System

Abstract

An object of a system according to an embodiment is to support anyone to easily cook.SOLUTION: A system includes a cooking procedure display part, a voice guide part, a recipe selection part, an ingredient recognition part, and a progress state management part. The cooking procedure display section displays a cooking procedure. The voice guide unit provides a voice guide. The recipe selection portion selects and customizes a recipe. The ingredient recognition unit recognizes and proposes an ingredient. The progress management unit manages the progress of cooking.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 provide methods for making cooking procedures easy to understand and support, and there is room for improvement.

[0005] The system according to the embodiment aims to support anyone to cook easily. [Means for solving the problem]

[0006] The system according to the embodiment includes a cooking procedure display unit, an audio guide unit, a recipe selection unit, an ingredient recognition unit, and a progress management unit. The cooking procedure display unit displays cooking procedures. The audio guide unit provides audio guidance. The recipe selection unit selects and customizes recipes. The ingredient recognition unit recognizes and suggests ingredients. The progress management unit manages the cooking progress. [Effects of the Invention]

[0007] The system according to the embodiment can help anyone to cook easily. [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 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) A cooking assistance system according to an embodiment of the present invention uses AR glasses to assist with cooking. This system displays cooking steps, provides audio guidance, selects and customizes recipes, recognizes and suggests ingredients, and manages the cooking progress. This allows the cooking assistance system to provide an environment in which anyone can easily enjoy cooking.

[0029] A cooking assistance system according to an embodiment includes a cooking procedure display unit, an audio guide unit, a recipe selection unit, an ingredient recognition unit, and a progress management unit. The cooking procedure display unit displays cooking procedures. For example, AR glasses may display instructions such as "Please chop the onion" and guide the user through the steps in real time. The cooking procedure display unit may also visually guide the user on how to chop ingredients, how to use cooking utensils, and how to adjust the heat. The audio guide unit provides audio guidance. For example, audio instructions such as "Next, add oil to a frying pan and heat over medium heat" may be played. The audio guide unit may also provide audio support as the user cooks. The recipe selection unit selects and customizes recipes. For example, the user may adjust the recipe to suit their preferences, such as "less spicy" or "more vegetables." The recipe selection unit may also select from a variety of recipes. The ingredient recognition unit recognizes and suggests ingredients. For example, by scanning ingredients in the refrigerator with a camera, recipes using those ingredients may be suggested. The ingredient recognition unit may also recognize ingredients the user owns. The progress management unit manages the progress of cooking. For example, it can use a timer function to issue instructions such as "simmer for 5 minutes" and sound an alarm when that time has elapsed. The progress management unit can also monitor the temperature and time during cooking and instruct the next step at the appropriate time. This allows the cooking assistance system according to the embodiment to provide an environment in which anyone can easily enjoy cooking. For example, even a beginner can cook like a professional chef and enjoy a pleasant mealtime with family and friends. It also allows people to cook efficiently even in their busy daily lives and maintain a healthy diet.

[0030] The cooking procedure display unit can track the user's hand movements in real time and guide them to perform precise actions. For example, the cooking procedure display unit can use AR glasses to track the user's hand movements in real time and guide them to perform precise actions. For example, it can provide real-time instructions on how to hold a knife and how to cut, allowing the user to perform the actions accurately. The cooking procedure display unit can also track the user's hand movements using sensor technology or camera technology. For example, a sensor can detect hand movements and guide the actions based on that data. This allows the user's hand movements to be tracked in real time and guided to perform the actions accurately.

[0031] The cooking procedure display unit can provide personalized advice based on the user's past cooking history. The cooking procedure display unit displays personalized advice based on, for example, the user's past cooking history. For example, it provides advice to improve the steps of a cooking that was unsuccessful in the past. The cooking procedure display unit can also store the user's past cooking history and provide advice based on that data. For example, it analyzes the history data and displays the most appropriate advice for the user. This makes it possible to provide personalized advice based on the user's past cooking history.

[0032] The cooking procedure display unit can recognize the surrounding environment and suggest the optimal flow line based on the kitchen layout. For example, the cooking procedure display unit uses AR glasses to recognize the kitchen layout and suggest the optimal flow line. For example, it displays an efficient flow line taking into account the arrangement of cooking utensils and ingredients. The cooking procedure display unit can also recognize the surrounding environment using camera technology and sensor technology. For example, a camera photographs the kitchen layout and suggests a flow line based on that data. This makes it possible to recognize the surrounding environment and suggest the optimal flow line.

[0033] The cooking procedure display unit can display other users' reviews and ratings in real time for reference. The cooking procedure display unit, for example, displays other users' reviews and ratings in real time for reference when creating cooking procedures. For example, it displays ratings and comments on specific procedures. The cooking procedure display unit can also collect review and rating data and display the results based on that data. For example, it can set the review collection method and display format and provide them to the user. This allows other users' reviews and ratings to be displayed in real time for reference.

