system

Abstract

The system according to the embodiment aims to foster respect for ancestors by enabling people to have conversations with their ancestors when visiting their graves. [Solution] The system according to the embodiment comprises a display unit, a face display unit, a dialogue unit, and a provision unit. The display unit displays a two-dimensional code when the grave is viewed with a smartphone camera. The face display unit reads the displayed two-dimensional code and displays the face of the person resting in the grave. When the dialogue unit speaks to the displayed face, a generation AI generates a reply. The provision unit provides the processing results of the dialogue unit to the user.

Description

[Technical Field]

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

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

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

[0004] Conventional technology does not provide a means for communicating with ancestors when visiting their graves, and there is room for improvement in fostering respect for ancestors.

[0005] The system according to the embodiment aims to foster respect for ancestors by enabling people to have conversations with their ancestors when visiting their graves. [Means for solving the problem]

[0006] The system according to the embodiment comprises a display unit, a face display unit, a dialogue unit, and a provision unit. The display unit displays a two-dimensional code when the grave is viewed with a smartphone camera. The face display unit reads the displayed two-dimensional code and displays the face of the person resting in the grave. When the dialogue unit speaks to the displayed face, the generation AI generates a reply. The provision unit provides the processing results of the dialogue unit to the user. [Effects of the Invention]

[0007] The system according to the embodiment enables a person to have a dialogue with their ancestors when visiting their graves, thereby fostering a sense of respect for their ancestors. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

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

[0028] (Example 1) In an embodiment of the ancestor honoring system of the present invention, when visiting an ancestor's grave during the Obon festival, a two-dimensional code appears when the user views the grave with a smartphone camera. Scanning the two-dimensional code (e.g., a QR code (registered trademark)) displays the face of the person resting on the grave. When the user speaks to the face, a generation AI responds. This system fosters respect for ancestors. For example, when a user views a grave with a smartphone camera, a two-dimensional code appears. This two-dimensional code is pre-set by the generation AI, and each grave has a different two-dimensional code. When a user scans the two-dimensional code, the face of the person resting on the grave is displayed. This face is generated by the generation AI based on a pre-registered photo or image. Furthermore, when the user speaks to the face, the generation AI analyzes the content and generates an appropriate response. For example, if the user speaks "Hello," the face responds with "Hello, how are you?" In this way, the user can communicate with the person resting on the grave and foster respect for their ancestors. This system not only fosters respect for ancestors, but also deepens bonds with family and relatives. For example, during the Obon period, the whole family can visit the grave and communicate with their ancestors using their smartphones, allowing the whole family to share a spirit of respect for their ancestors. Relatives who live far away can also share this spirit of respect for their ancestors through this system. This allows users to communicate with their ancestors when visiting the grave, fostering a spirit of respect for their ancestors.

[0029] An ancestor veneration system according to an embodiment includes a display unit, a face display unit, an interaction unit, and a provision unit. The display unit displays a two-dimensional code when a user views a gravestone with a smartphone camera. The two-dimensional code is pre-set by the generation AI, and a different two-dimensional code corresponds to each gravestone. For example, the display unit automatically displays the two-dimensional code when the user launches the smartphone's camera app and views the gravestone. The display unit can also adjust the timing and location of the two-dimensional code display. The face display unit displays the face of the person residing in the gravestone when the two-dimensional code is read. The face display unit displays a face generated by the generation AI based on a pre-registered photo or image. For example, the face display unit displays the face of the person residing in the gravestone on the smartphone screen when the two-dimensional code is read. The face display unit can also adjust the size and position of the displayed face. The interaction unit allows the generation AI to generate a response when the user speaks to the face displayed by the face display unit. The interaction unit analyzes what the user says and generates an appropriate response. For example, when a user says "Hello," the dialogue unit generates a reply such as "Hello, how are you?" The dialogue unit can also use the generation AI to generate a reply that suits the user's emotions and situation. The provision unit provides the processing result of the dialogue unit to the user. The provision unit displays the reply generated by the generation AI to the user. For example, the provision unit displays the reply generated by the generation AI on a smartphone screen. The provision unit can also play the reply generated by the generation AI by voice. In this way, the ancestor respect system according to the embodiment allows the user to interact with their ancestors when visiting their graves, thereby fostering a sense of respect for their ancestors.

[0030] The display unit can display the 2D code during a specific time period based on the location information of the grave. For example, the display unit can display the 2D code only during the Obon period and not display it at other times. The display unit can also display the 2D code only during a specific time period during the day (for example, from 9:00 AM to 5:00 PM). Furthermore, the display unit can also not display the 2D code after evening when it is dark around the grave. By displaying the 2D code only during specific time periods, it is possible to encourage use at appropriate times. Some or all of the above-mentioned processing in the display unit may be performed using, for example, AI, or may be performed without using AI. For example, the display unit can input location information data into the generation AI and have the generation AI set the timing for displaying the 2D code.

[0031] The display unit can detect the condition of the grave and display a two-dimensional code. For example, the display unit displays the two-dimensional code only when the grave has been cleaned. Furthermore, if the grave is dirty, the display unit can refrain from displaying the two-dimensional code and display a message indicating that cleaning is necessary. Furthermore, if the grave is not in good condition, the display unit can temporarily stop displaying the two-dimensional code and redisplay it after cleaning. In this way, by displaying the two-dimensional code according to the grave's condition, appropriate use can be promoted. Some or all of the above-mentioned processing in the display unit may be performed using, for example, AI, or may be performed without AI. For example, the display unit can input grave condition data into the generation AI and have the generation AI set to display the two-dimensional code.

[0032] The display unit can set the display of the 2D code based on environmental information about the area surrounding the grave. For example, the display unit refrains from displaying the 2D code when it is raining and displays it only when the weather is fine. The display unit can also temporarily stop displaying the 2D code when there is strong wind and redisplay it after the wind has died down. Furthermore, the display unit can adjust the background color to make the 2D code easier to see when the sun is strong. This allows for appropriate use by adjusting the display of the 2D code according to environmental information about the area surrounding the grave. Some or all of the above-mentioned processing in the display unit may be performed using, for example, AI, or may be performed without AI. For example, the display unit can input environmental information data into the generation AI and have the generation AI set the display of the 2D code.

