system

Abstract

We provide the system. [Solution] A means of automatically generating educational content scenarios using artificial intelligence, A means for automatically generating audio narration and subtitles based on a generated scenario, Methods for inserting interactive quizzes and feedback into video content, A means of tracking learners' progress and providing individualized feedback, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds 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 distance education and hybrid education environments, the demand for high-quality and efficient educational content is increasing. In particular, there is a need for specialized training modules adapted to various industries and individualized learning experiences according to the needs of each learner. However, since the content that meets these requirements requires a great deal of time and effort to create, it is difficult to provide it quickly and effectively. Furthermore, the current technology has not fully solved the problems of dealing with learners in multilingual environments and automatically tracking learning progress and providing feedback. In addition, the functions for providing an interactive learning experience are not standardized, and the educational effect may be limited. As a result, companies and educational institutions have challenges in providing appropriate educational tools.

Means for Solving the Problems

[0005] This invention solves the above problems by providing an educational content creation system that utilizes artificial intelligence. Specifically, it includes a function to automatically generate scenarios for educational content using artificial intelligence. This makes it possible to create high-quality content in a short time. Furthermore, by automatically generating voice narration and subtitles based on the generated scenarios, multilingual support is easily achieved. In addition, it includes a function to insert interactive quizzes and feedback into video content, tracking learner progress and providing individualized feedback. This system not only provides industry-specific standard training modules but also enables flexible educational support in multinational environments. It also enables the streamlining of the learning process and the achievement of effective learning outcomes. This makes it possible to build an optimal educational environment that meets the diverse needs of companies and educational institutions.

[0006] Artificial intelligence is a technology that enables computer systems to mimic human intellectual behavior and automate learning and problem-solving.

[0007] "Educational content" refers to informational materials and resources used by learners to acquire specific knowledge or skills.

[0008] A "scenario" is a plan or framework that defines the flow, structure, and content of educational materials.

[0009] "Voice narration" refers to the use of voice to explain content or convey information in educational materials.

[0010] "Subtitles" are textual information that transcribes the audio information of educational content and displays it on the screen.

[0011] A "quiz" refers to questions or problems administered to check learners' understanding and reinforce what they have learned.

[0012] "Feedback" refers to evaluation and guidance information provided regarding a learner's activities and achievements.

[0013] "Progress tracking" refers to recording and managing the progress and achievement level of learners' learning activities.

[0014] A "training module" is a part of an educational program designed to systematically teach specific skills or knowledge.

[0015] "Multilingual support" refers to the availability of a system or content in multiple languages. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This 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] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] 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.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] This invention relates to an educational content creation system utilizing artificial intelligence, and its embodiments are described in detail. This system consists of a server, a user terminal, and user operations, and is capable of quickly responding to diverse educational needs.

[0038] First, the user accesses the system using their device and logs in. The user can then choose either "Create a New Video" or "Take a Training Module," depending on their purpose. Based on the selected purpose, the device sends relevant information to the server.

[0039] The server receives the user's selection and first uses artificial intelligence to automatically generate appropriate educational content scenarios. In this scenario generation process, relevant information is retrieved from a database to determine the optimal configuration for the purpose. For example, if the purpose is medical training, a scenario including the necessary knowledge and procedures will be designed.

[0040] Next, based on the generated scenario, the server automatically creates voice narration using AI speech synthesis technology and also generates multilingual subtitles. This process enables the creation of effective educational content that transcends language barriers.

[0041] The server then adds interactive elements to the video content. Specifically, these include quizzes to assess the learner's understanding and feedback features that allow for immediate confirmation of learning effectiveness. Such features help reinforce learning and promote effective learning.

[0042] The completed video content is streamed to the user's device by the server. Users can track their progress in real time, and personalized feedback is provided from the server based on the collected data. For example, additional learning is suggested according to the learning progress, and necessary knowledge reinforcement is supported.

[0043] This system allows companies and educational institutions to deliver educational content quickly and flexibly, and enables learners to acquire knowledge at their own pace. As a result, an educational environment is created that efficiently improves skills and knowledge.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The user logs into the device and selects an option to create educational content or take a training module. The device then sends the user's selection information to the server.

[0047] Step 2:

[0048] Based on the received selection information, the server automatically generates relevant educational content scenarios using artificial intelligence. Here, the server retrieves necessary information from the database and determines the structure of the scenario.

[0049] Step 3:

[0050] The server uses the generated scenario to create narration using an AI speech synthesis engine. Simultaneously, the server generates multilingual subtitles and integrates them into the scenario.

[0051] Step 4:

[0052] The server adds interactive elements to the video content. Specifically, it embeds quizzes and real-time feedback features at appropriate points within the video.

[0053] Step 5:

[0054] The completed educational content is streamed from the server to the user's device. Users can view the content on their device and answer the provided quizzes.

[0055] Step 6:

[0056] The server tracks the user's learning progress and creates personalized feedback based on the collected data. This feedback is delivered to the user's device, allowing them to check their progress.

[0057] (Example 1)

[0058] 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."

[0059] In the modern field of education, it is difficult to quickly provide content that meets the diverse needs of learners. Furthermore, preparing educational materials that accommodate different languages ​​and cultures requires considerable effort and time. Moreover, providing individualized feedback tailored to each learner's progress requires advanced technology, and traditional methods are insufficient to address these challenges.

[0060] 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.

[0061] In this invention, the server includes means for automatically generating educational material scenarios using artificial intelligence, means for automatically generating audio output and text display based on the generated scenarios, and means for inserting interactive questions and responses into the audiovisual material. This enables rapid generation of educational content, multilingual support, and the provision of individualized feedback according to the learner's progress.

[0062] Artificial intelligence is a technology that gives computers the ability to learn and make decisions like humans.

[0063] "Educational materials" are content designed to help learners acquire specific skills or knowledge.

[0064] A "scenario" is a plan or storyline that defines the content and structure of educational materials.

[0065] "Audio output" is a technology that plays back synthesized audio based on a generated scenario.

[0066] "Text display" refers to text that is displayed on the screen to support the content of the audio output.

[0067] "Audiovisual materials" refer to educational videos and audio content.

[0068] "Interactive questions" are a type of learning content in which learners can choose or write their own answers.

[0069] A "response" is a reaction or feedback provided based on the learner's input in an interactive problem.

[0070] "Progress" refers to the extent to which learners have made progress in their learning through educational materials.

[0071] "Individualized feedback" is a function that provides specific improvement suggestions and evaluations tailored to the progress of each individual learner.

[0072] A "generative AI model" is an artificial intelligence model that has the ability to learn patterns from data and generate new data.

[0073] This invention is an educational content creation system that utilizes artificial intelligence. The system primarily consists of a server, a user terminal, and user operation. The server is the main hardware for executing programs and generates educational materials using a generative AI model. This system is capable of quickly responding to diverse educational needs.

[0074] Users can access the server via the internet using their device and log in to begin using the system. These devices include typical personal computers, tablets, or smartphones. After logging in, users can select options such as "Create a New Video" or "Take a Training Module" according to their learning objectives.

[0075] Based on user selections, the server initiates scenario generation using a generative AI model. This process collects and analyzes large amounts of data to create appropriate educational materials. For example, when creating training content for the medical field, scenarios incorporating essential knowledge and procedures are automatically constructed.

[0076] Next, the program uses AI speech synthesis technology to generate speech output and multilingual text display. This feature makes it compatible with users who speak different languages. Furthermore, the server incorporates interactive questions and response elements into the video content, creating an environment where users can actively participate in learning.

[0077] As a concrete example, consider a case where an elementary school teacher wants to create content for use in a natural science lesson. In this case, the user selects "Create New Video" and enters the prompt "Natural Science for Elementary School Students." Based on this information, the server creates an appropriate educational scenario and provides interactive educational content.

[0078] Example of a prompt:

[0079] "I'm creating science lesson content for elementary school students. The theme is the growth process of plants and the necessary conditions for growth. I want to include interactive quizzes to check students' understanding."

[0080] In this way, this system enables companies and educational institutions to provide educational content quickly and flexibly, and learners to acquire knowledge at their own pace.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The user accesses the system using a terminal and goes to the login screen. They enter their login information (user ID and password) and press the login button. The terminal sends this information to the server, which accesses the database to verify the authentication information. If the authentication is successful, the server returns an authentication success message to the terminal.

[0084] Step 2:

[0085] The user selects either "Create New Video" or "Take Training Module" from the menu screen on their device. The device sends this selection information to the server. The server prepares to start the appropriate process based on the user's selection.

[0086] Step 3:

[0087] Based on the selection information received from the user, the server begins generating scenarios using a generative AI model. A prompt provided by the user (e.g., "Natural Science for Elementary School Students") is given as input, and the server retrieves relevant knowledge data from the database to generate the optimal educational scenario. This generated scenario is then output.

[0088] Step 4:

[0089] The server generates speech output using AI speech synthesis technology based on the generated scenario. During this process, the scenario data is used as input, and an audio file is created. Simultaneously, multilingual text display data is also generated and output.

[0090] Step 5:

[0091] The server adds interactive elements (questions and feedback) to the generated audio and text data. Interactive elements, including quizzes and response options designed to encourage learner participation, are incorporated into the scenario, and the introduced interactive material becomes the output.

[0092] Step 6:

[0093] The server delivers the completed video content to the user's device via streaming. The device receives the stream in real time, and the user can watch the video. This completes the delivery of the educational content.

[0094] Step 7:

[0095] The server monitors the user's learning progress and uses the collected data to provide personalized feedback. The user's learning log is analyzed as input, and progress reports and suggestions for additional learning are output and displayed on the terminal.

[0096] (Application Example 1)

[0097] 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."

[0098] Traditional educational content systems have challenges in providing education tailored to specific situations in real time, and in providing immediate feedback based on the user's current progress. Furthermore, when supporting multiple languages, generating subtitles and other elements takes time, reducing usability. As a result, it has been difficult to create an environment where learners can learn optimally at their own pace.

[0099] 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.

[0100] In this invention, the server includes means for automatically generating an order of educational information using artificial intelligence, means for automatically generating voice guidance and text information based on the generated order, and means for transmitting the information in real time through a portable visual device. This enables learners to instantly receive optimal educational information on-site or while on the go.

[0101] "A means of automatically generating the order of educational information using artificial intelligence" refers to a function in which a program automatically determines the optimal order in which educational information is presented based on the learner's needs.

[0102] "Means for automatically generating audio guidance and text information based on the generated order" refers to a function that automatically creates audio explanations and corresponding subtitles in accordance with the determined order of educational information.

[0103] "Means of inserting interactive questions and assessments into informational content" refers to the function of incorporating quiz-style questions and immediate comprehension checks for learners into educational information.

[0104] "Means for tracking learner progress and providing individualized assessments" refers to a function that uses a system to measure how much information learners understand and remember, and then provides specific feedback and assessments based on that measurement.

[0105] "Means of transmitting information in real time through portable visual devices" refers to systems that use portable devices such as smart glasses to instantly deliver educational information to learners.

[0106] The system for implementing this invention mainly consists of a server, a user's visual device terminal, and a set of related programs. The server first uses artificial intelligence technology to automatically generate an order of information suitable for educational purposes based on the user's input data. Subsequently, it generates narration using speech synthesis technology and automatically generates text information according to the generated order of information. This makes it possible to create narration and subtitles that support multiple languages.

[0107] The server further incorporates interactive questions and assessments into the educational information. This allows the information presented to learners to include quizzes and real-time feedback to check their understanding. Each learner's progress is monitored by the server, and personalized feedback is generated. As a result, supplementary learning and additional suggestions are tailored to each learner, maximizing learning effectiveness.

[0108] Information is delivered to the user using a portable visual device, such as smart glasses. This device receives streaming data from a server and supports the user's educational experience on-site or while on the go. For example, at a construction site, users can watch educational videos on safety measures and take quizzes to check their understanding.

[0109] A concrete example of a prompt statement is, "Provide real-time explanations of safety measures at construction sites and generate content that includes a quiz to measure understanding." By using such prompt statements, the server can efficiently generate optimized educational scenarios and corresponding content.

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] The server analyzes educational input data received from the user. This input data includes, for example, learning subjects and learning levels. Based on the analysis results, a generative AI model is used to determine the optimal order of information. The input is the user's requested data, and the output is the order of the educational information.

[0113] Step 2:

[0114] The server automatically generates narration using speech synthesis technology based on the order of the generated information. AI speech synthesis software generates audio files on demand and converts them into a format for providing the narration. The input is the information order and text data, which are the output of step 1, and the output is an audio file.

