System

Abstract

An object of a system according to an embodiment is to make meal time richer by using music and video.SOLUTION: A system includes a music providing part, a video providing part, a theme producing part, and a menu interlocking part. The music providing unit provides specific music. The video providing unit provides a video according to the music provided by the music providing unit. The theme creating unit creates a story based on the theme of the meal based on the image provided by the image providing unit. A menu interlocking part performs a performance interlocked with the menu of the meal on the basis of the story produced by the theme producing part.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional technologies do not adequately address the issue of enriching mealtimes, and there is room for improvement.

[0005] The system according to the embodiment aims to enrich mealtimes by using music and video. [Means for solving the problem]

[0006] The system according to the embodiment includes a music providing unit, a video providing unit, a theme production unit, and a menu linkage unit. The music providing unit provides specific music. The video providing unit provides video that matches the music provided by the music providing unit. The theme production unit produces a story based on a meal theme based on the video provided by the video providing unit. The menu linkage unit produces a story that is linked to the meal menu based on the story produced by the theme production unit. [Effects of the Invention]

[0007] The system according to the embodiment can enrich mealtimes by using music and video. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The food texture cinema system according to the embodiment of the present invention is a system that stimulates the five senses by combining music and images, turning mealtime into a special time where you can experience a story. In this way, the food texture cinema system can turn mealtime into a special time where you can experience a story.

[0029] The food texture cinema system according to the embodiment includes a music providing unit, a video providing unit, a theme production unit, and a menu linkage unit. The music providing unit provides specific music. For example, it can provide music from genres such as classical music, pop, and jazz. The music providing unit can also select and provide music that matches the theme of the meal. The video providing unit provides video that matches the music provided by the music providing unit. For example, when enjoying Italian food, it can provide video that evokes the scenery and culture of Italy. The video providing unit can also select and provide video based on the theme of the meal. The theme production unit creates a story based on the theme of the meal based on the video provided by the video providing unit. For example, for a dinner themed around the French Revolution, music and video from that era can be used to provide an experience that makes the guest feel as if they have traveled back in time to that era. The theme production unit can also select and produce a story based on the theme of the meal. The menu linkage unit performs production linked to the meal menu based on the story produced by the theme production unit. For example, different music and video can be provided to match each course, such as an appetizer, a main dish, and a dessert. The menu linking section can also create a different story for each course. As a result, the food texture cinema system according to the embodiment can stimulate the five senses by combining music and images, turning mealtime into a special time where you can experience a story.

[0030] The video provider can deepen understanding and empathy for ingredients by incorporating the origins of the ingredients and the stories of the producers. For example, the video provider can incorporate scenery from the ingredients' origins and interviews with producers into the music and videos served during the meal. For example, a video could show how local farmers grow vegetables, with local traditional music playing in the background. The video provider can also deepen understanding and empathy for ingredients by incorporating the origins of the ingredients and the stories of the producers. For example, when serving dishes using ingredients from a particular region, the video could introduce the scenery and culture of that region. This can enrich the dining experience by helping diners understand the background of the ingredients.

[0031] The menu-linked unit can introduce a system that automatically changes the lighting and decorations on the table to match the food of each course. For example, the menu-linked unit introduces a system that automatically changes the lighting and decorations on the table to match the food of each course. For example, soft lighting and natural decorations are used for appetizers, and strong lighting and historical decorations are used for main dishes. The menu-linked unit can also automatically change the lighting and decorations on the table to match the food of each course. For example, romantic lighting and gorgeous decorations are used for dessert. This makes it possible to change the lighting and decorations to match the food of each course, thereby enriching the dining experience.

[0032] The theme production unit provides a function that allows the user to add their own story, thereby realizing a personalized experience. The theme production unit provides a function that allows the user to add their own story to a story based on a dining theme, for example. For example, the user can incorporate their own experiences and memories into the story. The theme production unit also provides a function that allows the user to add their own story, thereby realizing a personalized experience. For example, the user can add their favorite characters and scenes to the story. This allows the user to add their own story, thereby providing a personalized experience.