[0034] The voice guidance unit can have a function to analyze the user's speech in real time and respond immediately to questions or doubts. The voice guidance unit, for example, has a function to analyze the user's speech in real time and respond immediately to questions or doubts. For example, it can provide an immediate answer to a question such as, "How do I do this procedure?" The voice guidance unit can also analyze the user's speech using voice recognition technology. For example, voice recognition software analyzes the speech and responds according to its content. This allows the voice guidance unit to analyze the user's speech in real time and respond immediately to questions or doubts.

[0035] The audio guide unit can have a function to provide advice according to the user's cooking skill level. For example, the audio guide unit can provide audio guidance on simple steps for beginners and advanced techniques for advanced users. The audio guide unit can also evaluate the user's cooking skill level and provide advice based on that data. For example, it can set a skill level index and provide advice based on the evaluation results. This makes it possible to provide advice according to the user's cooking skill level.

[0036] The audio guide unit can add support for different languages ​​and accommodate international users. The audio guide unit can, for example, add support for different languages ​​and accommodate international users. For example, the audio guide unit can provide audio guidance in multiple languages, such as English, French, and Chinese. The audio guide unit can also set a list of supported languages ​​and provide support based on the list. For example, the audio guide unit can provide guidance in an appropriate language depending on the user's language setting. This allows the audio guide unit to add support for different languages ​​and accommodate international users.

[0037] The audio guide unit can provide background music and environmental sounds while cooking to create a cooking atmosphere. The audio guide unit can, for example, provide background music and environmental sounds while cooking to create a cooking atmosphere. For example, it can play relaxing music or natural sounds. The audio guide unit can also set the type of music and the timing of music provision, and provide audio based on that setting. For example, it can play appropriate music depending on the progress of cooking. In this way, background music and environmental sounds can be provided while cooking to create a cooking atmosphere.

[0038] The recipe selection unit can make personalized suggestions taking into account the user's past eating history and health condition. The recipe selection unit can make personalized recipe suggestions taking into account, for example, the user's past eating history and health condition. For example, it can suggest recipes that have been popular in the past or recipes that use healthy ingredients. The recipe selection unit can also store data on the user's eating history and health condition and make suggestions based on that data. For example, it can analyze the history data and suggest recipes that are optimal for the user. This makes it possible to make personalized suggestions taking into account the user's past eating history and health condition.

[0039] The recipe selection unit can learn the user's taste tendencies and suggest the most suitable seasonings and cooking methods. The recipe selection unit, for example, learns the user's taste tendencies and suggests the most suitable seasonings and cooking methods. For example, a recipe that emphasizes spiciness is suggested to a user who likes spicy food. The recipe selection unit can also collect data on the user's taste tendencies and make suggestions based on that data. For example, a taste index is set and suggestions are made based on the evaluation results. In this way, the recipe selection unit can learn the user's taste tendencies and suggest the most suitable seasonings and cooking methods.

[0040] The recipe selection unit can suggest recommended recipes according to the season and weather. The recipe selection unit can suggest recommended recipes according to the season and weather, for example. For example, cold dishes are suggested in the summer and hot dishes are suggested in the winter. The recipe selection unit can also collect data on seasons and weather and make suggestions based on that data. For example, the recipe selection unit can set the seasonal classification and weather type and suggest recipes based on those settings. This makes it possible to suggest recommended recipes according to the season and weather.

[0041] The recipe selection unit can add a function for referring to customization examples of other users. The recipe selection unit, for example, adds a function for referring to customization examples of other users and customizes a recipe. For example, it displays changes to seasonings and cooking techniques made by other users. The recipe selection unit can also collect data on customization examples and display the data based on that data. For example, it sets the method for collecting customization examples and the display format and provides them to the user. This allows the addition of a function for referring to customization examples of other users.

[0042] The ingredient recognition unit can be equipped with a function to evaluate the freshness and quality of ingredients and suggest the optimal timing for use. For example, the ingredient recognition unit can add a function to evaluate the freshness and quality of ingredients and suggest the optimal timing for use. For example, it can evaluate the freshness of vegetables and display the optimal timing for cooking. The ingredient recognition unit can also set indices for freshness and quality and make suggestions based on the evaluation results. For example, it can set an index for freshness and suggest the optimal timing for use based on the evaluation results. This makes it possible to evaluate the freshness and quality of ingredients and suggest the optimal timing for use.

[0043] The ingredient recognition unit can take into account the user's allergy information and suggest safe recipes. The ingredient recognition unit can, for example, take into account the user's allergy information and suggest safe recipes. For example, it can display recipes that do not contain allergenic ingredients. The ingredient recognition unit can also collect allergy information data and make suggestions based on that data. For example, it can suggest the removal of allergenic ingredients or alternative ingredients. This allows the user's allergy information to be taken into account and suggest safe recipes.

[0044] The ingredient recognition unit can add a function to suggest local specialties and seasonal ingredients. The ingredient recognition unit can add, for example, a function to suggest local specialties and seasonal ingredients and recognize ingredients. For example, it can suggest recipes using local specialties. The ingredient recognition unit can also collect data on local specialties and seasonal ingredients and make suggestions based on that data. For example, it can set a list of local specialties and a list of seasonal ingredients and make suggestions based on that setting. This allows for the addition of a function to suggest local specialties and seasonal ingredients.

