system

Abstract

We provide the system. [Solution] A means of converting voice input from a user into text data, A means for generating recipes based on the user's age, skill level, allergy information, and available ingredients, Means for displaying the generated recipe as visual and audio instructions, A means of monitoring user actions and detecting dangerous situations, Means of issuing warnings for detected dangers, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, the number of dual-income families and busy parents is increasing, and the need for children left alone to prepare meals safely by themselves is on the rise. However, for children with little cooking experience, the risks associated with handling ingredients and the cooking process remain high, and it is difficult to prepare safe and healthy meals. Therefore, there is a need to provide an environment where children can learn to cook safely and parents can cook with confidence even when they are not at home.

Means for Solving the Problems

[0005] This invention provides a means for children to easily select the dish they want to make by using speech recognition technology that converts user voice input into text data. Furthermore, it includes means to generate recipes based on the user's age, skill level, allergy information, and available ingredients, and to provide these recipes as visual and audio guides, making cooking procedures easy for even novice cooks to understand. In addition, it monitors the user's actions during cooking and provides means for danger detection and warning to ensure safety, thereby preventing accidents during cooking. This enables children to learn to cook safely and enjoyably, and to cook independently.

[0006] "Voice input" is a data format used to capture spoken words from a user into a machine.

[0007] "Text data" is a data format that represents information as a string of characters.

[0008] A "user" is any user of the system, including children.

[0009] "Age" refers to information indicating the number of years that have passed since the user was born.

[0010] "Skill level" refers to information that indicates the level of a user's specific abilities or skills.

[0011] "Allergy information" refers to information about a user's hypersensitivity reaction to a particular food or substance.

[0012] "Ingredients" refer to the food items and components used to make a dish.

[0013] A "recipe" is information that includes instructions on how to prepare a dish and lists the ingredients to be used.

[0014] "Visual instructions" refer to information that guides the user through procedures using illustrations and text displayed on the screen.

[0015] "Voice instruction" refers to information that conveys procedures and cautions to the user through voice.

[0016] "Monitoring" means constantly observing and recording the user's actions and environment.

[0017] "Danger" is a concept indicating a situation that may harm the user.

[0018] "Warning" is a message that conveys to the user that there is danger and prompts attention.

Brief Explanation of Drawings

[0019] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] [[ID=2…]]It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] …It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment…. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [[ID=…]] [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0020] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0021] First, the terms used in the following description will be explained.

[0022] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0023] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0024] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0025] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0027] [First Embodiment]

[0028] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0029] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0032] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0035] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0039] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0040] This invention is a system for children to safely learn to cook and cook independently, integrating functions such as voice input, text conversion, recipe generation, visual and audio guidance, hazard detection, and warning issuance. The system mainly consists of a server, terminals, and users.

[0041] The server is the core of the system, hosting an AI model that processes user input. Once the user's voice input is converted to text data, the server references this data and retrieves relevant information from the recipe database. Furthermore, it customizes the recipe based on the user's age, skill level, and allergy information. The server then formats the final recipe and cooking instructions and sends them to the device as visual and audio guides.

[0042] The terminal is a user-operated device that provides an interface between the user and the server through visual animations and audio guidance. The terminal receives recipes and instructions from the server and presents them to the user sequentially. It guides the user to the next step according to their progress and issues warnings as needed.

[0043] The user is the central user of the system, interacting with it through a terminal and performing cooking according to their wishes. For example, if the user enters "I want to make chocolate cookies" into the terminal, the entire system process begins. The user follows the guide on the terminal, prepares the ingredients, and proceeds with cooking according to the instructions. The terminal can provide real-time warnings for high-risk steps, such as when using a knife or setting the oven temperature.

[0044] Thus, this system provides an embodiment of a system that, by combining visual and auditory aids, enables users to easily learn how to cook and to proceed with cooking safely and efficiently.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user speaks into the device and enters the name of the dish they want to make. For example, they might say, "I want to make chocolate cookies."

[0048] Step 2:

[0049] The device records the user's voice and converts it into text data using speech recognition technology. This text data includes the name of the dish.

[0050] Step 3:

[0051] The device sends a request to the server containing the converted text data. This request also includes user information (age, skill level, allergy information, etc.).

[0052] Step 4:

[0053] The server receives the request and retrieves the appropriate recipe from the database based on the user information. Furthermore, it customizes the recipe to suit the user's needs.

[0054] Step 5:

[0055] The server formats customized recipes and cooking instructions into visual and audio guide formats and sends them to the terminal.

[0056] Step 6:

[0057] The device receives the data sent to it and provides the user with visual animations and audio guidance. This allows the user to proceed with cooking while receiving instructions step by step.

[0058] Step 7:

[0059] The user gathers the ingredients and begins cooking based on the instructions on the device. They follow the guide to perform the specific steps.

[0060] Step 8:

[0061] The device monitors the user's actions while cooking and ensures safety by issuing warnings when it detects dangers such as the use of knives or open flames.

[0062] Step 9:

[0063] If a user has any questions or concerns, they can ask them via voice through their device. For example, they might ask, "What should I do next?"

[0064] Step 10:

[0065] The server receives the user's question, generates an appropriate response, and sends it to the terminal.

[0066] Step 11:

[0067] The terminal communicates responses from the server to the user via voice and visuals, supporting the cooking process.

[0068] Step 12:

[0069] The user completes all cooking steps and the dish is finished. The device provides feedback by notifying the user with "Great job! Your dish is ready!"

[0070] (Example 1)

[0071] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0072] The problem this invention aims to solve is that it is difficult for users with limited skills, especially children, to learn to cook safely and effectively. There is a need to reduce the risk of accidents due to improper understanding of cooking procedures and dangerous cooking processes, and to support users so they can cook with confidence.

[0073] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0074] In this invention, the server includes a processing unit that converts user input voice into text data, a processing unit that constructs cooking procedures based on age, skill level, and health information, and a processing unit that provides the generated cooking procedures in both display and audio format. This enables users to enjoy a safe and effective cooking experience tailored to their own circumstances and abilities.

[0075] "Conversion of user-input speech to text data" is the process of recognizing the speech spoken by the user as a digital signal and converting it into text format.

[0076] "Cooking procedure configuration based on age, skill level, and health information" means selecting the most suitable recipes and procedures according to the user's attributes and customizing them to support learning and practicing cooking.

[0077] "Displaying and providing generated cooking instructions via audio" means guiding users through cooking procedures using a visual and audio interface designed for easy understanding.

[0078] "Monitoring user work status" means tracking the user's cooking process and evaluating the progress and safety of the process.

[0079] "Detecting safety threats" is a process that involves detecting potentially dangerous actions or conditions during cooking to prevent accidents.

[0080] "Implementing a warning" means prompting users to take precautions using audio or visual means and warning them to proceed with cooking safely.

[0081] This invention is a system aimed at enabling users to safely learn to cook and to cook independently. This system consists of a server, terminals, and users.

[0082] The server plays a central role in the system, utilizing a speech recognition API to convert user-input speech into text data. Here, the speech data is converted into text using Google's (registered trademark) speech recognition API or general speech recognition software. Based on this text data, a generative AI model is used to generate recipes. A general natural language processing model can be used as the generative AI model; a prompt might be "Generate a simple and safe chocolate cookie recipe for an 8-year-old child." Furthermore, the server accesses a database to customize the recipe, taking into account the user's age, skill level, and health information. The customized recipe is then formatted as a visual and audio guide and sent to the terminal.

[0083] The terminal is a device that guides the user through procedures using visual and audio guidance transmitted from the server. Sequential instructions are provided via animation and audio on devices such as tablets and smartphones. The terminal can monitor the user's cooking progress and provide safety warnings as needed. For example, when using a knife, the terminal will issue a real-time audio warning.

[0084] The user is the one who operates the terminal and follows the guide to cook. The user voice-inputs the desired dish into the terminal, prepares the ingredients based on the provided guide, and safely proceeds with cooking according to the procedure. For example, the user tells the server that they want to make chocolate cookies and proceeds with cooking according to the provided recipe and procedure.

[0085] In this way, this system can provide support for users to learn cooking in an easy-to-understand and safe manner.

[0086] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0087] Step 1:

[0088] The user inputs the desired recipe by voice into the terminal. For example, they might say, "I want to make chocolate cookies." This voice input becomes the input data.

[0089] Step 2:

[0090] The terminal transmits the recorded audio data as a digital signal to the server. This becomes the input to the server.

[0091] Step 3:

[0092] The server uses a speech recognition API to convert the received audio data into text data. This conversion process outputs the text "I want to make chocolate cookies." Here, analog data (voice input) is processed into digital text data.

[0093] Step 4:

[0094] The server inputs a prompt into the generating AI model. Based on the prompt, "Generate a simple and safe chocolate cookie recipe for an 8-year-old child," the AI ​​model generates recipe data. This becomes the input data for the next process.

[0095] Step 5:

[0096] The server reviews the generated recipe data and customizes it, taking into account the user's profile information (age, skill level, health information). For example, it might adjust the weight of ingredients to make it easier for children to use, or simplify the process. This results in a recipe optimized for the user.

[0097] Step 6:

[0098] The server formats the customized recipe as a visual and audio guide and sends it to the terminal. This is the input data for the terminal.

[0099] Step 7:

[0100] The device guides the user through the cooking process visually and audibly, based on the received guide data. Each step is clearly displayed with animation and audio, following the recipe order.

[0101] Step 8:

[0102] The terminal monitors the user's actions in real time and provides warnings via voice alerts and on-screen displays during potentially dangerous processes. For example, it issues warnings when using knives or when heating an oven. This output is intended to ensure the user's safety.

[0103] Step 9:

[0104] The user follows visual and audio guidance to complete the cooking process. This allows the user to complete the dish safely and effectively. The output is the finished dish.

[0105] (Application Example 1)

[0106] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0107] A support system for children to learn to cook safely and effectively requires the provision of flexible cooking procedures tailored to the child's age and skill level, as well as real-time hazard detection and warning. Furthermore, an interactive interface is needed to engage children's interest and encourage their active participation in cooking.

[0108] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0109] In this invention, the server includes means for converting voice input from the user into text data, means for generating cooking instructions based on the user's age, skill level, allergy information, and available ingredients, means for displaying the generated cooking instructions as visual and audio instructions, and means for monitoring the user's actions and detecting dangerous situations. This enables children to learn to cook safely and in an engaging way.

[0110] "Means of converting voice input from users into text data" refers to technology that converts information in audio format into digital text format.

[0111] "Means for generating cooking instructions based on the user's age, skill level, allergy information, and available ingredients" refers to an algorithm or program that creates optimal cooking instructions tailored to the user.

[0112] "Means for displaying generated cooking instructions as visual and audio instructions" refers to a display device or program for visually and aurally communicating generated instructions to the user.

[0113] "Means of monitoring user actions and detecting dangerous situations" refers to monitoring functions using sensors and software to track user behavior and determine safety.

[0114] "Means for providing a visual interface" refers to a design or platform for visually facilitating the exchange of information between the user and the system.

[0115] "Means of tracking user behavior and evaluating safety based on predetermined criteria" refers to algorithms or systems that analyze behavioral logs and automatically make safety judgments.

[0116] The system for implementing the present invention consists of three main elements: a server, a terminal, and a user. The server is the core of the system, converting the voice input provided by the user into text and generating cooking instructions based on that. Specifically, the server uses the Google Speech-to-Text API to convert voice into text data. This text data is processed by a recipe generation engine that uses an AI model hosted on the server, for example, OpenAI®'s GPT-3®. The engine takes into account the user's age, skill level, allergy information, and available ingredients to generate the optimal cooking instructions.

[0117] The terminal is the device that serves as the interface with the user. The terminal receives cooking instructions sent from the server and can utilize development platforms such as Unity and Flutter® to guide the user visually and audibly. The terminal also implements voice guidance using the Speech Synthesis API. It also has the ability to monitor user behavior in real time, recognize dangerous situations using libraries such as OpenCV, and issue warnings.

[0118] Users interact with the system through their device and utilize it to safely learn how to cook their desired dishes. For example, if an 8-year-old child requests to "make spaghetti," the AI ​​model receives the following prompt: "Please create a recipe that allows a child to safely and easily make spaghetti. The child is 8 years old, and only household equipment is allowed." Based on this information, the system generates safe and easy-to-understand instructions for children and guides them visually and audibly through the device. In this way, the present invention makes it possible to provide an environment in which users can learn to cook with interest and actively.

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] The user inputs cooking information into the device using voice. This voice input is based on the user's request and includes specific details such as the dish they want to make and any other requirements.

[0122] Step 2:

[0123] The device converts audio data into text data using the Google Speech-to-Text API. This conversion transforms the audio content into a digital format that the server can understand. The input is audio data, and the output is the corresponding text data.

[0124] Step 3:

[0125] The server receives input text and generates a prompt using an AI model (e.g., OpenAI GPT-3). This prompt contains information to output optimized cooking instructions based on the user's request. The input is the converted text, and the output is the prompt.

[0126] Step 4:

[0127] The server uses the generated prompts to create customized cooking instructions based on an AI model. This process takes into account the user's age, skill level, allergy information, and available ingredients. The input is the prompts, and the output is the optimized cooking instructions.

