites and social networking sites. The information acquisition unit can also analyze the content and evaluation criteria of reviews to provide information useful to users. For example, highly rated tourist destinations and popular activities can be displayed preferentially. Furthermore, the information acquisition unit can evaluate the reliability of reviews and display highly reliable reviews preferentially. This makes it possible to display reviews and ratings by other users for tourist destinations entered by the user.

[0034] The information acquisition unit can automatically collect the latest news and blog articles about tourist destinations and update the information. The information acquisition unit, for example, builds a system that automatically collects the latest news and blog articles about tourist destinations. For example, it acquires information using RSS feeds from news sites and blogs. The information acquisition unit can also collect the latest news and blog articles from the official website of the tourist destination or from reliable information sources. For example, it provides information about events at the tourist destination or information about new tourist spots. Furthermore, the information acquisition unit can regularly update the collected information and provide the user with the latest information. This makes it possible to automatically collect the latest news and blog articles about tourist destinations and update the information.

[0035] The information acquisition unit can preferentially acquire data from official tourist destination websites and other reliable information sources. The information acquisition unit, for example, builds a system that preferentially acquires data from official tourist destination websites and other reliable information sources. For example, it collects information from official tourist destination websites and government tourism information sites. The information acquisition unit can also acquire data from authenticated information sources and expert reviews. For example, it provides reliable information about the history and culture of the tourist destination. Furthermore, the information acquisition unit can evaluate the reliability of the collected data and provide reliable information preferentially. This makes it possible to preferentially acquire data from official tourist destination websites and other reliable information sources.

[0036] The information acquisition unit can simultaneously collect videos and images related to tourist destinations and provide visual information. The information acquisition unit, for example, automatically collects videos and images related to tourist destinations and builds a system that provides visual information. For example, it acquires videos and images of tourist destinations from YouTube and Instagram. The information acquisition unit can also collect videos and images from the official websites of tourist destinations and other reliable information sources. For example, it can provide promotional videos and photos of tourist destinations. Furthermore, the information acquisition unit can provide the collected videos and images in a format that is easy for users to view. This allows the system to simultaneously collect videos and images related to tourist destinations and provide visual information.

[0037] The information acquisition unit can also collect information in different languages ​​and provide a multilingual guide. The information acquisition unit, for example, automatically collects information in different languages ​​and builds a system that provides a multilingual guide. For example, the information acquisition unit collects information in multiple languages, such as English, French, and Chinese. The information acquisition unit can also translate the collected information with high accuracy and provide it to the user. For example, the information is translated using a translation API to create a multilingual guide. Furthermore, the information acquisition unit can also provide information in an appropriate language based on the user's language setting. This makes it possible to collect information in different languages ​​and provide a multilingual guide.

[0038] The information conversion unit can generate a customized guide tailored to the user's interests and concerns based on the collected information. The information conversion unit, for example, builds a system that generates a customized guide tailored to the user's interests and concerns based on the collected information. For example, the information conversion unit customizes the guide based on the user's past search history and preferences. The information conversion unit can also generate a guide based on the user's survey results and behavioral history. For example, the information conversion unit provides information based on the user's favorite types of tourist destinations and preferred activities. Furthermore, the information conversion unit can adjust the guide based on the user's real-time reactions. In this way, a customized guide tailored to the user's interests and concerns can be generated based on the collected information.

[0039] The information conversion unit can add detailed information about the history and culture of a tourist destination, promoting a deeper understanding. The information conversion unit, for example, builds a system that adds detailed information about the history and culture of a tourist destination based on collected information. For example, it details the historical background and cultural significance of a tourist destination. The information conversion unit can also provide detailed information based on expert commentary and literature information. For example, it details historical events and cultural characteristics of a tourist destination. Furthermore, the information conversion unit can provide detailed information tailored to the user's interests and concerns. This allows for the addition of detailed information about the history and culture of a tourist destination, promoting a deeper understanding.