[0033] The display unit can display the history and background information of the grave together with the 2D code. For example, the display unit can display a brief biography of the person buried in the grave next to the 2D code. The display unit can also display information about the history and origin of the grave below the 2D code. Furthermore, the display unit can display episodes and anecdotes related to the grave above the 2D code. This allows the user to deepen their understanding by displaying the history and background information of the grave. Some or all of the above-mentioned processing in the display unit may be performed using, or without, AI, for example. For example, the display unit can input history and background information data into a generation AI and have the generation AI set the information to be displayed together with the 2D code.

[0034] The face display unit can set the face display method based on the age and gender of the person residing in the grave. For example, if the person residing in the grave is elderly, the face display unit can display a facial expression appropriate to the person's age. Furthermore, if the person residing in the grave is young, the face display unit can also display a youthful facial expression. Furthermore, the face display unit can display a male or female facial expression depending on the gender of the person residing in the grave. This makes it possible to provide an appropriate face display method appropriate to the age and gender of the person residing in the grave. Some or all of the above-mentioned processing in the face display unit may be performed using, or without, a generation AI. For example, the face display unit can input age and gender data into the generation AI and have the generation AI set the face display method.

[0035] The face display unit can create facial details based on past photographs and videos. The face display unit generates facial details based on, for example, past photographs of the person residing in the grave. The face display unit can also generate facial expressions based on past videos of the person residing in the grave. Furthermore, the face display unit can generate facial features by referring to family photos of the person residing in the grave. This makes it possible to display a more realistic face by generating facial details based on past photographs and videos. Some or all of the above-mentioned processing in the face display unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the face display unit can input past photographs and video data into the generation AI and have the generation AI create facial details.

[0036] The face display unit can display the faces of related people taking into account the user's family composition information. For example, the face display unit can also display the faces of family members who are buried in the grave based on the user's family composition information. The face display unit can also display the faces of related family members by referring to the user's family composition information. Furthermore, the face display unit can display the faces of all family members by taking into account the user's family composition information. This makes it possible to provide a more familiar experience by displaying related faces based on the user's family composition information. Some or all of the above-mentioned processing in the face display unit can be performed using, or without, a generation AI. For example, the face display unit can input family composition information data into the generation AI and have the generation AI set to display related faces.

[0037] The face display unit can set the facial display content by referring to the user's past interaction history. The face display unit, for example, adjusts the facial expression based on the user's past interaction history. The face display unit can also customize the facial display content by referring to the user's past interaction history. Furthermore, the face display unit can also adjust the facial display method by taking the user's past interaction history into consideration. This makes it possible to provide a more personalized experience by adjusting the facial display content based on the user's past interaction history. Some or all of the above-mentioned processing in the face display unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the face display unit can input past interaction history data into the generation AI and have the generation AI set the facial display content.

[0038] The dialogue unit can create a reply based on the past statements and records of the person resting in the grave. The dialogue unit generates a reply based on, for example, the past statements of the person resting in the grave. The dialogue unit can also generate a reply by referring to the past records of the person resting in the grave. Furthermore, the dialogue unit can generate a reply based on the testimony of the family of the person resting in the grave. In this way, by generating a reply based on the past statements and records of the person resting in the grave, it is possible to provide a more realistic dialogue. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the dialogue unit can input past statements and record data into the generation AI and have the generation AI create a reply.

[0039] The dialogue unit can set the content of the reply by referring to the user's past dialogue history. The dialogue unit, for example, customizes the content of the reply based on the user's past dialogue history. The dialogue unit can also adjust the tone of the reply by referring to the user's past dialogue history. Furthermore, the dialogue unit can also optimize the content of the reply by taking the user's past dialogue history into consideration. This makes it possible to provide a more personalized dialogue by customizing the content of the reply based on the user's past dialogue history. Some or all of the above-mentioned processing in the dialogue unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the dialogue unit can input past dialogue history data into the generation AI and have the generation AI set the content of the reply.

[0040] The dialogue unit can create a reply taking into account the user's current situation. For example, if the user is tired, the dialogue unit can generate an encouraging reply. Furthermore, if the user is in good health, the dialogue unit can also generate an encouraging reply. Furthermore, if the user is not feeling well, the dialogue unit can also generate a caring reply. This makes it possible to generate an appropriate reply according to the user's current situation. Some or all of the above-mentioned processing in the dialogue unit may be performed using, or without, a generation AI. For example, the dialogue unit can input current situation data into the generation AI and have the generation AI create a reply.

[0041] The dialogue unit can set the content of the reply by referring to information about the user's family and relatives. For example, the dialogue unit generates a reply including a topic related to the family based on the user's family information. The dialogue unit can also generate a reply including a topic related to the relatives by referring to the user's relative information. Furthermore, the dialogue unit can customize the content of the reply by taking into account the information about the user's family and relatives. This makes it possible to provide a more friendly dialogue by adjusting the content of the reply based on the information about the user's family and relatives. Some or all of the above-mentioned processing in the dialogue unit may be performed using, or without, a generation AI. For example, the dialogue unit may input information data about the family and relatives into the generation AI and have the generation AI set the content of the reply.

[0042] The providing unit can record the dialogue content and make it available for later reference. For example, the providing unit can automatically record the content of a user's dialogue and make it available for later reference. The providing unit can also store the dialogue content in the cloud and make it accessible from multiple devices. Furthermore, the providing unit can organize the dialogue content by date and time to make it easy to search. By recording the dialogue content, it can be referenced later. Some or all of the above-described processing in the providing unit can be performed using, for example, AI, or can be performed without using AI. For example, the providing unit can input dialogue content data to a generation AI and cause the generation AI to perform recording and reference functions.

