system

Abstract

We provide the system. [Solution] A system comprising a chatbot using artificial intelligence, means for the chatbot to be applied in the field of education and training to provide answers to questions and guidance to students, and means for the chatbot to provide information on specific topics or subjects to help learners deepen their knowledge.

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 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 in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the fields of education and training, it is difficult for students to receive individual guidance according to their level of understanding. In addition, the information provided for students to deepen their learning voluntarily is not sufficient.

Means for Solving the Problems

[0005] The present invention applies a chatbot using artificial intelligence to the fields of education and training to provide students with answers to questions and guidance. Further, the chatbot provides information related to specific topics or subjects to assist learners in deepening their knowledge. In addition, the chatbot adjusts the method of providing information according to the level of understanding of the learner and automatically generates answers to questions from the learner.

Brief Description of the Drawings

[0006] [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] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 1 of Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2 of Embodiment 2. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Form Example 2. [Figure 15] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 3 of Example 3. [Figure 16]It is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Embodiment Example 3. [Figure 17] It is a sequence diagram showing the processing flow of the data processing system in Embodiment Example 1 of Embodiment Example 1 when combined with an emotion engine. [Figure 18] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Embodiment Example 1 when combined with an emotion engine. [Figure 19] It is a sequence diagram showing the processing flow of the data processing system in Embodiment Example 2 of Embodiment Example 2 when combined with an emotion engine. [Figure 20] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Embodiment Example 2 when combined with an emotion engine. [Figure 21] It is a sequence diagram showing the processing flow of the data processing system in Embodiment Example 3 of Embodiment Example 3 when combined with an emotion engine. [Figure 22] It is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Embodiment Example 3 when combined with an emotion engine. [Figure 23] It is a sequence diagram showing the processing flow of the data processing system in other embodiments.

Modes for Carrying Out the Invention

[0007] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0008] First, the language used in the following description will be explained.

[0009] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)), etc.

[0010] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0011] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0012] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0013] 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."

[0014] [First Embodiment]

[0015] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0027] "Example of form 1"

[0028] One embodiment of the present invention involves the application of an artificial intelligence-powered chatbot in the field of education and training. This chatbot provides students with answers to questions and guidance. For example, it could explain how to solve a math problem or provide information to deepen their understanding of a science experiment.

[0029] "Example of form 2"

[0030] Furthermore, chatbots can provide information on specific topics and subjects, helping learners deepen their knowledge. For example, they can provide detailed information about specific periods or events in history, or information to help interpret literary works.

[0031] "Example of form 3"

[0032] Furthermore, the chatbot adjusts how information is provided according to the learner's level of understanding. For example, if the learner is a beginner, it will provide basic information, and if the learner is advanced, it will provide more in-depth information.

[0033] "Example of form 4"

[0034] Furthermore, the chatbot automatically generates answers to learners' questions. For example, if a learner asks, "How do I find the solutions to a quadratic equation?", the chatbot will generate an answer explaining how to find the solutions to a quadratic equation.

[0035] The following describes the processing flow for each example of the form.

[0036] "Example of form 1"

[0037] Step 1: The learner enters a question into the chatbot. For example, they might enter the question, "How do I find the solutions to a quadratic equation?"

[0038] Step 2: The chatbot analyzes the question and generates an appropriate answer. In this case, it generates an answer explaining how to find the solutions to a quadratic equation.

[0039] Step 3: The chatbot provides the learner with the generated response. The learner then uses this response to continue their learning.

[0040] "Example of form 2"

[0041] Step 1: The learner requests information from the chatbot about a specific topic or subject. For example, they might request, "Teach me about Edo period society."

[0042] Step 2: The chatbot analyzes the request and generates appropriate information. In this case, it generates information about Edo period society.

[0043] Step 3: The chatbot provides the learner with the information it has generated. The learner then uses this information to continue their learning.

[0044] "Example of form 3"

[0045] Step 1: The chatbot evaluates the learner's understanding. For example, it evaluates understanding based on the results of tests submitted by the learner or the history of past questions.

[0046] Step 2: The chatbot adjusts how it provides information based on the evaluation results. For example, if it is evaluated as having a low level of understanding, it will start by providing basic information. If it is evaluated as having a high level of understanding, it will provide more in-depth information.

[0047] Step 3: The chatbot provides information to the learner based on the information delivery method it has set up. The learner then proceeds with their learning based on this information.

[0048] "Example of form 4"

[0049] Step 1: The learner enters a question into the chatbot. For example, they might enter the question, "How do I find the solutions to a quadratic equation?"

[0050] Step 2: The chatbot analyzes the question and automatically generates an appropriate answer. In this case, it generates an answer explaining how to find the solutions to a quadratic equation.

[0051] Step 3: The chatbot provides the learner with the generated response. The learner then uses this response to continue their learning.

[0052] (Example 1)

[0053] Next, we will describe Example 1 of Form 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."

[0054] Traditional information systems in the fields of education and training have faced challenges in providing flexible instruction tailored to the individual understanding and needs of learners. Furthermore, while there is a need to respond quickly and accurately to a wide range of inquiries from learners, there has been a lack of efficient means to achieve this.

[0055] 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.

[0056] In this invention, the server includes means for providing responses to inquiries and guidance to learners using an information processing device employing artificial intelligence, means for generating responses to inquiries using a generative AI model, and means for transmitting the generated responses to the learner's terminal. This enables flexible guidance tailored to the learner's individual level of understanding and needs, and allows for quick and accurate responses to a variety of inquiries.

[0057] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[0058] An "information processing device" is a device that receives data, processes it based on a specific algorithm, and outputs the result.

[0059] A "learner" is an individual who seeks to acquire knowledge and skills in the process of education or training.

[0060] An "inquiry" is a question or request that a learner makes to an information processing device in search of information or guidance.

[0061] A "response" is the answer or information that an information processing device provides in response to a learner's inquiry.

[0062] A "generative AI model" is a model that uses artificial intelligence technology to generate new information or responses based on input data.

[0063] A "terminal" is a device that a user uses to interface with an information processing device.

[0064] This invention is a system that utilizes an artificial intelligence-based information processing device to provide flexible guidance to learners in the fields of education and training. The server generates responses to learner inquiries using a generative AI model. Specifically, the server analyzes the learner's inquiry using natural language processing technology and understands its intent. The analyzed information is sent to the generative AI model as a prompt. For example, a model that excels at natural language generation is used as the generative AI model.

[0065] The server sends the response obtained from the generated AI model to the learner's device. The device displays the received response to the learner, allowing them to review it. This enables learners to obtain information tailored to their level of understanding, thereby improving learning efficiency.

[0066] For example, if a user asks a question via their device such as "Please explain the process of photosynthesis," the server sends this question as a prompt to the generating AI model. The generating AI model generates a response such as "Photosynthesis is the process by which plants use light energy to produce oxygen and glucose from carbon dioxide and water," and the server sends this response to the device. The user can then review the response displayed on their device and ask further questions if necessary.

[0067] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0068] Step 1:

[0069] The user enters a question into the chatbot via their device. The entered question is sent to the server as text data. Specifically, the user enters "Please explain the process of photosynthesis" into the chat interface on their device and clicks the send button.

[0070] Step 2:

[0071] The server receives text data sent by the user. It analyzes the received data using natural language processing techniques to understand the intent of the question. Specifically, the server tokenizes the text and performs grammatical analysis to identify the subject of the question. This analysis result becomes the input for the next step.

[0072] Step 3:

[0073] The server sends prompt messages to the generating AI model based on the analysis results. These prompt messages contain instructions for generating appropriate answers to the user's questions. Specifically, the server generates a prompt message such as "Please explain the process of photosynthesis in detail" and sends it to the generating AI model.

[0074] Step 4:

[0075] The generative AI model generates an answer based on the received prompt. The model utilizes pre-learned knowledge to create a detailed answer to the user's question. Specifically, the generative AI model might produce an answer such as, "Photosynthesis is the process by which plants use light energy to produce oxygen and glucose from carbon dioxide and water." This generated answer then becomes the input for the next step.

[0076] Step 5:

[0077] The server sends the response received from the generated AI model to the user's device. Specifically, the server sends the generated response in text format to the user's device and displays it in the chat interface.

[0078] Step 6:

[0079] The user reviews the answers displayed on the device to deepen their understanding of the questions. Specifically, the user reads the answers displayed on the device screen and enters further questions as needed.

[0080] (Application Example 1)

[0081] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0082] In modern educational and training settings, there is a challenge in that learners often struggle to obtain individually tailored learning experiences. Furthermore, while there is a demand for prompt and accurate answers to learners' questions, traditional methods are sometimes insufficient. Additionally, there is a need to adjust information provision according to the learner's level of understanding, but there is a lack of efficient means to achieve this.

[0083] 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.

[0084] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for the interactive program to provide a learning experience that is individually customized based on the subject selected by the learner, and means for generating answers to the user's questions using a generative AI model. As a result, learners can obtain an individually customized learning experience and receive quick and accurate answers. Furthermore, it becomes possible to adjust the information provided according to the learner's level of understanding.

[0085] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[0086] An "interactive program" is software that provides information or answers questions through dialogue with the user.

[0087] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[0088] A "learner" is an individual who seeks to acquire specific knowledge or skills.

[0089] A "personally customized learning experience" means providing educational content and methods that are tailored to the learner's needs and level of understanding.

[0090] A "generative AI model" is a mathematical model that uses artificial intelligence technology to generate new information or answers.

[0091] A "prompt statement" is an instruction given to a generative AI model to generate specific information.

[0092] The system for carrying out this invention consists of a network environment including a server and user terminals. The server executes an interactive program using artificial intelligence and receives input from the user terminals. The user terminals are devices such as smartphones and head-mounted displays, and provide an interface for the user to interact with the interactive program.

[0093] The server runs a generative AI model using software such as Python and TENSORFLOW®. User input is analyzed using natural language processing techniques and converted into a format suitable for the generative AI model. The generative AI model generates answers to the user's questions and sends the results to the user's terminal.

[0094] As a concrete example, if a user enters "Teach me the basics of differentiation" into their terminal, the server analyzes this input and sends the prompt "Please explain the basics of differentiation" to the generative AI model. The generative AI model generates an explanation of the basics of differentiation and returns it to the user's terminal. The user can then view this explanation on their terminal and continue learning.

[0095] This system allows users to receive a personalized learning experience and get quick and accurate answers.

[0096] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0097] Step 1:

[0098] The user enters a question using a terminal. The entered question is sent to the server through the terminal's interface. The input data is in text format and reflects the user's learning needs.

[0099] Step 2:

[0100] The server analyzes the user's question using natural language processing techniques. Specifically, it uses a Python natural language processing library to tokenize the input text and perform semantic analysis. This process helps understand the intent of the question and generates a prompt suitable for the generative AI model.

[0101] Step 3:

[0102] The server uses the generated prompt to query the generative AI model. The generative AI model receives the prompt as input and generates relevant information and answers. The generative AI model is built using TensorFlow and generates answers based on pre-trained data.

[0103] Step 4:

[0104] The responses obtained from the generative AI model are received by the server in text format. The server then formats these responses into a format that is easy for the user to understand and sends them to the device.

[0105] Step 5:

[0106] The terminal displays the answers received from the server to the user. The user can view the answers on the terminal screen and proceed with their learning. The displayed information is customized according to the user's learning needs.

[0107] (Example 2)

[0108] Next, we will describe Example 2 of Form 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".

[0109] Traditional educational support systems have faced challenges in enabling learners to quickly and accurately obtain detailed information on specific subjects. Furthermore, the lack of adequate information tailored to each learner's level of understanding makes it difficult to provide optimal learning support for individual students.

[0110] 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.

[0111] In this invention, the server includes an interactive program using an information processing device, means for applying the interactive program in the field of education to provide learners with responses to inquiries and guidance, and means for the interactive program to provide information on a specific subject and support learners in deepening their knowledge. As a result, learners can quickly obtain detailed information on a specific subject and information can be provided according to their level of understanding.

[0112] An "information processing device" is a device that has the functions of receiving, processing, and transmitting data, and includes hardware and software for executing interactive programs.

[0113] An "interactive program" is software that generates responses and provides information in response to user input, and is used in the field of education to support learners.

[0114] The "education field" refers to activities and areas that provide knowledge and skills to learners and support their learning.

[0115] A "learner" refers to an individual who seeks to acquire knowledge or skills related to a specific subject.

[0116] An "inquiry" refers to a question or request that a learner makes to an interactive program in order to obtain specific information.

[0117] "Response" refers to the information or instructions that an interactive program provides in response to a learner's inquiry.

[0118] A "subject" refers to a specific topic or subject that a learner is interested in and wishes to study.

[0119] "Support for deepening knowledge" refers to the information and instruction provided to help learners deepen their understanding of a particular subject.

[0120] This invention relates to a system for executing interactive programs using an information processing device. The server generates information based on user prompts, utilizing a generative AI model. Specifically, the server uses natural language processing technology to analyze user input and perform calculations to generate relevant information. A general-purpose natural language processing model can be used as the generative AI model.

[0121] The user enters a prompt message through the terminal. For example, they might enter a prompt message such as, "Tell me about the themes in Shakespeare's 'Hamlet'." The terminal sends this prompt message to the server. The server passes the received prompt message to a generation AI model, which generates information based on the prompt message. The generated information is sent from the server to the terminal and displayed to the user.

[0122] This system allows users to quickly obtain detailed information on specific topics. Furthermore, by utilizing generative AI models, it becomes possible to provide information tailored to the user's level of understanding, offering optimal learning support for individual learners.

[0123] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0124] Step 1:

[0125] The user enters a prompt using the terminal. For example, they might enter a specific question such as, "Tell me about the main events of the French Revolution." The entered prompt is then ready to be sent to the server through the terminal's interface.

[0126] Step 2:

[0127] The terminal sends the prompt text entered by the user to the server. Here, the terminal converts the prompt text into the appropriate data format and sends the data to the server using a communication protocol. The input is the prompt text, and the output is the transmission to the server.

[0128] Specific actions:

[0129] The terminal receives user input, converts the data into packets, and sends them to the server over the network.

[0130] Step 3: The server passes the prompt message to the AI ​​model.

[0131] The server parses the received prompt message and prepares it for the generative AI model. The server converts the prompt message into a format that the generative AI model can understand. The server inputs the prompt message into the generative AI model and waits for the model to process the information.

[0132] Step 4: The generative AI model generates information based on the prompt.

[0133] The generative AI model receives a prompt as input and generates relevant information. The model uses natural language processing techniques to generate the best possible answer to the user's question. Specifically, the model references a large dataset, extracts relevant information, and generates the answer in natural language.

[0134] Step 5: The server receives the generated information and sends it to the terminal.

[0135] The server receives the information returned from the generated AI model and sends it to the user's terminal. The server formats the information appropriately and sends the data to the terminal using a communication protocol. The server verifies the accuracy of the information and retrieves additional information as needed.

[0136] Step 6: The device displays information to the user.

[0137] The device displays information received from the server to the user. Specifically, it displays information generated on the device's screen, making it easy for the user to read and review. The user can then proceed with their learning based on the displayed information.

[0138] (Application Example 2)

[0139] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0140] Modern learners are required to acquire information on specific topics and subjects quickly and efficiently. However, traditional education systems face challenges in providing information tailored to individual learners' interests and levels of understanding, as well as in enabling real-time information acquisition. Furthermore, the lack of sufficient learning support utilizing portable information terminals and visual display devices means that learners cannot obtain in-depth information the moment they become interested.

[0141] 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.

[0142] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for installing the interactive program on a portable information terminal or visual display device, converting the user's voice input into text, acquiring information using a generative AI model, and displaying the results, and means for the interactive program to provide information in real time based on the user's interests. This makes it possible for learners to obtain in-depth information the moment they become interested.

[0143] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[0144] An "interactive program" is software that enables communication with users using natural language, providing information and answering questions.

[0145] A "portable information terminal" is a portable electronic device used for acquiring information and communicating.

[0146] A "visual display device" is a device used to visually display information and to confirm information.

[0147] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate new information or content based on input data.

[0148] "Real-time" refers to a state where information processing and communication occur instantly, and results are obtained without delay.

[0149] "Converting user voice input to text" is the process of converting a user's spoken words into text information using speech recognition technology.

[0150] The system for implementing this invention is centered around an interactive program using artificial intelligence. The server receives voice input from the user and uses speech recognition software to convert it into text. Specifically, speech recognition technologies such as Google® Speech-to-Text API can be used. The converted text is input into a generative AI model (e.g., OpenAI® GPT-3®) to generate information in response to the user's request.

[0151] The generated information is displayed on portable information terminals and visual display devices. This allows users to obtain information of interest in real time. For example, if a user uses their smartphone to voice-input "Tell me about the Napoleonic Wars," the information will be displayed immediately.

[0152] This system provides information based on the user's interests, allowing learners to gain in-depth information the moment they become interested. An example of a prompt would be, "Please tell me more about the plot and themes of Shakespeare's 'Hamlet'."

[0153] In this way, the invention can provide information to learners efficiently and effectively, and support the acquisition of knowledge.

[0154] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0155] Step 1:

[0156] The user inputs their question by voice into a portable information terminal or visual display device. The voice input is acquired through the terminal's microphone.

[0157] Step 2:

[0158] The device converts the acquired audio data into text data using speech recognition software (e.g., Google Speech-to-Text API). In this step, the audio waveform is analyzed and the corresponding string is generated. The input is audio data, and the output is text data.

[0159] Step 3:

[0160] The server sends the converted text data to a generating AI model (e.g., OpenAI GPT-3). Here, the server inputs the text data as a prompt into the AI ​​model, which then generates the relevant information. The input is text data, and the output is the generated information.

[0161] Step 4:

[0162] The server sends information obtained from the generated AI model to the terminal. The terminal visually displays the received information to the user. Here, the information is displayed on the screen for the user to review. The input is the generated information, and the output is the visual display.

[0163] Step 5:

[0164] The user can review the displayed information and ask further questions if necessary. At this step, the user can return to step 1 by entering a new question via voice input.

[0165] (Example 3)

[0166] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0167] Traditional interactive programs have faced challenges in providing appropriate information tailored to the learner's level of understanding, hindering efficient knowledge acquisition. Furthermore, they lack the ability to automatically generate appropriate answers to learners' questions, limiting the effectiveness of the learning process.

[0168] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0169] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for determining the learner's level of understanding and generating prompt sentences to provide information according to that level of understanding, and means for generating answers based on the prompt sentences using a generation AI model. This enables the provision of appropriate information according to the learner's level of understanding and the automatic generation of answers.

[0170] Artificial intelligence is a technology in which computer systems imitate human intellectual activity, performing tasks such as learning, reasoning, and problem-solving.

[0171] An "interactive program" is software that provides information or answers questions through dialogue with the user.

[0172] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[0173] A "learner" is an individual whose purpose is to acquire knowledge and skills.

[0174] A "prompt sentence" is an instruction sentence input into a generative AI model, and it contains information that forms the basis of the generated response.

[0175] A "generative AI model" is an artificial intelligence technology that generates natural language responses based on a prompt.

[0176] "Comprehension level" is an indicator that shows how well a learner understands a particular piece of knowledge or skill.

[0177] The embodiment for carrying out this invention is centered on an interactive program using artificial intelligence. The server receives input from the user and generates an appropriate response using a generative AI model. Specifically, the server receives a question sent from the user's terminal and analyzes its content. Based on the analysis results, it determines the user's level of understanding and generates a prompt sentence corresponding to that level of understanding.

[0178] The generated prompt is sent to a generative AI model. This model generates a natural language response based on the prompt. The generated response is returned to the user's terminal via the server. This allows the user to efficiently obtain information tailored to their level of understanding.

[0179] The hardware used includes a server and a user terminal, while the software includes a generative AI model. The generative AI model generates responses from prompt sentences using natural language processing techniques.