[0040] The information conversion unit can visually present the collected information in infographic or mind map format. The information conversion unit, for example, builds a system that visually presents the collected information in infographic format. For example, it illustrates the main attractions of a tourist destination and how to access it. The information conversion unit can also provide the collected information in mind map format. For example, it can organize information about tourist destinations hierarchically and display it visually. Furthermore, the information conversion unit can adjust the design tools used and the data visualization method to provide the information in an easy-to-read format. This makes it possible to visually present the collected information in infographic or mind map format.

[0041] The information conversion unit can also simultaneously provide information on related tourist destinations that may be of interest to the user. The information conversion unit, for example, builds a system that automatically collects and simultaneously provides information on related tourist destinations that may be of interest to the user. For example, it suggests tourist destinations near a tourist destination that the user wants to visit. The information conversion unit can also select related tourist destinations based on thematic similarity or geographical proximity. For example, it suggests tourist destinations with the same theme or nearby tourist destinations. Furthermore, the information conversion unit can also select related tourist destinations based on the user's past behavior history and preferences. This makes it possible to simultaneously provide information on related tourist destinations that may be of interest to the user.

[0042] The information conversion unit can use the reading function to customize the tone of voice and speaking style to suit the user's preferences. For example, the information conversion unit builds a system that customizes the tone of voice and speaking style to suit the user's preferences when reading aloud. For example, the tone of voice and speaking style selected by the user are reflected. The information conversion unit can also adjust the tone of voice and speaking style using speech synthesis technology. For example, the speaking speed and intonation can be adjusted. Furthermore, the information conversion unit can also adjust the tone of voice and speaking style based on the user's real-time response. This makes it possible to customize the tone of voice and speaking style to suit the user's preferences when reading aloud.

[0043] The information conversion unit can add background music and sound effects in addition to the reading function to enhance the sense of realism. The information conversion unit, for example, builds a system that adds background music and sound effects in addition to the reading function. For example, it plays music and sound effects that match the atmosphere of a tourist spot. The information conversion unit can also adjust the genre and volume of the music to enhance the sense of realism. For example, it plays calm music in quiet places and lively music in noisy places. Furthermore, the information conversion unit can adjust the type and timing of the sound effects to enhance the sense of realism. This makes it possible to add background music and sound effects in addition to the reading function to enhance the sense of realism.

[0044] The information conversion unit can adjust the readout content to match the user's pace and provide it at a speed that is easy to understand. The information conversion unit, for example, builds a system that adjusts the readout content to match the user's pace. For example, it reads at a speed set by the user. The information conversion unit can also adjust the readout speed based on the user's response. For example, it provides information at a speed that is easy for the user to understand. Furthermore, the information conversion unit can also adjust the readout speed depending on the complexity of the information. This allows the readout content to be adjusted to match the user's pace and provided at a speed that is easy to understand.

[0045] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0046] Digital platforms can also monitor users' health status and reflect this in travel destination suggestions. For example, they can track a user's heart rate and number of steps and suggest travel destinations based on their health status. If the user's heart rate is high, they can suggest relaxing tourist spots, and if the user's step count is low, they can suggest active tourist spots. They can also suggest appropriate restaurants based on the user's dietary restrictions and allergies. This makes it possible to provide travel plans customized to the user's health status.

[0047] The digital platform can also analyze a user's past travel photos and use them to suggest the user's next travel destination. For example, it can analyze the characteristics of scenery and buildings in photos taken by the user in the past and suggest similar tourist spots. It can also analyze activities and events shown in the photos and suggest events that the user may be interested in. It can also suggest recommended spots for the user's next travel destination based on photos of tourist spots the user has visited in the past. This makes it possible to suggest the user's next travel destination by utilizing the user's past travel photos.

[0048] The digital platform can also suggest optimal tourist spots based on the user's real-time weather information. For example, if it is raining in the user's current location, indoor tourist spots will be suggested, and if it is sunny, outdoor tourist spots will be suggested. The platform can also suggest optimal dates when planning a trip based on the weather forecast. Furthermore, it can suggest activities at tourist spots based on the weather information. This allows the platform to suggest optimal tourist spots based on the user's real-time weather information.