[0043] The providing unit can select a display method based on the user's past interaction history. For example, the providing unit selects the optimal display method based on the user's past interaction history. The providing unit can also preferentially provide a display method that the user has previously preferred. Furthermore, the providing unit can analyze the user's past interaction history and suggest a display method with the highest visibility. This makes it possible to provide the optimal display method based on the user's past interaction history. Some or all of the above-described processing in the providing unit may be performed using AI, for example, or may be performed without using AI. For example, the providing unit can input past interaction history data to a generation AI and cause the generation AI to select a display method.

[0044] The providing unit can select a display method taking into account the user's device information. For example, if the user is using a smartphone, the providing unit can provide a display method that matches the screen size. Furthermore, if the user is using a tablet, the providing unit can also provide a display method optimized for a large screen. Furthermore, if the user is using a smartwatch, the providing unit can also provide a display method that is simple and highly visible. This makes it possible to provide an optimal display method based on the user's device information. Some or all of the above-described processing in the providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the providing unit can input device information data to the generating AI and cause the generating AI to select a display method.

[0045] The providing unit can add a function for sharing the dialogue content with other family members and relatives. For example, the providing unit generates a link for sharing the dialogue content with family members and relatives. The providing unit can also provide a function for sending the dialogue content to family members and relatives by email. Furthermore, the providing unit can also provide a dedicated app for sharing the dialogue content with family members and relatives. This allows the user to deepen ties with family members and relatives by sharing the dialogue content with other family members and relatives. Some or all of the above-described processing in the providing unit may be performed using, or without, AI, for example. For example, the providing unit can input dialogue content data to a generating AI and cause the generating AI to execute a sharing function.

[0046] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0047] The ancestor respect system may further include a notification unit. The notification unit may notify the user's smartphone of the timing for visiting the grave. For example, as the Obon festival approaches, the notification unit may send the user a notification such as "It's time to visit the grave." The notification unit may also suggest a suitable day for visiting the grave based on weather information. For example, on a day when fine weather is predicted, the notification unit may notify the user that "Tomorrow is the best day to visit the grave." Furthermore, the notification unit may simultaneously send notifications to all family members, encouraging the whole family to plan a grave visit together. This allows the user to visit the grave at the appropriate time and foster a spirit of respect for ancestors.

[0048] The ancestor veneration system can further include a location tracking unit. The location tracking unit can track the user's current location and provide navigation to the location of the grave. For example, when a user goes to visit a grave with their smartphone, the location tracking unit can detect the user's current location and guide them to the optimal route. The location tracking unit can also provide information on tourist spots and rest areas around the grave. This allows the user to arrive at the grave without getting lost and enjoy a comfortable grave visit. Furthermore, the location tracking unit can share the location information of all family members and set a meeting place. This allows the entire family to visit the grave smoothly.

[0049] The ancestor veneration system may further include a weather forecasting unit. The weather forecasting unit may provide a weather forecast tailored to the user's grave visit plans. For example, if the user plans to visit the grave on a specific day, the weather forecasting unit may predict the weather for that day and notify the user. The weather forecasting unit may also suggest an alternative day if bad weather is predicted. This allows the user to visit the grave regardless of the weather. Furthermore, the weather forecasting unit may provide a list of items to bring when visiting the grave based on weather information. For example, if rain is predicted, the unit may notify the user to bring an umbrella or raincoat.

[0050] The ancestor veneration system may further include a photo sharing unit. The photo sharing unit allows a user to share photos taken during a visit to a grave with family and relatives. For example, when a user takes a photo of a grave with a smartphone, the photo sharing unit uploads the photo to the cloud and sends a sharing link to family and relatives. The photo sharing unit may also provide a function for adding comments to the photos taken. This allows family and relatives to share memories of visiting the grave. Furthermore, the photo sharing unit may organize previously taken photos in an album format for easy viewing.

[0051] The ancestor veneration system may further include a reminder unit. The reminder unit can send reminders to the user to periodically visit the grave. For example, when Obon or the anniversary of a death approaches, the reminder unit notifies the user that "it's time to visit the grave." The reminder unit can also record the date and time when the user previously visited the grave and suggest the timing of the next visit. This allows the user to regularly visit the grave without forgetting. Furthermore, the reminder unit can simultaneously send reminders to all family members, encouraging the whole family to make plans to visit the grave together.

[0052] The processing flow of the first embodiment will be briefly explained below.

[0053] Step 1: When the smartphone camera is used to view the grave, the display unit displays a 2D code. The 2D code is pre-set by the generating AI, and each grave has a different 2D code. For example, when the display unit launches the smartphone's camera app and views the grave, it automatically displays the 2D code. The display unit can also adjust the timing and location of the 2D code display. Step 2: When the 2D code is read, the face display unit displays the face of the person resting in the grave. The face display unit displays a face generated by AI based on pre-registered photos and images. For example, when the face display unit reads the 2D code, it displays the face of the person resting in the grave on the smartphone screen. The face display unit can also adjust the size and position of the displayed face. Step 3: When the dialogue unit speaks to the face displayed by the face display unit, the generation AI generates a reply. The dialogue unit uses the generation AI to analyze what the user has said and generate an appropriate reply. For example, when the user says "Hello," the dialogue unit generates a reply such as "Hello, how are you?" The dialogue unit can also use the generation AI to generate a reply that suits the user's emotions and situation. Step 4: The providing unit provides the processing results of the dialogue unit to the user. The providing unit displays the reply generated by the generation AI to the user. For example, the providing unit may display the reply generated by the generation AI on a smartphone screen. The providing unit may also play the reply generated by the generation AI as audio.