[0045] The ingredient recognition unit can add a function to refer to reviews and ratings from other users. The ingredient recognition unit, for example, adds a function to refer to reviews and ratings from other users and recognizes ingredients. For example, it displays ratings and comments on specific ingredients. The ingredient recognition unit can also collect review and rating data and display based on that data. For example, it sets the review collection method and display format and provides them to the user. This allows the addition of a function to refer to reviews and ratings from other users.

[0046] The progress status management unit can track the user's hand movements in real time and instruct the next step at precise timing. The progress status management unit, for example, tracks the user's hand movements in real time and instructs the next step at precise timing. For example, it can accurately instruct the timing of stir-frying. The progress status management unit can also track the user's hand movements using sensor technology or camera technology. For example, a sensor detects hand movements and instructs the next step based on that data. This makes it possible to track the user's hand movements in real time and instruct the next step at precise timing.

[0047] The progress management unit can provide personalized advice based on the user's past cooking history. The progress management unit can, for example, provide personalized advice based on the user's past cooking history. For example, it can provide advice to improve the steps of a cooking that was unsuccessful in the past. The progress management unit can also collect data on the user's cooking history and provide advice based on that data. For example, it can analyze the history data and provide optimal advice to the user. This makes it possible to provide personalized advice based on the user's past cooking history.

[0048] The progress management unit can display other users' reviews and ratings in real time for reference. The progress management unit, for example, displays other users' reviews and ratings in real time for reference when creating cooking steps. For example, it displays ratings and comments on specific steps. The progress management unit can also collect review and rating data and display based on that data. For example, it can set the review collection method and display format and provide it to the user. This allows other users' reviews and ratings to be displayed in real time for reference.

[0049] The progress management unit can add support for different languages ​​and accommodate international users. For example, the progress management unit can add support for different languages ​​and accommodate international users. For example, the progress management unit can provide support in multiple languages, such as English, French, and Chinese. The progress management unit can also set a list of supported languages ​​and provide support based on the list. For example, the progress management unit can provide support in an appropriate language depending on the user's language setting. This allows the progress management unit to add support for different languages ​​and accommodate international users.

[0050] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0051] The cooking procedure display unit can track the user's hand movements in real time and guide them to the correct actions. For example, it can instruct the user on how to hold a knife and how to cut in real time, allowing the user to perform the actions accurately. The cooking procedure display unit can also track the user's hand movements using sensor technology and camera technology. For example, a sensor can detect hand movements and guide the user's actions based on that data. This allows the user's hand movements to be tracked in real time and guided to the correct actions.

[0052] The cooking procedure display unit can provide personalized advice based on the user's past cooking history. For example, it can provide advice to improve the cooking procedures for cooking that was unsuccessful in the past. The cooking procedure display unit can also store the user's past cooking history and provide advice based on that data. For example, it can analyze the history data and display the most suitable advice for the user. This makes it possible to provide personalized advice based on the user's past cooking history.

[0053] The cooking procedure display unit can recognize the surrounding environment and suggest optimal flow lines based on the kitchen layout. For example, it displays an efficient flow line taking into account the arrangement of cooking utensils and ingredients. The cooking procedure display unit can also recognize the surrounding environment using camera technology and sensor technology. For example, a camera can capture the kitchen layout and suggest a flow line based on that data. This makes it possible to recognize the surrounding environment and suggest an optimal flow line.

[0054] The cooking procedure display unit can display other users' reviews and ratings in real time for reference. For example, it can display ratings and comments on specific procedures. The cooking procedure display unit can also collect review and rating data and display the results based on that data. For example, it can set the review collection method and display format and provide them to the user. This allows other users' reviews and ratings to be displayed in real time for reference.

[0055] The voice guidance unit can have the function of analyzing the user's speech in real time and responding immediately to questions or doubts. For example, it can provide an immediate response to a question such as, "How do I do this procedure?" The voice guidance unit can also analyze the user's speech using voice recognition technology. For example, voice recognition software can analyze the speech and respond according to its content. This allows the unit to analyze the user's speech in real time and respond immediately to questions or doubts.

[0056] The audio guide unit can have a function to provide advice according to the user's cooking skill level. For example, it can provide audio guidance on simple steps for beginners and advanced techniques for advanced cooks. The audio guide unit can also evaluate the user's cooking skill level and provide advice based on that data. For example, it can set a skill level index and provide advice based on the evaluation results. This allows it to provide advice according to the user's cooking skill level.

[0057] The audio guide unit can add support for different languages ​​and cater to international users. For example, it can provide audio guides in multiple languages, such as English, French, and Chinese. The audio guide unit can also set a list of supported languages ​​and provide support based on that list. For example, it can provide a guide in an appropriate language depending on the user's language setting. This allows it to add support for different languages ​​and cater to international users.

