system

Abstract

The system according to this embodiment aims to alleviate the shortage of tour guides and provide tourists with high-quality, multilingual tourist information. [Solution] The system according to this embodiment comprises a guidance unit, a translation unit, a suggestion unit, and a storytelling unit. The guidance unit provides tourist information. The translation unit performs real-time multilingual translation. The suggestion unit proposes personalized tourist routes based on the tourist's preferences and interests. The storytelling unit performs storytelling about the local history and culture.

Description

Technical Field

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

Background Art

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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the prior art, there are shortages of tourist guides and difficulties in multilingual support, which may lead to a decline in the quality of services for tourists.

[0005] The system according to the embodiment aims to eliminate the shortage of tourist guides and provide high-quality multilingual tourist guidance for tourists.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a guidance unit, a translation unit, a suggestion unit, and a storytelling unit. The guidance unit provides tourist information. The translation unit performs real-time multilingual translation. The suggestion unit proposes personalized tourist routes based on the tourist's preferences and interests. The storytelling unit performs storytelling about the local history and culture. [Effects of the Invention]

[0007] The system according to this embodiment can alleviate the shortage of tour guides and provide tourists with high-quality, multilingual tourist information. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

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

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

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

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

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

[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, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are 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 comprises a computer 36, a receiving device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The receiving device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

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

[0025] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction 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 a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also 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 processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The tourist guide system according to an embodiment of the present invention is a system for solving the shortage of tourist guides. This tourist guide system provides tourist information at any time when tourists need it, through an AI agent. The tourist guide system performs real-time multilingual translation and proposes personalized tourist routes based on the tourist's preferences and interests. Furthermore, the tourist guide system tells stories about the history and culture of the region. This mechanism can solve the problems faced by local governments and tourist facility operators in tourist areas, foreign tourists visiting Japan, and domestic travelers, such as the shortage of guide personnel, language barriers, and the inability to fully convey the charm of the region. For example, when a tourist arrives at a tourist destination, the tourist guide system will guide them to the highlights and recommended tourist spots. This allows tourists to enjoy the tourist destination even without a guide. Next, the tourist guide system performs real-time multilingual translation to eliminate language barriers. For example, even if a tourist does not understand Japanese, the tourist guide system will provide tourist information in multiple languages, allowing the tourist to enjoy sightseeing without feeling a language barrier. Furthermore, the tourist guide system proposes personalized tourist routes based on the tourist's preferences and interests. For example, if a tourist is interested in historical buildings, the tourist guide system will propose a route that visits historical buildings best suited to that tourist. This allows tourists to enjoy sightseeing tailored to their interests. Finally, the tourist guide system tells stories about the region's history and culture, fully conveying its charm. For example, by having the tourist guide system explain the history and culture of a place a tourist visits in detail, the tourist can gain a deeper understanding of the place's appeal. This system can solve the problems faced by local governments, tourist facility operators, foreign tourists visiting Japan, and domestic travelers, such as a shortage of guides, language barriers, and the inability to fully convey the charm of a region. Furthermore, by utilizing the tourist guide system, it is expected that the market size of the tourism industry will expand and inbound tourism spending will increase. Moreover, as AI technology matures, more advanced tourist guidance, multilingual translation, personalized sightseeing route suggestions, and storytelling will become possible, further improving tourist satisfaction.This allows the tourist guide system to improve tourist satisfaction.

[0029] The tourist guide system according to this embodiment comprises an information unit, a translation unit, a suggestion unit, and a storytelling unit. The information unit provides tourist information. For example, the information unit guides users to the highlights and recommended tourist spots of a tourist destination. The information unit can guide users to popular spots, historical sites, cultural facilities, etc. of a tourist destination. For example, the information unit displays a map of the tourist destination and indicates spots that tourists should visit. The information unit can also provide detailed information such as event information and opening hours of the tourist destination. For example, the information unit displays an event calendar of the tourist destination and guides tourists to events they can participate in. The translation unit performs real-time multilingual translation. For example, the translation unit provides tourist information in multiple languages. The translation unit can automatically translate tourist information according to the language used by the tourist. For example, the translation unit supports multiple languages ​​such as English, Chinese, and French. In addition, the translation unit can appropriately translate technical terms and proper nouns such as place names in order to accurately translate the content of the tourist information. For example, the translation unit can accurately translate the names of tourist destinations and historical buildings. The suggestion department proposes personalized sightseeing routes based on tourists' preferences and interests. For example, the suggestion department proposes routes based on themes that tourists are interested in. The suggestion department can analyze tourists' past visit history and current interests to propose the optimal sightseeing route. For example, the suggestion department customizes sightseeing routes based on places tourists have visited in the past and themes that tourists are interested in. The suggestion department can also adjust sightseeing routes according to tourists' schedules and length of stay. For example, if tourists have a short stay, the suggestion department will prioritize showing them major tourist attractions. The storytelling department provides storytelling about the history and culture of the region. For example, the storytelling department provides detailed explanations of the history and culture of the places tourists have visited. The storytelling department can provide background information and anecdotes about the places tourists have visited. For example, the storytelling department tells stories about historical events and cultural significance of tourist destinations. The storytelling department can also customize the content of the storytelling based on themes that tourists are interested in.For example, the storytelling section provides stories about historical figures and events that are of interest to tourists. This allows the tourist guide system according to this embodiment to improve tourist satisfaction.

[0030] The information desk provides tourist information. For example, it can guide visitors to the highlights and recommended tourist spots of a tourist destination. Specifically, it can provide information on popular spots, historical sites, and cultural facilities. For example, the information desk can display a map of the tourist destination and indicate the places tourists should visit. The information desk can also provide detailed information such as event information and opening hours of tourist destinations. For example, the information desk can display an event calendar of the tourist destination and guide tourists to events they can participate in. Furthermore, the information desk can provide information on access to tourist destinations and transportation options. For example, it can provide directions from the nearest train station or bus stop to the tourist destination and timetables for available transportation options. The information desk can also provide information on restaurants and accommodations around the tourist destination. For example, it can provide information on recommended menus and opening hours of restaurants and cafes around the tourist destination, as well as accommodation rates and availability. This allows tourists to obtain all the necessary information for visiting a tourist destination at once and enjoy their sightseeing smoothly. Furthermore, the information desk can also provide photos and videos of tourist destinations. For example, the information desk can display photos of beautiful scenery and historical buildings in tourist areas, as well as videos of events, to attract tourists' interest. The information desk can also display reviews and comments about tourist destinations. For instance, it can show ratings and impressions posted by other tourists, which can be used as a reference when planning a visit. This allows the information desk to provide tourists with comprehensive information and convey the charm of the tourist destination to its fullest potential.

[0031] The translation department provides real-time multilingual translation. For example, it can provide tourist information in multiple languages. Specifically, it can automatically translate tourist information according to the language used by the tourist. For example, the translation department supports multiple languages ​​such as English, Chinese, and French. Furthermore, to ensure accurate translation of tourist information, the translation department can appropriately translate technical terms and proper nouns such as place names. For example, it accurately translates the names of tourist attractions and historical buildings. In addition, the translation department can translate questions asked by tourists in real time and provide tourist information. For example, if a tourist enters a question using a smartphone or tablet, the translation department automatically translates the question and provides an appropriate answer. The translation department can also use speech recognition technology to convert tourists' voices into text and translate them. For example, if a tourist asks a question by voice, the translation department converts the voice into text, translates it, and provides an answer. This allows tourists to receive tourist information smoothly without experiencing language barriers. Furthermore, the translation department can also translate the content of signs and brochures at tourist attractions. For example, if a tourist takes a photo of the content of an information board at a tourist spot with their smartphone, the translation unit will automatically translate the content and display it to the tourist. It can also translate the content of brochures distributed at tourist spots and provide it in a format that is easy for tourists to understand. In this way, the translation unit can provide tourists with multilingual tourist information, making their experience at tourist destinations more fulfilling.