[0180] For example, if a user asks, "How do I find the solutions to a quadratic equation?", the server analyzes this question and, if it determines that the user is a beginner, generates a prompt such as, "Please explain the basic methods for solving quadratic equations." Based on this prompt, the AI ​​model generates an answer such as, "There are several ways to find the solutions to a quadratic equation, including factorization, completing the square, and using the quadratic formula," and provides it to the user.

[0181] In this way, the invention enables the provision of information tailored to the learner's level of understanding, thereby supporting efficient learning. The flow of the specific processing in Example 3 will be explained using Figure 15.

[0182] Step 1:

[0183] The user enters a question through their terminal. For example, they might enter a question like, "How do I find the solutions to a quadratic equation?" This input is then sent to the server.

[0184] Step 2:

[0185] The server receives questions from users and analyzes their content. Natural language processing techniques are used for the analysis to extract the intent and keywords of the questions. Based on these analysis results, data is generated to determine the user's level of understanding.

[0186] Step 3:

[0187] The server determines the user's level of understanding based on the analysis results. This determination takes into account past interaction data and the complexity of the questions. Using this determination, the server generates prompts appropriate to the user's level of understanding. For example, for a beginner, it might generate a prompt such as "Please explain the basic methods for solving quadratic equations."

[0188] Step 4:

[0189] The server sends the generated prompt to the generation AI model. The generation AI model receives the prompt as input and generates a natural language response based on it. During this generation process, data calculations are performed according to the content of the prompt.

[0190] Step 5:

[0191] The AI ​​model generates an answer which is then returned to the server. The server receives this answer and sends it to the user's device. The user can then view this answer through their device. For example, an answer such as, "There are several ways to find the solutions to a quadratic equation, including factorization, completing the square, and using the quadratic formula," might be provided.

[0192] This series of processes allows users to efficiently obtain information tailored to their level of understanding.

[0193] (Application Example 3)

[0194] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0195] Traditional education systems have faced challenges in providing optimal learning materials based on individual learners' comprehension levels and learning histories, and in generating appropriate answers to learners' questions immediately. This can hinder learners' efficient learning.

[0196] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0197] In this invention, the server includes means for analyzing the learner's past learning history using an interactive program with artificial intelligence and recommending the most suitable learning materials; means for instantly generating answers to questions from the learner and providing additional information to deepen understanding; and means for generating answers to questions from the learner using a generative AI model. This enables the provision of optimal learning materials tailored to the learner's individual level of understanding and prompt and appropriate answers to questions.

[0198] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[0199] An "interactive program" is software that provides information and answers questions through dialogue with the user using natural language.

[0200] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[0201] A "learner" is an individual who seeks to acquire specific knowledge or skills.

[0202] "Means of providing answers to questions and guidance" refers to methods of providing appropriate information in response to learners' questions and supporting their learning.

[0203] "Specific subjects or topics" refer to specific topics or fields that are covered in education or training.

[0204] "Methods for analyzing learners' past learning history" refer to methods for evaluating what learners have learned so far, their progress, and understanding their level of comprehension.

[0205] "A method for recommending the most suitable learning materials" refers to a method of selecting and presenting the most effective learning materials based on the learner's level of understanding and learning history.

[0206] A "generative AI model" is an algorithm or model that uses artificial intelligence technology to perform natural language processing and data generation.

[0207] "Means of providing additional information" refers to methods of providing supplementary information in addition to basic information in order to deepen learners' understanding.

[0208] To implement this invention, a server and a user terminal are required. The server runs an interactive program using artificial intelligence and analyzes the learner's past learning history. Specifically, the server retrieves the learner's history data from a database and evaluates their level of understanding using a machine learning algorithm. Software such as Python or TensorFlow can be used for this purpose.

[0209] The server recommends the most suitable learning materials based on the analysis results. These recommendations are displayed on the user's device using a web framework such as Flask. When the user enters a question, the server instantly generates an answer using a generative AI model. This model includes algorithms that leverage natural language processing techniques.

[0210] The user terminal is a device such as a smartphone or tablet that receives information provided by the server and displays it to the user. The user can input questions through the terminal and receive answers from the server.

[0211] For example, if a user enters "I want to learn the basics of differential and integral calculus," the server analyzes the user's past learning history and recommends basic differential and integral calculus learning materials. Also, if the user asks "Can you explain the basic formulas for differentiation?", the generative AI model instantly generates an answer and provides it to the user.

[0212] An example of a prompt message would be: "Recommend the best learning materials for a user who wants to learn the basics of differential and integral calculus. Also, answer questions about the fundamental formulas of differentiation."

[0213] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[0214] Step 1:

[0215] The user enters the topic they want to learn about using their device. The entered data is sent to the server. The server receives this input and retrieves the user's learning history data from its database.

[0216] Step 2:

[0217] The server evaluates the user's understanding based on the acquired learning history data. Here, machine learning algorithms are executed using Python and TensorFlow to analyze the user's past learning patterns. The input is the learning history data, and the output is the user's understanding evaluation result.

[0218] Step 3:

[0219] The server selects the most suitable learning materials based on the comprehension assessment results. The selected learning material information is sent to the user's terminal using Flask. The input is the comprehension assessment results, and the output is the recommended learning material information.

[0220] Step 4:

[0221] The user reviews the recommended learning materials on their device and then enters a question. The entered question is sent to the server. The server receives this question and uses a generative AI model to generate an answer.

[0222] Step 5:

[0223] The server generates answers to questions using a generative AI model. Here, natural language processing techniques are utilized to input prompts into the generative AI model. The input is the user's question, and the output is the generated answer.

[0224] Step 6:

[0225] The server sends the generated response to the user's terminal. The user can review the response on the terminal and ask additional questions if necessary. The input is the generated response, and the output is the display of the response to the user.

[0226] 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.

[0227] "Example of form 1"

[0228] One embodiment of the present invention provides a chatbot incorporating an emotion engine. This emotion engine recognizes emotions from the user's text or voice input. For example, if the user enters the phrase "I don't understand this problem," the emotion engine recognizes the user's frustration.

[0229] "Example of form 2"

[0230] After the emotion engine recognizes the user's emotions, the chatbot's response is adjusted accordingly. For example, if the chatbot detects that the user is feeling frustrated, it will respond in a more polite tone and provide additional explanations or support if necessary.

[0231] "Example of form 3"

[0232] Furthermore, the emotion engine adjusts how it educates and trains learners. For example, if it perceives that a user is agitated, the chatbot will move to a more advanced topic. Conversely, if it perceives that a user is confused, the chatbot will return to a more basic topic.

[0233] The following describes the processing flow for each example of the form.

[0234] "Example of form 1"

[0235] Step 1: The user sends a text or voice message to the chatbot.

[0236] Step 2: The emotion engine recognizes emotions from the user's message. For example, it recognizes the user's frustration from the phrase "I don't understand this problem."

[0237] "Example of form 2"

[0238] Step 1: The emotion engine recognizes the user's emotions.

[0239] Step 2: The chatbot adjusts its response based on the emotion engine's output. For example, if it perceives that the user is feeling frustrated, the chatbot will respond in a more polite tone and provide additional explanations or support if needed.

[0240] "Example of form 3"

[0241] Step 1: The emotion engine recognizes the user's emotions.

[0242] Step 2: The emotion engine adjusts how it educates and trains the learner. For example, if it perceives the user as agitated, the chatbot moves to a more advanced topic. Conversely, if it perceives the user as confused, the chatbot returns to a more basic topic.

[0243] (Example 1)

[0244] Next, we will describe Example 1 of Form 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."

[0245] Traditional interactive programs in education and training have struggled to provide appropriate instruction tailored to each learner's individual level of understanding and emotional state. Furthermore, they have limitations in their ability to generate quick and detailed answers to learners' questions. This has resulted in reduced learner efficiency and insufficient learning support that meets individual needs.

[0246] 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.

[0247] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for recognizing the learner's emotions using an emotion analysis function and generating appropriate feedback, and means for generating detailed answers to the learner's questions using a generative model. This makes it possible to provide appropriate guidance tailored to the learner's individual level of understanding and emotions, and to generate rapid and detailed answers.

[0248] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[0249] An "interactive program" is software that enables natural language interaction with the user and has functions for question answering and instruction.

[0250] "Education and training" refers to the activities and processes by which learners acquire new knowledge and skills.

[0251] A "learner" refers to an individual who receives education or training, with the aim of improving their knowledge and skills.

[0252] "Emotion analysis functionality" is a technology that recognizes emotions from a user's text or voice and generates an appropriate response based on those emotions.

[0253] A "generative model" is an algorithm that generates new data or information based on input data, and is particularly used in natural language processing.

[0254] "Feedback" refers to evaluation and guidance information provided regarding a learner's behavior and responses, intended to promote improvement in their learning.

[0255] In this embodiment of the invention, the server executes an interactive program using artificial intelligence. The server uses a common library as a natural language processing library to analyze text input from the user. Specifically, the server uses Python and leverages natural language processing libraries such as NLTK and spaCy to understand the user's intent and the content of their questions. Furthermore, for sentiment analysis, it recognizes the user's emotions using the sentiment analysis library TextBlob and a machine learning framework.

[0256] The terminal's role is to receive input from the user and send it to the server. When the user enters a prompt such as "Teach me the basics of differentiation," the terminal sends that text to the server. The server uses a common generative model as its generative AI model to generate a detailed answer to the user's question. This generative AI model uses natural language generation technology to create an appropriate answer to the user's question.

[0257] Users can receive responses from the server through their device and proceed with their learning. For example, if a user inputs "I don't understand this problem," the server uses sentiment analysis to recognize the user's frustration and generate appropriate feedback. This allows users to learn at their own pace.

[0258] The flow of the specific processing in Example 1 will be explained using Figure 17.

[0259] Step 1:

[0260] The user enters questions or requests via text or voice through the terminal. For example, they might enter a prompt such as, "Teach me the basics of differentiation." The terminal then sends this input to the server as text data.

[0261] Step 2:

[0262] The server analyzes the received text data using natural language processing libraries. Specifically, it uses NLTK and spaCy to process the data in order to understand the user's intent and the content of the question. This analysis identifies the subject and purpose of the user's question.

[0263] Step 3:

[0264] The server recognizes the user's emotions using sentiment analysis capabilities. Using TextBlob and machine learning frameworks, it extracts emotions from the input text to determine the user's emotional state. For example, if the user inputs "I don't understand this problem," it detects frustration.

[0265] Step 4:

[0266] The server uses a generative AI model to generate detailed answers to user questions. The generative model generates appropriate answers in natural language based on analyzed intent and sentiment. For example, it might create an explanation of the basics of differentiation, including concrete examples.

[0267] Step 5:

[0268] The server sends the generated answer to the terminal. The terminal displays this answer to the user. The user can then proceed with their learning based on the displayed information. This allows the user to learn at their own pace.

[0269] (Application Example 1)

[0270] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0271] Traditional education and training systems have struggled to provide appropriate instruction in real time, tailored to learners' emotions and levels of understanding. Furthermore, the work environment lacked the means to obtain immediate feedback through visual guidance. This resulted in challenges such as decreased learner motivation and hindered efficient learning.

[0272] 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.

[0273] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for incorporating an emotion recognition engine to recognize the learner's emotions, and means for providing real-time instruction through a visual device in the work environment. This enables the provision of appropriate instruction in real time according to the learner's emotions and level of understanding, and allows for immediate feedback in the work environment.

[0274] "Artificial intelligence" refers to a technology in which a computer system imitates human intelligence and performs learning and problem-solving.

[0275] "Interactive program" refers to software that provides information and answers questions through interaction with users.

[0276] "Field of education and training" refers to the field where activities for learners to acquire knowledge and skills are carried out.

[0277] "Emotion recognition engine" refers to a technology that analyzes and recognizes emotions from a user's text and voice.

[0278] "Visual device" refers to a device for a user to receive visual information, and includes smart glasses as an example.

[0279] "Provide guidance in real time" means to provide appropriate guidance and feedback immediately according to the user's situation.

[0280] "Learner" refers to an individual who attempts to acquire knowledge and skills.

[0281] "Feedback" refers to evaluation and guidance information provided for a user's behavior and situation.

[0282] The system for implementing this invention is mainly composed of an interactive program using artificial intelligence. The server incorporates an emotion recognition engine and analyzes and recognizes emotions from the user's text and voice input. As a result, it is possible to provide appropriate guidance and feedback in real time according to the user's emotions.

[0283] Specifically, the server uses an emotion recognition library developed with Python (e.g., OpenAI's Sentiment Analysis API) to process user input data. Voice input is converted to text using the Google Speech-to-Text API, and then emotion analysis is performed. Based on the analysis results, the interactive program uses a chatbot framework such as Rasa to generate an appropriate response to the user.

[0284] Smart glasses (e.g., Google Glass®) are used as the terminal, allowing users to receive information visually. This enables immediate feedback even in the work environment.

[0285] For example, if a user asks a question via voice, such as "I don't know how to attach this part," the server will sense the user's anxiety, and the interactive program will instruct them, "Please stay calm. First, attach part A to part B."

[0286] Examples of prompts for a generative AI model are as follows:

[0287] User input: "I don't know how to install this part."

[0288] Sentiment analysis result: "Anxiety"

[0289] Chatbot response: "Please stay calm. First, attach part A to part B."

[0290] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[0291] Step 1:

[0292] The user provides voice input through the device. The device converts the user's voice into text data using the Google Speech-to-Text API. The input for this step is voice data, and the output is text data.

[0293] Step 2:

[0294] The server receives the text data and analyzes the user's sentiment using a sentiment recognition engine. Specifically, it uses the sentiment analysis API of OpenAI to extract sentiment from the text data. The input of this step is the text data, and the output is the sentiment analysis result.

[0295] Step 3:

[0296] Based on the sentiment analysis result, the server uses a chatbot framework such as Rasa to generate an appropriate response to the user. The input of this step is the sentiment analysis result, and the output is the chatbot's response.

[0297] Step 4:

[0298] The terminal provides the generated chatbot response to the user visually or audibly. Specifically, it displays text through smart glasses or provides guidance via voice. The input of this step is the chatbot's response, and the output is the feedback to the user.

[0299] Step 5:

[0300] The user proceeds with the work based on the provided feedback. If necessary, the user can ask questions again and repeat the process. The input of this step is the feedback to the user, and the output is the user's action.

[0301] (Example 2)

[0302] Next, Example 2 of Embodiment 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0303] Traditional interactive programs have faced challenges in providing responses that take into account the user's emotions and insufficient information tailored to the learner's level of understanding. Furthermore, they have difficulty providing detailed information on specific topics and generating appropriate responses based on user input.

[0304] 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.

[0305] In this invention, the server includes means for providing an interactive program using an information processing device, means for recognizing the user's emotions and adjusting the response using emotion recognition technology, and means for analyzing the user's input and generating an appropriate response using a generative model. This makes it possible to adjust the response according to the user's emotions and provide information according to the learner's level of understanding.

[0306] An "information processing device" is a device used for inputting, processing, and outputting data, and includes devices such as computers and servers.

[0307] An "interactive program" is software that provides information and answers questions through dialogue with the user.

[0308] The "field of education and training" is the area in which activities are carried out to help learners acquire knowledge and skills.

[0309] A "learner" is an individual or group whose purpose is to acquire knowledge or skills.

[0310] A "subject or field" refers to a specific area of ​​knowledge or topic, and is the content that learners are supposed to study.

[0311] "Emotion recognition technology" refers to technology for analyzing and recognizing a user's emotions, and includes technology for determining emotions from voice and text.

[0312] A "generative model" is an algorithm or technique for generating new data or responses based on input data.

[0313] "Adjusting responses" means changing the information provided and how it is presented according to the user's emotions and circumstances.

[0314] This invention is a system for implementing an interactive program using an information processing device. The server utilizes a generative AI model to analyze user input and generate an appropriate response. Specifically, it uses natural language processing technology to understand the user's prompt and generates a response using a generative model. Furthermore, it uses emotion recognition technology to recognize the user's emotions and adjust the response accordingly.

[0315] The server receives prompt messages entered by the user through the terminal. For example, if the user enters "Tell me about Renaissance art," the server analyzes this input and provides information about representative artists and works of the Renaissance. Similarly, if the user asks "What is the theme of this poem?", the server analyzes the content of the poem and generates information about its theme.

[0316] By using emotion recognition technology, the server can determine the user's emotions and adjust the tone and content of its response. For example, if the server detects that the user is confused, it will offer additional support to help the user understand, such as "Shall I explain this topic in more detail?"

[0317] In this way, the server adjusts its responses to the user's emotions and provides information tailored to the learner's level of understanding. This allows learners to deepen their knowledge of specific subjects and fields.

[0318] The flow of the specific processing in Example 2 will be explained using Figure 19.

[0319] Step 1:

[0320] The user enters a prompt message through the terminal. For example, they might enter a question like, "Tell me about Renaissance art." This input is then sent to the server.

[0321] Step 2:

[0322] The server parses the received prompt message. Using natural language processing techniques, it understands the intent and content of the input text. This analysis identifies what information the user is seeking. As a result of the analysis, data regarding the user's intent is generated.

[0323] Step 3:

[0324] The server uses emotion recognition technology to recognize the user's emotions. It extracts emotional keywords and context from the input text to determine the user's emotional state. For example, if it determines that the user is confused, that information will influence the response generation in the next step.

[0325] Step 4:

[0326] The server uses a generative AI model to generate appropriate responses to user questions. Based on the analysis results and sentiment recognition results, it creates responses that provide information aligned with the user's intent. For example, a response containing detailed information about Renaissance art might be generated.

[0327] Step 5:

[0328] The server adjusts the generated response. It modifies the tone and content of the response according to the user's emotions. For confused users, it adjusts to provide additional explanations in a more polite and helpful tone.

[0329] Step 6:

[0330] The server sends a pre-arranged response to the terminal. The user can then view the chatbot's response on their terminal and continue asking further questions. This allows the user to obtain the necessary information.

[0331] (Application Example 2)

[0332] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0333] Traditional interactive programs in education and training have struggled to provide personalized learning experiences due to their inability to flexibly adapt to learners' emotions and levels of understanding. Furthermore, even when providing information on specific topics, the generated information sometimes failed to fully meet learners' needs. This resulted in challenges such as decreased learner motivation and reduced learning effectiveness.

[0334] 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.

[0335] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for recognizing the user's emotions using an emotion recognition engine and adjusting the response according to those emotions, and means for generating information based on prompt sentences using a generative AI model. This makes it possible to provide a personalized learning experience that is tailored to the learner's emotions and level of understanding, and to provide information on specific topics more appropriately.

[0336] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[0337] An "interactive program" is software that engages in natural language dialogue with the user to provide information and answer questions.

[0338] "Education and training" refers to the activities and processes by which learners acquire new knowledge and skills.

[0339] A "participant" is an individual who participates in an educational or training program and engages in learning.

[0340] "Means of providing answers to questions and guidance" refers to methods and techniques for generating appropriate answers to learners' questions and supporting their learning.

[0341] "Specific topics or subjects" refer to specific fields or topics that the learner is interested in.

[0342] An "emotion recognition engine" is a technology that analyzes and identifies emotions from a user's voice or text.

[0343] A "generative AI model" is an artificial intelligence model that generates natural language text based on input prompts.

[0344] A "prompt message" is text containing instructions or questions that are input into a generative AI model.

[0345] The system for implementing this invention mainly consists of a server and a user terminal. The server executes an interactive program using artificial intelligence and communicates with the user terminal. The user terminal is a device such as a smartphone or tablet, and interacts with the interactive program through an interface.

[0346] The server analyzes the user's emotions using an emotion recognition engine. Specifically, it receives the user's voice and text input and processes the data to identify their emotions. This process utilizes emotion recognition technologies such as Microsoft® Azure® Emotion API.

[0347] Furthermore, the server uses a generative AI model to generate information based on user prompts. OpenAI GPT-3 is one example of a generative AI model used. A prompt is a text containing information or a question the user wants to know, such as "Please provide detailed information about World War II."

[0348] When a user requests information on a specific topic, the server uses a generative AI model to generate relevant information and sends it to the user's device. If the user's emotions indicate frustration, the server adjusts its response, providing additional explanations in a more polite tone. This allows the user to have a personalized learning experience.