[0049] The digital platform can also provide users with safety information during their trip. For example, it can provide information about the safety of the destination and emergency contacts. It can also provide real-time information about natural disasters, traffic information, and other important travel information. It can also provide information about the nearest medical institutions and police stations based on the user's current location. This allows it to provide information to ensure the user's safety during their trip.

[0050] Digital platforms can also support users' communication while traveling. For example, they can provide simple phrases and sample conversations in the local language. They can also use translation functions to help users communicate with local people. They can also provide information about local culture and etiquette to help users communicate smoothly. In this way, they can support users' communication while traveling.

[0051] The processing flow of the first embodiment will be briefly explained below.

[0052] Step 1: The input unit accepts user instructions. For example, the user inputs the tourist spots or destinations they want to visit as text. Instructions can also be accepted using voice input. Furthermore, tourist spots can also be selected using touch operations. Step 2: The information acquisition unit collects information from the Internet based on the instructions received by the input unit. For example, it collects information such as the history and highlights of tourist destinations, how to access them, and nearby restaurants. The information acquisition unit can also obtain data from reliable sources. Furthermore, the information acquisition unit can also collect the latest information using APIs. Step 3: The information conversion unit converts the information collected by the information acquisition unit into a tourist guide-style document. For example, it analyzes the collected data, selects information that is useful to the user, and converts it into an easy-to-read format. The information conversion unit can also adjust the writing style and information structure, and reorganize the text into a tourist guide-style document. Furthermore, the information conversion unit can provide information based on the template used.

[0053] (Example 2) The digital platform according to an embodiment of the present invention is a system that uses an AI tour conductor to create and provide customized guides for tourist spots and destinations specified by users, enabling the digital platform to meet various needs of travelers, from planning trips to guiding them during the actual trip.

[0054] A digital platform according to an embodiment includes an input unit, an information acquisition unit, and an information conversion unit. The input unit accepts user instructions. For example, the user inputs tourist spots or destinations they want to visit via text. Instructions can also be accepted using voice input. Furthermore, tourist spots can be selected using touch operations. The information acquisition unit collects information from the Internet based on the instructions accepted by the input unit. For example, the information acquisition unit collects information such as the history, highlights, access methods, and nearby restaurants of the tourist spot. The information acquisition unit can also acquire data from reliable sources. Furthermore, the information acquisition unit can collect the latest information using an API. The information conversion unit converts the information collected by the information acquisition unit into a tourist guide-style information. For example, the information acquisition unit analyzes the collected data, selects information useful to the user, and converts it into an easy-to-read format. The information conversion unit can also adjust the writing style and information structure and reorganize the information into a tourist guide-style text. Furthermore, the information conversion unit can provide information based on a template used. This allows the digital platform according to an embodiment to create and provide a tourist guide based on user instructions. For example, if a user types "Tell me about tourist spots in Tokyo," the system will collect information about tourist spots in Tokyo and provide it in a tourist guide format. If a user uses voice input to give instructions, the system will analyze the voice and similarly collect and provide information. Furthermore, if a user selects a tourist spot using touch operations, the system will also collect and provide information about the selected tourist spot.

[0055] The input unit can learn the user's past travel history and preferences and automatically generate suggestions for the next travel destination. The input unit, for example, stores the user's past travel history in a database and suggests the next travel destination based on that data. For example, it analyzes information on cities and tourist destinations visited in the past and suggests similar tourist destinations. The input unit can also learn the user's preferences and automatically generate suggestions for the next travel destination. For example, it makes suggestions based on the type of tourist destination the user likes and the activities they prefer. Furthermore, the input unit can make suggestions based on the user's past search history and survey results. This makes it possible to suggest the next travel destination based on the user's past travel history and preferences.

[0056] The input unit can suggest nearby tourist spots based on the user's real-time location information. The input unit, for example, uses the GPS function of the user's smartphone to obtain real-time location information and suggest nearby tourist spots. For example, the input unit may list tourist spots within walking distance of the current location. The input unit can also obtain location information using Wi-Fi location information or mobile base station information. For example, the input unit may identify the current location based on the location information of a Wi-Fi access point and suggest nearby tourist spots. Furthermore, the input unit can combine multiple data sources to improve the accuracy of the location information. This allows the input unit to suggest nearby tourist spots based on the user's real-time location information.