[0032] The suggestion department proposes personalized sightseeing routes based on tourists' preferences and interests. For example, it suggests routes based on themes that tourists are interested in. Specifically, it can analyze tourists' past visit history and current interests to propose the optimal sightseeing route. For example, the suggestion department customizes sightseeing routes based on places tourists have visited in the past and themes they are interested in. The suggestion department can also adjust sightseeing routes according to tourists' schedules and length of stay. For example, if tourists have a short stay, it will prioritize showing them major tourist spots. Furthermore, the suggestion department can optimize sightseeing routes according to tourists' means of transportation and physical ability. For example, for tourists who have difficulty traveling on foot, it will suggest routes using public transport or taxis. The suggestion department can also suggest restaurants and cafes, taking into account tourists' dietary preferences and allergy information. For example, it will suggest restaurants that offer vegetarian menus to vegetarian tourists. In this way, the suggestion department can provide a personalized sightseeing experience tailored to the needs of each individual tourist. Furthermore, the suggestion department can collect real-time feedback from tourists and continuously improve its suggestions. For example, the department can collect ratings and feedback from tourists about the places they visited and the activities they experienced, and incorporate this into future recommendations. The department can also analyze tourists' social media posts and review site information to understand the latest trends and popular spots. This allows the department to consistently propose optimal sightseeing routes based on the most up-to-date information, thereby improving tourist satisfaction.

[0033] The Storytelling Department conducts storytelling about the history and culture of the region. For example, the Storytelling Department can provide detailed explanations of the history and culture of places that tourists visit. Specifically, they can provide background information and anecdotes about the places tourists visit. For example, the Storytelling Department can tell stories about historical events and cultural significance of tourist destinations. The Storytelling Department can also customize the content of the storytelling based on themes that tourists are interested in. For example, they can provide stories about historical figures or events that tourists are interested in. Furthermore, the Storytelling Department can provide tourists with immersive storytelling through audio guides and video content. For example, they can provide videos recreating historical events at tourist destinations or footage of cultural events. The Storytelling Department also provides interactive features that allow tourists to create their own stories. For example, tourists can upload photos and videos of places they have visited and create original stories based on them. This allows tourists to gain a deeper understanding of the region's history and culture through their own experiences. Furthermore, the Storytelling Department can provide more in-depth information through interviews with local residents and experts. For example, interviews with experts knowledgeable about the region's history and culture can be recorded and shared with tourists. Furthermore, the charm and stories of tourist destinations can be introduced through dialogues with local residents. In this way, the storytelling department can foster a deeper understanding of the region's history and culture among tourists, enriching their travel experience.

[0034] The information desk can guide visitors to the sights and recommended tourist spots of a tourist destination. For example, it can guide visitors to popular spots, historical sites, and cultural facilities. The information desk can display a map of the tourist destination and indicate places that tourists should visit. The information desk can also provide detailed information such as event information and opening hours of the tourist destination. For example, the information desk can display an event calendar of the tourist destination and guide tourists to events they can participate in. This improves tourist satisfaction by guiding them to the sights and recommended tourist spots of the tourist destination. Some or all of the above processing in the information desk may be performed using AI, for example, or not using AI. For example, the information desk can input map data of the tourist destination into a generating AI and have the generating AI perform the task of providing information on tourist spots.

[0035] The translation unit can provide tourist information in multiple languages. For example, the translation unit can provide tourist information in multiple languages ​​such as English, Chinese, and French. The translation unit can automatically translate tourist information according to the language used by tourists. In addition, the translation unit can appropriately translate proper nouns such as technical terms and place names in order to accurately translate the content of the tourist information. For example, the translation unit can accurately translate the names of tourist attractions and historical buildings. This eliminates language barriers by providing tourist information in multiple languages. Some or all of the above processing in the translation unit may be performed using AI, for example, or not using AI. For example, the translation unit can input the text data of the tourist information into a generating AI and have the generating AI perform multilingual translation.

[0036] The suggestion unit can propose the optimal sightseeing route based on the tourist's preferences and interests. For example, the suggestion unit can propose a sightseeing route based on themes that the tourist is interested in. The suggestion unit can analyze the tourist's past visit history and current interests to propose the optimal sightseeing route. For example, the suggestion unit can customize the sightseeing route based on places the tourist has visited in the past and themes that the tourist is interested in. The suggestion unit can also adjust the sightseeing route according to the tourist's schedule and length of stay. For example, if the tourist has a short stay, the suggestion unit will prioritize showing them major tourist spots. This improves tourist satisfaction by proposing the optimal sightseeing route based on the tourist's preferences and interests. Some or all of the above processing in the suggestion unit may be performed using AI, for example, or not using AI. For example, the suggestion unit can input tourist interest data into a generating AI and have the generating AI propose the optimal sightseeing route.

[0037] The storytelling unit can provide detailed information about the history and culture of the places tourists visit. For example, the storytelling unit can provide detailed information about the history and culture of the places tourists visit. The storytelling unit can provide background information and anecdotes about the places tourists visit. For example, the storytelling unit can tell stories about historical events and cultural significance of the tourist destination. The storytelling unit can also customize the content of the storytelling based on themes that tourists are interested in. For example, the storytelling unit can provide stories about historical figures and events that tourists are interested in. This deepens the tourist's understanding by providing detailed information about the history and culture of the places they visit. Some or all of the above processes in the storytelling unit may be performed using AI, for example, or not using AI. For example, the storytelling unit can input historical data of the tourist destination into a generating AI and have the generating AI execute the storytelling content.

[0038] The information desk can analyze a tourist's past visit history and select the most appropriate guidance method. For example, the information desk can suggest similar tourist spots based on data of places the tourist has visited in the past. The information desk can also suggest sightseeing routes that include similar activities based on activities the tourist has enjoyed in the past. Furthermore, the information desk can consider the congestion levels of places the tourist has visited in the past and suggest routes that avoid congestion. In this way, more appropriate guidance becomes possible by analyzing the tourist's past visit history. Some or all of the above processing in the information desk may be performed using AI, for example, or not using AI. For example, the information desk can input the tourist's visit history data into a generating AI and have the generating AI select the most appropriate guidance method.

[0039] The information desk can filter information based on the tourist's current length of stay and schedule. For example, if the tourist has a short stay, the information desk will only guide them to major tourist spots. If the tourist has ample time in their schedule, the information desk can suggest a leisurely sightseeing route. The information desk can also guide tourists to the most suitable tourist spots for each time of day, according to their schedule. This allows for more appropriate guidance by adjusting the information according to the tourist's length of stay and schedule. Some or all of the above processing in the information desk may be performed using AI, for example, or not. For example, the information desk can input tourist schedule data into a generating AI and have the generating AI perform the filtering.

[0040] The guidance system can prioritize guiding tourists to highly relevant spots by considering their geographical location. For example, it can prioritize guiding tourists to tourist spots close to their current location. If a tourist is in a specific area, it can prioritize guiding tourists to tourist spots within that area. Furthermore, if a tourist is on the move, it can prioritize guiding tourists to tourist spots along their travel route. This allows for more appropriate guidance by considering the tourist's geographical location. Some or all of the above processing in the guidance system may be performed using AI, for example, or without AI. For example, the guidance system can input the tourist's geographical location data into a generating AI and have the generating AI guide tourists to highly relevant spots.

[0041] The information desk can analyze tourists' social media activity and guide them to relevant spots. For example, it can guide tourists to relevant tourist spots based on places they have shared on social media. It can also analyze posts from accounts that tourists follow on social media and guide them to spots that might interest them. Furthermore, it can guide tourists to nearby tourist spots based on places they have checked in to on social media. This allows for more appropriate guidance by analyzing tourists' social media activity. Some or all of the above processing in the information desk may be performed using AI, for example, or not. For example, the information desk can input tourists' social media data into a generating AI and have the generating AI generate guidance to relevant spots.

[0042] The translation unit can adjust the level of detail in the translation based on the importance of the tourist information. For example, the translation unit can translate information about important tourist spots in detail, while translating information about general tourist spots concisely. Furthermore, the translation unit can quickly translate emergency information, providing only the essential details. This allows for more appropriate translations by adjusting the level of detail based on the importance of the tourist information. Some or all of the above processing in the translation unit may be performed using AI, for example, or not. For example, the translation unit can input tourist information importance data into a generating AI and have the generating AI perform the adjustment of the level of detail in the translation.