[0054] (Example 2) In an embodiment of the ancestor honoring system of the present invention, when visiting an ancestor's grave during the Obon festival, a 2D code appears when the user views the grave with a smartphone camera. Scanning the 2D code displays the face of the person buried there, and when the user speaks to the face, the AI ​​responds. This system fosters respect for ancestors. For example, when a user views a grave with a smartphone camera, a 2D code appears. This 2D code is pre-set by the AI, and each grave has a different 2D code. When a user scans the 2D code, the face of the person buried there appears. This face is generated by the AI ​​based on pre-registered photos or images. Furthermore, when the user speaks to the face, the AI ​​analyzes the content and generates an appropriate response. For example, if the user speaks "Hello," the AI ​​responds with "Hello, how are you?" This allows the user to communicate with the person buried there and foster respect for their ancestors. This system not only fosters respect for ancestors, but also deepens bonds with family and relatives. For example, during the Obon period, the whole family can visit the grave and communicate with their ancestors using their smartphones, allowing the whole family to share a spirit of respect for their ancestors. Relatives who live far away can also share this spirit of respect for their ancestors through this system. This allows users to communicate with their ancestors when visiting the grave, fostering a spirit of respect for their ancestors.

[0055] An ancestor veneration system according to an embodiment includes a display unit, a face display unit, an interaction unit, and a provision unit. The display unit displays a two-dimensional code when a user views a gravestone with a smartphone camera. The two-dimensional code is pre-set by the generation AI, and a different two-dimensional code corresponds to each gravestone. For example, the display unit automatically displays the two-dimensional code when the user launches the smartphone's camera app and views the gravestone. The display unit can also adjust the timing and location of the two-dimensional code display. The face display unit displays the face of the person residing in the gravestone when the two-dimensional code is read. The face display unit displays a face generated by the generation AI based on a pre-registered photo or image. For example, the face display unit displays the face of the person residing in the gravestone on the smartphone screen when the two-dimensional code is read. The face display unit can also adjust the size and position of the displayed face. The interaction unit allows the generation AI to generate a response when the user speaks to the face displayed by the face display unit. The interaction unit analyzes what the user says and generates an appropriate response. For example, when a user says "Hello," the dialogue unit generates a reply such as "Hello, how are you?" The dialogue unit can also use the generation AI to generate a reply that suits the user's emotions and situation. The provision unit provides the processing result of the dialogue unit to the user. The provision unit displays the reply generated by the generation AI to the user. For example, the provision unit displays the reply generated by the generation AI on a smartphone screen. The provision unit can also play the reply generated by the generation AI by voice. In this way, the ancestor respect system according to the embodiment allows the user to interact with their ancestors when visiting their graves, thereby fostering a sense of respect for their ancestors.

[0056] The display unit can estimate the user's emotions and set the timing for displaying the 2D code based on the estimated user emotions. For example, if the user is emotional, the display unit can delay the display of the 2D code slightly until the user calms down. Alternatively, if the user is in a hurry, the display unit can immediately display the 2D code to allow the user to quickly proceed to the next step. Furthermore, if the user is relaxed, the display unit can slowly fade in the display of the 2D code to provide a calming experience. This allows the 2D code to be displayed at an appropriate timing according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the display unit can be performed using, for example, AI, or without AI. For example, the display unit can input the user's facial expression data into the generation AI and have the generation AI perform emotion estimation.

[0057] The display unit can display the 2D code during a specific time period based on the location information of the grave. For example, the display unit can display the 2D code only during the Obon period and not display it at other times. The display unit can also display the 2D code only during a specific time period during the day (for example, from 9:00 AM to 5:00 PM). Furthermore, the display unit can also not display the 2D code after evening when it is dark around the grave. By displaying the 2D code only during specific time periods, it is possible to encourage use at appropriate times. Some or all of the above-mentioned processing in the display unit may be performed using, for example, AI, or may be performed without using AI. For example, the display unit can input location information data into the generation AI and have the generation AI set the timing for displaying the 2D code.

[0058] The display unit can detect the condition of the grave and display a two-dimensional code. For example, the display unit displays the two-dimensional code only when the grave has been cleaned. Furthermore, if the grave is dirty, the display unit can refrain from displaying the two-dimensional code and display a message indicating that cleaning is necessary. Furthermore, if the grave is not in good condition, the display unit can temporarily stop displaying the two-dimensional code and redisplay it after cleaning. In this way, by displaying the two-dimensional code according to the grave's condition, appropriate use can be promoted. Some or all of the above-mentioned processing in the display unit may be performed using, for example, AI, or may be performed without AI. For example, the display unit can input grave condition data into the generation AI and have the generation AI set to display the two-dimensional code.

[0059] The display unit can estimate the user's emotions and set the display method of the 2D code based on the estimated user emotions. For example, if the user is emotional, the display unit can slowly fade in the 2D code when displaying it. Alternatively, if the user is in a hurry, the display unit can quickly display the 2D code to allow the user to proceed to the next step quickly. Furthermore, if the user is relaxed, the display unit can gently display the 2D code, providing a visually pleasant experience. This allows the 2D code to be displayed in an appropriate manner according to the user's emotions. The emotion estimation is realized using an emotion estimation function, such as an emotion engine or a generation AI. The generation AI can be, but is not limited to, a text generation AI (e.g., LLM) or a multimodal generation AI. Some or all of the above-described processing in the display unit can be performed using, for example, an AI, or without an AI. For example, the display unit can input the user's facial expression data into the generation AI and have the generation AI perform emotion estimation.

[0060] The display unit can set the display of the 2D code based on environmental information about the area surrounding the grave. For example, the display unit refrains from displaying the 2D code when it is raining and displays it only when the weather is fine. The display unit can also temporarily stop displaying the 2D code when there is strong wind and redisplay it after the wind has died down. Furthermore, the display unit can adjust the background color to make the 2D code easier to see when the sun is strong. This allows for appropriate use by adjusting the display of the 2D code according to environmental information about the area surrounding the grave. Some or all of the above-mentioned processing in the display unit may be performed using, for example, AI, or may be performed without AI. For example, the display unit can input environmental information data into the generation AI and have the generation AI set the display of the 2D code.