[0033] The thematic production unit can combine stories of different themes to provide a complex storyline in which multiple stories intersect. The thematic production unit can, for example, combine stories of the French Revolution and the Italian Renaissance. The thematic production unit can also combine stories of different themes to provide a complex storyline in which multiple stories intersect. For example, stories from the present and the past can be interwoven. This allows multiple stories to intertwine, providing a more multi-layered experience.

[0034] The menu linking unit can combine different cuisine courses to provide an international fusion cuisine experience. The menu linking unit can, for example, combine different cuisine courses to provide an international fusion cuisine experience. For example, a Japanese dish can be offered for the appetizer, an Italian dish for the main dish, and a French dish for the dessert. The menu linking unit can also combine different cuisine courses to provide an international fusion cuisine experience. For example, a menu can be offered that combines Asian and European cuisine. This makes it possible to combine different cuisine courses to provide an international fusion cuisine experience.

[0035] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0036] The music providing unit can customize music based on the user's preferences. For example, if the user likes a particular artist or genre, the music providing unit can select and provide music based on that information. The music providing unit can also analyze the user's past music selection history and suggest the most suitable music. Furthermore, the music providing unit can also allow the user to create their own playlist and provide music based on that playlist. This allows the user to have a music experience tailored to their preferences.

[0037] The video providing unit provides a function for users to import videos they have taken themselves, thereby enabling a personalized video experience. For example, a user can upload videos they have taken while traveling to the system and play the videos while they are eating. The video providing unit can also enable users to select their favorite videos and provide the videos while they are eating. Furthermore, the video providing unit can also provide a function for users to add music and sound effects to their videos. This allows a personalized experience to be provided using the users' own videos.

[0038] The theme production unit allows the user to select a theme of their choice and provide a story based on that theme. For example, if the user likes fantasy, a fantasy story can be provided. Alternatively, if the user likes history, a historical story can be provided. Furthermore, the theme production unit can provide a function that allows the user to add their favorite characters and scenes to the story. This allows the user to have a story experience based on their favorite theme.

[0039] The menu linking unit allows the user to select a dish and provide a presentation based on that dish. For example, if the user selects a specific dish, music and video that match the dish are provided. The user can also customize a menu and provide a presentation based on that menu. Furthermore, the menu linking unit can allow the user to combine their favorite dishes and provide a presentation based on that combination. This makes it possible to provide a personalized experience based on the dishes selected by the user.

[0040] The theme director can combine stories from different cultures and eras to provide users with a multicultural experience. For example, a story from ancient Egypt can be combined with a modern story. The theme director can also combine stories from different cultures and eras to provide users with a multicultural experience. For example, a story from Asia can be intertwined with a story from Europe. This allows users to have a multicultural experience by combining stories from different cultures and eras.

[0041] The menu linking unit can input the user's dietary preferences and allergy information and suggest optimal menus based on that information. For example, if the user is allergic to a particular ingredient, the unit can suggest menus that avoid that ingredient. Also, if the user has specific dietary preferences, the unit can suggest menus based on those preferences. Furthermore, the menu linking unit can provide a function that allows the user to customize menus based on their health condition and diet goals. This makes it possible to provide a dining experience that is tailored to the user's individual needs.

[0042] The processing flow of the first embodiment will be briefly explained below.

[0043] Step 1: The music provider provides specific music. For example, music from genres such as classical music, pop, and jazz can be provided. The music provider can also select and provide music that matches the theme of the meal. Step 2: The video providing unit provides a video that matches the music provided by the music providing unit. For example, when enjoying Italian cuisine, a video that gives a sense of Italian scenery and culture can be provided. The video providing unit can also select and provide a video based on the theme of the meal. Step 3: The theme production department creates a story based on the theme of the meal using the video provided by the video provider. For example, a dinner themed around the French Revolution can use music and video from that era to create an experience that makes guests feel as if they have traveled back in time. The theme production department can also select and direct a story based on the theme of the meal. Step 4: The menu linking unit performs a performance linked to the meal menu based on the story created by the theme production unit. For example, different music and images can be provided for each course, such as appetizer, main dish, and dessert. The menu linking unit can also perform a performance that allows the viewer to feel a different story for each course.