[0043] The translation unit can apply different translation algorithms depending on the category of the tourist information during translation. For example, the translation unit can apply a translation algorithm that includes specialized terminology to guides to historical tourist spots. For guides to natural tourist spots, it can apply a translation algorithm that is concise and easy to understand. Furthermore, for guides to shopping spots, it can apply an algorithm that accurately translates product names and prices. By applying different translation algorithms depending on the category of tourist information, more appropriate translations can be achieved. Some or all of the above processing in the translation unit may be performed using AI, for example, or not using AI. For example, the translation unit can input tourist information category data into a generating AI and have the generating AI perform the application of translation algorithms.

[0044] The translation department can prioritize translations based on the timing of tourist information submissions. For example, the department might prioritize translating emergency information. It might also prioritize translating information about important tourist spots. Furthermore, it might postpone translating information about general tourist spots. This allows for more accurate translations by prioritizing translations based on the timing of tourist information submissions. Some or all of the above processing in the translation department may be performed using AI, for example, or not. For example, the translation department could input tourist information submission timing data into a generating AI and have the generating AI determine the translation priorities.

[0045] The translation unit can adjust the order of translations based on the relevance of the tourist information during the translation process. For example, the translation unit can prioritize translating information about tourist spots close to the tourist's current location. It can also prioritize translating information about tourist spots that the tourist has shown interest in. Furthermore, it can prioritize translating information about tourist spots that the tourist plans to visit. By adjusting the order of translations based on the relevance of the tourist information, more appropriate translations can be achieved. Some or all of the above processing in the translation unit may be performed using AI, for example, or not using AI. For example, the translation unit can input the relevance data of the tourist information into a generating AI and have the generating AI perform the adjustment of the translation order.

[0046] The suggestion unit can adjust the level of detail in its suggestions based on the importance of the tourist route. For example, it can suggest routes to important tourist spots in detail, while suggesting routes to common tourist spots concisely. It can also quickly suggest emergency routes and provide only the minimum necessary information. By adjusting the level of detail in suggestions based on the importance of the tourist route, more appropriate suggestions can be made. Some or all of the above processing in the suggestion unit may be performed using AI, for example, or not. For example, the suggestion unit can input tourist route importance data into a generating AI and have the generating AI perform the adjustment of the level of detail in the suggestions.

[0047] The suggestion unit can apply different suggestion algorithms depending on the category of the tourist route when making suggestions. For example, the suggestion unit can apply a suggestion algorithm that includes specialized terminology to routes of historical tourist spots. For routes of natural tourist spots, it can apply a suggestion algorithm that is concise and easy to understand. Furthermore, for routes of shopping spots, the suggestion unit can apply an algorithm that accurately suggests product names and prices. By applying different suggestion algorithms depending on the category of the tourist route, more appropriate suggestions can be made. Some or all of the above processing in the suggestion unit may be performed using AI, for example, or without AI. For example, the suggestion unit can input tourist route category data into a generating AI and have the generating AI execute the application of the suggestion algorithm.

[0048] The proposal department can determine the priority of proposals based on the timing of tourist route submissions. For example, the proposal department can prioritize emergency routes. It can also prioritize routes to important tourist spots. Furthermore, it can postpone the proposal of routes to general tourist spots. This allows for more appropriate proposals by prioritizing proposals based on the timing of tourist route submissions. Some or all of the above processing in the proposal department may be performed using AI, for example, or not. For example, the proposal department can input tourist route submission timing data into a generating AI and have the generating AI determine the priority of proposals.

[0049] The suggestion unit can adjust the order of suggestions based on the relevance of tourist routes. For example, the suggestion unit can prioritize suggesting routes to tourist spots close to the tourist's current location. It can also prioritize suggesting routes to tourist spots that the tourist has shown interest in. Furthermore, it can prioritize suggesting routes to tourist spots that the tourist plans to visit. By adjusting the order of suggestions based on the relevance of tourist routes, more appropriate suggestions can be made. Some or all of the above processing in the suggestion unit may be performed using AI, for example, or without AI. For example, the suggestion unit can input tourist route relevance data into a generating AI and have the generating AI perform the adjustment of the suggestion order.

[0050] The storytelling unit can select the optimal storytelling method by referring to the tourist's past visit history during storytelling. For example, the storytelling unit can create a story that includes relevant episodes based on data of places the tourist has visited in the past. The storytelling unit can create relevant storytelling based on themes the tourist has shown interest in in the past. The storytelling unit can also create a story that relates to the history and culture of places the tourist has visited in the past. This makes it possible to create more appropriate storytelling by referring to the tourist's past visit history. Some or all of the above processing in the storytelling unit may be performed using AI, for example, or not using AI. For example, the storytelling unit can input the tourist's visit history data into a generating AI and have the generating AI select the optimal storytelling method.

[0051] The storytelling unit can customize the content of the storytelling based on the tourist's current interests and concerns. For example, the storytelling unit can create relevant storytelling based on themes the tourist is currently interested in. The storytelling unit can create storytelling related to events or activities the tourist is currently interested in. Furthermore, the storytelling unit can create customized storytelling based on specific characteristics of the place the tourist is currently visiting. This allows for more appropriate storytelling by customizing the content based on the tourist's current interests and concerns. Some or all of the above processes in the storytelling unit may be performed using AI, for example, or not. For example, the storytelling unit can input tourist interest data into a generating AI and have the generating AI customize the content of the storytelling.

[0052] The storytelling unit can select the optimal storytelling method by considering the tourist's geographical location information during storytelling. For example, the storytelling unit can tell stories related to the history and culture of the place where the tourist is currently located. If the tourist is on the move, the storytelling unit can tell stories related to tourist spots along the travel route. Furthermore, if the tourist is in a specific area, the storytelling unit can tell stories related to tourist spots within that area. This allows for more appropriate storytelling by considering the tourist's geographical location information. Some or all of the above processing in the storytelling unit may be performed using AI, for example, or without AI. For example, the storytelling unit can input the tourist's geographical location data into a generating AI and have the generating AI select the optimal storytelling method.

[0053] The storytelling unit can analyze tourists' social media activity during storytelling and suggest story content. For example, the storytelling unit can tell stories related to places that tourists have shared on social media. The storytelling unit can analyze posts from accounts that tourists follow on social media and tell stories that are likely to be of interest to them. The storytelling unit can also tell stories related to places that tourists have checked in to on social media. This allows for more appropriate storytelling by analyzing tourists' social media activity. Some or all of the above processing in the storytelling unit may be performed using AI, for example, or not. For example, the storytelling unit can input tourists' social media data into a generating AI and have the generating AI suggest story content.

[0054] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0055] A tourist guide system can analyze a tourist's past visit history and suggest the optimal sightseeing route. For example, it can suggest similar tourist spots based on data from places a tourist has visited in the past. It can also suggest sightseeing routes that include similar activities based on activities a tourist has enjoyed in the past. Furthermore, it can consider the congestion levels of places a tourist has visited in the past and suggest routes that avoid crowds. In this way, it can utilize a tourist's past visit history to suggest more appropriate sightseeing routes.

[0056] The tourist guide system can tailor tours based on tourists' current length of stay and schedules. For example, if tourists have limited time, it can guide them to only the main attractions. If tourists have more time, it can suggest a more leisurely sightseeing route. Furthermore, it can guide tourists to the most suitable attractions for each time of day, according to their schedule. This allows for optimal tourist guidance tailored to each tourist's length of stay and schedule.

[0057] The tourist guide system can prioritize highly relevant spots by considering the tourist's geographical location. For example, it can prioritize tourist attractions close to the tourist's current location. Furthermore, if the tourist is in a specific area, it can prioritize attractions within that area. Additionally, if the tourist is on the move, it can prioritize attractions along their travel route. This enables optimal tourist guidance that takes the tourist's geographical location into account.

[0058] The tourist guide system can analyze tourists' social media activity and guide them to relevant spots. For example, it can guide tourists to relevant tourist spots based on places they have shared on social media. It can also analyze posts from accounts tourists follow on social media and guide them to places they might be interested in. Furthermore, it can guide tourists to nearby tourist spots based on places they have checked in to on social media. This enables optimal tourist guidance that leverages tourists' social media activity.

[0059] The tourist guide system can adjust the level of detail in translations based on the importance of the tourist information. For example, information about important tourist spots can be translated in detail, while information about general tourist spots can be translated concisely. Furthermore, emergency information can be translated quickly, providing only the essential information. This enables optimal translation based on the importance of the tourist information.

