system

Abstract

We provide the system. [Solution] A device placed in a public space, A means of analyzing the user's actions and speech in real time using multiple sensors, A means of presenting educational materials obtained from external information providers, A means of providing immediate feedback to users using artificial intelligence, A means for generating user-specific evaluation information based on analysis results, A system including means for displaying the aforementioned evaluation information to the user.

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 as a 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, individuals leading busy lives lack opportunities to receive high-quality education and training at appropriate times. In addition to this problem, there is also the issue that it is difficult to receive guidance optimized for individual abilities and goals. Therefore, there is a need for a system that provides individually optimized education and training in an easily accessible form.

Means for Solving the Problems

[0005] The present invention provides a device to be deployed in a public space, which includes means for analyzing the user's actions and speech in real time using multiple sensors, means for presenting educational materials obtained from external information providers, means for providing immediate feedback to the user using artificial intelligence, and means for generating and displaying user-specific evaluation information based on the analysis results. This device enables users to efficiently receive education and training tailored to their individual needs.

[0006] 1. "Public space" refers to places that are freely accessible to the general public, such as in front of train stations or in city blocks.

[0007] 2. "Device" refers to a collection of hardware and software combined to perform a specific function.

[0008] 3. A "sensor" refers to a device that detects specific physical information (such as motion or sound) and converts it into digital data.

[0009] 4. "User" refers to an individual who uses this system to receive specific education or training.

[0010] 5. "Action" refers to the physical movements and gestures performed by the user.

[0011] 6. "Speech" refers to the sounds and words that a user makes.

[0012] 7. "Real-time analysis" refers to the process of instantly processing the user's actions and speech and generating results.

[0013] 8. "External information providers" refer to third-party organizations or companies that provide educational materials and data necessary for coaching and education.

[0014] 9. "Artificial intelligence" refers to human-like intellectual abilities that are mimicked by computer programs.

[0015] 10. "Immediate feedback" refers to evaluations or instructions that are returned instantaneously in response to actions or statements.

[0016] 11. "Dedicated evaluation information" refers to evaluation results generated based on the activities and progress of individual users.

[0017] 12. "Display" refers to outputting as visual information to a screen or display.

Brief Description of the Drawings

[0018] [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] 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 a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [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 Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the language used in the following description will be explained.

[0021] In the following embodiments, a 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 a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0023] 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.

[0024] 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).

[0025] 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."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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".

[0039] One embodiment of this invention is a system that enables users to receive individually optimized education and training using a device installed in a public space. This system consists of three main components: a server, a terminal, and a user.

[0040] System Overview

[0041] The device incorporates multiple high-precision sensors and cameras to record and analyze the user's actions and speech in real time. The terminal displays educational materials obtained from external providers to support the specific training or educational program selected by the user. This provides an AI-powered interactive learning experience.

[0042] Program Description

[0043] The server identifies the appropriate AI model and learning materials based on the user's selection information sent from the terminal. The server constantly maintains and manages multiple AI models, each with specific educational and training functions built in.

[0044] After the user registers and selects a program, the terminal communicates with the server to retrieve the necessary learning materials and AI models, and immediately presents them to the user. The terminal also processes input data from sensors in real time, providing the user with immediate visual and audible feedback.

[0045] Users receive training and education through their chosen program. During this process, sensors detect the user's movements and speech, and the data is sent to an AI model via a server, providing optimal instructions and advice through the device.

[0046] For example, when a user selects a sports training program, the device utilizes an AI model to analyze sports movements and provides specific instructions on form and performance in real time. This allows the user to make precise adjustments to their movements and optimize their performance on the spot.

[0047] Through the configuration and processes described above, this system can provide users with high-quality educational and training opportunities that are available at any time.

[0048] The following describes the processing flow.

[0049] Step 1:

[0050] The server records the user's registration information and the type of program selected, received from the terminal, in a database. This information is used to determine the appropriate AI model and content.

[0051] Step 2:

[0052] The terminal displays details of available programs to the user on the screen. The user selects their desired program from the displayed options and confirms its specific details.

[0053] Step 3:

[0054] Once the user selects a program, the terminal sends that selection information to the server and requests the necessary learning materials and AI models.

[0055] Step 4:

[0056] The server accesses databases of external information providers to retrieve the most suitable learning materials for the program selected by the user. It also delivers AI models related to the selected program to the device.

[0057] Step 5:

[0058] The device provides users with an interactive screen using the delivered educational materials and AI models. The device captures user actions and speech data through sensors.

[0059] Step 6:

[0060] The server processes data sent from the terminal in real time and performs analysis based on an AI model. This generates immediate feedback for the user.

[0061] Step 7:

[0062] The device visualizes the feedback received from the server and provides instructions for the next action or utterance. The user continues training and learning while referring to these instructions.

[0063] Step 8:

[0064] When a user ends a session, the device sends that information to the server, which evaluates the user's performance data and creates feedback that includes areas for improvement for the next session.

[0065] Step 9:

[0066] The server saves the generated feedback to the user's account, and the device displays this to the user before ending the session. The user can then use the information they have reviewed to schedule their next session.

[0067] (Example 1)

[0068] 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."

[0069] In today's educational and training environments, providing learning and instruction optimized for individual needs in real time is considered difficult. Furthermore, the ability to provide effective, immediate feedback to users is required, but achieving this demands advanced technology. Additionally, there is still a lack of efficient and flexible systems capable of providing optimal learning experiences based on diverse user choices.

[0070] 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.

[0071] In this invention, the server includes means for identifying and operating the optimal generative AI model based on the user's selection, means for generating optimal instructions and learning materials from the AI ​​model using prompt statements, and means for displaying the evaluation information to the user. This makes it possible to provide the user with individually optimized education and training and to provide effective feedback in real time.

[0072] A "public space" refers to a place that is accessible to the general public and used for education and training.

[0073] A "device" refers to a piece of equipment with a hardware structure that provides users with an interactive experience through sensing and computation.

[0074] A "sensor" refers to a device that acquires external data, such as the user's actions and speech, and inputs it for analysis.

[0075] "External information providers" refer to information sources outside the system that provide educational content or training materials.

[0076] "Artificial intelligence" refers to computational algorithms designed to generate immediate feedback for the user.

[0077] "Feedback" refers to response information, including instructions and evaluations, provided in response to actions or utterances performed by the user.

[0078] "Evaluation information" refers to individual evaluation data generated based on the user's performance.

[0079] A "generative AI model" refers to an AI model used to generate optimal instructions based on user selections.

[0080] A "prompt statement" refers to an input statement used to cause an AI model to generate a specific output.

[0081] This invention is a system that enables users to receive individually optimized education and training using devices installed in public spaces. The system consists of three main components: a server, a terminal, and the user.

[0082] The server maintains and manages multiple AI models, identifying and running the optimal model based on user selections. During this process, prompts are used, and the AI ​​model generates instructions and training materials optimized for the user. This generated data is then provided to the user as immediate feedback.

[0083] The device utilizes multiple built-in high-precision sensors and cameras to record the user's actions and speech in real time and analyze the data. This analysis is sent to a server and used to generate appropriate instruction. The device also presents learning materials obtained from external providers, enhancing the learning experience through visual and audio feedback.

[0084] Users participate in programs offered through the device and receive personalized guidance from a generated AI model. For example, if a user selects a sports training program, the device uses a motion analysis model to immediately provide detailed guidance on improving form. An example of a specific prompt might be, "Create a basic form guide for the sport selected by the user."

[0085] Through this system, users can receive highly personalized education and training in real time, which is expected to improve learning efficiency and results.

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

[0087] Step 1:

[0088] Users access the system using a terminal and register. During registration, they enter personal information and educational / training programs of interest. The entered data is saved as a user profile and sent to the server. The terminal displays a list of currently available programs and prompts the user to make a selection. The user's selection information is then entered.

[0089] Step 2:

[0090] The terminal sends user selection information to the server. This information includes details about the program selected by the user. Based on the received selection information, the server selects an appropriate generative AI model. In the process, it generates prompt statements to apply to the selected AI model. Through these prompt statements, input is provided to optimize the instructions for the AI ​​model.

[0091] Step 3:

[0092] The server activates the selected AI model and generates optimal instructions and learning materials from the model using prompt messages. The prompt messages are input to the AI ​​model, which then outputs specific instruction content for the user as data. This data is immediately sent to the terminal.

[0093] Step 4:

[0094] The terminal receives the output of the AI ​​model sent from the server and displays it to the user. It also uses high-precision sensors and a camera within the terminal to record and analyze the user's actions and speech in real time. This analysis result is used as feedback. It receives real-time user data as input and outputs the processing results as feedback.

[0095] Step 5:

[0096] Users complete their selected educational and training programs based on instructions and feedback displayed on their devices. Continuous feedback on user actions and speech allows for immediate confirmation of performance improvements. Additional input regarding changes in user behavior is received, and improvement guidance is output based on this input.

[0097] (Application Example 1)

[0098] 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."

[0099] Improving the quality of customer service in modern brick-and-mortar stores requires effectively and efficiently enhancing the skills of each individual employee. However, traditional methods present challenges, such as abstract and immediacy-lacking feedback to employees, making it difficult to point out individual areas for improvement in a timely manner. Furthermore, accurately understanding customer service situations and providing specific advice requires significant resources and time.

[0100] 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.

[0101] In this invention, the server includes means for analyzing the user's actions and speech in real time using multiple detectors, means for presenting educational materials obtained from an external information source, means for providing immediate feedback to the user using artificial intelligence, means for generating user-specific evaluation information based on the analysis results, means for displaying the evaluation information to the user, and means for evaluating actions and pointing out areas for improvement in actual behavior verbally and visually. This makes it possible to quickly and concretely support the improvement of individual customer service skills of store employees in physical stores.

[0102] A "public space" is a specific area or place that is accessible to a large number of people and used for public purposes.

[0103] "Device" is a general term for equipment or tools configured to serve a specific purpose.

[0104] A "detector" is a device used to sense physical or chemical changes and acquire that information.

[0105] "Users" refer to the people who actually operate or use this system or device.

[0106] "Action" refers to the physical actions or behaviors performed by the user.

[0107] "Speech" refers to communication using words and sounds uttered by the user.

[0108] "Analysis" is the act or process of evaluating and interpreting acquired data to derive meaningful information.

[0109] "External information sources" refer to sources or providers that supply information and data from outside this system.

[0110] "Educational materials" refer to materials and content provided for learning or training.

[0111] Artificial intelligence is a technology that uses computers to mimic human intellectual activity and possesses the ability to learn, reason, and self-correct.

[0112] "Feedback" is information that is communicated to the recipient regarding the evaluation or results of an activity, in order to help with subsequent improvement or adjustment.

[0113] "Evaluation information" refers to information that indicates judgments about the user's skills and abilities based on the analysis results.

[0114] "Display" refers to the act of presenting information visually and allowing the user to confirm it.

[0115] "Evaluating an action" is the process of determining the effectiveness and accuracy of an action, either mechanically or manually.

[0116] "Areas for improvement in actions" refer to aspects of current methods and actions that need to be reviewed or improved.

[0117] "Verbal and visual feedback" refers to the act of indicating necessary improvements through audio or visual presentation.

[0118] This invention is a system for improving customer service skills in physical stores. This system uses a device equipped with multiple detectors to analyze the actions and speech of the store employee in real time and provide optimized feedback.

[0119] The server receives and analyzes data transmitted from various devices installed within the store. In particular, it utilizes speech recognition and image recognition APIs to convert the obtained data into text and visual information. This analysis is then processed by a specific AI model to evaluate the user's customer service skills. The server identifies areas for improvement during customer service, generates feedback, and sends it to the terminal.

[0120] The device provides an interface for conveying this feedback to the user. Specifically, it uses speech synthesis software and a display to intuitively present evaluation information. Based on the information presented, the user can immediately improve their customer service skills.

[0121] As an example of this system, when a store employee greets a customer with "Welcome," the AI ​​analyzes their tone of voice and posture and immediately provides advice such as "Speak louder" or "Try speaking in a more relaxed posture." This gives the employee an opportunity to adjust their behavior on the spot and improve the quality of their customer service.

[0122] The specific hardware used to realize this technology includes smart glasses, microphones, speakers, and displays. The software, on the other hand, utilizes speech recognition APIs (e.g., Google® Speech-to-Text), image recognition APIs, and AI model frameworks (such as PyTorch or Tensorflow®).

[0123] An example of a prompt statement is, "We will develop a system in which AI analyzes the first words spoken to customers entering the store and provides real-time advice to improve customer service skills." This prompt statement concisely describes the purpose and function of a system using a generative AI model.

[0124] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0125] Step 1:

[0126] When a user puts on the device, the terminal begins capturing the user's voice and visual data through the smart glasses. The input consists of the user's verbal greetings and gestures, which are collected by sensors. The output is the captured raw data.

[0127] Step 2:

[0128] The device sends the captured audio data to the server. The server uses a speech recognition API (e.g., Google Speech-to-Text) to convert the audio data into text data. The input is audio data, and the output is text data. This conversion extracts the spoken content from the audio.