[0128] Step 5:

[0129] The device receives cooking instructions sent from the server and generates visual and audio guides using Unity and Flutter. These guides are designed to make it easy for the user to intuitively understand the steps. The input is customized cooking instructions, and the output is a visual and audio interface.

[0130] Step 6:

[0131] The user follows the terminal's instructions to proceed with cooking. The terminal monitors the user's actions and movements in real time and detects dangerous situations using libraries such as OpenCV. Input is user action data, and output is a warning alert in case of danger.

[0132] Step 7:

[0133] If the device detects a hazard, it immediately issues an audible and visual warning, prompting the user to take appropriate safety measures. At this time, the user's progress is temporarily paused, and the next step is not guided until the situation is safe. The input is hazard detection information, and the output is the warning interface.

[0134] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0135] This invention is a system that enables users, including children, to safely learn to cook and cook independently. The system has means to convert voice input into text data, generate recipes based on the user's age, skill level, allergy information, and available ingredients, and provide visual and audio guidance. It also has a function to monitor user operations, detect dangers, and issue warnings. In addition, the invention incorporates an emotion engine, providing a new ability to recognize user emotions and adjust the system's operation accordingly.

[0136] The server receives the user's voice input and converts it into text data using speech recognition technology. Based on this, the server refers to user data, retrieves appropriate recipes from the database, and customizes them. The server further analyzes the user's emotional state using an emotion engine and suggests or adjusts recipes according to the user's emotions. The results are then formatted into visual and audio guide formats and sent to the terminal.

[0137] The device provides the user with visual animations and audio guidance based on data sent from the server. The device understands the user's emotional state and adjusts the tone and content of the guidance accordingly. For example, if the user is anxious, it can provide more detailed explanations or words of encouragement. The device also monitors the user's actions and issues warnings if it detects danger through sensors or cameras. The emotion engine plays a crucial role here as well, adjusting the priority and delivery of warnings to match the user's mental state.

[0138] When a user begins cooking, they enter the name of the dish they want to make into the device. They then proceed with cooking according to the device's instructions, but especially if they are emotionally unstable or doing it for the first time, the device provides support that takes the user's emotions into consideration. For example, if cooking is not going as planned, the device senses the user's emotions and provides support such as, "It's okay, let's relax and continue."

[0139] These comprehensive features allow the system to provide users with a safe and enjoyable cooking experience, not only by teaching them how to cook, but also by offering emotional support.

[0140] The following describes the processing flow.

[0141] Step 1:

[0142] The user speaks into the device to specify the dish they want to make. For example, they might say, "I want to make lasagna."

[0143] Step 2:

[0144] The device records the user's voice and uses a speech recognition engine to convert the voice data into text data. This text includes the user's cooking preferences.

[0145] Step 3:

[0146] The terminal sends the converted text data to the server and sends a request that includes user information, age, skill level, and allergy information.

[0147] Step 4:

[0148] The server receives the request and retrieves the corresponding recipe from the database. It then adjusts the recipe according to the user's skill level and then customizes it.

[0149] Step 5:

[0150] The server customizes recipes based on the user's age, skill level, and allergy information, and uses an emotion engine to analyze additional data (e.g., voice and facial expressions) to estimate the user's emotions.

[0151] Step 6:

[0152] Based on the user's emotions analyzed by the server, the system formats customized recipes and guides as audio and visual data and sends them to the device.

[0153] Step 7:

[0154] The device receives data from the server, visually displays recipe instructions on the screen, and provides voice guidance to the user. The instructions are delivered in a calm tone that is adjusted to the user's emotional state.

[0155] Step 8:

[0156] The user follows the visual and audio guidance on the device to perform the cooking process. This includes gathering ingredients and following instructions.

[0157] Step 9:

[0158] The device monitors user actions through sensors and user feedback, and issues warnings when danger is anticipated, such as the use of knives or firearms. The strength of the warning is adjusted according to the user's emotions.

[0159] Step 10:

[0160] If a user has questions while cooking, they can contact the device. For example, they might ask, "Could you explain in more detail?"

[0161] Step 11:

[0162] The server receives the user's question, analyzes its content, generates an appropriate answer, and sends it to the terminal.

[0163] Step 12:

[0164] The terminal communicates responses from the server to the user via voice and text, supporting the progress of the cooking process.

[0165] Step 13:

[0166] The user completes all steps and finishes cooking. The device provides feedback saying, "Great job! Your dish is finished!" and praises the user.

[0167] (Example 2)

[0168] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0169] In modern society, learning and practicing cooking safely is an important skill. However, especially for children and beginners, the dangers posed by the tools and heating equipment used in the cooking process make it difficult to learn with peace of mind. Furthermore, it is difficult to meet individual needs because it is not possible to provide guides that are appropriately tailored to the learner's skill level and mental state. As a result, the cooking learning process can become inadequate and stressful, potentially leading to decreased motivation and failure to ensure safety.

[0170] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0171] In this invention, the server includes means for converting acoustic input into textual information, means for generating procedures based on the user's age, skill level, allergy information, and available ingredients, and means for guiding the generated procedures visually and audibly. This makes it possible to provide an optimized cooking learning environment for each individual user while ensuring user safety.

[0172] "Means for converting audio input into textual information" refers to technology that converts audio data spoken by a user into digital text, and has the function of converting speech into text using speech recognition technology.

[0173] "Textual information" refers to text data converted from audio data and recorded in digital format, enabling further processing and analysis on the server.

[0174] "Means for generating procedures based on the user's age, skill level, allergy information, and available ingredients" refers to technology that utilizes algorithms and databases to suggest the optimal cooking procedure according to the individual user's basic information and circumstances.

[0175] "Means of providing guidance visually and audibly" refers to technologies that use display devices and speech synthesis technology to provide guidance information in order to present the generated cooking procedures in a user-friendly format.

[0176] "Means for monitoring user actions and detecting dangerous situations" refers to technologies that monitor user actions in real time through sensors and cameras to identify potential dangers.

[0177] "Warning mechanisms" refer to technologies that communicate messages through visual and auditory means to warn or alert users to identified dangers.

[0178] "Means for analyzing emotional states and adjusting procedures and warnings accordingly" refers to emotion analysis technology that identifies the user's emotions and dynamically optimizes cooking procedures and warning content based on the results.

[0179] This system is designed to allow users to learn to cook safely and efficiently. First, the user voice-inputs the desired dish into the terminal. The terminal uses its built-in microphone to capture the voice data and transmits it to the server.

[0180] The server converts audio data into text data using speech recognition technology. A commonly used speech recognition service is employed for this purpose. For example, a general speech recognition platform can be used as a means of "converting acoustic input into text information." Based on the converted text data, the server generates the optimal cooking procedure (recipe) from a database, taking into account the user's age, skill level, allergy information, and available ingredients. A general database management system is used for this.

[0181] Next, the server uses sentiment analysis technology to evaluate the user's emotional state. This analysis can utilize a general sentiment analysis API. Based on the evaluation results, it generates appropriate instructions and warning messages for the user's situation. For example, if the user is feeling anxious, detailed and reassuring guidance is provided.

[0182] The server then sends the adjusted recipe and guide to the terminal. The terminal provides visual and audio guidance to the user based on the received data. A display device is used for visual guidance, and text-to-speech technology is used for audio guidance. This embodiment allows the user to receive guidance tailored to their current situation. For example, if the user wants to know how to make omurice, they might input the following prompt: "Please tell me an easy way to make omurice. I would appreciate it if you could also provide the necessary ingredients and specific steps."

[0183] This system allows users to learn cooking techniques safely and in a way that is tailored to their individual circumstances. Furthermore, if a hazard is anticipated, the terminal will issue appropriate warnings through real-time monitoring, ensuring safety during cooking.

[0184] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0185] Step 1:

[0186] The user inputs their cooking preferences and related information by voice into the terminal. The terminal captures this audio data through its microphone and saves it as an audio file. The input is the user's voice, and the output is data in audio file format. The terminal compresses the audio file on-device and prepares it for transfer to the server.

[0187] Step 2:

[0188] The server receives audio files sent from the terminal. The received audio files are analyzed through a speech recognition system and converted into text data. Here, the input is an audio file, and the output is text data. The server processes this text data and extracts information such as the name of the dish and the required ingredients.

[0189] Step 3:

[0190] The server searches for the optimal recipe based on the extracted text data and references the user's basic information. Input consists of text data and user information, while output is customized recipe data. The server executes appropriate database queries, taking into account the user's age, skill level, allergy information, and available ingredients.

[0191] Step 4:

[0192] The server uses an emotion analysis engine to analyze text data and available historical information from the user to evaluate their emotional state. The input is text data and associated historical information, and the output is the evaluation result of the emotional state. Based on this result, the server flexibly adjusts the recipe content and guidance methods.

[0193] Step 5:

[0194] The server formats the adjusted recipes and guidance methods into visual and audio guidance formats and sends them to the terminal. The input is customized recipe data and sentiment evaluation results, and the output is formatted guide data.

[0195] Step 6:

[0196] The terminal displays visual guidance to the user based on guide data received from the server and provides voice guidance using speech synthesis technology. The input is guide data, and the output is visual information on the display and voice information played from the speaker.

[0197] Step 7:

[0198] The terminal uses built-in sensors and cameras to monitor user actions in real time and ensure security. Input is data from sensors and cameras, and output is a warning message if safety measures are required. In addition, it dynamically provides further detailed guidance if needed in response to user actions.

[0199] (Application Example 2)

[0200] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0201] In modern society, there is a need for beginners and children to learn cooking skills safely and meaningfully. However, conventional cooking support systems lack sufficient individual support that takes into account the user's skill level and emotional state, and in particular, they lack adjustment functions that utilize emotional states. This can lead to users feeling stressed and potentially lower the quality of the cooking experience.

[0202] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0203] In this invention, the server includes means for converting voice input from the user into text data, means for generating recipes based on the user's age, skill level, allergy information, and items, and means for recognizing the user's emotional state and adjusting the system's operation. This enables optimal and flexible cooking support tailored to the individual characteristics of each user.

[0204] "User" refers to a person who uses this system to cook.

[0205] "Means of converting voice input into text data" refers to methods for converting voice information from a user into text information.

[0206] "Age group" refers to information indicating the user's age range or stage of development.

[0207] "Technical level" refers to information that represents the user's level of knowledge and skills regarding cooking.

[0208] "Allergy information" refers to information about food allergies that the user possesses.

[0209] "Means for generating manufacturing methods based on articles" refers to methods for creating cooking methods based on the ingredients a user possesses.

[0210] "Means of displaying as visual and auditory instructions" refers to methods for clearly presenting generated cooking information to the user.

[0211] "Means of monitoring and detecting dangerous situations" means methods for constantly observing user behavior and recognizing conditions that could potentially compromise safety.

[0212] "Warning mechanisms" refer to methods used to alert users to detected risks.

[0213] "Means of recognizing emotional states and adjusting system operation" refers to methods for analyzing a user's emotional responses and appropriately modifying the instructions and support provided by the system.

[0214] The system for implementing this invention combines multiple functions to provide users with a safe and educational cooking experience. Specific examples are shown below.

[0215] The server utilizes a cloud-based platform that runs speech recognition and natural language processing technologies. Specifically, it leverages Amazon AWS® and Google Cloud AI, and converts user voice input into text data via the OpenAI API. This voice data is used by an emotion engine to analyze the user's emotions. Based on this emotion analysis, the recipes and advice provided to the user are dynamically adjusted.

[0216] The device in question is a smartphone, which plays a role in providing visual and audio guidance to the user. Based on data received from the server, it displays recipes that take into account the user's age, skill level, allergies, and available ingredients, and monitors the user's actions and emotions while cooking. It can also detect hazards using its built-in camera and sensors and issue warnings in real time.

[0217] As the user progresses through each step of the cooking process, they receive instructions from the device and ask questions via voice as needed. If the user's emotions are unstable, the device proactively offers words of encouragement and detailed explanations, responding in a way that is sensitive to the user's feelings. This allows the user to continue cooking with peace of mind.

[0218] For example, if a user is making fruit salad for the first time, the device can provide voice support such as, "Next, cut the apples. If you're unsure how to cut them, you can proceed slowly."

[0219] An example of a prompt for a generative AI model is, "What kind of support should be offered if a user becomes confused while eating a fruit salad?" This prompt allows the AI ​​to generate appropriate advice and guidance.

[0220] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0221] Step 1:

[0222] The server receives voice input from the user and converts it into text data using cloud-based speech recognition technology. The input is the user's voice, and the output is text data. In this conversion, a speech recognition API is used to perform data processing such as noise reduction and speech feature extraction.

[0223] Step 2:

[0224] The server references the user's age, skill level, allergy information, and available ingredients from text data to generate appropriate recipes from the database. Input is text data and user profile information, and output is user-optimized recipe information. The server queries the database to select recipes that match the specified criteria.

[0225] Step 3:

[0226] The server uses an emotion engine to analyze the user's emotional state and adjusts recipes and advice according to the user's emotions. Input is the user's text data and profile data, and output is adjusted recipe information that reflects their emotions. Natural language processing and sentiment analysis are used to determine appropriate instructions for the user.

[0227] Step 4:

[0228] The terminal provides visual and audio instructions to the user based on pre-configured recipe information received from the server. The input is the recipe information from the server, and the output is the visual and audio instructions to the user. The terminal application manages this and presents it to the user via a digital interface.