[0061] The display unit can display the history and background information of the grave together with the 2D code. For example, the display unit can display a brief biography of the person buried in the grave next to the 2D code. The display unit can also display information about the history and origin of the grave below the 2D code. Furthermore, the display unit can display episodes and anecdotes related to the grave above the 2D code. This allows the user to deepen their understanding by displaying the history and background information of the grave. Some or all of the above-mentioned processing in the display unit may be performed using, or without, AI, for example. For example, the display unit can input history and background information data into a generation AI and have the generation AI set the information to be displayed together with the 2D code.

[0062] The face display unit can estimate the user's emotions and set the facial expression to be displayed based on the estimated user's emotions. For example, if the user is moved, the face display unit can display a calm-looking face. If the user is sad, the face display unit can also display a gentle-looking face. If the user is happy, the face display unit can also display a smiling face. This makes it possible to display a face with an appropriate expression according to the user's emotions. Emotion estimation is realized using an emotion estimation function, for example, with an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the face display unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the face display unit can input the user's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0063] The face display unit can set the face display method based on the age and gender of the person residing in the grave. For example, if the person residing in the grave is elderly, the face display unit can display a facial expression appropriate to the person's age. Furthermore, if the person residing in the grave is young, the face display unit can also display a youthful facial expression. Furthermore, the face display unit can display a male or female facial expression depending on the gender of the person residing in the grave. This makes it possible to provide an appropriate face display method appropriate to the age and gender of the person residing in the grave. Some or all of the above-mentioned processing in the face display unit may be performed using, or without, a generation AI. For example, the face display unit can input age and gender data into the generation AI and have the generation AI set the face display method.

[0064] The face display unit can create facial details based on past photographs and videos. The face display unit generates facial details based on, for example, past photographs of the person residing in the grave. The face display unit can also generate facial expressions based on past videos of the person residing in the grave. Furthermore, the face display unit can generate facial features by referring to family photos of the person residing in the grave. This makes it possible to display a more realistic face by generating facial details based on past photographs and videos. Some or all of the above-mentioned processing in the face display unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the face display unit can input past photographs and video data into the generation AI and have the generation AI create facial details.

[0065] The face display unit can estimate the user's emotions and set the face display time based on the estimated user emotions. For example, if the user is emotional, the face display unit can increase the face display time to allow the user more time to share their emotions. Furthermore, if the user is in a hurry, the face display unit can shorten the face display time to allow the user to quickly proceed to the next step. Furthermore, if the user is relaxed, the face display unit can appropriately adjust the face display time to provide a calm experience. This allows the face to be displayed for an appropriate time according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the face display unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the face display unit can input the user's facial expression data into the generation AI and have the generation AI execute emotion estimation.

[0066] The face display unit can display the faces of related people taking into account the user's family composition information. For example, the face display unit can also display the faces of family members who are buried in the grave based on the user's family composition information. The face display unit can also display the faces of related family members by referring to the user's family composition information. Furthermore, the face display unit can display the faces of all family members by taking into account the user's family composition information. This makes it possible to provide a more familiar experience by displaying related faces based on the user's family composition information. Some or all of the above-mentioned processing in the face display unit can be performed using, or without, a generation AI. For example, the face display unit can input family composition information data into the generation AI and have the generation AI set to display related faces.

[0067] The face display unit can set the facial display content by referring to the user's past interaction history. The face display unit, for example, adjusts the facial expression based on the user's past interaction history. The face display unit can also customize the facial display content by referring to the user's past interaction history. Furthermore, the face display unit can also adjust the facial display method by taking the user's past interaction history into consideration. This makes it possible to provide a more personalized experience by adjusting the facial display content based on the user's past interaction history. Some or all of the above-mentioned processing in the face display unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the face display unit can input past interaction history data into the generation AI and have the generation AI set the facial display content.

[0068] The dialogue unit can estimate the user's emotions and set the content of a reply based on the estimated user emotions. For example, if the user is emotional, the dialogue unit generates a reply that shares the emotion. Furthermore, if the user is sad, the dialogue unit can generate a reply that comforts the user. Furthermore, if the user is happy, the dialogue unit can generate a reply that shares the joy. This makes it possible to generate an appropriate reply according to the user's emotions. Emotion estimation is realized using an emotion estimation function, for example, with an emotion engine or a generation AI. The generation AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, AI, or may be performed without using AI. For example, the dialogue unit can input the user's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0069] The dialogue unit can create a reply based on the past statements and records of the person resting in the grave. The dialogue unit generates a reply based on, for example, the past statements of the person resting in the grave. The dialogue unit can also generate a reply by referring to the past records of the person resting in the grave. Furthermore, the dialogue unit can generate a reply based on the testimony of the family of the person resting in the grave. In this way, by generating a reply based on the past statements and records of the person resting in the grave, it is possible to provide a more realistic dialogue. Some or all of the above-mentioned processing in the dialogue unit may be performed using, for example, a generation AI, or may be performed without using a generation AI. For example, the dialogue unit can input past statements and record data into the generation AI and have the generation AI create a reply.

[0070] The dialogue unit can set the content of the reply by referring to the user's past dialogue history. The dialogue unit, for example, customizes the content of the reply based on the user's past dialogue history. The dialogue unit can also adjust the tone of the reply by referring to the user's past dialogue history. Furthermore, the dialogue unit can also optimize the content of the reply by taking the user's past dialogue history into consideration. This makes it possible to provide a more personalized dialogue by customizing the content of the reply based on the user's past dialogue history. Some or all of the above-mentioned processing in the dialogue unit may be performed, for example, using a generation AI, or may be performed without using a generation AI. For example, the dialogue unit can input past dialogue history data into the generation AI and have the generation AI set the content of the reply.