[0129] Step 3:

[0130] Next, the server uses an image recognition API to analyze visual data related to the user's gestures and facial expressions. The input is visual data, and the output is the analysis results regarding the user's actions. Based on these results, the server identifies the characteristics of the actions.

[0131] Step 4:

[0132] The server uses an AI model to evaluate the user's customer service skills based on the analysis results of their voice and actions. Inputs are text and action analysis results, and outputs are a list of evaluation scores and areas for improvement. The AI ​​model compares these results to historical data and training sets to make its evaluation.

[0133] Step 5:

[0134] The server generates immediate feedback based on the evaluation results and sends it to the terminal. This feedback includes voice instructions generated using speech synthesis software and visual instructions displayed on the screen. Input is a list of evaluation points and areas for improvement, while output is a feedback message.

[0135] Step 6:

[0136] The device provides the user with feedback via voice and display. The user can then immediately adjust their customer service style accordingly. The device uses the feedback to inform changes in the user's behavior for the next step (Step 1).

[0137] This allows the entire system to function cyclically, enabling real-time support for improving users' customer service skills.

[0138] 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.

[0139] This invention is a system that uses devices installed in public spaces to provide individually optimized education and training to users, and further recognizes and utilizes the user's emotions. This system is implemented using three main components: a server, a terminal, and a user.

[0140] System configuration and operation

[0141] This device is equipped with multiple high-precision sensors and cameras, allowing it to record and analyze user actions and speech in real time. Furthermore, the device features an emotion engine that can recognize emotions from the user's actions and facial expressions.

[0142] Program operation description

[0143] The server selects the optimal AI model and educational materials from external information providers based on information sent by the user and data acquired in real time. It also customizes the program by taking into account the emotional data detected by the emotion engine.

[0144] The device utilizes AI models and educational materials provided by the server to deliver an interactive educational and training experience to the user. The device provides real-time feedback and adjusts the content to suit the user based on the results of the emotion engine.

[0145] After selecting an educational program, the user's actions, speech, and facial expressions are captured by sensors. Recognizing the user's emotions allows for more personalized feedback and the presentation of learning materials by internal algorithms.

[0146] For example, if a user selects an interview training program and the system's emotion engine detects nervousness or a lack of confidence, the device will provide real-time feedback to boost their confidence. This feedback is based on positive language and settings to help the user respond with greater confidence.

[0147] In this way, this system provides high-quality, individually optimized education and training in public spaces, and can respond to the user's emotions. By quickly recognizing different emotions such as anger, satisfaction, and interest, and providing appropriate guidance, it creates a more effective learning environment.

[0148] The following describes the processing flow.

[0149] Step 1:

[0150] The user enters the booth and signs in to the program using the interface provided by the device. A welcome message is displayed, and it is explained that emotion detection technology will be used.

[0151] Step 2:

[0152] The device displays a list of available programs to the user. The user selects a program of interest, reviews its detailed purpose and learning content, and then chooses that program.

[0153] Step 3:

[0154] User selection information is sent from the terminal to the server. The server identifies the most suitable learning materials and AI model for that program and sends them to the terminal. It also triggers the activation of the emotion engine.

[0155] Step 4:

[0156] The device prepares an interactive initial screen for the user based on the acquired educational materials and AI model. Sensors and cameras begin to continuously acquire data on the user's movements, speech, and facial expressions.

[0157] Step 5:

[0158] The server analyzes the received motion and speech data in real time. In parallel, the emotion engine recognizes the user's emotions and sends the results back to the server.

[0159] Step 6:

[0160] The server generates feedback using an AI model based on the analyzed data and recognized emotions. This feedback includes positive reinforcement and necessary guidance tailored to the user's emotions.

[0161] Step 7:

[0162] The device presents feedback sent from the server to the user visually and audibly. The tone and content of the feedback are adjusted according to the user's emotions.

[0163] Step 8:

[0164] Users continue learning and training based on feedback, and adjust their efforts as needed.

[0165] Step 9:

[0166] After the session ends, the terminal displays the performance evaluation results to the user, and they can book their next session. The server anonymizes the data and uses it to improve future AI models.

[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 as the "terminal".

[0169] Traditional education and training systems struggle to provide individualized optimization that fully considers the emotional state of users, and real-time feedback and adjustments are limited. Furthermore, the process of users scheduling their next session is cumbersome. Therefore, there is a need for a system that provides a more effective and personalized learning experience while continuously supporting users' engagement.

[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 acquiring and analyzing the user's behavior and voice in real time using multiple sensors and imaging devices, means for identifying the user's emotions using an emotion analysis engine, and means for adapting and presenting educational materials acquired from external information sources to the user based on the analysis results and emotion data. This provides the user with an individually optimized educational and training experience, as well as enabling individualized feedback and adjustments in response to emotions.

[0172] A "public space" refers to a place that can be used or entered by an unspecified number of people, and is a space designed for education or training.

[0173] "Equipment" refers to a collection of physical devices and electronic devices installed to constitute a system, including sensors and imaging devices.

[0174] A "sensor" is a device that detects physical phenomena and outputs them in the form of electrical signals or other means, and is used to acquire the user's actions and voice.

[0175] An "imaging device" is a device that uses optical means to record images or videos, and its role is to capture the user's facial expressions and movements.

[0176] An "emotion analysis engine" refers to an algorithm and software system that identifies a user's emotional state from their facial expressions, actions, and other observations.

[0177] "External information sources" refer to external databases and content providers to which the system connects to obtain educational materials and training programs.

[0178] A "generated artificial intelligence model" is a machine learning model trained on a specific task and used to provide appropriate feedback and guidance to the user.

[0179] "Interactive feedback" refers to the responses and comments that a system provides in real time in response to the user's actions and statements, thereby improving the quality of education and training.

[0180] "Evaluation information" refers to information that compiles objective and subjective data generated based on the user's learning and training progress and results.

[0181] This invention is a system that provides users with individually optimized educational and training experiences through equipment installed in public spaces. The system mainly consists of three elements: a server, terminals, and users.

[0182] The server plays a central role in processing data transmitted from the terminal. Using multiple sensors and imaging devices, it receives data such as the user's behavior, facial expressions, and voice, acquired in real time by the terminal. This data is analyzed by an emotion analysis engine to identify the user's emotional state. Based on this emotional state and the acquired behavioral data, the server uses a generated artificial intelligence model to select educational materials and programs adapted to the user. Specifically, machine learning libraries such as TensorFlow and PyTorch are expected to be used.

[0183] The device provides interactive feedback to the user based on individually optimized educational and training content provided by the server. The device has the ability to monitor the user's behavior and speech in real time and adjust the educational content as needed, thereby improving the user's learning efficiency. The device responds immediately to the user's emotional responses, sending positive feedback and guidance. An example of a prompt might be, "Generate confidence-building feedback for a nervous user."

[0184] Users utilize equipment installed in public spaces to receive educational programs tailored to their choices. Their actions and speech are captured by sensors, allowing them to experience how the interactive experience provided is personalized. For example, if a user selects interview training and an emotion indicating nervousness is detected, the terminal provides appropriate guidance, allowing them to participate in the training with confidence.

[0185] In this way, the system provides feedback tailored to each user's individual emotions and learning patterns, resulting in a high-quality, personalized educational and training experience.

[0186] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0187] Step 1:

[0188] The device uses multiple sensors and imaging devices to capture the user's movements, facial expressions, and speech in real time. Input consists of the user's physical movements and speech, which are acquired as digital data. Output consists of raw sensor data and image data. Specifically, the sensors monitor the user's movements, and the camera acquires facial expressions as image data for analysis.

[0189] Step 2:

[0190] The terminal formats the captured data and sends it to the server. The input is the raw data acquired in step 1, and the output is formatted data. Specifically, the terminal compresses the data and processes it into a form that can be efficiently transferred.

[0191] Step 3:

[0192] The server analyzes the data received from the terminal. The input is formatted data of the user's actions and facial expressions, and the server uses an emotion analysis engine to recognize the user's emotional state. The output is the analyzed emotional status. Specifically, the server uses machine learning algorithms to analyze the input data and perform emotion recognition.

[0193] Step 4:

[0194] The server uses a generative AI model to determine appropriate learning materials and feedback based on recognized emotion data and user data. The input is emotion status and user performance data, and the output is individually optimized educational content. Specifically, the server searches a database of learning materials from external sources and configures a program tailored to the user's needs.

[0195] Step 5:

[0196] The device provides users with an interactive educational experience based on educational content received from the server. Input consists of optimized learning materials and feedback from the server, while output is real-time feedback to the user. Specifically, the device offers advice and instructions to improve the user's actions in real time, and adjusts this feedback as the learning material progresses.

[0197] Step 6:

[0198] The user receives feedback and learning materials from the device. The input is interactive feedback from the device, which is output as their learning or training outcome. The user follows the instructions and takes action to improve their skills. For example, during an interview training program, the user might receive and act on tips from the device to alleviate anxiety.

[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 public spaces for education and training, there is a need to accommodate the diverse learning styles and emotional states of individual users, but conventional systems are insufficient in this regard. Furthermore, it is difficult to provide immediate feedback and encouraging messages that respond to the user's emotions, resulting in a failure to deliver an effective learning 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 analyzing the user's behavior and speech in real time using multiple detection devices, means for providing immediate feedback to the user using an intelligent algorithm, and means for generating and displaying encouraging messages that correspond to the user's emotions by incorporating emotion analysis technology. This makes it possible to provide individually optimized education and training that corresponds to each user's learning style and emotional state.

[0204] "Public space" refers to public places and facilities that are accessible to the general public.

[0205] "Detection device" refers to hardware such as sensors and cameras used to acquire the user's behavior and speech.

[0206] "Behavior" refers to the physical actions and words performed by the user.

[0207] "Speech" refers to words or sounds that a user utters orally.

[0208] "Real-time analysis" means processing data instantly and obtaining results quickly.

[0209] An "intelligent algorithm" refers to a set of computational procedures used to analyze data and generate appropriate feedback.

[0210] "Instant feedback" refers to information and advice that is returned instantly based on the user's behavior and emotional state.

[0211] "Emotional analysis technology" is a technology that recognizes and analyzes emotions from the user's facial expressions and voice.

[0212] "Supportive messages" refer to text or audio generated to encourage users based on their emotional state.

[0213] "Individualized optimization" means providing the most effective method tailored to each user's characteristics and circumstances.

[0214] The system of this invention provides users with individually optimized education and training using terminals installed in public spaces. Specifically, it is equipped with a detection device for analyzing the user's behavior and speech in real time, and an intelligent algorithm based on the acquired data provides immediate feedback to the user. These functions are realized by the following hardware and software.

[0215] The server uses multiple sensors and cameras to capture the user's behavior and speech. These devices can analyze the user's actions and words in real time, and the data is immediately transmitted to the server. The intelligent algorithm uses the OpenCV data analysis library to analyze facial and movement features, and Amazon Rekognition to identify emotions. This generates emotion data.

[0216] The device executes educational programs based on information sent from the server, providing users with an interactive experience. The device displays feedback generated by intelligent algorithms and outputs encouraging messages to boost user motivation. These messages are customized based on the user's emotional data at the time.

[0217] As a concrete example, when staff receiving customer service training in a physical store use this system, the terminal provides feedback such as, "Customer service with confidence!" This feedback is displayed when the intelligent algorithm determines that the user is feeling nervous. Furthermore, if good customer service skills are observed, a positive message such as, "That was excellent service!" can be displayed. An example of a prompt would be, "Generate a positive message to alleviate tension and anxiety during customer service."

[0218] Thus, the present invention functions as a platform for providing individually optimized education and training in real time, thereby enhancing the learning effectiveness of users.

[0219] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0220] Step 1:

[0221] The user logs into the system via their terminal. The system receives the user's authentication information as input. The server verifies the authentication information and loads the user profile. The user's profile data is displayed on the terminal as output.

[0222] Step 2:

[0223] The user selects the educational program they wish to learn. The terminal receives program selection information as input. The terminal then sends the selected program information to the server. The output presents the user with an overview of the program and instructions for getting started.

[0224] Step 3:

[0225] The detection device captures the user's behavior and speech in real time. It acquires camera video and microphone audio data as input. The server analyzes the video data using OpenCV and generates emotion data using Amazon Rekognition. The analysis results are then fed into an intelligent algorithm as output.

[0226] Step 4:

[0227] The server generates appropriate feedback using the acquired behavioral and sentimental data. It receives behavioral and sentimental data as input. An intelligent algorithm processes the data to create a feedback message. The generated feedback is sent to the terminal as output.

[0228] Step 5:

[0229] The device displays generated feedback and encouraging messages to the user in real time. It receives feedback data from the server as input. It performs specific actions to present immediate advice and encouraging messages to the user. The user's response is fed back to the device as output.