[0060] The tourist guide system can apply different translation algorithms depending on the category of tourist information. For example, a translation algorithm that includes specialized terminology can be applied to guides to historical sites. A concise and easy-to-understand translation algorithm can be applied to guides to natural attractions. Furthermore, an algorithm that accurately translates product names and prices can be applied to guides to shopping spots. This allows for optimal translation tailored to each category of tourist information.

[0061] The tourist guide system can adjust the level of detail in its suggestions based on the importance of each tourist route. For example, routes to important tourist spots can be suggested in detail, while routes to more common tourist spots can be suggested concisely. Furthermore, emergency routes can be suggested quickly, providing only the essential information. This allows for optimal suggestions based on the importance of each tourist route.

[0062] The following briefly describes the processing flow for example form 1.

[0063] Step 1: The information desk provides tourist information. For example, it provides information on the highlights and recommended tourist spots of the area, displays a map of the area to show places tourists should visit. It can also provide detailed information such as event information and opening hours of the tourist area. Step 2: The translation department performs real-time multilingual translation. For example, it provides tourist information in multiple languages ​​and automatically translates it according to the language used by the tourist. It supports multiple languages ​​such as English, Chinese, and French, and accurately translates the names of tourist attractions and historical buildings. Step 3: The suggestion department proposes personalized sightseeing routes based on the tourist's preferences and interests. For example, it analyzes the tourist's past visit history and current interests to suggest the optimal sightseeing route. It can also adjust the sightseeing route according to the tourist's schedule and length of stay. Step 4: The storytelling team will conduct storytelling sessions about the local history and culture. For example, they will provide detailed explanations of the history and culture of the places tourists visit, offering background information and anecdotes. The content of the storytelling can also be customized based on themes that tourists are interested in.

[0064] (Example of form 2) The tourist guide system according to an embodiment of the present invention is a system for solving the shortage of tourist guides. This tourist guide system provides tourist information at any time when tourists need it, through an AI agent. The tourist guide system performs real-time multilingual translation and proposes personalized tourist routes based on the tourist's preferences and interests. Furthermore, the tourist guide system tells stories about the history and culture of the region. This mechanism can solve the problems faced by local governments and tourist facility operators in tourist areas, foreign tourists visiting Japan, and domestic travelers, such as the shortage of guide personnel, language barriers, and the inability to fully convey the charm of the region. For example, when a tourist arrives at a tourist destination, the tourist guide system will guide them to the highlights and recommended tourist spots. This allows tourists to enjoy the tourist destination even without a guide. Next, the tourist guide system performs real-time multilingual translation to eliminate language barriers. For example, even if a tourist does not understand Japanese, the tourist guide system will provide tourist information in multiple languages, allowing the tourist to enjoy sightseeing without feeling a language barrier. Furthermore, the tourist guide system proposes personalized tourist routes based on the tourist's preferences and interests. For example, if a tourist is interested in historical buildings, the tourist guide system will propose a route that visits historical buildings best suited to that tourist. This allows tourists to enjoy sightseeing tailored to their interests. Finally, the tourist guide system tells stories about the region's history and culture, fully conveying its charm. For example, by having the tourist guide system explain the history and culture of a place a tourist visits in detail, the tourist can gain a deeper understanding of the place's appeal. This system can solve the problems faced by local governments, tourist facility operators, foreign tourists visiting Japan, and domestic travelers, such as a shortage of guides, language barriers, and the inability to fully convey the charm of a region. Furthermore, by utilizing the tourist guide system, it is expected that the market size of the tourism industry will expand and inbound tourism spending will increase. Moreover, as AI technology matures, more advanced tourist guidance, multilingual translation, personalized sightseeing route suggestions, and storytelling will become possible, further improving tourist satisfaction.This allows the tourist guide system to improve tourist satisfaction.

[0065] The tourist guide system according to this embodiment comprises an information unit, a translation unit, a suggestion unit, and a storytelling unit. The information unit provides tourist information. For example, the information unit guides users to the highlights and recommended tourist spots of a tourist destination. The information unit can guide users to popular spots, historical sites, cultural facilities, etc. of a tourist destination. For example, the information unit displays a map of the tourist destination and indicates spots that tourists should visit. The information unit can also provide detailed information such as event information and opening hours of the tourist destination. For example, the information unit displays an event calendar of the tourist destination and guides tourists to events they can participate in. The translation unit performs real-time multilingual translation. For example, the translation unit provides tourist information in multiple languages. The translation unit can automatically translate tourist information according to the language used by the tourist. For example, the translation unit supports multiple languages ​​such as English, Chinese, and French. In addition, the translation unit can appropriately translate technical terms and proper nouns such as place names in order to accurately translate the content of the tourist information. For example, the translation unit can accurately translate the names of tourist destinations and historical buildings. The suggestion department proposes personalized sightseeing routes based on tourists' preferences and interests. For example, the suggestion department proposes routes based on themes that tourists are interested in. The suggestion department can analyze tourists' past visit history and current interests to propose the optimal sightseeing route. For example, the suggestion department customizes sightseeing routes based on places tourists have visited in the past and themes that tourists are interested in. The suggestion department can also adjust sightseeing routes according to tourists' schedules and length of stay. For example, if tourists have a short stay, the suggestion department will prioritize showing them major tourist attractions. The storytelling department provides storytelling about the history and culture of the region. For example, the storytelling department provides detailed explanations of the history and culture of the places tourists have visited. The storytelling department can provide background information and anecdotes about the places tourists have visited. For example, the storytelling department tells stories about historical events and cultural significance of tourist destinations. The storytelling department can also customize the content of the storytelling based on themes that tourists are interested in.For example, the storytelling section provides stories about historical figures and events that are of interest to tourists. This allows the tourist guide system according to this embodiment to improve tourist satisfaction.

[0066] The information desk provides tourist information. For example, it can guide visitors to the highlights and recommended tourist spots of a tourist destination. Specifically, it can provide information on popular spots, historical sites, and cultural facilities. For example, the information desk can display a map of the tourist destination and indicate the places tourists should visit. The information desk can also provide detailed information such as event information and opening hours of tourist destinations. For example, the information desk can display an event calendar of the tourist destination and guide tourists to events they can participate in. Furthermore, the information desk can provide information on access to tourist destinations and transportation options. For example, it can provide directions from the nearest train station or bus stop to the tourist destination and timetables for available transportation options. The information desk can also provide information on restaurants and accommodations around the tourist destination. For example, it can provide information on recommended menus and opening hours of restaurants and cafes around the tourist destination, as well as accommodation rates and availability. This allows tourists to obtain all the necessary information for visiting a tourist destination at once and enjoy their sightseeing smoothly. Furthermore, the information desk can also provide photos and videos of tourist destinations. For example, the information desk can display photos of beautiful scenery and historical buildings in tourist areas, as well as videos of events, to attract tourists' interest. The information desk can also display reviews and comments about tourist destinations. For instance, it can show ratings and impressions posted by other tourists, which can be used as a reference when planning a visit. This allows the information desk to provide tourists with comprehensive information and convey the charm of the tourist destination to its fullest potential.

[0067] The translation department provides real-time multilingual translation. For example, it can provide tourist information in multiple languages. Specifically, it can automatically translate tourist information according to the language used by the tourist. For example, the translation department supports multiple languages ​​such as English, Chinese, and French. Furthermore, to ensure accurate translation of tourist information, the translation department can appropriately translate technical terms and proper nouns such as place names. For example, it accurately translates the names of tourist attractions and historical buildings. In addition, the translation department can translate questions asked by tourists in real time and provide tourist information. For example, if a tourist enters a question using a smartphone or tablet, the translation department automatically translates the question and provides an appropriate answer. The translation department can also use speech recognition technology to convert tourists' voices into text and translate them. For example, if a tourist asks a question by voice, the translation department converts the voice into text, translates it, and provides an answer. This allows tourists to receive tourist information smoothly without experiencing language barriers. Furthermore, the translation department can also translate the content of signs and brochures at tourist attractions. For example, if a tourist takes a photo of the content of an information board at a tourist spot with their smartphone, the translation unit will automatically translate the content and display it to the tourist. It can also translate the content of brochures distributed at tourist spots and provide it in a format that is easy for tourists to understand. In this way, the translation unit can provide tourists with multilingual tourist information, making their experience at tourist destinations more fulfilling.