[0349] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[0350] Step 1:

[0351] The user uses a terminal to enter a prompt requesting information on a specific topic. The entered prompt might be in the format of, for example, "Please provide detailed information about World War II." The terminal then sends this prompt to the server.

[0352] Step 2:

[0353] The server parses the received prompt and inputs it into a generative AI model. The generative AI model (e.g., OpenAI GPT-3) generates relevant information based on the prompt. The generated information is output to the server as an answer to the prompt.

[0354] Step 3:

[0355] The server receives voice and text input from the user's device and analyzes the user's emotions using an emotion recognition engine. It processes the input data to identify the user's emotional state (e.g., frustration, excitement).

[0356] Step 4:

[0357] The server adjusts its response based on the generated information and the user's emotional state. For example, if the user is feeling frustrated, the server will generate a response in a more polite tone that includes additional explanations.

[0358] Step 5:

[0359] The server sends a tailored response to the user's device. The user can then receive personalized information and responses through their device, enabling them to have a better learning experience.

[0360] (Example 3)

[0361] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0362] Traditional interactive programs have failed to adequately provide information tailored to learners' levels of understanding and emotional states, making it difficult to address individual learners' needs. Furthermore, the automatic and appropriate generation of answers to learners' questions has been insufficient, preventing the maximization of learning effectiveness.

[0363] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0364] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for analyzing the learner's past dialogue data and evaluating their level of understanding, means for analyzing the learner's emotional state and adjusting the method of information provision, and means for generating prompt sentences and appropriate answers using a generative model. This enables personalized information provision according to the learner's level of understanding and emotional state, and realizes the automatic and appropriate generation of answers to questions from the learner.

[0365] Artificial intelligence is a technology in which computer systems imitate human intellectual behavior, enabling them to learn, reason, and solve problems.

[0366] An "interactive program" is software that provides information and answers questions through dialogue with the user.

[0367] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[0368] A "participant" is an individual who participates in an educational or training program and engages in learning.

[0369] A "subject or topic" refers to a specific area of ​​knowledge or topic that is covered in education or training.

[0370] "Comprehension level" is an indicator that shows how well a learner understands a particular piece of knowledge or skill.

[0371] "Emotional state" refers to the learner's psychological state and includes emotions such as excitement and confusion.

[0372] A "generative model" is an algorithm or technique for generating new data based on input data.

[0373] A "prompt statement" is an instruction given to a generative model, providing guidelines for obtaining a specific output.

[0374] A description of embodiments for carrying out this invention will be given.

[0375] The server runs an interactive program using artificial intelligence. This program utilizes a generative AI model to generate responses based on user input. Specifically, it analyzes user input using natural language processing techniques and understands their intent. A general natural language generation technique is used as the generative AI model.

[0376] The terminal collects the user's past conversation data and uses machine learning algorithms to evaluate the user's level of understanding. Based on this evaluation, the server adjusts the depth and detail of the information provided to the user. Furthermore, the terminal performs sentiment analysis on the input text to analyze the user's emotional state. This allows it to determine whether the user is agitated or confused and appropriately adjust the way information is delivered.

[0377] Users interact with interactive programs through their terminals. For example, if a user asks, "How do I find the solutions to a quadratic equation?", the server uses a generative AI model to generate a prompt and provide an appropriate answer. An example of a prompt might be, "The user is asking about how to solve a quadratic equation. Please explain the basic solution method for beginners."

[0378] This system allows users to receive personalized information tailored to their level of understanding and emotional state, maximizing learning effectiveness. The flow of specific processing in Example 3 will be explained using Figure 21.

[0379] Step 1:

[0380] Users input questions and requests through their terminals. For example, they might input a specific question like, "Please tell me how to find the solutions to a quadratic equation." This input serves as the starting point for the system's processing.

[0381] Step 2:

[0382] The server analyzes the input received from the user. Using natural language processing techniques, it tokenizes the input text and performs grammatical analysis to understand the user's intent. This analysis clarifies the meaning of the input and extracts the information necessary for the next processing step.

[0383] Step 3:

[0384] The terminal references the user's past conversation data and uses machine learning algorithms to assess the user's level of understanding. This assessment is based on the user's past questions and answers to determine whether the user is a beginner or an advanced user. This result is used to determine the depth of information provided by the server.

[0385] Step 4:

[0386] The server uses an emotion engine to analyze the user's emotional state. It performs sentiment analysis on the input text to determine whether the user is agitated or confused. This analysis is used to adjust the way information is delivered.

[0387] Step 5:

[0388] The server generates prompt sentences to be input into the generative AI model. These prompt sentences are adjusted according to the user's level of understanding and emotional state. For example, it might say, "The user is asking about solving quadratic equations. Please explain the basic solution method for beginners." These prompt sentences become the input to the generative AI model.

[0389] Step 6:

[0390] The server generates responses based on prompts using a generative AI model. The generative AI model receives prompts as input and generates appropriate responses. These responses include specific explanations and guidance regarding the user's questions.

[0391] Step 7:

[0392] The device displays the generated answer to the user. The user can receive the answer from the chatbot and deepen their understanding. For example, the chatbot may provide a specific explanation such as, "Quadratic equations can be solved using methods such as completing the square or factorization."

[0393] (Application Example 3)

[0394] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0395] In the field of modern education and training, there is a demand for flexible educational content that is tailored to each learner's individual level of understanding and emotional state. However, conventional systems have struggled to analyze learners' emotions and level of understanding in real time and provide appropriate learning content based on that analysis. This has hindered learners from efficiently acquiring knowledge.

[0396] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0397] In this invention, the server includes means for analyzing the learner's emotional state using an interactive program with artificial intelligence, means for generating learning content suitable for the learner using a generative AI model, and means for inputting prompt sentences into the generative AI model to generate learning content. This makes it possible to provide optimal educational content that corresponds to the learner's level of understanding and emotions.

[0398] "Artificial intelligence" is a technology in which computers imitate human intelligence and perform learning, reasoning, and problem-solving.

[0399] An "interactive program" is software that provides information or answers questions through natural dialogue with the user.

[0400] The "field of education and training" refers to the activities and processes by which learners acquire new knowledge and skills.

[0401] A "learner" refers to an individual who seeks to acquire specific knowledge or skills.

[0402] "Emotional state" refers to the learner's psychological state and changes in their emotions.

[0403] A "generative AI model" is an artificial intelligence model that generates new data or content based on given input.

[0404] A "prompt statement" is an instruction or question given to a generative AI model to obtain a specific output.

[0405] "Learning content" refers to educational materials and information that learners use to acquire knowledge and skills.

[0406] The system for carrying out this invention includes a server and a user terminal. The server executes an interactive program using artificial intelligence and receives input from the user terminal. The user terminal is a device such as a smartphone or a head-mounted display, and provides an interface with the user.

[0407] The server uses an emotion recognition engine (e.g., Microsoft Azure Emotion API) to analyze the user's voice and facial expression data and evaluate the user's emotional state. Based on this evaluation, the server uses a generative AI model (e.g., OpenAI GPT-3) to generate learning content suitable for the user. The generative AI model can generate specific learning content by inputting prompts.

[0408] For example, if a user asks, "Please explain the basics of differential and integral calculus," the server detects confusion from the user's facial expression. In this case, it prompts the generative AI model with "Please explain the basic concepts of differential and integral calculus in a way that is easy for beginners to understand," and sends the generated content to the user's device. This allows the user to receive an optimal learning experience tailored to their level of understanding and emotional state.

[0409] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[0410] Step 1:

[0411] The user enters a question via a terminal. The terminal captures the user's voice and facial expression data and sends it to the server. The input consists of the user's question text and voice / facial expression data.

[0412] Step 2:

[0413] The server inputs received audio and facial expression data into an emotion recognition engine to analyze the user's emotional state. For data processing, audio data is converted to text, and facial expression data is analyzed using image analysis. The output is an evaluation result indicating the user's emotional state.

[0414] Step 3:

[0415] The server generates and inputs prompt sentences into the generative AI model based on the user's question text and the evaluation of their emotional state. Specifically, prompt sentences are generated such as "Please explain the basic concepts of differential and integral calculus in a way that is easy for beginners to understand." The input is the prompt sentence, and the output is the generated training content.

[0416] Step 4:

[0417] The generative AI model generates appropriate training content based on prompt text. As a data processing technique, the model uses natural language processing to construct the content. The output is training content to be provided to the user.

[0418] Step 5:

[0419] The server sends the generated learning content to the user's terminal. The terminal displays the content to the user and assists with learning. Specifically, the terminal presents the content in text or audio. The output is the learning content received by the user.

[0420] (Other examples)

[0421] Next, other embodiments will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0422] Conventional educational support systems have the challenge of not being able to maximize learning effectiveness because they struggle to provide appropriate guidance and information tailored to each learner's individual level of understanding and emotional state. In particular, the lack of flexible response generation using generative AI models and response adjustments based on learners' emotions makes it difficult to meet the diverse needs of learners.

[0423] The identification process performed by the identification processing unit 290 of the data processing device 12 in other embodiments is realized by the following means.

[0424] In this invention, the server includes means for analyzing input from the learner and obtaining relevant information from a database; means for creating prompt statements to instruct a generative AI model to generate answers and inputting the prompts into the generative AI model; and means for analyzing the learner's past interaction data and evaluating their level of understanding. This enables appropriate guidance and information provision tailored to the learner's individual level of understanding and emotional state.

[0425] "Artificial intelligence" is a technology in which computer systems mimic human intelligence and perform tasks such as learning, reasoning, and problem-solving.

[0426] An "interactive program" is software that provides information and answers questions through interaction with the user.

[0427] A "generative AI model" is an artificial intelligence model that generates natural language text based on input data, and specifically refers to a neural network trained on a large dataset.

[0428] A "prompt statement" is an input statement used to instruct a generative AI model to perform a specific task, and it serves as a guide for the model to generate an appropriate response.

[0429] An "emotion recognition engine" is software or hardware that analyzes a user's voice or text data to determine their emotional state.

[0430] "Comprehension level" is an indicator that shows how well learners understand the knowledge related to a particular subject or topic.

[0431] A "database" is a system for efficiently storing, searching, and managing information, and is particularly suited to handling structured data.

[0432] This invention is a system that implements an interactive program using artificial intelligence, providing learners with answers to questions and guidance in the fields of education and training. Specific embodiments of this system are described below.

[0433] The server receives questions and instructions sent from the user's terminal. The user inputs questions, such as "Please explain the basics of differentiation," through an interface on the terminal. The server analyzes this input using a natural language processing library (e.g., spaCy) and extracts important keywords and intent.

[0434] Based on the analyzed keywords, the server retrieves relevant information from a database (e.g., MongoDB). For example, it searches the database for information related to "basic differential calculus" and retrieves it.

[0435] Next, the server creates a prompt for a generative AI model (e.g., OpenAI's GPT-3) to generate an answer. This prompt is input to the generative AI model, which then generates an appropriate answer. An example of a prompt is: "The user is asking a question about the basics of differentiation. Please explain the basic concepts of differentiation."

[0436] Furthermore, the server analyzes the learner's past interaction data using machine learning algorithms (e.g., scikit-learn) to assess their comprehension. This comprehension score is taken into consideration when providing information.

[0437] Furthermore, the server uses an emotion recognition engine (e.g., Microsoft Azure's Emotion API) to analyze the user's voice and text data and determine their emotional state. Based on the analyzed emotional state, it adjusts its response and provides the user with appropriate feedback.

[0438] Ultimately, the server integrates the responses from the generated AI model with information retrieved from the database and sends them to the user. The terminal receives the information and responses sent from the server and displays them to the user. The user can review this and ask additional questions if necessary.

[0439] The flow of specific processing in other embodiments will be explained using Figure 23.

[0440] Step 1:

[0441] The user inputs questions and instructions through an interface on the terminal. For example, they might input a question like, "Please explain the basics of differentiation." The terminal sends this input to the server. The input is the user's question text, and the output is the data sent to the server.

[0442] Step 2:

[0443] The server analyzes the input data received from the user using a natural language processing library (e.g., spaCy). The input is the user's question text, and the output is extracted keywords and intent. Specifically, the text is tokenized, part-of-speech tags are applied, and important keywords such as "differentiation" and "basic" are extracted.

[0444] Step 3:

[0445] The server retrieves relevant information from a database (e.g., MongoDB) based on the analyzed keywords. The input is the extracted keywords, and the output is the information retrieved from the database. Specifically, it executes database queries using the keywords to retrieve information about "the basics of differentiation."

[0446] Step 4:

[0447] The server creates prompts to generate answers for a generative AI model (e.g., OpenAI's GPT-3). The input is the user's question and analysis results, and the output is the prompt to be input to the generative AI model. Specifically, it creates a prompt such as, "The user is asking a question about the basics of differentiation. Please explain the basic concepts of differentiation."

[0448] Step 5:

[0449] The server inputs a prompt message into a generative AI model and retrieves the response generated by the model. The input is the prompt message, and the output is the generated response. Specifically, the prompt message is sent to the generative AI model via an API, and the response from the model is received.

[0450] Step 6:

[0451] The server analyzes the learner's past interaction data using a machine learning algorithm (e.g., scikit-learn) to evaluate their comprehension. The input is past interaction data, and the output is a comprehension score. Specifically, the data is extracted as features, and a model is used to predict the level of comprehension.

[0452] Step 7:

[0453] The server uses an emotion recognition engine (e.g., Microsoft Azure's Emotion API) to analyze the user's voice and text data and determine their emotional state. The input is the user's voice and text data, and the output is their emotional state. Specifically, it analyzes the voice data, assigns an emotion label, and adjusts the response accordingly.

[0454] Step 8:

[0455] The server integrates the responses from the generated AI model with information retrieved from the database and sends it to the user. The input is the generated response and retrieved information, and the output is the data sent to the user. Specifically, the response and information are combined, formatted into a single message, and sent to the user's terminal.

[0456] Step 9:

[0457] The terminal receives information and responses sent from the server and displays them to the user. Input is the data sent from the server, and output is the content displayed to the user. Specifically, it displays the received data on the screen so the user can confirm it.

[0458] 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.

[0459] Data generation model 58 is a form of 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> 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.

[0460] Other examples of generative AI include Gemini® (registered trademark) (Internet search). <url: https: gemini.google.com ?hl="ja">) are some examples.

[0461] 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.

[0462] [Second Embodiment]

[0463] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0464] 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.

[0465] 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).

[0466] 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.

[0467] 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.

[0468] 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).

[0469] 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.

[0470] 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.

[0471] 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.

[0472] 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.

[0473] 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.

[0474] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0475] "Example of form 1"

[0476] One embodiment of the present invention involves the application of an artificial intelligence-powered chatbot in the field of education and training. This chatbot provides students with answers to questions and guidance. For example, it could explain how to solve a math problem or provide information to deepen their understanding of a science experiment.

[0477] "Example of form 2"

[0478] Furthermore, chatbots can provide information on specific topics and subjects, helping learners deepen their knowledge. For example, they can provide detailed information about specific periods or events in history, or information to help interpret literary works.

[0479] "Example of form 3"

[0480] Furthermore, the chatbot adjusts how information is provided according to the learner's level of understanding. For example, if the learner is a beginner, it will provide basic information, and if the learner is advanced, it will provide more in-depth information.

[0481] "Example of form 4"

[0482] Furthermore, the chatbot automatically generates answers to learners' questions. For example, if a learner asks, "How do I find the solutions to a quadratic equation?", the chatbot will generate an answer explaining how to find the solutions to a quadratic equation.

[0483] The following describes the processing flow for each example of the form.

[0484] "Example of form 1"

[0485] Step 1: The learner enters a question into the chatbot. For example, they might enter the question, "How do I find the solutions to a quadratic equation?"

[0486] Step 2: The chatbot analyzes the question and generates an appropriate answer. In this case, it generates an answer explaining how to find the solutions to a quadratic equation.

[0487] Step 3: The chatbot provides the learner with the generated response. The learner then uses this response to continue their learning.

[0488] "Example of form 2"

[0489] Step 1: The learner requests information from the chatbot about a specific topic or subject. For example, they might request, "Teach me about Edo period society."

[0490] Step 2: The chatbot analyzes the request and generates appropriate information. In this case, it generates information about Edo period society.

[0491] Step 3: The chatbot provides the learner with the information it has generated. The learner then uses this information to continue their learning.

[0492] "Example of form 3"

[0493] Step 1: The chatbot evaluates the learner's understanding. For example, it evaluates understanding based on the results of tests submitted by the learner or the history of past questions.

[0494] Step 2: The chatbot adjusts how it provides information based on the evaluation results. For example, if it is evaluated as having a low level of understanding, it will start by providing basic information. If it is evaluated as having a high level of understanding, it will provide more in-depth information.

[0495] Step 3: The chatbot provides information to the learner based on the information delivery method it has set up. The learner then proceeds with their learning based on this information.

[0496] "Example of form 4"

[0497] Step 1: The learner enters a question into the chatbot. For example, they might enter the question, "How do I find the solutions to a quadratic equation?"

[0498] Step 2: The chatbot analyzes the question and automatically generates an appropriate answer. In this case, it generates an answer explaining how to find the solutions to a quadratic equation.

[0499] Step 3: The chatbot provides the learner with the generated response. The learner then uses this response to continue their learning.

[0500] (Example 1)

[0501] Next, we will describe Example 1 of Form 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".

[0502] Traditional information systems in the fields of education and training have faced challenges in providing flexible instruction tailored to the individual understanding and needs of learners. Furthermore, while there is a need to respond quickly and accurately to a wide range of inquiries from learners, there has been a lack of efficient means to achieve this.

[0503] 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.

[0504] In this invention, the server includes means for providing responses to inquiries and guidance to learners using an information processing device employing artificial intelligence, means for generating responses to inquiries using a generative AI model, and means for transmitting the generated responses to the learner's terminal. This enables flexible guidance tailored to the learner's individual level of understanding and needs, and allows for quick and accurate responses to a variety of inquiries.

[0505] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[0506] An "information processing device" is a device that receives data, processes it based on a specific algorithm, and outputs the result.

[0507] A "learner" is an individual who seeks to acquire knowledge and skills in the process of education or training.

[0508] An "inquiry" is a question or request that a learner makes to an information processing device in search of information or guidance.

[0509] A "response" is the answer or information that an information processing device provides in response to a learner's inquiry.

[0510] A "generative AI model" is a model that uses artificial intelligence technology to generate new information or responses based on input data.

[0511] A "terminal" is a device that a user uses to interface with an information processing device.

[0512] This invention is a system that utilizes an artificial intelligence-based information processing device to provide flexible guidance to learners in the fields of education and training. The server generates responses to learner inquiries using a generative AI model. Specifically, the server analyzes the learner's inquiry using natural language processing technology and understands its intent. The analyzed information is sent to the generative AI model as a prompt. For example, a model that excels at natural language generation is used as the generative AI model.

[0513] The server sends the response obtained from the generated AI model to the learner's device. The device displays the received response to the learner, allowing them to review it. This enables learners to obtain information tailored to their level of understanding, thereby improving learning efficiency.

[0514] For example, if a user asks a question via their device such as "Please explain the process of photosynthesis," the server sends this question as a prompt to the generating AI model. The generating AI model generates a response such as "Photosynthesis is the process by which plants use light energy to produce oxygen and glucose from carbon dioxide and water," and the server sends this response to the device. The user can then review the response displayed on their device and ask further questions if necessary.

[0515] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0516] Step 1:

[0517] The user enters a question into the chatbot via their device. The entered question is sent to the server as text data. Specifically, the user enters "Please explain the process of photosynthesis" into the chat interface on their device and clicks the send button.

[0518] Step 2:

[0519] The server receives text data sent by the user. It analyzes the received data using natural language processing techniques to understand the intent of the question. Specifically, the server tokenizes the text and performs grammatical analysis to identify the subject of the question. This analysis result becomes the input for the next step.