[0230] Step 6:

[0231] After the session ends, the server stores all data for later analysis and improvement of intelligent algorithms. It receives all data collected during the session as input. This data is anonymized and used for long-term functionality improvements. The output is stored in the system's database.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] [Second Embodiment]

[0236] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0237] 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.

[0238] 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).

[0239] 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.

[0240] 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.

[0241] 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).

[0242] 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.

[0243] 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.

[0244] 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.

[0245] 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.

[0246] 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.

[0247] 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".

[0248] One embodiment of this invention is a system that enables users to receive individually optimized education and training using a device installed in a public space. This system consists of three main components: a server, a terminal, and a user.

[0249] System Overview

[0250] The device incorporates multiple high-precision sensors and cameras to record and analyze the user's actions and speech in real time. The terminal displays educational materials obtained from external providers to support the specific training or educational program selected by the user. This provides an AI-powered interactive learning experience.

[0251] Program Description

[0252] The server identifies the appropriate AI model and learning materials based on the user's selection information sent from the terminal. The server constantly maintains and manages multiple AI models, each with specific educational and training functions built in.

[0253] After the user registers and selects a program, the terminal communicates with the server to retrieve the necessary learning materials and AI models, and immediately presents them to the user. The terminal also processes input data from sensors in real time, providing the user with immediate visual and audible feedback.

[0254] Users receive training and education through their chosen program. During this process, sensors detect the user's movements and speech, and the data is sent to an AI model via a server, providing optimal instructions and advice through the device.

[0255] For example, when a user selects a sports training program, the device utilizes an AI model to analyze sports movements and provides specific instructions on form and performance in real time. This allows the user to make precise adjustments to their movements and optimize their performance on the spot.

[0256] Through the configuration and processes described above, this system can provide users with high-quality educational and training opportunities that are available at any time.

[0257] The following describes the processing flow.

[0258] Step 1:

[0259] The server records the user's registration information and the type of program selected, received from the terminal, in a database. This information is used to determine the appropriate AI model and content.

[0260] Step 2:

[0261] The terminal displays details of available programs to the user on the screen. The user selects their desired program from the displayed options and confirms its specific details.

[0262] Step 3:

[0263] Once the user selects a program, the terminal sends that selection information to the server and requests the necessary learning materials and AI models.

[0264] Step 4:

[0265] The server accesses databases of external information providers to retrieve the most suitable learning materials for the program selected by the user. It also delivers AI models related to the selected program to the device.

[0266] Step 5:

[0267] The device provides users with an interactive screen using the delivered educational materials and AI models. The device captures user actions and speech data through sensors.

[0268] Step 6:

[0269] The server processes data sent from the terminal in real time and performs analysis based on an AI model. This generates immediate feedback for the user.

[0270] Step 7:

[0271] The device visualizes the feedback received from the server and provides instructions for the next action or utterance. The user continues training and learning while referring to these instructions.

[0272] Step 8:

[0273] When a user ends a session, the device sends that information to the server, which evaluates the user's performance data and creates feedback that includes areas for improvement for the next session.

[0274] Step 9:

[0275] The server saves the generated feedback to the user's account, and the device displays this to the user before ending the session. The user can then use the information they have reviewed to schedule their next session.

[0276] (Example 1)

[0277] 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 glasses 214 will be referred to as the "terminal".

[0278] In today's educational and training environments, providing learning and instruction optimized for individual needs in real time is considered difficult. Furthermore, the ability to provide effective, immediate feedback to users is required, but achieving this demands advanced technology. Additionally, there is still a lack of efficient and flexible systems capable of providing optimal learning experiences based on diverse user choices.

[0279] 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.

[0280] In this invention, the server includes means for identifying and operating an optimal generative AI model based on a user's selection, means for generating optimal instructions and learning materials from the AI model using a prompt sentence, and means for displaying the evaluation information to the user. As a result, it becomes possible to provide the user with individually optimized education and training and to provide effective feedback in real time.

[0281] The "public space" refers to a place that is accessible to the general public and is used for education and training.

[0282] The "device" refers to a device having a hardware structure for providing an interactive experience to the user through sensing and calculation.

[0283] The "sensor" refers to a device for acquiring external data such as the user's actions and speech and inputting them for analysis.

[0284] The "external information provider" refers to an information source outside the system that provides educational content and training materials.

[0285] "Artificial intelligence" refers to a computational algorithm designed to generate immediate feedback to the user.

[0286] "Feedback" refers to response information including instructions and evaluations provided for the actions and speech executed by the user.

[0287] "Evaluation information" refers to individual evaluation data generated based on the user's performance.

[0288] The "generative AI model" refers to an AI model used to generate optimal instructions according to the user's selection.

[0289] The "prompt sentence" refers to an input sentence used to cause the AI model to generate a specific output.

[0290] This invention is a system that enables users to receive individually optimized education and training using devices installed in public spaces. The system consists of three main components: a server, a terminal, and the user.

[0291] The server maintains and manages multiple AI models, identifying and running the optimal model based on user selections. During this process, prompts are used, and the AI ​​model generates instructions and training materials optimized for the user. This generated data is then provided to the user as immediate feedback.

[0292] The device utilizes multiple built-in high-precision sensors and cameras to record the user's actions and speech in real time and analyze the data. This analysis is sent to a server and used to generate appropriate instruction. The device also presents learning materials obtained from external providers, enhancing the learning experience through visual and audio feedback.

[0293] Users participate in programs offered through the device and receive personalized guidance from a generated AI model. For example, if a user selects a sports training program, the device uses a motion analysis model to immediately provide detailed guidance on improving form. An example of a specific prompt might be, "Create a basic form guide for the sport selected by the user."

[0294] Through this system, users can receive highly personalized education and training in real time, which is expected to improve learning efficiency and results.

[0295] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0296] Step 1:

[0297] Users access the system using a terminal and register. During registration, they enter personal information and educational / training programs of interest. The entered data is saved as a user profile and sent to the server. The terminal displays a list of currently available programs and prompts the user to make a selection. The user's selection information is then entered.

[0298] Step 2:

[0299] The terminal sends user selection information to the server. This information includes details about the program selected by the user. Based on the received selection information, the server selects an appropriate generative AI model. In the process, it generates prompt statements to apply to the selected AI model. Through these prompt statements, input is provided to optimize the instructions for the AI ​​model.

[0300] Step 3:

[0301] The server activates the selected AI model and generates optimal instructions and learning materials from the model using prompt messages. The prompt messages are input to the AI ​​model, which then outputs specific instruction content for the user as data. This data is immediately sent to the terminal.

[0302] Step 4:

[0303] The terminal receives the output of the AI ​​model sent from the server and displays it to the user. It also uses high-precision sensors and a camera within the terminal to record and analyze the user's actions and speech in real time. This analysis result is used as feedback. It receives real-time user data as input and outputs the processing results as feedback.

[0304] Step 5:

[0305] Based on the instructions and feedback displayed on the terminal, the user implements the selected education and training program. Since feedback on the user's actions and speech is continuously provided, performance improvement can be immediately confirmed. Additional input regarding the user's behavior change is obtained, and improvement guidance based on it is output.

[0306] (Application Example 1)

[0307] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0308] When aiming to improve the quality of customer service in modern physical stores, it is required to effectively and efficiently improve the skills of each individual store employee. However, there is a problem that with conventional methods, feedback to store employees is abstract and lacks immediacy, making it difficult to timely point out individual areas for improvement. Furthermore, accurately grasping the customer service situation and providing specific advice also requires a lot of resources and time.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0310] In this invention, the server includes means for analyzing the actions and speech of the user in real time using a plurality of detectors, means for presenting teaching materials acquired from an external information source, means for providing immediate feedback to the user using artificial intelligence, means for generating evaluation information dedicated to the user based on the analysis results, means for displaying the evaluation information to the user, and means for evaluating actions and verbally and visually pointing out areas for improvement in on-site behavior. Thereby, it becomes possible to quickly and specifically support the improvement of the individual customer service skills of store employees within the physical store.

[0311] A "public space" refers to a specific area or location that is accessible to an unspecified number of people and is used for public purposes.

[0312] "Device" is a general term for equipment or tools configured to serve a specific purpose.

[0313] A "detector" is a device used to sense physical or chemical changes and acquire that information.

[0314] "Users" refer to the people who actually operate or use this system or device.

[0315] "Action" refers to the physical actions or behaviors performed by the user.

[0316] "Speech" refers to communication using words and sounds uttered by the user.

[0317] "Analysis" is the act or process of evaluating and interpreting acquired data to derive meaningful information.

[0318] "External information sources" refer to sources or providers that supply information and data from outside this system.

[0319] "Educational materials" refer to materials and content provided for learning or training.

[0320] Artificial intelligence is a technology that uses computers to mimic human intellectual activity and possesses the ability to learn, reason, and self-correct.

[0321] "Feedback" is information that is communicated to the recipient regarding the evaluation or results of an activity, in order to help with subsequent improvement or adjustment.

[0322] "Evaluation information" refers to information that indicates judgments about the user's skills and abilities based on the analysis results.

[0323] "Display" refers to the act of presenting information visually and allowing the user to confirm it.

[0324] "Evaluating an action" is the process of determining the effectiveness and accuracy of an action, either mechanically or manually.

[0325] "Areas for improvement in actions" refer to aspects of current methods and actions that need to be reviewed or improved.

[0326] "Verbal and visual feedback" refers to the act of indicating necessary improvements through audio or visual presentation.

[0327] This invention is a system for improving customer service skills in physical stores. This system uses a device equipped with multiple detectors to analyze the actions and speech of the store employee in real time and provide optimized feedback.

[0328] The server receives and analyzes data transmitted from various devices installed within the store. In particular, it utilizes speech recognition and image recognition APIs to convert the obtained data into text and visual information. This analysis is then processed by a specific AI model to evaluate the user's customer service skills. The server identifies areas for improvement during customer service, generates feedback, and sends it to the terminal.

[0329] The device provides an interface for conveying this feedback to the user. Specifically, it uses speech synthesis software and a display to intuitively present evaluation information. Based on the information presented, the user can immediately improve their customer service skills.

[0330] As an example of this system, when a store employee greets a customer with "Welcome," the AI ​​analyzes their tone of voice and posture and immediately provides advice such as "Speak louder" or "Try speaking in a more relaxed posture." This gives the employee an opportunity to adjust their behavior on the spot and improve the quality of their customer service.

[0331] The specific hardware used to implement this technology includes smart glasses, a microphone, speakers, and a display. The software, on the other hand, utilizes speech recognition APIs (such as Google Speech-to-Text), image recognition APIs, and AI modeling frameworks (such as PyTorch or TensorFlow).

[0332] An example of a prompt statement is, "We will develop a system in which AI analyzes the first words spoken to customers entering the store and provides real-time advice to improve customer service skills." This prompt statement concisely describes the purpose and function of a system using a generative AI model.

[0333] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0334] Step 1:

[0335] When a user puts on the device, the terminal begins capturing the user's voice and visual data through the smart glasses. The input consists of the user's verbal greetings and gestures, which are collected by sensors. The output is the captured raw data.

[0336] Step 2:

[0337] The device sends the captured audio data to the server. The server uses a speech recognition API (e.g., Google Speech-to-Text) to convert the audio data into text data. The input is audio data, and the output is text data. This conversion extracts the spoken content from the audio.

[0338] Step 3:

[0339] Next, the server uses an image recognition API to analyze visual data related to the user's gestures and facial expressions. The input is visual data, and the output is the analysis results regarding the user's actions. Based on these results, the server identifies the characteristics of the actions.

[0340] Step 4:

[0341] The server uses an AI model to evaluate the user's customer service skills based on the analysis results of their voice and actions. Inputs are text and action analysis results, and outputs are a list of evaluation scores and areas for improvement. The AI ​​model compares these results to historical data and training sets to make its evaluation.

[0342] Step 5:

[0343] The server generates immediate feedback based on the evaluation results and sends it to the terminal. This feedback includes voice instructions generated using speech synthesis software and visual instructions displayed on the screen. Input is a list of evaluation points and areas for improvement, while output is a feedback message.

[0344] Step 6:

[0345] The device provides the user with feedback via voice and display. The user can then immediately adjust their customer service style accordingly. The device uses the feedback to inform changes in the user's behavior for the next step (Step 1).

[0346] This allows the entire system to function cyclically, enabling real-time support for improving users' customer service skills.

[0347] 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.

[0348] This invention is a system that uses devices installed in public spaces to provide individually optimized education and training to users, and further recognizes and utilizes the user's emotions. This system is implemented using three main components: a server, a terminal, and a user.

[0349] System configuration and operation

[0350] This device is equipped with multiple high-precision sensors and cameras, allowing it to record and analyze user actions and speech in real time. Furthermore, the device features an emotion engine that can recognize emotions from the user's actions and facial expressions.

[0351] Program operation description

[0352] The server selects the optimal AI model and educational materials from external information providers based on information sent by the user and data acquired in real time. It also customizes the program by taking into account the emotional data detected by the emotion engine.

[0353] The device utilizes AI models and educational materials provided by the server to deliver an interactive educational and training experience to the user. The device provides real-time feedback and adjusts the content to suit the user based on the results of the emotion engine.