[0115] Step 3:

[0116] The server generates multilingual subtitles using an AI model. This involves translating text into multiple languages ​​based on information order. The input is the information order output from step 1, and the output is subtitle files for each language.

[0117] Step 4:

[0118] The server inserts interactive questions and assessments into the generated information content. Based on the information submitted by the user, it designs quiz-style questions and integrates them into the system. This allows for real-time monitoring of the learner's understanding. The input is the information sequence from Step 1, and the output is information content with interactive quizzes.

[0119] Step 5:

[0120] The device streams completed educational content to the user via a portable visual device. Streaming technology is used to process data from the server in real time and deliver it to the user. The input is content data from the server, and the output is educational information displayed on the user's visual device.

[0121] Step 6:

[0122] Users experience educational content displayed through a visual device and answer interactive quizzes. The user's response data is sent back to the server for evaluation of their progress and understanding. Inputs are the educational content displayed on the visual device and user feedback data, while output is evaluation data sent to the server.

[0123] 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.

[0124] This invention integrates an emotion engine into an AI-powered educational content creation system to recognize user emotions and optimize the learning experience. This enables personalized education tailored to the needs of each learner.

[0125] This system consists of a server, a user terminal, and an emotion engine. Users first log in to the system via their terminal and select to create a video or take a training module. The selected information is then sent to the server by the terminal.

[0126] Based on the information received, the server uses artificial intelligence to automatically generate scenarios for educational content. In this process, relevant data is retrieved from a database, and a scenario aligned with the selected topic is formed. Based on the formed scenario, the server creates voice narration using AI speech synthesis and generates subtitles in multiple languages.

[0127] Furthermore, interactive elements will be added to the video content. Specifically, these will include quizzes to assess the user's understanding and real-time feedback features. These features will deepen the user's understanding during learning and make the content more meaningful.

[0128] This is where the emotion engine, a key feature of the present invention, comes into play. While the user is watching a video, the emotion engine analyzes the user's facial expressions and voice through the device's camera and sensors, recognizing emotions in real time. This recognition result is sent to a server and used to adjust the difficulty level of the content and the content of the feedback. For example, if the user is confused, the system can adjust by simplifying the explanation of the content or providing supplementary information.

[0129] Users can view this customized content and participate in interactive elements as needed. As learning progresses, the server records progress and provides personalized feedback based on the collected data. This allows learners to deepen their learning at their own pace, maximizing educational effectiveness.

[0130] In this way, the present invention can significantly improve the user's learning experience by incorporating emotion recognition using an emotion engine. As a result, companies and educational institutions can provide personalized learning environments to diverse learners.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] The user logs into the system using their device. They select either "Create a video" or "Take a training module" from the available options. The selected information is sent from the device to the server.

[0134] Step 2:

[0135] Based on the received selection information, the server automatically generates relevant educational content scenarios using artificial intelligence. In this process, the server retrieves necessary information from the database and determines the content and structure of the scenarios.

[0136] Step 3:

[0137] Based on the generated scenario, the server automatically produces voice narration using an AI speech synthesis engine. Simultaneously, the server generates subtitles in various languages ​​and integrates them into the educational content.

[0138] Step 4:

[0139] The emotion engine analyzes the user's facial expressions and voice in real time through the device's camera and microphone. The server receives this analysis data and recognizes the user's emotional state.

[0140] Step 5:

[0141] Based on the user's emotions, the server adjusts the educational content and feedback. For example, if the user is confused, the server provides additional supplementary information or an alternative explanation approach.

[0142] Step 6:

[0143] Interactive elements (e.g., quizzes and feedback features) are integrated into the content by the server. Users participate in these through their devices, deepening their learning experience.

[0144] Step 7:

[0145] The server tracks the progress of the entire learning session and assesses how well the user understands the content. Using the collected data, the server generates personalized feedback and provides it to the user through the device.

[0146] (Example 2)

[0147] 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".

[0148] There is a challenge in providing efficient and effective education while responding to the diverse needs of learners. In particular, there is a need for individualized support based on each learner's feelings and level of understanding, but conventional systems have found it difficult to make flexible adjustments accordingly.

[0149] 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.

[0150] In this invention, the server includes means for automatically generating a plan of educational information using artificial intelligence, means for automatically generating audio commentary and multilingual subtitles based on the generated plan, and means for recognizing the user's emotions in real time during learning and adjusting the educational content accordingly. This enables the provision of personalized and efficient education tailored to the diverse needs of learners.

[0151] Artificial intelligence is a technology that can automatically perform specific tasks by analyzing and learning from data.

[0152] An "educational information plan" is a set of guidelines and scripts for structuring the content and activities necessary to achieve specific educational goals for learners.

[0153] "Audio commentary" refers to educational information explained through audio, serving as a supplementary tool to help learners understand the material more easily.

[0154] "Multilingual subtitles" are text displayed in multiple languages, complementing audio explanations and video content, and providing visual support to learners.

[0155] "Interactive questions" are problems or questions presented in an interactive format with the user to assess whether the learner understands the learning material.

[0156] "Immediate response" refers to feedback and assessment provided quickly based on the learner's input and actions.

[0157] "Progress tracking" refers to the system tracking and saving the learner's progress and achievements as they progress through their learning process.

[0158] "Individualized feedback" refers to specific suggestions and advice provided based on each learner's individual learning situation and needs.

[0159] "Real-time emotional recognition" is a technology that analyzes a learner's facial expressions, tone of voice, etc., to instantly grasp their current emotional state.

[0160] "Adjusting educational content" means optimizing the difficulty level and methods of educational information according to the learner's level of understanding and emotions.

[0161] This invention is a system that utilizes artificial intelligence to provide users with personalized educational experiences. The system mainly consists of a server, a user terminal, and an emotion recognition engine.

[0162] First, the user logs into the system using their device and selects whether to create or take educational content. This selection information is sent from the device to the server. The server receives this information and uses a generative AI model to automatically generate a plan for the relevant educational content. For example, it might use the prompt "Generate a video scenario that explains environmental issues in an easy-to-understand way."

[0163] Based on the generated plan, the server uses AI-powered speech synthesis technology to create audio commentary and also generates multilingual subtitles. The latest technology is employed for both speech synthesis and subtitle generation. Users then view the generated content on their devices.

[0164] The videos include interactive elements such as two-way questions and real-time responses to deepen user understanding. During learning, the device's camera and sensors analyze the user's facial expressions and voice in real time, and an emotion recognition engine analyzes the user's emotional state. This analysis is sent to a server and used to adjust the difficulty level of the educational information and the content of the feedback. For example, if the server determines that the user is confused, it will provide a simpler explanation.

[0165] In this way, embodiments of the present invention can provide deep learning effects and realize personalized educational experiences that meet diverse needs. The flexible design of the system allows educational institutions and companies to provide the optimal learning environment for each learner.

[0166] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0167] Step 1:

[0168] The user logs into the system using a terminal. The user enters their username and password. The terminal verifies this information against the database, and if authentication is successful, grants access. The output indicates that a login session has started.

[0169] Step 2:

[0170] The user selects whether to create or take educational content through the terminal's interface. The user's selection information becomes input data, and the terminal packets this information and sends it to the server. The selected data arrives at the server as output.

[0171] Step 3:

[0172] The server uses a generation AI model based on the received selection information to automatically generate a plan for educational information. Specifically, it uses the prompt "Generate a video scenario that explains environmental issues in an easy-to-understand way" to have the model perform data calculations. The output is the generated educational scenario.

[0173] Step 4:

[0174] The server uses AI speech synthesis technology to create audio commentary based on the generated educational scenarios and also generates multilingual subtitles. This process utilizes a speech synthesis engine and subtitle generation software. The output consists of audio files and subtitle data.

[0175] Step 5:

[0176] The server generates interactive educational videos that include audio commentary and multilingual subtitles, and sends them to the user's terminal. The videos include interactive questions and real-time response functions to deepen the user's understanding. As output, the interactive video data is delivered to the user's terminal.

[0177] Step 6:

[0178] Users watch videos through their devices and participate in interactive elements. The device uses cameras and sensors to analyze the user's facial expressions and voice in real time, and obtains emotion recognition results. As output, data regarding the user's emotions and level of understanding is generated.

[0179] Step 7:

[0180] The server receives user sentiment data and adjusts the difficulty level and content of educational information. Specifically, it supplements or simplifies explanations based on the analysis results from the sentiment engine. The output is the adjusted feedback content.

[0181] Step 8:

[0182] Users view tailored content and progress through the learning process. Their device records their progress and sends it to the server. The server then provides personalized feedback based on the collected data. The output is feedback based on the final learning outcome.

[0183] (Application Example 2)

[0184] 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".

[0185] Conventional educational content creation systems have struggled to adjust content in real time based on learners' emotions and comprehension levels, making it impossible to provide personalized learning experiences. Furthermore, while there is a need for immediate multilingual support in environments where learners use multiple languages, there has been a lack of effective means to achieve this.

[0186] 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.

[0187] In this invention, the server includes means for automatically generating educational content plans using artificial intelligence, means for automatically generating voice guidance and subtitles based on the generated plans, means for inserting interactive questions and responses into video information, means for tracking learners' progress and providing individualized responses, and means for recognizing user emotions and adjusting the difficulty level and content of the content in real time. This enables the provision of personalized learning experiences that respond to learners' emotions and real-time multilingual support in diverse language environments.

[0188] "Artificial intelligence" refers to the technology in which computer systems perform intelligent tasks and mimic human judgment and learning abilities.

[0189] "Educational content" is a collection of information and materials designed to provide learners with knowledge and skills.

[0190] A "plan" is a detailed outline created to direct a series of actions or activities toward a specific objective.

[0191] "Voice guidance" refers to instructions or data generated to convey information using voice.

[0192] Subtitles are visually displayed textual information, typically provided to complement audio content.

[0193] "Video information" refers to dynamic digital recordings that include both video and audio.

[0194] A "problem" is a task or question that learners should attempt to solve in order to measure their understanding.

[0195] A "response" is a solution or answer to a problem or question that has been presented.

[0196] "Progress" refers to the current situation or level of achievement in a particular activity or learning process.

[0197] "Emotion" refers to the psychological response a person shows to a particular situation or information, and encompasses a wide range of mental states.

[0198] This invention is a system for providing personalized educational content, incorporating a server, a user terminal, and an emotion recognition engine. The server automatically generates educational content plans using artificial intelligence. Based on information from the user terminal, the server generates voice guidance and subtitles, and has the function of inserting interactive questions and responses into video information. Furthermore, the server tracks the learner's progress and provides individualized responses.

[0199] The user terminal has the capability to capture video and audio, capturing the user's facial expressions through the camera and transmitting them to the emotion recognition engine. The emotion recognition engine analyzes the user's emotions in real time and provides this data to the server. This allows the server to adjust the difficulty level and content of the content in a timely manner based on the user's emotions.

[0200] The software used includes OpenCV, which is utilized for image processing. It also implements a proprietary algorithm for detecting emotional patterns. The system aims to enhance user immersion and maximize individual learning effectiveness.

[0201] For example, if a user shows signs of confusion while learning calculus, the emotion recognition engine will detect this, and the server will immediately adjust the content to simplify the explanation and provide supplementary diagrams.

[0202] An example of a prompt used with a generative AI model is, "If the user is confused by difficult content, please suggest specific ways in which the content can be simplified." This allows for timely support for user comprehension and provides a more meaningful learning experience for learners.

[0203] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0204] Step 1:

[0205] The server receives login information from the user's terminal and waits for the user to select learning content. Once the user selects a training module, the server uses artificial intelligence to generate a content plan based on that information. The input is the selected topic, and the output is the generated content plan.

[0206] Step 2:

[0207] The server automatically generates audio guidance and multilingual subtitles based on the generated content plan. The input is the content plan, and the output is audio guidance data and subtitle data. The data is processed using speech synthesis software and a subtitle generation algorithm.

[0208] Step 3:

[0209] The server inserts interactive questions and responses into the content, allowing users to react to the questions and making the learning experience interactive. The input is the content plan, and the output is content containing interactive questions.

[0210] Step 4:

[0211] The user device collects video and audio data during learning. The device's camera captures the user's facial expressions. The input is a real-time video feed, and the output is captured image data.

[0212] Step 5:

[0213] The user terminal sends captured image data to an emotion recognition engine, where the user's emotions are analyzed. The input is image data, and the output is recognized emotion information. The data is analyzed using an emotion recognition algorithm.