[0229] Step 5:

[0230] The user performs cooking actions, which are monitored by the device's built-in camera and sensors. The input is the user's cooking actions, and the output is detected data related to hazards or safety. Image processing technology is used to identify dangerous behaviors in real time.

[0231] Step 6:

[0232] The device alerts the user if a threat is detected. The input is the detected threat information, and the output is a warning message to the user. Audio and visual warnings are provided to immediately draw the user's attention.

[0233] Step 7:

[0234] When a user experiences emotional distress, the device provides comforting words and encouraging messages based on emotional data. The input is the user's emotional data, and the output is words of encouragement. A generative AI model is used to generate prompts and appropriate words to stabilize the user's emotions.

[0235] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0236] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0237] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0238] [Second Embodiment]

[0239] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0240] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0241] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0242] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0243] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0244] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0245] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0246] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0247] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0248] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0249] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0250] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0251] This invention is a system for children to safely learn to cook and cook independently, integrating functions such as voice input, text conversion, recipe generation, visual and audio guidance, hazard detection, and warning issuance. The system mainly consists of a server, terminals, and users.

[0252] The server is the core of the system, hosting an AI model that processes user input. Once the user's voice input is converted to text data, the server references this data and retrieves relevant information from the recipe database. Furthermore, it customizes the recipe based on the user's age, skill level, and allergy information. The server then formats the final recipe and cooking instructions and sends them to the device as visual and audio guides.

[0253] The terminal is a user-operated device that provides an interface between the user and the server through visual animations and audio guidance. The terminal receives recipes and instructions from the server and presents them to the user sequentially. It guides the user to the next step according to their progress and issues warnings as needed.

[0254] The user is the central user of the system, interacting with it through a terminal and performing cooking according to their wishes. For example, if the user enters "I want to make chocolate cookies" into the terminal, the entire system process begins. The user follows the guide on the terminal, prepares the ingredients, and proceeds with cooking according to the instructions. The terminal can provide real-time warnings for high-risk steps, such as when using a knife or setting the oven temperature.

[0255] Thus, this system provides an embodiment of a system that, by combining visual and auditory aids, enables users to easily learn how to cook and to proceed with cooking safely and efficiently.

[0256] The following describes the processing flow.

[0257] Step 1:

[0258] The user speaks into the device and enters the name of the dish they want to make. For example, they might say, "I want to make chocolate cookies."

[0259] Step 2:

[0260] The device records the user's voice and converts it into text data using speech recognition technology. This text data includes the name of the dish.

[0261] Step 3:

[0262] The device sends a request to the server containing the converted text data. This request also includes user information (age, skill level, allergy information, etc.).

[0263] Step 4:

[0264] The server receives the request and retrieves the appropriate recipe from the database based on the user information. Furthermore, it customizes the recipe to suit the user's needs.

[0265] Step 5:

[0266] The server formats customized recipes and cooking instructions into visual and audio guide formats and sends them to the terminal.

[0267] Step 6:

[0268] The device receives the data sent to it and provides the user with visual animations and audio guidance. This allows the user to proceed with cooking while receiving instructions step by step.

[0269] Step 7:

[0270] The user gathers the ingredients and begins cooking based on the instructions on the device. They follow the guide to perform the specific steps.

[0271] Step 8:

[0272] The device monitors the user's actions while cooking and ensures safety by issuing warnings when it detects dangers such as the use of knives or open flames.

[0273] Step 9:

[0274] If the user has any questions or uncertainties, they make an inquiry by voice to the terminal. For example, they ask, "What should I do next?"

[0275] Step 10:

[0276] The server receives the user's question, generates an appropriate response, and transmits it to the terminal.

[0277] Step 11:

[0278] <00008​​​​​​​​​​​​​​​​​​​​​​​​​​​​In this invention, the server includes a processing device that converts user input voice into character data, a processing device that configures cooking procedures based on age, skill level, and health information, and a processing device that provides the generated cooking procedures visually and audibly. As a result, the user can enjoy a safe and effective cooking experience according to their own situation and capabilities.

[0286] "Conversion of user input voice into character data" refers to the process of recognizing the voice uttered by the user as a digital signal and converting it into text format.

[0287] "Configuration of cooking procedures based on age, skill level, and health information" refers to selecting the optimal recipe and procedures according to the user's attributes and customizing them to assist in cooking learning and practice.

[0288] "Visual and audible provision of the generated cooking procedures" refers to providing an interface that is visually and audibly presented for easy understanding by the user to guide the cooking procedures.

[0289] "Monitoring of the user's working situation" refers to tracking the user's cooking process and evaluating the progress and safety of the process.

[0290] "Detection of threats related to safety" refers to the process of detecting actions and states that involve risks during cooking and preventing accidents.

[0291] "Implementation of alerting" refers to prompting the user to pay attention using voice or visual means and warning the user to proceed with cooking safely.

[0292] The present invention is a system aimed at enabling users to safely learn cooking and cook independently. This system is composed of a server, a terminal, and a user.

[0293] The server plays a central role in the system, utilizing a speech recognition API to convert user-input speech into text data. Here, the speech data is converted into text using Google's speech recognition API or general speech recognition software. Based on this text data, a generative AI model is used to generate recipes. A general natural language processing model can be used as the generative AI model; a possible prompt would be "Generate a simple and safe chocolate cookie recipe for an 8-year-old child." Furthermore, the server accesses a database to customize the recipe, taking into account the user's age, skill level, and health information. The customized recipe is then formatted as a visual and audio guide and sent to the terminal.

[0294] The terminal is a device that guides the user through procedures using visual and audio guidance transmitted from the server. Sequential instructions are provided via animation and audio on devices such as tablets and smartphones. The terminal can monitor the user's cooking progress and provide safety warnings as needed. For example, when using a knife, the terminal will issue a real-time audio warning.

[0295] The user is the one who operates the terminal and follows the guide to cook. The user voice-inputs the desired dish into the terminal, prepares the ingredients based on the provided guide, and safely proceeds with cooking according to the procedure. For example, the user tells the server that they want to make chocolate cookies and proceeds with cooking according to the provided recipe and procedure.

[0296] In this way, this system can provide support for users to learn cooking in an easy-to-understand and safe manner.

[0297] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0298] Step 1:

[0299] The user inputs the desired cooking content towards the terminal by voice. For example, say "I want to make chocolate cookies". This voice becomes the input data.

[0300] Step 2:

[0301] The terminal transmits the recorded voice data as a digital signal to the server. This becomes the input to the server.

[0302] Step 3:

[0303] The server uses the speech recognition API to convert the received voice data into text data. Through this conversion process, the text "I want to make chocolate cookies" is output. Here, the analog data of voice input is processed into digital text data.

[0304] Step 4:

[0305] The server inputs a prompt sentence into the generation AI model. Based on the prompt "Generate a simple and safe chocolate cookie recipe for an 8-year-old child", the AI model generates recipe data. This becomes the input data for the next process.

[0306] Step 5:

[0307] The server checks the generated recipe data and customizes the recipe considering the user's profile information (age, skill level, health information). For example, processing such as adjusting the weight of the ingredients to be easier for children to use or simplifying the steps is performed. As a result, a recipe optimized for the user is output.

[0308] Step 6:

[0309] The server formats the customized recipe as a visual and voice guide and transmits it to the terminal. This is the input data to the terminal.

[0310] Step 7:

[0311] The device guides the user through the cooking process visually and audibly, based on the received guide data. Each step is clearly displayed with animation and audio, following the recipe order.

[0312] Step 8:

[0313] The terminal monitors the user's actions in real time and provides warnings via voice alerts and on-screen displays during potentially dangerous processes. For example, it issues warnings when using knives or when heating an oven. This output is intended to ensure the user's safety.

[0314] Step 9:

[0315] The user follows visual and audio guidance to complete the cooking process. This allows the user to complete the dish safely and effectively. The output is the finished dish.

[0316] (Application Example 1)

[0317] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0318] A support system for children to learn to cook safely and effectively requires the provision of flexible cooking procedures tailored to the child's age and skill level, as well as real-time hazard detection and warning. Furthermore, an interactive interface is needed to engage children's interest and encourage their active participation in cooking.

[0319] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0320] In this invention, the server includes means for converting voice input from the user into text data, means for generating cooking instructions based on the user's age, skill level, allergy information, and available ingredients, means for displaying the generated cooking instructions as visual and audio instructions, and means for monitoring the user's actions and detecting dangerous situations. This enables children to learn to cook safely and in an engaging way.

[0321] "Means of converting voice input from users into text data" refers to technology that converts information in audio format into digital text format.

[0322] "Means for generating cooking instructions based on the user's age, skill level, allergy information, and available ingredients" refers to an algorithm or program that creates optimal cooking instructions tailored to the user.

[0323] "Means for displaying generated cooking instructions as visual and audio instructions" refers to a display device or program for visually and aurally communicating generated instructions to the user.

[0324] "Means of monitoring user actions and detecting dangerous situations" refers to monitoring functions using sensors and software to track user behavior and determine safety.

[0325] "Means for providing a visual interface" refers to a design or platform for visually facilitating the exchange of information between the user and the system.

[0326] "Means of tracking user behavior and evaluating safety based on predetermined criteria" refers to algorithms or systems that analyze behavioral logs and automatically make safety judgments.

[0327] The system for implementing the present invention consists of three main elements: a server, a terminal, and a user. The server is the core of the system, converting the voice input provided by the user into text and generating cooking instructions based on that. Specifically, the server uses the Google Speech-to-Text API to convert voice into text data. This text data is processed by a recipe generation engine using an AI model hosted on the server, for example, OpenAI's GPT-3 can be used. The engine takes into account the user's age, skill level, allergy information, and available ingredients to generate the optimal cooking instructions.

[0328] The terminal is the device that serves as the interface with the user. The terminal receives cooking instructions sent from the server and can utilize development platforms such as Unity and Flutter to guide the user visually and audibly. The terminal also implements voice guidance using the Speech Synthesis API. It also has the capability to monitor user behavior in real time, recognize dangerous situations using libraries such as OpenCV, and issue warnings.

[0329] Users interact with the system through their device and utilize it to safely learn how to cook their desired dishes. For example, if an 8-year-old child requests to "make spaghetti," the AI ​​model receives the following prompt: "Please create a recipe that allows a child to safely and easily make spaghetti. The child is 8 years old, and only household equipment is allowed." Based on this information, the system generates safe and easy-to-understand instructions for children and guides them visually and audibly through the device. In this way, the present invention makes it possible to provide an environment in which users can learn to cook with interest and actively.

[0330] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0331] Step 1:

[0332] The user inputs cooking information into the device using voice. This voice input is based on the user's request and includes specific details such as the dish they want to make and any other requirements.

[0333] Step 2:

[0334] The device converts audio data into text data using the Google Speech-to-Text API. This conversion transforms the audio content into a digital format that the server can understand. The input is audio data, and the output is the corresponding text data.

[0335] Step 3:

[0336] The server receives input text and generates a prompt using an AI model (e.g., OpenAI GPT-3). This prompt contains information to output optimized cooking instructions based on the user's request. The input is the converted text, and the output is the prompt.

[0337] Step 4:

[0338] The server uses the generated prompts to create customized cooking instructions based on an AI model. This process takes into account the user's age, skill level, allergy information, and available ingredients. The input is the prompts, and the output is the optimized cooking instructions.

[0339] Step 5:

[0340] The device receives cooking instructions sent from the server and generates visual and audio guides using Unity and Flutter. These guides are designed to make it easy for the user to intuitively understand the steps. The input is customized cooking instructions, and the output is a visual and audio interface.

[0341] Step 6:

[0342] The user follows the terminal's instructions to proceed with cooking. The terminal monitors the user's actions and movements in real time and detects dangerous situations using libraries such as OpenCV. Input is user action data, and output is a warning alert in case of danger.

[0343] Step 7:

[0344] If the device detects a hazard, it immediately issues an audible and visual warning, prompting the user to take appropriate safety measures. At this time, the user's progress is temporarily paused, and the next step is not guided until the situation is safe. The input is hazard detection information, and the output is the warning interface.

[0345] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0346] This invention is a system that enables users, including children, to safely learn to cook and cook independently. The system has means to convert voice input into text data, generate recipes based on the user's age, skill level, allergy information, and available ingredients, and provide visual and audio guidance. It also has a function to monitor user operations, detect dangers, and issue warnings. In addition, the invention incorporates an emotion engine, providing a new ability to recognize user emotions and adjust the system's operation accordingly.

[0347] The server receives the user's voice input and converts it into text data using speech recognition technology. Based on this, the server refers to user data, retrieves appropriate recipes from the database, and customizes them. The server further analyzes the user's emotional state using an emotion engine and suggests or adjusts recipes according to the user's emotions. The results are then formatted into visual and audio guide formats and sent to the terminal.

[0348] The device provides the user with visual animations and audio guidance based on data sent from the server. The device understands the user's emotional state and adjusts the tone and content of the guidance accordingly. For example, if the user is anxious, it can provide more detailed explanations or words of encouragement. The device also monitors the user's actions and issues warnings if it detects danger through sensors or cameras. The emotion engine plays a crucial role here as well, adjusting the priority and delivery of warnings to match the user's mental state.