[0058] The processing flow of the first embodiment will be briefly explained below.

[0059] Step 1: The cooking procedure display unit displays the cooking procedure. For example, the AR glasses display instructions such as "Please chop the onion" and guide the user through the procedure in real time. It can also visually show how to chop ingredients, use cooking utensils, adjust the heat, and more. Step 2: The audio guide unit provides audio guidance. For example, audio instructions such as "Next, add oil to a frying pan and heat over medium heat" are played. Audio support can also be provided as the user proceeds with cooking. Step 3: The recipe selection unit selects and customizes recipes. For example, users can adjust the recipe to their preference, such as "less spicy" or "more vegetables." A variety of recipes are also available. Step 4: The ingredient recognition unit recognizes and suggests ingredients. For example, if you scan ingredients in your refrigerator with a camera, it can suggest recipes using those ingredients. It can also recognize ingredients that the user has on hand. Step 5: The progress management unit manages the progress of cooking. For example, it can use the timer function to give instructions such as "simmer for 5 minutes" and sound an alarm when that time has elapsed. It can also monitor the temperature and time during cooking and give instructions on the next step at the appropriate time.

[0060] (Example 2) A cooking assistance system according to an embodiment of the present invention uses AR glasses to assist with cooking. This system displays cooking steps, provides audio guidance, selects and customizes recipes, recognizes and suggests ingredients, and manages the cooking progress. This allows the cooking assistance system to provide an environment in which anyone can easily enjoy cooking.

[0061] A cooking assistance system according to an embodiment includes a cooking procedure display unit, an audio guide unit, a recipe selection unit, an ingredient recognition unit, and a progress management unit. The cooking procedure display unit displays cooking procedures. For example, AR glasses may display instructions such as "Please chop the onion" and guide the user through the steps in real time. The cooking procedure display unit may also visually guide the user on how to chop ingredients, how to use cooking utensils, and how to adjust the heat. The audio guide unit provides audio guidance. For example, audio instructions such as "Next, add oil to a frying pan and heat over medium heat" may be played. The audio guide unit may also provide audio support as the user cooks. The recipe selection unit selects and customizes recipes. For example, the user may adjust the recipe to suit their preferences, such as "less spicy" or "more vegetables." The recipe selection unit may also select from a variety of recipes. The ingredient recognition unit recognizes and suggests ingredients. For example, by scanning ingredients in the refrigerator with a camera, recipes using those ingredients may be suggested. The ingredient recognition unit may also recognize ingredients the user owns. The progress management unit manages the progress of cooking. For example, it can use a timer function to issue instructions such as "simmer for 5 minutes" and sound an alarm when that time has elapsed. The progress management unit can also monitor the temperature and time during cooking and instruct the next step at the appropriate time. This allows the cooking assistance system according to the embodiment to provide an environment in which anyone can easily enjoy cooking. For example, even a beginner can cook like a professional chef and enjoy a pleasant mealtime with family and friends. It also allows people to cook efficiently even in their busy daily lives and maintain a healthy diet.

[0062] The cooking procedure display unit can track the user's hand movements in real time and guide them to perform precise actions. For example, the cooking procedure display unit can use AR glasses to track the user's hand movements in real time and guide them to perform precise actions. For example, it can provide real-time instructions on how to hold a knife and how to cut, allowing the user to perform the actions accurately. The cooking procedure display unit can also track the user's hand movements using sensor technology or camera technology. For example, a sensor can detect hand movements and guide the actions based on that data. This allows the user's hand movements to be tracked in real time and guided to perform the actions accurately.

[0063] The cooking procedure display unit can provide personalized advice based on the user's past cooking history. The cooking procedure display unit displays personalized advice based on, for example, the user's past cooking history. For example, it provides advice to improve the steps of a cooking that was unsuccessful in the past. The cooking procedure display unit can also store the user's past cooking history and provide advice based on that data. For example, it analyzes the history data and displays the most appropriate advice for the user. This makes it possible to provide personalized advice based on the user's past cooking history.

[0064] The cooking procedure display unit can detect the user's stress level using an emotion estimation function and display cooking procedures that will help the user relax. The cooking procedure display unit can, for example, use the emotion estimation function to detect the user's stress level in real time and display cooking procedures that will help the user relax. For example, if the user is highly stressed, easier procedures can be displayed preferentially. The cooking procedure display unit can also detect the user's stress level using technologies such as facial expression recognition and voice analysis. For example, it can analyze changes in facial expression and tone of voice to evaluate the stress level. This makes it possible to detect the user's stress level and display cooking procedures that will help the user relax.

[0065] The cooking procedure display unit can recognize the surrounding environment and suggest the optimal flow line based on the kitchen layout. For example, the cooking procedure display unit uses AR glasses to recognize the kitchen layout and suggest the optimal flow line. For example, it displays an efficient flow line taking into account the arrangement of cooking utensils and ingredients. The cooking procedure display unit can also recognize the surrounding environment using camera technology and sensor technology. For example, a camera photographs the kitchen layout and suggests a flow line based on that data. This makes it possible to recognize the surrounding environment and suggest the optimal flow line.