[0214] Step 6:

[0215] The server adjusts the difficulty and content of the material in real time based on recognized sentiment information. For example, if a user is confused, the server simplifies the content or provides supplementary information. The input is sentiment information, and the output is the adjusted content.

[0216] Step 7:

[0217] As the user progresses through the learning process, the server tracks their progress and provides timely, personalized feedback. The input is learning history data, and the output is feedback data. The server analyzes the user's proficiency and processes the data to suggest the next learning steps.

[0218] Through this processing flow, users can obtain a more personalized educational experience.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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".

[0235] This invention relates to an educational content creation system utilizing artificial intelligence, and its embodiments are described in detail. This system consists of a server, a user terminal, and user operations, and is capable of quickly responding to diverse educational needs.

[0236] First, the user accesses the system using their device and logs in. The user can then choose either "Create a New Video" or "Take a Training Module," depending on their purpose. Based on the selected purpose, the device sends relevant information to the server.

[0237] The server receives the user's selection and first uses artificial intelligence to automatically generate appropriate educational content scenarios. In this scenario generation process, relevant information is retrieved from a database to determine the optimal configuration for the purpose. For example, if the purpose is medical training, a scenario including the necessary knowledge and procedures will be designed.

[0238] Next, based on the generated scenario, the server automatically creates voice narration using AI speech synthesis technology and also generates multilingual subtitles. This process enables the creation of effective educational content that transcends language barriers.

[0239] The server then adds interactive elements to the video content. Specifically, these include quizzes to assess the learner's understanding and feedback features that allow for immediate confirmation of learning effectiveness. Such features help reinforce learning and promote effective learning.

[0240] The completed video content is streamed to the user's device by the server. Users can track their progress in real time, and personalized feedback is provided from the server based on the collected data. For example, additional learning is suggested according to the learning progress, and necessary knowledge reinforcement is supported.

[0241] This system allows companies and educational institutions to deliver educational content quickly and flexibly, and enables learners to acquire knowledge at their own pace. As a result, an educational environment is created that efficiently improves skills and knowledge.

[0242] The following describes the processing flow.

[0243] Step 1:

[0244] The user logs into the device and selects an option to create educational content or take a training module. The device then sends the user's selection information to the server.

[0245] Step 2:

[0246] Based on the received selection information, the server automatically generates relevant educational content scenarios using artificial intelligence. Here, the server retrieves necessary information from the database and determines the structure of the scenario.

[0247] Step 3:

[0248] The server uses the generated scenario to create narration using an AI speech synthesis engine. Simultaneously, the server generates multilingual subtitles and integrates them into the scenario.

[0249] Step 4:

[0250] The server adds interactive elements to the video content. Specifically, it embeds quizzes and real-time feedback features at appropriate points within the video.

[0251] Step 5:

[0252] The completed educational content is streamed from the server to the user's device. Users can view the content on their device and answer the provided quizzes.

[0253] Step 6:

[0254] The server tracks the user's learning progress and creates personalized feedback based on the collected data. This feedback is delivered to the user's device, allowing them to check their progress.

[0255] (Example 1)

[0256] 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."

[0257] In the modern field of education, it is difficult to quickly provide content that meets the diverse needs of learners. Furthermore, preparing educational materials that accommodate different languages ​​and cultures requires considerable effort and time. Moreover, providing individualized feedback tailored to each learner's progress requires advanced technology, and traditional methods are insufficient to address these challenges.

[0258] 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.

[0259] In this invention, the server includes means for automatically generating educational material scenarios using artificial intelligence, means for automatically generating audio output and text display based on the generated scenarios, and means for inserting interactive questions and responses into the audiovisual material. This enables rapid generation of educational content, multilingual support, and the provision of individualized feedback according to the learner's progress.

[0260] Artificial intelligence is a technology that gives computers the ability to learn and make decisions like humans.

[0261] "Educational materials" are content designed to help learners acquire specific skills or knowledge.

[0262] A "scenario" is a plan or storyline that defines the content and structure of educational materials.

[0263] "Audio output" is a technology that plays back synthesized audio based on a generated scenario.

[0264] "Text display" refers to text that is displayed on the screen to support the content of the audio output.

[0265] "Audiovisual materials" refer to educational videos and audio content.

[0266] "Interactive questions" are a type of learning content in which learners can choose or write their own answers.

[0267] A "response" is a reaction or feedback provided based on the learner's input in an interactive problem.

[0268] "Progress" refers to the extent to which learners have made progress in their learning through educational materials.

[0269] "Individualized feedback" is a function that provides specific improvement suggestions and evaluations tailored to the progress of each individual learner.

[0270] A "generative AI model" is an artificial intelligence model that has the ability to learn patterns from data and generate new data.

[0271] This invention is an educational content creation system that utilizes artificial intelligence. The system primarily consists of a server, a user terminal, and user operation. The server is the main hardware for executing programs and generates educational materials using a generative AI model. This system is capable of quickly responding to diverse educational needs.

[0272] Users can access the server via the internet using their device and log in to begin using the system. These devices include typical personal computers, tablets, or smartphones. After logging in, users can select options such as "Create a New Video" or "Take a Training Module" according to their learning objectives.

[0273] Based on user selections, the server initiates scenario generation using a generative AI model. This process collects and analyzes large amounts of data to create appropriate educational materials. For example, when creating training content for the medical field, scenarios incorporating essential knowledge and procedures are automatically constructed.

[0274] Next, the program uses AI speech synthesis technology to generate speech output and multilingual text display. This feature makes it compatible with users who speak different languages. Furthermore, the server incorporates interactive questions and response elements into the video content, creating an environment where users can actively participate in learning.

[0275] As a concrete example, consider a case where an elementary school teacher wants to create content for use in a natural science lesson. In this case, the user selects "Create New Video" and enters the prompt "Natural Science for Elementary School Students." Based on this information, the server creates an appropriate educational scenario and provides interactive educational content.

[0276] Example of a prompt:

[0277] "I'm creating science lesson content for elementary school students. The theme is the growth process of plants and the necessary conditions for growth. I want to include interactive quizzes to check students' understanding."

[0278] In this way, this system enables companies and educational institutions to provide educational content quickly and flexibly, and learners to acquire knowledge at their own pace.

[0279] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0280] Step 1:

[0281] The user accesses the system using a terminal and goes to the login screen. They enter their login information (user ID and password) and press the login button. The terminal sends this information to the server, which accesses the database to verify the authentication information. If the authentication is successful, the server returns an authentication success message to the terminal.

[0282] Step 2:

[0283] The user selects "Create New Video" or "Take Training Module" from the menu screen on the terminal. The terminal sends this selection information to the server. The server prepares to start an appropriate process based on the user's selection.

[0284] Step 3:

[0285] Based on the selection information received from the user, the server starts scenario generation using the generative AI model. The prompt text provided by the user (e.g., "Natural Science for Elementary Schools") is given as input, and the server retrieves relevant knowledge data from the database and generates an optimal educational scenario. This generated scenario is output.

[0286] Step 4:

[0287] Based on the generated scenario, the server generates voice output using AI voice synthesis technology. At this time, the scenario data is used as input, and an audio file is created. At the same time, character display data supporting multiple languages is also generated and output.

[0288] Step 5:

[0289] The server adds interactive elements (questions and feedback) to the generated voice and character data. Interactive elements including quizzes and response options that encourage learners' participation are incorporated into the scenario, and the introduced interactive materials are output.

[0290] Step 6:

[0291] The server distributes the completed video content to the user's terminal in streaming format. The terminal receives the streaming in real time, and the user can watch the video. Thus, the provision of educational content is completed.

[0292] Step 7:

[0293] The server monitors the user's learning progress and uses the collected data to provide personalized feedback. The user's learning log is analyzed as input, and progress reports and suggestions for additional learning are output and displayed on the terminal.

[0294] (Application Example 1)

[0295] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0296] Traditional educational content systems have challenges in providing education tailored to specific situations in real time, and in providing immediate feedback based on the user's current progress. Furthermore, when supporting multiple languages, generating subtitles and other elements takes time, reducing usability. As a result, it has been difficult to create an environment where learners can learn optimally at their own pace.

[0297] 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.

[0298] In this invention, the server includes means for automatically generating an order of educational information using artificial intelligence, means for automatically generating voice guidance and text information based on the generated order, and means for transmitting the information in real time through a portable visual device. This enables learners to instantly receive optimal educational information on-site or while on the go.

[0299] "A means of automatically generating the order of educational information using artificial intelligence" refers to a function in which a program automatically determines the optimal order in which educational information is presented based on the learner's needs.

[0300] "Means for automatically generating audio guidance and text information based on the generated order" refers to a function that automatically creates audio explanations and corresponding subtitles in accordance with the determined order of educational information.

[0301] "Means of inserting interactive questions and assessments into informational content" refers to the function of incorporating quiz-style questions and immediate comprehension checks for learners into educational information.

[0302] "Means for tracking learner progress and providing individualized assessments" refers to a function that uses a system to measure how much information learners understand and remember, and then provides specific feedback and assessments based on that measurement.

[0303] "Means of transmitting information in real time through portable visual devices" refers to systems that use portable devices such as smart glasses to instantly deliver educational information to learners.

[0304] The system for implementing this invention mainly consists of a server, a user's visual device terminal, and a set of related programs. The server first uses artificial intelligence technology to automatically generate an order of information suitable for educational purposes based on the user's input data. Subsequently, it generates narration using speech synthesis technology and automatically generates text information according to the generated order of information. This makes it possible to create narration and subtitles that support multiple languages.

[0305] The server further incorporates interactive questions and assessments into the educational information. This allows the information presented to learners to include quizzes and real-time feedback to check their understanding. Each learner's progress is monitored by the server, and personalized feedback is generated. As a result, supplementary learning and additional suggestions are tailored to each learner, maximizing learning effectiveness.

[0306] Information is delivered to the user using a portable visual device, such as smart glasses. This device receives streaming data from a server and supports the user's educational experience on-site or while on the go. For example, at a construction site, users can watch educational videos on safety measures and take quizzes to check their understanding.

[0307] As a specific example of a prompt sentence, "Generate content that explains safety measures at a construction site in real time and includes quizzes to measure the level of understanding" can be cited. By using such a prompt sentence, the server can efficiently generate optimized educational scenarios and corresponding content.

[0308] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0309] Step 1:

[0310] The server analyzes the input data for educational purposes received from the user. This input data includes, for example, the learning field and learning level. Based on the analysis result, the generation AI model is used to determine the optimal order of information. The input is the user's request data, and the output is the order of educational information.

[0311] Step 2:

[0312] The server automatically generates a narration using voice synthesis technology based on the order of the generated information. The AI voice synthesis software generates an audio file according to the order and converts it into a format for providing the narration. The input is the order of information and text data, which is the output of Step 1, and the output is the audio file.

[0313] Step 3:

[0314] The server creates multilingual subtitles using the generation AI model. This includes the process of translating the text based on the order of information into multiple languages. The input is the order of information output in Step 1, and the output is the subtitle files in each language.

[0315] Step 4:

[0316] The server inserts interactive questions and assessments into the generated information content. Based on the information submitted by the user, it designs quiz-style questions and integrates them into the system. This allows for real-time monitoring of the learner's understanding. The input is the information sequence from Step 1, and the output is information content with interactive quizzes.

[0317] Step 5:

[0318] The device streams completed educational content to the user via a portable visual device. Streaming technology is used to process data from the server in real time and deliver it to the user. The input is content data from the server, and the output is educational information displayed on the user's visual device.

[0319] Step 6:

[0320] Users experience educational content displayed through a visual device and answer interactive quizzes. The user's response data is sent back to the server for evaluation of their progress and understanding. Inputs are the educational content displayed on the visual device and user feedback data, while output is evaluation data sent to the server.

[0321] 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.

[0322] This invention integrates an emotion engine into an AI-powered educational content creation system to recognize user emotions and optimize the learning experience. This enables personalized education tailored to the needs of each learner.

[0323] This system consists of a server, a user terminal, and an emotion engine. Users first log in to the system via their terminal and select to create a video or take a training module. The selected information is then sent to the server by the terminal.

[0324] Based on the information received, the server uses artificial intelligence to automatically generate scenarios for educational content. In this process, relevant data is retrieved from a database, and a scenario aligned with the selected topic is formed. Based on the formed scenario, the server creates voice narration using AI speech synthesis and generates subtitles in multiple languages.