[0354] After selecting an educational program, the user's actions, speech, and facial expressions are captured by sensors. Recognizing the user's emotions allows for more personalized feedback and the presentation of learning materials by internal algorithms.

[0355] For example, if a user selects an interview training program and the system's emotion engine detects nervousness or a lack of confidence, the device will provide real-time feedback to boost their confidence. This feedback is based on positive language and settings to help the user respond with greater confidence.

[0356] In this way, this system provides high-quality, individually optimized education and training in public spaces, and can respond to the user's emotions. By quickly recognizing different emotions such as anger, satisfaction, and interest, and providing appropriate guidance, it creates a more effective learning environment.

[0357] The following describes the processing flow.

[0358] Step 1:

[0359] The user enters the booth and signs in to the program using the interface provided by the device. A welcome message is displayed, and it is explained that emotion detection technology will be used.

[0360] Step 2:

[0361] The device displays a list of available programs to the user. The user selects a program of interest, reviews its detailed purpose and learning content, and then chooses that program.

[0362] Step 3:

[0363] User selection information is sent from the terminal to the server. The server identifies the most suitable learning materials and AI model for that program and sends them to the terminal. It also triggers the activation of the emotion engine.

[0364] Step 4:

[0365] The device prepares an interactive initial screen for the user based on the acquired educational materials and AI model. Sensors and cameras begin to continuously acquire data on the user's movements, speech, and facial expressions.

[0366] Step 5:

[0367] The server analyzes the received motion and speech data in real time. In parallel, the emotion engine recognizes the user's emotions and sends the results back to the server.

[0368] Step 6:

[0369] The server generates feedback using an AI model based on the analyzed data and recognized emotions. This feedback includes positive reinforcement and necessary guidance tailored to the user's emotions.

[0370] Step 7:

[0371] The device presents feedback sent from the server to the user visually and audibly. The tone and content of the feedback are adjusted according to the user's emotions.

[0372] Step 8:

[0373] Users continue learning and training based on feedback, and adjust their efforts as needed.

[0374] Step 9:

[0375] After the session ends, the terminal displays the performance evaluation results to the user, and they can book their next session. The server anonymizes the data and uses it to improve future AI models.

[0376] (Example 2)

[0377] 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".

[0378] Traditional education and training systems struggle to provide individualized optimization that fully considers the emotional state of users, and real-time feedback and adjustments are limited. Furthermore, the process of users scheduling their next session is cumbersome. Therefore, there is a need for a system that provides a more effective and personalized learning experience while continuously supporting users' engagement.

[0379] 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.

[0380] In this invention, the server includes means for acquiring and analyzing the user's behavior and voice in real time using multiple sensors and imaging devices, means for identifying the user's emotions using an emotion analysis engine, and means for adapting and presenting educational materials acquired from external information sources to the user based on the analysis results and emotion data. This provides the user with an individually optimized educational and training experience, as well as enabling individualized feedback and adjustments in response to emotions.

[0381] A "public space" refers to a place that can be used or entered by an unspecified number of people, and is a space designed for education or training.

[0382] "Equipment" refers to a collection of physical devices and electronic devices installed to constitute a system, including sensors and imaging devices.

[0383] A "sensor" is a device that detects physical phenomena and outputs them in the form of electrical signals or other means, and is used to acquire the user's actions and voice.

[0384] An "imaging device" is a device that uses optical means to record images or videos, and its role is to capture the user's facial expressions and movements.

[0385] An "emotion analysis engine" refers to an algorithm and software system that identifies a user's emotional state from their facial expressions, actions, and other observations.

[0386] "External information sources" refer to external databases and content providers to which the system connects to obtain educational materials and training programs.

[0387] A "generated artificial intelligence model" is a machine learning model trained on a specific task and used to provide appropriate feedback and guidance to the user.

[0388] "Interactive feedback" refers to the responses and comments that a system provides in real time in response to the user's actions and statements, thereby improving the quality of education and training.

[0389] "Evaluation information" refers to information that compiles objective and subjective data generated based on the user's learning and training progress and results.

[0390] This invention is a system that provides users with individually optimized educational and training experiences through equipment installed in public spaces. The system mainly consists of three elements: a server, terminals, and users.

[0391] The server plays a central role in processing data transmitted from the terminal. Using multiple sensors and imaging devices, it receives data such as the user's behavior, facial expressions, and voice, acquired in real time by the terminal. This data is analyzed by an emotion analysis engine to identify the user's emotional state. Based on this emotional state and the acquired behavioral data, the server uses a generated artificial intelligence model to select educational materials and programs adapted to the user. Specifically, machine learning libraries such as TensorFlow and PyTorch are expected to be used.

[0392] The device provides interactive feedback to the user based on individually optimized educational and training content provided by the server. The device has the ability to monitor the user's behavior and speech in real time and adjust the educational content as needed, thereby improving the user's learning efficiency. The device responds immediately to the user's emotional responses, sending positive feedback and guidance. An example of a prompt might be, "Generate confidence-building feedback for a nervous user."

[0393] Users utilize equipment installed in public spaces to receive educational programs tailored to their choices. Their actions and speech are captured by sensors, allowing them to experience how the interactive experience provided is personalized. For example, if a user selects interview training and an emotion indicating nervousness is detected, the terminal provides appropriate guidance, allowing them to participate in the training with confidence.

[0394] In this way, the system provides feedback tailored to each user's individual emotions and learning patterns, resulting in a high-quality, personalized educational and training experience.

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

[0396] Step 1:

[0397] The device uses multiple sensors and imaging devices to capture the user's movements, facial expressions, and speech in real time. Input consists of the user's physical movements and speech, which are acquired as digital data. Output consists of raw sensor data and image data. Specifically, the sensors monitor the user's movements, and the camera acquires facial expressions as image data for analysis.

[0398] Step 2:

[0399] The terminal formats the captured data and sends it to the server. The input is the raw data acquired in step 1, and the output is formatted data. Specifically, the terminal compresses the data and processes it into a form that can be efficiently transferred.

[0400] Step 3:

[0401] The server analyzes the data received from the terminal. The input is formatted data of the user's actions and facial expressions, and the server uses an emotion analysis engine to recognize the user's emotional state. The output is the analyzed emotional status. Specifically, the server uses machine learning algorithms to analyze the input data and perform emotion recognition.

[0402] Step 4:

[0403] The server uses a generative AI model to determine appropriate learning materials and feedback based on recognized emotion data and user data. The input is emotion status and user performance data, and the output is individually optimized educational content. Specifically, the server searches a database of learning materials from external sources and configures a program tailored to the user's needs.

[0404] Step 5:

[0405] The device provides users with an interactive educational experience based on educational content received from the server. Input consists of optimized learning materials and feedback from the server, while output is real-time feedback to the user. Specifically, the device offers advice and instructions to improve the user's actions in real time, and adjusts this feedback as the learning material progresses.

[0406] Step 6:

[0407] The user receives feedback and learning materials from the device. The input is interactive feedback from the device, which is output as their learning or training outcome. The user follows the instructions and takes action to improve their skills. For example, during an interview training program, the user might receive and act on tips from the device to alleviate anxiety.

[0408] (Application Example 2)

[0409] 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."

[0410] In modern public spaces for education and training, there is a need to accommodate the diverse learning styles and emotional states of individual users, but conventional systems are insufficient in this regard. Furthermore, it is difficult to provide immediate feedback and encouraging messages that respond to the user's emotions, resulting in a failure to deliver an effective learning experience.

[0411] 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.

[0412] In this invention, the server includes means for analyzing the user's behavior and speech in real time using multiple detection devices, means for providing immediate feedback to the user using an intelligent algorithm, and means for generating and displaying encouraging messages that correspond to the user's emotions by incorporating emotion analysis technology. This makes it possible to provide individually optimized education and training that corresponds to each user's learning style and emotional state.

[0413] "Public space" refers to public places and facilities that are accessible to the general public.

[0414] "Detection device" refers to hardware such as sensors and cameras used to acquire the user's behavior and speech.

[0415] "Behavior" refers to the physical actions and words performed by the user.

[0416] "Speech" refers to words or sounds that a user utters orally.

[0417] "Real-time analysis" means processing data instantly and obtaining results quickly.

[0418] An "intelligent algorithm" refers to a set of computational procedures used to analyze data and generate appropriate feedback.

[0419] "Instant feedback" refers to information and advice that is returned instantly based on the user's behavior and emotional state.

[0420] "Emotional analysis technology" is a technology that recognizes and analyzes emotions from the user's facial expressions and voice.

[0421] "Supportive messages" refer to text or audio generated to encourage users based on their emotional state.

[0422] "Individualized optimization" means providing the most effective method tailored to each user's characteristics and circumstances.

[0423] The system of this invention provides users with individually optimized education and training using terminals installed in public spaces. Specifically, it is equipped with a detection device for analyzing the user's behavior and speech in real time, and an intelligent algorithm based on the acquired data provides immediate feedback to the user. These functions are realized by the following hardware and software.

[0424] The server uses multiple sensors and cameras to capture the user's behavior and speech. These devices can analyze the user's actions and words in real time, and the data is immediately transmitted to the server. The intelligent algorithm uses the OpenCV data analysis library to analyze facial and movement features, and Amazon Rekognition to identify emotions. This generates emotion data.

[0425] The device executes educational programs based on information sent from the server, providing users with an interactive experience. The device displays feedback generated by intelligent algorithms and outputs encouraging messages to boost user motivation. These messages are customized based on the user's emotional data at the time.

[0426] As a concrete example, when staff receiving customer service training in a physical store use this system, the terminal provides feedback such as, "Customer service with confidence!" This feedback is displayed when the intelligent algorithm determines that the user is feeling nervous. Furthermore, if good customer service skills are observed, a positive message such as, "That was excellent service!" can be displayed. An example of a prompt would be, "Generate a positive message to alleviate tension and anxiety during customer service."

[0427] Thus, the present invention functions as a platform for providing individually optimized education and training in real time, thereby enhancing the learning effectiveness of users.

[0428] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0429] Step 1:

[0430] The user logs into the system via their terminal. The system receives the user's authentication information as input. The server verifies the authentication information and loads the user profile. The user's profile data is displayed on the terminal as output.

[0431] Step 2:

[0432] The user selects the educational program they wish to learn. The terminal receives program selection information as input. The terminal then sends the selected program information to the server. The output presents the user with an overview of the program and instructions for getting started.

[0433] Step 3:

[0434] The detection device captures the user's behavior and speech in real time. It acquires camera video and microphone audio data as input. The server analyzes the video data using OpenCV and generates emotion data using Amazon Rekognition. The analysis results are then fed into an intelligent algorithm as output.

[0435] Step 4:

[0436] The server generates appropriate feedback using the acquired behavioral and sentimental data. It receives behavioral and sentimental data as input. An intelligent algorithm processes the data to create a feedback message. The generated feedback is sent to the terminal as output.

[0437] Step 5:

[0438] The device displays generated feedback and encouraging messages to the user in real time. It receives feedback data from the server as input. It performs specific actions to present immediate advice and encouraging messages to the user. The user's response is fed back to the device as output.

[0439] Step 6:

[0440] After the session ends, the server stores all data for later analysis and improvement of intelligent algorithms. It receives all data collected during the session as input. This data is anonymized and used for long-term functionality improvements. The output is stored in the system's database.

[0441] 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.

[0442] 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.

[0443] 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.

[0444] [Third Embodiment]

[0445] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0446] 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.

[0447] 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).

[0448] 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.

[0449] 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.

[0450] 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).

[0451] 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.

[0452] 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.

[0453] 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.

[0454] 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.

[0455] 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.

[0456] 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".

[0457] One embodiment of this invention is a system that enables users to receive individually optimized education and training using a device installed in a public space. This system consists of three main components: a server, a terminal, and a user.

[0458] System Overview

[0459] The device incorporates multiple high-precision sensors and cameras to record and analyze the user's actions and speech in real time. The terminal displays educational materials obtained from external providers to support the specific training or educational program selected by the user. This provides an AI-powered interactive learning experience.

[0460] Program Description

[0461] The server identifies the appropriate AI model and learning materials based on the user's selection information sent from the terminal. The server constantly maintains and manages multiple AI models, each with specific educational and training functions built in.

[0462] After the user registers and selects a program, the terminal communicates with the server to retrieve the necessary learning materials and AI models, and immediately presents them to the user. The terminal also processes input data from sensors in real time, providing the user with immediate visual and audible feedback.

[0463] Users receive training and education through their chosen program. During this process, sensors detect the user's movements and speech, and the data is sent to an AI model via a server, providing optimal instructions and advice through the device.

[0464] For example, when a user selects a sports training program, the device utilizes an AI model to analyze sports movements and provides specific instructions on form and performance in real time. This allows the user to make precise adjustments to their movements and optimize their performance on the spot.

[0465] Through the configuration and processes described above, this system can provide users with high-quality educational and training opportunities that are available at any time.