[0044] (Example 2) The food texture cinema system according to the embodiment of the present invention is a system that stimulates the five senses by combining music and images, turning mealtime into a special time where you can experience a story. In this way, the food texture cinema system can turn mealtime into a special time where you can experience a story.

[0045] The food texture cinema system according to the embodiment includes a music providing unit, a video providing unit, a theme production unit, and a menu linkage unit. The music providing unit provides specific music. For example, it can provide music from genres such as classical music, pop, and jazz. The music providing unit can also select and provide music that matches the theme of the meal. The video providing unit provides video that matches the music provided by the music providing unit. For example, when enjoying Italian food, it can provide video that evokes the scenery and culture of Italy. The video providing unit can also select and provide video based on the theme of the meal. The theme production unit creates a story based on the theme of the meal based on the video provided by the video providing unit. For example, for a dinner themed around the French Revolution, music and video from that era can be used to provide an experience that makes the guest feel as if they have traveled back in time to that era. The theme production unit can also select and produce a story based on the theme of the meal. The menu linkage unit performs production linked to the meal menu based on the story produced by the theme production unit. For example, different music and video can be provided to match each course, such as an appetizer, a main dish, and a dessert. The menu linking section can also create a different story for each course. As a result, the food texture cinema system according to the embodiment can stimulate the five senses by combining music and images, turning mealtime into a special time where you can experience a story.

[0046] The music provision unit uses a generative AI to analyze the user's emotions in real time and automatically adjust the music according to the emotion. For example, while the user is eating, the music provision unit uses a camera and microphone to analyze the user's facial expressions and tone of voice in real time, and the generative AI infers the emotion based on that data. For example, if the user is relaxed, it plays calm music and soft-toned images. The music provision unit can also analyze the user's emotions in real time using a generative AI and automatically adjust the music according to the emotion. For example, if the user is excited, it provides fast-paced music. This allows the user to have a more emotional experience by providing music that matches their emotions.

[0047] The video provider can deepen understanding and empathy for ingredients by incorporating the origins of the ingredients and the stories of the producers. For example, the video provider can incorporate scenery from the ingredients' origins and interviews with producers into the music and videos served during the meal. For example, a video could show how local farmers grow vegetables, with local traditional music playing in the background. The video provider can also deepen understanding and empathy for ingredients by incorporating the origins of the ingredients and the stories of the producers. For example, when serving dishes using ingredients from a particular region, the video could introduce the scenery and culture of that region. This can enrich the dining experience by helping diners understand the background of the ingredients.

[0048] The theme direction unit can use the emotion estimation function to dynamically change the progress and ending of the story based on the user's emotions. The theme direction unit, for example, uses the emotion estimation function to dynamically change the progress of the story in accordance with the user's emotions. For example, if the user is excited, the tempo of the story can be increased. The theme direction unit can also use the emotion estimation function to dynamically change the ending of the story based on the user's emotions. For example, if the user is moved, an emotional ending can be provided. In this way, by changing the progress and ending of the story in accordance with the user's emotions, a more emotional experience can be provided.

[0049] The menu-linked unit can introduce a system that automatically changes the lighting and decorations on the table to match the food of each course. For example, the menu-linked unit introduces a system that automatically changes the lighting and decorations on the table to match the food of each course. For example, soft lighting and natural decorations are used for appetizers, and strong lighting and historical decorations are used for main dishes. The menu-linked unit can also automatically change the lighting and decorations on the table to match the food of each course. For example, romantic lighting and gorgeous decorations are used for dessert. This makes it possible to change the lighting and decorations to match the food of each course, thereby enriching the dining experience.

[0050] The menu linkage unit can use the emotion estimation function to analyze the user's emotional response to each course of food and optimize the presentation of the next course. The menu linkage unit, for example, uses the emotion estimation function to analyze the user's emotional response to each course of food in real time. For example, the menu linkage unit can adjust the music and video for the next course based on the user's emotional response to the appetizer. The menu linkage unit can also use the emotion estimation function to analyze the user's emotional response to each course of food and optimize the presentation of the next course. For example, the menu linkage unit can adjust the presentation of the dessert based on the user's emotional response to the main dish. This makes it possible to provide a more emotional experience by optimizing the presentation of the next course based on the user's emotional response.