[0325] Furthermore, interactive elements will be added to the video content. Specifically, these will include quizzes to assess the user's understanding and real-time feedback features. These features will deepen the user's understanding during learning and make the content more meaningful.

[0326] This is where the emotion engine, a key feature of the present invention, comes into play. While the user is watching a video, the emotion engine analyzes the user's facial expressions and voice through the device's camera and sensors, recognizing emotions in real time. This recognition result is sent to a server and used to adjust the difficulty level of the content and the content of the feedback. For example, if the user is confused, the system can adjust by simplifying the explanation of the content or providing supplementary information.

[0327] Users can view this customized content and participate in interactive elements as needed. As learning progresses, the server records progress and provides personalized feedback based on the collected data. This allows learners to deepen their learning at their own pace, maximizing educational effectiveness.

[0328] In this way, the present invention can significantly improve the user's learning experience by incorporating emotion recognition using an emotion engine. As a result, companies and educational institutions can provide personalized learning environments to diverse learners.

[0329] The following describes the processing flow.

[0330] Step 1:

[0331] The user logs into the system using their device. They select either "Create a video" or "Take a training module" from the available options. The selected information is sent from the device to the server.

[0332] Step 2:

[0333] Based on the received selection information, the server automatically generates relevant educational content scenarios using artificial intelligence. In this process, the server retrieves necessary information from the database and determines the content and structure of the scenarios.

[0334] Step 3:

[0335] Based on the generated scenario, the server automatically produces voice narration using an AI speech synthesis engine. Simultaneously, the server generates subtitles in various languages ​​and integrates them into the educational content.

[0336] Step 4:

[0337] The emotion engine analyzes the user's facial expressions and voice in real time through the device's camera and microphone. The server receives this analysis data and recognizes the user's emotional state.

[0338] Step 5:

[0339] Based on the user's emotions, the server adjusts the educational content and feedback. For example, if the user is confused, the server provides additional supplementary information or an alternative explanation approach.

[0340] Step 6:

[0341] Interactive elements (e.g., quizzes and feedback features) are integrated into the content by the server. Users participate in these through their devices, deepening their learning experience.

[0342] Step 7:

[0343] The server tracks the progress of the entire learning session and assesses how well the user understands the content. Using the collected data, the server generates personalized feedback and provides it to the user through the device.

[0344] (Example 2)

[0345] 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".

[0346] There is a challenge in providing efficient and effective education while responding to the diverse needs of learners. In particular, there is a need for individualized support based on each learner's feelings and level of understanding, but conventional systems have found it difficult to make flexible adjustments accordingly.

[0347] 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.

[0348] In this invention, the server includes means for automatically generating a plan of educational information using artificial intelligence, means for automatically generating audio commentary and multilingual subtitles based on the generated plan, and means for recognizing the user's emotions in real time during learning and adjusting the educational content accordingly. This enables the provision of personalized and efficient education tailored to the diverse needs of learners.

[0349] Artificial intelligence is a technology that can automatically perform specific tasks by analyzing and learning from data.

[0350] An "educational information plan" is a set of guidelines and scripts for structuring the content and activities necessary to achieve specific educational goals for learners.

[0351] "Audio commentary" refers to educational information explained through audio, serving as a supplementary tool to help learners understand the material more easily.

[0352] "Multilingual subtitles" are text displayed in multiple languages, complementing audio explanations and video content, and providing visual support to learners.

[0353] "Interactive questions" are problems or questions presented in an interactive format with the user to assess whether the learner understands the learning material.

[0354] "Immediate response" refers to feedback and assessment provided quickly based on the learner's input and actions.

[0355] "Progress tracking" refers to the system tracking and saving the learner's progress and achievements as they progress through their learning process.

[0356] "Individualized feedback" refers to specific suggestions and advice provided based on each learner's individual learning situation and needs.

[0357] "Real-time emotional recognition" is a technology that analyzes a learner's facial expressions, tone of voice, etc., to instantly grasp their current emotional state.

[0358] "Adjusting educational content" means optimizing the difficulty level and methods of educational information according to the learner's level of understanding and emotions.

[0359] This invention is a system that utilizes artificial intelligence to provide users with personalized educational experiences. The system mainly consists of a server, a user terminal, and an emotion recognition engine.

[0360] First, the user logs into the system using their device and selects whether to create or take educational content. This selection information is sent from the device to the server. The server receives this information and uses a generative AI model to automatically generate a plan for the relevant educational content. For example, it might use the prompt "Generate a video scenario that explains environmental issues in an easy-to-understand way."

[0361] Based on the generated plan, the server uses AI-powered speech synthesis technology to create audio commentary and also generates multilingual subtitles. The latest technology is employed for both speech synthesis and subtitle generation. Users then view the generated content on their devices.

[0362] The videos include interactive elements such as two-way questions and real-time responses to deepen user understanding. During learning, the device's camera and sensors analyze the user's facial expressions and voice in real time, and an emotion recognition engine analyzes the user's emotional state. This analysis is sent to a server and used to adjust the difficulty level of the educational information and the content of the feedback. For example, if the server determines that the user is confused, it will provide a simpler explanation.

[0363] In this way, embodiments of the present invention can provide deep learning effects and realize personalized educational experiences that meet diverse needs. The flexible design of the system allows educational institutions and companies to provide the optimal learning environment for each learner.

[0364] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0365] Step 1:

[0366] The user logs into the system using a terminal. The user enters their username and password. The terminal verifies this information against the database, and if authentication is successful, grants access. The output indicates that a login session has started.

[0367] Step 2:

[0368] The user selects whether to create or take educational content through the terminal's interface. The user's selection information becomes input data, and the terminal packets this information and sends it to the server. The selected data arrives at the server as output.

[0369] Step 3:

[0370] The server uses a generation AI model based on the received selection information to automatically generate a plan for educational information. Specifically, it uses the prompt "Generate a video scenario that explains environmental issues in an easy-to-understand way" to have the model perform data calculations. The output is the generated educational scenario.

[0371] Step 4:

[0372] The server uses AI speech synthesis technology to create audio commentary based on the generated educational scenarios and also generates multilingual subtitles. This process utilizes a speech synthesis engine and subtitle generation software. The output consists of audio files and subtitle data.

[0373] Step 5:

[0374] The server generates interactive educational videos that include audio commentary and multilingual subtitles, and sends them to the user's terminal. The videos include interactive questions and real-time response functions to deepen the user's understanding. As output, the interactive video data is delivered to the user's terminal.

[0375] Step 6:

[0376] Users watch videos through their devices and participate in interactive elements. The device uses cameras and sensors to analyze the user's facial expressions and voice in real time, and obtains emotion recognition results. As output, data regarding the user's emotions and level of understanding is generated.

[0377] Step 7:

[0378] The server receives user sentiment data and adjusts the difficulty level and content of educational information. Specifically, it supplements or simplifies explanations based on the analysis results from the sentiment engine. The output is the adjusted feedback content.

[0379] Step 8:

[0380] Users view tailored content and progress through the learning process. Their device records their progress and sends it to the server. The server then provides personalized feedback based on the collected data. The output is feedback based on the final learning outcome.

[0381] (Application Example 2)

[0382] 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."

[0383] Conventional educational content creation systems have struggled to adjust content in real time based on learners' emotions and comprehension levels, making it impossible to provide personalized learning experiences. Furthermore, while there is a need for immediate multilingual support in environments where learners use multiple languages, there has been a lack of effective means to achieve this.

[0384] 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.

[0385] In this invention, the server includes means for automatically generating educational content plans using artificial intelligence, means for automatically generating voice guidance and subtitles based on the generated plans, means for inserting interactive questions and responses into video information, means for tracking learners' progress and providing individualized responses, and means for recognizing user emotions and adjusting the difficulty level and content of the content in real time. This enables the provision of personalized learning experiences that respond to learners' emotions and real-time multilingual support in diverse language environments.

[0386] "Artificial intelligence" refers to the technology in which computer systems perform intelligent tasks and mimic human judgment and learning abilities.

[0387] "Educational content" is a collection of information and materials designed to provide learners with knowledge and skills.

[0388] A "plan" is a detailed outline created to direct a series of actions or activities toward a specific objective.

[0389] "Voice guidance" refers to instructions or data generated to convey information using voice.

[0390] Subtitles are visually displayed textual information, typically provided to complement audio content.

[0391] "Video information" refers to dynamic digital recordings that include both video and audio.

[0392] A "problem" is a task or question that learners should attempt to solve in order to measure their understanding.

[0393] A "response" is a solution or answer to a problem or question that has been presented.

[0394] "Progress" refers to the current situation or level of achievement in a particular activity or learning process.

[0395] "Emotion" refers to the psychological response a person shows to a particular situation or information, and encompasses a wide range of mental states.

[0396] This invention is a system for providing personalized educational content, incorporating a server, a user terminal, and an emotion recognition engine. The server automatically generates educational content plans using artificial intelligence. Based on information from the user terminal, the server generates voice guidance and subtitles, and has the function of inserting interactive questions and responses into video information. Furthermore, the server tracks the learner's progress and provides individualized responses.

[0397] The user terminal has the capability to capture video and audio, capturing the user's facial expressions through the camera and transmitting them to the emotion recognition engine. The emotion recognition engine analyzes the user's emotions in real time and provides this data to the server. This allows the server to adjust the difficulty level and content of the content in a timely manner based on the user's emotions.

[0398] The software used includes OpenCV, which is utilized for image processing. It also implements a proprietary algorithm for detecting emotional patterns. The system aims to enhance user immersion and maximize individual learning effectiveness.

[0399] For example, if a user shows signs of confusion while learning calculus, the emotion recognition engine will detect this, and the server will immediately adjust the content to simplify the explanation and provide supplementary diagrams.

[0400] An example of a prompt used with a generative AI model is, "If the user is confused by difficult content, please suggest specific ways in which the content can be simplified." This allows for timely support for user comprehension and provides a more meaningful learning experience for learners.

[0401] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0402] Step 1:

[0403] The server receives login information from the user's terminal and waits for the user to select learning content. Once the user selects a training module, the server uses artificial intelligence to generate a content plan based on that information. The input is the selected topic, and the output is the generated content plan.

[0404] Step 2:

[0405] The server automatically generates audio guidance and multilingual subtitles based on the generated content plan. The input is the content plan, and the output is audio guidance data and subtitle data. The data is processed using speech synthesis software and a subtitle generation algorithm.

[0406] Step 3:

[0407] The server inserts interactive questions and responses into the content, allowing users to react to the questions and making the learning experience interactive. The input is the content plan, and the output is content containing interactive questions.

[0408] Step 4:

[0409] The user device collects video and audio data during learning. The device's camera captures the user's facial expressions. The input is a real-time video feed, and the output is captured image data.

[0410] Step 5:

[0411] The user terminal sends captured image data to an emotion recognition engine, where the user's emotions are analyzed. The input is image data, and the output is recognized emotion information. The data is analyzed using an emotion recognition algorithm.

[0412] Step 6:

[0413] The server adjusts the difficulty and content of the material in real time based on recognized sentiment information. For example, if a user is confused, the server simplifies the content or provides supplementary information. The input is sentiment information, and the output is the adjusted content.

[0414] Step 7:

[0415] As the user progresses through the learning process, the server tracks their progress and provides timely, personalized feedback. The input is learning history data, and the output is feedback data. The server analyzes the user's proficiency and processes the data to suggest the next learning steps.

[0416] Through this processing flow, users can obtain a more personalized educational experience.

[0417] 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.

[0418] 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.

[0419] 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.

[0420] [Third Embodiment]

[0421] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0422] 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.

[0423] 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).

[0424] 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.

[0425] 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.

[0426] 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).

[0427] 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.

[0428] 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.

[0429] 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.

[0430] 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.

[0431] 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.

[0432] 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".

[0433] This invention relates to an educational content creation system utilizing artificial intelligence, and its embodiments are described in detail. This system consists of a server, a user terminal, and user operations, and is capable of quickly responding to diverse educational needs.

[0434] First, the user accesses the system using their device and logs in. The user can then choose either "Create a New Video" or "Take a Training Module," depending on their purpose. Based on the selected purpose, the device sends relevant information to the server.

[0435] The server receives the user's selection and first uses artificial intelligence to automatically generate appropriate educational content scenarios. In this scenario generation process, relevant information is retrieved from a database to determine the optimal configuration for the purpose. For example, if the purpose is medical training, a scenario including the necessary knowledge and procedures will be designed.

[0436] Next, based on the generated scenario, the server automatically creates voice narration using AI speech synthesis technology and also generates multilingual subtitles. This process enables the creation of effective educational content that transcends language barriers.