[0520] Step 3:

[0521] The server sends prompt messages to the generating AI model based on the analysis results. These prompt messages contain instructions for generating appropriate answers to the user's questions. Specifically, the server generates a prompt message such as "Please explain the process of photosynthesis in detail" and sends it to the generating AI model.

[0522] Step 4:

[0523] The generative AI model generates an answer based on the received prompt. The model utilizes pre-learned knowledge to create a detailed answer to the user's question. Specifically, the generative AI model might produce an answer such as, "Photosynthesis is the process by which plants use light energy to produce oxygen and glucose from carbon dioxide and water." This generated answer then becomes the input for the next step.

[0524] Step 5:

[0525] The server sends the response received from the generated AI model to the user's device. Specifically, the server sends the generated response in text format to the user's device and displays it in the chat interface.

[0526] Step 6:

[0527] The user reviews the answers displayed on the device to deepen their understanding of the questions. Specifically, the user reads the answers displayed on the device screen and enters further questions as needed.

[0528] (Application Example 1)

[0529] Next, we will describe Application Example 1 of Form 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."

[0530] In modern educational and training settings, there is a challenge in that learners often struggle to obtain individually tailored learning experiences. Furthermore, while there is a demand for prompt and accurate answers to learners' questions, traditional methods are sometimes insufficient. Additionally, there is a need to adjust information provision according to the learner's level of understanding, but there is a lack of efficient means to achieve this.

[0531] 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.

[0532] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for the interactive program to provide a learning experience that is individually customized based on the subject selected by the learner, and means for generating answers to the user's questions using a generative AI model. As a result, learners can obtain an individually customized learning experience and receive quick and accurate answers. Furthermore, it becomes possible to adjust the information provided according to the learner's level of understanding.

[0533] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[0534] An "interactive program" is software that provides information or answers questions through dialogue with the user.

[0535] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[0536] A "learner" is an individual who seeks to acquire specific knowledge or skills.

[0537] A "personally customized learning experience" means providing educational content and methods that are tailored to the learner's needs and level of understanding.

[0538] A "generative AI model" is a mathematical model that uses artificial intelligence technology to generate new information or answers.

[0539] A "prompt statement" is an instruction given to a generative AI model to generate specific information.

[0540] The system for carrying out this invention consists of a network environment including a server and user terminals. The server executes an interactive program using artificial intelligence and receives input from the user terminals. The user terminals are devices such as smartphones and head-mounted displays, and provide an interface for the user to interact with the interactive program.

[0541] The server runs generative AI models using software such as Python and TensorFlow. User input is analyzed using natural language processing techniques and converted into a format suitable for the generative AI model. The generative AI model generates answers to the user's questions and sends the results to the user's terminal.

[0542] As a concrete example, if a user enters "Teach me the basics of differentiation" into their terminal, the server analyzes this input and sends the prompt "Please explain the basics of differentiation" to the generative AI model. The generative AI model generates an explanation of the basics of differentiation and returns it to the user's terminal. The user can then view this explanation on their terminal and continue learning.

[0543] This system allows users to receive a personalized learning experience and get quick and accurate answers.

[0544] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0545] Step 1:

[0546] The user enters a question using a terminal. The entered question is sent to the server through the terminal's interface. The input data is in text format and reflects the user's learning needs.

[0547] Step 2:

[0548] The server analyzes the user's question using natural language processing techniques. Specifically, it uses a Python natural language processing library to tokenize the input text and perform semantic analysis. This process helps understand the intent of the question and generates a prompt suitable for the generative AI model.

[0549] Step 3:

[0550] The server uses the generated prompt to query the generative AI model. The generative AI model receives the prompt as input and generates relevant information and answers. The generative AI model is built using TensorFlow and generates answers based on pre-trained data.

[0551] Step 4:

[0552] The responses obtained from the generative AI model are received by the server in text format. The server then formats these responses into a format that is easy for the user to understand and sends them to the device.

[0553] Step 5:

[0554] The terminal displays the answers received from the server to the user. The user can view the answers on the terminal screen and proceed with their learning. The displayed information is customized according to the user's learning needs.

[0555] (Example 2)

[0556] Next, we will describe Example 2 of Form 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".

[0557] Traditional educational support systems have faced challenges in enabling learners to quickly and accurately obtain detailed information on specific subjects. Furthermore, the lack of adequate information tailored to each learner's level of understanding makes it difficult to provide optimal learning support for individual students.

[0558] 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.

[0559] In this invention, the server includes an interactive program using an information processing device, means for applying the interactive program in the field of education to provide learners with responses to inquiries and guidance, and means for the interactive program to provide information on a specific subject and support learners in deepening their knowledge. As a result, learners can quickly obtain detailed information on a specific subject and information can be provided according to their level of understanding.

[0560] An "information processing device" is a device that has the functions of receiving, processing, and transmitting data, and includes hardware and software for executing interactive programs.

[0561] An "interactive program" is software that generates responses and provides information in response to user input, and is used in the field of education to support learners.

[0562] The "education field" refers to activities and areas that provide knowledge and skills to learners and support their learning.

[0563] A "learner" refers to an individual who seeks to acquire knowledge or skills related to a specific subject.

[0564] An "inquiry" refers to a question or request that a learner makes to an interactive program in order to obtain specific information.

[0565] "Response" refers to the information or instructions that an interactive program provides in response to a learner's inquiry.

[0566] A "subject" refers to a specific topic or subject that a learner is interested in and wishes to study.

[0567] "Support for deepening knowledge" refers to the information and instruction provided to help learners deepen their understanding of a particular subject.

[0568] This invention relates to a system for executing interactive programs using an information processing device. The server generates information based on user prompts, utilizing a generative AI model. Specifically, the server uses natural language processing technology to analyze user input and perform calculations to generate relevant information. A general-purpose natural language processing model can be used as the generative AI model.

[0569] The user enters a prompt message through the terminal. For example, they might enter a prompt message such as, "Tell me about the themes in Shakespeare's 'Hamlet'." The terminal sends this prompt message to the server. The server passes the received prompt message to a generation AI model, which generates information based on the prompt message. The generated information is sent from the server to the terminal and displayed to the user.

[0570] This system allows users to quickly obtain detailed information on specific topics. Furthermore, by utilizing generative AI models, it becomes possible to provide information tailored to the user's level of understanding, offering optimal learning support for individual learners.

[0571] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0572] Step 1:

[0573] The user enters a prompt using the terminal. For example, they might enter a specific question such as, "Tell me about the main events of the French Revolution." The entered prompt is then ready to be sent to the server through the terminal's interface.

[0574] Step 2:

[0575] The terminal sends the prompt text entered by the user to the server. Here, the terminal converts the prompt text into the appropriate data format and sends the data to the server using a communication protocol. The input is the prompt text, and the output is the transmission to the server.

[0576] Specific actions:

[0577] The terminal receives user input, converts the data into packets, and sends them to the server over the network.

[0578] Step 3: The server passes the prompt message to the AI ​​model.

[0579] The server parses the received prompt message and prepares it for the generative AI model. The server converts the prompt message into a format that the generative AI model can understand. The server inputs the prompt message into the generative AI model and waits for the model to process the information.

[0580] Step 4: The generative AI model generates information based on the prompt.

[0581] The generative AI model receives a prompt as input and generates relevant information. The model uses natural language processing techniques to generate the best possible answer to the user's question. Specifically, the model references a large dataset, extracts relevant information, and generates the answer in natural language.

[0582] Step 5: The server receives the generated information and sends it to the terminal.

[0583] The server receives the information returned from the generated AI model and sends it to the user's terminal. The server formats the information appropriately and sends the data to the terminal using a communication protocol. The server verifies the accuracy of the information and retrieves additional information as needed.

[0584] Step 6: The device displays information to the user.

[0585] The device displays information received from the server to the user. Specifically, it displays information generated on the device's screen, making it easy for the user to read and review. The user can then proceed with their learning based on the displayed information.

[0586] (Application Example 2)

[0587] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0588] Modern learners are required to acquire information on specific topics and subjects quickly and efficiently. However, traditional education systems face challenges in providing information tailored to individual learners' interests and levels of understanding, as well as in enabling real-time information acquisition. Furthermore, the lack of sufficient learning support utilizing portable information terminals and visual display devices means that learners cannot obtain in-depth information the moment they become interested.

[0589] 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.

[0590] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for installing the interactive program on a portable information terminal or visual display device, converting the user's voice input into text, acquiring information using a generative AI model, and displaying the results, and means for the interactive program to provide information in real time based on the user's interests. This makes it possible for learners to obtain in-depth information the moment they become interested.

[0591] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[0592] An "interactive program" is software that enables communication with users using natural language, providing information and answering questions.

[0593] A "portable information terminal" is a portable electronic device used for acquiring information and communicating.

[0594] A "visual display device" is a device used to visually display information and to confirm information.

[0595] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate new information or content based on input data.

[0596] "Real-time" refers to a state where information processing and communication occur instantly, and results are obtained without delay.

[0597] "Converting user voice input to text" is the process of converting a user's spoken words into text information using speech recognition technology.

[0598] The system for implementing this invention is centered around an interactive program using artificial intelligence. The server receives voice input from the user and uses speech recognition software to convert it into text. Specifically, speech recognition technologies such as the Google Speech-to-Text API can be used. The converted text is input into a generative AI model (e.g., OpenAI GPT-3) to generate information in response to the user's request.

[0599] The generated information is displayed on portable information terminals and visual display devices. This allows users to obtain information of interest in real time. For example, if a user uses their smartphone to voice-input "Tell me about the Napoleonic Wars," the information will be displayed immediately.

[0600] This system provides information based on the user's interests, allowing learners to gain in-depth information the moment they become interested. An example of a prompt would be, "Please tell me more about the plot and themes of Shakespeare's 'Hamlet'."

[0601] In this way, the invention can provide information to learners efficiently and effectively, and support the acquisition of knowledge.

[0602] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0603] Step 1:

[0604] The user inputs their question by voice into a portable information terminal or visual display device. The voice input is acquired through the terminal's microphone.

[0605] Step 2:

[0606] The device converts the acquired audio data into text data using speech recognition software (e.g., Google Speech-to-Text API). In this step, the audio waveform is analyzed and the corresponding string is generated. The input is audio data, and the output is text data.

[0607] Step 3:

[0608] The server sends the converted text data to a generating AI model (e.g., OpenAI GPT-3). Here, the server inputs the text data as a prompt into the AI ​​model, which then generates the relevant information. The input is text data, and the output is the generated information.

[0609] Step 4:

[0610] The server sends information obtained from the generated AI model to the terminal. The terminal visually displays the received information to the user. Here, the information is displayed on the screen for the user to review. The input is the generated information, and the output is the visual display.

[0611] Step 5:

[0612] The user can review the displayed information and ask further questions if necessary. At this step, the user can return to step 1 by entering a new question via voice input.

[0613] (Example 3)

[0614] Next, we will describe Embodiment 3 of Embodiment Example 3. 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".

[0615] Traditional interactive programs have faced challenges in providing appropriate information tailored to the learner's level of understanding, hindering efficient knowledge acquisition. Furthermore, they lack the ability to automatically generate appropriate answers to learners' questions, limiting the effectiveness of the learning process.

[0616] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0617] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for determining the learner's level of understanding and generating prompt sentences to provide information according to that level of understanding, and means for generating answers based on the prompt sentences using a generation AI model. This enables the provision of appropriate information according to the learner's level of understanding and the automatic generation of answers.

[0618] Artificial intelligence is a technology in which computer systems imitate human intellectual activity, performing tasks such as learning, reasoning, and problem-solving.

[0619] An "interactive program" is software that provides information or answers questions through dialogue with the user.

[0620] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[0621] A "learner" is an individual whose purpose is to acquire knowledge and skills.

[0622] A "prompt sentence" is an instruction sentence input into a generative AI model, and it contains information that forms the basis of the generated response.

[0623] A "generative AI model" is an artificial intelligence technology that generates natural language responses based on a prompt.

[0624] "Comprehension level" is an indicator that shows how well a learner understands a particular piece of knowledge or skill.

[0625] The embodiment for carrying out this invention is centered on an interactive program using artificial intelligence. The server receives input from the user and generates an appropriate response using a generative AI model. Specifically, the server receives a question sent from the user's terminal and analyzes its content. Based on the analysis results, it determines the user's level of understanding and generates a prompt sentence corresponding to that level of understanding.

[0626] The generated prompt is sent to a generative AI model. This model generates a natural language response based on the prompt. The generated response is returned to the user's terminal via the server. This allows the user to efficiently obtain information tailored to their level of understanding.

[0627] The hardware used includes a server and a user terminal, while the software includes a generative AI model. The generative AI model generates responses from prompt sentences using natural language processing techniques.

[0628] For example, if a user asks, "How do I find the solutions to a quadratic equation?", the server analyzes this question and, if it determines that the user is a beginner, generates a prompt such as, "Please explain the basic methods for solving quadratic equations." Based on this prompt, the AI ​​model generates an answer such as, "There are several ways to find the solutions to a quadratic equation, including factorization, completing the square, and using the quadratic formula," and provides it to the user.

[0629] In this way, the invention enables the provision of information tailored to the learner's level of understanding, thereby supporting efficient learning. The flow of the specific processing in Example 3 will be explained using Figure 15.

[0630] Step 1:

[0631] The user enters a question through their terminal. For example, they might enter a question like, "How do I find the solutions to a quadratic equation?" This input is then sent to the server.

[0632] Step 2:

[0633] The server receives questions from users and analyzes their content. Natural language processing techniques are used for the analysis to extract the intent and keywords of the questions. Based on these analysis results, data is generated to determine the user's level of understanding.

[0634] Step 3:

[0635] The server determines the user's level of understanding based on the analysis results. This determination takes into account past interaction data and the complexity of the questions. Using this determination, the server generates prompts appropriate to the user's level of understanding. For example, for a beginner, it might generate a prompt such as "Please explain the basic methods for solving quadratic equations."

[0636] Step 4:

[0637] The server sends the generated prompt to the generation AI model. The generation AI model receives the prompt as input and generates a natural language response based on it. During this generation process, data calculations are performed according to the content of the prompt.

[0638] Step 5:

[0639] The AI ​​model generates an answer which is then returned to the server. The server receives this answer and sends it to the user's device. The user can then view this answer through their device. For example, an answer such as, "There are several ways to find the solutions to a quadratic equation, including factorization, completing the square, and using the quadratic formula," might be provided.

[0640] This series of processes allows users to efficiently obtain information tailored to their level of understanding.

[0641] (Application Example 3)

[0642] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0643] Traditional education systems have faced challenges in providing optimal learning materials based on individual learners' comprehension levels and learning histories, and in generating appropriate answers to learners' questions immediately. This can hinder learners' efficient learning.

[0644] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0645] In this invention, the server includes means for analyzing the learner's past learning history using an interactive program with artificial intelligence and recommending the most suitable learning materials; means for instantly generating answers to questions from the learner and providing additional information to deepen understanding; and means for generating answers to questions from the learner using a generative AI model. This enables the provision of optimal learning materials tailored to the learner's individual level of understanding and prompt and appropriate answers to questions.

[0646] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[0647] An "interactive program" is software that provides information and answers questions through dialogue with the user using natural language.

[0648] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[0649] A "learner" is an individual who seeks to acquire specific knowledge or skills.

[0650] "Means of providing answers to questions and guidance" refers to methods of providing appropriate information in response to learners' questions and supporting their learning.

[0651] "Specific subjects or topics" refer to specific topics or fields that are covered in education or training.

[0652] "Methods for analyzing learners' past learning history" refer to methods for evaluating what learners have learned so far, their progress, and understanding their level of comprehension.

[0653] "A method for recommending the most suitable learning materials" refers to a method of selecting and presenting the most effective learning materials based on the learner's level of understanding and learning history.

[0654] A "generative AI model" is an algorithm or model that uses artificial intelligence technology to perform natural language processing and data generation.

[0655] "Means of providing additional information" refers to methods of providing supplementary information in addition to basic information in order to deepen learners' understanding.

[0656] To implement this invention, a server and a user terminal are required. The server runs an interactive program using artificial intelligence and analyzes the learner's past learning history. Specifically, the server retrieves the learner's history data from a database and evaluates their level of understanding using a machine learning algorithm. Software such as Python or TensorFlow can be used for this purpose.

[0657] The server recommends the most suitable learning materials based on the analysis results. These recommendations are displayed on the user's device using a web framework such as Flask. When the user enters a question, the server instantly generates an answer using a generative AI model. This model includes algorithms that leverage natural language processing techniques.

[0658] The user terminal is a device such as a smartphone or tablet that receives information provided by the server and displays it to the user. The user can input questions through the terminal and receive answers from the server.

[0659] For example, if a user enters "I want to learn the basics of differential and integral calculus," the server analyzes the user's past learning history and recommends basic differential and integral calculus learning materials. Also, if the user asks "Can you explain the basic formulas for differentiation?", the generative AI model instantly generates an answer and provides it to the user.

[0660] An example of a prompt message would be: "Recommend the best learning materials for a user who wants to learn the basics of differential and integral calculus. Also, answer questions about the fundamental formulas of differentiation."

[0661] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[0662] Step 1:

[0663] The user enters the topic they want to learn about using their device. The entered data is sent to the server. The server receives this input and retrieves the user's learning history data from its database.

[0664] Step 2:

[0665] The server evaluates the user's understanding based on the acquired learning history data. Here, machine learning algorithms are executed using Python and TensorFlow to analyze the user's past learning patterns. The input is the learning history data, and the output is the user's understanding evaluation result.

[0666] Step 3:

[0667] The server selects the most suitable learning materials based on the comprehension assessment results. The selected learning material information is sent to the user's terminal using Flask. The input is the comprehension assessment results, and the output is the recommended learning material information.

[0668] Step 4:

[0669] The user reviews the recommended learning materials on their device and then enters a question. The entered question is sent to the server. The server receives this question and uses a generative AI model to generate an answer.

[0670] Step 5:

[0671] The server generates answers to questions using a generative AI model. Here, natural language processing techniques are utilized to input prompts into the generative AI model. The input is the user's question, and the output is the generated answer.

[0672] Step 6:

[0673] The server sends the generated response to the user's terminal. The user can review the response on the terminal and ask additional questions if necessary. The input is the generated response, and the output is the display of the response to the user.

[0674] 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.

[0675] "Example of form 1"

[0676] One embodiment of the present invention provides a chatbot incorporating an emotion engine. This emotion engine recognizes emotions from the user's text or voice input. For example, if the user enters the phrase "I don't understand this problem," the emotion engine recognizes the user's frustration.

[0677] "Example of form 2"

[0678] After the emotion engine recognizes the user's emotions, the chatbot's response is adjusted accordingly. For example, if the chatbot detects that the user is feeling frustrated, it will respond in a more polite tone and provide additional explanations or support if necessary.

[0679] "Example of form 3"

[0680] Furthermore, the emotion engine adjusts how it educates and trains learners. For example, if it perceives that a user is agitated, the chatbot will move to a more advanced topic. Conversely, if it perceives that a user is confused, the chatbot will return to a more basic topic.

[0681] The following describes the processing flow for each example of the form.

[0682] "Example of form 1"

[0683] Step 1: The user sends a text or voice message to the chatbot.

[0684] Step 2: The emotion engine recognizes emotions from the user's message. For example, it recognizes the user's frustration from the phrase "I don't understand this problem."

[0685] "Example of form 2"

[0686] Step 1: The emotion engine recognizes the user's emotions.

[0687] Step 2: The chatbot adjusts its response based on the emotion engine's output. For example, if it perceives that the user is feeling frustrated, the chatbot will respond in a more polite tone and provide additional explanations or support if needed.

[0688] "Example of form 3"

[0689] Step 1: The emotion engine recognizes the user's emotions.

[0690] Step 2: The emotion engine adjusts how it educates and trains the learner. For example, if it perceives the user as agitated, the chatbot moves to a more advanced topic. Conversely, if it perceives the user as confused, the chatbot returns to a more basic topic.

[0691] (Example 1)

[0692] Next, we will describe Example 1 of Form 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".