[0466] The following describes the processing flow.

[0467] Step 1:

[0468] The server records the user's registration information and the type of program selected, received from the terminal, in a database. This information is used to determine the appropriate AI model and content.

[0469] Step 2:

[0470] The terminal displays details of available programs to the user on the screen. The user selects their desired program from the displayed options and confirms its specific details.

[0471] Step 3:

[0472] Once the user selects a program, the terminal sends that selection information to the server and requests the necessary learning materials and AI models.

[0473] Step 4:

[0474] The server accesses databases of external information providers to retrieve the most suitable learning materials for the program selected by the user. It also delivers AI models related to the selected program to the device.

[0475] Step 5:

[0476] The device provides users with an interactive screen using the delivered educational materials and AI models. The device captures user actions and speech data through sensors.

[0477] Step 6:

[0478] The server processes data sent from the terminal in real time and performs analysis based on an AI model. This generates immediate feedback for the user.

[0479] Step 7:

[0480] The device visualizes the feedback received from the server and provides instructions for the next action or utterance. The user continues training and learning while referring to these instructions.

[0481] Step 8:

[0482] When a user ends a session, the device sends that information to the server, which evaluates the user's performance data and creates feedback that includes areas for improvement for the next session.

[0483] Step 9:

[0484] The server saves the generated feedback to the user's account, and the device displays this to the user before ending the session. The user can then use the information they have reviewed to schedule their next session.

[0485] (Example 1)

[0486] 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."

[0487] In today's educational and training environments, providing learning and instruction optimized for individual needs in real time is considered difficult. Furthermore, the ability to provide effective, immediate feedback to users is required, but achieving this demands advanced technology. Additionally, there is still a lack of efficient and flexible systems capable of providing optimal learning experiences based on diverse user choices.

[0488] 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.

[0489] In this invention, the server includes means for identifying and operating the optimal generative AI model based on the user's selection, means for generating optimal instructions and learning materials from the AI ​​model using prompt statements, and means for displaying the evaluation information to the user. This makes it possible to provide the user with individually optimized education and training and to provide effective feedback in real time.

[0490] A "public space" refers to a place that is accessible to the general public and used for education and training.

[0491] A "device" refers to a piece of equipment with a hardware structure that provides users with an interactive experience through sensing and computation.

[0492] A "sensor" refers to a device that acquires external data, such as the user's actions and speech, and inputs it for analysis.

[0493] "External information providers" refer to information sources outside the system that provide educational content or training materials.

[0494] "Artificial intelligence" refers to computational algorithms designed to generate immediate feedback for the user.

[0495] "Feedback" refers to response information, including instructions and evaluations, provided in response to actions or utterances performed by the user.

[0496] "Evaluation information" refers to individual evaluation data generated based on the user's performance.

[0497] A "generative AI model" refers to an AI model used to generate optimal instructions based on user selections.

[0498] A "prompt statement" refers to an input statement used to cause an AI model to generate a specific output.

[0499] This invention is a system that enables users to receive individually optimized education and training using devices installed in public spaces. The system consists of three main components: a server, a terminal, and the user.

[0500] The server maintains and manages multiple AI models, identifying and running the optimal model based on user selections. During this process, prompts are used, and the AI ​​model generates instructions and training materials optimized for the user. This generated data is then provided to the user as immediate feedback.

[0501] The device utilizes multiple built-in high-precision sensors and cameras to record the user's actions and speech in real time and analyze the data. This analysis is sent to a server and used to generate appropriate instruction. The device also presents learning materials obtained from external providers, enhancing the learning experience through visual and audio feedback.

[0502] Users participate in programs offered through the device and receive personalized guidance from a generated AI model. For example, if a user selects a sports training program, the device uses a motion analysis model to immediately provide detailed guidance on improving form. An example of a specific prompt might be, "Create a basic form guide for the sport selected by the user."

[0503] Through this system, users can receive highly personalized education and training in real time, which is expected to improve learning efficiency and results.

[0504] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0505] Step 1:

[0506] Users access the system using a terminal and register. During registration, they enter personal information and educational / training programs of interest. The entered data is saved as a user profile and sent to the server. The terminal displays a list of currently available programs and prompts the user to make a selection. The user's selection information is then entered.

[0507] Step 2:

[0508] The terminal sends user selection information to the server. This information includes details about the program selected by the user. Based on the received selection information, the server selects an appropriate generative AI model. In the process, it generates prompt statements to apply to the selected AI model. Through these prompt statements, input is provided to optimize the instructions for the AI ​​model.

[0509] Step 3:

[0510] The server activates the selected AI model and generates optimal instructions and learning materials from the model using prompt messages. The prompt messages are input to the AI ​​model, which then outputs specific instruction content for the user as data. This data is immediately sent to the terminal.

[0511] Step 4:

[0512] The terminal receives the output of the AI ​​model sent from the server and displays it to the user. It also uses high-precision sensors and a camera within the terminal to record and analyze the user's actions and speech in real time. This analysis result is used as feedback. It receives real-time user data as input and outputs the processing results as feedback.

[0513] Step 5:

[0514] Users complete their selected educational and training programs based on instructions and feedback displayed on their devices. Continuous feedback on user actions and speech allows for immediate confirmation of performance improvements. Additional input regarding changes in user behavior is received, and improvement guidance is output based on this input.

[0515] (Application Example 1)

[0516] 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."

[0517] Improving the quality of customer service in modern brick-and-mortar stores requires effectively and efficiently enhancing the skills of each individual employee. However, traditional methods present challenges, such as abstract and immediacy-lacking feedback to employees, making it difficult to point out individual areas for improvement in a timely manner. Furthermore, accurately understanding customer service situations and providing specific advice requires significant resources and time.

[0518] 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.

[0519] In this invention, the server includes means for analyzing the user's actions and speech in real time using multiple detectors, means for presenting educational materials obtained from an external information source, means for providing immediate feedback to the user using artificial intelligence, means for generating user-specific evaluation information based on the analysis results, means for displaying the evaluation information to the user, and means for evaluating actions and pointing out areas for improvement in actual behavior verbally and visually. This makes it possible to quickly and concretely support the improvement of individual customer service skills of store employees in physical stores.

[0520] A "public space" is a specific area or place that is accessible to a large number of people and used for public purposes.

[0521] "Device" is a general term for equipment or tools configured to serve a specific purpose.

[0522] A "detector" is a device used to sense physical or chemical changes and acquire that information.

[0523] "Users" refer to the people who actually operate or use this system or device.

[0524] "Action" refers to the physical actions or behaviors performed by the user.

[0525] "Speech" refers to communication using words and sounds uttered by the user.

[0526] "Analysis" is the act or process of evaluating and interpreting acquired data to derive meaningful information.

[0527] "External information sources" refer to sources or providers that supply information and data from outside this system.

[0528] "Educational materials" refer to materials and content provided for learning or training.

[0529] Artificial intelligence is a technology that uses computers to mimic human intellectual activity and possesses the ability to learn, reason, and self-correct.

[0530] "Feedback" is information that is communicated to the recipient regarding the evaluation or results of an activity, in order to help with subsequent improvement or adjustment.

[0531] "Evaluation information" refers to information that indicates judgments about the user's skills and abilities based on the analysis results.

[0532] "Display" refers to the act of presenting information visually and allowing the user to confirm it.

[0533] "Evaluating an action" is the process of determining the effectiveness and accuracy of an action, either mechanically or manually.

[0534] "Areas for improvement in actions" refer to aspects of current methods and actions that need to be reviewed or improved.

[0535] "Verbal and visual feedback" refers to the act of indicating necessary improvements through audio or visual presentation.

[0536] This invention is a system for improving customer service skills in physical stores. This system uses a device equipped with multiple detectors to analyze the actions and speech of the store employee in real time and provide optimized feedback.

[0537] The server receives and analyzes data transmitted from various devices installed within the store. In particular, it utilizes speech recognition and image recognition APIs to convert the obtained data into text and visual information. This analysis is then processed by a specific AI model to evaluate the user's customer service skills. The server identifies areas for improvement during customer service, generates feedback, and sends it to the terminal.

[0538] The device provides an interface for conveying this feedback to the user. Specifically, it uses speech synthesis software and a display to intuitively present evaluation information. Based on the information presented, the user can immediately improve their customer service skills.

[0539] As an example of this system, when a store employee greets a customer with "Welcome," the AI ​​analyzes their tone of voice and posture and immediately provides advice such as "Speak louder" or "Try speaking in a more relaxed posture." This gives the employee an opportunity to adjust their behavior on the spot and improve the quality of their customer service.

[0540] The specific hardware used to implement this technology includes smart glasses, a microphone, speakers, and a display. The software, on the other hand, utilizes speech recognition APIs (such as Google Speech-to-Text), image recognition APIs, and AI modeling frameworks (such as PyTorch or TensorFlow).

[0541] An example of a prompt statement is, "We will develop a system in which AI analyzes the first words spoken to customers entering the store and provides real-time advice to improve customer service skills." This prompt statement concisely describes the purpose and function of a system using a generative AI model.

[0542] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0543] Step 1:

[0544] When a user puts on the device, the terminal begins capturing the user's voice and visual data through the smart glasses. The input consists of the user's verbal greetings and gestures, which are collected by sensors. The output is the captured raw data.

[0545] Step 2:

[0546] The device sends the captured audio data to the server. The server uses a speech recognition API (e.g., Google Speech-to-Text) to convert the audio data into text data. The input is audio data, and the output is text data. This conversion extracts the spoken content from the audio.

[0547] Step 3:

[0548] Next, the server uses an image recognition API to analyze visual data related to the user's gestures and facial expressions. The input is visual data, and the output is the analysis results regarding the user's actions. Based on these results, the server identifies the characteristics of the actions.

[0549] Step 4:

[0550] The server uses an AI model to evaluate the user's customer service skills based on the analysis results of their voice and actions. Inputs are text and action analysis results, and outputs are a list of evaluation scores and areas for improvement. The AI ​​model compares these results to historical data and training sets to make its evaluation.

[0551] Step 5:

[0552] The server generates immediate feedback based on the evaluation results and sends it to the terminal. This feedback includes voice instructions generated using speech synthesis software and visual instructions displayed on the screen. Input is a list of evaluation points and areas for improvement, while output is a feedback message.

[0553] Step 6:

[0554] The device provides the user with feedback via voice and display. The user can then immediately adjust their customer service style accordingly. The device uses the feedback to inform changes in the user's behavior for the next step (Step 1).

[0555] This allows the entire system to function cyclically, enabling real-time support for improving users' customer service skills.

[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 uses devices installed in public spaces to provide individually optimized education and training to users, and further recognizes and utilizes the user's emotions. This system is implemented using three main components: a server, a terminal, and a user.

[0558] System configuration and operation

[0559] This device is equipped with multiple high-precision sensors and cameras, allowing it to record and analyze user actions and speech in real time. Furthermore, the device features an emotion engine that can recognize emotions from the user's actions and facial expressions.

[0560] Program operation description

[0561] The server selects the optimal AI model and educational materials from external information providers based on information sent by the user and data acquired in real time. It also customizes the program by taking into account the emotional data detected by the emotion engine.

[0562] The device utilizes AI models and educational materials provided by the server to deliver an interactive educational and training experience to the user. The device provides real-time feedback and adjusts the content to suit the user based on the results of the emotion engine.

[0563] After selecting an educational program, the user's actions, speech, and facial expressions are captured by sensors. Recognizing the user's emotions allows for more personalized feedback and the presentation of learning materials by internal algorithms.

[0564] For example, if a user selects an interview training program and the system's emotion engine detects nervousness or a lack of confidence, the device will provide real-time feedback to boost their confidence. This feedback is based on positive language and settings to help the user respond with greater confidence.

[0565] In this way, this system provides high-quality, individually optimized education and training in public spaces, and can respond to the user's emotions. By quickly recognizing different emotions such as anger, satisfaction, and interest, and providing appropriate guidance, it creates a more effective learning environment.

[0566] The following describes the processing flow.

[0567] Step 1:

[0568] The user enters the booth and signs in to the program using the interface provided by the device. A welcome message is displayed, and it is explained that emotion detection technology will be used.

[0569] Step 2:

[0570] The device displays a list of available programs to the user. The user selects a program of interest, reviews its detailed purpose and learning content, and then chooses that program.

[0571] Step 3:

[0572] User selection information is sent from the terminal to the server. The server identifies the most suitable learning materials and AI model for that program and sends them to the terminal. It also triggers the activation of the emotion engine.

[0573] Step 4:

[0574] The device prepares an interactive initial screen for the user based on the acquired educational materials and AI model. Sensors and cameras begin to continuously acquire data on the user's movements, speech, and facial expressions.

[0575] Step 5:

[0576] The server analyzes the received motion and speech data in real time. In parallel, the emotion engine recognizes the user's emotions and sends the results back to the server.

[0577] Step 6:

[0578] The server generates feedback using an AI model based on the analyzed data and recognized emotions. This feedback includes positive reinforcement and necessary guidance tailored to the user's emotions.