[0437] The server then adds interactive elements to the video content. Specifically, these include quizzes to assess the learner's understanding and feedback features that allow for immediate confirmation of learning effectiveness. Such features help reinforce learning and promote effective learning.

[0438] The completed video content is streamed to the user's device by the server. Users can track their progress in real time, and personalized feedback is provided from the server based on the collected data. For example, additional learning is suggested according to the learning progress, and necessary knowledge reinforcement is supported.

[0439] This system allows companies and educational institutions to deliver educational content quickly and flexibly, and enables learners to acquire knowledge at their own pace. As a result, an educational environment is created that efficiently improves skills and knowledge.

[0440] The following describes the processing flow.

[0441] Step 1:

[0442] The user logs into the device and selects an option to create educational content or take a training module. The device then sends the user's selection information to the server.

[0443] Step 2:

[0444] Based on the received selection information, the server automatically generates relevant educational content scenarios using artificial intelligence. Here, the server retrieves necessary information from the database and determines the structure of the scenario.

[0445] Step 3:

[0446] The server uses the generated scenario to create narration using an AI speech synthesis engine. Simultaneously, the server generates multilingual subtitles and integrates them into the scenario.

[0447] Step 4:

[0448] The server adds interactive elements to the video content. Specifically, it embeds quizzes and real-time feedback features at appropriate points within the video.

[0449] Step 5:

[0450] The completed educational content is streamed from the server to the user's device. Users can view the content on their device and answer the provided quizzes.

[0451] Step 6:

[0452] The server tracks the user's learning progress and creates personalized feedback based on the collected data. This feedback is delivered to the user's device, allowing them to check their progress.

[0453] (Example 1)

[0454] 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."

[0455] In the modern field of education, it is difficult to quickly provide content that meets the diverse needs of learners. Furthermore, preparing educational materials that accommodate different languages ​​and cultures requires considerable effort and time. Moreover, providing individualized feedback tailored to each learner's progress requires advanced technology, and traditional methods are insufficient to address these challenges.

[0456] 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.

[0457] In this invention, the server includes means for automatically generating educational material scenarios using artificial intelligence, means for automatically generating audio output and text display based on the generated scenarios, and means for inserting interactive questions and responses into the audiovisual material. This enables rapid generation of educational content, multilingual support, and the provision of individualized feedback according to the learner's progress.

[0458] Artificial intelligence is a technology that gives computers the ability to learn and make decisions like humans.

[0459] "Educational materials" are content designed to help learners acquire specific skills or knowledge.

[0460] A "scenario" is a plan or storyline that defines the content and structure of educational materials.

[0461] "Audio output" is a technology that plays back synthesized audio based on a generated scenario.

[0462] "Text display" refers to text that is displayed on the screen to support the content of the audio output.

[0463] "Audiovisual materials" refer to educational videos and audio content.

[0464] "Interactive questions" are a type of learning content in which learners can choose or write their own answers.

[0465] A "response" is a reaction or feedback provided based on the learner's input in an interactive problem.

[0466] "Progress" refers to the extent to which learners have made progress in their learning through educational materials.

[0467] "Individualized feedback" is a function that provides specific improvement suggestions and evaluations tailored to the progress of each individual learner.

[0468] A "generative AI model" is an artificial intelligence model that has the ability to learn patterns from data and generate new data.

[0469] This invention is an educational content creation system that utilizes artificial intelligence. The system primarily consists of a server, a user terminal, and user operation. The server is the main hardware for executing programs and generates educational materials using a generative AI model. This system is capable of quickly responding to diverse educational needs.

[0470] Users can access the server via the internet using their device and log in to begin using the system. These devices include typical personal computers, tablets, or smartphones. After logging in, users can select options such as "Create a New Video" or "Take a Training Module" according to their learning objectives.

[0471] Based on user selections, the server initiates scenario generation using a generative AI model. This process collects and analyzes large amounts of data to create appropriate educational materials. For example, when creating training content for the medical field, scenarios incorporating essential knowledge and procedures are automatically constructed.

[0472] Next, the program uses AI speech synthesis technology to generate speech output and multilingual text display. This feature makes it compatible with users who speak different languages. Furthermore, the server incorporates interactive questions and response elements into the video content, creating an environment where users can actively participate in learning.

[0473] As a concrete example, consider a case where an elementary school teacher wants to create content for use in a natural science lesson. In this case, the user selects "Create New Video" and enters the prompt "Natural Science for Elementary School Students." Based on this information, the server creates an appropriate educational scenario and provides interactive educational content.

[0474] Example of a prompt:

[0475] "I'm creating science lesson content for elementary school students. The theme is the growth process of plants and the necessary conditions for growth. I want to include interactive quizzes to check students' understanding."

[0476] In this way, this system enables companies and educational institutions to provide educational content quickly and flexibly, and learners to acquire knowledge at their own pace.

[0477] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0478] Step 1:

[0479] The user accesses the system using a terminal and goes to the login screen. They enter their login information (user ID and password) and press the login button. The terminal sends this information to the server, which accesses the database to verify the authentication information. If the authentication is successful, the server returns an authentication success message to the terminal.

[0480] Step 2:

[0481] The user selects either "Create New Video" or "Take Training Module" from the menu screen on their device. The device sends this selection information to the server. The server prepares to start the appropriate process based on the user's selection.

[0482] Step 3:

[0483] Based on the selection information received from the user, the server begins generating scenarios using a generative AI model. A prompt provided by the user (e.g., "Natural Science for Elementary School Students") is given as input, and the server retrieves relevant knowledge data from the database to generate the optimal educational scenario. This generated scenario is then output.

[0484] Step 4:

[0485] The server generates speech output using AI speech synthesis technology based on the generated scenario. During this process, the scenario data is used as input, and an audio file is created. Simultaneously, multilingual text display data is also generated and output.

[0486] Step 5:

[0487] The server adds interactive elements (questions and feedback) to the generated audio and text data. Interactive elements, including quizzes and response options designed to encourage learner participation, are incorporated into the scenario, and the introduced interactive material becomes the output.

[0488] Step 6:

[0489] The server delivers the completed video content to the user's device via streaming. The device receives the stream in real time, and the user can watch the video. This completes the delivery of the educational content.

[0490] Step 7:

[0491] The server monitors the user's learning progress and uses the collected data to provide personalized feedback. The user's learning log is analyzed as input, and progress reports and suggestions for additional learning are output and displayed on the terminal.

[0492] (Application Example 1)

[0493] 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."

[0494] Traditional educational content systems have challenges in providing education tailored to specific situations in real time, and in providing immediate feedback based on the user's current progress. Furthermore, when supporting multiple languages, generating subtitles and other elements takes time, reducing usability. As a result, it has been difficult to create an environment where learners can learn optimally at their own pace.

[0495] 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.

[0496] In this invention, the server includes means for automatically generating an order of educational information using artificial intelligence, means for automatically generating voice guidance and text information based on the generated order, and means for transmitting the information in real time through a portable visual device. This enables learners to instantly receive optimal educational information on-site or while on the go.

[0497] "A means of automatically generating the order of educational information using artificial intelligence" refers to a function in which a program automatically determines the optimal order in which educational information is presented based on the learner's needs.

[0498] "Means for automatically generating audio guidance and text information based on the generated order" refers to a function that automatically creates audio explanations and corresponding subtitles in accordance with the determined order of educational information.

[0499] "Means of inserting interactive questions and assessments into informational content" refers to the function of incorporating quiz-style questions and immediate comprehension checks for learners into educational information.

[0500] "Means for tracking learner progress and providing individualized assessments" refers to a function that uses a system to measure how much information learners understand and remember, and then provides specific feedback and assessments based on that measurement.

[0501] "Means of transmitting information in real time through portable visual devices" refers to systems that use portable devices such as smart glasses to instantly deliver educational information to learners.

[0502] The system for implementing this invention mainly consists of a server, a user's visual device terminal, and a set of related programs. The server first uses artificial intelligence technology to automatically generate an order of information suitable for educational purposes based on the user's input data. Subsequently, it generates narration using speech synthesis technology and automatically generates text information according to the generated order of information. This makes it possible to create narration and subtitles that support multiple languages.

[0503] The server further incorporates interactive questions and assessments into the educational information. This allows the information presented to learners to include quizzes and real-time feedback to check their understanding. Each learner's progress is monitored by the server, and personalized feedback is generated. As a result, supplementary learning and additional suggestions are tailored to each learner, maximizing learning effectiveness.

[0504] Information is delivered to the user using a portable visual device, such as smart glasses. This device receives streaming data from a server and supports the user's educational experience on-site or while on the go. For example, at a construction site, users can watch educational videos on safety measures and take quizzes to check their understanding.

[0505] A concrete example of a prompt statement is, "Provide real-time explanations of safety measures at construction sites and generate content that includes a quiz to measure understanding." By using such prompt statements, the server can efficiently generate optimized educational scenarios and corresponding content.

[0506] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0507] Step 1:

[0508] The server analyzes educational input data received from the user. This input data includes, for example, learning subjects and learning levels. Based on the analysis results, a generative AI model is used to determine the optimal order of information. The input is the user's requested data, and the output is the order of the educational information.

[0509] Step 2:

[0510] The server automatically generates narration using speech synthesis technology based on the order of the generated information. AI speech synthesis software generates audio files on demand and converts them into a format for providing the narration. The input is the information order and text data, which are the output of step 1, and the output is an audio file.

[0511] Step 3:

[0512] The server generates multilingual subtitles using an AI model. This involves translating text into multiple languages ​​based on information order. The input is the information order output from step 1, and the output is subtitle files for each language.

[0513] Step 4:

[0514] The server inserts interactive questions and assessments into the generated information content. Based on the information submitted by the user, it designs quiz-style questions and integrates them into the system. This allows for real-time monitoring of the learner's understanding. The input is the information sequence from Step 1, and the output is information content with interactive quizzes.

[0515] Step 5:

[0516] The device streams completed educational content to the user via a portable visual device. Streaming technology is used to process data from the server in real time and deliver it to the user. The input is content data from the server, and the output is educational information displayed on the user's visual device.

[0517] Step 6:

[0518] Users experience educational content displayed through a visual device and answer interactive quizzes. The user's response data is sent back to the server for evaluation of their progress and understanding. Inputs are the educational content displayed on the visual device and user feedback data, while output is evaluation data sent to the server.

[0519] 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.

[0520] This invention integrates an emotion engine into an AI-powered educational content creation system to recognize user emotions and optimize the learning experience. This enables personalized education tailored to the needs of each learner.

[0521] This system consists of a server, a user terminal, and an emotion engine. Users first log in to the system via their terminal and select to create a video or take a training module. The selected information is then sent to the server by the terminal.

[0522] Based on the information received, the server uses artificial intelligence to automatically generate scenarios for educational content. In this process, relevant data is retrieved from a database, and a scenario aligned with the selected topic is formed. Based on the formed scenario, the server creates voice narration using AI speech synthesis and generates subtitles in multiple languages.

[0523] Furthermore, interactive elements will be added to the video content. Specifically, these will include quizzes to assess the user's understanding and real-time feedback features. These features will deepen the user's understanding during learning and make the content more meaningful.

[0524] This is where the emotion engine, a key feature of the present invention, comes into play. While the user is watching a video, the emotion engine analyzes the user's facial expressions and voice through the device's camera and sensors, recognizing emotions in real time. This recognition result is sent to a server and used to adjust the difficulty level of the content and the content of the feedback. For example, if the user is confused, the system can adjust by simplifying the explanation of the content or providing supplementary information.

[0525] Users can view this customized content and participate in interactive elements as needed. As learning progresses, the server records progress and provides personalized feedback based on the collected data. This allows learners to deepen their learning at their own pace, maximizing educational effectiveness.

[0526] In this way, the present invention can significantly improve the user's learning experience by incorporating emotion recognition using an emotion engine. As a result, companies and educational institutions can provide personalized learning environments to diverse learners.

[0527] The following describes the processing flow.

[0528] Step 1:

[0529] The user logs into the system using their device. They select either "Create a video" or "Take a training module" from the available options. The selected information is sent from the device to the server.

[0530] Step 2:

[0531] Based on the received selection information, the server automatically generates relevant educational content scenarios using artificial intelligence. In this process, the server retrieves necessary information from the database and determines the content and structure of the scenarios.

[0532] Step 3:

[0533] Based on the generated scenario, the server automatically produces voice narration using an AI speech synthesis engine. Simultaneously, the server generates subtitles in various languages ​​and integrates them into the educational content.