[0693] Traditional interactive programs in education and training have struggled to provide appropriate instruction tailored to each learner's individual level of understanding and emotional state. Furthermore, they have limitations in their ability to generate quick and detailed answers to learners' questions. This has resulted in reduced learner efficiency and insufficient learning support that meets individual needs.

[0694] 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.

[0695] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for recognizing the learner's emotions using an emotion analysis function and generating appropriate feedback, and means for generating detailed answers to the learner's questions using a generative model. This makes it possible to provide appropriate guidance tailored to the learner's individual level of understanding and emotions, and to generate rapid and detailed answers.

[0696] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[0697] An "interactive program" is software that enables natural language interaction with the user and has functions for question answering and instruction.

[0698] "Education and training" refers to the activities and processes by which learners acquire new knowledge and skills.

[0699] A "learner" refers to an individual who receives education or training, with the aim of improving their knowledge and skills.

[0700] "Emotion analysis functionality" is a technology that recognizes emotions from a user's text or voice and generates an appropriate response based on those emotions.

[0701] A "generative model" is an algorithm that generates new data or information based on input data, and is particularly used in natural language processing.

[0702] "Feedback" refers to evaluation and guidance information provided regarding a learner's behavior and responses, intended to promote improvement in their learning.

[0703] In this embodiment of the invention, the server executes an interactive program using artificial intelligence. The server uses a common library as a natural language processing library to analyze text input from the user. Specifically, the server uses Python and leverages natural language processing libraries such as NLTK and spaCy to understand the user's intent and the content of their questions. Furthermore, for sentiment analysis, it recognizes the user's emotions using the sentiment analysis library TextBlob and a machine learning framework.

[0704] The terminal's role is to receive input from the user and send it to the server. When the user enters a prompt such as "Teach me the basics of differentiation," the terminal sends that text to the server. The server uses a common generative model as its generative AI model to generate a detailed answer to the user's question. This generative AI model uses natural language generation technology to create an appropriate answer to the user's question.

[0705] Users can receive responses from the server through their device and proceed with their learning. For example, if a user inputs "I don't understand this problem," the server uses sentiment analysis to recognize the user's frustration and generate appropriate feedback. This allows users to learn at their own pace.

[0706] The flow of the specific processing in Example 1 will be explained using Figure 17.

[0707] Step 1:

[0708] The user enters questions or requests via text or voice through the terminal. For example, they might enter a prompt such as, "Teach me the basics of differentiation." The terminal then sends this input to the server as text data.

[0709] Step 2:

[0710] The server analyzes the received text data using natural language processing libraries. Specifically, it uses NLTK and spaCy to process the data in order to understand the user's intent and the content of the question. This analysis identifies the subject and purpose of the user's question.

[0711] Step 3:

[0712] The server recognizes the user's emotions using sentiment analysis capabilities. Using TextBlob and machine learning frameworks, it extracts emotions from the input text to determine the user's emotional state. For example, if the user inputs "I don't understand this problem," it detects frustration.

[0713] Step 4:

[0714] The server uses a generative AI model to generate detailed answers to user questions. The generative model generates appropriate answers in natural language based on analyzed intent and sentiment. For example, it might create an explanation of the basics of differentiation, including concrete examples.

[0715] Step 5:

[0716] The server sends the generated answer to the terminal. The terminal displays this answer to the user. The user can then proceed with their learning based on the displayed information. This allows the user to learn at their own pace.

[0717] (Application Example 1)

[0718] Next, we will describe Application Example 1 of Form 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."

[0719] Traditional education and training systems have struggled to provide appropriate instruction in real time, tailored to learners' emotions and levels of understanding. Furthermore, the work environment lacked the means to obtain immediate feedback through visual guidance. This resulted in challenges such as decreased learner motivation and hindered efficient learning.

[0720] 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.

[0721] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for incorporating an emotion recognition engine to recognize the learner's emotions, and means for providing real-time instruction through a visual device in the work environment. This enables the provision of appropriate instruction in real time according to the learner's emotions and level of understanding, and allows for immediate feedback in the work environment.

[0722] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[0723] An "interactive program" is software that provides information and answers questions through dialogue with the user.

[0724] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[0725] An "emotion recognition engine" is a technology that analyzes and recognizes emotions from a user's text or voice.

[0726] A "visual device" is a device that allows a user to receive information visually, and smart glasses are an example of such a device.

[0727] "Providing real-time guidance" means providing appropriate guidance and feedback immediately according to the user's situation.

[0728] A "learner" is an individual who seeks to acquire knowledge or skills.

[0729] "Feedback" refers to evaluations and guidance provided regarding a user's actions and circumstances.

[0730] The system for implementing this invention is centered around an interactive program using artificial intelligence. The server incorporates an emotion recognition engine that analyzes and recognizes emotions from the user's text and voice input. This makes it possible to provide appropriate guidance and feedback in real time, tailored to the user's emotions.

[0731] Specifically, the server uses an emotion recognition library developed with Python (e.g., OpenAI's Sentiment Analysis API) to process user input data. Voice input is converted to text using the Google Speech-to-Text API, and then emotion analysis is performed. Based on the analysis results, the interactive program uses a chatbot framework such as Rasa to generate an appropriate response to the user.

[0732] Smart glasses (e.g., Google Glass) are used as the device, allowing users to receive information visually. This enables immediate feedback even in the work environment.

[0733] For example, if a user asks a question via voice, such as "I don't know how to attach this part," the server will sense the user's anxiety, and the interactive program will instruct them, "Please stay calm. First, attach part A to part B."

[0734] Examples of prompts for a generative AI model are as follows:

[0735] User input: "I don't know how to install this part."

[0736] Sentiment analysis result: "Anxiety"

[0737] Chatbot response: "Please stay calm. First, attach part A to part B."

[0738] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[0739] Step 1:

[0740] The user provides voice input through the device. The device converts the user's voice into text data using the Google Speech-to-Text API. The input for this step is voice data, and the output is text data.

[0741] Step 2:

[0742] The server receives text data and analyzes the user's emotions using an emotion recognition engine. Specifically, it uses OpenAI's emotion analysis API to extract emotions from the text data. The input for this step is text data, and the output is the emotion analysis result.

[0743] Step 3:

[0744] Based on the sentiment analysis results, the server uses a chatbot framework such as Rasa to generate an appropriate response to the user. The input for this step is the sentiment analysis results, and the output is the chatbot's response.

[0745] Step 4:

[0746] The device provides the user with the generated chatbot responses visually or audibly. Specifically, this may involve displaying text through smart glasses or providing voice guidance. The input in this step is the chatbot's response, and the output is feedback to the user.

[0747] Step 5:

[0748] The user proceeds with the work based on the feedback provided. If necessary, they can ask further questions and repeat the process. The input in this step is the user's feedback, and the output is the user's actions.

[0749] (Example 2)

[0750] Next, we will describe Example 2 of Form 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".

[0751] Traditional interactive programs have faced challenges in providing responses that take into account the user's emotions and insufficient information tailored to the learner's level of understanding. Furthermore, they have difficulty providing detailed information on specific topics and generating appropriate responses based on user input.

[0752] 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.

[0753] In this invention, the server includes means for providing an interactive program using an information processing device, means for recognizing the user's emotions and adjusting the response using emotion recognition technology, and means for analyzing the user's input and generating an appropriate response using a generative model. This makes it possible to adjust the response according to the user's emotions and provide information according to the learner's level of understanding.

[0754] An "information processing device" is a device used for inputting, processing, and outputting data, and includes devices such as computers and servers.

[0755] An "interactive program" is software that provides information and answers questions through dialogue with the user.

[0756] The "field of education and training" is the area in which activities are carried out to help learners acquire knowledge and skills.

[0757] A "learner" is an individual or group whose purpose is to acquire knowledge or skills.

[0758] A "subject or field" refers to a specific area of ​​knowledge or topic, and is the content that learners are supposed to study.

[0759] "Emotion recognition technology" refers to technology for analyzing and recognizing a user's emotions, and includes technology for determining emotions from voice and text.

[0760] A "generative model" is an algorithm or technique for generating new data or responses based on input data.

[0761] "Adjusting responses" means changing the information provided and how it is presented according to the user's emotions and circumstances.

[0762] This invention is a system for implementing an interactive program using an information processing device. The server utilizes a generative AI model to analyze user input and generate an appropriate response. Specifically, it uses natural language processing technology to understand the user's prompt and generates a response using a generative model. Furthermore, it uses emotion recognition technology to recognize the user's emotions and adjust the response accordingly.

[0763] The server receives prompt messages entered by the user through the terminal. For example, if the user enters "Tell me about Renaissance art," the server analyzes this input and provides information about representative artists and works of the Renaissance. Similarly, if the user asks "What is the theme of this poem?", the server analyzes the content of the poem and generates information about its theme.

[0764] By using emotion recognition technology, the server can determine the user's emotions and adjust the tone and content of its response. For example, if the server detects that the user is confused, it will offer additional support to help the user understand, such as "Shall I explain this topic in more detail?"

[0765] In this way, the server adjusts its responses to the user's emotions and provides information tailored to the learner's level of understanding. This allows learners to deepen their knowledge of specific subjects and fields.

[0766] The flow of the specific processing in Example 2 will be explained using Figure 19.

[0767] Step 1:

[0768] The user enters a prompt message through the terminal. For example, they might enter a question like, "Tell me about Renaissance art." This input is then sent to the server.

[0769] Step 2:

[0770] The server parses the received prompt message. Using natural language processing techniques, it understands the intent and content of the input text. This analysis identifies what information the user is seeking. As a result of the analysis, data regarding the user's intent is generated.

[0771] Step 3:

[0772] The server uses emotion recognition technology to recognize the user's emotions. It extracts emotional keywords and context from the input text to determine the user's emotional state. For example, if it determines that the user is confused, that information will influence the response generation in the next step.

[0773] Step 4:

[0774] The server uses a generative AI model to generate appropriate responses to user questions. Based on the analysis results and sentiment recognition results, it creates responses that provide information aligned with the user's intent. For example, a response containing detailed information about Renaissance art might be generated.

[0775] Step 5:

[0776] The server adjusts the generated response. It modifies the tone and content of the response according to the user's emotions. For confused users, it adjusts to provide additional explanations in a more polite and helpful tone.

[0777] Step 6:

[0778] The server sends a pre-arranged response to the terminal. The user can then view the chatbot's response on their terminal and continue asking further questions. This allows the user to obtain the necessary information.

[0779] (Application Example 2)

[0780] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0781] Traditional interactive programs in education and training have struggled to provide personalized learning experiences due to their inability to flexibly adapt to learners' emotions and levels of understanding. Furthermore, even when providing information on specific topics, the generated information sometimes failed to fully meet learners' needs. This resulted in challenges such as decreased learner motivation and reduced learning effectiveness.

[0782] 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.

[0783] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for recognizing the user's emotions using an emotion recognition engine and adjusting the response according to those emotions, and means for generating information based on prompt sentences using a generative AI model. This makes it possible to provide a personalized learning experience that is tailored to the learner's emotions and level of understanding, and to provide information on specific topics more appropriately.

[0784] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[0785] An "interactive program" is software that engages in natural language dialogue with the user to provide information and answer questions.

[0786] "Education and training" refers to the activities and processes by which learners acquire new knowledge and skills.

[0787] A "participant" is an individual who participates in an educational or training program and engages in learning.

[0788] "Means of providing answers to questions and guidance" refers to methods and techniques for generating appropriate answers to learners' questions and supporting their learning.

[0789] "Specific topics or subjects" refer to specific fields or topics that the learner is interested in.

[0790] An "emotion recognition engine" is a technology that analyzes and identifies emotions from a user's voice or text.

[0791] A "generative AI model" is an artificial intelligence model that generates natural language text based on input prompts.

[0792] A "prompt message" is text containing instructions or questions that are input into a generative AI model.

[0793] The system for implementing this invention mainly consists of a server and a user terminal. The server executes an interactive program using artificial intelligence and communicates with the user terminal. The user terminal is a device such as a smartphone or tablet, and interacts with the interactive program through an interface.

[0794] The server analyzes the user's emotions using an emotion recognition engine. Specifically, it receives the user's voice and text input and processes the data to identify their emotions. This process utilizes emotion recognition technologies such as the Microsoft Azure Emotion API.

[0795] Furthermore, the server uses a generative AI model to generate information based on user prompts. OpenAI GPT-3 is one example of a generative AI model used. A prompt is a text containing information or a question the user wants to know, such as "Please provide detailed information about World War II."

[0796] When a user requests information on a specific topic, the server uses a generative AI model to generate relevant information and sends it to the user's device. If the user's emotions indicate frustration, the server adjusts its response, providing additional explanations in a more polite tone. This allows the user to have a personalized learning experience.

[0797] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[0798] Step 1:

[0799] The user uses a terminal to enter a prompt requesting information on a specific topic. The entered prompt might be in the format of, for example, "Please provide detailed information about World War II." The terminal then sends this prompt to the server.

[0800] Step 2:

[0801] The server parses the received prompt and inputs it into a generative AI model. The generative AI model (e.g., OpenAI GPT-3) generates relevant information based on the prompt. The generated information is output to the server as an answer to the prompt.

[0802] Step 3:

[0803] The server receives voice and text input from the user's device and analyzes the user's emotions using an emotion recognition engine. It processes the input data to identify the user's emotional state (e.g., frustration, excitement).

[0804] Step 4:

[0805] The server adjusts its response based on the generated information and the user's emotional state. For example, if the user is feeling frustrated, the server will generate a response in a more polite tone that includes additional explanations.

[0806] Step 5:

[0807] The server sends a tailored response to the user's device. The user can then receive personalized information and responses through their device, enabling them to have a better learning experience.

[0808] (Example 3)

[0809] Next, we will describe Embodiment 3 of Embodiment Example 3. 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".

[0810] Traditional interactive programs have failed to adequately provide information tailored to learners' levels of understanding and emotional states, making it difficult to address individual learners' needs. Furthermore, the automatic and appropriate generation of answers to learners' questions has been insufficient, preventing the maximization of learning effectiveness.

[0811] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0812] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for analyzing the learner's past dialogue data and evaluating their level of understanding, means for analyzing the learner's emotional state and adjusting the method of information provision, and means for generating prompt sentences and appropriate answers using a generative model. This enables personalized information provision according to the learner's level of understanding and emotional state, and realizes the automatic and appropriate generation of answers to questions from the learner.

[0813] Artificial intelligence is a technology in which computer systems imitate human intellectual behavior, enabling them to learn, reason, and solve problems.

[0814] An "interactive program" is software that provides information and answers questions through dialogue with the user.

[0815] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[0816] A "participant" is an individual who participates in an educational or training program and engages in learning.

[0817] A "subject or topic" refers to a specific area of ​​knowledge or topic that is covered in education or training.

[0818] "Comprehension level" is an indicator that shows how well a learner understands a particular piece of knowledge or skill.

[0819] "Emotional state" refers to the learner's psychological state and includes emotions such as excitement and confusion.

[0820] A "generative model" is an algorithm or technique for generating new data based on input data.

[0821] A "prompt statement" is an instruction given to a generative model, providing guidelines for obtaining a specific output.

[0822] A description of embodiments for carrying out this invention will be given.

[0823] The server runs an interactive program using artificial intelligence. This program utilizes a generative AI model to generate responses based on user input. Specifically, it analyzes user input using natural language processing techniques and understands their intent. A general natural language generation technique is used as the generative AI model.

[0824] The terminal collects the user's past conversation data and uses machine learning algorithms to evaluate the user's level of understanding. Based on this evaluation, the server adjusts the depth and detail of the information provided to the user. Furthermore, the terminal performs sentiment analysis on the input text to analyze the user's emotional state. This allows it to determine whether the user is agitated or confused and appropriately adjust the way information is delivered.

[0825] Users interact with interactive programs through their terminals. For example, if a user asks, "How do I find the solutions to a quadratic equation?", the server uses a generative AI model to generate a prompt and provide an appropriate answer. An example of a prompt might be, "The user is asking about how to solve a quadratic equation. Please explain the basic solution method for beginners."

[0826] This system allows users to receive personalized information tailored to their level of understanding and emotional state, maximizing learning effectiveness. The flow of specific processing in Example 3 will be explained using Figure 21.

[0827] Step 1:

[0828] Users input questions and requests through their terminals. For example, they might input a specific question like, "Please tell me how to find the solutions to a quadratic equation." This input serves as the starting point for the system's processing.

[0829] Step 2:

[0830] The server analyzes the input received from the user. Using natural language processing techniques, it tokenizes the input text and performs grammatical analysis to understand the user's intent. This analysis clarifies the meaning of the input and extracts the information necessary for the next processing step.

[0831] Step 3:

[0832] The terminal references the user's past conversation data and uses machine learning algorithms to assess the user's level of understanding. This assessment is based on the user's past questions and answers to determine whether the user is a beginner or an advanced user. This result is used to determine the depth of information provided by the server.

[0833] Step 4:

[0834] The server uses an emotion engine to analyze the user's emotional state. It performs sentiment analysis on the input text to determine whether the user is agitated or confused. This analysis is used to adjust the way information is delivered.

[0835] Step 5:

[0836] The server generates prompt sentences to be input into the generative AI model. These prompt sentences are adjusted according to the user's level of understanding and emotional state. For example, it might say, "The user is asking about solving quadratic equations. Please explain the basic solution method for beginners." These prompt sentences become the input to the generative AI model.

[0837] Step 6:

[0838] The server generates responses based on prompts using a generative AI model. The generative AI model receives prompts as input and generates appropriate responses. These responses include specific explanations and guidance regarding the user's questions.

[0839] Step 7:

[0840] The device displays the generated answer to the user. The user can receive the answer from the chatbot and deepen their understanding. For example, the chatbot may provide a specific explanation such as, "Quadratic equations can be solved using methods such as completing the square or factorization."

[0841] (Application Example 3)

[0842] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0843] In the field of modern education and training, there is a demand for flexible educational content that is tailored to each learner's individual level of understanding and emotional state. However, conventional systems have struggled to analyze learners' emotions and level of understanding in real time and provide appropriate learning content based on that analysis. This has hindered learners from efficiently acquiring knowledge.

[0844] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0845] In this invention, the server includes means for analyzing the learner's emotional state using an interactive program with artificial intelligence, means for generating learning content suitable for the learner using a generative AI model, and means for inputting prompt sentences into the generative AI model to generate learning content. This makes it possible to provide optimal educational content that corresponds to the learner's level of understanding and emotions.

[0846] "Artificial intelligence" is a technology in which computers imitate human intelligence and perform learning, reasoning, and problem-solving.

[0847] An "interactive program" is software that provides information or answers questions through natural dialogue with the user.

[0848] The "field of education and training" refers to the activities and processes by which learners acquire new knowledge and skills.

[0849] A "learner" refers to an individual who seeks to acquire specific knowledge or skills.

[0850] "Emotional state" refers to the learner's psychological state and changes in their emotions.

[0851] A "generative AI model" is an artificial intelligence model that generates new data or content based on given input.

[0852] A "prompt statement" is an instruction or question given to a generative AI model to obtain a specific output.

[0853] "Learning content" refers to educational materials and information that learners use to acquire knowledge and skills.

[0854] The system for carrying out this invention includes a server and a user terminal. The server executes an interactive program using artificial intelligence and receives input from the user terminal. The user terminal is a device such as a smartphone or a head-mounted display, and provides an interface with the user.

[0855] The server uses an emotion recognition engine (e.g., Microsoft Azure Emotion API) to analyze the user's voice and facial expression data and evaluate the user's emotional state. Based on this evaluation, the server uses a generative AI model (e.g., OpenAI GPT-3) to generate learning content suitable for the user. The generative AI model can generate specific learning content by inputting prompts.

[0856] For example, if a user asks, "Please explain the basics of differential and integral calculus," the server detects confusion from the user's facial expression. In this case, it prompts the generative AI model with "Please explain the basic concepts of differential and integral calculus in a way that is easy for beginners to understand," and sends the generated content to the user's device. This allows the user to receive an optimal learning experience tailored to their level of understanding and emotional state.