[0068] The suggestion department proposes personalized sightseeing routes based on tourists' preferences and interests. For example, it suggests routes based on themes that tourists are interested in. Specifically, it can analyze tourists' past visit history and current interests to propose the optimal sightseeing route. For example, the suggestion department customizes sightseeing routes based on places tourists have visited in the past and themes they are interested in. The suggestion department can also adjust sightseeing routes according to tourists' schedules and length of stay. For example, if tourists have a short stay, it will prioritize showing them major tourist spots. Furthermore, the suggestion department can optimize sightseeing routes according to tourists' means of transportation and physical ability. For example, for tourists who have difficulty traveling on foot, it will suggest routes using public transport or taxis. The suggestion department can also suggest restaurants and cafes, taking into account tourists' dietary preferences and allergy information. For example, it will suggest restaurants that offer vegetarian menus to vegetarian tourists. In this way, the suggestion department can provide a personalized sightseeing experience tailored to the needs of each individual tourist. Furthermore, the suggestion department can collect real-time feedback from tourists and continuously improve its suggestions. For example, the department can collect ratings and feedback from tourists about the places they visited and the activities they experienced, and incorporate this into future recommendations. The department can also analyze tourists' social media posts and review site information to understand the latest trends and popular spots. This allows the department to consistently propose optimal sightseeing routes based on the most up-to-date information, thereby improving tourist satisfaction.

[0069] The Storytelling Department conducts storytelling about the history and culture of the region. For example, the Storytelling Department can provide detailed explanations of the history and culture of places that tourists visit. Specifically, they can provide background information and anecdotes about the places tourists visit. For example, the Storytelling Department can tell stories about historical events and cultural significance of tourist destinations. The Storytelling Department can also customize the content of the storytelling based on themes that tourists are interested in. For example, they can provide stories about historical figures or events that tourists are interested in. Furthermore, the Storytelling Department can provide tourists with immersive storytelling through audio guides and video content. For example, they can provide videos recreating historical events at tourist destinations or footage of cultural events. The Storytelling Department also provides interactive features that allow tourists to create their own stories. For example, tourists can upload photos and videos of places they have visited and create original stories based on them. This allows tourists to gain a deeper understanding of the region's history and culture through their own experiences. Furthermore, the Storytelling Department can provide more in-depth information through interviews with local residents and experts. For example, interviews with experts knowledgeable about the region's history and culture can be recorded and shared with tourists. Furthermore, the charm and stories of tourist destinations can be introduced through dialogues with local residents. In this way, the storytelling department can foster a deeper understanding of the region's history and culture among tourists, enriching their travel experience.

[0070] The information desk can guide visitors to the sights and recommended tourist spots of a tourist destination. For example, it can guide visitors to popular spots, historical sites, and cultural facilities. The information desk can display a map of the tourist destination and indicate places that tourists should visit. The information desk can also provide detailed information such as event information and opening hours of the tourist destination. For example, the information desk can display an event calendar of the tourist destination and guide tourists to events they can participate in. This improves tourist satisfaction by guiding them to the sights and recommended tourist spots of the tourist destination. Some or all of the above processing in the information desk may be performed using AI, for example, or not using AI. For example, the information desk can input map data of the tourist destination into a generating AI and have the generating AI perform the task of providing information on tourist spots.

[0071] The translation unit can provide tourist information in multiple languages. For example, the translation unit can provide tourist information in multiple languages ​​such as English, Chinese, and French. The translation unit can automatically translate tourist information according to the language used by tourists. In addition, the translation unit can appropriately translate proper nouns such as technical terms and place names in order to accurately translate the content of the tourist information. For example, the translation unit can accurately translate the names of tourist attractions and historical buildings. This eliminates language barriers by providing tourist information in multiple languages. Some or all of the above processing in the translation unit may be performed using AI, for example, or not using AI. For example, the translation unit can input the text data of the tourist information into a generating AI and have the generating AI perform multilingual translation.

[0072] The suggestion unit can propose the optimal sightseeing route based on the tourist's preferences and interests. For example, the suggestion unit can propose a sightseeing route based on themes that the tourist is interested in. The suggestion unit can analyze the tourist's past visit history and current interests to propose the optimal sightseeing route. For example, the suggestion unit can customize the sightseeing route based on places the tourist has visited in the past and themes that the tourist is interested in. The suggestion unit can also adjust the sightseeing route according to the tourist's schedule and length of stay. For example, if the tourist has a short stay, the suggestion unit will prioritize showing them major tourist spots. This improves tourist satisfaction by proposing the optimal sightseeing route based on the tourist's preferences and interests. Some or all of the above processing in the suggestion unit may be performed using AI, for example, or not using AI. For example, the suggestion unit can input tourist interest data into a generating AI and have the generating AI propose the optimal sightseeing route.

[0073] The storytelling unit can provide detailed information about the history and culture of the places tourists visit. For example, the storytelling unit can provide detailed information about the history and culture of the places tourists visit. The storytelling unit can provide background information and anecdotes about the places tourists visit. For example, the storytelling unit can tell stories about historical events and cultural significance of the tourist destination. The storytelling unit can also customize the content of the storytelling based on themes that tourists are interested in. For example, the storytelling unit can provide stories about historical figures and events that tourists are interested in. This deepens the tourist's understanding by providing detailed information about the history and culture of the places they visit. Some or all of the above processes in the storytelling unit may be performed using AI, for example, or not using AI. For example, the storytelling unit can input historical data of the tourist destination into a generating AI and have the generating AI execute the storytelling content.

[0074] The guidance system can estimate the emotions of tourists and adjust the timing of guidance based on those emotions. For example, if a tourist is tired, the guidance system can guide them to a rest spot and suggest a time to resume sightseeing after they have refreshed themselves. If a tourist is excited, the guidance system can immediately guide them to the next sightseeing spot to maintain their excitement. Furthermore, if a tourist is lost, the guidance system can immediately check their current location and guide them to the optimal route. This allows for more appropriate guidance by adjusting the timing of guidance according to the tourist's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above-described processes in the guidance system may be performed using AI, or not. For example, the guidance system can input tourist emotion data into a generative AI and have the generative AI adjust the timing of guidance.

[0075] The information desk can analyze a tourist's past visit history and select the most appropriate guidance method. For example, the information desk can suggest similar tourist spots based on data of places the tourist has visited in the past. The information desk can also suggest sightseeing routes that include similar activities based on activities the tourist has enjoyed in the past. Furthermore, the information desk can consider the congestion levels of places the tourist has visited in the past and suggest routes that avoid congestion. In this way, more appropriate guidance becomes possible by analyzing the tourist's past visit history. Some or all of the above processing in the information desk may be performed using AI, for example, or not using AI. For example, the information desk can input the tourist's visit history data into a generating AI and have the generating AI select the most appropriate guidance method.

[0076] The information desk can filter information based on the tourist's current length of stay and schedule. For example, if the tourist has a short stay, the information desk will only guide them to major tourist spots. If the tourist has ample time in their schedule, the information desk can suggest a leisurely sightseeing route. The information desk can also guide tourists to the most suitable tourist spots for each time of day, according to their schedule. This allows for more appropriate guidance by adjusting the information according to the tourist's length of stay and schedule. Some or all of the above processing in the information desk may be performed using AI, for example, or not. For example, the information desk can input tourist schedule data into a generating AI and have the generating AI perform the filtering.

[0077] The information desk can estimate the emotions of tourists and determine the priority of sightseeing spots to guide them to based on the estimated emotions. For example, if a tourist is excited, the information desk can prioritize sightseeing spots that include active activities. If a tourist is relaxed, the information desk can prioritize quiet places or spots where they can enjoy nature. Also, if a tourist is tired, the information desk can prioritize places where they can rest. This allows for more appropriate guidance by prioritizing sightseeing spots according to the emotions of tourists. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the information desk may be performed using AI, for example, or not using AI. For example, the information desk can input tourist emotion data into a generative AI and have the generative AI perform the determination of sightseeing spot priorities.