[0579] Step 7:

[0580] The device presents feedback sent from the server to the user visually and audibly. The tone and content of the feedback are adjusted according to the user's emotions.

[0581] Step 8:

[0582] Users continue learning and training based on feedback, and adjust their efforts as needed.

[0583] Step 9:

[0584] After the session ends, the terminal displays the performance evaluation results to the user, and they can book their next session. The server anonymizes the data and uses it to improve future AI models.

[0585] (Example 2)

[0586] 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."

[0587] Traditional education and training systems struggle to provide individualized optimization that fully considers the emotional state of users, and real-time feedback and adjustments are limited. Furthermore, the process of users scheduling their next session is cumbersome. Therefore, there is a need for a system that provides a more effective and personalized learning experience while continuously supporting users' engagement.

[0588] 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.

[0589] In this invention, the server includes means for acquiring and analyzing the user's behavior and voice in real time using multiple sensors and imaging devices, means for identifying the user's emotions using an emotion analysis engine, and means for adapting and presenting educational materials acquired from external information sources to the user based on the analysis results and emotion data. This provides the user with an individually optimized educational and training experience, as well as enabling individualized feedback and adjustments in response to emotions.

[0590] A "public space" refers to a place that can be used or entered by an unspecified number of people, and is a space designed for education or training.

[0591] "Equipment" refers to a collection of physical devices and electronic devices installed to constitute a system, including sensors and imaging devices.

[0592] A "sensor" is a device that detects physical phenomena and outputs them in the form of electrical signals or other means, and is used to acquire the user's actions and voice.

[0593] An "imaging device" is a device that uses optical means to record images or videos, and its role is to capture the user's facial expressions and movements.

[0594] An "emotion analysis engine" refers to an algorithm and software system that identifies a user's emotional state from their facial expressions, actions, and other observations.

[0595] "External information sources" refer to external databases and content providers to which the system connects to obtain educational materials and training programs.

[0596] A "generated artificial intelligence model" is a machine learning model trained on a specific task and used to provide appropriate feedback and guidance to the user.

[0597] "Interactive feedback" refers to the responses and comments that a system provides in real time in response to the user's actions and statements, thereby improving the quality of education and training.

[0598] "Evaluation information" refers to information that compiles objective and subjective data generated based on the user's learning and training progress and results.

[0599] This invention is a system that provides users with individually optimized educational and training experiences through equipment installed in public spaces. The system mainly consists of three elements: a server, terminals, and users.

[0600] The server plays a central role in processing data transmitted from the terminal. Using multiple sensors and imaging devices, it receives data such as the user's behavior, facial expressions, and voice, acquired in real time by the terminal. This data is analyzed by an emotion analysis engine to identify the user's emotional state. Based on this emotional state and the acquired behavioral data, the server uses a generated artificial intelligence model to select educational materials and programs adapted to the user. Specifically, machine learning libraries such as TensorFlow and PyTorch are expected to be used.

[0601] The device provides interactive feedback to the user based on individually optimized educational and training content provided by the server. The device has the ability to monitor the user's behavior and speech in real time and adjust the educational content as needed, thereby improving the user's learning efficiency. The device responds immediately to the user's emotional responses, sending positive feedback and guidance. An example of a prompt might be, "Generate confidence-building feedback for a nervous user."

[0602] Users utilize equipment installed in public spaces to receive educational programs tailored to their choices. Their actions and speech are captured by sensors, allowing them to experience how the interactive experience provided is personalized. For example, if a user selects interview training and an emotion indicating nervousness is detected, the terminal provides appropriate guidance, allowing them to participate in the training with confidence.

[0603] In this way, the system provides feedback tailored to each user's individual emotions and learning patterns, resulting in a high-quality, personalized educational and training experience.

[0604] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0605] Step 1:

[0606] The device uses multiple sensors and imaging devices to capture the user's movements, facial expressions, and speech in real time. Input consists of the user's physical movements and speech, which are acquired as digital data. Output consists of raw sensor data and image data. Specifically, the sensors monitor the user's movements, and the camera acquires facial expressions as image data for analysis.

[0607] Step 2:

[0608] The terminal formats the captured data and sends it to the server. The input is the raw data acquired in step 1, and the output is formatted data. Specifically, the terminal compresses the data and processes it into a form that can be efficiently transferred.

[0609] Step 3:

[0610] The server analyzes the data received from the terminal. The input is formatted data of the user's actions and facial expressions, and the server uses an emotion analysis engine to recognize the user's emotional state. The output is the analyzed emotional status. Specifically, the server uses machine learning algorithms to analyze the input data and perform emotion recognition.

[0611] Step 4:

[0612] The server uses a generative AI model to determine appropriate learning materials and feedback based on recognized emotion data and user data. The input is emotion status and user performance data, and the output is individually optimized educational content. Specifically, the server searches a database of learning materials from external sources and configures a program tailored to the user's needs.

[0613] Step 5:

[0614] The device provides users with an interactive educational experience based on educational content received from the server. Input consists of optimized learning materials and feedback from the server, while output is real-time feedback to the user. Specifically, the device offers advice and instructions to improve the user's actions in real time, and adjusts this feedback as the learning material progresses.

[0615] Step 6:

[0616] The user receives feedback and learning materials from the device. The input is interactive feedback from the device, which is output as their learning or training outcome. The user follows the instructions and takes action to improve their skills. For example, during an interview training program, the user might receive and act on tips from the device to alleviate anxiety.

[0617] (Application Example 2)

[0618] 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."

[0619] In modern public spaces for education and training, there is a need to accommodate the diverse learning styles and emotional states of individual users, but conventional systems are insufficient in this regard. Furthermore, it is difficult to provide immediate feedback and encouraging messages that respond to the user's emotions, resulting in a failure to deliver an effective learning experience.

[0620] 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.

[0621] In this invention, the server includes means for analyzing the user's behavior and speech in real time using multiple detection devices, means for providing immediate feedback to the user using an intelligent algorithm, and means for generating and displaying encouraging messages that correspond to the user's emotions by incorporating emotion analysis technology. This makes it possible to provide individually optimized education and training that corresponds to each user's learning style and emotional state.

[0622] "Public space" refers to public places and facilities that are accessible to the general public.

[0623] "Detection device" refers to hardware such as sensors and cameras used to acquire the user's behavior and speech.

[0624] "Behavior" refers to the physical actions and words performed by the user.

[0625] "Speech" refers to words or sounds that a user utters orally.

[0626] "Real-time analysis" means processing data instantly and obtaining results quickly.

[0627] An "intelligent algorithm" refers to a set of computational procedures used to analyze data and generate appropriate feedback.

[0628] "Instant feedback" refers to information and advice that is returned instantly based on the user's behavior and emotional state.

[0629] "Emotional analysis technology" is a technology that recognizes and analyzes emotions from the user's facial expressions and voice.

[0630] "Supportive messages" refer to text or audio generated to encourage users based on their emotional state.

[0631] "Individualized optimization" means providing the most effective method tailored to each user's characteristics and circumstances.

[0632] The system of this invention provides users with individually optimized education and training using terminals installed in public spaces. Specifically, it is equipped with a detection device for analyzing the user's behavior and speech in real time, and an intelligent algorithm based on the acquired data provides immediate feedback to the user. These functions are realized by the following hardware and software.

[0633] The server uses multiple sensors and cameras to capture the user's behavior and speech. These devices can analyze the user's actions and words in real time, and the data is immediately transmitted to the server. The intelligent algorithm uses the OpenCV data analysis library to analyze facial and movement features, and Amazon Rekognition to identify emotions. This generates emotion data.

[0634] The device executes educational programs based on information sent from the server, providing users with an interactive experience. The device displays feedback generated by intelligent algorithms and outputs encouraging messages to boost user motivation. These messages are customized based on the user's emotional data at the time.

[0635] As a concrete example, when staff receiving customer service training in a physical store use this system, the terminal provides feedback such as, "Customer service with confidence!" This feedback is displayed when the intelligent algorithm determines that the user is feeling nervous. Furthermore, if good customer service skills are observed, a positive message such as, "That was excellent service!" can be displayed. An example of a prompt would be, "Generate a positive message to alleviate tension and anxiety during customer service."

[0636] Thus, the present invention functions as a platform for providing individually optimized education and training in real time, thereby enhancing the learning effectiveness of users.

[0637] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0638] Step 1:

[0639] The user logs into the system via their terminal. The system receives the user's authentication information as input. The server verifies the authentication information and loads the user profile. The user's profile data is displayed on the terminal as output.

[0640] Step 2:

[0641] The user selects the educational program they wish to learn. The terminal receives program selection information as input. The terminal then sends the selected program information to the server. The output presents the user with an overview of the program and instructions for getting started.

[0642] Step 3:

[0643] The detection device captures the user's behavior and speech in real time. It acquires camera video and microphone audio data as input. The server analyzes the video data using OpenCV and generates emotion data using Amazon Rekognition. The analysis results are then fed into an intelligent algorithm as output.

[0644] Step 4:

[0645] The server generates appropriate feedback using the acquired behavioral and sentimental data. It receives behavioral and sentimental data as input. An intelligent algorithm processes the data to create a feedback message. The generated feedback is sent to the terminal as output.

[0646] Step 5:

[0647] The device displays generated feedback and encouraging messages to the user in real time. It receives feedback data from the server as input. It performs specific actions to present immediate advice and encouraging messages to the user. The user's response is fed back to the device as output.

[0648] Step 6:

[0649] After the session ends, the server stores all data for later analysis and improvement of intelligent algorithms. It receives all data collected during the session as input. This data is anonymized and used for long-term functionality improvements. The output is stored in the system's database.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] [Fourth Embodiment]

[0654] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0655] 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.

[0656] 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).

[0657] 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.

[0658] 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.

[0659] 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).

[0660] 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.

[0661] 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.

[0662] 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.

[0663] 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.

[0664] 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.

[0665] 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.

[0666] 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".

[0667] One embodiment of this invention is a system that enables users to receive individually optimized education and training using a device installed in a public space. This system consists of three main components: a server, a terminal, and a user.

[0668] System Overview

[0669] The device incorporates multiple high-precision sensors and cameras to record and analyze the user's actions and speech in real time. The terminal displays educational materials obtained from external providers to support the specific training or educational program selected by the user. This provides an AI-powered interactive learning experience.

[0670] Program Description

[0671] The server identifies the appropriate AI model and learning materials based on the user's selection information sent from the terminal. The server constantly maintains and manages multiple AI models, each with specific educational and training functions built in.

[0672] After the user registers and selects a program, the terminal communicates with the server to retrieve the necessary learning materials and AI models, and immediately presents them to the user. The terminal also processes input data from sensors in real time, providing the user with immediate visual and audible feedback.

[0673] Users receive training and education through their chosen program. During this process, sensors detect the user's movements and speech, and the data is sent to an AI model via a server, providing optimal instructions and advice through the device.

[0674] For example, when a user selects a sports training program, the device utilizes an AI model to analyze sports movements and provides specific instructions on form and performance in real time. This allows the user to make precise adjustments to their movements and optimize their performance on the spot.

[0675] Through the configuration and processes described above, this system can provide users with high-quality educational and training opportunities that are available at any time.

[0676] The following describes the processing flow.

[0677] Step 1:

[0678] The server records the user's registration information and the type of program selected, received from the terminal, in a database. This information is used to determine the appropriate AI model and content.

[0679] Step 2:

[0680] The terminal displays details of available programs to the user on the screen. The user selects their desired program from the displayed options and confirms its specific details.

[0681] Step 3:

[0682] Once the user selects a program, the terminal sends that selection information to the server and requests the necessary learning materials and AI models.

[0683] Step 4:

[0684] The server accesses databases of external information providers to retrieve the most suitable learning materials for the program selected by the user. It also delivers AI models related to the selected program to the device.

[0685] Step 5:

[0686] The device provides users with an interactive screen using the delivered educational materials and AI models. The device captures user actions and speech data through sensors.

[0687] Step 6:

[0688] The server processes data sent from the terminal in real time and performs analysis based on an AI model. This generates immediate feedback for the user.

[0689] Step 7:

[0690] The device visualizes the feedback received from the server and provides instructions for the next action or utterance. The user continues training and learning while referring to these instructions.

[0691] Step 8:

[0692] When a user ends a session, the device sends that information to the server, which evaluates the user's performance data and creates feedback that includes areas for improvement for the next session.

[0693] Step 9:

[0694] The server saves the generated feedback to the user's account, and the device displays this to the user before ending the session. The user can then use the information they have reviewed to schedule their next session.

[0695] (Example 1)

[0696] 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".

[0697] In today's educational and training environments, providing learning and instruction optimized for individual needs in real time is considered difficult. Furthermore, the ability to provide effective, immediate feedback to users is required, but achieving this demands advanced technology. Additionally, there is still a lack of efficient and flexible systems capable of providing optimal learning experiences based on diverse user choices.

[0698] 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.