[0857] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[0858] Step 1:

[0859] The user enters a question via a terminal. The terminal captures the user's voice and facial expression data and sends it to the server. The input consists of the user's question text and voice / facial expression data.

[0860] Step 2:

[0861] The server inputs received audio and facial expression data into an emotion recognition engine to analyze the user's emotional state. For data processing, audio data is converted to text, and facial expression data is analyzed using image analysis. The output is an evaluation result indicating the user's emotional state.

[0862] Step 3:

[0863] The server generates and inputs prompt sentences into the generative AI model based on the user's question text and the evaluation of their emotional state. Specifically, prompt sentences are generated such as "Please explain the basic concepts of differential and integral calculus in a way that is easy for beginners to understand." The input is the prompt sentence, and the output is the generated training content.

[0864] Step 4:

[0865] The generative AI model generates appropriate training content based on prompt text. As a data processing technique, the model uses natural language processing to construct the content. The output is training content to be provided to the user.

[0866] Step 5:

[0867] The server sends the generated learning content to the user's terminal. The terminal displays the content to the user and assists with learning. Specifically, the terminal presents the content in text or audio. The output is the learning content received by the user.

[0868] (Other examples)

[0869] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[0870] 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.

[0871] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> 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.

[0872] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[0873] 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.

[0874] [Third Embodiment]

[0875] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0876] 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.

[0877] 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).

[0878] 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.

[0879] 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.

[0880] 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).

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0887] "Example of form 1"

[0888] One embodiment of the present invention involves the application of an artificial intelligence-powered chatbot in the field of education and training. This chatbot provides students with answers to questions and guidance. For example, it could explain how to solve a math problem or provide information to deepen their understanding of a science experiment.

[0889] "Example of form 2"

[0890] Furthermore, chatbots can provide information on specific topics and subjects, helping learners deepen their knowledge. For example, they can provide detailed information about specific periods or events in history, or information to help interpret literary works.

[0891] "Example of form 3"

[0892] Furthermore, the chatbot adjusts how information is provided according to the learner's level of understanding. For example, if the learner is a beginner, it will provide basic information, and if the learner is advanced, it will provide more in-depth information.

[0893] "Example of form 4"

[0894] Furthermore, the chatbot automatically generates answers to learners' questions. For example, if a learner asks, "How do I find the solutions to a quadratic equation?", the chatbot will generate an answer explaining how to find the solutions to a quadratic equation.

[0895] The following describes the processing flow for each example of the form.

[0896] "Example of form 1"

[0897] Step 1: The learner enters a question into the chatbot. For example, they might enter the question, "How do I find the solutions to a quadratic equation?"

[0898] Step 2: The chatbot analyzes the question and generates an appropriate answer. In this case, it generates an answer explaining how to find the solutions to a quadratic equation.

[0899] Step 3: The chatbot provides the learner with the generated response. The learner then uses this response to continue their learning.

[0900] "Example of form 2"

[0901] Step 1: The learner requests information from the chatbot about a specific topic or subject. For example, they might request, "Teach me about Edo period society."

[0902] Step 2: The chatbot analyzes the request and generates appropriate information. In this case, it generates information about Edo period society.

[0903] Step 3: The chatbot provides the learner with the information it has generated. The learner then uses this information to continue their learning.

[0904] "Example of form 3"

[0905] Step 1: The chatbot evaluates the learner's understanding. For example, it evaluates understanding based on the results of tests submitted by the learner or the history of past questions.

[0906] Step 2: The chatbot adjusts how it provides information based on the evaluation results. For example, if it is evaluated as having a low level of understanding, it will start by providing basic information. If it is evaluated as having a high level of understanding, it will provide more in-depth information.

[0907] Step 3: The chatbot provides information to the learner based on the information delivery method it has set up. The learner then proceeds with their learning based on this information.

[0908] "Example of form 4"

[0909] Step 1: The learner enters a question into the chatbot. For example, they might enter the question, "How do I find the solutions to a quadratic equation?"

[0910] Step 2: The chatbot analyzes the question and automatically generates an appropriate answer. In this case, it generates an answer explaining how to find the solutions to a quadratic equation.

[0911] Step 3: The chatbot provides the learner with the generated response. The learner then uses this response to continue their learning.

[0912] (Example 1)

[0913] Next, we will describe Embodiment 1 of 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."

[0914] Traditional information systems in the fields of education and training have faced challenges in providing flexible instruction tailored to the individual understanding and needs of learners. Furthermore, while there is a need to respond quickly and accurately to a wide range of inquiries from learners, there has been a lack of efficient means to achieve this.

[0915] 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.

[0916] In this invention, the server includes means for providing responses to inquiries and guidance to learners using an information processing device employing artificial intelligence, means for generating responses to inquiries using a generative AI model, and means for transmitting the generated responses to the learner's terminal. This enables flexible guidance tailored to the learner's individual level of understanding and needs, and allows for quick and accurate responses to a variety of inquiries.

[0917] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[0918] An "information processing device" is a device that receives data, processes it based on a specific algorithm, and outputs the result.

[0919] A "learner" is an individual who seeks to acquire knowledge and skills in the process of education or training.

[0920] An "inquiry" is a question or request that a learner makes to an information processing device in search of information or guidance.

[0921] A "response" is the answer or information that an information processing device provides in response to a learner's inquiry.

[0922] A "generative AI model" is a model that uses artificial intelligence technology to generate new information or responses based on input data.

[0923] A "terminal" is a device that a user uses to interface with an information processing device.

[0924] This invention is a system that utilizes an artificial intelligence-based information processing device to provide flexible guidance to learners in the fields of education and training. The server generates responses to learner inquiries using a generative AI model. Specifically, the server analyzes the learner's inquiry using natural language processing technology and understands its intent. The analyzed information is sent to the generative AI model as a prompt. For example, a model that excels at natural language generation is used as the generative AI model.

[0925] The server sends the response obtained from the generated AI model to the learner's device. The device displays the received response to the learner, allowing them to review it. This enables learners to obtain information tailored to their level of understanding, thereby improving learning efficiency.

[0926] For example, if a user asks a question via their device such as "Please explain the process of photosynthesis," the server sends this question as a prompt to the generating AI model. The generating AI model generates a response such as "Photosynthesis is the process by which plants use light energy to produce oxygen and glucose from carbon dioxide and water," and the server sends this response to the device. The user can then review the response displayed on their device and ask further questions if necessary.

[0927] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0928] Step 1:

[0929] The user enters a question into the chatbot via their device. The entered question is sent to the server as text data. Specifically, the user enters "Please explain the process of photosynthesis" into the chat interface on their device and clicks the send button.

[0930] Step 2:

[0931] The server receives text data sent by the user. It analyzes the received data using natural language processing techniques to understand the intent of the question. Specifically, the server tokenizes the text and performs grammatical analysis to identify the subject of the question. This analysis result becomes the input for the next step.

[0932] Step 3:

[0933] The server sends prompt messages to the generating AI model based on the analysis results. These prompt messages contain instructions for generating appropriate answers to the user's questions. Specifically, the server generates a prompt message such as "Please explain the process of photosynthesis in detail" and sends it to the generating AI model.

[0934] Step 4:

[0935] The generative AI model generates an answer based on the received prompt. The model utilizes pre-learned knowledge to create a detailed answer to the user's question. Specifically, the generative AI model might produce an answer such as, "Photosynthesis is the process by which plants use light energy to produce oxygen and glucose from carbon dioxide and water." This generated answer then becomes the input for the next step.

[0936] Step 5:

[0937] The server sends the response received from the generated AI model to the user's device. Specifically, the server sends the generated response in text format to the user's device and displays it in the chat interface.

[0938] Step 6:

[0939] The user reviews the answers displayed on the device to deepen their understanding of the questions. Specifically, the user reads the answers displayed on the device screen and enters further questions as needed.

[0940] (Application Example 1)

[0941] Next, we will describe Application Example 1 of Form 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."

[0942] In modern educational and training settings, there is a challenge in that learners often struggle to obtain individually tailored learning experiences. Furthermore, while there is a demand for prompt and accurate answers to learners' questions, traditional methods are sometimes insufficient. Additionally, there is a need to adjust information provision according to the learner's level of understanding, but there is a lack of efficient means to achieve this.

[0943] 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.

[0944] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for the interactive program to provide a learning experience that is individually customized based on the subject selected by the learner, and means for generating answers to the user's questions using a generative AI model. As a result, learners can obtain an individually customized learning experience and receive quick and accurate answers. Furthermore, it becomes possible to adjust the information provided according to the learner's level of understanding.

[0945] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[0946] An "interactive program" is software that provides information or answers questions through dialogue with the user.

[0947] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[0948] A "learner" is an individual who seeks to acquire specific knowledge or skills.

[0949] A "personally customized learning experience" means providing educational content and methods that are tailored to the learner's needs and level of understanding.

[0950] A "generative AI model" is a mathematical model that uses artificial intelligence technology to generate new information or answers.

[0951] A "prompt statement" is an instruction given to a generative AI model to generate specific information.

[0952] The system for carrying out this invention consists of a network environment including a server and user terminals. The server executes an interactive program using artificial intelligence and receives input from the user terminals. The user terminals are devices such as smartphones and head-mounted displays, and provide an interface for the user to interact with the interactive program.

[0953] The server runs generative AI models using software such as Python and TensorFlow. User input is analyzed using natural language processing techniques and converted into a format suitable for the generative AI model. The generative AI model generates answers to the user's questions and sends the results to the user's terminal.

[0954] As a concrete example, if a user enters "Teach me the basics of differentiation" into their terminal, the server analyzes this input and sends the prompt "Please explain the basics of differentiation" to the generative AI model. The generative AI model generates an explanation of the basics of differentiation and returns it to the user's terminal. The user can then view this explanation on their terminal and continue learning.

[0955] This system allows users to receive a personalized learning experience and get quick and accurate answers.

[0956] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0957] Step 1:

[0958] The user enters a question using a terminal. The entered question is sent to the server through the terminal's interface. The input data is in text format and reflects the user's learning needs.

[0959] Step 2:

[0960] The server analyzes the user's question using natural language processing techniques. Specifically, it uses a Python natural language processing library to tokenize the input text and perform semantic analysis. This process helps understand the intent of the question and generates a prompt suitable for the generative AI model.

[0961] Step 3:

[0962] The server uses the generated prompt to query the generative AI model. The generative AI model receives the prompt as input and generates relevant information and answers. The generative AI model is built using TensorFlow and generates answers based on pre-trained data.

[0963] Step 4:

[0964] The responses obtained from the generative AI model are received by the server in text format. The server then formats these responses into a format that is easy for the user to understand and sends them to the device.

[0965] Step 5:

[0966] The terminal displays the answers received from the server to the user. The user can view the answers on the terminal screen and proceed with their learning. The displayed information is customized according to the user's learning needs.

[0967] (Example 2)

[0968] Next, we will describe Example 2 of the morphological example. 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."

[0969] Traditional educational support systems have faced challenges in enabling learners to quickly and accurately obtain detailed information on specific subjects. Furthermore, the lack of adequate information tailored to each learner's level of understanding makes it difficult to provide optimal learning support for individual students.

[0970] 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.

[0971] In this invention, the server includes an interactive program using an information processing device, means for applying the interactive program in the field of education to provide learners with responses to inquiries and guidance, and means for the interactive program to provide information on a specific subject and support learners in deepening their knowledge. As a result, learners can quickly obtain detailed information on a specific subject and information can be provided according to their level of understanding.

[0972] An "information processing device" is a device that has the functions of receiving, processing, and transmitting data, and includes hardware and software for executing interactive programs.

[0973] An "interactive program" is software that generates responses and provides information in response to user input, and is used in the field of education to support learners.

[0974] The "education field" refers to activities and areas that provide knowledge and skills to learners and support their learning.

[0975] A "learner" refers to an individual who seeks to acquire knowledge or skills related to a specific subject.

[0976] An "inquiry" refers to a question or request that a learner makes to an interactive program in order to obtain specific information.

[0977] "Response" refers to the information or instructions that an interactive program provides in response to a learner's inquiry.

[0978] A "subject" refers to a specific topic or subject that a learner is interested in and wishes to study.

[0979] "Support for deepening knowledge" refers to the information and instruction provided to help learners deepen their understanding of a particular subject.

[0980] This invention relates to a system for executing interactive programs using an information processing device. The server generates information based on user prompts, utilizing a generative AI model. Specifically, the server uses natural language processing technology to analyze user input and perform calculations to generate relevant information. A general-purpose natural language processing model can be used as the generative AI model.

[0981] The user enters a prompt message through the terminal. For example, they might enter a prompt message such as, "Tell me about the themes in Shakespeare's 'Hamlet'." The terminal sends this prompt message to the server. The server passes the received prompt message to a generation AI model, which generates information based on the prompt message. The generated information is sent from the server to the terminal and displayed to the user.

[0982] This system allows users to quickly obtain detailed information on specific topics. Furthermore, by utilizing generative AI models, it becomes possible to provide information tailored to the user's level of understanding, offering optimal learning support for individual learners.

[0983] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0984] Step 1:

[0985] The user enters a prompt using the terminal. For example, they might enter a specific question such as, "Tell me about the main events of the French Revolution." The entered prompt is then ready to be sent to the server through the terminal's interface.

[0986] Step 2:

[0987] The terminal sends the prompt text entered by the user to the server. Here, the terminal converts the prompt text into the appropriate data format and sends the data to the server using a communication protocol. The input is the prompt text, and the output is the transmission to the server.

[0988] Specific actions:

[0989] The terminal receives user input, converts the data into packets, and sends them to the server over the network.

[0990] Step 3: The server passes the prompt message to the AI ​​model.

[0991] The server parses the received prompt message and prepares it for the generative AI model. The server converts the prompt message into a format that the generative AI model can understand. The server inputs the prompt message into the generative AI model and waits for the model to process the information.

[0992] Step 4: The generative AI model generates information based on the prompt.

[0993] The generative AI model receives a prompt as input and generates relevant information. The model uses natural language processing techniques to generate the best possible answer to the user's question. Specifically, the model references a large dataset, extracts relevant information, and generates the answer in natural language.

[0994] Step 5: The server receives the generated information and sends it to the terminal.

[0995] The server receives the information returned from the generated AI model and sends it to the user's terminal. The server formats the information appropriately and sends the data to the terminal using a communication protocol. The server verifies the accuracy of the information and retrieves additional information as needed.

[0996] Step 6: The device displays information to the user.

[0997] The device displays information received from the server to the user. Specifically, it displays information generated on the device's screen, making it easy for the user to read and review. The user can then proceed with their learning based on the displayed information.

[0998] (Application Example 2)

[0999] Next, we will describe application example 2 of form 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."

[1000] Modern learners are required to acquire information on specific topics and subjects quickly and efficiently. However, traditional education systems face challenges in providing information tailored to individual learners' interests and levels of understanding, as well as in enabling real-time information acquisition. Furthermore, the lack of sufficient learning support utilizing portable information terminals and visual display devices means that learners cannot obtain in-depth information the moment they become interested.

[1001] 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.

[1002] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for installing the interactive program on a portable information terminal or visual display device, converting the user's voice input into text, acquiring information using a generative AI model, and displaying the results, and means for the interactive program to provide information in real time based on the user's interests. This makes it possible for learners to obtain in-depth information the moment they become interested.

[1003] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[1004] An "interactive program" is software that enables communication with users using natural language, providing information and answering questions.

[1005] A "portable information terminal" is a portable electronic device used for acquiring information and communicating.

[1006] A "visual display device" is a device used to visually display information and to confirm information.

[1007] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate new information or content based on input data.

[1008] "Real-time" refers to a state where information processing and communication occur instantly, and results are obtained without delay.

[1009] "Converting user voice input to text" is the process of converting a user's spoken words into text information using speech recognition technology.

[1010] The system for implementing this invention is centered around an interactive program using artificial intelligence. The server receives voice input from the user and uses speech recognition software to convert it into text. Specifically, speech recognition technologies such as the Google Speech-to-Text API can be used. The converted text is input into a generative AI model (e.g., OpenAI GPT-3) to generate information in response to the user's request.

[1011] The generated information is displayed on portable information terminals and visual display devices. This allows users to obtain information of interest in real time. For example, if a user uses their smartphone to voice-input "Tell me about the Napoleonic Wars," the information will be displayed immediately.

[1012] This system provides information based on the user's interests, allowing learners to gain in-depth information the moment they become interested. An example of a prompt would be, "Please tell me more about the plot and themes of Shakespeare's 'Hamlet'."

[1013] In this way, the invention can provide information to learners efficiently and effectively, and support the acquisition of knowledge.

[1014] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1015] Step 1:

[1016] The user inputs their question by voice into a portable information terminal or visual display device. The voice input is acquired through the terminal's microphone.

[1017] Step 2:

[1018] The device converts the acquired audio data into text data using speech recognition software (e.g., Google Speech-to-Text API). In this step, the audio waveform is analyzed and the corresponding string is generated. The input is audio data, and the output is text data.

[1019] Step 3:

[1020] The server sends the converted text data to a generating AI model (e.g., OpenAI GPT-3). Here, the server inputs the text data as a prompt into the AI ​​model, which then generates the relevant information. The input is text data, and the output is the generated information.

[1021] Step 4:

[1022] The server sends information obtained from the generated AI model to the terminal. The terminal visually displays the received information to the user. Here, the information is displayed on the screen for the user to review. The input is the generated information, and the output is the visual display.

[1023] Step 5:

[1024] The user can review the displayed information and ask further questions if necessary. At this step, the user can return to step 1 by entering a new question via voice input.

[1025] (Example 3)

[1026] Next, we will describe Embodiment 3 of Embodiment Example 3. 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."

[1027] Traditional interactive programs have faced challenges in providing appropriate information tailored to the learner's level of understanding, hindering efficient knowledge acquisition. Furthermore, they lack the ability to automatically generate appropriate answers to learners' questions, limiting the effectiveness of the learning process.

[1028] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1029] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for determining the learner's level of understanding and generating prompt sentences to provide information according to that level of understanding, and means for generating answers based on the prompt sentences using a generation AI model. This enables the provision of appropriate information according to the learner's level of understanding and the automatic generation of answers.

[1030] Artificial intelligence is a technology in which computer systems imitate human intellectual activity, performing tasks such as learning, reasoning, and problem-solving.

[1031] An "interactive program" is software that provides information or answers questions through dialogue with the user.

[1032] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[1033] A "learner" is an individual whose purpose is to acquire knowledge and skills.

[1034] A "prompt sentence" is an instruction sentence input into a generative AI model, and it contains information that forms the basis of the generated response.

[1035] A "generative AI model" is an artificial intelligence technology that generates natural language responses based on a prompt.

[1036] "Comprehension level" is an indicator that shows how well a learner understands a particular piece of knowledge or skill.

[1037] The embodiment for carrying out this invention is centered on an interactive program using artificial intelligence. The server receives input from the user and generates an appropriate response using a generative AI model. Specifically, the server receives a question sent from the user's terminal and analyzes its content. Based on the analysis results, it determines the user's level of understanding and generates a prompt sentence corresponding to that level of understanding.

[1038] The generated prompt is sent to a generative AI model. This model generates a natural language response based on the prompt. The generated response is returned to the user's terminal via the server. This allows the user to efficiently obtain information tailored to their level of understanding.

[1039] The hardware used includes a server and a user terminal, while the software includes a generative AI model. The generative AI model generates responses from prompt sentences using natural language processing techniques.

[1040] For example, if a user asks, "How do I find the solutions to a quadratic equation?", the server analyzes this question and, if it determines that the user is a beginner, generates a prompt such as, "Please explain the basic methods for solving quadratic equations." Based on this prompt, the AI ​​model generates an answer such as, "There are several ways to find the solutions to a quadratic equation, including factorization, completing the square, and using the quadratic formula," and provides it to the user.