[0078] The guidance system can prioritize guiding tourists to highly relevant spots by considering their geographical location. For example, it can prioritize guiding tourists to tourist spots close to their current location. If a tourist is in a specific area, it can prioritize guiding tourists to tourist spots within that area. Furthermore, if a tourist is on the move, it can prioritize guiding tourists to tourist spots along their travel route. This allows for more appropriate guidance by considering the tourist's geographical location. Some or all of the above processing in the guidance system may be performed using AI, for example, or without AI. For example, the guidance system can input the tourist's geographical location data into a generating AI and have the generating AI guide tourists to highly relevant spots.

[0079] The information desk can analyze tourists' social media activity and guide them to relevant spots. For example, it can guide tourists to relevant tourist spots based on places they have shared on social media. It can also analyze posts from accounts that tourists follow on social media and guide them to spots that might interest them. Furthermore, it can guide tourists to nearby tourist spots based on places they have checked in to on social media. This allows for more appropriate guidance by analyzing tourists' social media activity. Some or all of the above processing in the information desk may be performed using AI, for example, or not. For example, the information desk can input tourists' social media data into a generating AI and have the generating AI generate guidance to relevant spots.

[0080] The translation unit can estimate the emotions of tourists and adjust the translation's expression based on the estimated emotions. For example, if a tourist is nervous, the translation unit will use concise and easy-to-understand language. If a tourist is relaxed, the translation unit can use language that includes detailed explanations. Furthermore, if a tourist is excited, the translation unit can use language that enhances the emotions. This allows for more appropriate translations by adjusting the translation's expression according to the tourist's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the translation unit may be performed using AI, or not. For example, the translation unit can input tourist emotion data into a generative AI and have the generative AI adjust the translation's expression.

[0081] The translation unit can adjust the level of detail in the translation based on the importance of the tourist information. For example, the translation unit can translate information about important tourist spots in detail, while translating information about general tourist spots concisely. Furthermore, the translation unit can quickly translate emergency information, providing only the essential details. This allows for more appropriate translations by adjusting the level of detail based on the importance of the tourist information. Some or all of the above processing in the translation unit may be performed using AI, for example, or not. For example, the translation unit can input tourist information importance data into a generating AI and have the generating AI perform the adjustment of the level of detail in the translation.

[0082] The translation unit can apply different translation algorithms depending on the category of the tourist information during translation. For example, the translation unit can apply a translation algorithm that includes specialized terminology to guides to historical tourist spots. For guides to natural tourist spots, it can apply a translation algorithm that is concise and easy to understand. Furthermore, for guides to shopping spots, it can apply an algorithm that accurately translates product names and prices. By applying different translation algorithms depending on the category of tourist information, more appropriate translations can be achieved. Some or all of the above processing in the translation unit may be performed using AI, for example, or not using AI. For example, the translation unit can input tourist information category data into a generating AI and have the generating AI perform the application of translation algorithms.

[0083] The translation unit can estimate the tourist's emotions and adjust the translation length based on the estimated emotions. For example, if the tourist is in a hurry, the translation unit can provide a short, concise translation. If the tourist is relaxed, the translation unit can provide a longer translation that includes detailed explanations. Furthermore, if the tourist is excited, the translation unit can provide a longer, more emotionally charged translation. By adjusting the translation length according to the tourist's emotions, a more appropriate translation becomes possible. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the translation unit may be performed using AI or not. For example, the translation unit can input tourist emotion data into a generative AI and have the generative AI adjust the translation length.

[0084] The translation department can prioritize translations based on the timing of tourist information submissions. For example, the department might prioritize translating emergency information. It might also prioritize translating information about important tourist spots. Furthermore, it might postpone translating information about general tourist spots. This allows for more accurate translations by prioritizing translations based on the timing of tourist information submissions. Some or all of the above processing in the translation department may be performed using AI, for example, or not. For example, the translation department could input tourist information submission timing data into a generating AI and have the generating AI determine the translation priorities.

[0085] The translation unit can adjust the order of translations based on the relevance of the tourist information during the translation process. For example, the translation unit can prioritize translating information about tourist spots close to the tourist's current location. It can also prioritize translating information about tourist spots that the tourist has shown interest in. Furthermore, it can prioritize translating information about tourist spots that the tourist plans to visit. By adjusting the order of translations based on the relevance of the tourist information, more appropriate translations can be achieved. Some or all of the above processing in the translation unit may be performed using AI, for example, or not using AI. For example, the translation unit can input the relevance data of the tourist information into a generating AI and have the generating AI perform the adjustment of the translation order.

[0086] The suggestion unit can estimate the tourist's emotions and adjust the way it presents its suggestions based on those emotions. For example, if the tourist is relaxed, the suggestion unit can present suggestions that proceed at a leisurely pace. If the tourist is in a hurry, the suggestion unit can present suggestions that emphasize the shortest route. If the tourist is excited, the suggestion unit can also present suggestions with visually stimulating effects. By adjusting the way suggestions are presented according to the tourist's emotions, more appropriate suggestions can be made. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI may be, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the suggestion unit may be performed using AI or not. For example, the suggestion unit can input tourist emotion data into a generative AI and have the generative AI adjust the way suggestions are presented.

[0087] The suggestion unit can adjust the level of detail in its suggestions based on the importance of the tourist route. For example, it can suggest routes to important tourist spots in detail, while suggesting routes to common tourist spots concisely. It can also quickly suggest emergency routes and provide only the minimum necessary information. By adjusting the level of detail in suggestions based on the importance of the tourist route, more appropriate suggestions can be made. Some or all of the above processing in the suggestion unit may be performed using AI, for example, or not. For example, the suggestion unit can input tourist route importance data into a generating AI and have the generating AI perform the adjustment of the level of detail in the suggestions.

[0088] The suggestion unit can apply different suggestion algorithms depending on the category of the tourist route when making suggestions. For example, the suggestion unit can apply a suggestion algorithm that includes specialized terminology to routes of historical tourist spots. For routes of natural tourist spots, it can apply a suggestion algorithm that is concise and easy to understand. Furthermore, for routes of shopping spots, the suggestion unit can apply an algorithm that accurately suggests product names and prices. By applying different suggestion algorithms depending on the category of the tourist route, more appropriate suggestions can be made. Some or all of the above processing in the suggestion unit may be performed using AI, for example, or without AI. For example, the suggestion unit can input tourist route category data into a generating AI and have the generating AI execute the application of the suggestion algorithm.

[0089] The suggestion unit can estimate the tourist's emotions and adjust the length of the suggestion based on the estimated emotions. For example, if the tourist is in a hurry, the suggestion unit can provide a short, concise suggestion. If the tourist is relaxed, the suggestion unit can provide a longer suggestion with detailed explanations. If the tourist is excited, the suggestion unit can also provide a longer suggestion with visually stimulating effects. By adjusting the length of the suggestion according to the tourist's emotions, more appropriate suggestions can be made. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the suggestion unit may be performed using AI or not. For example, the suggestion unit can input tourist emotion data into a generative AI and have the generative AI adjust the length of the suggestion.

[0090] The proposal department can determine the priority of proposals based on the timing of tourist route submissions. For example, the proposal department can prioritize emergency routes. It can also prioritize routes to important tourist spots. Furthermore, it can postpone the proposal of routes to general tourist spots. This allows for more appropriate proposals by prioritizing proposals based on the timing of tourist route submissions. Some or all of the above processing in the proposal department may be performed using AI, for example, or not. For example, the proposal department can input tourist route submission timing data into a generating AI and have the generating AI determine the priority of proposals.

[0091] The suggestion unit can adjust the order of suggestions based on the relevance of tourist routes. For example, the suggestion unit can prioritize suggesting routes to tourist spots close to the tourist's current location. It can also prioritize suggesting routes to tourist spots that the tourist has shown interest in. Furthermore, it can prioritize suggesting routes to tourist spots that the tourist plans to visit. By adjusting the order of suggestions based on the relevance of tourist routes, more appropriate suggestions can be made. Some or all of the above processing in the suggestion unit may be performed using AI, for example, or without AI. For example, the suggestion unit can input tourist route relevance data into a generating AI and have the generating AI perform the adjustment of the suggestion order.