[0349] When a user begins cooking, they enter the name of the dish they want to make into the device. They then proceed with cooking according to the device's instructions, but especially if they are emotionally unstable or doing it for the first time, the device provides support that takes the user's emotions into consideration. For example, if cooking is not going as planned, the device senses the user's emotions and provides support such as, "It's okay, let's relax and continue."

[0350] These comprehensive features allow the system to provide users with a safe and enjoyable cooking experience, not only by teaching them how to cook, but also by offering emotional support.

[0351] The following describes the processing flow.

[0352] Step 1:

[0353] The user speaks into the device to specify the dish they want to make. For example, they might say, "I want to make lasagna."

[0354] Step 2:

[0355] The device records the user's voice and uses a speech recognition engine to convert the voice data into text data. This text includes the user's cooking preferences.

[0356] Step 3:

[0357] The terminal sends the converted text data to the server and sends a request that includes user information, age, skill level, and allergy information.

[0358] Step 4:

[0359] The server receives the request and retrieves the corresponding recipe from the database. It then adjusts the recipe according to the user's skill level and then customizes it.

[0360] Step 5:

[0361] The server customizes recipes based on the user's age, skill level, and allergy information, and uses an emotion engine to analyze additional data (e.g., voice and facial expressions) to estimate the user's emotions.

[0362] Step 6:

[0363] Based on the user's emotions analyzed by the server, the system formats customized recipes and guides as audio and visual data and sends them to the device.

[0364] Step 7:

[0365] The device receives data from the server, visually displays recipe instructions on the screen, and provides voice guidance to the user. The instructions are delivered in a calm tone that is adjusted to the user's emotional state.

[0366] Step 8:

[0367] The user follows the visual and audio guidance on the device to perform the cooking process. This includes gathering ingredients and following instructions.

[0368] Step 9:

[0369] The device monitors user actions through sensors and user feedback, and issues warnings when danger is anticipated, such as the use of knives or firearms. The strength of the warning is adjusted according to the user's emotions.

[0370] Step 10:

[0371] If a user has questions while cooking, they can contact the device. For example, they might ask, "Could you explain in more detail?"

[0372] Step 11:

[0373] The server receives the user's question, analyzes its content, generates an appropriate answer, and sends it to the terminal.

[0374] Step 12:

[0375] The terminal communicates responses from the server to the user via voice and text, supporting the progress of the cooking process.

[0376] Step 13:

[0377] The user completes all steps and finishes cooking. The device provides feedback saying, "Great job! Your dish is finished!" and praises the user.

[0378] (Example 2)

[0379] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0380] In modern society, learning and practicing cooking safely is an important skill. However, especially for children and beginners, the dangers posed by the tools and heating equipment used in the cooking process make it difficult to learn with peace of mind. Furthermore, it is difficult to meet individual needs because it is not possible to provide guides that are appropriately tailored to the learner's skill level and mental state. As a result, the cooking learning process can become inadequate and stressful, potentially leading to decreased motivation and failure to ensure safety.

[0381] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0382] In this invention, the server includes means for converting acoustic input into textual information, means for generating procedures based on the user's age, skill level, allergy information, and available ingredients, and means for guiding the generated procedures visually and audibly. This makes it possible to provide an optimized cooking learning environment for each individual user while ensuring user safety.

[0383] "Means for converting audio input into textual information" refers to technology that converts audio data spoken by a user into digital text, and has the function of converting speech into text using speech recognition technology.

[0384] "Textual information" refers to text data converted from audio data and recorded in digital format, enabling further processing and analysis on the server.

[0385] "Means for generating procedures based on the user's age, skill level, allergy information, and available ingredients" refers to technology that utilizes algorithms and databases to suggest the optimal cooking procedure according to the individual user's basic information and circumstances.

[0386] "Means of providing guidance visually and audibly" refers to technologies that use display devices and speech synthesis technology to provide guidance information in order to present the generated cooking procedures in a user-friendly format.

[0387] "Means for monitoring user actions and detecting dangerous situations" refers to technologies that monitor user actions in real time through sensors and cameras to identify potential dangers.

[0388] "Warning mechanisms" refer to technologies that communicate messages through visual and auditory means to warn or alert users to identified dangers.

[0389] "Means for analyzing emotional states and adjusting procedures and warnings accordingly" refers to emotion analysis technology that identifies the user's emotions and dynamically optimizes cooking procedures and warning content based on the results.

[0390] This system is designed to allow users to learn to cook safely and efficiently. First, the user voice-inputs the desired dish into the terminal. The terminal uses its built-in microphone to capture the voice data and transmits it to the server.

[0391] The server converts audio data into text data using speech recognition technology. A commonly used speech recognition service is employed for this purpose. For example, a general speech recognition platform can be used as a means of "converting acoustic input into text information." Based on the converted text data, the server generates the optimal cooking procedure (recipe) from a database, taking into account the user's age, skill level, allergy information, and available ingredients. A general database management system is used for this.

[0392] Next, the server uses sentiment analysis technology to evaluate the user's emotional state. This analysis can utilize a general sentiment analysis API. Based on the evaluation results, it generates appropriate instructions and warning messages for the user's situation. For example, if the user is feeling anxious, detailed and reassuring guidance is provided.

[0393] The server then sends the adjusted recipe and guide to the terminal. The terminal provides visual and audio guidance to the user based on the received data. A display device is used for visual guidance, and text-to-speech technology is used for audio guidance. This embodiment allows the user to receive guidance tailored to their current situation. For example, if the user wants to know how to make omurice, they might input the following prompt: "Please tell me an easy way to make omurice. I would appreciate it if you could also provide the necessary ingredients and specific steps."

[0394] This system allows users to learn cooking techniques safely and in a way that is tailored to their individual circumstances. Furthermore, if a hazard is anticipated, the terminal will issue appropriate warnings through real-time monitoring, ensuring safety during cooking.

[0395] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0396] Step 1:

[0397] The user inputs their cooking preferences and related information by voice into the terminal. The terminal captures this audio data through its microphone and saves it as an audio file. The input is the user's voice, and the output is data in audio file format. The terminal compresses the audio file on-device and prepares it for transfer to the server.

[0398] Step 2:

[0399] The server receives audio files sent from the terminal. The received audio files are analyzed through a speech recognition system and converted into text data. Here, the input is an audio file, and the output is text data. The server processes this text data and extracts information such as the name of the dish and the required ingredients.

[0400] Step 3:

[0401] The server searches for the optimal recipe based on the extracted text data and references the user's basic information. Input consists of text data and user information, while output is customized recipe data. The server executes appropriate database queries, taking into account the user's age, skill level, allergy information, and available ingredients.

[0402] Step 4:

[0403] The server uses an emotion analysis engine to analyze text data and available historical information from the user to evaluate their emotional state. The input is text data and associated historical information, and the output is the evaluation result of the emotional state. Based on this result, the server flexibly adjusts the recipe content and guidance methods.

[0404] Step 5:

[0405] The server formats the adjusted recipes and guidance methods into visual and audio guidance formats and sends them to the terminal. The input is customized recipe data and sentiment evaluation results, and the output is formatted guide data.

[0406] Step 6:

[0407] The terminal displays visual guidance to the user based on guide data received from the server and provides voice guidance using speech synthesis technology. The input is guide data, and the output is visual information on the display and voice information played from the speaker.

[0408] Step 7:

[0409] The terminal uses built-in sensors and cameras to monitor user actions in real time and ensure security. Input is data from sensors and cameras, and output is a warning message if safety measures are required. In addition, it dynamically provides further detailed guidance if needed in response to user actions.

[0410] (Application Example 2)

[0411] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0412] In modern society, there is a need for beginners and children to learn cooking skills safely and meaningfully. However, conventional cooking support systems lack sufficient individual support that takes into account the user's skill level and emotional state, and in particular, they lack adjustment functions that utilize emotional states. This can lead to users feeling stressed and potentially lower the quality of the cooking experience.

[0413] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0414] In this invention, the server includes means for converting voice input from the user into text data, means for generating recipes based on the user's age, skill level, allergy information, and items, and means for recognizing the user's emotional state and adjusting the system's operation. This enables optimal and flexible cooking support tailored to the individual characteristics of each user.

[0415] "User" refers to a person who uses this system to cook.

[0416] "Means of converting voice input into text data" refers to methods for converting voice information from a user into text information.

[0417] "Age group" refers to information indicating the user's age range or stage of development.

[0418] "Technical level" refers to information that represents the user's level of knowledge and skills regarding cooking.

[0419] "Allergy information" refers to information about food allergies that the user possesses.

[0420] "Means for generating manufacturing methods based on articles" refers to methods for creating cooking methods based on the ingredients a user possesses.

[0421] "Means of displaying as visual and auditory instructions" refers to methods for clearly presenting generated cooking information to the user.

[0422] "Means of monitoring and detecting dangerous situations" means methods for constantly observing user behavior and recognizing conditions that could potentially compromise safety.

[0423] "Warning mechanisms" refer to methods used to alert users to detected risks.

[0424] "Means of recognizing emotional states and adjusting system operation" refers to methods for analyzing a user's emotional responses and appropriately modifying the instructions and support provided by the system.

[0425] The system for implementing this invention combines multiple functions to provide users with a safe and educational cooking experience. Specific examples are shown below.

[0426] The server utilizes a cloud-based platform that runs speech recognition and natural language processing technologies. Specifically, it leverages Amazon AWS and Google Cloud AI, and further converts user voice input into text data via the OpenAI API. This voice data is used by an emotion engine to analyze the user's emotions. Based on this emotion analysis, the recipes and advice provided to the user are dynamically adjusted.

[0427] The device in question is a smartphone, which plays a role in providing visual and audio guidance to the user. Based on data received from the server, it displays recipes that take into account the user's age, skill level, allergies, and available ingredients, and monitors the user's actions and emotions while cooking. It can also detect hazards using its built-in camera and sensors and issue warnings in real time.

[0428] As the user progresses through each step of the cooking process, they receive instructions from the device and ask questions via voice as needed. If the user's emotions are unstable, the device proactively offers words of encouragement and detailed explanations, responding in a way that is sensitive to the user's feelings. This allows the user to continue cooking with peace of mind.

[0429] For example, if a user is making fruit salad for the first time, the device can provide voice support such as, "Next, cut the apples. If you're unsure how to cut them, you can proceed slowly."

[0430] An example of a prompt for a generative AI model is, "What kind of support should be offered if a user becomes confused while eating a fruit salad?" This prompt allows the AI ​​to generate appropriate advice and guidance.

[0431] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0432] Step 1:

[0433] The server receives voice input from the user and converts it into text data using cloud-based speech recognition technology. The input is the user's voice, and the output is text data. In this conversion, a speech recognition API is used to perform data processing such as noise reduction and speech feature extraction.

[0434] Step 2:

[0435] The server references the user's age, skill level, allergy information, and available ingredients from text data to generate appropriate recipes from the database. Input is text data and user profile information, and output is user-optimized recipe information. The server queries the database to select recipes that match the specified criteria.

[0436] Step 3:

[0437] The server uses an emotion engine to analyze the user's emotional state and adjusts recipes and advice according to the user's emotions. Input is the user's text data and profile data, and output is adjusted recipe information that reflects their emotions. Natural language processing and sentiment analysis are used to determine appropriate instructions for the user.

[0438] Step 4:

[0439] The terminal provides visual and audio instructions to the user based on pre-configured recipe information received from the server. The input is the recipe information from the server, and the output is the visual and audio instructions to the user. The terminal application manages this and presents it to the user via a digital interface.

[0440] Step 5:

[0441] The user performs cooking actions, which are monitored by the device's built-in camera and sensors. The input is the user's cooking actions, and the output is detected data related to hazards or safety. Image processing technology is used to identify dangerous behaviors in real time.

[0442] Step 6:

[0443] The device alerts the user if a threat is detected. The input is the detected threat information, and the output is a warning message to the user. Audio and visual warnings are provided to immediately draw the user's attention.

[0444] Step 7:

[0445] When a user experiences emotional distress, the device provides comforting words and encouraging messages based on emotional data. The input is the user's emotional data, and the output is words of encouragement. A generative AI model is used to generate prompts and appropriate words to stabilize the user's emotions.

[0446] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0447] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0448] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0449] [Third Embodiment]

[0450] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0451] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0452] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0453] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0454] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0455] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0456] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0457] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0458] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0459] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0460] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0461] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0462] This invention is a system for children to safely learn to cook and cook independently, integrating functions such as voice input, text conversion, recipe generation, visual and audio guidance, hazard detection, and warning issuance. The system mainly consists of a server, terminals, and users.

[0463] The server is the core of the system, hosting an AI model that processes user input. Once the user's voice input is converted to text data, the server references this data and retrieves relevant information from the recipe database. Furthermore, it customizes the recipe based on the user's age, skill level, and allergy information. The server then formats the final recipe and cooking instructions and sends them to the device as visual and audio guides.

[0464] The terminal is a user-operated device that provides an interface between the user and the server through visual animations and audio guidance. The terminal receives recipes and instructions from the server and presents them to the user sequentially. It guides the user to the next step according to their progress and issues warnings as needed.

[0465] The user is the central user of the system, interacting with it through a terminal and performing cooking according to their wishes. For example, if the user enters "I want to make chocolate cookies" into the terminal, the entire system process begins. The user follows the guide on the terminal, prepares the ingredients, and proceeds with cooking according to the instructions. The terminal can provide real-time warnings for high-risk steps, such as when using a knife or setting the oven temperature.