[0071] The dialogue unit can estimate the user's emotions and set the tone of the reply based on the estimated user's emotions. For example, if the user is moved, the dialogue unit can generate a reply in a gentle tone. If the user is sad, the dialogue unit can also generate a reply in a soft tone. If the user is happy, the dialogue unit can also generate a reply in a bright tone. This makes it possible to generate a reply in an appropriate tone according to the user's emotions. Emotion estimation is realized using an emotion estimation function, for example, with an emotion engine or generation AI. The generation AI can be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the dialogue unit may be performed using AI, for example, or without AI. For example, the dialogue unit can input the user's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0072] The dialogue unit can create a reply taking into account the user's current situation. For example, if the user is tired, the dialogue unit can generate an encouraging reply. Furthermore, if the user is in good health, the dialogue unit can also generate an encouraging reply. Furthermore, if the user is not feeling well, the dialogue unit can also generate a caring reply. This makes it possible to generate an appropriate reply according to the user's current situation. Some or all of the above-mentioned processing in the dialogue unit may be performed using, or without, a generation AI. For example, the dialogue unit can input current situation data into the generation AI and have the generation AI create a reply.

[0073] The dialogue unit can set the content of the reply by referring to information about the user's family and relatives. For example, the dialogue unit generates a reply including a topic related to the family based on the user's family information. The dialogue unit can also generate a reply including a topic related to the relatives by referring to the user's relative information. Furthermore, the dialogue unit can customize the content of the reply by taking into account the information about the user's family and relatives. This makes it possible to provide a more friendly dialogue by adjusting the content of the reply based on the information about the user's family and relatives. Some or all of the above-mentioned processing in the dialogue unit may be performed using, or without, a generation AI. For example, the dialogue unit may input information data about the family and relatives into the generation AI and have the generation AI set the content of the reply.

[0074] The providing unit can estimate the user's emotions and set a display method for the dialogue result based on the estimated user's emotions. For example, if the user is emotional, the providing unit can display the dialogue result calmly. Furthermore, if the user is in a hurry, the providing unit can also display the dialogue result quickly. Furthermore, if the user is relaxed, the providing unit can also display the dialogue result slowly. This allows the dialogue result to be displayed in an appropriate manner according to the user's emotions. Emotion estimation is realized using an emotion estimation function, for example, using an emotion engine or a generation AI. The generation AI may be a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-mentioned processing in the providing unit may be performed using AI, for example, or without AI. For example, the providing unit can input the user's facial expression data into the generation AI and cause the generation AI to estimate emotions.

[0075] The providing unit can record the dialogue content and make it available for later reference. For example, the providing unit can automatically record the content of a user's dialogue and make it available for later reference. The providing unit can also store the dialogue content in the cloud and make it accessible from multiple devices. Furthermore, the providing unit can organize the dialogue content by date and time to make it easy to search. By recording the dialogue content, it can be referenced later. Some or all of the above-described processing in the providing unit can be performed using, for example, AI, or can be performed without using AI. For example, the providing unit can input dialogue content data to a generation AI and cause the generation AI to perform recording and reference functions.

[0076] The providing unit can select a display method based on the user's past interaction history. For example, the providing unit selects the optimal display method based on the user's past interaction history. The providing unit can also preferentially provide a display method that the user has previously preferred. Furthermore, the providing unit can analyze the user's past interaction history and suggest a display method with the highest visibility. This makes it possible to provide the optimal display method based on the user's past interaction history. Some or all of the above-described processing in the providing unit may be performed using AI, for example, or may be performed without using AI. For example, the providing unit can input past interaction history data to a generation AI and cause the generation AI to select a display method.

[0077] The providing unit can estimate the user's emotions and set the display order of the dialogue results based on the estimated user emotions. For example, if the user is emotional, the providing unit can first display content that shares the emotion. Furthermore, if the user is in a hurry, the providing unit can also display important content first. Furthermore, if the user is relaxed, the providing unit can display the results in a natural flow without worrying about the order. This allows the dialogue results to be displayed in an appropriate order according to the user's emotions. The emotion estimation is realized using an emotion estimation function, for example, an emotion engine or a generation AI. The generation AI can be, for example, a text generation AI (e.g., LLM) or a multimodal generation AI, but is not limited to such examples. Some or all of the above-described processing in the providing unit may be performed using, for example, an AI, or may be performed without using an AI. For example, the providing unit can input the user's facial expression data into the generation AI and cause the generation AI to estimate the emotion.

[0078] The providing unit can select a display method taking into account the user's device information. For example, if the user is using a smartphone, the providing unit can provide a display method that matches the screen size. Furthermore, if the user is using a tablet, the providing unit can also provide a display method optimized for a large screen. Furthermore, if the user is using a smartwatch, the providing unit can also provide a display method that is simple and highly visible. This makes it possible to provide an optimal display method based on the user's device information. Some or all of the above-described processing in the providing unit may be performed using, for example, AI, or may be performed without using AI. For example, the providing unit can input device information data to the generating AI and cause the generating AI to select a display method.