[1041] In this way, the invention enables the provision of information tailored to the learner's level of understanding, thereby supporting efficient learning. The flow of the specific processing in Example 3 will be explained using Figure 15.

[1042] Step 1:

[1043] The user enters a question through their terminal. For example, they might enter a question like, "How do I find the solutions to a quadratic equation?" This input is then sent to the server.

[1044] Step 2:

[1045] The server receives questions from users and analyzes their content. Natural language processing techniques are used for the analysis to extract the intent and keywords of the questions. Based on these analysis results, data is generated to determine the user's level of understanding.

[1046] Step 3:

[1047] The server determines the user's level of understanding based on the analysis results. This determination takes into account past interaction data and the complexity of the questions. Using this determination, the server generates prompts appropriate to the user's level of understanding. For example, for a beginner, it might generate a prompt such as "Please explain the basic methods for solving quadratic equations."

[1048] Step 4:

[1049] The server sends the generated prompt to the generation AI model. The generation AI model receives the prompt as input and generates a natural language response based on it. During this generation process, data calculations are performed according to the content of the prompt.

[1050] Step 5:

[1051] The AI ​​model generates an answer which is then returned to the server. The server receives this answer and sends it to the user's device. The user can then view this answer through their device. For example, an answer such as, "There are several ways to find the solutions to a quadratic equation, including factorization, completing the square, and using the quadratic formula," might be provided.

[1052] This series of processes allows users to efficiently obtain information tailored to their level of understanding.

[1053] (Application Example 3)

[1054] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server," and the headset-type terminal 314 will be referred to as a "terminal."

[1055] Traditional education systems have faced challenges in providing optimal learning materials based on individual learners' comprehension levels and learning histories, and in generating appropriate answers to learners' questions immediately. This can hinder learners' efficient learning.

[1056] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1057] In this invention, the server includes means for analyzing the learner's past learning history using an interactive program with artificial intelligence and recommending the most suitable learning materials; means for instantly generating answers to questions from the learner and providing additional information to deepen understanding; and means for generating answers to questions from the learner using a generative AI model. This enables the provision of optimal learning materials tailored to the learner's individual level of understanding and prompt and appropriate answers to questions.

[1058] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[1059] An "interactive program" is software that provides information and answers questions through dialogue with the user using natural language.

[1060] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[1061] A "learner" is an individual who seeks to acquire specific knowledge or skills.

[1062] "Means of providing answers to questions and guidance" refers to methods of providing appropriate information in response to learners' questions and supporting their learning.

[1063] "Specific subjects or topics" refer to specific topics or fields that are covered in education or training.

[1064] "Methods for analyzing learners' past learning history" refer to methods for evaluating what learners have learned so far, their progress, and understanding their level of comprehension.

[1065] "A method for recommending the most suitable learning materials" refers to a method of selecting and presenting the most effective learning materials based on the learner's level of understanding and learning history.

[1066] A "generative AI model" is an algorithm or model that uses artificial intelligence technology to perform natural language processing and data generation.

[1067] "Means of providing additional information" refers to methods of providing supplementary information in addition to basic information in order to deepen learners' understanding.

[1068] To implement this invention, a server and a user terminal are required. The server runs an interactive program using artificial intelligence and analyzes the learner's past learning history. Specifically, the server retrieves the learner's history data from a database and evaluates their level of understanding using a machine learning algorithm. Software such as Python or TensorFlow can be used for this purpose.

[1069] The server recommends the most suitable learning materials based on the analysis results. These recommendations are displayed on the user's device using a web framework such as Flask. When the user enters a question, the server instantly generates an answer using a generative AI model. This model includes algorithms that leverage natural language processing techniques.

[1070] The user terminal is a device such as a smartphone or tablet that receives information provided by the server and displays it to the user. The user can input questions through the terminal and receive answers from the server.

[1071] For example, if a user enters "I want to learn the basics of differential and integral calculus," the server analyzes the user's past learning history and recommends basic differential and integral calculus learning materials. Also, if the user asks "Can you explain the basic formulas for differentiation?", the generative AI model instantly generates an answer and provides it to the user.

[1072] An example of a prompt message would be: "Recommend the best learning materials for a user who wants to learn the basics of differential and integral calculus. Also, answer questions about the fundamental formulas of differentiation."

[1073] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[1074] Step 1:

[1075] The user enters the topic they want to learn about using their device. The entered data is sent to the server. The server receives this input and retrieves the user's learning history data from its database.

[1076] Step 2:

[1077] The server evaluates the user's understanding based on the acquired learning history data. Here, machine learning algorithms are executed using Python and TensorFlow to analyze the user's past learning patterns. The input is the learning history data, and the output is the user's understanding evaluation result.

[1078] Step 3:

[1079] The server selects the most suitable learning materials based on the comprehension assessment results. The selected learning material information is sent to the user's terminal using Flask. The input is the comprehension assessment results, and the output is the recommended learning material information.

[1080] Step 4:

[1081] The user reviews the recommended learning materials on their device and then enters a question. The entered question is sent to the server. The server receives this question and uses a generative AI model to generate an answer.

[1082] Step 5:

[1083] The server generates answers to questions using a generative AI model. Here, natural language processing techniques are utilized to input prompts into the generative AI model. The input is the user's question, and the output is the generated answer.

[1084] Step 6:

[1085] The server sends the generated response to the user's terminal. The user can review the response on the terminal and ask additional questions if necessary. The input is the generated response, and the output is the display of the response to the user.

[1086] 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.

[1087] "Example of form 1"

[1088] One embodiment of the present invention provides a chatbot incorporating an emotion engine. This emotion engine recognizes emotions from the user's text or voice input. For example, if the user enters the phrase "I don't understand this problem," the emotion engine recognizes the user's frustration.

[1089] "Example of form 2"

[1090] After the emotion engine recognizes the user's emotions, the chatbot's response is adjusted accordingly. For example, if the chatbot detects that the user is feeling frustrated, it will respond in a more polite tone and provide additional explanations or support if necessary.

[1091] "Example of form 3"

[1092] Furthermore, the emotion engine adjusts how it educates and trains learners. For example, if it perceives that a user is agitated, the chatbot will move to a more advanced topic. Conversely, if it perceives that a user is confused, the chatbot will return to a more basic topic.

[1093] The following describes the processing flow for each example of the form.

[1094] "Example of form 1"

[1095] Step 1: The user sends a text or voice message to the chatbot.

[1096] Step 2: The emotion engine recognizes emotions from the user's message. For example, it recognizes the user's frustration from the phrase "I don't understand this problem."

[1097] "Example of form 2"

[1098] Step 1: The emotion engine recognizes the user's emotions.

[1099] Step 2: The chatbot adjusts its response based on the emotion engine's output. For example, if it perceives that the user is feeling frustrated, the chatbot will respond in a more polite tone and provide additional explanations or support if needed.

[1100] "Example of form 3"

[1101] Step 1: The emotion engine recognizes the user's emotions.

[1102] Step 2: The emotion engine adjusts how it educates and trains the learner. For example, if it perceives the user as agitated, the chatbot moves to a more advanced topic. Conversely, if it perceives the user as confused, the chatbot returns to a more basic topic.

[1103] (Example 1)

[1104] Next, we will describe Embodiment 1 of 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."

[1105] Traditional interactive programs in education and training have struggled to provide appropriate instruction tailored to each learner's individual level of understanding and emotional state. Furthermore, they have limitations in their ability to generate quick and detailed answers to learners' questions. This has resulted in reduced learner efficiency and insufficient learning support that meets individual needs.

[1106] 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.

[1107] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for recognizing the learner's emotions using an emotion analysis function and generating appropriate feedback, and means for generating detailed answers to the learner's questions using a generative model. This makes it possible to provide appropriate guidance tailored to the learner's individual level of understanding and emotions, and to generate rapid and detailed answers.

[1108] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[1109] An "interactive program" is software that enables natural language interaction with the user and has functions for question answering and instruction.

[1110] "Education and training" refers to the activities and processes by which learners acquire new knowledge and skills.

[1111] A "learner" refers to an individual who receives education or training, with the aim of improving their knowledge and skills.

[1112] "Emotion analysis functionality" is a technology that recognizes emotions from a user's text or voice and generates an appropriate response based on those emotions.

[1113] A "generative model" is an algorithm that generates new data or information based on input data, and is particularly used in natural language processing.

[1114] "Feedback" refers to evaluation and guidance information provided regarding a learner's behavior and responses, intended to promote improvement in their learning.

[1115] In this embodiment of the invention, the server executes an interactive program using artificial intelligence. The server uses a common library as a natural language processing library to analyze text input from the user. Specifically, the server uses Python and leverages natural language processing libraries such as NLTK and spaCy to understand the user's intent and the content of their questions. Furthermore, for sentiment analysis, it recognizes the user's emotions using the sentiment analysis library TextBlob and a machine learning framework.

[1116] The terminal's role is to receive input from the user and send it to the server. When the user enters a prompt such as "Teach me the basics of differentiation," the terminal sends that text to the server. The server uses a common generative model as its generative AI model to generate a detailed answer to the user's question. This generative AI model uses natural language generation technology to create an appropriate answer to the user's question.

[1117] Users can receive responses from the server through their device and proceed with their learning. For example, if a user inputs "I don't understand this problem," the server uses sentiment analysis to recognize the user's frustration and generate appropriate feedback. This allows users to learn at their own pace.

[1118] The flow of the specific processing in Example 1 will be explained using Figure 17.

[1119] Step 1:

[1120] The user enters questions or requests via text or voice through the terminal. For example, they might enter a prompt such as, "Teach me the basics of differentiation." The terminal then sends this input to the server as text data.

[1121] Step 2:

[1122] The server analyzes the received text data using natural language processing libraries. Specifically, it uses NLTK and spaCy to process the data in order to understand the user's intent and the content of the question. This analysis identifies the subject and purpose of the user's question.

[1123] Step 3:

[1124] The server recognizes the user's emotions using sentiment analysis capabilities. Using TextBlob and machine learning frameworks, it extracts emotions from the input text to determine the user's emotional state. For example, if the user inputs "I don't understand this problem," it detects frustration.

[1125] Step 4:

[1126] The server uses a generative AI model to generate detailed answers to user questions. The generative model generates appropriate answers in natural language based on analyzed intent and sentiment. For example, it might create an explanation of the basics of differentiation, including concrete examples.

[1127] Step 5:

[1128] The server sends the generated answer to the terminal. The terminal displays this answer to the user. The user can then proceed with their learning based on the displayed information. This allows the user to learn at their own pace.

[1129] (Application Example 1)

[1130] Next, we will describe Application Example 1 of Form 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."

[1131] Traditional education and training systems have struggled to provide appropriate instruction in real time, tailored to learners' emotions and levels of understanding. Furthermore, the work environment lacked the means to obtain immediate feedback through visual guidance. This resulted in challenges such as decreased learner motivation and hindered efficient learning.

[1132] 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.

[1133] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for incorporating an emotion recognition engine to recognize the learner's emotions, and means for providing real-time instruction through a visual device in the work environment. This enables the provision of appropriate instruction in real time according to the learner's emotions and level of understanding, and allows for immediate feedback in the work environment.

[1134] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[1135] An "interactive program" is software that provides information and answers questions through dialogue with the user.

[1136] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[1137] An "emotion recognition engine" is a technology that analyzes and recognizes emotions from a user's text or voice.

[1138] A "visual device" is a device that allows a user to receive information visually, and smart glasses are an example of such a device.

[1139] "Providing real-time guidance" means providing appropriate guidance and feedback immediately according to the user's situation.

[1140] A "learner" is an individual who seeks to acquire knowledge or skills.

[1141] "Feedback" refers to evaluations and guidance provided regarding a user's actions and circumstances.

[1142] The system for implementing this invention is centered around an interactive program using artificial intelligence. The server incorporates an emotion recognition engine that analyzes and recognizes emotions from the user's text and voice input. This makes it possible to provide appropriate guidance and feedback in real time, tailored to the user's emotions.

[1143] Specifically, the server uses an emotion recognition library developed with Python (e.g., OpenAI's Sentiment Analysis API) to process user input data. Voice input is converted to text using the Google Speech-to-Text API, and then emotion analysis is performed. Based on the analysis results, the interactive program uses a chatbot framework such as Rasa to generate an appropriate response to the user.

[1144] Smart glasses (e.g., Google Glass) are used as the device, allowing users to receive information visually. This enables immediate feedback even in the work environment.

[1145] For example, if a user asks a question via voice, such as "I don't know how to attach this part," the server will sense the user's anxiety, and the interactive program will instruct them, "Please stay calm. First, attach part A to part B."

[1146] Examples of prompts for a generative AI model are as follows:

[1147] User input: "I don't know how to install this part."

[1148] Sentiment analysis result: "Anxiety"

[1149] Chatbot response: "Please stay calm. First, attach part A to part B."

[1150] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[1151] Step 1:

[1152] The user provides voice input through the device. The device converts the user's voice into text data using the Google Speech-to-Text API. The input for this step is voice data, and the output is text data.

[1153] Step 2:

[1154] The server receives text data and analyzes the user's emotions using an emotion recognition engine. Specifically, it uses OpenAI's emotion analysis API to extract emotions from the text data. The input for this step is text data, and the output is the emotion analysis result.

[1155] Step 3:

[1156] Based on the sentiment analysis results, the server uses a chatbot framework such as Rasa to generate an appropriate response to the user. The input for this step is the sentiment analysis results, and the output is the chatbot's response.

[1157] Step 4:

[1158] The device provides the user with the generated chatbot responses visually or audibly. Specifically, this may involve displaying text through smart glasses or providing voice guidance. The input in this step is the chatbot's response, and the output is feedback to the user.

[1159] Step 5:

[1160] The user proceeds with the work based on the feedback provided. If necessary, they can ask further questions and repeat the process. The input in this step is the user's feedback, and the output is the user's actions.

[1161] (Example 2)

[1162] Next, we will describe Example 2 of the morphological example. 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."

[1163] Traditional interactive programs have faced challenges in providing responses that take into account the user's emotions and insufficient information tailored to the learner's level of understanding. Furthermore, they have difficulty providing detailed information on specific topics and generating appropriate responses based on user input.

[1164] 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.

[1165] In this invention, the server includes means for providing an interactive program using an information processing device, means for recognizing the user's emotions and adjusting the response using emotion recognition technology, and means for analyzing the user's input and generating an appropriate response using a generative model. This makes it possible to adjust the response according to the user's emotions and provide information according to the learner's level of understanding.

[1166] An "information processing device" is a device used for inputting, processing, and outputting data, and includes devices such as computers and servers.

[1167] An "interactive program" is software that provides information and answers questions through dialogue with the user.

[1168] The "field of education and training" is the area in which activities are carried out to help learners acquire knowledge and skills.

[1169] A "learner" is an individual or group whose purpose is to acquire knowledge or skills.

[1170] A "subject or field" refers to a specific area of ​​knowledge or topic, and is the content that learners are supposed to study.

[1171] "Emotion recognition technology" refers to technology for analyzing and recognizing a user's emotions, and includes technology for determining emotions from voice and text.

[1172] A "generative model" is an algorithm or technique for generating new data or responses based on input data.

[1173] "Adjusting responses" means changing the information provided and how it is presented according to the user's emotions and circumstances.

[1174] This invention is a system for implementing an interactive program using an information processing device. The server utilizes a generative AI model to analyze user input and generate an appropriate response. Specifically, it uses natural language processing technology to understand the user's prompt and generates a response using a generative model. Furthermore, it uses emotion recognition technology to recognize the user's emotions and adjust the response accordingly.

[1175] The server receives prompt messages entered by the user through the terminal. For example, if the user enters "Tell me about Renaissance art," the server analyzes this input and provides information about representative artists and works of the Renaissance. Similarly, if the user asks "What is the theme of this poem?", the server analyzes the content of the poem and generates information about its theme.

[1176] By using emotion recognition technology, the server can determine the user's emotions and adjust the tone and content of its response. For example, if the server detects that the user is confused, it will offer additional support to help the user understand, such as "Shall I explain this topic in more detail?"

[1177] In this way, the server adjusts its responses to the user's emotions and provides information tailored to the learner's level of understanding. This allows learners to deepen their knowledge of specific subjects and fields.

[1178] The flow of the specific processing in Example 2 will be explained using Figure 19.

[1179] Step 1:

[1180] The user enters a prompt message through the terminal. For example, they might enter a question like, "Tell me about Renaissance art." This input is then sent to the server.

[1181] Step 2:

[1182] The server parses the received prompt message. Using natural language processing techniques, it understands the intent and content of the input text. This analysis identifies what information the user is seeking. As a result of the analysis, data regarding the user's intent is generated.

[1183] Step 3:

[1184] The server uses emotion recognition technology to recognize the user's emotions. It extracts emotional keywords and context from the input text to determine the user's emotional state. For example, if it determines that the user is confused, that information will influence the response generation in the next step.

[1185] Step 4:

[1186] The server uses a generative AI model to generate appropriate responses to user questions. Based on the analysis results and sentiment recognition results, it creates responses that provide information aligned with the user's intent. For example, a response containing detailed information about Renaissance art might be generated.

[1187] Step 5:

[1188] The server adjusts the generated response. It modifies the tone and content of the response according to the user's emotions. For confused users, it adjusts to provide additional explanations in a more polite and helpful tone.

[1189] Step 6:

[1190] The server sends a pre-arranged response to the terminal. The user can then view the chatbot's response on their terminal and continue asking further questions. This allows the user to obtain the necessary information.

[1191] (Application Example 2)

[1192] Next, we will describe application example 2 of form 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."

[1193] Traditional interactive programs in education and training have struggled to provide personalized learning experiences due to their inability to flexibly adapt to learners' emotions and levels of understanding. Furthermore, even when providing information on specific topics, the generated information sometimes failed to fully meet learners' needs. This resulted in challenges such as decreased learner motivation and reduced learning effectiveness.

[1194] 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.

[1195] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for recognizing the user's emotions using an emotion recognition engine and adjusting the response according to those emotions, and means for generating information based on prompt sentences using a generative AI model. This makes it possible to provide a personalized learning experience that is tailored to the learner's emotions and level of understanding, and to provide information on specific topics more appropriately.

[1196] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[1197] An "interactive program" is software that engages in natural language dialogue with the user to provide information and answer questions.

[1198] "Education and training" refers to the activities and processes by which learners acquire new knowledge and skills.

[1199] A "participant" is an individual who participates in an educational or training program and engages in learning.

[1200] "Means of providing answers to questions and guidance" refers to methods and techniques for generating appropriate answers to learners' questions and supporting their learning.

[1201] "Specific topics or subjects" refer to specific fields or topics that the learner is interested in.

[1202] An "emotion recognition engine" is a technology that analyzes and identifies emotions from a user's voice or text.

[1203] A "generative AI model" is an artificial intelligence model that generates natural language text based on input prompts.

[1204] A "prompt message" is text containing instructions or questions that are input into a generative AI model.

[1205] The system for implementing this invention mainly consists of a server and a user terminal. The server executes an interactive program using artificial intelligence and communicates with the user terminal. The user terminal is a device such as a smartphone or tablet, and interacts with the interactive program through an interface.

[1206] The server analyzes the user's emotions using an emotion recognition engine. Specifically, it receives the user's voice and text input and processes the data to identify their emotions. This process utilizes emotion recognition technologies such as the Microsoft Azure Emotion API.

[1207] Furthermore, the server uses a generative AI model to generate information based on user prompts. OpenAI GPT-3 is one example of a generative AI model used. A prompt is a text containing information or a question the user wants to know, such as "Please provide detailed information about World War II."

[1208] When a user requests information on a specific topic, the server uses a generative AI model to generate relevant information and sends it to the user's device. If the user's emotions indicate frustration, the server adjusts its response, providing additional explanations in a more polite tone. This allows the user to have a personalized learning experience.

[1209] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[1210] Step 1:

[1211] The user uses a terminal to enter a prompt requesting information on a specific topic. The entered prompt might be in the format of, for example, "Please provide detailed information about World War II." The terminal then sends this prompt to the server.