[0466] Thus, this system provides an embodiment of a system that, by combining visual and auditory aids, enables users to easily learn how to cook and to proceed with cooking safely and efficiently.

[0467] The following describes the processing flow.

[0468] Step 1:

[0469] The user speaks into the device and enters the name of the dish they want to make. For example, they might say, "I want to make chocolate cookies."

[0470] Step 2:

[0471] The device records the user's voice and converts it into text data using speech recognition technology. This text data includes the name of the dish.

[0472] Step 3:

[0473] The device sends a request to the server containing the converted text data. This request also includes user information (age, skill level, allergy information, etc.).

[0474] Step 4:

[0475] The server receives the request and retrieves the appropriate recipe from the database based on the user information. Furthermore, it customizes the recipe to suit the user's needs.

[0476] Step 5:

[0477] The server formats customized recipes and cooking instructions into visual and audio guide formats and sends them to the terminal.

[0478] Step 6:

[0479] The device receives the data sent to it and provides the user with visual animations and audio guidance. This allows the user to proceed with cooking while receiving instructions step by step.

[0480] Step 7:

[0481] The user gathers the ingredients and begins cooking based on the instructions on the device. They follow the guide to perform the specific steps.

[0482] Step 8:

[0483] The device monitors the user's actions while cooking and ensures safety by issuing warnings when it detects dangers such as the use of knives or open flames.

[0484] Step 9:

[0485] If a user has any questions or concerns, they can ask them via voice through their device. For example, they might ask, "What should I do next?"

[0486] Step 10:

[0487] The server receives the user's question, generates an appropriate response, and sends it to the terminal.

[0488] Step 11:

[0489] The terminal communicates responses from the server to the user via voice and visuals, supporting the cooking process.

[0490] Step 12:

[0491] The user completes all cooking steps and the dish is finished. The device provides feedback by notifying the user with "Great job! Your dish is ready!"

[0492] (Example 1)

[0493] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0494] The problem this invention aims to solve is that it is difficult for users with limited skills, especially children, to learn to cook safely and effectively. There is a need to reduce the risk of accidents due to improper understanding of cooking procedures and dangerous cooking processes, and to support users so they can cook with confidence.

[0495] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0496] In this invention, the server includes a processing unit that converts user input voice into text data, a processing unit that constructs cooking procedures based on age, skill level, and health information, and a processing unit that provides the generated cooking procedures in both display and audio format. This enables users to enjoy a safe and effective cooking experience tailored to their own circumstances and abilities.

[0497] "Conversion of user-input speech to text data" is the process of recognizing the speech spoken by the user as a digital signal and converting it into text format.

[0498] "Cooking procedure configuration based on age, skill level, and health information" means selecting the most suitable recipes and procedures according to the user's attributes and customizing them to support learning and practicing cooking.

[0499] "Displaying and providing generated cooking instructions via audio" means guiding users through cooking procedures using a visual and audio interface designed for easy understanding.

[0500] "Monitoring user work status" means tracking the user's cooking process and evaluating the progress and safety of the process.

[0501] "Detecting safety threats" is a process that involves detecting potentially dangerous actions or conditions during cooking to prevent accidents.

[0502] "Implementing a warning" means prompting users to take precautions using audio or visual means and warning them to proceed with cooking safely.

[0503] This invention is a system aimed at enabling users to safely learn to cook and to cook independently. This system consists of a server, terminals, and users.

[0504] The server plays a central role in the system, utilizing a speech recognition API to convert user-input speech into text data. Here, the speech data is converted into text using Google's speech recognition API or general speech recognition software. Based on this text data, a generative AI model is used to generate recipes. A general natural language processing model can be used as the generative AI model; a possible prompt would be "Generate a simple and safe chocolate cookie recipe for an 8-year-old child." Furthermore, the server accesses a database to customize the recipe, taking into account the user's age, skill level, and health information. The customized recipe is then formatted as a visual and audio guide and sent to the terminal.

[0505] The terminal is a device that guides the user through procedures using visual and audio guidance transmitted from the server. Sequential instructions are provided via animation and audio on devices such as tablets and smartphones. The terminal can monitor the user's cooking progress and provide safety warnings as needed. For example, when using a knife, the terminal will issue a real-time audio warning.

[0506] The user is the one who operates the terminal and follows the guide to cook. The user voice-inputs the desired dish into the terminal, prepares the ingredients based on the provided guide, and safely proceeds with cooking according to the procedure. For example, the user tells the server that they want to make chocolate cookies and proceeds with cooking according to the provided recipe and procedure.

[0507] In this way, this system can provide support for users to learn cooking in an easy-to-understand and safe manner.

[0508] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0509] Step 1:

[0510] The user inputs the desired recipe by voice into the terminal. For example, they might say, "I want to make chocolate cookies." This voice input becomes the input data.

[0511] Step 2:

[0512] The terminal transmits the recorded audio data as a digital signal to the server. This becomes the input to the server.

[0513] Step 3:

[0514] The server uses a speech recognition API to convert the received audio data into text data. This conversion process outputs the text "I want to make chocolate cookies." Here, analog data (voice input) is processed into digital text data.

[0515] Step 4:

[0516] The server inputs a prompt into the generating AI model. Based on the prompt, "Generate a simple and safe chocolate cookie recipe for an 8-year-old child," the AI ​​model generates recipe data. This becomes the input data for the next process.

[0517] Step 5:

[0518] The server reviews the generated recipe data and customizes it, taking into account the user's profile information (age, skill level, health information). For example, it might adjust the weight of ingredients to make it easier for children to use, or simplify the process. This results in a recipe optimized for the user.

[0519] Step 6:

[0520] The server formats the customized recipe as a visual and audio guide and sends it to the terminal. This is the input data for the terminal.

[0521] Step 7:

[0522] The device guides the user through the cooking process visually and audibly, based on the received guide data. Each step is clearly displayed with animation and audio, following the recipe order.

[0523] Step 8:

[0524] The terminal monitors the user's actions in real time and provides warnings via voice alerts and on-screen displays during potentially dangerous processes. For example, it issues warnings when using knives or when heating an oven. This output is intended to ensure the user's safety.

[0525] Step 9:

[0526] The user follows visual and audio guidance to complete the cooking process. This allows the user to complete the dish safely and effectively. The output is the finished dish.

[0527] (Application Example 1)

[0528] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0529] A support system for children to learn to cook safely and effectively requires the provision of flexible cooking procedures tailored to the child's age and skill level, as well as real-time hazard detection and warning. Furthermore, an interactive interface is needed to engage children's interest and encourage their active participation in cooking.

[0530] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0531] In this invention, the server includes means for converting voice input from the user into text data, means for generating cooking instructions based on the user's age, skill level, allergy information, and available ingredients, means for displaying the generated cooking instructions as visual and audio instructions, and means for monitoring the user's actions and detecting dangerous situations. This enables children to learn to cook safely and in an engaging way.

[0532] "Means of converting voice input from users into text data" refers to technology that converts information in audio format into digital text format.

[0533] "Means for generating cooking instructions based on the user's age, skill level, allergy information, and available ingredients" refers to an algorithm or program that creates optimal cooking instructions tailored to the user.

[0534] "Means for displaying generated cooking instructions as visual and audio instructions" refers to a display device or program for visually and aurally communicating generated instructions to the user.

[0535] "Means of monitoring user actions and detecting dangerous situations" refers to monitoring functions using sensors and software to track user behavior and determine safety.

[0536] "Means for providing a visual interface" refers to a design or platform for visually facilitating the exchange of information between the user and the system.

[0537] "Means of tracking user behavior and evaluating safety based on predetermined criteria" refers to algorithms or systems that analyze behavioral logs and automatically make safety judgments.

[0538] The system for implementing the present invention consists of three main elements: a server, a terminal, and a user. The server is the core of the system, converting the voice input provided by the user into text and generating cooking instructions based on that. Specifically, the server uses the Google Speech-to-Text API to convert voice into text data. This text data is processed by a recipe generation engine using an AI model hosted on the server, for example, OpenAI's GPT-3 can be used. The engine takes into account the user's age, skill level, allergy information, and available ingredients to generate the optimal cooking instructions.

[0539] The terminal is the device that serves as the interface with the user. The terminal receives cooking instructions sent from the server and can utilize development platforms such as Unity and Flutter to guide the user visually and audibly. The terminal also implements voice guidance using the Speech Synthesis API. It also has the capability to monitor user behavior in real time, recognize dangerous situations using libraries such as OpenCV, and issue warnings.

[0540] Users interact with the system through their device and utilize it to safely learn how to cook their desired dishes. For example, if an 8-year-old child requests to "make spaghetti," the AI ​​model receives the following prompt: "Please create a recipe that allows a child to safely and easily make spaghetti. The child is 8 years old, and only household equipment is allowed." Based on this information, the system generates safe and easy-to-understand instructions for children and guides them visually and audibly through the device. In this way, the present invention makes it possible to provide an environment in which users can learn to cook with interest and actively.

[0541] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0542] Step 1:

[0543] The user inputs cooking information into the device using voice. This voice input is based on the user's request and includes specific details such as the dish they want to make and any other requirements.

[0544] Step 2:

[0545] The device converts audio data into text data using the Google Speech-to-Text API. This conversion transforms the audio content into a digital format that the server can understand. The input is audio data, and the output is the corresponding text data.

[0546] Step 3:

[0547] The server receives input text and generates a prompt using an AI model (e.g., OpenAI GPT-3). This prompt contains information to output optimized cooking instructions based on the user's request. The input is the converted text, and the output is the prompt.

[0548] Step 4:

[0549] The server uses the generated prompts to create customized cooking instructions based on an AI model. This process takes into account the user's age, skill level, allergy information, and available ingredients. The input is the prompts, and the output is the optimized cooking instructions.

[0550] Step 5:

[0551] The device receives cooking instructions sent from the server and generates visual and audio guides using Unity and Flutter. These guides are designed to make it easy for the user to intuitively understand the steps. The input is customized cooking instructions, and the output is a visual and audio interface.

[0552] Step 6:

[0553] The user follows the terminal's instructions to proceed with cooking. The terminal monitors the user's actions and movements in real time and detects dangerous situations using libraries such as OpenCV. Input is user action data, and output is a warning alert in case of danger.

[0554] Step 7:

[0555] If the device detects a hazard, it immediately issues an audible and visual warning, prompting the user to take appropriate safety measures. At this time, the user's progress is temporarily paused, and the next step is not guided until the situation is safe. The input is hazard detection information, and the output is the warning interface.

[0556] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0557] This invention is a system that enables users, including children, to safely learn to cook and cook independently. The system has means to convert voice input into text data, generate recipes based on the user's age, skill level, allergy information, and available ingredients, and provide visual and audio guidance. It also has a function to monitor user operations, detect dangers, and issue warnings. In addition, the invention incorporates an emotion engine, providing a new ability to recognize user emotions and adjust the system's operation accordingly.

[0558] The server receives the user's voice input and converts it into text data using speech recognition technology. Based on this, the server refers to user data, retrieves appropriate recipes from the database, and customizes them. The server further analyzes the user's emotional state using an emotion engine and suggests or adjusts recipes according to the user's emotions. The results are then formatted into visual and audio guide formats and sent to the terminal.

[0559] The device provides the user with visual animations and audio guidance based on data sent from the server. The device understands the user's emotional state and adjusts the tone and content of the guidance accordingly. For example, if the user is anxious, it can provide more detailed explanations or words of encouragement. The device also monitors the user's actions and issues warnings if it detects danger through sensors or cameras. The emotion engine plays a crucial role here as well, adjusting the priority and delivery of warnings to match the user's mental state.

[0560] When a user begins cooking, they enter the name of the dish they want to make into the device. They then proceed with cooking according to the device's instructions, but especially if they are emotionally unstable or doing it for the first time, the device provides support that takes the user's emotions into consideration. For example, if cooking is not going as planned, the device senses the user's emotions and provides support such as, "It's okay, let's relax and continue."

[0561] These comprehensive features allow the system to provide users with a safe and enjoyable cooking experience, not only by teaching them how to cook, but also by offering emotional support.

[0562] The following describes the processing flow.

[0563] Step 1:

[0564] The user speaks into the device to specify the dish they want to make. For example, they might say, "I want to make lasagna."

[0565] Step 2:

[0566] The device records the user's voice and uses a speech recognition engine to convert the voice data into text data. This text includes the user's cooking preferences.

[0567] Step 3:

[0568] The terminal sends the converted text data to the server and sends a request that includes user information, age, skill level, and allergy information.

[0569] Step 4:

[0570] The server receives the request and retrieves the corresponding recipe from the database. It then adjusts the recipe according to the user's skill level and then customizes it.

[0571] Step 5:

[0572] The server customizes recipes based on the user's age, skill level, and allergy information, and uses an emotion engine to analyze additional data (e.g., voice and facial expressions) to estimate the user's emotions.

[0573] Step 6:

[0574] Based on the user's emotions analyzed by the server, the system formats customized recipes and guides as audio and visual data and sends them to the device.

[0575] Step 7:

[0576] The device receives data from the server, visually displays recipe instructions on the screen, and provides voice guidance to the user. The instructions are delivered in a calm tone that is adjusted to the user's emotional state.