[0079] The providing unit can add a function for sharing the dialogue content with other family members and relatives. For example, the providing unit generates a link for sharing the dialogue content with family members and relatives. The providing unit can also provide a function for sending the dialogue content to family members and relatives by email. Furthermore, the providing unit can also provide a dedicated app for sharing the dialogue content with family members and relatives. This allows the user to deepen ties with family members and relatives by sharing the dialogue content with other family members and relatives. Some or all of the above-described processing in the providing unit may be performed using, or without, AI, for example. For example, the providing unit can input dialogue content data to a generating AI and cause the generating AI to execute a sharing function. === Hard Collateral 1-1 === Each of the multiple elements including the display unit, face display unit, dialogue unit, and provision unit described above is realized, for example, by at least one of the smart device 14 and the data processing device 12. For example, the display unit displays a two-dimensional code when viewing a grave using the camera 42 of the smart device 14. The face display unit reads the two-dimensional code and displays the face of the person resting in the grave on the display 40A of the smart device 14. The dialogue unit acquires what the user has said using the microphone 38B of the smart device 14, and the generation AI generates a reply via the specific processing unit 290 of the data processing device 12. The provision unit provides the reply generated by the generation AI to the user via the display 40A or speaker 40B of the smart device 14. === Hard Collateral 1-2 === Each of the multiple elements including the display unit, face display unit, dialogue unit, and provision unit described above is realized, for example, by at least one of the smart glasses 214 and the data processing device 12. For example, the display unit displays a two-dimensional code when viewing a grave using the camera 42 of the smart glasses 214. The face display unit reads the two-dimensional code and displays the face of the person resting in the grave on the display of the smart glasses 214. The dialogue unit acquires what the user has said using the microphone 238 of the smart glasses 214, and the generation AI generates a reply via the specific processing unit 290 of the data processing device 12. The provision unit provides the reply generated by the generation AI to the user via the display or speaker 240 of the smart glasses 214. === Hard Collateral 1-3 === Each of the multiple elements including the display unit, face display unit, dialogue unit, and provision unit described above is realized, for example, by at least one of the headset terminal 314 and the data processing device 12. For example, the display unit displays a two-dimensional code when the grave is viewed using the camera 42 of the headset terminal 314. When the face display unit reads the two-dimensional code, it displays the face of the person resting in the grave on the display 343 of the headset terminal 314. The dialogue unit acquires what the user has said using the microphone 238 of the headset terminal 314, and the generation AI generates a reply via the specific processing unit 290 of the data processing device 12. The provision unit provides the reply generated by the generation AI to the user via the display 343 or speaker 240 of the headset terminal 314. === Hard Collateral 1-4 === Each of the multiple elements including the display unit, face display unit, dialogue unit, and provision unit described above is realized, for example, by at least one of the robot 414 and the data processing device 12. For example, the display unit displays a two-dimensional code when viewing a grave using the camera 42 of the robot 414. When the face display unit reads the two-dimensional code, it displays the face of the person resting in the grave on the display of the robot 414. The dialogue unit acquires what the user has said using the microphone 238 of the robot 414, and the generation AI generates a reply via the specific processing unit 290 of the data processing device 12. The provision unit provides the reply generated by the generation AI to the user via the display or speaker 240 of the robot 414.

[0080] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0081] The ancestor veneration system can further include a voice recognition unit. The voice recognition unit can analyze the user's voice and detect specific keywords and phrases. For example, if the user says, "Tell me a story from your memory," the voice recognition unit detects this phrase and sends instructions to the dialogue unit. The dialogue unit can use a generative AI to generate a story from the past and provide it to the user. The voice recognition unit can also analyze the tone and speed of the user's voice to estimate the user's emotions. This allows for appropriate dialogue to be provided based on the user's emotions. For example, if the user is excited, the dialogue unit can generate a gentle response to calm the user. Furthermore, the voice recognition unit can distinguish between the voices of multiple users and respond individually. This allows the whole family to enjoy dialogue at the same time.

[0082] The ancestor respect system may further include a notification unit. The notification unit may notify the user's smartphone of the timing for visiting the grave. For example, as the Obon festival approaches, the notification unit may send the user a notification such as "It's time to visit the grave." The notification unit may also suggest a suitable day for visiting the grave based on weather information. For example, on a day when fine weather is predicted, the notification unit may notify the user that "Tomorrow is the best day to visit the grave." Furthermore, the notification unit may simultaneously send notifications to all family members, encouraging the whole family to plan a grave visit together. This allows the user to visit the grave at the appropriate time and foster a spirit of respect for ancestors.

[0083] The ancestor veneration system may further include a recording unit. The recording unit can record the date and time when the user visits the grave and the content of the conversation. For example, it can automatically record the date and time when the user reads the 2D code and the content of the conversation. The recording unit can also estimate the emotions felt by the user during the conversation and record those emotions. This allows the user to look back on records of past grave visits and check the history of conversations with their ancestors. Furthermore, the recording unit can analyze the recorded data and provide the user with information that will be useful for the next grave visit. For example, it can suggest a topic for the next conversation based on the content of the previous conversation.

[0084] The ancestor veneration system can further include a translation unit. When a user speaks in a different language, the translation unit can automatically translate the language and send it to the dialogue unit. For example, if a user says "Hello" in English, the translation unit translates this into Japanese and sends it to the dialogue unit. The dialogue unit can then use a generative AI to generate an appropriate reply, which can then be translated back into English by the translation unit and provided to the user. This allows users who speak different languages ​​to converse with their ancestors. The translation unit can also estimate the user's emotions and perform translations based on those emotions. For example, if the user is moved, it can perform translations that share the emotion.

[0085] The ancestor veneration system can further include a voice synthesis unit. The voice synthesis unit can play back the response generated by the generation AI as voice. For example, if the dialogue unit generates a response such as "Hello, how are you?", the voice synthesis unit will play this back as voice. The voice synthesis unit can also estimate the user's emotions and play back voice in a tone that corresponds to the emotion. For example, if the user is emotional, it can play back voice in a calm tone. Furthermore, the voice synthesis unit can also reproduce the voice of someone buried in a grave based on past recording data. This allows users to enjoy more realistic conversations.

[0086] The ancestor veneration system can further include a location tracking unit. The location tracking unit can track the user's current location and provide navigation to the location of the grave. For example, when a user goes to visit a grave with their smartphone, the location tracking unit can detect the user's current location and guide them to the optimal route. The location tracking unit can also provide information on tourist spots and rest areas around the grave. This allows the user to arrive at the grave without getting lost and enjoy a comfortable grave visit. Furthermore, the location tracking unit can share the location information of all family members and set a meeting place. This allows the entire family to visit the grave smoothly.

[0087] The ancestor veneration system may further include a weather forecasting unit. The weather forecasting unit may provide a weather forecast tailored to the user's grave visit plans. For example, if the user plans to visit the grave on a specific day, the weather forecasting unit may predict the weather for that day and notify the user. The weather forecasting unit may also suggest an alternative day if bad weather is predicted. This allows the user to visit the grave regardless of the weather. Furthermore, the weather forecasting unit may provide a list of items to bring when visiting the grave based on weather information. For example, if rain is predicted, the unit may notify the user to bring an umbrella or raincoat.