[0066] The cooking procedure display unit can display other users' reviews and ratings in real time for reference. The cooking procedure display unit, for example, displays other users' reviews and ratings in real time for reference when creating cooking procedures. For example, it displays ratings and comments on specific procedures. The cooking procedure display unit can also collect review and rating data and display the results based on that data. For example, it can set the review collection method and display format and provide them to the user. This allows other users' reviews and ratings to be displayed in real time for reference.

[0067] The cooking procedure display unit can use an emotion estimation function to determine whether the user is enjoying themselves and display entertainment elements to increase the enjoyment. The cooking procedure display unit can, for example, use the emotion estimation function to determine whether the user is enjoying themselves and display entertainment elements to increase the enjoyment. For example, it can display jokes or quizzes while cooking. The cooking procedure display unit can also evaluate the emotional state of the user using technologies such as facial expression recognition and voice analysis. For example, it can analyze changes in facial expression and tone of voice to determine whether the user is enjoying themselves. This makes it possible to determine whether the user is enjoying themselves and display entertainment elements to increase the enjoyment.

[0068] The voice guidance unit can have a function to analyze the user's speech in real time and respond immediately to questions or doubts. The voice guidance unit, for example, has a function to analyze the user's speech in real time and respond immediately to questions or doubts. For example, it can provide an immediate answer to a question such as, "How do I do this procedure?" The voice guidance unit can also analyze the user's speech using voice recognition technology. For example, voice recognition software analyzes the speech and responds according to its content. This allows the voice guidance unit to analyze the user's speech in real time and respond immediately to questions or doubts.

[0069] The audio guide unit can have a function to provide advice according to the user's cooking skill level. For example, the audio guide unit can provide audio guidance on simple steps for beginners and advanced techniques for advanced users. The audio guide unit can also evaluate the user's cooking skill level and provide advice based on that data. For example, it can set a skill level index and provide advice based on the evaluation results. This makes it possible to provide advice according to the user's cooking skill level.

[0070] The voice guidance unit can use the emotion estimation function to provide encouraging or relaxing voice guidance according to the user's emotional state. The voice guidance unit can, for example, use the emotion estimation function to provide encouraging or relaxing voice guidance according to the user's emotional state. For example, if the user is under high stress, a message to help them relax can be played. The voice guidance unit can also evaluate the user's emotional state using technologies such as facial expression recognition and voice analysis. For example, the voice guidance unit can analyze changes in facial expression and tone of voice to determine the user's emotional state. This makes it possible to provide encouraging or relaxing voice guidance according to the user's emotional state.

[0071] The audio guide unit can add support for different languages ​​and accommodate international users. The audio guide unit can, for example, add support for different languages ​​and accommodate international users. For example, the audio guide unit can provide audio guidance in multiple languages, such as English, French, and Chinese. The audio guide unit can also set a list of supported languages ​​and provide support based on the list. For example, the audio guide unit can provide guidance in an appropriate language depending on the user's language setting. This allows the audio guide unit to add support for different languages ​​and accommodate international users.

[0072] The audio guide unit can provide background music and environmental sounds while cooking to create a cooking atmosphere. The audio guide unit can, for example, provide background music and environmental sounds while cooking to create a cooking atmosphere. For example, it can play relaxing music or natural sounds. The audio guide unit can also set the type of music and the timing of music provision, and provide audio based on that setting. For example, it can play appropriate music depending on the progress of cooking. In this way, background music and environmental sounds can be provided while cooking to create a cooking atmosphere.

[0073] The recipe selection unit can make personalized suggestions taking into account the user's past eating history and health condition. The recipe selection unit can make personalized recipe suggestions taking into account, for example, the user's past eating history and health condition. For example, it can suggest recipes that have been popular in the past or recipes that use healthy ingredients. The recipe selection unit can also store data on the user's eating history and health condition and make suggestions based on that data. For example, it can analyze the history data and suggest recipes that are optimal for the user. This makes it possible to make personalized suggestions taking into account the user's past eating history and health condition.

[0074] The recipe selection unit can learn the user's taste tendencies and suggest the most suitable seasonings and cooking methods. The recipe selection unit, for example, learns the user's taste tendencies and suggests the most suitable seasonings and cooking methods. For example, a recipe that emphasizes spiciness is suggested to a user who likes spicy food. The recipe selection unit can also collect data on the user's taste tendencies and make suggestions based on that data. For example, a taste index is set and suggestions are made based on the evaluation results. In this way, the recipe selection unit can learn the user's taste tendencies and suggest the most suitable seasonings and cooking methods.