[0057] The input unit can use the emotion estimation function to suggest travel destinations that match the user's current mood. The input unit, for example, analyzes the user's facial expressions and voice to build a system that estimates the user's current mood. For example, if the user is in the mood to relax, the input unit can suggest quiet tourist spots. The input unit can also estimate the user's mood using text analysis. For example, it can analyze emotions from text entered by the user and suggest travel destinations that match the user's mood. Furthermore, the input unit can collect the user's biometric data (heart rate and electrodermal activity) using a sensor and analyze the user's mood using an emotion estimation algorithm. This makes it possible to suggest travel destinations that match the user's current mood.

[0058] The information acquisition unit can automatically add event information and seasonal attractions related to the tourist destination entered by the user. The information acquisition unit, for example, builds a system that automatically collects event information related to the tourist destination entered by the user and adds it to the guide. For example, it provides information on festivals and concerts held at the tourist destination. The information acquisition unit can also automatically collect seasonal attractions and add them to the guide. For example, it provides seasonal natural scenery such as cherry blossoms in spring and autumn leaves. Furthermore, the information acquisition unit can collect event information and attractions from the official website of the tourist destination or from reliable information sources. This makes it possible to automatically add event information and seasonal attractions related to the tourist destination entered by the user.

[0059] The information acquisition unit can display reviews and ratings by other users for tourist destinations entered by the user. The information acquisition unit, for example, automatically collects reviews and ratings by other users for tourist destinations entered by the user and builds a system to display them in a guide. For example, the information acquisition unit acquires information from tourist destination review sites and social networking sites. The information acquisition unit can also analyze the content and evaluation criteria of reviews to provide information useful to users. For example, highly rated tourist destinations and popular activities can be displayed preferentially. Furthermore, the information acquisition unit can evaluate the reliability of reviews and display highly reliable reviews preferentially. This makes it possible to display reviews and ratings by other users for tourist destinations entered by the user.

[0060] The information acquisition unit uses the emotion estimation function to analyze the emotion of the user when entering text in real time and make suggestions that elicit positive emotions. The information acquisition unit, for example, analyzes the facial expressions and voice of the user when entering text to build a system that estimates the emotion in real time. For example, the information acquisition unit analyzes the user's emotion using a camera or microphone and makes positive suggestions when negative emotions are detected. The information acquisition unit can also analyze the user's emotion in real time using text analysis. For example, it analyzes the emotion from the text entered by the user and makes positive suggestions. Furthermore, the information acquisition unit can collect the user's biometric data (heart rate and electrodermal activity) using a sensor and analyze the emotion in real time using an emotion estimation algorithm. This makes it possible to analyze the user's emotion when entering text in real time and make suggestions that elicit positive emotions.

[0061] The information acquisition unit can automatically collect the latest news and blog articles about tourist destinations and update the information. The information acquisition unit, for example, builds a system that automatically collects the latest news and blog articles about tourist destinations. For example, it acquires information using RSS feeds from news sites and blogs. The information acquisition unit can also collect the latest news and blog articles from the official website of the tourist destination or from reliable information sources. For example, it provides information about events at the tourist destination or information about new tourist spots. Furthermore, the information acquisition unit can regularly update the collected information and provide the user with the latest information. This makes it possible to automatically collect the latest news and blog articles about tourist destinations and update the information.

[0062] The information acquisition unit can preferentially acquire data from official tourist destination websites and other reliable information sources. The information acquisition unit, for example, builds a system that preferentially acquires data from official tourist destination websites and other reliable information sources. For example, it collects information from official tourist destination websites and government tourism information sites. The information acquisition unit can also acquire data from authenticated information sources and expert reviews. For example, it provides reliable information about the history and culture of the tourist destination. Furthermore, the information acquisition unit can evaluate the reliability of the collected data and provide reliable information preferentially. This makes it possible to preferentially acquire data from official tourist destination websites and other reliable information sources.