[0092] The storytelling unit can estimate the emotions of tourists and adjust the storytelling method based on the estimated emotions. For example, if a tourist is relaxed, the storytelling unit will proceed at a leisurely pace. If a tourist is in a hurry, the storytelling unit can perform a concise storytelling. Furthermore, if a tourist is excited, the storytelling unit can add visually stimulating effects to the storytelling. This allows for more appropriate storytelling by adjusting the storytelling method according to the tourist's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. The generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the storytelling unit may be performed using AI or not using AI. For example, the storytelling unit can input tourist emotion data into the generative AI and have the generative AI perform the adjustment of the storytelling method.

[0093] The storytelling unit can select the optimal storytelling method by referring to the tourist's past visit history during storytelling. For example, the storytelling unit can create a story that includes relevant episodes based on data of places the tourist has visited in the past. The storytelling unit can create relevant storytelling based on themes the tourist has shown interest in in the past. The storytelling unit can also create a story that relates to the history and culture of places the tourist has visited in the past. This makes it possible to create more appropriate storytelling by referring to the tourist's past visit history. Some or all of the above processing in the storytelling unit may be performed using AI, for example, or not using AI. For example, the storytelling unit can input the tourist's visit history data into a generating AI and have the generating AI select the optimal storytelling method.

[0094] The storytelling unit can customize the content of the storytelling based on the tourist's current interests and concerns. For example, the storytelling unit can create relevant storytelling based on themes the tourist is currently interested in. The storytelling unit can create storytelling related to events or activities the tourist is currently interested in. Furthermore, the storytelling unit can create customized storytelling based on specific characteristics of the place the tourist is currently visiting. This allows for more appropriate storytelling by customizing the content based on the tourist's current interests and concerns. Some or all of the above processes in the storytelling unit may be performed using AI, for example, or not. For example, the storytelling unit can input tourist interest data into a generating AI and have the generating AI customize the content of the storytelling.

[0095] The storytelling unit can estimate the emotions of tourists and determine the priority of storytelling based on the estimated emotions. For example, if a tourist is excited, the storytelling unit will prioritize telling episodes that evoke strong emotions. If a tourist is relaxed, the storytelling unit can prioritize telling episodes that proceed at a leisurely pace. Furthermore, if a tourist is tired, the storytelling unit can prioritize telling short, concise episodes. This allows for more appropriate storytelling by determining the priority of storytelling according to the tourist's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI. Some or all of the above processing in the storytelling unit may be performed using AI, or not using AI. For example, the storytelling unit can input tourist emotion data into a generative AI and have the generative AI determine the priority of storytelling.

[0096] The storytelling unit can select the optimal storytelling method by considering the tourist's geographical location information during storytelling. For example, the storytelling unit can tell stories related to the history and culture of the place where the tourist is currently located. If the tourist is on the move, the storytelling unit can tell stories related to tourist spots along the travel route. Furthermore, if the tourist is in a specific area, the storytelling unit can tell stories related to tourist spots within that area. This allows for more appropriate storytelling by considering the tourist's geographical location information. Some or all of the above processing in the storytelling unit may be performed using AI, for example, or without AI. For example, the storytelling unit can input the tourist's geographical location data into a generating AI and have the generating AI select the optimal storytelling method.

[0097] The storytelling unit can analyze tourists' social media activity during storytelling and suggest story content. For example, the storytelling unit can tell stories related to places that tourists have shared on social media. The storytelling unit can analyze posts from accounts that tourists follow on social media and tell stories that are likely to be of interest to them. The storytelling unit can also tell stories related to places that tourists have checked in to on social media. This allows for more appropriate storytelling by analyzing tourists' social media activity. Some or all of the above processing in the storytelling unit may be performed using AI, for example, or not. For example, the storytelling unit can input tourists' social media data into a generating AI and have the generating AI suggest story content.

[0098] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0099] A tourist guide system can estimate a tourist's emotions and adjust the content of the tour based on those emotions. For example, if a tourist is excited, the system can prioritize recommending active activities and events. If the tourist is relaxed, it can recommend quiet places or spots where they can enjoy nature. Furthermore, if the tourist is tired, it can recommend resting places or places where they can refresh themselves. This enables optimal tour guidance tailored to the tourist's emotions, thereby improving tourist satisfaction.

[0100] A tourist guide system can analyze a tourist's past visit history and suggest the optimal sightseeing route. For example, it can suggest similar tourist spots based on data from places a tourist has visited in the past. It can also suggest sightseeing routes that include similar activities based on activities a tourist has enjoyed in the past. Furthermore, it can consider the congestion levels of places a tourist has visited in the past and suggest routes that avoid crowds. In this way, it can utilize a tourist's past visit history to suggest more appropriate sightseeing routes.

[0101] The tourist guide system can tailor tours based on tourists' current length of stay and schedules. For example, if tourists have limited time, it can guide them to only the main attractions. If tourists have more time, it can suggest a more leisurely sightseeing route. Furthermore, it can guide tourists to the most suitable attractions for each time of day, according to their schedule. This allows for optimal tourist guidance tailored to each tourist's length of stay and schedule.

[0102] The tourist guide system can prioritize highly relevant spots by considering the tourist's geographical location. For example, it can prioritize tourist attractions close to the tourist's current location. Furthermore, if the tourist is in a specific area, it can prioritize attractions within that area. Additionally, if the tourist is on the move, it can prioritize attractions along their travel route. This enables optimal tourist guidance that takes the tourist's geographical location into account.

[0103] The tourist guide system can analyze tourists' social media activity and guide them to relevant spots. For example, it can guide tourists to relevant tourist spots based on places they have shared on social media. It can also analyze posts from accounts tourists follow on social media and guide them to places they might be interested in. Furthermore, it can guide tourists to nearby tourist spots based on places they have checked in to on social media. This enables optimal tourist guidance that leverages tourists' social media activity.

[0104] The tourist guide system can estimate the emotions of tourists and adjust the translation based on those emotions. For example, if a tourist is nervous, it can use concise and easy-to-understand language. If a tourist is relaxed, it can use language that includes detailed explanations. Furthermore, if a tourist is excited, it can use language that enhances their emotions. This enables optimal translation tailored to the tourist's emotions, thereby improving tourist satisfaction.

[0105] The tourist guide system can adjust the level of detail in translations based on the importance of the tourist information. For example, information about important tourist spots can be translated in detail, while information about general tourist spots can be translated concisely. Furthermore, emergency information can be translated quickly, providing only the essential information. This enables optimal translation based on the importance of the tourist information.

[0106] The tourist guide system can apply different translation algorithms depending on the category of tourist information. For example, a translation algorithm that includes specialized terminology can be applied to guides to historical sites. A concise and easy-to-understand translation algorithm can be applied to guides to natural attractions. Furthermore, an algorithm that accurately translates product names and prices can be applied to guides to shopping spots. This allows for optimal translation tailored to each category of tourist information.

[0107] The tourist guide system can estimate the emotions of tourists and adjust the way suggestions are presented based on those emotions. For example, if a tourist is relaxed, it can offer suggestions that proceed at a leisurely pace. If a tourist is in a hurry, it can emphasize the shortest route. Furthermore, if a tourist is excited, it can offer suggestions with visually stimulating effects. This allows for optimal suggestions tailored to the tourist's emotions, thereby improving tourist satisfaction.

[0108] The tourist guide system can adjust the level of detail in its suggestions based on the importance of each tourist route. For example, routes to important tourist spots can be suggested in detail, while routes to more common tourist spots can be suggested concisely. Furthermore, emergency routes can be suggested quickly, providing only the essential information. This allows for optimal suggestions based on the importance of each tourist route.

[0109] The following briefly describes the processing flow for example form 2.

[0110] Step 1: The information desk provides tourist information. For example, it provides information on the highlights and recommended tourist spots of the area, displays a map of the area to show places tourists should visit. It can also provide detailed information such as event information and opening hours of the tourist area. Step 2: The translation department performs real-time multilingual translation. For example, it provides tourist information in multiple languages ​​and automatically translates it according to the language used by the tourist. It supports multiple languages ​​such as English, Chinese, and French, and accurately translates the names of tourist attractions and historical buildings. Step 3: The suggestion department proposes personalized sightseeing routes based on the tourist's preferences and interests. For example, it analyzes the tourist's past visit history and current interests to suggest the optimal sightseeing route. It can also adjust the sightseeing route according to the tourist's schedule and length of stay. Step 4: The storytelling team will conduct storytelling sessions about the local history and culture. For example, they will provide detailed explanations of the history and culture of the places tourists visit, offering background information and anecdotes. The content of the storytelling can also be customized based on themes that tourists are interested in.