[0075] The recipe selection unit uses the emotion estimation function to suggest recipes that match the user's mood, thereby increasing the enjoyment of cooking. The recipe selection unit, for example, uses the emotion estimation function to suggest recipes that match the user's mood. For example, if the user is under high stress, the recipe selection unit may suggest dishes that are relaxing. The recipe selection unit can also evaluate the user's mood using technologies such as facial expression recognition and voice analysis. For example, the recipe selection unit may analyze changes in facial expression and tone of voice to determine the user's mood. This allows the recipe selection unit to suggest recipes that match the user's mood, thereby increasing the enjoyment of cooking.

[0076] The recipe selection unit can suggest recommended recipes according to the season and weather. The recipe selection unit can suggest recommended recipes according to the season and weather, for example. For example, cold dishes are suggested in the summer and hot dishes are suggested in the winter. The recipe selection unit can also collect data on seasons and weather and make suggestions based on that data. For example, the recipe selection unit can set the seasonal classification and weather type and suggest recipes based on those settings. This makes it possible to suggest recommended recipes according to the season and weather.

[0077] The recipe selection unit can add a function for referring to customization examples of other users. The recipe selection unit, for example, adds a function for referring to customization examples of other users and customizes a recipe. For example, it displays changes to seasonings and cooking techniques made by other users. The recipe selection unit can also collect data on customization examples and display the data based on that data. For example, it sets the method for collecting customization examples and the display format and provides them to the user. This allows the addition of a function for referring to customization examples of other users.

[0078] The recipe selection unit can use the emotion estimation function to determine whether the user is enjoying themselves and incorporate entertainment elements into the recipe to increase the enjoyment. The recipe selection unit can, for example, use the emotion estimation function to determine whether the user is enjoying themselves and incorporate entertainment elements into the recipe to increase the enjoyment. For example, the recipe selection unit can display jokes or quizzes while cooking. The recipe selection unit can also evaluate the user's emotional state using technologies such as facial expression recognition and voice analysis. For example, the recipe selection unit can analyze changes in facial expression and tone of voice to determine whether the user is enjoying themselves. This allows the recipe selection unit to determine whether the user is enjoying themselves and incorporate entertainment elements into the recipe to increase the enjoyment.

[0079] The ingredient recognition unit can be equipped with a function to evaluate the freshness and quality of ingredients and suggest the optimal timing for use. For example, the ingredient recognition unit can add a function to evaluate the freshness and quality of ingredients and suggest the optimal timing for use. For example, it can evaluate the freshness of vegetables and display the optimal timing for cooking. The ingredient recognition unit can also set indices for freshness and quality and make suggestions based on the evaluation results. For example, it can set an index for freshness and suggest the optimal timing for use based on the evaluation results. This makes it possible to evaluate the freshness and quality of ingredients and suggest the optimal timing for use.

[0080] The ingredient recognition unit can take into account the user's allergy information and suggest safe recipes. The ingredient recognition unit can, for example, take into account the user's allergy information and suggest safe recipes. For example, it can display recipes that do not contain allergenic ingredients. The ingredient recognition unit can also collect allergy information data and make suggestions based on that data. For example, it can suggest the removal of allergenic ingredients or alternative ingredients. This allows the user's allergy information to be taken into account and suggest safe recipes.

[0081] The ingredient recognition unit uses an emotion estimation function to suggest ingredients that match the user's mood, thereby increasing the enjoyment of cooking. The ingredient recognition unit, for example, uses the emotion estimation function to suggest ingredients that match the user's mood. For example, if the user is under high stress, the ingredient recognition unit may suggest ingredients that will help them relax. The ingredient recognition unit can also evaluate the user's mood using techniques such as facial expression recognition and voice analysis. For example, it may analyze changes in facial expression and tone of voice to determine the user's mood. This allows the ingredient recognition unit to suggest ingredients that match the user's mood, thereby increasing the enjoyment of cooking.

[0082] The ingredient recognition unit can add a function to suggest local specialties and seasonal ingredients. The ingredient recognition unit can add, for example, a function to suggest local specialties and seasonal ingredients and recognize ingredients. For example, it can suggest recipes using local specialties. The ingredient recognition unit can also collect data on local specialties and seasonal ingredients and make suggestions based on that data. For example, it can set a list of local specialties and a list of seasonal ingredients and make suggestions based on that setting. This allows for the addition of a function to suggest local specialties and seasonal ingredients.

[0083] The ingredient recognition unit can add a function to refer to reviews and ratings from other users. The ingredient recognition unit, for example, adds a function to refer to reviews and ratings from other users and recognizes ingredients. For example, it displays ratings and comments on specific ingredients. The ingredient recognition unit can also collect review and rating data and display based on that data. For example, it sets the review collection method and display format and provides them to the user. This allows the addition of a function to refer to reviews and ratings from other users.

[0084] The ingredient recognition unit can use an emotion estimation function to determine whether the user is enjoying themselves and incorporate entertainment elements to enhance the enjoyment into the ingredient suggestions. The ingredient recognition unit can, for example, use the emotion estimation function to determine whether the user is enjoying themselves and incorporate entertainment elements to enhance the enjoyment into the ingredient suggestions. For example, it can display jokes or quizzes while cooking. The ingredient recognition unit can also evaluate the user's emotional state using technologies such as facial expression recognition and voice analysis. For example, it can analyze changes in facial expression and tone of voice to determine whether the user is enjoying themselves. This makes it possible to determine whether the user is enjoying themselves and incorporate entertainment elements to enhance the enjoyment into the ingredient suggestions.