[0577] Step 8:

[0578] The user follows the visual and audio guidance on the device to perform the cooking process. This includes gathering ingredients and following instructions.

[0579] Step 9:

[0580] The device monitors user actions through sensors and user feedback, and issues warnings when danger is anticipated, such as the use of knives or firearms. The strength of the warning is adjusted according to the user's emotions.

[0581] Step 10:

[0582] If a user has questions while cooking, they can contact the device. For example, they might ask, "Could you explain in more detail?"

[0583] Step 11:

[0584] The server receives the user's question, analyzes its content, generates an appropriate answer, and sends it to the terminal.

[0585] Step 12:

[0586] The terminal communicates responses from the server to the user via voice and text, supporting the progress of the cooking process.

[0587] Step 13:

[0588] The user completes all steps and finishes cooking. The device provides feedback saying, "Great job! Your dish is finished!" and praises the user.

[0589] (Example 2)

[0590] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0591] In modern society, learning and practicing cooking safely is an important skill. However, especially for children and beginners, the dangers posed by the tools and heating equipment used in the cooking process make it difficult to learn with peace of mind. Furthermore, it is difficult to meet individual needs because it is not possible to provide guides that are appropriately tailored to the learner's skill level and mental state. As a result, the cooking learning process can become inadequate and stressful, potentially leading to decreased motivation and failure to ensure safety.

[0592] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0593] In this invention, the server includes means for converting acoustic input into textual information, means for generating procedures based on the user's age, skill level, allergy information, and available ingredients, and means for guiding the generated procedures visually and audibly. This makes it possible to provide an optimized cooking learning environment for each individual user while ensuring user safety.

[0594] "Means for converting audio input into textual information" refers to technology that converts audio data spoken by a user into digital text, and has the function of converting speech into text using speech recognition technology.

[0595] "Textual information" refers to text data converted from audio data and recorded in digital format, enabling further processing and analysis on the server.

[0596] "Means for generating procedures based on the user's age, skill level, allergy information, and available ingredients" refers to technology that utilizes algorithms and databases to suggest the optimal cooking procedure according to the individual user's basic information and circumstances.

[0597] "Means of providing guidance visually and audibly" refers to technologies that use display devices and speech synthesis technology to provide guidance information in order to present the generated cooking procedures in a user-friendly format.

[0598] "Means for monitoring user actions and detecting dangerous situations" refers to technologies that monitor user actions in real time through sensors and cameras to identify potential dangers.

[0599] "Warning mechanisms" refer to technologies that communicate messages through visual and auditory means to warn or alert users to identified dangers.

[0600] "Means for analyzing emotional states and adjusting procedures and warnings accordingly" refers to emotion analysis technology that identifies the user's emotions and dynamically optimizes cooking procedures and warning content based on the results.

[0601] This system is designed to allow users to learn to cook safely and efficiently. First, the user voice-inputs the desired dish into the terminal. The terminal uses its built-in microphone to capture the voice data and transmits it to the server.

[0602] The server converts audio data into text data using speech recognition technology. A commonly used speech recognition service is employed for this purpose. For example, a general speech recognition platform can be used as a means of "converting acoustic input into text information." Based on the converted text data, the server generates the optimal cooking procedure (recipe) from a database, taking into account the user's age, skill level, allergy information, and available ingredients. A general database management system is used for this.

[0603] Next, the server uses sentiment analysis technology to evaluate the user's emotional state. This analysis can utilize a general sentiment analysis API. Based on the evaluation results, it generates appropriate instructions and warning messages for the user's situation. For example, if the user is feeling anxious, detailed and reassuring guidance is provided.

[0604] The server then sends the adjusted recipe and guide to the terminal. The terminal provides visual and audio guidance to the user based on the received data. A display device is used for visual guidance, and text-to-speech technology is used for audio guidance. This embodiment allows the user to receive guidance tailored to their current situation. For example, if the user wants to know how to make omurice, they might input the following prompt: "Please tell me an easy way to make omurice. I would appreciate it if you could also provide the necessary ingredients and specific steps."

[0605] This system allows users to learn cooking techniques safely and in a way that is tailored to their individual circumstances. Furthermore, if a hazard is anticipated, the terminal will issue appropriate warnings through real-time monitoring, ensuring safety during cooking.

[0606] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0607] Step 1:

[0608] The user inputs their cooking preferences and related information by voice into the terminal. The terminal captures this audio data through its microphone and saves it as an audio file. The input is the user's voice, and the output is data in audio file format. The terminal compresses the audio file on-device and prepares it for transfer to the server.

[0609] Step 2:

[0610] The server receives audio files sent from the terminal. The received audio files are analyzed through a speech recognition system and converted into text data. Here, the input is an audio file, and the output is text data. The server processes this text data and extracts information such as the name of the dish and the required ingredients.

[0611] Step 3:

[0612] The server searches for the optimal recipe based on the extracted text data and references the user's basic information. Input consists of text data and user information, while output is customized recipe data. The server executes appropriate database queries, taking into account the user's age, skill level, allergy information, and available ingredients.

[0613] Step 4:

[0614] The server uses an emotion analysis engine to analyze text data and available historical information from the user to evaluate their emotional state. The input is text data and associated historical information, and the output is the evaluation result of the emotional state. Based on this result, the server flexibly adjusts the recipe content and guidance methods.

[0615] Step 5:

[0616] The server formats the adjusted recipes and guidance methods into visual and audio guidance formats and sends them to the terminal. The input is customized recipe data and sentiment evaluation results, and the output is formatted guide data.

[0617] Step 6:

[0618] The terminal displays visual guidance to the user based on guide data received from the server and provides voice guidance using speech synthesis technology. The input is guide data, and the output is visual information on the display and voice information played from the speaker.

[0619] Step 7:

[0620] The terminal uses built-in sensors and cameras to monitor user actions in real time and ensure security. Input is data from sensors and cameras, and output is a warning message if safety measures are required. In addition, it dynamically provides further detailed guidance if needed in response to user actions.

[0621] (Application Example 2)

[0622] Next, we will explain Application Example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0623] In modern society, there is a need for beginners and children to learn cooking skills safely and meaningfully. However, conventional cooking support systems lack sufficient individual support that takes into account the user's skill level and emotional state, and in particular, they lack adjustment functions that utilize emotional states. This can lead to users feeling stressed and potentially lower the quality of the cooking experience.

[0624] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0625] In this invention, the server includes means for converting voice input from the user into text data, means for generating recipes based on the user's age, skill level, allergy information, and items, and means for recognizing the user's emotional state and adjusting the system's operation. This enables optimal and flexible cooking support tailored to the individual characteristics of each user.

[0626] "User" refers to a person who uses this system to cook.

[0627] "Means of converting voice input into text data" refers to methods for converting voice information from a user into text information.

[0628] "Age group" refers to information indicating the user's age range or stage of development.

[0629] "Technical level" refers to information that represents the user's level of knowledge and skills regarding cooking.

[0630] "Allergy information" refers to information about food allergies that the user possesses.

[0631] "Means for generating manufacturing methods based on articles" refers to methods for creating cooking methods based on the ingredients a user possesses.

[0632] "Means of displaying as visual and auditory instructions" refers to methods for clearly presenting generated cooking information to the user.

[0633] "Means of monitoring and detecting dangerous situations" means methods for constantly observing user behavior and recognizing conditions that could potentially compromise safety.

[0634] "Warning mechanisms" refer to methods used to alert users to detected risks.

[0635] "Means of recognizing emotional states and adjusting system operation" refers to methods for analyzing a user's emotional responses and appropriately modifying the instructions and support provided by the system.

[0636] The system for implementing this invention combines multiple functions to provide users with a safe and educational cooking experience. Specific examples are shown below.

[0637] The server utilizes a cloud-based platform that runs speech recognition and natural language processing technologies. Specifically, it leverages Amazon AWS and Google Cloud AI, and further converts user voice input into text data via the OpenAI API. This voice data is used by an emotion engine to analyze the user's emotions. Based on this emotion analysis, the recipes and advice provided to the user are dynamically adjusted.

[0638] The device in question is a smartphone, which plays a role in providing visual and audio guidance to the user. Based on data received from the server, it displays recipes that take into account the user's age, skill level, allergies, and available ingredients, and monitors the user's actions and emotions while cooking. It can also detect hazards using its built-in camera and sensors and issue warnings in real time.

[0639] As the user progresses through each step of the cooking process, they receive instructions from the device and ask questions via voice as needed. If the user's emotions are unstable, the device proactively offers words of encouragement and detailed explanations, responding in a way that is sensitive to the user's feelings. This allows the user to continue cooking with peace of mind.

[0640] For example, if a user is making fruit salad for the first time, the device can provide voice support such as, "Next, cut the apples. If you're unsure how to cut them, you can proceed slowly."

[0641] An example of a prompt for a generative AI model is, "What kind of support should be offered if a user becomes confused while eating a fruit salad?" This prompt allows the AI ​​to generate appropriate advice and guidance.

[0642] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0643] Step 1:

[0644] The server receives voice input from the user and converts it into text data using cloud-based speech recognition technology. The input is the user's voice, and the output is text data. In this conversion, a speech recognition API is used to perform data processing such as noise reduction and speech feature extraction.

[0645] Step 2:

[0646] The server references the user's age, skill level, allergy information, and available ingredients from text data to generate appropriate recipes from the database. Input is text data and user profile information, and output is user-optimized recipe information. The server queries the database to select recipes that match the specified criteria.

[0647] Step 3:

[0648] The server uses an emotion engine to analyze the user's emotional state and adjusts recipes and advice according to the user's emotions. Input is the user's text data and profile data, and output is adjusted recipe information that reflects their emotions. Natural language processing and sentiment analysis are used to determine appropriate instructions for the user.

[0649] Step 4:

[0650] The terminal provides visual and audio instructions to the user based on pre-configured recipe information received from the server. The input is the recipe information from the server, and the output is the visual and audio instructions to the user. The terminal application manages this and presents it to the user via a digital interface.

[0651] Step 5:

[0652] The user performs cooking actions, which are monitored by the device's built-in camera and sensors. The input is the user's cooking actions, and the output is detected data related to hazards or safety. Image processing technology is used to identify dangerous behaviors in real time.

[0653] Step 6:

[0654] The device alerts the user if a threat is detected. The input is the detected threat information, and the output is a warning message to the user. Audio and visual warnings are provided to immediately draw the user's attention.

[0655] Step 7:

[0656] When a user experiences emotional distress, the device provides comforting words and encouraging messages based on emotional data. The input is the user's emotional data, and the output is words of encouragement. A generative AI model is used to generate prompts and appropriate words to stabilize the user's emotions.

[0657] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0658] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0659] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0660] [Fourth Embodiment]

[0661] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0662] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0663] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0664] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0665] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0666] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0667] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0668] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0669] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0670] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0671] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0672] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0673] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0674] This invention is a system for children to safely learn to cook and cook independently, integrating functions such as voice input, text conversion, recipe generation, visual and audio guidance, hazard detection, and warning issuance. The system mainly consists of a server, terminals, and users.

[0675] The server is the core of the system, hosting an AI model that processes user input. Once the user's voice input is converted to text data, the server references this data and retrieves relevant information from the recipe database. Furthermore, it customizes the recipe based on the user's age, skill level, and allergy information. The server then formats the final recipe and cooking instructions and sends them to the device as visual and audio guides.

[0676] The terminal is a user-operated device that provides an interface between the user and the server through visual animations and audio guidance. The terminal receives recipes and instructions from the server and presents them to the user sequentially. It guides the user to the next step according to their progress and issues warnings as needed.

[0677] The user is the central user of the system, interacting with it through a terminal and performing cooking according to their wishes. For example, if the user enters "I want to make chocolate cookies" into the terminal, the entire system process begins. The user follows the guide on the terminal, prepares the ingredients, and proceeds with cooking according to the instructions. The terminal can provide real-time warnings for high-risk steps, such as when using a knife or setting the oven temperature.

[0678] Thus, this system provides an embodiment of a system that, by combining visual and auditory aids, enables users to easily learn how to cook and to proceed with cooking safely and efficiently.

[0679] The following describes the processing flow.

[0680] Step 1:

[0681] The user speaks into the device and enters the name of the dish they want to make. For example, they might say, "I want to make chocolate cookies."

[0682] Step 2:

[0683] The device records the user's voice and converts it into text data using speech recognition technology. This text data includes the name of the dish.

[0684] Step 3:

[0685] The device sends a request to the server containing the converted text data. This request also includes user information (age, skill level, allergy information, etc.).

[0686] Step 4:

[0687] The server receives the request and retrieves the appropriate recipe from the database based on the user information. Furthermore, it customizes the recipe to suit the user's needs.

[0688] Step 5:

[0689] The server formats customized recipes and cooking instructions into visual and audio guide formats and sends them to the terminal.

[0690] Step 6:

[0691] The device receives the data sent to it and provides the user with visual animations and audio guidance. This allows the user to proceed with cooking while receiving instructions step by step.

[0692] Step 7:

[0693] The user gathers the ingredients and begins cooking based on the instructions on the device. They follow the guide to perform the specific steps.

[0694] Step 8:

[0695] The device monitors the user's actions while cooking and ensures safety by issuing warnings when it detects dangers such as the use of knives or open flames.

[0696] Step 9:

[0697] If a user has any questions or concerns, they can ask them via voice through their device. For example, they might ask, "What should I do next?"