[0111] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0112] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0113] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, 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.

[0114] Each of the multiple elements described above, including the guidance unit, translation unit, suggestion unit, and storytelling unit, is implemented by at least one of the smart device 14 and the data processing unit 12. For example, the guidance unit is implemented by the control unit 46A of the smart device 14 and provides information on the sights and recommended tourist spots of the area. The translation unit is implemented by the specific processing unit 290 of the data processing unit 12 and performs real-time multilingual translation. The suggestion unit is implemented by the specific processing unit 290 of the data processing unit 12 and proposes personalized tourist routes based on the tourist's preferences and interests. The storytelling unit is implemented by the control unit 46A of the smart device 14 and performs storytelling about the history and culture of the region. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0115] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0116] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0117] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0118] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0119] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0120] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0121] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0122] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0123] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0124] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0125] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. 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 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0126] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0127] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0128] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0129] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0130] Each of the multiple elements described above, including the guidance unit, translation unit, suggestion unit, and storytelling unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the guidance unit is implemented by the control unit 46A of the smart glasses 214 and provides information on the sights and recommended tourist spots of the area. The translation unit is implemented by the specific processing unit 290 of the data processing unit 12 and performs real-time multilingual translation. The suggestion unit is implemented by the specific processing unit 290 of the data processing unit 12 and suggests personalized tourist routes based on the tourist's preferences and interests. The storytelling unit is implemented by the control unit 46A of the smart glasses 214 and tells stories about the history and culture of the region. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0131] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0132] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0133] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0134] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0135] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0136] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0137] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0138] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0139] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0140] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0141] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0142] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0143] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0144] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0145] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0146] Each of the multiple elements described above, including the guidance unit, translation unit, suggestion unit, and storytelling unit, is implemented by at least one of the headset terminal 314 and the data processing unit 12. For example, the guidance unit is implemented by the control unit 46A of the headset terminal 314 and provides information on the sights and recommended tourist spots of the area. The translation unit is implemented by the specific processing unit 290 of the data processing unit 12 and performs real-time multilingual translation. The suggestion unit is implemented by the specific processing unit 290 of the data processing unit 12 and proposes personalized tourist routes based on the tourist's preferences and interests. The storytelling unit is implemented by the control unit 46A of the headset terminal 314 and tells stories about the history and culture of the region. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0147] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0148] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0149] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0150] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0151] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0152] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0153] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0154] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0155] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0156] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0157] Storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0158] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0159] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0160] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0161] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0162] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0163] Each of the multiple elements described above, including the guidance unit, translation unit, suggestion unit, and storytelling unit, is implemented by, for example, at least one of the robot 414 and the data processing unit 12. For example, the guidance unit is implemented by the control unit 46A of the robot 414 and provides information on the sights and recommended tourist spots of the area. The translation unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and performs real-time multilingual translation. The suggestion unit is implemented by, for example, the specific processing unit 290 of the data processing unit 12 and proposes personalized tourist routes based on the tourist's preferences and interests. The storytelling unit is implemented by, for example, the control unit 46A of the robot 414 and tells stories about the history and culture of the region. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0164] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0165] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0166] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0167] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0168] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0169] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0170] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0171] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0172] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0173] 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.

[0174] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0175] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0176] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0177] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0178] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0179] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0180] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0181] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0182] (Note 1) The information desk provides tourist information, The translation department performs real-time multilingual translation, The proposal department suggests personalized sightseeing routes based on the preferences and interests of tourists, It includes a storytelling department that performs storytelling about the local history and culture. A system characterized by the following features. (Note 2) The aforementioned guide section is This guide will show you the highlights and recommended tourist spots in the area. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned translation department, Tourist information is provided in multiple languages. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned proposal section is, We suggest the optimal sightseeing route based on the preferences and interests of tourists. The system described in Appendix 1, characterized by the features described herein. (Note 5) The aforementioned storytelling section is, Provide detailed explanations about the history and culture of the places tourists visit. The system described in Appendix 1, characterized by the features described herein. (Note 6) The aforementioned guide section is The system estimates the emotions of tourists and adjusts the timing of the tour based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 7) The aforementioned guide section is Analyze tourists' past visit history to select the most suitable guidance method. The system described in Appendix 1, characterized by the features described herein. (Note 8) The aforementioned guide section is Filter based on tourists' current length of stay and schedule. The system described in Appendix 1, characterized by the features described herein. (Note 9) The aforementioned guide section is The system estimates the emotions of tourists and determines the priority of tourist attractions to guide them to based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The aforementioned guide section is The system prioritizes guiding tourists to highly relevant spots, taking into account their geographical location. The system described in Appendix 1, characterized by the features described herein. (Note 11) The aforementioned guide section is Analyze tourists' social media activity and guide them to relevant spots. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned translation department, The system estimates the emotions of tourists and adjusts the translation's expression based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned translation department, The level of detail in the translation is adjusted based on the importance of the tourist information during translation. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned translation department, Apply different translation algorithms during translation depending on the category of tourist information. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned translation department, Estimate the sentiment of tourists and adjust the translation length based on the estimated sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned translation department, When translating, prioritize translations based on the submission date of the tourist guide. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned translation department, The order of translations is adjusted based on the relevance of the tourist information during translation. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned proposal section is, We estimate the emotions of tourists and adjust the way we present our proposals based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned proposal section is, When making a proposal, adjust the level of detail based on the importance of the tourist route. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned proposal section is, When making suggestions, different suggestion algorithms are applied depending on the category of the tourist route. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned proposal section is, Estimate the sentiment of tourists and adjust the length of the suggestion based on the estimated sentiment. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned proposal section is, When submitting proposals, priority will be determined based on the timing of submission of the tourist routes. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned proposal section is, When making a proposal, adjust the order of suggestions based on the relevance of the tourist route. The system described in Appendix 1, characterized by the features described herein. (Note 24) The aforementioned storytelling section is, We estimate the emotions of tourists and adjust the storytelling method based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 25) The aforementioned storytelling section is, When storytelling, refer to the tourist's past visit history to select the most suitable storytelling method. The system described in Appendix 1, characterized by the features described herein. (Note 26) The aforementioned storytelling section is, During storytelling, customize the content of the story based on the tourists' current interests and concerns. The system described in Appendix 1, characterized by the features described herein. (Note 27) The aforementioned storytelling section is, Estimate the emotions of tourists and determine storytelling priorities based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The aforementioned storytelling section is, When storytelling, consider the geographical location of tourists to select the most suitable storytelling method. The system described in Appendix 1, characterized by the features described herein. (Note 29) The aforementioned storytelling section is, Analyze tourists' social media activity during storytelling to suggest content for the story. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0183] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. The information desk provides tourist information, The translation department performs real-time multilingual translation, The proposal department suggests personalized sightseeing routes based on the preferences and interests of tourists, It includes a storytelling department that performs storytelling about the local history and culture. A system characterized by the following features.

2. The aforementioned guide section is This guide will show you the highlights and recommended tourist spots in the area. The system according to feature 1.

3. The aforementioned translation department, Tourist information is provided in multiple languages. The system according to feature 1.

4. The aforementioned proposal section is, We suggest the optimal sightseeing route based on the preferences and interests of tourists. The system according to feature 1.

5. The aforementioned storytelling section is, Provide detailed explanations about the history and culture of the places tourists visit. The system according to feature 1.

6. The aforementioned guide section is The system estimates the emotions of tourists and adjusts the timing of the tour based on those estimated emotions. The system according to feature 1.

7. The aforementioned guide section is Analyze tourists' past visit history to select the most suitable guidance method. The system according to feature 1.

8. The aforementioned guide section is Filter based on tourists' current length of stay and schedule. The system according to feature 1.

9. The aforementioned guide section is The system estimates the emotions of tourists and determines the priority of tourist attractions to guide them to based on those estimated emotions. The system according to feature 1.

10. The aforementioned guide section is The system prioritizes guiding tourists to highly relevant spots, taking into account their geographical location. The system according to feature 1.

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