[0085] The progress status management unit can track the user's hand movements in real time and instruct the next step at precise timing. The progress status management unit, for example, tracks the user's hand movements in real time and instructs the next step at precise timing. For example, it can accurately instruct the timing of stir-frying. The progress status management unit can also track the user's hand movements using sensor technology or camera technology. For example, a sensor detects hand movements and instructs the next step based on that data. This makes it possible to track the user's hand movements in real time and instruct the next step at precise timing.

[0086] The progress management unit can provide personalized advice based on the user's past cooking history. The progress management unit can, for example, provide personalized advice based on the user's past cooking history. For example, it can provide advice to improve the steps of a cooking that was unsuccessful in the past. The progress management unit can also collect data on the user's cooking history and provide advice based on that data. For example, it can analyze the history data and provide optimal advice to the user. This makes it possible to provide personalized advice based on the user's past cooking history.

[0087] The progress management unit can display other users' reviews and ratings in real time for reference. The progress management unit, for example, displays other users' reviews and ratings in real time for reference when creating cooking steps. For example, it displays ratings and comments on specific steps. The progress management unit can also collect review and rating data and display based on that data. For example, it can set the review collection method and display format and provide it to the user. This allows other users' reviews and ratings to be displayed in real time for reference.

[0088] The progress management unit can add support for different languages ​​and accommodate international users. For example, the progress management unit can add support for different languages ​​and accommodate international users. For example, the progress management unit can provide support in multiple languages, such as English, French, and Chinese. The progress management unit can also set a list of supported languages ​​and provide support based on the list. For example, the progress management unit can provide support in an appropriate language depending on the user's language setting. This allows the progress management unit to add support for different languages ​​and accommodate international users.

[0089] The progress status management unit can use the emotion estimation function to determine whether the user is enjoying themselves and incorporate entertainment elements to increase the enjoyment into the progress status management. The progress status management unit can, for example, use the emotion estimation function to determine whether the user is enjoying themselves and incorporate entertainment elements to increase the enjoyment into the progress status management. For example, jokes or quizzes can be displayed while cooking. The progress status management unit can also evaluate the user's emotional state using technologies such as facial expression recognition and voice analysis. For example, it can analyze changes in facial expressions and tone of voice to determine whether the user is enjoying themselves. This makes it possible to determine whether the user is enjoying themselves and incorporate entertainment elements to increase the enjoyment into the progress status management.

[0090] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0091] The cooking procedure display unit can track the user's hand movements in real time and guide them to the correct actions. For example, it can instruct the user on how to hold a knife and how to cut in real time, allowing the user to perform the actions accurately. The cooking procedure display unit can also track the user's hand movements using sensor technology and camera technology. For example, a sensor can detect hand movements and guide the user's actions based on that data. This allows the user's hand movements to be tracked in real time and guided to the correct actions.

[0092] The cooking procedure display unit can provide personalized advice based on the user's past cooking history. For example, it can provide advice to improve the cooking procedures for cooking that was unsuccessful in the past. The cooking procedure display unit can also store the user's past cooking history and provide advice based on that data. For example, it can analyze the history data and display the most suitable advice for the user. This makes it possible to provide personalized advice based on the user's past cooking history.

[0093] The cooking procedure display unit can detect the user's stress level using an emotion estimation function and display cooking procedures that will help them relax. For example, if stress is high, it will prioritize displaying simpler procedures. The cooking procedure display unit can also detect the user's stress level using technologies such as facial expression recognition and voice analysis. For example, it can analyze changes in facial expressions and tone of voice to evaluate the stress level. This makes it possible to detect the user's stress level and display cooking procedures that will help them relax.

[0094] The cooking procedure display unit can recognize the surrounding environment and suggest optimal flow lines based on the kitchen layout. For example, it displays an efficient flow line taking into account the arrangement of cooking utensils and ingredients. The cooking procedure display unit can also recognize the surrounding environment using camera technology and sensor technology. For example, a camera can capture the kitchen layout and suggest a flow line based on that data. This makes it possible to recognize the surrounding environment and suggest an optimal flow line.

[0095] The cooking procedure display unit can display other users' reviews and ratings in real time for reference. For example, it can display ratings and comments on specific procedures. The cooking procedure display unit can also collect review and rating data and display the results based on that data. For example, it can set the review collection method and display format and provide them to the user. This allows other users' reviews and ratings to be displayed in real time for reference.

[0096] The cooking procedure display unit can use an emotion estimation function to determine whether the user is enjoying themselves and display entertainment elements to enhance the enjoyment. For example, it can display jokes or quizzes while cooking. The cooking procedure display unit can also use technologies such as facial expression recognition and voice analysis to evaluate the user's emotional state. For example, it can analyze changes in facial expression and tone of voice to determine whether the user is enjoying themselves. This allows it to determine whether the user is enjoying themselves and display entertainment elements to enhance the enjoyment.