[0063] The information acquisition unit can use the emotion estimation function to select information that is most interesting to the user from the collected information. The information acquisition unit, for example, performs emotion estimation on the collected information and builds a system that selects information that is most interesting to the user. For example, information that has a high number of positive emotional responses can be preferentially displayed. The information acquisition unit can also select information that is likely to be of interest to the user based on the user's past behavioral history and preferences. For example, information related to tourist spots and activities that the user has previously searched for can be preferentially provided. Furthermore, the information acquisition unit can also select information based on the user's real-time emotional responses. This makes it possible to select information that is most interesting to the user from the collected information.

[0064] The information acquisition unit can simultaneously collect videos and images related to tourist destinations and provide visual information. The information acquisition unit, for example, automatically collects videos and images related to tourist destinations and builds a system that provides visual information. For example, it acquires videos and images of tourist destinations from YouTube and Instagram. The information acquisition unit can also collect videos and images from the official websites of tourist destinations and other reliable information sources. For example, it can provide promotional videos and photos of tourist destinations. Furthermore, the information acquisition unit can provide the collected videos and images in a format that is easy for users to view. This allows the system to simultaneously collect videos and images related to tourist destinations and provide visual information.

[0065] The information acquisition unit can also collect information in different languages ​​and provide a multilingual guide. The information acquisition unit, for example, automatically collects information in different languages ​​and builds a system that provides a multilingual guide. For example, the information acquisition unit collects information in multiple languages, such as English, French, and Chinese. The information acquisition unit can also translate the collected information with high accuracy and provide it to the user. For example, the information is translated using a translation API to create a multilingual guide. Furthermore, the information acquisition unit can also provide information in an appropriate language based on the user's language setting. This makes it possible to collect information in different languages ​​and provide a multilingual guide.

[0066] The information acquisition unit can use the emotion estimation function to analyze the user's emotional response to the collected information and provide optimal information. The information acquisition unit, for example, performs emotion estimation on the collected information and builds a system that analyzes the user's emotional response. For example, information with a high number of positive emotional responses can be preferentially provided. The information acquisition unit can also select optimal information based on the user's past behavioral history and preferences. For example, information related to tourist spots and activities that the user has previously searched for can be preferentially provided. Furthermore, the information acquisition unit can select information based on the user's real-time emotional response. This makes it possible to analyze the user's emotional response to the collected information and provide optimal information.

[0067] The information conversion unit can generate a customized guide tailored to the user's interests and concerns based on the collected information. The information conversion unit, for example, builds a system that generates a customized guide tailored to the user's interests and concerns based on the collected information. For example, the information conversion unit customizes the guide based on the user's past search history and preferences. The information conversion unit can also generate a guide based on the user's survey results and behavioral history. For example, the information conversion unit provides information based on the user's favorite types of tourist destinations and preferred activities. Furthermore, the information conversion unit can adjust the guide based on the user's real-time reactions. In this way, a customized guide tailored to the user's interests and concerns can be generated based on the collected information.

[0068] The information conversion unit can add detailed information about the history and culture of a tourist destination, promoting a deeper understanding. The information conversion unit, for example, builds a system that adds detailed information about the history and culture of a tourist destination based on collected information. For example, it details the historical background and cultural significance of a tourist destination. The information conversion unit can also provide detailed information based on expert commentary and literature information. For example, it details historical events and cultural characteristics of a tourist destination. Furthermore, the information conversion unit can provide detailed information tailored to the user's interests and concerns. This allows for the addition of detailed information about the history and culture of a tourist destination, promoting a deeper understanding.

[0069] The information conversion unit can use the emotion estimation function to provide information in a storytelling format that most moves the user. The information conversion unit, for example, uses the emotion estimation function to build a system that provides information in a storytelling format that most moves the user. For example, the information conversion unit customizes a story based on the user's emotional response. The information conversion unit can also adjust the structure of the story and the techniques used to provide moving storytelling. For example, the information conversion unit provides a story that incorporates elements that elicit emotions. Furthermore, the information conversion unit can also adjust the storytelling to suit the user's preferences. This makes it possible to provide information in a storytelling format that most moves the user.