[0698] Step 10:

[0699] The server receives the user's question, generates an appropriate response, and sends it to the terminal.

[0700] Step 11:

[0701] The terminal communicates responses from the server to the user via voice and visuals, supporting the cooking process.

[0702] Step 12:

[0703] The user completes all cooking steps and the dish is finished. The device provides feedback by notifying the user with "Great job! Your dish is ready!"

[0704] (Example 1)

[0705] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0706] The problem this invention aims to solve is that it is difficult for users with limited skills, especially children, to learn to cook safely and effectively. There is a need to reduce the risk of accidents due to improper understanding of cooking procedures and dangerous cooking processes, and to support users so they can cook with confidence.

[0707] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0708] In this invention, the server includes a processing unit that converts user input voice into text data, a processing unit that constructs cooking procedures based on age, skill level, and health information, and a processing unit that provides the generated cooking procedures in both display and audio format. This enables users to enjoy a safe and effective cooking experience tailored to their own circumstances and abilities.

[0709] "Conversion of user-input speech to text data" is the process of recognizing the speech spoken by the user as a digital signal and converting it into text format.

[0710] "Cooking procedure configuration based on age, skill level, and health information" means selecting the most suitable recipes and procedures according to the user's attributes and customizing them to support learning and practicing cooking.

[0711] "Displaying and providing generated cooking instructions via audio" means guiding users through cooking procedures using a visual and audio interface designed for easy understanding.

[0712] "Monitoring user work status" means tracking the user's cooking process and evaluating the progress and safety of the process.

[0713] "Detecting safety threats" is a process that involves detecting potentially dangerous actions or conditions during cooking to prevent accidents.

[0714] "Implementing a warning" means prompting users to take precautions using audio or visual means and warning them to proceed with cooking safely.

[0715] This invention is a system aimed at enabling users to safely learn to cook and to cook independently. This system consists of a server, terminals, and users.

[0716] The server plays a central role in the system, utilizing a speech recognition API to convert user-input speech into text data. Here, the speech data is converted into text using Google's speech recognition API or general speech recognition software. Based on this text data, a generative AI model is used to generate recipes. A general natural language processing model can be used as the generative AI model; a possible prompt would be "Generate a simple and safe chocolate cookie recipe for an 8-year-old child." Furthermore, the server accesses a database to customize the recipe, taking into account the user's age, skill level, and health information. The customized recipe is then formatted as a visual and audio guide and sent to the terminal.

[0717] The terminal is a device that guides the user through procedures using visual and audio guidance transmitted from the server. Sequential instructions are provided via animation and audio on devices such as tablets and smartphones. The terminal can monitor the user's cooking progress and provide safety warnings as needed. For example, when using a knife, the terminal will issue a real-time audio warning.

[0718] The user is the one who operates the terminal and follows the guide to cook. The user voice-inputs the desired dish into the terminal, prepares the ingredients based on the provided guide, and safely proceeds with cooking according to the procedure. For example, the user tells the server that they want to make chocolate cookies and proceeds with cooking according to the provided recipe and procedure.

[0719] In this way, this system can provide support for users to learn cooking in an easy-to-understand and safe manner.

[0720] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0721] Step 1:

[0722] The user inputs the desired recipe by voice into the terminal. For example, they might say, "I want to make chocolate cookies." This voice input becomes the input data.

[0723] Step 2:

[0724] The terminal transmits the recorded audio data as a digital signal to the server. This becomes the input to the server.

[0725] Step 3:

[0726] The server uses a speech recognition API to convert the received audio data into text data. This conversion process outputs the text "I want to make chocolate cookies." Here, analog data (voice input) is processed into digital text data.

[0727] Step 4:

[0728] The server inputs a prompt into the generating AI model. Based on the prompt, "Generate a simple and safe chocolate cookie recipe for an 8-year-old child," the AI ​​model generates recipe data. This becomes the input data for the next process.

[0729] Step 5:

[0730] The server reviews the generated recipe data and customizes it, taking into account the user's profile information (age, skill level, health information). For example, it might adjust the weight of ingredients to make it easier for children to use, or simplify the process. This results in a recipe optimized for the user.

[0731] Step 6:

[0732] The server formats the customized recipe as a visual and audio guide and sends it to the terminal. This is the input data for the terminal.

[0733] Step 7:

[0734] The device guides the user through the cooking process visually and audibly, based on the received guide data. Each step is clearly displayed with animation and audio, following the recipe order.

[0735] Step 8:

[0736] The terminal monitors the user's actions in real time and provides warnings via voice alerts and on-screen displays during potentially dangerous processes. For example, it issues warnings when using knives or when heating an oven. This output is intended to ensure the user's safety.

[0737] Step 9:

[0738] The user follows visual and audio guidance to complete the cooking process. This allows the user to complete the dish safely and effectively. The output is the finished dish.

[0739] (Application Example 1)

[0740] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0741] A support system for children to learn to cook safely and effectively requires the provision of flexible cooking procedures tailored to the child's age and skill level, as well as real-time hazard detection and warning. Furthermore, an interactive interface is needed to engage children's interest and encourage their active participation in cooking.

[0742] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0743] In this invention, the server includes means for converting voice input from the user into text data, means for generating cooking instructions based on the user's age, skill level, allergy information, and available ingredients, means for displaying the generated cooking instructions as visual and audio instructions, and means for monitoring the user's actions and detecting dangerous situations. This enables children to learn to cook safely and in an engaging way.

[0744] "Means of converting voice input from users into text data" refers to technology that converts information in audio format into digital text format.

[0745] "Means for generating cooking instructions based on the user's age, skill level, allergy information, and available ingredients" refers to an algorithm or program that creates optimal cooking instructions tailored to the user.

[0746] "Means for displaying generated cooking instructions as visual and audio instructions" refers to a display device or program for visually and aurally communicating generated instructions to the user.

[0747] "Means of monitoring user actions and detecting dangerous situations" refers to monitoring functions using sensors and software to track user behavior and determine safety.

[0748] "Means for providing a visual interface" refers to a design or platform for visually facilitating the exchange of information between the user and the system.

[0749] "Means of tracking user behavior and evaluating safety based on predetermined criteria" refers to algorithms or systems that analyze behavioral logs and automatically make safety judgments.

[0750] The system for implementing the present invention consists of three main elements: a server, a terminal, and a user. The server is the core of the system, converting the voice input provided by the user into text and generating cooking instructions based on that. Specifically, the server uses the Google Speech-to-Text API to convert voice into text data. This text data is processed by a recipe generation engine using an AI model hosted on the server, for example, OpenAI's GPT-3 can be used. The engine takes into account the user's age, skill level, allergy information, and available ingredients to generate the optimal cooking instructions.

[0751] The terminal is the device that serves as the interface with the user. The terminal receives cooking instructions sent from the server and can utilize development platforms such as Unity and Flutter to guide the user visually and audibly. The terminal also implements voice guidance using the Speech Synthesis API. It also has the capability to monitor user behavior in real time, recognize dangerous situations using libraries such as OpenCV, and issue warnings.

[0752] Users interact with the system through their device and utilize it to safely learn how to cook their desired dishes. For example, if an 8-year-old child requests to "make spaghetti," the AI ​​model receives the following prompt: "Please create a recipe that allows a child to safely and easily make spaghetti. The child is 8 years old, and only household equipment is allowed." Based on this information, the system generates safe and easy-to-understand instructions for children and guides them visually and audibly through the device. In this way, the present invention makes it possible to provide an environment in which users can learn to cook with interest and actively.

[0753] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0754] Step 1:

[0755] The user inputs cooking information into the device using voice. This voice input is based on the user's request and includes specific details such as the dish they want to make and any other requirements.

[0756] Step 2:

[0757] The device converts audio data into text data using the Google Speech-to-Text API. This conversion transforms the audio content into a digital format that the server can understand. The input is audio data, and the output is the corresponding text data.

[0758] Step 3:

[0759] The server receives input text and generates a prompt using an AI model (e.g., OpenAI GPT-3). This prompt contains information to output optimized cooking instructions based on the user's request. The input is the converted text, and the output is the prompt.

[0760] Step 4:

[0761] The server uses the generated prompts to create customized cooking instructions based on an AI model. This process takes into account the user's age, skill level, allergy information, and available ingredients. The input is the prompts, and the output is the optimized cooking instructions.

[0762] Step 5:

[0763] The device receives cooking instructions sent from the server and generates visual and audio guides using Unity and Flutter. These guides are designed to make it easy for the user to intuitively understand the steps. The input is customized cooking instructions, and the output is a visual and audio interface.

[0764] Step 6:

[0765] The user follows the terminal's instructions to proceed with cooking. The terminal monitors the user's actions and movements in real time and detects dangerous situations using libraries such as OpenCV. Input is user action data, and output is a warning alert in case of danger.

[0766] Step 7:

[0767] If the device detects a hazard, it immediately issues an audible and visual warning, prompting the user to take appropriate safety measures. At this time, the user's progress is temporarily paused, and the next step is not guided until the situation is safe. The input is hazard detection information, and the output is the warning interface.

[0768] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0769] This invention is a system that enables users, including children, to safely learn to cook and cook independently. The system has means to convert voice input into text data, generate recipes based on the user's age, skill level, allergy information, and available ingredients, and provide visual and audio guidance. It also has a function to monitor user operations, detect dangers, and issue warnings. In addition, the invention incorporates an emotion engine, providing a new ability to recognize user emotions and adjust the system's operation accordingly.

[0770] The server receives the user's voice input and converts it into text data using speech recognition technology. Based on this, the server refers to user data, retrieves appropriate recipes from the database, and customizes them. The server further analyzes the user's emotional state using an emotion engine and suggests or adjusts recipes according to the user's emotions. The results are then formatted into visual and audio guide formats and sent to the terminal.

[0771] The device provides the user with visual animations and audio guidance based on data sent from the server. The device understands the user's emotional state and adjusts the tone and content of the guidance accordingly. For example, if the user is anxious, it can provide more detailed explanations or words of encouragement. The device also monitors the user's actions and issues warnings if it detects danger through sensors or cameras. The emotion engine plays a crucial role here as well, adjusting the priority and delivery of warnings to match the user's mental state.

[0772] When a user begins cooking, they enter the name of the dish they want to make into the device. They then proceed with cooking according to the device's instructions, but especially if they are emotionally unstable or doing it for the first time, the device provides support that takes the user's emotions into consideration. For example, if cooking is not going as planned, the device senses the user's emotions and provides support such as, "It's okay, let's relax and continue."

[0773] These comprehensive features allow the system to provide users with a safe and enjoyable cooking experience, not only by teaching them how to cook, but also by offering emotional support.

[0774] The following describes the processing flow.

[0775] Step 1:

[0776] The user speaks into the device to specify the dish they want to make. For example, they might say, "I want to make lasagna."

[0777] Step 2:

[0778] The device records the user's voice and uses a speech recognition engine to convert the voice data into text data. This text includes the user's cooking preferences.

[0779] Step 3:

[0780] The terminal sends the converted text data to the server and sends a request that includes user information, age, skill level, and allergy information.

[0781] Step 4:

[0782] The server receives the request and retrieves the corresponding recipe from the database. It then adjusts the recipe according to the user's skill level and then customizes it.

[0783] Step 5:

[0784] The server customizes recipes based on the user's age, skill level, and allergy information, and uses an emotion engine to analyze additional data (e.g., voice and facial expressions) to estimate the user's emotions.

[0785] Step 6:

[0786] Based on the user's emotions analyzed by the server, the system formats customized recipes and guides as audio and visual data and sends them to the device.

[0787] Step 7:

[0788] The device receives data from the server, visually displays recipe instructions on the screen, and provides voice guidance to the user. The instructions are delivered in a calm tone that is adjusted to the user's emotional state.

[0789] Step 8:

[0790] The user follows the visual and audio guidance on the device to perform the cooking process. This includes gathering ingredients and following instructions.

[0791] Step 9:

[0792] The device monitors user actions through sensors and user feedback, and issues warnings when danger is anticipated, such as the use of knives or firearms. The strength of the warning is adjusted according to the user's emotions.

[0793] Step 10:

[0794] If a user has questions while cooking, they can contact the device. For example, they might ask, "Could you explain in more detail?"

[0795] Step 11:

[0796] The server receives the user's question, analyzes its content, generates an appropriate answer, and sends it to the terminal.

[0797] Step 12:

[0798] The terminal communicates responses from the server to the user via voice and text, supporting the progress of the cooking process.

[0799] Step 13:

[0800] The user completes all steps and finishes cooking. The device provides feedback saying, "Great job! Your dish is finished!" and praises the user.

[0801] (Example 2)

[0802] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0803] In modern society, learning and practicing cooking safely is an important skill. However, especially for children and beginners, the dangers posed by the tools and heating equipment used in the cooking process make it difficult to learn with peace of mind. Furthermore, it is difficult to meet individual needs because it is not possible to provide guides that are appropriately tailored to the learner's skill level and mental state. As a result, the cooking learning process can become inadequate and stressful, potentially leading to decreased motivation and failure to ensure safety.

[0804] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0805] In this invention, the server includes means for converting acoustic input into textual information, means for generating procedures based on the user's age, skill level, allergy information, and available ingredients, and means for guiding the generated procedures visually and audibly. This makes it possible to provide an optimized cooking learning environment for each individual user while ensuring user safety.