[0088] The ancestor veneration system may further include a photo sharing unit. The photo sharing unit allows a user to share photos taken during a visit to a grave with family and relatives. For example, when a user takes a photo of a grave with a smartphone, the photo sharing unit uploads the photo to the cloud and sends a sharing link to family and relatives. The photo sharing unit may also provide a function for adding comments to the photos taken. This allows family and relatives to share memories of visiting the grave. Furthermore, the photo sharing unit may organize previously taken photos in an album format for easy viewing.

[0089] The ancestor veneration system may further include a reminder unit. The reminder unit can send reminders to the user to periodically visit the grave. For example, when Obon or the anniversary of a death approaches, the reminder unit notifies the user that "it's time to visit the grave." The reminder unit can also record the date and time when the user previously visited the grave and suggest the timing of the next visit. This allows the user to regularly visit the grave without forgetting. Furthermore, the reminder unit can simultaneously send reminders to all family members, encouraging the whole family to make plans to visit the grave together.

[0090] The ancestor veneration system may further include an emotion analysis unit. The emotion analysis unit can analyze the content of the user's conversation and facial expressions to analyze the user's emotions in detail. For example, if the user smiles during a conversation, the emotion analysis unit can detect the smile and determine that the user is happy. Also, if the user sheds tears during a conversation, the emotion analysis unit can detect the tears and determine that the user is moved. This allows the dialogue unit to generate a more appropriate response based on the user's emotions. Furthermore, the emotion analysis unit can record changes in the user's emotions and analyze long-term emotional trends. This makes it possible to provide a personalized dialogue based on the user's emotions.

[0091] The processing flow of the second embodiment will be briefly explained below.

[0092] Step 1: When the smartphone camera is used to view the grave, the display unit displays a 2D code. The 2D code is pre-set by the generating AI, and each grave has a different 2D code. For example, when the display unit launches the smartphone's camera app and views the grave, it automatically displays the 2D code. The display unit can also adjust the timing and location of the 2D code display. Step 2: When the 2D code is read, the face display unit displays the face of the person resting in the grave. The face display unit displays a face generated by AI based on pre-registered photos and images. For example, when the face display unit reads the 2D code, it displays the face of the person resting in the grave on the smartphone screen. The face display unit can also adjust the size and position of the displayed face. Step 3: When the dialogue unit speaks to the face displayed by the face display unit, the generation AI generates a reply. The dialogue unit uses the generation AI to analyze what the user has said and generate an appropriate reply. For example, when the user says "Hello," the dialogue unit generates a reply such as "Hello, how are you?" The dialogue unit can also use the generation AI to generate a reply that suits the user's emotions and situation. Step 4: The providing unit provides the processing results of the dialogue unit to the user. The providing unit displays the reply generated by the generation AI to the user. For example, the providing unit may display the reply generated by the generation AI on a smartphone screen. The providing unit may also play the reply generated by the generation AI as audio.

[0093] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0094] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> Examples of the generative AI include a neural network (NN) and a neural network (NN). The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats of voice data, text data, image data, etc. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and may perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-mentioned parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. The processing performed by an AI including the generative AI may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI including the generative AI.

[0095] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0096] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0097] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0098] 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.

[0099] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0100] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0101] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0102] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0103] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0104] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0105] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0106] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0107] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0108] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0109] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0110] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, 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), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0111] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0112] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0113] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0114] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0115] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0116] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0117] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0119] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0120] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0121] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0122] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0123] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the identification processing unit 290 using these models.

[0124] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0125] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0126] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, 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), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0127] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0128] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0129] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0130] 7, a 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.

[0131] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0132] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0133] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0134] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0135] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0136] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0137] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0138] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0139] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0140] In the robot 414, the processor 46 performs the identification process. The storage 50 stores the identification program 60. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as the control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 also has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform the same process as the identification processing unit 290 using these models.

[0141] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0142] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0143] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt including an instruction, as well as inference data such as audio data indicating speech, text data indicating text, and image data indicating an image (e.g., still image data or video data). The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in one or more data formats, such as audio data, text data, and image data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation models 58 include AIs other than the generation AI. Examples of AIs other than the generation AI include, but are not limited to, 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), and naive Bayes. These AIs can perform various types of processing, but are not limited to these examples. The AI ​​may also be an AI agent. When the processing of each of the above-described parts is performed by an AI, the processing may be performed in part or entirely by the AI, but is not limited to these examples. Processing performed by an AI, including the generation AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by an AI, including the generation AI.

[0144] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0145] The correspondence between each part and the device or control part is not limited to the example described above, and various modifications are possible.

[0146] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0147] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0148] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0149] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0150] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0151] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0152] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0153] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0154] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0155] 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.

[0156] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0157] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0158] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0159] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0160] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0161] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0162] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0163] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[0164] [Explanation of symbols]

[0165] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. A display that displays a 2D code when you view the grave with your smartphone camera, a face display unit that displays the face of the person resting in the grave when the two-dimensional code displayed by the display unit is read; a dialogue unit that generates a reply when the user speaks to the face displayed by the display unit; a providing unit that provides a processing result of the dialogue unit to a user. A system characterized by:

2. The display unit The user's emotion is estimated, and the timing of displaying the two-dimensional code is set based on the estimated user's emotion. The system of claim 1 .

3. The display unit A 2D code is displayed at specific times based on the location of the grave. The system of claim 1 .

4. The display unit Detects the condition of the grave and displays a 2D code The system of claim 1 .

5. The display unit The user's emotion is estimated, and a display method of the two-dimensional code is set based on the estimated user's emotion. The system of claim 1 .

6. The display unit Set the display of a 2D code based on the environmental information around the grave The system of claim 1 .

7. The display unit The history and background information of the grave is displayed together with a 2D code. The system of claim 1 .

8. The face display unit Estimate the user's emotion and set the facial expression to be displayed based on the estimated user emotion. The system of claim 1 .

Images