[0070] The information conversion unit can visually present the collected information in infographic or mind map format. The information conversion unit, for example, builds a system that visually presents the collected information in infographic format. For example, it illustrates the main attractions of a tourist destination and how to access it. The information conversion unit can also provide the collected information in mind map format. For example, it can organize information about tourist destinations hierarchically and display it visually. Furthermore, the information conversion unit can adjust the design tools used and the data visualization method to provide the information in an easy-to-read format. This makes it possible to visually present the collected information in infographic or mind map format.

[0071] The information conversion unit can also simultaneously provide information on related tourist destinations that may be of interest to the user. The information conversion unit, for example, builds a system that automatically collects and simultaneously provides information on related tourist destinations that may be of interest to the user. For example, it suggests tourist destinations near a tourist destination that the user wants to visit. The information conversion unit can also select related tourist destinations based on thematic similarity or geographical proximity. For example, it suggests tourist destinations with the same theme or nearby tourist destinations. Furthermore, the information conversion unit can also select related tourist destinations based on the user's past behavior history and preferences. This makes it possible to simultaneously provide information on related tourist destinations that may be of interest to the user.

[0072] The information conversion unit can use the emotion estimation function to prioritize displaying information that is of most interest to the user. For example, the information conversion unit uses the emotion estimation function to build a system that prioritizes displaying information that is of most interest to the user. For example, the information conversion unit adjusts the display order of information based on the user's emotional response. The information conversion unit can also select and prioritize information based on the user's past behavioral history and preferences. For example, information related to tourist spots and activities that the user has previously searched for can be displayed preferentially. Furthermore, the information conversion unit can select and prioritize information based on real-time emotional responses. This makes it possible to prioritize displaying information that is of most interest to the user.

[0073] The information conversion unit can use the reading function to customize the tone of voice and speaking style to suit the user's preferences. For example, the information conversion unit builds a system that customizes the tone of voice and speaking style to suit the user's preferences when reading aloud. For example, the tone of voice and speaking style selected by the user are reflected. The information conversion unit can also adjust the tone of voice and speaking style using speech synthesis technology. For example, the speaking speed and intonation can be adjusted. Furthermore, the information conversion unit can also adjust the tone of voice and speaking style based on the user's real-time response. This makes it possible to customize the tone of voice and speaking style to suit the user's preferences when reading aloud.

[0074] The information conversion unit can analyze the user's reactions in real time while reading aloud and adjust the content as necessary. For example, the information conversion unit can build a system that analyzes the user's reactions in real time while reading aloud and adjusts the content as necessary. For example, the information conversion unit can change the content by analyzing the user's facial expressions and voice. The information conversion unit can also analyze the user's reactions in real time using text analysis. For example, it can highlight parts that the user showed interest in. Furthermore, the information conversion unit can collect the user's biometric data (heart rate and electrodermal activity) using a sensor and analyze the reactions in real time. This makes it possible to analyze the user's reactions in real time while reading aloud and adjust the content as necessary.

[0075] The information conversion unit can use the emotion estimation function to read aloud in a voice that makes the user feel most relaxed. The information conversion unit, for example, uses the emotion estimation function to build a system that reads aloud in a voice that makes the user feel most relaxed. For example, the tone of the voice is adjusted based on the user's emotional response. The information conversion unit can also generate a relaxing voice using voice synthesis technology. For example, a gentle tone or a slow speaking style is adopted. Furthermore, the information conversion unit can adjust the tone of the voice and speaking style to suit the user's preferences. This allows the system to read aloud in a voice that makes the user feel most relaxed.

[0076] The information conversion unit can add background music and sound effects in addition to the reading function to enhance the sense of realism. The information conversion unit, for example, builds a system that adds background music and sound effects in addition to the reading function. For example, it plays music and sound effects that match the atmosphere of a tourist spot. The information conversion unit can also adjust the genre and volume of the music to enhance the sense of realism. For example, it plays calm music in quiet places and lively music in noisy places. Furthermore, the information conversion unit can adjust the type and timing of the sound effects to enhance the sense of realism. This makes it possible to add background music and sound effects in addition to the reading function to enhance the sense of realism.