[0051] The theme production unit provides a function that allows the user to add their own story, thereby realizing a personalized experience. The theme production unit provides a function that allows the user to add their own story to a story based on a dining theme, for example. For example, the user can incorporate their own experiences and memories into the story. The theme production unit also provides a function that allows the user to add their own story, thereby realizing a personalized experience. For example, the user can add their favorite characters and scenes to the story. This allows the user to add their own story, thereby providing a personalized experience.

[0052] The thematic production unit can combine stories of different themes to provide a complex storyline in which multiple stories intersect. The thematic production unit can, for example, combine stories of the French Revolution and the Italian Renaissance. The thematic production unit can also combine stories of different themes to provide a complex storyline in which multiple stories intersect. For example, stories from the present and the past can be interwoven. This allows multiple stories to intertwine, providing a more multi-layered experience.

[0053] The menu linking unit can combine different cuisine courses to provide an international fusion cuisine experience. The menu linking unit can, for example, combine different cuisine courses to provide an international fusion cuisine experience. For example, a Japanese dish can be offered for the appetizer, an Italian dish for the main dish, and a French dish for the dessert. The menu linking unit can also combine different cuisine courses to provide an international fusion cuisine experience. For example, a menu can be offered that combines Asian and European cuisine. This makes it possible to combine different cuisine courses to provide an international fusion cuisine experience.

[0054] The menu linkage unit can use the emotion estimation function to identify a dish combination that is most emotionally satisfying to the user and suggest a menu based on that combination. The menu linkage unit can, for example, use the emotion estimation function to identify a dish combination that is most emotionally satisfying to the user. For example, it can suggest a new menu based on a dish combination that impressed the user in the past. The menu linkage unit can also use the emotion estimation function to identify a dish combination that is most emotionally satisfying to the user and suggest a menu based on that combination. For example, it can suggest an optimal dish combination based on the user's emotional response. This can provide a more satisfying dining experience by suggesting a dish combination that is most emotionally satisfying to the user.

[0055] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0056] The music providing unit can customize music based on the user's preferences. For example, if the user likes a particular artist or genre, the music providing unit can select and provide music based on that information. The music providing unit can also analyze the user's past music selection history and suggest the most suitable music. Furthermore, the music providing unit can also allow the user to create their own playlist and provide music based on that playlist. This allows the user to have a music experience tailored to their preferences.

[0057] The video providing unit can estimate the user's emotions and dynamically change the content of the video based on those emotions. For example, if the user is relaxed, it can provide videos of tranquil scenery or nature. If the user is excited, it can provide action scenes or dynamic videos. Furthermore, the video providing unit can adjust the color tone and brightness of the video based on the user's emotions. This makes it possible to provide a video experience that matches the user's emotions.

[0058] The theme direction unit can estimate the user's emotions and dynamically change the progress of the story based on those emotions. For example, if the user is moved, it can add an emotional scene. Or, if the user is excited, it can increase the number of action scenes. Furthermore, the theme direction unit can change the ending of the story based on the user's emotions. This makes it possible to provide a story experience that matches the user's emotions.

[0059] The menu linkage unit can estimate the user's emotions and change the order in which dishes are served based on the emotions. For example, if the user is relaxed, it can start with a light appetizer. On the other hand, if the user is excited, it can serve the main dish earlier. Furthermore, the menu linkage unit can adjust the amount and presentation of dishes based on the user's emotions. This makes it possible to provide a dining experience that matches the user's emotions.

[0060] The theme director can estimate the user's emotions and dynamically change the background sounds and sound effects of the story based on the emotions. For example, if the user is relaxed, calm background sounds can be provided. If the user is excited, fast-paced sound effects can be added. Furthermore, the theme director can adjust the sound effects of the story based on the user's emotions. This allows for an audio experience tailored to the user's emotions.

[0061] The video providing unit provides a function for users to import videos they have taken themselves, thereby enabling a personalized video experience. For example, a user can upload videos they have taken while traveling to the system and play the videos while they are eating. The video providing unit can also enable users to select their favorite videos and provide the videos while they are eating. Furthermore, the video providing unit can also provide a function for users to add music and sound effects to their videos. This allows a personalized experience to be provided using the users' own videos.