[0097] The voice guidance unit can have the function of analyzing the user's speech in real time and responding immediately to questions or doubts. For example, it can provide an immediate response to a question such as, "How do I do this procedure?" The voice guidance unit can also analyze the user's speech using voice recognition technology. For example, voice recognition software can analyze the speech and respond according to its content. This allows the unit to analyze the user's speech in real time and respond immediately to questions or doubts.

[0098] The audio guide unit can have a function to provide advice according to the user's cooking skill level. For example, it can provide audio guidance on simple steps for beginners and advanced techniques for advanced cooks. The audio guide unit can also evaluate the user's cooking skill level and provide advice based on that data. For example, it can set a skill level index and provide advice based on the evaluation results. This allows it to provide advice according to the user's cooking skill level.

[0099] The voice guidance unit can use the emotion estimation function to provide encouraging or relaxing voice guidance according to the user's emotional state. For example, if the user is highly stressed, a message to help them relax can be played. The voice guidance unit can also evaluate the user's emotional state using technologies such as facial expression recognition and voice analysis. For example, it can analyze changes in facial expressions and tone of voice to determine the user's emotional state. This allows it to provide encouraging or relaxing voice guidance according to the user's emotional state.

[0100] The audio guide unit can add support for different languages ​​and cater to international users. For example, it can provide audio guides in multiple languages, such as English, French, and Chinese. The audio guide unit can also set a list of supported languages ​​and provide support based on that list. For example, it can provide a guide in an appropriate language depending on the user's language setting. This allows it to add support for different languages ​​and cater to international users.

[0101] The processing flow of the second embodiment will be briefly explained below.

[0102] Step 1: The cooking procedure display unit displays the cooking procedure. For example, the AR glasses display instructions such as "Please chop the onion" and guide the user through the procedure in real time. It can also visually show how to chop ingredients, use cooking utensils, adjust the heat, and more. Step 2: The audio guide unit provides audio guidance. For example, audio instructions such as "Next, add oil to a frying pan and heat over medium heat" are played. Audio support can also be provided as the user proceeds with cooking. Step 3: The recipe selection unit selects and customizes recipes. For example, users can adjust the recipe to their preference, such as "less spicy" or "more vegetables." A variety of recipes are also available. Step 4: The ingredient recognition unit recognizes and suggests ingredients. For example, if you scan ingredients in your refrigerator with a camera, it can suggest recipes using those ingredients. It can also recognize ingredients that the user has on hand. Step 5: The progress management unit manages the progress of cooking. For example, it can use the timer function to give instructions such as "simmer for 5 minutes" and sound an alarm when that time has elapsed. It can also monitor the temperature and time during cooking and give instructions on the next step at the appropriate time.

[0103] 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.

[0104] 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.

[0105] 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.

[0106] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0107] 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.

[0108] 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.

[0109] 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.

[0110] 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.

[0111] 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).

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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.

[0119] 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.

[0120] 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.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 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.

[0123] 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.

[0124] 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.

[0125] 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.

[0126] 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).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0137] 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.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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).

[0142] 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.

[0143] 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.

[0144] 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.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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.

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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.

[0154] 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.

[0155] 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).

[0156] 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 "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[0157] 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."

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] The hardware resource for executing a specific process can be any of the following processors: A CPU is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A dedicated electrical circuit, such as a field-programmable gate array (FPGA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC), is a processor with a circuit configuration specifically designed to execute a specific process. Each processor has built-in or connected memory, and uses the memory to execute the specific process.

[0164] 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.

[0165] 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.

[0166] 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.

[0167] 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.

[0168] 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.

[0169] 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]

[0170] 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 cooking procedure display unit that displays cooking procedures; an audio guide unit that provides an audio guide; a recipe selection section for selecting and customizing recipes; an ingredient recognition unit that recognizes and suggests ingredients; A progress management unit that manages the progress of cooking. A system characterized by:

2. The cooking procedure display unit Tracks the user's hand movements in real time and guides them to precise movements 2. The system of claim 1.

3. The cooking procedure display unit Recognizes the surrounding environment and suggests optimal flow of movement based on the kitchen layout 2. The system of claim 1.

4. The voice guide unit It has the ability to analyze user utterances in real time and respond immediately to questions and doubts.

2. The system of claim 1.

5. The recipe selection unit Providing personalized suggestions based on the user's dietary history and health status 2. The system of claim 1.

6. The ingredient recognition unit Equipped with a function to evaluate the freshness and quality of the ingredients and suggest the best time to use them 2. The system of claim 1.

7. The progress status management unit Tracking the user's hand movements in real time and instructing the next step with precise timing 2. The system of claim 1.

8. The cooking procedure display unit Using emotion estimation, the app detects the user's stress level and displays cooking instructions to help them relax.

2. The system of claim 1.

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