[0077] The information conversion unit can adjust the readout content to match the user's pace and provide it at a speed that is easy to understand. The information conversion unit, for example, builds a system that adjusts the readout content to match the user's pace. For example, it reads at a speed set by the user. The information conversion unit can also adjust the readout speed based on the user's response. For example, it provides information at a speed that is easy for the user to understand. Furthermore, the information conversion unit can also adjust the readout speed depending on the complexity of the information. This allows the readout content to be adjusted to match the user's pace and provided at a speed that is easy to understand.

[0078] The information conversion unit can use the emotion estimation function to emphasize and read out the parts that the user is most interested in. For example, the information conversion unit uses the emotion estimation function to build a system that emphasizes and reads out the parts that the user is most interested in. For example, it emphasizes important parts based on the user's emotional response. The information conversion unit can also select and emphasize parts that the user is interested in based on the user's past behavior history and preferences. For example, it can emphasize information related to tourist spots and activities that the user has searched for in the past. Furthermore, the information conversion unit can select information based on real-time emotional responses and emphasize and read out. This makes it possible to emphasize and read out the parts that the user is most interested in.

[0079] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0080] Digital platforms can also monitor users' health status and reflect this in travel destination suggestions. For example, they can track a user's heart rate and number of steps and suggest travel destinations based on their health status. If the user's heart rate is high, they can suggest relaxing tourist spots, and if the user's step count is low, they can suggest active tourist spots. They can also suggest appropriate restaurants based on the user's dietary restrictions and allergies. This makes it possible to provide travel plans customized to the user's health status.

[0081] The digital platform can also analyze a user's past travel photos and use them to suggest the user's next travel destination. For example, it can analyze the characteristics of scenery and buildings in photos taken by the user in the past and suggest similar tourist spots. It can also analyze activities and events shown in the photos and suggest events that the user may be interested in. It can also suggest recommended spots for the user's next travel destination based on photos of tourist spots the user has visited in the past. This makes it possible to suggest the user's next travel destination by utilizing the user's past travel photos.

[0082] The digital platform can also suggest optimal tourist spots based on the user's real-time weather information. For example, if it is raining in the user's current location, indoor tourist spots will be suggested, and if it is sunny, outdoor tourist spots will be suggested. The platform can also suggest optimal dates when planning a trip based on the weather forecast. Furthermore, it can suggest activities at tourist spots based on the weather information. This allows the platform to suggest optimal tourist spots based on the user's real-time weather information.

[0083] The digital platform can further estimate the user's emotions and suggest travel destinations based on the estimated emotions. For example, if the user is feeling stressed, it can suggest relaxing tourist spots, and if the user is feeling excited, it can suggest active tourist spots. It can also suggest activities and events at the travel destination based on the user's emotions. Furthermore, it can monitor the user's emotions in real time and adjust suggestions during the trip. This makes it possible to suggest the best travel destinations based on the user's emotions.

[0084] The digital platform can further estimate the user's emotions and suggest activities at tourist spots based on the estimated emotions. For example, if the user is in the mood for relaxation, it can suggest spas and hot springs. If the user is adventurous, it can suggest hiking and adventure sports. It can also suggest dining and shopping at tourist spots based on the user's emotions. Furthermore, it can monitor the user's emotions in real time and adjust activity suggestions. This allows it to suggest optimal activities based on the user's emotions.

[0085] The digital platform can further estimate the user's emotions and provide support during the trip based on the estimated emotions. For example, if the user is feeling anxious, it can provide information and support that reassures the user. If the user is excited, it can suggest information and activities to maintain excitement. It can also provide troubleshooting and emergency support during the trip based on the user's emotions. Furthermore, it can monitor the user's emotions in real time and adjust the support content. This allows it to provide optimal support during the trip based on the user's emotions.