[0062] The theme production unit allows the user to select a theme of their choice and provide a story based on that theme. For example, if the user likes fantasy, a fantasy story can be provided. Alternatively, if the user likes history, a historical story can be provided. Furthermore, the theme production unit can provide a function that allows the user to add their favorite characters and scenes to the story. This allows the user to have a story experience based on their favorite theme.

[0063] The menu linking unit allows the user to select a dish and provide a presentation based on that dish. For example, if the user selects a specific dish, music and video that match the dish are provided. The user can also customize a menu and provide a presentation based on that menu. Furthermore, the menu linking unit can allow the user to combine their favorite dishes and provide a presentation based on that combination. This makes it possible to provide a personalized experience based on the dishes selected by the user.

[0064] The theme director can combine stories from different cultures and eras to provide users with a multicultural experience. For example, a story from ancient Egypt can be combined with a modern story. The theme director can also combine stories from different cultures and eras to provide users with a multicultural experience. For example, a story from Asia can be intertwined with a story from Europe. This allows users to have a multicultural experience by combining stories from different cultures and eras.

[0065] The menu linking unit can input the user's dietary preferences and allergy information and suggest optimal menus based on that information. For example, if the user is allergic to a particular ingredient, the unit can suggest menus that avoid that ingredient. Also, if the user has specific dietary preferences, the unit can suggest menus based on those preferences. Furthermore, the menu linking unit can provide a function that allows the user to customize menus based on their health condition and diet goals. This makes it possible to provide a dining experience that is tailored to the user's individual needs.

[0066] The processing flow of the second embodiment will be briefly explained below.

[0067] Step 1: The music provider provides specific music. For example, music from genres such as classical music, pop, and jazz can be provided. The music provider can also select and provide music that matches the theme of the meal. Step 2: The video providing unit provides a video that matches the music provided by the music providing unit. For example, when enjoying Italian cuisine, a video that gives a sense of Italian scenery and culture can be provided. The video providing unit can also select and provide a video based on the theme of the meal. Step 3: The theme production department creates a story based on the theme of the meal using the video provided by the video provider. For example, a dinner themed around the French Revolution can use music and video from that era to create an experience that makes guests feel as if they have traveled back in time. The theme production department can also select and direct a story based on the theme of the meal. Step 4: The menu linking unit performs a performance linked to the meal menu based on the story created by the theme production unit. For example, different music and images can be provided for each course, such as appetizer, main dish, and dessert. The menu linking unit can also perform a performance that allows the viewer to feel a different story for each course.

[0068] 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.

[0069] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0070] 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.

[0071] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0072] 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.

[0073] 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.

[0074] 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.

[0075] 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.

[0076] 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).

[0077] 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.

[0078] 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.

[0079] 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.

[0080] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0081] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0082] 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.

[0083] 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.

[0084] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0085] 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.

[0086] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0087] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0088] 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.

[0089] 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.

[0090] 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.

[0091] 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).

[0092] 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.

[0093] 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.

[0094] 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.

[0095] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0096] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0097] 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.

[0098] 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.

[0099] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0100] 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.

[0101] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0102] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] 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).

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0112] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0113] 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.

[0114] 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.

[0115] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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).

[0121] 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.

[0122] 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."

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0135] 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 music providing section that provides specific music; a video providing unit that provides a video that matches the music provided by the music providing unit; a theme production unit that produces a story based on a meal theme based on the video provided by the video providing unit; a menu linking unit that performs a performance linked to a meal menu based on the story performed by the theme performance unit. A system characterized by:

2. The music providing unit Using generative AI to analyze user emotions in real time and automatically adjust music according to those emotions 2. The system of claim 1.

3. The video providing unit By incorporating the origins of ingredients and the stories of their producers, customers can deepen their understanding and empathy for the ingredients.

2. The system of claim 1.

4. The theme production unit: Dynamically change the progression and ending of the story based on the user's emotions 2. The system of claim 1.

5. The menu linking unit Introducing a system that automatically changes the lighting and decorations on the table to match each course.

2. The system of claim 1.

Images