[0534] Step 4:

[0535] The emotion engine analyzes the user's facial expressions and voice in real time through the device's camera and microphone. The server receives this analysis data and recognizes the user's emotional state.

[0536] Step 5:

[0537] Based on the user's emotions, the server adjusts the educational content and feedback. For example, if the user is confused, the server provides additional supplementary information or an alternative explanation approach.

[0538] Step 6:

[0539] Interactive elements (e.g., quizzes and feedback features) are integrated into the content by the server. Users participate in these through their devices, deepening their learning experience.

[0540] Step 7:

[0541] The server tracks the progress of the entire learning session and assesses how well the user understands the content. Using the collected data, the server generates personalized feedback and provides it to the user through the device.

[0542] (Example 2)

[0543] 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."

[0544] There is a challenge in providing efficient and effective education while responding to the diverse needs of learners. In particular, there is a need for individualized support based on each learner's feelings and level of understanding, but conventional systems have found it difficult to make flexible adjustments accordingly.

[0545] 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.

[0546] In this invention, the server includes means for automatically generating a plan of educational information using artificial intelligence, means for automatically generating audio commentary and multilingual subtitles based on the generated plan, and means for recognizing the user's emotions in real time during learning and adjusting the educational content accordingly. This enables the provision of personalized and efficient education tailored to the diverse needs of learners.

[0547] Artificial intelligence is a technology that can automatically perform specific tasks by analyzing and learning from data.

[0548] An "educational information plan" is a set of guidelines and scripts for structuring the content and activities necessary to achieve specific educational goals for learners.

[0549] "Audio commentary" refers to educational information explained through audio, serving as a supplementary tool to help learners understand the material more easily.

[0550] "Multilingual subtitles" are text displayed in multiple languages, complementing audio explanations and video content, and providing visual support to learners.

[0551] "Interactive questions" are problems or questions presented in an interactive format with the user to assess whether the learner understands the learning material.

[0552] "Immediate response" refers to feedback and assessment provided quickly based on the learner's input and actions.

[0553] "Progress tracking" refers to the system tracking and saving the learner's progress and achievements as they progress through their learning process.

[0554] "Individualized feedback" refers to specific suggestions and advice provided based on each learner's individual learning situation and needs.

[0555] "Real-time emotional recognition" is a technology that analyzes a learner's facial expressions, tone of voice, etc., to instantly grasp their current emotional state.

[0556] "Adjusting educational content" means optimizing the difficulty level and methods of educational information according to the learner's level of understanding and emotions.

[0557] This invention is a system that utilizes artificial intelligence to provide users with personalized educational experiences. The system mainly consists of a server, a user terminal, and an emotion recognition engine.

[0558] First, the user logs into the system using their device and selects whether to create or take educational content. This selection information is sent from the device to the server. The server receives this information and uses a generative AI model to automatically generate a plan for the relevant educational content. For example, it might use the prompt "Generate a video scenario that explains environmental issues in an easy-to-understand way."

[0559] Based on the generated plan, the server uses AI-powered speech synthesis technology to create audio commentary and also generates multilingual subtitles. The latest technology is employed for both speech synthesis and subtitle generation. Users then view the generated content on their devices.

[0560] The videos include interactive elements such as two-way questions and real-time responses to deepen user understanding. During learning, the device's camera and sensors analyze the user's facial expressions and voice in real time, and an emotion recognition engine analyzes the user's emotional state. This analysis is sent to a server and used to adjust the difficulty level of the educational information and the content of the feedback. For example, if the server determines that the user is confused, it will provide a simpler explanation.

[0561] In this way, embodiments of the present invention can provide deep learning effects and realize personalized educational experiences that meet diverse needs. The flexible design of the system allows educational institutions and companies to provide the optimal learning environment for each learner.

[0562] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0563] Step 1:

[0564] The user logs into the system using a terminal. The user enters their username and password. The terminal verifies this information against the database, and if authentication is successful, grants access. The output indicates that a login session has started.

[0565] Step 2:

[0566] The user selects whether to create or take educational content through the terminal's interface. The user's selection information becomes input data, and the terminal packets this information and sends it to the server. The selected data arrives at the server as output.

[0567] Step 3:

[0568] The server uses a generation AI model based on the received selection information to automatically generate a plan for educational information. Specifically, it uses the prompt "Generate a video scenario that explains environmental issues in an easy-to-understand way" to have the model perform data calculations. The output is the generated educational scenario.

[0569] Step 4:

[0570] The server uses AI speech synthesis technology to create audio commentary based on the generated educational scenarios and also generates multilingual subtitles. This process utilizes a speech synthesis engine and subtitle generation software. The output consists of audio files and subtitle data.

[0571] Step 5:

[0572] The server generates interactive educational videos that include audio commentary and multilingual subtitles, and sends them to the user's terminal. The videos include interactive questions and real-time response functions to deepen the user's understanding. As output, the interactive video data is delivered to the user's terminal.

[0573] Step 6:

[0574] Users watch videos through their devices and participate in interactive elements. The device uses cameras and sensors to analyze the user's facial expressions and voice in real time, and obtains emotion recognition results. As output, data regarding the user's emotions and level of understanding is generated.

[0575] Step 7:

[0576] The server receives user sentiment data and adjusts the difficulty level and content of educational information. Specifically, it supplements or simplifies explanations based on the analysis results from the sentiment engine. The output is the adjusted feedback content.

[0577] Step 8:

[0578] Users view tailored content and progress through the learning process. Their device records their progress and sends it to the server. The server then provides personalized feedback based on the collected data. The output is feedback based on the final learning outcome.

[0579] (Application Example 2)

[0580] 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."

[0581] Conventional educational content creation systems have struggled to adjust content in real time based on learners' emotions and comprehension levels, making it impossible to provide personalized learning experiences. Furthermore, while there is a need for immediate multilingual support in environments where learners use multiple languages, there has been a lack of effective means to achieve this.

[0582] 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.

[0583] In this invention, the server includes means for automatically generating educational content plans using artificial intelligence, means for automatically generating voice guidance and subtitles based on the generated plans, means for inserting interactive questions and responses into video information, means for tracking learners' progress and providing individualized responses, and means for recognizing user emotions and adjusting the difficulty level and content of the content in real time. This enables the provision of personalized learning experiences that respond to learners' emotions and real-time multilingual support in diverse language environments.

[0584] "Artificial intelligence" refers to the technology in which computer systems perform intelligent tasks and mimic human judgment and learning abilities.

[0585] "Educational content" is a collection of information and materials designed to provide learners with knowledge and skills.

[0586] A "plan" is a detailed outline created to direct a series of actions or activities toward a specific objective.

[0587] "Voice guidance" refers to instructions or data generated to convey information using voice.

[0588] Subtitles are visually displayed textual information, typically provided to complement audio content.

[0589] "Video information" refers to dynamic digital recordings that include both video and audio.

[0590] A "problem" is a task or question that learners should attempt to solve in order to measure their understanding.

[0591] A "response" is a solution or answer to a problem or question that has been presented.

[0592] "Progress" refers to the current situation or level of achievement in a particular activity or learning process.

[0593] "Emotion" refers to the psychological response a person shows to a particular situation or information, and encompasses a wide range of mental states.

[0594] This invention is a system for providing personalized educational content, incorporating a server, a user terminal, and an emotion recognition engine. The server automatically generates educational content plans using artificial intelligence. Based on information from the user terminal, the server generates voice guidance and subtitles, and has the function of inserting interactive questions and responses into video information. Furthermore, the server tracks the learner's progress and provides individualized responses.

[0595] The user terminal has the capability to capture video and audio, capturing the user's facial expressions through the camera and transmitting them to the emotion recognition engine. The emotion recognition engine analyzes the user's emotions in real time and provides this data to the server. This allows the server to adjust the difficulty level and content of the content in a timely manner based on the user's emotions.

[0596] The software used includes OpenCV, which is utilized for image processing. It also implements a proprietary algorithm for detecting emotional patterns. The system aims to enhance user immersion and maximize individual learning effectiveness.

[0597] For example, if a user shows signs of confusion while learning calculus, the emotion recognition engine will detect this, and the server will immediately adjust the content to simplify the explanation and provide supplementary diagrams.

[0598] An example of a prompt used with a generative AI model is, "If the user is confused by difficult content, please suggest specific ways in which the content can be simplified." This allows for timely support for user comprehension and provides a more meaningful learning experience for learners.

[0599] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0600] Step 1:

[0601] The server receives login information from the user's terminal and waits for the user to select learning content. Once the user selects a training module, the server uses artificial intelligence to generate a content plan based on that information. The input is the selected topic, and the output is the generated content plan.

[0602] Step 2:

[0603] The server automatically generates audio guidance and multilingual subtitles based on the generated content plan. The input is the content plan, and the output is audio guidance data and subtitle data. The data is processed using speech synthesis software and a subtitle generation algorithm.

[0604] Step 3:

[0605] The server inserts interactive questions and responses into the content, allowing users to react to the questions and making the learning experience interactive. The input is the content plan, and the output is content containing interactive questions.

[0606] Step 4:

[0607] The user device collects video and audio data during learning. The device's camera captures the user's facial expressions. The input is a real-time video feed, and the output is captured image data.

[0608] Step 5:

[0609] The user terminal sends captured image data to an emotion recognition engine, where the user's emotions are analyzed. The input is image data, and the output is recognized emotion information. The data is analyzed using an emotion recognition algorithm.

[0610] Step 6:

[0611] The server adjusts the difficulty and content of the material in real time based on recognized sentiment information. For example, if a user is confused, the server simplifies the content or provides supplementary information. The input is sentiment information, and the output is the adjusted content.

[0612] Step 7:

[0613] As the user progresses through the learning process, the server tracks their progress and provides timely, personalized feedback. The input is learning history data, and the output is feedback data. The server analyzes the user's proficiency and processes the data to suggest the next learning steps.

[0614] Through this processing flow, users can obtain a more personalized educational experience.

[0615] 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.

[0616] 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.

[0617] 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.

[0618] [Fourth Embodiment]

[0619] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0620] 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.

[0621] 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).

[0622] 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.

[0623] 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.

[0624] 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).

[0625] 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.

[0626] 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.

[0627] 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.

[0628] 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.

[0629] 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.

[0630] 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.

[0631] 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".

[0632] This invention relates to an educational content creation system utilizing artificial intelligence, and its embodiments are described in detail. This system consists of a server, a user terminal, and user operations, and is capable of quickly responding to diverse educational needs.

[0633] First, the user accesses the system using their device and logs in. The user can then choose either "Create a New Video" or "Take a Training Module," depending on their purpose. Based on the selected purpose, the device sends relevant information to the server.

[0634] The server receives the user's selection and first uses artificial intelligence to automatically generate appropriate educational content scenarios. In this scenario generation process, relevant information is retrieved from a database to determine the optimal configuration for the purpose. For example, if the purpose is medical training, a scenario including the necessary knowledge and procedures will be designed.

[0635] Next, based on the generated scenario, the server automatically creates voice narration using AI speech synthesis technology and also generates multilingual subtitles. This process enables the creation of effective educational content that transcends language barriers.

[0636] The server then adds interactive elements to the video content. Specifically, these include quizzes to assess the learner's understanding and feedback features that allow for immediate confirmation of learning effectiveness. Such features help reinforce learning and promote effective learning.

[0637] The completed video content is streamed to the user's device by the server. Users can track their progress in real time, and personalized feedback is provided from the server based on the collected data. For example, additional learning is suggested according to the learning progress, and necessary knowledge reinforcement is supported.

[0638] This system allows companies and educational institutions to deliver educational content quickly and flexibly, and enables learners to acquire knowledge at their own pace. As a result, an educational environment is created that efficiently improves skills and knowledge.

[0639] The following describes the processing flow.

[0640] Step 1:

[0641] The user logs into the device and selects an option to create educational content or take a training module. The device then sends the user's selection information to the server.

[0642] Step 2:

[0643] Based on the received selection information, the server automatically generates relevant educational content scenarios using artificial intelligence. Here, the server retrieves necessary information from the database and determines the structure of the scenario.

[0644] Step 3:

[0645] The server uses the generated scenario to create narration using an AI speech synthesis engine. Simultaneously, the server generates multilingual subtitles and integrates them into the scenario.

[0646] Step 4:

[0647] The server adds interactive elements to the video content. Specifically, it embeds quizzes and real-time feedback features at appropriate points within the video.