[0086] The digital platform can also estimate the user's emotions and make dining recommendations based on the estimated emotions. For example, if the user is in a relaxing mood, it can suggest quiet restaurants and cafes. If the user is feeling adventurous, it can suggest exotic cuisine and new dining experiences. It can also suggest meal times and locations based on the user's emotions. Furthermore, it can monitor the user's emotions in real time and adjust the meal recommendations accordingly. This allows it to make optimal meal recommendations based on the user's emotions.

[0087] The digital platform can also estimate the user's emotions and make shopping suggestions at the travel destination based on the estimated emotions. For example, if the user is in a relaxing mood, it can suggest quiet shopping areas and relaxing stores. If the user is feeling adventurous, it can suggest unique products and new shopping experiences. It can also suggest shopping times and places based on the user's emotions. Furthermore, it can monitor the user's emotions in real time and adjust the shopping suggestions. This allows it to make optimal shopping suggestions based on the user's emotions.

[0088] The digital platform can also provide users with safety information during their trip. For example, it can provide information about the safety of the destination and emergency contacts. It can also provide real-time information about natural disasters, traffic information, and other important travel information. It can also provide information about the nearest medical institutions and police stations based on the user's current location. This allows it to provide information to ensure the user's safety during their trip.

[0089] Digital platforms can also support users' communication while traveling. For example, they can provide simple phrases and sample conversations in the local language. They can also use translation functions to help users communicate with local people. They can also provide information about local culture and etiquette to help users communicate smoothly. In this way, they can support users' communication while traveling.

[0090] The processing flow of the second embodiment will be briefly explained below.

[0091] Step 1: The input unit accepts user instructions. For example, the user inputs the tourist spots or destinations they want to visit as text. Instructions can also be accepted using voice input. Furthermore, tourist spots can also be selected using touch operations. Step 2: The information acquisition unit collects information from the Internet based on the instructions received by the input unit. For example, it collects information such as the history and highlights of tourist destinations, how to access them, and nearby restaurants. The information acquisition unit can also obtain data from reliable sources. Furthermore, the information acquisition unit can also collect the latest information using APIs. Step 3: The information conversion unit converts the information collected by the information acquisition unit into a tourist guide-style document. For example, it analyzes the collected data, selects information that is useful to the user, and converts it into an easy-to-read format. The information conversion unit can also adjust the writing style and information structure, and reorganize the text into a tourist guide-style document. Furthermore, the information conversion unit can provide information based on the template used.

[0092] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0093] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0094] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0095] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0096] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0097] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0098] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0099] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0100] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0101] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0102] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0103] 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.

[0104] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0105] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0106] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0107] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0108] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0109] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0110] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0111] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0112] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0113] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0114] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0115] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0116] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0117] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0118] 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.

[0119] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0120] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0121] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0122] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0123] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0124] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0125] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0126] 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.

[0127] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0128] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0129] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0130] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0131] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0132] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0133] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0134] 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.

[0135] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0136] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0137] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0138] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0139] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0140] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0141] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0142] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0143] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0144] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0145] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0146] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0147] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0148] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0149] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0150] 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.

[0151] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0152] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0153] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0154] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0155] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0156] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0157] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, in order to avoid confusion and to facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0158] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0159] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. an input unit that accepts instructions from a user; an information acquisition unit that collects information from the Internet based on instructions received by the input unit; an information conversion unit that converts the information collected by the information acquisition unit into a tourist guide style information A system characterized by:

2. The input unit Suggesting nearby tourist spots based on the user's real-time location information 2. The system of claim 1.

3. The information acquisition unit Automatically add event information and seasonal attractions related to tourist destinations entered by the user 2. The system of claim 1.

4. The information acquisition unit Automatically gather and update the latest news and blog posts about tourist destinations 2. The system of claim 1.

5. The information conversion unit Generate a customized guide based on the user's interests and concerns using the collected information 2. The system of claim 1.

6. The information conversion unit Present information in a storytelling format that is most compelling to users 2. The system of claim 1.

7. The information conversion unit Analyze user responses in real time while reading and adjust content as needed 2. The system of claim 1.

8. The input unit Suggesting travel destinations that match the user's current mood 2. The system of claim 1.

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