[0699] In this invention, the server includes means for identifying and operating the optimal generative AI model based on the user's selection, means for generating optimal instructions and learning materials from the AI ​​model using prompt statements, and means for displaying the evaluation information to the user. This makes it possible to provide the user with individually optimized education and training and to provide effective feedback in real time.

[0700] A "public space" refers to a place that is accessible to the general public and used for education and training.

[0701] A "device" refers to a piece of equipment with a hardware structure that provides users with an interactive experience through sensing and computation.

[0702] A "sensor" refers to a device that acquires external data, such as the user's actions and speech, and inputs it for analysis.

[0703] "External information providers" refer to information sources outside the system that provide educational content or training materials.

[0704] "Artificial intelligence" refers to computational algorithms designed to generate immediate feedback for the user.

[0705] "Feedback" refers to response information, including instructions and evaluations, provided in response to actions or utterances performed by the user.

[0706] "Evaluation information" refers to individual evaluation data generated based on the user's performance.

[0707] A "generative AI model" refers to an AI model used to generate optimal instructions based on user selections.

[0708] A "prompt statement" refers to an input statement used to cause an AI model to generate a specific output.

[0709] This invention is a system that enables users to receive individually optimized education and training using devices installed in public spaces. The system consists of three main components: a server, a terminal, and the user.

[0710] The server maintains and manages multiple AI models, identifying and running the optimal model based on user selections. During this process, prompts are used, and the AI ​​model generates instructions and training materials optimized for the user. This generated data is then provided to the user as immediate feedback.

[0711] The device utilizes multiple built-in high-precision sensors and cameras to record the user's actions and speech in real time and analyze the data. This analysis is sent to a server and used to generate appropriate instruction. The device also presents learning materials obtained from external providers, enhancing the learning experience through visual and audio feedback.

[0712] Users participate in programs offered through the device and receive personalized guidance from a generated AI model. For example, if a user selects a sports training program, the device uses a motion analysis model to immediately provide detailed guidance on improving form. An example of a specific prompt might be, "Create a basic form guide for the sport selected by the user."

[0713] Through this system, users can receive highly personalized education and training in real time, which is expected to improve learning efficiency and results.

[0714] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0715] Step 1:

[0716] Users access the system using a terminal and register. During registration, they enter personal information and educational / training programs of interest. The entered data is saved as a user profile and sent to the server. The terminal displays a list of currently available programs and prompts the user to make a selection. The user's selection information is then entered.

[0717] Step 2:

[0718] The terminal sends user selection information to the server. This information includes details about the program selected by the user. Based on the received selection information, the server selects an appropriate generative AI model. In the process, it generates prompt statements to apply to the selected AI model. Through these prompt statements, input is provided to optimize the instructions for the AI ​​model.

[0719] Step 3:

[0720] The server activates the selected AI model and generates optimal instructions and learning materials from the model using prompt messages. The prompt messages are input to the AI ​​model, which then outputs specific instruction content for the user as data. This data is immediately sent to the terminal.

[0721] Step 4:

[0722] The terminal receives the output of the AI ​​model sent from the server and displays it to the user. It also uses high-precision sensors and a camera within the terminal to record and analyze the user's actions and speech in real time. This analysis result is used as feedback. It receives real-time user data as input and outputs the processing results as feedback.

[0723] Step 5:

[0724] Users complete their selected educational and training programs based on instructions and feedback displayed on their devices. Continuous feedback on user actions and speech allows for immediate confirmation of performance improvements. Additional input regarding changes in user behavior is received, and improvement guidance is output based on this input.

[0725] (Application Example 1)

[0726] 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".

[0727] Improving the quality of customer service in modern brick-and-mortar stores requires effectively and efficiently enhancing the skills of each individual employee. However, traditional methods present challenges, such as abstract and immediacy-lacking feedback to employees, making it difficult to point out individual areas for improvement in a timely manner. Furthermore, accurately understanding customer service situations and providing specific advice requires significant resources and time.

[0728] 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.

[0729] In this invention, the server includes means for analyzing the user's actions and speech in real time using multiple detectors, means for presenting educational materials obtained from an external information source, means for providing immediate feedback to the user using artificial intelligence, means for generating user-specific evaluation information based on the analysis results, means for displaying the evaluation information to the user, and means for evaluating actions and pointing out areas for improvement in actual behavior verbally and visually. This makes it possible to quickly and concretely support the improvement of individual customer service skills of store employees in physical stores.

[0730] A "public space" is a specific area or place that is accessible to a large number of people and used for public purposes.

[0731] "Device" is a general term for equipment or tools configured to serve a specific purpose.

[0732] A "detector" is a device used to sense physical or chemical changes and acquire that information.

[0733] "Users" refer to the people who actually operate or use this system or device.

[0734] "Action" refers to the physical actions or behaviors performed by the user.

[0735] "Speech" refers to communication using words and sounds uttered by the user.

[0736] "Analysis" is the act or process of evaluating and interpreting acquired data to derive meaningful information.

[0737] "External information sources" refer to sources or providers that supply information and data from outside this system.

[0738] "Educational materials" refer to materials and content provided for learning or training.

[0739] Artificial intelligence is a technology that uses computers to mimic human intellectual activity and possesses the ability to learn, reason, and self-correct.

[0740] "Feedback" is information that is communicated to the recipient regarding the evaluation or results of an activity, in order to help with subsequent improvement or adjustment.

[0741] "Evaluation information" refers to information that indicates judgments about the user's skills and abilities based on the analysis results.

[0742] "Display" refers to the act of presenting information visually and allowing the user to confirm it.

[0743] "Evaluating an action" is the process of determining the effectiveness and accuracy of an action, either mechanically or manually.

[0744] "Areas for improvement in actions" refer to aspects of current methods and actions that need to be reviewed or improved.

[0745] "Verbal and visual feedback" refers to the act of indicating necessary improvements through audio or visual presentation.

[0746] This invention is a system for improving customer service skills in physical stores. This system uses a device equipped with multiple detectors to analyze the actions and speech of the store employee in real time and provide optimized feedback.

[0747] The server receives and analyzes data transmitted from various devices installed within the store. In particular, it utilizes speech recognition and image recognition APIs to convert the obtained data into text and visual information. This analysis is then processed by a specific AI model to evaluate the user's customer service skills. The server identifies areas for improvement during customer service, generates feedback, and sends it to the terminal.

[0748] The device provides an interface for conveying this feedback to the user. Specifically, it uses speech synthesis software and a display to intuitively present evaluation information. Based on the information presented, the user can immediately improve their customer service skills.

[0749] As an example of this system, when a store employee greets a customer with "Welcome," the AI ​​analyzes their tone of voice and posture and immediately provides advice such as "Speak louder" or "Try speaking in a more relaxed posture." This gives the employee an opportunity to adjust their behavior on the spot and improve the quality of their customer service.

[0750] The specific hardware used to implement this technology includes smart glasses, a microphone, speakers, and a display. The software, on the other hand, utilizes speech recognition APIs (such as Google Speech-to-Text), image recognition APIs, and AI modeling frameworks (such as PyTorch or TensorFlow).

[0751] An example of a prompt statement is, "We will develop a system in which AI analyzes the first words spoken to customers entering the store and provides real-time advice to improve customer service skills." This prompt statement concisely describes the purpose and function of a system using a generative AI model.

[0752] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0753] Step 1:

[0754] When a user puts on the device, the terminal begins capturing the user's voice and visual data through the smart glasses. The input consists of the user's verbal greetings and gestures, which are collected by sensors. The output is the captured raw data.

[0755] Step 2:

[0756] The device sends the captured audio data to the server. The server uses a speech recognition API (e.g., Google Speech-to-Text) to convert the audio data into text data. The input is audio data, and the output is text data. This conversion extracts the spoken content from the audio.

[0757] Step 3:

[0758] Next, the server uses an image recognition API to analyze visual data related to the user's gestures and facial expressions. The input is visual data, and the output is the analysis results regarding the user's actions. Based on these results, the server identifies the characteristics of the actions.

[0759] Step 4:

[0760] The server uses an AI model to evaluate the user's customer service skills based on the analysis results of their voice and actions. Inputs are text and action analysis results, and outputs are a list of evaluation scores and areas for improvement. The AI ​​model compares these results to historical data and training sets to make its evaluation.

[0761] Step 5:

[0762] The server generates immediate feedback based on the evaluation results and sends it to the terminal. This feedback includes voice instructions generated using speech synthesis software and visual instructions displayed on the screen. Input is a list of evaluation points and areas for improvement, while output is a feedback message.

[0763] Step 6:

[0764] The device provides the user with feedback via voice and display. The user can then immediately adjust their customer service style accordingly. The device uses the feedback to inform changes in the user's behavior for the next step (Step 1).

[0765] This allows the entire system to function cyclically, enabling real-time support for improving users' customer service skills.

[0766] 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.

[0767] This invention is a system that uses devices installed in public spaces to provide individually optimized education and training to users, and further recognizes and utilizes the user's emotions. This system is implemented using three main components: a server, a terminal, and a user.

[0768] System configuration and operation

[0769] This device is equipped with multiple high-precision sensors and cameras, allowing it to record and analyze user actions and speech in real time. Furthermore, the device features an emotion engine that can recognize emotions from the user's actions and facial expressions.

[0770] Program operation description

[0771] The server selects the optimal AI model and educational materials from external information providers based on information sent by the user and data acquired in real time. It also customizes the program by taking into account the emotional data detected by the emotion engine.

[0772] The device utilizes AI models and educational materials provided by the server to deliver an interactive educational and training experience to the user. The device provides real-time feedback and adjusts the content to suit the user based on the results of the emotion engine.

[0773] After selecting an educational program, the user's actions, speech, and facial expressions are captured by sensors. Recognizing the user's emotions allows for more personalized feedback and the presentation of learning materials by internal algorithms.

[0774] For example, if a user selects an interview training program and the system's emotion engine detects nervousness or a lack of confidence, the device will provide real-time feedback to boost their confidence. This feedback is based on positive language and settings to help the user respond with greater confidence.

[0775] In this way, this system provides high-quality, individually optimized education and training in public spaces, and can respond to the user's emotions. By quickly recognizing different emotions such as anger, satisfaction, and interest, and providing appropriate guidance, it creates a more effective learning environment.

[0776] The following describes the processing flow.

[0777] Step 1:

[0778] The user enters the booth and signs in to the program using the interface provided by the device. A welcome message is displayed, and it is explained that emotion detection technology will be used.

[0779] Step 2:

[0780] The device displays a list of available programs to the user. The user selects a program of interest, reviews its detailed purpose and learning content, and then chooses that program.

[0781] Step 3:

[0782] User selection information is sent from the terminal to the server. The server identifies the most suitable learning materials and AI model for that program and sends them to the terminal. It also triggers the activation of the emotion engine.

[0783] Step 4:

[0784] The device prepares an interactive initial screen for the user based on the acquired educational materials and AI model. Sensors and cameras begin to continuously acquire data on the user's movements, speech, and facial expressions.

[0785] Step 5:

[0786] The server analyzes the received motion and speech data in real time. In parallel, the emotion engine recognizes the user's emotions and sends the results back to the server.

[0787] Step 6:

[0788] The server generates feedback using an AI model based on the analyzed data and recognized emotions. This feedback includes positive reinforcement and necessary guidance tailored to the user's emotions.

[0789] Step 7:

[0790] The device presents feedback sent from the server to the user visually and audibly. The tone and content of the feedback are adjusted according to the user's emotions.

[0791] Step 8:

[0792] Users continue learning and training based on feedback, and adjust their efforts as needed.

[0793] Step 9:

[0794] After the session ends, the terminal displays the performance evaluation results to the user, and they can book their next session. The server anonymizes the data and uses it to improve future AI models.

[0795] (Example 2)

[0796] 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".

[0797] Traditional education and training systems struggle to provide individualized optimization that fully considers the emotional state of users, and real-time feedback and adjustments are limited. Furthermore, the process of users scheduling their next session is cumbersome. Therefore, there is a need for a system that provides a more effective and personalized learning experience while continuously supporting users' engagement.

[0798] 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.

[0799] In this invention, the server includes means for acquiring and analyzing the user's behavior and voice in real time using multiple sensors and imaging devices, means for identifying the user's emotions using an emotion analysis engine, and means for adapting and presenting educational materials acquired from external information sources to the user based on the analysis results and emotion data. This provides the user with an individually optimized educational and training experience, as well as enabling individualized feedback and adjustments in response to emotions.

[0800] A "public space" refers to a place that can be used or entered by an unspecified number of people, and is a space designed for education or training.

[0801] "Equipment" refers to a collection of physical devices and electronic devices installed to constitute a system, including sensors and imaging devices.

[0802] A "sensor" is a device that detects physical phenomena and outputs them in the form of electrical signals or other means, and is used to acquire the user's actions and voice.

[0803] An "imaging device" is a device that uses optical means to record images or videos, and its role is to capture the user's facial expressions and movements.

[0804] An "emotion analysis engine" refers to an algorithm and software system that identifies a user's emotional state from their facial expressions, actions, and other observations.