[0648] Step 5:

[0649] The completed educational content is streamed from the server to the user's device. Users can view the content on their device and answer the provided quizzes.

[0650] Step 6:

[0651] The server tracks the user's learning progress and creates personalized feedback based on the collected data. This feedback is delivered to the user's device, allowing them to check their progress.

[0652] (Example 1)

[0653] 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".

[0654] In the modern field of education, it is difficult to quickly provide content that meets the diverse needs of learners. Furthermore, preparing educational materials that accommodate different languages ​​and cultures requires considerable effort and time. Moreover, providing individualized feedback tailored to each learner's progress requires advanced technology, and traditional methods are insufficient to address these challenges.

[0655] 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.

[0656] In this invention, the server includes means for automatically generating educational material scenarios using artificial intelligence, means for automatically generating audio output and text display based on the generated scenarios, and means for inserting interactive questions and responses into the audiovisual material. This enables rapid generation of educational content, multilingual support, and the provision of individualized feedback according to the learner's progress.

[0657] Artificial intelligence is a technology that gives computers the ability to learn and make decisions like humans.

[0658] "Educational materials" are content designed to help learners acquire specific skills or knowledge.

[0659] A "scenario" is a plan or storyline that defines the content and structure of educational materials.

[0660] "Audio output" is a technology that plays back synthesized audio based on a generated scenario.

[0661] "Text display" refers to text that is displayed on the screen to support the content of the audio output.

[0662] "Audiovisual materials" refer to educational videos and audio content.

[0663] "Interactive questions" are a type of learning content in which learners can choose or write their own answers.

[0664] A "response" is a reaction or feedback provided based on the learner's input in an interactive problem.

[0665] "Progress" refers to the extent to which learners have made progress in their learning through educational materials.

[0666] "Individualized feedback" is a function that provides specific improvement suggestions and evaluations tailored to the progress of each individual learner.

[0667] A "generative AI model" is an artificial intelligence model that has the ability to learn patterns from data and generate new data.

[0668] This invention is an educational content creation system that utilizes artificial intelligence. The system primarily consists of a server, a user terminal, and user operation. The server is the main hardware for executing programs and generates educational materials using a generative AI model. This system is capable of quickly responding to diverse educational needs.

[0669] Users can access the server via the internet using their device and log in to begin using the system. These devices include typical personal computers, tablets, or smartphones. After logging in, users can select options such as "Create a New Video" or "Take a Training Module" according to their learning objectives.

[0670] Based on user selections, the server initiates scenario generation using a generative AI model. This process collects and analyzes large amounts of data to create appropriate educational materials. For example, when creating training content for the medical field, scenarios incorporating essential knowledge and procedures are automatically constructed.

[0671] Next, the program uses AI speech synthesis technology to generate speech output and multilingual text display. This feature makes it compatible with users who speak different languages. Furthermore, the server incorporates interactive questions and response elements into the video content, creating an environment where users can actively participate in learning.

[0672] As a concrete example, consider a case where an elementary school teacher wants to create content for use in a natural science lesson. In this case, the user selects "Create New Video" and enters the prompt "Natural Science for Elementary School Students." Based on this information, the server creates an appropriate educational scenario and provides interactive educational content.

[0673] Example of a prompt:

[0674] "I'm creating science lesson content for elementary school students. The theme is the growth process of plants and the necessary conditions for growth. I want to include interactive quizzes to check students' understanding."

[0675] In this way, this system enables companies and educational institutions to provide educational content quickly and flexibly, and learners to acquire knowledge at their own pace.

[0676] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0677] Step 1:

[0678] The user accesses the system using a terminal and goes to the login screen. They enter their login information (user ID and password) and press the login button. The terminal sends this information to the server, which accesses the database to verify the authentication information. If the authentication is successful, the server returns an authentication success message to the terminal.

[0679] Step 2:

[0680] The user selects either "Create New Video" or "Take Training Module" from the menu screen on their device. The device sends this selection information to the server. The server prepares to start the appropriate process based on the user's selection.

[0681] Step 3:

[0682] Based on the selection information received from the user, the server begins generating scenarios using a generative AI model. A prompt provided by the user (e.g., "Natural Science for Elementary School Students") is given as input, and the server retrieves relevant knowledge data from the database to generate the optimal educational scenario. This generated scenario is then output.

[0683] Step 4:

[0684] The server generates speech output using AI speech synthesis technology based on the generated scenario. During this process, the scenario data is used as input, and an audio file is created. Simultaneously, multilingual text display data is also generated and output.

[0685] Step 5:

[0686] The server adds interactive elements (questions and feedback) to the generated audio and text data. Interactive elements, including quizzes and response options designed to encourage learner participation, are incorporated into the scenario, and the introduced interactive material becomes the output.

[0687] Step 6:

[0688] The server delivers the completed video content to the user's device via streaming. The device receives the stream in real time, and the user can watch the video. This completes the delivery of the educational content.

[0689] Step 7:

[0690] The server monitors the user's learning progress and uses the collected data to provide personalized feedback. The user's learning log is analyzed as input, and progress reports and suggestions for additional learning are output and displayed on the terminal.

[0691] (Application Example 1)

[0692] 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".

[0693] Traditional educational content systems have challenges in providing education tailored to specific situations in real time, and in providing immediate feedback based on the user's current progress. Furthermore, when supporting multiple languages, generating subtitles and other elements takes time, reducing usability. As a result, it has been difficult to create an environment where learners can learn optimally at their own pace.

[0694] 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.

[0695] In this invention, the server includes means for automatically generating an order of educational information using artificial intelligence, means for automatically generating voice guidance and text information based on the generated order, and means for transmitting the information in real time through a portable visual device. This enables learners to instantly receive optimal educational information on-site or while on the go.

[0696] "A means of automatically generating the order of educational information using artificial intelligence" refers to a function in which a program automatically determines the optimal order in which educational information is presented based on the learner's needs.

[0697] "Means for automatically generating audio guidance and text information based on the generated order" refers to a function that automatically creates audio explanations and corresponding subtitles in accordance with the determined order of educational information.

[0698] "Means of inserting interactive questions and assessments into informational content" refers to the function of incorporating quiz-style questions and immediate comprehension checks for learners into educational information.

[0699] "Means for tracking learner progress and providing individualized assessments" refers to a function that uses a system to measure how much information learners understand and remember, and then provides specific feedback and assessments based on that measurement.

[0700] "Means of transmitting information in real time through portable visual devices" refers to systems that use portable devices such as smart glasses to instantly deliver educational information to learners.

[0701] The system for implementing this invention mainly consists of a server, a user's visual device terminal, and a set of related programs. The server first uses artificial intelligence technology to automatically generate an order of information suitable for educational purposes based on the user's input data. Subsequently, it generates narration using speech synthesis technology and automatically generates text information according to the generated order of information. This makes it possible to create narration and subtitles that support multiple languages.

[0702] The server further incorporates interactive questions and assessments into the educational information. This allows the information presented to learners to include quizzes and real-time feedback to check their understanding. Each learner's progress is monitored by the server, and personalized feedback is generated. As a result, supplementary learning and additional suggestions are tailored to each learner, maximizing learning effectiveness.

[0703] Information is delivered to the user using a portable visual device, such as smart glasses. This device receives streaming data from a server and supports the user's educational experience on-site or while on the go. For example, at a construction site, users can watch educational videos on safety measures and take quizzes to check their understanding.

[0704] A concrete example of a prompt statement is, "Provide real-time explanations of safety measures at construction sites and generate content that includes a quiz to measure understanding." By using such prompt statements, the server can efficiently generate optimized educational scenarios and corresponding content.

[0705] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0706] Step 1:

[0707] The server analyzes educational input data received from the user. This input data includes, for example, learning subjects and learning levels. Based on the analysis results, a generative AI model is used to determine the optimal order of information. The input is the user's requested data, and the output is the order of the educational information.

[0708] Step 2:

[0709] The server automatically generates narration using speech synthesis technology based on the order of the generated information. AI speech synthesis software generates audio files on demand and converts them into a format for providing the narration. The input is the information order and text data, which are the output of step 1, and the output is an audio file.

[0710] Step 3:

[0711] The server generates multilingual subtitles using an AI model. This involves translating text into multiple languages ​​based on information order. The input is the information order output from step 1, and the output is subtitle files for each language.

[0712] Step 4:

[0713] The server inserts interactive questions and assessments into the generated information content. Based on the information submitted by the user, it designs quiz-style questions and integrates them into the system. This allows for real-time monitoring of the learner's understanding. The input is the information sequence from Step 1, and the output is information content with interactive quizzes.

[0714] Step 5:

[0715] The device streams completed educational content to the user via a portable visual device. Streaming technology is used to process data from the server in real time and deliver it to the user. The input is content data from the server, and the output is educational information displayed on the user's visual device.

[0716] Step 6:

[0717] Users experience educational content displayed through a visual device and answer interactive quizzes. The user's response data is sent back to the server for evaluation of their progress and understanding. Inputs are the educational content displayed on the visual device and user feedback data, while output is evaluation data sent to the server.

[0718] 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.

[0719] This invention integrates an emotion engine into an AI-powered educational content creation system to recognize user emotions and optimize the learning experience. This enables personalized education tailored to the needs of each learner.

[0720] This system consists of a server, a user terminal, and an emotion engine. Users first log in to the system via their terminal and select to create a video or take a training module. The selected information is then sent to the server by the terminal.

[0721] Based on the information received, the server uses artificial intelligence to automatically generate scenarios for educational content. In this process, relevant data is retrieved from a database, and a scenario aligned with the selected topic is formed. Based on the formed scenario, the server creates voice narration using AI speech synthesis and generates subtitles in multiple languages.

[0722] Furthermore, interactive elements will be added to the video content. Specifically, these will include quizzes to assess the user's understanding and real-time feedback features. These features will deepen the user's understanding during learning and make the content more meaningful.

[0723] This is where the emotion engine, a key feature of the present invention, comes into play. While the user is watching a video, the emotion engine analyzes the user's facial expressions and voice through the device's camera and sensors, recognizing emotions in real time. This recognition result is sent to a server and used to adjust the difficulty level of the content and the content of the feedback. For example, if the user is confused, the system can adjust by simplifying the explanation of the content or providing supplementary information.

[0724] Users can view this customized content and participate in interactive elements as needed. As learning progresses, the server records progress and provides personalized feedback based on the collected data. This allows learners to deepen their learning at their own pace, maximizing educational effectiveness.

[0725] In this way, the present invention can significantly improve the user's learning experience by incorporating emotion recognition using an emotion engine. As a result, companies and educational institutions can provide personalized learning environments to diverse learners.

[0726] The following describes the processing flow.

[0727] Step 1:

[0728] The user logs into the system using their device. They select either "Create a video" or "Take a training module" from the available options. The selected information is sent from the device to the server.

[0729] Step 2:

[0730] Based on the received selection information, the server automatically generates relevant educational content scenarios using artificial intelligence. In this process, the server retrieves necessary information from the database and determines the content and structure of the scenarios.

[0731] Step 3:

[0732] Based on the generated scenario, the server automatically produces voice narration using an AI speech synthesis engine. Simultaneously, the server generates subtitles in various languages ​​and integrates them into the educational content.

[0733] Step 4:

[0734] The emotion engine analyzes the user's facial expressions and voice in real time through the device's camera and microphone. The server receives this analysis data and recognizes the user's emotional state.

[0735] Step 5:

[0736] Based on the user's emotions, the server adjusts the educational content and feedback. For example, if the user is confused, the server provides additional supplementary information or an alternative explanation approach.

[0737] Step 6:

[0738] Interactive elements (e.g., quizzes and feedback features) are integrated into the content by the server. Users participate in these through their devices, deepening their learning experience.

[0739] Step 7:

[0740] The server tracks the progress of the entire learning session and assesses how well the user understands the content. Using the collected data, the server generates personalized feedback and provides it to the user through the device.

[0741] (Example 2)

[0742] 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".

[0743] There is a challenge in providing efficient and effective education while responding to the diverse needs of learners. In particular, there is a need for individualized support based on each learner's feelings and level of understanding, but conventional systems have found it difficult to make flexible adjustments accordingly.

[0744] 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.

[0745] In this invention, the server includes means for automatically generating a plan of educational information using artificial intelligence, means for automatically generating audio commentary and multilingual subtitles based on the generated plan, and means for recognizing the user's emotions in real time during learning and adjusting the educational content accordingly. This enables the provision of personalized and efficient education tailored to the diverse needs of learners.