[0806] "Means for converting audio input into textual information" refers to technology that converts audio data spoken by a user into digital text, and has the function of converting speech into text using speech recognition technology.

[0807] "Textual information" refers to text data converted from audio data and recorded in digital format, enabling further processing and analysis on the server.

[0808] "Means for generating procedures based on the user's age, skill level, allergy information, and available ingredients" refers to technology that utilizes algorithms and databases to suggest the optimal cooking procedure according to the individual user's basic information and circumstances.

[0809] "Means of providing guidance visually and audibly" refers to technologies that use display devices and speech synthesis technology to provide guidance information in order to present the generated cooking procedures in a user-friendly format.

[0810] "Means for monitoring user actions and detecting dangerous situations" refers to technologies that monitor user actions in real time through sensors and cameras to identify potential dangers.

[0811] "Warning mechanisms" refer to technologies that communicate messages through visual and auditory means to warn or alert users to identified dangers.

[0812] "Means for analyzing emotional states and adjusting procedures and warnings accordingly" refers to emotion analysis technology that identifies the user's emotions and dynamically optimizes cooking procedures and warning content based on the results.

[0813] This system is designed to allow users to learn to cook safely and efficiently. First, the user voice-inputs the desired dish into the terminal. The terminal uses its built-in microphone to capture the voice data and transmits it to the server.

[0814] The server converts audio data into text data using speech recognition technology. A commonly used speech recognition service is employed for this purpose. For example, a general speech recognition platform can be used as a means of "converting acoustic input into text information." Based on the converted text data, the server generates the optimal cooking procedure (recipe) from a database, taking into account the user's age, skill level, allergy information, and available ingredients. A general database management system is used for this.

[0815] Next, the server uses sentiment analysis technology to evaluate the user's emotional state. This analysis can utilize a general sentiment analysis API. Based on the evaluation results, it generates appropriate instructions and warning messages for the user's situation. For example, if the user is feeling anxious, detailed and reassuring guidance is provided.

[0816] The server then sends the adjusted recipe and guide to the terminal. The terminal provides visual and audio guidance to the user based on the received data. A display device is used for visual guidance, and text-to-speech technology is used for audio guidance. This embodiment allows the user to receive guidance tailored to their current situation. For example, if the user wants to know how to make omurice, they might input the following prompt: "Please tell me an easy way to make omurice. I would appreciate it if you could also provide the necessary ingredients and specific steps."

[0817] This system allows users to learn cooking techniques safely and in a way that is tailored to their individual circumstances. Furthermore, if a hazard is anticipated, the terminal will issue appropriate warnings through real-time monitoring, ensuring safety during cooking.

[0818] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0819] Step 1:

[0820] The user inputs their cooking preferences and related information by voice into the terminal. The terminal captures this audio data through its microphone and saves it as an audio file. The input is the user's voice, and the output is data in audio file format. The terminal compresses the audio file on-device and prepares it for transfer to the server.

[0821] Step 2:

[0822] The server receives audio files sent from the terminal. The received audio files are analyzed through a speech recognition system and converted into text data. Here, the input is an audio file, and the output is text data. The server processes this text data and extracts information such as the name of the dish and the required ingredients.

[0823] Step 3:

[0824] The server searches for the optimal recipe based on the extracted text data and references the user's basic information. Input consists of text data and user information, while output is customized recipe data. The server executes appropriate database queries, taking into account the user's age, skill level, allergy information, and available ingredients.

[0825] Step 4:

[0826] The server uses an emotion analysis engine to analyze text data and available historical information from the user to evaluate their emotional state. The input is text data and associated historical information, and the output is the evaluation result of the emotional state. Based on this result, the server flexibly adjusts the recipe content and guidance methods.

[0827] Step 5:

[0828] The server formats the adjusted recipes and guidance methods into visual and audio guidance formats and sends them to the terminal. The input is customized recipe data and sentiment evaluation results, and the output is formatted guide data.

[0829] Step 6:

[0830] The terminal displays visual guidance to the user based on guide data received from the server and provides voice guidance using speech synthesis technology. The input is guide data, and the output is visual information on the display and voice information played from the speaker.

[0831] Step 7:

[0832] The terminal uses built-in sensors and cameras to monitor user actions in real time and ensure security. Input is data from sensors and cameras, and output is a warning message if safety measures are required. In addition, it dynamically provides further detailed guidance if needed in response to user actions.

[0833] (Application Example 2)

[0834] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0835] In modern society, there is a need for beginners and children to learn cooking skills safely and meaningfully. However, conventional cooking support systems lack sufficient individual support that takes into account the user's skill level and emotional state, and in particular, they lack adjustment functions that utilize emotional states. This can lead to users feeling stressed and potentially lower the quality of the cooking experience.

[0836] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0837] In this invention, the server includes means for converting voice input from the user into text data, means for generating recipes based on the user's age, skill level, allergy information, and items, and means for recognizing the user's emotional state and adjusting the system's operation. This enables optimal and flexible cooking support tailored to the individual characteristics of each user.

[0838] "User" refers to a person who uses this system to cook.

[0839] "Means of converting voice input into text data" refers to methods for converting voice information from a user into text information.

[0840] "Age group" refers to information indicating the user's age range or stage of development.

[0841] "Technical level" refers to information that represents the user's level of knowledge and skills regarding cooking.

[0842] "Allergy information" refers to information about food allergies that the user possesses.

[0843] "Means for generating manufacturing methods based on articles" refers to methods for creating cooking methods based on the ingredients a user possesses.

[0844] "Means of displaying as visual and auditory instructions" refers to methods for clearly presenting generated cooking information to the user.

[0845] "Means of monitoring and detecting dangerous situations" means methods for constantly observing user behavior and recognizing conditions that could potentially compromise safety.

[0846] "Warning mechanisms" refer to methods used to alert users to detected risks.

[0847] "Means of recognizing emotional states and adjusting system operation" refers to methods for analyzing a user's emotional responses and appropriately modifying the instructions and support provided by the system.

[0848] The system for implementing this invention combines multiple functions to provide users with a safe and educational cooking experience. Specific examples are shown below.

[0849] The server utilizes a cloud-based platform that runs speech recognition and natural language processing technologies. Specifically, it leverages Amazon AWS and Google Cloud AI, and further converts user voice input into text data via the OpenAI API. This voice data is used by an emotion engine to analyze the user's emotions. Based on this emotion analysis, the recipes and advice provided to the user are dynamically adjusted.

[0850] The device in question is a smartphone, which plays a role in providing visual and audio guidance to the user. Based on data received from the server, it displays recipes that take into account the user's age, skill level, allergies, and available ingredients, and monitors the user's actions and emotions while cooking. It can also detect hazards using its built-in camera and sensors and issue warnings in real time.

[0851] As the user progresses through each step of the cooking process, they receive instructions from the device and ask questions via voice as needed. If the user's emotions are unstable, the device proactively offers words of encouragement and detailed explanations, responding in a way that is sensitive to the user's feelings. This allows the user to continue cooking with peace of mind.

[0852] For example, if a user is making fruit salad for the first time, the device can provide voice support such as, "Next, cut the apples. If you're unsure how to cut them, you can proceed slowly."

[0853] An example of a prompt for a generative AI model is, "What kind of support should be offered if a user becomes confused while eating a fruit salad?" This prompt allows the AI ​​to generate appropriate advice and guidance.

[0854] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0855] Step 1:

[0856] The server receives voice input from the user and converts it into text data using cloud-based speech recognition technology. The input is the user's voice, and the output is text data. In this conversion, a speech recognition API is used to perform data processing such as noise reduction and speech feature extraction.

[0857] Step 2:

[0858] The server references the user's age, skill level, allergy information, and available ingredients from text data to generate appropriate recipes from the database. Input is text data and user profile information, and output is user-optimized recipe information. The server queries the database to select recipes that match the specified criteria.

[0859] Step 3:

[0860] The server uses an emotion engine to analyze the user's emotional state and adjusts recipes and advice according to the user's emotions. Input is the user's text data and profile data, and output is adjusted recipe information that reflects their emotions. Natural language processing and sentiment analysis are used to determine appropriate instructions for the user.

[0861] Step 4:

[0862] The terminal provides visual and audio instructions to the user based on pre-configured recipe information received from the server. The input is the recipe information from the server, and the output is the visual and audio instructions to the user. The terminal application manages this and presents it to the user via a digital interface.

[0863] Step 5:

[0864] The user performs cooking actions, which are monitored by the device's built-in camera and sensors. The input is the user's cooking actions, and the output is detected data related to hazards or safety. Image processing technology is used to identify dangerous behaviors in real time.

[0865] Step 6:

[0866] The device alerts the user if a threat is detected. The input is the detected threat information, and the output is a warning message to the user. Audio and visual warnings are provided to immediately draw the user's attention.

[0867] Step 7:

[0868] When a user experiences emotional distress, the device provides comforting words and encouraging messages based on emotional data. The input is the user's emotional data, and the output is words of encouragement. A generative AI model is used to generate prompts and appropriate words to stabilize the user's emotions.

[0869] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0870] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0871] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0872] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0873] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0874] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0875] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0876] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0877] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0878] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0879] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0880] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0881] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0882] 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.

[0883] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0884] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0885] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0886] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0887] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0888] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0889] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0890] The following is further disclosed regarding the embodiments described above.

[0891] (Claim 1)

[0892] A means of converting voice input from a user into text data,

[0893] A means for generating recipes based on the user's age, skill level, allergy information, and available ingredients,

[0894] Means for displaying the generated recipe as visual and audio instructions,

[0895] A means of monitoring user actions and detecting dangerous situations,

[0896] Means of issuing warnings for detected dangers,

[0897] A system that includes this.

[0898] (Claim 2)

[0899] The system according to claim 1, comprising means for generating a response to a user inquiry.

[0900] (Claim 3)

[0901] The system according to claim 1, further comprising means for adjusting recipes according to the user's skill level.

[0902] "Example 1"

[0903] (Claim 1)

[0904] A processing device that converts user input speech into text data,

[0905] A processing device that constructs cooking procedures based on age, skill level, and health information,

[0906] A processing device that provides generated cooking instructions via display and audio,

[0907] A processing unit that monitors the user's work status and detects security threats,

[0908] A processing device that issues a warning about detected threats,

[0909] A device that includes this.

[0910] (Claim 2)

[0911] The apparatus according to claim 1, comprising a processing device for generating answers to user questions.

[0912] (Claim 3)

[0913] The apparatus according to claim 1, comprising a processing device that optimizes cooking procedures according to the user's abilities.

[0914] "Application Example 1"

[0915] (Claim 1)

[0916] A means of converting voice input from a user into text data,

[0917] A means for generating cooking instructions based on the user's age, skill level, allergy information, and available ingredients,

[0918] Means for displaying the generated cooking procedure as visual and audio instructions,

[0919] A means of monitoring user actions and detecting dangerous situations,

[0920] Means of issuing warnings for detected dangers,

[0921] Means for providing a visual interface,

[0922] A means of tracking user behavior and evaluating safety based on predetermined criteria,

[0923] A system that includes this.

[0924] (Claim 2)

[0925] The system according to claim 1, comprising means for generating a response to a user inquiry.

[0926] (Claim 3)

[0927] The system according to claim 1, further comprising means for adjusting cooking procedures according to the user's skill level.

[0928] "Example 2 of combining an emotion engine"

[0929] (Claim 1)

[0930] A means of converting audio input into text information,

[0931] A means for generating procedures based on the user's age, skill level, allergy information, and materials possessed,

[0932] A means of guiding the generated procedure visually and audibly,

[0933] A means of monitoring user operations and detecting dangerous situations,

[0934] Means of issuing warnings for detected dangers,

[0935] A means for analyzing the user's emotional state and adjusting procedures and warnings accordingly,

[0936] A system that includes this.

[0937] (Claim 2)

[0938] The system according to claim 1, comprising means for generating a response to a user inquiry based on the user's emotional state.

[0939] (Claim 3)

[0940] The system according to claim 1, further comprising means for adjusting procedures according to the user's skill level and emotional state.

[0941] "Application example 2 when combining with an emotional engine"

[0942] (Claim 1)

[0943] A means of converting voice input from a user into text data,

[0944] Means for generating a manufacturing process based on the user's age, skill level, allergy information, and the item,

[0945] Means for displaying the generated manufacturing process as visual and audio instructions,

[0946] A means of monitoring user actions and detecting dangerous situations,

[0947] Means of issuing warnings for detected dangers,

[0948] A means of recognizing the user's emotional state and adjusting the system's operation,

[0949] A system that includes this.

[0950] (Claim 2)

[0951] The system according to claim 1, comprising means for generating a response to a user inquiry.

[0952] (Claim 3)

[0953] The system according to claim 1, further comprising means for adjusting the manufacturing process according to the user's skill level. [Explanation of symbols]

[0954] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of converting voice input from a user into text data, A means for generating recipes based on the user's age, skill level, allergy information, and available ingredients, Means for displaying the generated recipe as visual and audio instructions, A means of monitoring user actions and detecting dangerous situations, Means of issuing warnings for detected dangers, A system that includes this.

2. The system according to claim 1, comprising means for generating a response to a user inquiry.

3. The system according to claim 1, further comprising means for adjusting recipes according to the user's skill level.

Images