[0805] "External information sources" refer to external databases and content providers to which the system connects to obtain educational materials and training programs.

[0806] A "generated artificial intelligence model" is a machine learning model trained on a specific task and used to provide appropriate feedback and guidance to the user.

[0807] "Interactive feedback" refers to the responses and comments that a system provides in real time in response to the user's actions and statements, thereby improving the quality of education and training.

[0808] "Evaluation information" refers to information that compiles objective and subjective data generated based on the user's learning and training progress and results.

[0809] This invention is a system that provides users with individually optimized educational and training experiences through equipment installed in public spaces. The system mainly consists of three elements: a server, terminals, and users.

[0810] The server plays a central role in processing data transmitted from the terminal. Using multiple sensors and imaging devices, it receives data such as the user's behavior, facial expressions, and voice, acquired in real time by the terminal. This data is analyzed by an emotion analysis engine to identify the user's emotional state. Based on this emotional state and the acquired behavioral data, the server uses a generated artificial intelligence model to select educational materials and programs adapted to the user. Specifically, machine learning libraries such as TensorFlow and PyTorch are expected to be used.

[0811] The device provides interactive feedback to the user based on individually optimized educational and training content provided by the server. The device has the ability to monitor the user's behavior and speech in real time and adjust the educational content as needed, thereby improving the user's learning efficiency. The device responds immediately to the user's emotional responses, sending positive feedback and guidance. An example of a prompt might be, "Generate confidence-building feedback for a nervous user."

[0812] Users utilize equipment installed in public spaces to receive educational programs tailored to their choices. Their actions and speech are captured by sensors, allowing them to experience how the interactive experience provided is personalized. For example, if a user selects interview training and an emotion indicating nervousness is detected, the terminal provides appropriate guidance, allowing them to participate in the training with confidence.

[0813] In this way, the system provides feedback tailored to each user's individual emotions and learning patterns, resulting in a high-quality, personalized educational and training experience.

[0814] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0815] Step 1:

[0816] The device uses multiple sensors and imaging devices to capture the user's movements, facial expressions, and speech in real time. Input consists of the user's physical movements and speech, which are acquired as digital data. Output consists of raw sensor data and image data. Specifically, the sensors monitor the user's movements, and the camera acquires facial expressions as image data for analysis.

[0817] Step 2:

[0818] The terminal formats the captured data and sends it to the server. The input is the raw data acquired in step 1, and the output is formatted data. Specifically, the terminal compresses the data and processes it into a form that can be efficiently transferred.

[0819] Step 3:

[0820] The server analyzes the data received from the terminal. The input is formatted data of the user's actions and facial expressions, and the server uses an emotion analysis engine to recognize the user's emotional state. The output is the analyzed emotional status. Specifically, the server uses machine learning algorithms to analyze the input data and perform emotion recognition.

[0821] Step 4:

[0822] The server uses a generative AI model to determine appropriate learning materials and feedback based on recognized emotion data and user data. The input is emotion status and user performance data, and the output is individually optimized educational content. Specifically, the server searches a database of learning materials from external sources and configures a program tailored to the user's needs.

[0823] Step 5:

[0824] The device provides users with an interactive educational experience based on educational content received from the server. Input consists of optimized learning materials and feedback from the server, while output is real-time feedback to the user. Specifically, the device offers advice and instructions to improve the user's actions in real time, and adjusts this feedback as the learning material progresses.

[0825] Step 6:

[0826] The user receives feedback and learning materials from the device. The input is interactive feedback from the device, which is output as their learning or training outcome. The user follows the instructions and takes action to improve their skills. For example, during an interview training program, the user might receive and act on tips from the device to alleviate anxiety.

[0827] (Application Example 2)

[0828] 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".

[0829] In modern public spaces for education and training, there is a need to accommodate the diverse learning styles and emotional states of individual users, but conventional systems are insufficient in this regard. Furthermore, it is difficult to provide immediate feedback and encouraging messages that respond to the user's emotions, resulting in a failure to deliver an effective learning experience.

[0830] 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.

[0831] In this invention, the server includes means for analyzing the user's behavior and speech in real time using multiple detection devices, means for providing immediate feedback to the user using an intelligent algorithm, and means for generating and displaying encouraging messages that correspond to the user's emotions by incorporating emotion analysis technology. This makes it possible to provide individually optimized education and training that corresponds to each user's learning style and emotional state.

[0832] "Public space" refers to public places and facilities that are accessible to the general public.

[0833] "Detection device" refers to hardware such as sensors and cameras used to acquire the user's behavior and speech.

[0834] "Behavior" refers to the physical actions and words performed by the user.

[0835] "Speech" refers to words or sounds that a user utters orally.

[0836] "Real-time analysis" means processing data instantly and obtaining results quickly.

[0837] An "intelligent algorithm" refers to a set of computational procedures used to analyze data and generate appropriate feedback.

[0838] "Instant feedback" refers to information and advice that is returned instantly based on the user's behavior and emotional state.

[0839] "Emotional analysis technology" is a technology that recognizes and analyzes emotions from the user's facial expressions and voice.

[0840] "Supportive messages" refer to text or audio generated to encourage users based on their emotional state.

[0841] "Individualized optimization" means providing the most effective method tailored to each user's characteristics and circumstances.

[0842] The system of this invention provides users with individually optimized education and training using terminals installed in public spaces. Specifically, it is equipped with a detection device for analyzing the user's behavior and speech in real time, and an intelligent algorithm based on the acquired data provides immediate feedback to the user. These functions are realized by the following hardware and software.

[0843] The server uses multiple sensors and cameras to capture the user's behavior and speech. These devices can analyze the user's actions and words in real time, and the data is immediately transmitted to the server. The intelligent algorithm uses the OpenCV data analysis library to analyze facial and movement features, and Amazon Rekognition to identify emotions. This generates emotion data.

[0844] The device executes educational programs based on information sent from the server, providing users with an interactive experience. The device displays feedback generated by intelligent algorithms and outputs encouraging messages to boost user motivation. These messages are customized based on the user's emotional data at the time.

[0845] As a concrete example, when staff receiving customer service training in a physical store use this system, the terminal provides feedback such as, "Customer service with confidence!" This feedback is displayed when the intelligent algorithm determines that the user is feeling nervous. Furthermore, if good customer service skills are observed, a positive message such as, "That was excellent service!" can be displayed. An example of a prompt would be, "Generate a positive message to alleviate tension and anxiety during customer service."

[0846] Thus, the present invention functions as a platform for providing individually optimized education and training in real time, thereby enhancing the learning effectiveness of users.

[0847] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0848] Step 1:

[0849] The user logs into the system via their terminal. The system receives the user's authentication information as input. The server verifies the authentication information and loads the user profile. The user's profile data is displayed on the terminal as output.

[0850] Step 2:

[0851] The user selects the educational program they wish to learn. The terminal receives program selection information as input. The terminal then sends the selected program information to the server. The output presents the user with an overview of the program and instructions for getting started.

[0852] Step 3:

[0853] The detection device captures the user's behavior and speech in real time. It acquires camera video and microphone audio data as input. The server analyzes the video data using OpenCV and generates emotion data using Amazon Rekognition. The analysis results are then fed into an intelligent algorithm as output.

[0854] Step 4:

[0855] The server generates appropriate feedback using the acquired behavioral and sentimental data. It receives behavioral and sentimental data as input. An intelligent algorithm processes the data to create a feedback message. The generated feedback is sent to the terminal as output.

[0856] Step 5:

[0857] The device displays generated feedback and encouraging messages to the user in real time. It receives feedback data from the server as input. It performs specific actions to present immediate advice and encouraging messages to the user. The user's response is fed back to the device as output.

[0858] Step 6:

[0859] After the session ends, the server stores all data for later analysis and improvement of intelligent algorithms. It receives all data collected during the session as input. This data is anonymized and used for long-term functionality improvements. The output is stored in the system's database.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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."

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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 as being incorporated by reference.

[0881] The following is further disclosed regarding the embodiments described above.

[0882] (Claim 1)

[0883] A device placed in a public space,

[0884] A means of analyzing the user's actions and speech in real time using multiple sensors,

[0885] A means of presenting educational materials obtained from external information providers,

[0886] A means of providing immediate feedback to users using artificial intelligence,

[0887] A means for generating user-specific evaluation information based on analysis results,

[0888] A system including means for displaying the aforementioned evaluation information to the user.

[0889] (Claim 2)

[0890] The system according to claim 1, characterized in that it includes means for automatically acquiring and anonymizing motion data, storing it, and using it to improve the artificial intelligence.

[0891] (Claim 3)

[0892] The system according to claim 1, characterized in that it includes a means for the user to make a reservation for the next session after the end of each evaluation session.

[0893] "Example 1"

[0894] (Claim 1)

[0895] A device placed in a public space,

[0896] A means of analyzing the user's actions and speech in real time using multiple sensors,

[0897] A means of presenting educational materials obtained from external information providers,

[0898] A means of providing immediate feedback to users using artificial intelligence,

[0899] A means for generating user-specific evaluation information based on analysis results,

[0900] A means of identifying and operating the optimal generative AI model based on user selection,

[0901] A means of generating optimal instructions and learning materials from an AI model using prompt statements,

[0902] A system including means for displaying the aforementioned evaluation information to the user.

[0903] (Claim 2)

[0904] The system according to claim 1, which includes means for automatically acquiring and anonymizing motion data, and using it to improve the artificial intelligence.

[0905] (Claim 3)

[0906] The system according to claim 1, which includes a means for the user to make a reservation for the next use after each evaluation session has ended.

[0907] "Application Example 1"

[0908] (Claim 1)

[0909] A device placed in a public space,

[0910] A means of analyzing the user's actions and speech in real time using multiple detectors,

[0911] A means of presenting educational materials obtained from external information sources,

[0912] A means of providing immediate feedback to users using artificial intelligence,

[0913] A means for generating user-specific evaluation information based on analysis results,

[0914] Means for displaying the aforementioned evaluation information to the user,

[0915] A means of evaluating actions and pointing out areas for improvement in practical behavior, both verbally and visually.

[0916] A system that includes this.

[0917] (Claim 2)

[0918] The system according to claim 1, which includes means for automatically acquiring and anonymizing motion data, and using it to improve the artificial intelligence.

[0919] (Claim 3)

[0920] The system according to claim 1, which includes a means for the user to make a reservation for the next use after each evaluation session has ended.

[0921] "Example 2 of combining an emotion engine"

[0922] (Claim 1)

[0923] Equipment placed in public spaces,

[0924] A means of acquiring and analyzing the user's actions and voice in real time using multiple sensors and imaging devices,

[0925] A means of identifying the user's emotions using an emotion analysis engine,

[0926] A means of adapting and presenting educational materials obtained from external sources based on analysis results and emotional data to the user,

[0927] A means of providing interactive feedback to the user using the generated artificial intelligence model,

[0928] A means for generating individually optimized evaluation information based on analysis results and feedback, and presenting it to the user,

[0929] A system that includes means for adjusting educational and training content in real time.

[0930] (Claim 2)

[0931] The system according to claim 1, further comprising means for anonymizing and accumulating acquired behavioral data and using it to improve the generated artificial intelligence model.

[0932] (Claim 3)

[0933] The system according to claim 1, which includes means for the user to easily reserve the next use after each evaluation session has ended.

[0934] "Application example 2 when combining with an emotional engine"

[0935] (Claim 1)

[0936] A device placed in a public space,

[0937] A means of analyzing the user's behavior and speech in real time using multiple detection devices,

[0938] A means of presenting educational materials obtained from external information providers,

[0939] A means of providing immediate feedback to the user using an intelligent algorithm,

[0940] A means for generating user-specific evaluation information based on analysis results,

[0941] Means for displaying the aforementioned evaluation information to the user,

[0942] A means of generating and displaying encouraging messages tailored to the user's emotions, incorporating emotion analysis technology.

[0943] A means for analyzing the user's behavior and providing facilitative navigation selected by an intelligent algorithm.

[0944] A system that includes this.

[0945] (Claim 2)

[0946] The system according to claim 1, characterized in that it includes means for automatically acquiring behavioral data and emotional data, anonymizing and accumulating them, and using them to improve the intelligent algorithm.

[0947] (Claim 3)

[0948] The system according to claim 1, characterized in that it includes a means for the user to make a reservation for the next session after the end of each evaluation session, and for providing a feedback history in text format. [Explanation of Symbols]

[0949] 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 device placed in a public space, A means of analyzing the user's actions and speech in real time using multiple sensors, A means of presenting educational materials obtained from external information providers, A means of providing immediate feedback to users using artificial intelligence, A means for generating user-specific evaluation information based on analysis results, A system including means for displaying the aforementioned evaluation information to the user.

2. The system according to claim 1, characterized in that it includes means for automatically acquiring and anonymizing motion data, storing it, and using it to improve the artificial intelligence.

3. The system according to claim 1, characterized in that it includes a means for the user to make a reservation for the next session after the end of each evaluation session.

Images