[0746] Artificial intelligence is a technology that can automatically perform specific tasks by analyzing and learning from data.

[0747] An "educational information plan" is a set of guidelines and scripts for structuring the content and activities necessary to achieve specific educational goals for learners.

[0748] "Audio commentary" refers to educational information explained through audio, serving as a supplementary tool to help learners understand the material more easily.

[0749] "Multilingual subtitles" are text displayed in multiple languages, complementing audio explanations and video content, and providing visual support to learners.

[0750] "Interactive questions" are problems or questions presented in an interactive format with the user to assess whether the learner understands the learning material.

[0751] "Immediate response" refers to feedback and assessment provided quickly based on the learner's input and actions.

[0752] "Progress tracking" refers to the system tracking and saving the learner's progress and achievements as they progress through their learning process.

[0753] "Individualized feedback" refers to specific suggestions and advice provided based on each learner's individual learning situation and needs.

[0754] "Real-time emotional recognition" is a technology that analyzes a learner's facial expressions, tone of voice, etc., to instantly grasp their current emotional state.

[0755] "Adjusting educational content" means optimizing the difficulty level and methods of educational information according to the learner's level of understanding and emotions.

[0756] This invention is a system that utilizes artificial intelligence to provide users with personalized educational experiences. The system mainly consists of a server, a user terminal, and an emotion recognition engine.

[0757] First, the user logs into the system using their device and selects whether to create or take educational content. This selection information is sent from the device to the server. The server receives this information and uses a generative AI model to automatically generate a plan for the relevant educational content. For example, it might use the prompt "Generate a video scenario that explains environmental issues in an easy-to-understand way."

[0758] Based on the generated plan, the server uses AI-powered speech synthesis technology to create audio commentary and also generates multilingual subtitles. The latest technology is employed for both speech synthesis and subtitle generation. Users then view the generated content on their devices.

[0759] The videos include interactive elements such as two-way questions and real-time responses to deepen user understanding. During learning, the device's camera and sensors analyze the user's facial expressions and voice in real time, and an emotion recognition engine analyzes the user's emotional state. This analysis is sent to a server and used to adjust the difficulty level of the educational information and the content of the feedback. For example, if the server determines that the user is confused, it will provide a simpler explanation.

[0760] In this way, embodiments of the present invention can provide deep learning effects and realize personalized educational experiences that meet diverse needs. The flexible design of the system allows educational institutions and companies to provide the optimal learning environment for each learner.

[0761] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0762] Step 1:

[0763] The user logs into the system using a terminal. The user enters their username and password. The terminal verifies this information against the database, and if authentication is successful, grants access. The output indicates that a login session has started.

[0764] Step 2:

[0765] The user selects whether to create or take educational content through the terminal's interface. The user's selection information becomes input data, and the terminal packets this information and sends it to the server. The selected data arrives at the server as output.

[0766] Step 3:

[0767] The server uses a generation AI model based on the received selection information to automatically generate a plan for educational information. Specifically, it uses the prompt "Generate a video scenario that explains environmental issues in an easy-to-understand way" to have the model perform data calculations. The output is the generated educational scenario.

[0768] Step 4:

[0769] The server uses AI speech synthesis technology to create audio commentary based on the generated educational scenarios and also generates multilingual subtitles. This process utilizes a speech synthesis engine and subtitle generation software. The output consists of audio files and subtitle data.

[0770] Step 5:

[0771] The server generates interactive educational videos that include audio commentary and multilingual subtitles, and sends them to the user's terminal. The videos include interactive questions and real-time response functions to deepen the user's understanding. As output, the interactive video data is delivered to the user's terminal.

[0772] Step 6:

[0773] Users watch videos through their devices and participate in interactive elements. The device uses cameras and sensors to analyze the user's facial expressions and voice in real time, and obtains emotion recognition results. As output, data regarding the user's emotions and level of understanding is generated.

[0774] Step 7:

[0775] The server receives user sentiment data and adjusts the difficulty level and content of educational information. Specifically, it supplements or simplifies explanations based on the analysis results from the sentiment engine. The output is the adjusted feedback content.

[0776] Step 8:

[0777] Users view tailored content and progress through the learning process. Their device records their progress and sends it to the server. The server then provides personalized feedback based on the collected data. The output is feedback based on the final learning outcome.

[0778] (Application Example 2)

[0779] 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".

[0780] Conventional educational content creation systems have struggled to adjust content in real time based on learners' emotions and comprehension levels, making it impossible to provide personalized learning experiences. Furthermore, while there is a need for immediate multilingual support in environments where learners use multiple languages, there has been a lack of effective means to achieve this.

[0781] 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.

[0782] In this invention, the server includes means for automatically generating educational content plans using artificial intelligence, means for automatically generating voice guidance and subtitles based on the generated plans, means for inserting interactive questions and responses into video information, means for tracking learners' progress and providing individualized responses, and means for recognizing user emotions and adjusting the difficulty level and content of the content in real time. This enables the provision of personalized learning experiences that respond to learners' emotions and real-time multilingual support in diverse language environments.

[0783] "Artificial intelligence" refers to the technology in which computer systems perform intelligent tasks and mimic human judgment and learning abilities.

[0784] "Educational content" is a collection of information and materials designed to provide learners with knowledge and skills.

[0785] A "plan" is a detailed outline created to direct a series of actions or activities toward a specific objective.

[0786] "Voice guidance" refers to instructions or data generated to convey information using voice.

[0787] Subtitles are visually displayed textual information, typically provided to complement audio content.

[0788] "Video information" refers to dynamic digital recordings that include both video and audio.

[0789] A "problem" is a task or question that learners should attempt to solve in order to measure their understanding.

[0790] A "response" is a solution or answer to a problem or question that has been presented.

[0791] "Progress" refers to the current situation or level of achievement in a particular activity or learning process.

[0792] "Emotion" refers to the psychological response a person shows to a particular situation or information, and encompasses a wide range of mental states.

[0793] This invention is a system for providing personalized educational content, incorporating a server, a user terminal, and an emotion recognition engine. The server automatically generates educational content plans using artificial intelligence. Based on information from the user terminal, the server generates voice guidance and subtitles, and has the function of inserting interactive questions and responses into video information. Furthermore, the server tracks the learner's progress and provides individualized responses.

[0794] The user terminal has the capability to capture video and audio, capturing the user's facial expressions through the camera and transmitting them to the emotion recognition engine. The emotion recognition engine analyzes the user's emotions in real time and provides this data to the server. This allows the server to adjust the difficulty level and content of the content in a timely manner based on the user's emotions.

[0795] The software used includes OpenCV, which is utilized for image processing. It also implements a proprietary algorithm for detecting emotional patterns. The system aims to enhance user immersion and maximize individual learning effectiveness.

[0796] For example, if a user shows signs of confusion while learning calculus, the emotion recognition engine will detect this, and the server will immediately adjust the content to simplify the explanation and provide supplementary diagrams.

[0797] An example of a prompt used with a generative AI model is, "If the user is confused by difficult content, please suggest specific ways in which the content can be simplified." This allows for timely support for user comprehension and provides a more meaningful learning experience for learners.

[0798] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0799] Step 1:

[0800] The server receives login information from the user's terminal and waits for the user to select learning content. Once the user selects a training module, the server uses artificial intelligence to generate a content plan based on that information. The input is the selected topic, and the output is the generated content plan.

[0801] Step 2:

[0802] The server automatically generates audio guidance and multilingual subtitles based on the generated content plan. The input is the content plan, and the output is audio guidance data and subtitle data. The data is processed using speech synthesis software and a subtitle generation algorithm.

[0803] Step 3:

[0804] The server inserts interactive questions and responses into the content, allowing users to react to the questions and making the learning experience interactive. The input is the content plan, and the output is content containing interactive questions.

[0805] Step 4:

[0806] The user device collects video and audio data during learning. The device's camera captures the user's facial expressions. The input is a real-time video feed, and the output is captured image data.

[0807] Step 5:

[0808] The user terminal sends captured image data to an emotion recognition engine, where the user's emotions are analyzed. The input is image data, and the output is recognized emotion information. The data is analyzed using an emotion recognition algorithm.

[0809] Step 6:

[0810] The server adjusts the difficulty and content of the material in real time based on recognized sentiment information. For example, if a user is confused, the server simplifies the content or provides supplementary information. The input is sentiment information, and the output is the adjusted content.

[0811] Step 7:

[0812] As the user progresses through the learning process, the server tracks their progress and provides timely, personalized feedback. The input is learning history data, and the output is feedback data. The server analyzes the user's proficiency and processes the data to suggest the next learning steps.

[0813] Through this processing flow, users can obtain a more personalized educational experience.

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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.

[0820] 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.

[0821] 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.

[0822] 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."

[0823] 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.

[0824] 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0835] The following is further disclosed regarding the embodiments described above.

[0836] (Claim 1)

[0837] A means of automatically generating educational content scenarios using artificial intelligence,

[0838] A means for automatically generating audio narration and subtitles based on a generated scenario,

[0839] Methods for inserting interactive quizzes and feedback into video content,

[0840] A means of tracking learners' progress and providing individualized feedback,

[0841] A system that includes this.

[0842] (Claim 2)

[0843] The system according to claim 1, which provides industry-specific standard training modules.

[0844] (Claim 3)

[0845] The system according to claim 1, which generates subtitles in multiple languages ​​in order to achieve multilingual support.

[0846] "Example 1"

[0847] (Claim 1)

[0848] A means of automatically generating scenarios for educational materials using artificial intelligence,

[0849] A means for automatically generating audio output and text display based on the generated scenario,

[0850] A means of inserting interactive questions and responses into audiovisual material,

[0851] A means of tracking learners' progress and providing individualized assessments,

[0852] A means to promote the adaptation of educational content through data processing using generative AI models,

[0853] A system that includes this.

[0854] (Claim 2)

[0855] The system according to claim 1, which provides standard learning modules tailored to a specialized field.

[0856] (Claim 3)

[0857] The system according to claim 1, which generates text displays in multiple languages ​​for multilingual support.

[0858] "Application Example 1"

[0859] (Claim 1)

[0860] A means of automatically generating the order of educational information using artificial intelligence,

[0861] A means for automatically generating voice guidance and text information based on the generated order,

[0862] Means for inserting interactive questions and evaluations into informational content,

[0863] A means of tracking learners' progress and providing individualized assessments,

[0864] A means of transmitting information in real time through a portable visual device,

[0865] A system that includes this.

[0866] (Claim 2)

[0867] The system according to claim 1, which provides industry-specific standard training modules.

[0868] (Claim 3)

[0869] The system according to claim 1, which generates text information in multiple languages ​​in order to achieve multilingual support.

[0870] "Example 2 of combining an emotion engine"

[0871] (Claim 1)

[0872] A means of automatically generating educational information plans using artificial intelligence,

[0873] A means for automatically generating audio commentary and multilingual subtitles based on the generated plan,

[0874] A means of inserting interactive questions and immediate responses into educational videos,

[0875] A means of recording learners' progress and providing individual feedback,

[0876] A means of recognizing the user's emotions in real time during learning and adjusting the educational content accordingly,

[0877] A system that includes this.

[0878] (Claim 2)

[0879] The system according to claim 1, which provides industry-specific standard learning modules.

[0880] (Claim 3)

[0881] The system according to claim 1, which generates subtitles in multiple languages ​​in order to achieve multilingual support.

[0882] "Application example 2 when combining with an emotional engine"

[0883] (Claim 1)

[0884] A means of automatically generating educational content plans using artificial intelligence,

[0885] A means for automatically generating audio guidance and subtitles based on the generated plan,

[0886] A means of inserting manipulative questions or responses into video information,

[0887] A means of tracking learners' progress and providing individual responses,

[0888] A means of recognizing user emotions and adjusting the difficulty level and content of the material in real time,

[0889] A system that includes this.

[0890] (Claim 2)

[0891] The system according to claim 1, which provides industry-specific standard learning modules.

[0892] (Claim 3)

[0893] The system according to claim 1, which generates subtitles in multiple languages ​​in order to achieve multilingual support. [Explanation of Symbols]

[0894] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of automatically generating educational content scenarios using artificial intelligence, A means for automatically generating audio narration and subtitles based on a generated scenario, Methods for inserting interactive quizzes and feedback into video content, A means of tracking learners' progress and providing individualized feedback, A system that includes this.

2. The system according to claim 1, which provides industry-specific standard training modules.

3. The system according to claim 1, which generates subtitles in multiple languages ​​in order to achieve multilingual support.

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