[1212] Step 2:

[1213] The server parses the received prompt and inputs it into a generative AI model. The generative AI model (e.g., OpenAI GPT-3) generates relevant information based on the prompt. The generated information is output to the server as an answer to the prompt.

[1214] Step 3:

[1215] The server receives voice and text input from the user's device and analyzes the user's emotions using an emotion recognition engine. It processes the input data to identify the user's emotional state (e.g., frustration, excitement).

[1216] Step 4:

[1217] The server adjusts its response based on the generated information and the user's emotional state. For example, if the user is feeling frustrated, the server will generate a response in a more polite tone that includes additional explanations.

[1218] Step 5:

[1219] The server sends a tailored response to the user's device. The user can then receive personalized information and responses through their device, enabling them to have a better learning experience.

[1220] (Example 3)

[1221] Next, we will describe Embodiment 3 of Embodiment Example 3. 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."

[1222] Traditional interactive programs have failed to adequately provide information tailored to learners' levels of understanding and emotional states, making it difficult to address individual learners' needs. Furthermore, the automatic and appropriate generation of answers to learners' questions has been insufficient, preventing the maximization of learning effectiveness.

[1223] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1224] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for analyzing the learner's past dialogue data and evaluating their level of understanding, means for analyzing the learner's emotional state and adjusting the method of information provision, and means for generating prompt sentences and appropriate answers using a generative model. This enables personalized information provision according to the learner's level of understanding and emotional state, and realizes the automatic and appropriate generation of answers to questions from the learner.

[1225] Artificial intelligence is a technology in which computer systems imitate human intellectual behavior, enabling them to learn, reason, and solve problems.

[1226] An "interactive program" is software that provides information and answers questions through dialogue with the user.

[1227] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[1228] A "participant" is an individual who participates in an educational or training program and engages in learning.

[1229] A "subject or topic" refers to a specific area of ​​knowledge or topic that is covered in education or training.

[1230] "Comprehension level" is an indicator that shows how well a learner understands a particular piece of knowledge or skill.

[1231] "Emotional state" refers to the learner's psychological state and includes emotions such as excitement and confusion.

[1232] A "generative model" is an algorithm or technique for generating new data based on input data.

[1233] A "prompt statement" is an instruction given to a generative model, providing guidelines for obtaining a specific output.

[1234] A description of embodiments for carrying out this invention will be given.

[1235] The server runs an interactive program using artificial intelligence. This program utilizes a generative AI model to generate responses based on user input. Specifically, it analyzes user input using natural language processing techniques and understands their intent. A general natural language generation technique is used as the generative AI model.

[1236] The terminal collects the user's past conversation data and uses machine learning algorithms to evaluate the user's level of understanding. Based on this evaluation, the server adjusts the depth and detail of the information provided to the user. Furthermore, the terminal performs sentiment analysis on the input text to analyze the user's emotional state. This allows it to determine whether the user is agitated or confused and appropriately adjust the way information is delivered.

[1237] Users interact with interactive programs through their terminals. For example, if a user asks, "How do I find the solutions to a quadratic equation?", the server uses a generative AI model to generate a prompt and provide an appropriate answer. An example of a prompt might be, "The user is asking about how to solve a quadratic equation. Please explain the basic solution method for beginners."

[1238] This system allows users to receive personalized information tailored to their level of understanding and emotional state, maximizing learning effectiveness. The flow of specific processing in Example 3 will be explained using Figure 21.

[1239] Step 1:

[1240] Users input questions and requests through their terminals. For example, they might input a specific question like, "Please tell me how to find the solutions to a quadratic equation." This input serves as the starting point for the system's processing.

[1241] Step 2:

[1242] The server analyzes the input received from the user. Using natural language processing techniques, it tokenizes the input text and performs grammatical analysis to understand the user's intent. This analysis clarifies the meaning of the input and extracts the information necessary for the next processing step.

[1243] Step 3:

[1244] The terminal references the user's past conversation data and uses machine learning algorithms to assess the user's level of understanding. This assessment is based on the user's past questions and answers to determine whether the user is a beginner or an advanced user. This result is used to determine the depth of information provided by the server.

[1245] Step 4:

[1246] The server uses an emotion engine to analyze the user's emotional state. It performs sentiment analysis on the input text to determine whether the user is agitated or confused. This analysis is used to adjust the way information is delivered.

[1247] Step 5:

[1248] The server generates prompt sentences to be input into the generative AI model. These prompt sentences are adjusted according to the user's level of understanding and emotional state. For example, it might say, "The user is asking about solving quadratic equations. Please explain the basic solution method for beginners." These prompt sentences become the input to the generative AI model.

[1249] Step 6:

[1250] The server generates responses based on prompts using a generative AI model. The generative AI model receives prompts as input and generates appropriate responses. These responses include specific explanations and guidance regarding the user's questions.

[1251] Step 7:

[1252] The device displays the generated answer to the user. The user can receive the answer from the chatbot and deepen their understanding. For example, the chatbot may provide a specific explanation such as, "Quadratic equations can be solved using methods such as completing the square or factorization."

[1253] (Application Example 3)

[1254] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server," and the headset-type terminal 314 will be referred to as a "terminal."

[1255] In the field of modern education and training, there is a demand for flexible educational content that is tailored to each learner's individual level of understanding and emotional state. However, conventional systems have struggled to analyze learners' emotions and level of understanding in real time and provide appropriate learning content based on that analysis. This has hindered learners from efficiently acquiring knowledge.

[1256] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1257] In this invention, the server includes means for analyzing the learner's emotional state using an interactive program with artificial intelligence, means for generating learning content suitable for the learner using a generative AI model, and means for inputting prompt sentences into the generative AI model to generate learning content. This makes it possible to provide optimal educational content that corresponds to the learner's level of understanding and emotions.

[1258] "Artificial intelligence" is a technology in which computers imitate human intelligence and perform learning, reasoning, and problem-solving.

[1259] An "interactive program" is software that provides information or answers questions through natural dialogue with the user.

[1260] The "field of education and training" refers to the activities and processes by which learners acquire new knowledge and skills.

[1261] A "learner" refers to an individual who seeks to acquire specific knowledge or skills.

[1262] "Emotional state" refers to the learner's psychological state and changes in their emotions.

[1263] A "generative AI model" is an artificial intelligence model that generates new data or content based on given input.

[1264] A "prompt statement" is an instruction or question given to a generative AI model to obtain a specific output.

[1265] "Learning content" refers to educational materials and information that learners use to acquire knowledge and skills.

[1266] The system for carrying out this invention includes a server and a user terminal. The server executes an interactive program using artificial intelligence and receives input from the user terminal. The user terminal is a device such as a smartphone or a head-mounted display, and provides an interface with the user.

[1267] The server uses an emotion recognition engine (e.g., Microsoft Azure Emotion API) to analyze the user's voice and facial expression data and evaluate the user's emotional state. Based on this evaluation, the server uses a generative AI model (e.g., OpenAI GPT-3) to generate learning content suitable for the user. The generative AI model can generate specific learning content by inputting prompts.

[1268] For example, if a user asks, "Please explain the basics of differential and integral calculus," the server detects confusion from the user's facial expression. In this case, it prompts the generative AI model with "Please explain the basic concepts of differential and integral calculus in a way that is easy for beginners to understand," and sends the generated content to the user's device. This allows the user to receive an optimal learning experience tailored to their level of understanding and emotional state.

[1269] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[1270] Step 1:

[1271] The user enters a question via a terminal. The terminal captures the user's voice and facial expression data and sends it to the server. The input consists of the user's question text and voice / facial expression data.

[1272] Step 2:

[1273] The server inputs received audio and facial expression data into an emotion recognition engine to analyze the user's emotional state. For data processing, audio data is converted to text, and facial expression data is analyzed using image analysis. The output is an evaluation result indicating the user's emotional state.

[1274] Step 3:

[1275] The server generates and inputs prompt sentences into the generative AI model based on the user's question text and the evaluation of their emotional state. Specifically, prompt sentences are generated such as "Please explain the basic concepts of differential and integral calculus in a way that is easy for beginners to understand." The input is the prompt sentence, and the output is the generated training content.

[1276] Step 4:

[1277] The generative AI model generates appropriate training content based on prompt text. As a data processing technique, the model uses natural language processing to construct the content. The output is training content to be provided to the user.

[1278] Step 5:

[1279] The server sends the generated learning content to the user's terminal. The terminal displays the content to the user and assists with learning. Specifically, the terminal presents the content in text or audio. The output is the learning content received by the user.

[1280] (Other examples)

[1281] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[1282] 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.

[1283] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> 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.

[1284] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[1285] 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.

[1286] [Fourth Embodiment]

[1287] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1288] 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.

[1289] 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).

[1290] 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.

[1291] 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.

[1292] 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).

[1293] 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.

[1294] 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.

[1295] 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.

[1296] 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.

[1297] 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.

[1298] 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.

[1299] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[1300] "Example of form 1"

[1301] One embodiment of the present invention involves the application of an artificial intelligence-powered chatbot in the field of education and training. This chatbot provides students with answers to questions and guidance. For example, it could explain how to solve a math problem or provide information to deepen their understanding of a science experiment.

[1302] "Example of form 2"

[1303] Furthermore, chatbots can provide information on specific topics and subjects, helping learners deepen their knowledge. For example, they can provide detailed information about specific periods or events in history, or information to help interpret literary works.

[1304] "Example of form 3"

[1305] Furthermore, the chatbot adjusts how information is provided according to the learner's level of understanding. For example, if the learner is a beginner, it will provide basic information, and if the learner is advanced, it will provide more in-depth information.

[1306] "Example of form 4"

[1307] Furthermore, the chatbot automatically generates answers to learners' questions. For example, if a learner asks, "How do I find the solutions to a quadratic equation?", the chatbot will generate an answer explaining how to find the solutions to a quadratic equation.

[1308] The following describes the processing flow for each example of the form.

[1309] "Example of form 1"

[1310] Step 1: The learner enters a question into the chatbot. For example, they might enter the question, "How do I find the solutions to a quadratic equation?"

[1311] Step 2: The chatbot analyzes the question and generates an appropriate answer. In this case, it generates an answer explaining how to find the solutions to a quadratic equation.

[1312] Step 3: The chatbot provides the learner with the generated response. The learner then uses this response to continue their learning.

[1313] "Example of form 2"

[1314] Step 1: The learner requests information from the chatbot about a specific topic or subject. For example, they might request, "Teach me about Edo period society."

[1315] Step 2: The chatbot analyzes the request and generates appropriate information. In this case, it generates information about Edo period society.

[1316] Step 3: The chatbot provides the learner with the information it has generated. The learner then uses this information to continue their learning.

[1317] "Example of form 3"

[1318] Step 1: The chatbot evaluates the learner's understanding. For example, it evaluates understanding based on the results of tests submitted by the learner or the history of past questions.

[1319] Step 2: The chatbot adjusts how it provides information based on the evaluation results. For example, if it is evaluated as having a low level of understanding, it will start by providing basic information. If it is evaluated as having a high level of understanding, it will provide more in-depth information.

[1320] Step 3: The chatbot provides information to the learner based on the information delivery method it has set up. The learner then proceeds with their learning based on this information.

[1321] "Example of form 4"

[1322] Step 1: The learner enters a question into the chatbot. For example, they might enter the question, "How do I find the solutions to a quadratic equation?"

[1323] Step 2: The chatbot analyzes the question and automatically generates an appropriate answer. In this case, it generates an answer explaining how to find the solutions to a quadratic equation.

[1324] Step 3: The chatbot provides the learner with the generated response. The learner then uses this response to continue their learning.

[1325] (Example 1)

[1326] Next, we will describe Embodiment 1 of Example Form 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1327] Traditional information systems in the fields of education and training have faced challenges in providing flexible instruction tailored to the individual understanding and needs of learners. Furthermore, while there is a need to respond quickly and accurately to a wide range of inquiries from learners, there has been a lack of efficient means to achieve this.

[1328] 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.

[1329] In this invention, the server includes means for providing responses to inquiries and guidance to learners using an information processing device employing artificial intelligence, means for generating responses to inquiries using a generative AI model, and means for transmitting the generated responses to the learner's terminal. This enables flexible guidance tailored to the learner's individual level of understanding and needs, and allows for quick and accurate responses to a variety of inquiries.

[1330] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[1331] An "information processing device" is a device that receives data, processes it based on a specific algorithm, and outputs the result.

[1332] A "learner" is an individual who seeks to acquire knowledge and skills in the process of education or training.

[1333] An "inquiry" is a question or request that a learner makes to an information processing device in search of information or guidance.

[1334] A "response" is the answer or information that an information processing device provides in response to a learner's inquiry.

[1335] A "generative AI model" is a model that uses artificial intelligence technology to generate new information or responses based on input data.

[1336] A "terminal" is a device that a user uses to interface with an information processing device.

[1337] This invention is a system that utilizes an artificial intelligence-based information processing device to provide flexible guidance to learners in the fields of education and training. The server generates responses to learner inquiries using a generative AI model. Specifically, the server analyzes the learner's inquiry using natural language processing technology and understands its intent. The analyzed information is sent to the generative AI model as a prompt. For example, a model that excels at natural language generation is used as the generative AI model.

[1338] The server sends the response obtained from the generated AI model to the learner's device. The device displays the received response to the learner, allowing them to review it. This enables learners to obtain information tailored to their level of understanding, thereby improving learning efficiency.

[1339] For example, if a user asks a question via their device such as "Please explain the process of photosynthesis," the server sends this question as a prompt to the generating AI model. The generating AI model generates a response such as "Photosynthesis is the process by which plants use light energy to produce oxygen and glucose from carbon dioxide and water," and the server sends this response to the device. The user can then review the response displayed on their device and ask further questions if necessary.

[1340] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1341] Step 1:

[1342] The user enters a question into the chatbot via their device. The entered question is sent to the server as text data. Specifically, the user enters "Please explain the process of photosynthesis" into the chat interface on their device and clicks the send button.

[1343] Step 2:

[1344] The server receives text data sent by the user. It analyzes the received data using natural language processing techniques to understand the intent of the question. Specifically, the server tokenizes the text and performs grammatical analysis to identify the subject of the question. This analysis result becomes the input for the next step.

[1345] Step 3:

[1346] The server sends prompt messages to the generating AI model based on the analysis results. These prompt messages contain instructions for generating appropriate answers to the user's questions. Specifically, the server generates a prompt message such as "Please explain the process of photosynthesis in detail" and sends it to the generating AI model.

[1347] Step 4:

[1348] The generative AI model generates an answer based on the received prompt. The model utilizes pre-learned knowledge to create a detailed answer to the user's question. Specifically, the generative AI model might produce an answer such as, "Photosynthesis is the process by which plants use light energy to produce oxygen and glucose from carbon dioxide and water." This generated answer then becomes the input for the next step.

[1349] Step 5:

[1350] The server sends the response received from the generated AI model to the user's device. Specifically, the server sends the generated response in text format to the user's device and displays it in the chat interface.

[1351] Step 6:

[1352] The user reviews the answers displayed on the device to deepen their understanding of the questions. Specifically, the user reads the answers displayed on the device screen and enters further questions as needed.

[1353] (Application Example 1)

[1354] Next, we will describe Application Example 1 of Form 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".

[1355] In modern educational and training settings, there is a challenge in that learners often struggle to obtain individually tailored learning experiences. Furthermore, while there is a demand for prompt and accurate answers to learners' questions, traditional methods are sometimes insufficient. Additionally, there is a need to adjust information provision according to the learner's level of understanding, but there is a lack of efficient means to achieve this.

[1356] 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.

[1357] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for the interactive program to provide a learning experience that is individually customized based on the subject selected by the learner, and means for generating answers to the user's questions using a generative AI model. As a result, learners can obtain an individually customized learning experience and receive quick and accurate answers. Furthermore, it becomes possible to adjust the information provided according to the learner's level of understanding.

[1358] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[1359] An "interactive program" is software that provides information or answers questions through dialogue with the user.

[1360] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[1361] A "learner" is an individual who seeks to acquire specific knowledge or skills.

[1362] A "personally customized learning experience" means providing educational content and methods that are tailored to the learner's needs and level of understanding.

[1363] A "generative AI model" is a mathematical model that uses artificial intelligence technology to generate new information or answers.

[1364] A "prompt statement" is an instruction given to a generative AI model to generate specific information.

[1365] The system for carrying out this invention consists of a network environment including a server and user terminals. The server executes an interactive program using artificial intelligence and receives input from the user terminals. The user terminals are devices such as smartphones and head-mounted displays, and provide an interface for the user to interact with the interactive program.

[1366] The server runs generative AI models using software such as Python and TensorFlow. User input is analyzed using natural language processing techniques and converted into a format suitable for the generative AI model. The generative AI model generates answers to the user's questions and sends the results to the user's terminal.

[1367] As a concrete example, if a user enters "Teach me the basics of differentiation" into their terminal, the server analyzes this input and sends the prompt "Please explain the basics of differentiation" to the generative AI model. The generative AI model generates an explanation of the basics of differentiation and returns it to the user's terminal. The user can then view this explanation on their terminal and continue learning.

[1368] This system allows users to receive a personalized learning experience and get quick and accurate answers.

[1369] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1370] Step 1:

[1371] The user enters a question using a terminal. The entered question is sent to the server through the terminal's interface. The input data is in text format and reflects the user's learning needs.

[1372] Step 2:

[1373] The server analyzes the user's question using natural language processing techniques. Specifically, it uses a Python natural language processing library to tokenize the input text and perform semantic analysis. This process helps understand the intent of the question and generates a prompt suitable for the generative AI model.

[1374] Step 3:

[1375] The server uses the generated prompt to query the generative AI model. The generative AI model receives the prompt as input and generates relevant information and answers. The generative AI model is built using TensorFlow and generates answers based on pre-trained data.

[1376] Step 4:

[1377] The responses obtained from the generative AI model are received by the server in text format. The server then formats these responses into a format that is easy for the user to understand and sends them to the device.

[1378] Step 5:

[1379] The terminal displays the answers received from the server to the user. The user can view the answers on the terminal screen and proceed with their learning. The displayed information is customized according to the user's learning needs.

[1380] (Example 2)

[1381] Next, we will describe Example 2 of the morphological example. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1382] Traditional educational support systems have faced challenges in enabling learners to quickly and accurately obtain detailed information on specific subjects. Furthermore, the lack of adequate information tailored to each learner's level of understanding makes it difficult to provide optimal learning support for individual students.

[1383] 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.

[1384] In this invention, the server includes an interactive program using an information processing device, means for applying the interactive program in the field of education to provide learners with responses to inquiries and guidance, and means for the interactive program to provide information on a specific subject and support learners in deepening their knowledge. As a result, learners can quickly obtain detailed information on a specific subject and information can be provided according to their level of understanding.

[1385] An "information processing device" is a device that has the functions of receiving, processing, and transmitting data, and includes hardware and software for executing interactive programs.

[1386] An "interactive program" is software that generates responses and provides information in response to user input, and is used in the field of education to support learners.

[1387] The "education field" refers to activities and areas that provide knowledge and skills to learners and support their learning.

[1388] A "learner" refers to an individual who seeks to acquire knowledge or skills related to a specific subject.

[1389] An "inquiry" refers to a question or request that a learner makes to an interactive program in order to obtain specific information.

[1390] "Response" refers to the information or instructions that an interactive program provides in response to a learner's inquiry.

[1391] A "subject" refers to a specific topic or subject that a learner is interested in and wishes to study.

[1392] "Support for deepening knowledge" refers to the information and instruction provided to help learners deepen their understanding of a particular subject.

[1393] This invention relates to a system for executing interactive programs using an information processing device. The server generates information based on user prompts, utilizing a generative AI model. Specifically, the server uses natural language processing technology to analyze user input and perform calculations to generate relevant information. A general-purpose natural language processing model can be used as the generative AI model.

[1394] The user enters a prompt message through the terminal. For example, they might enter a prompt message such as, "Tell me about the themes in Shakespeare's 'Hamlet'." The terminal sends this prompt message to the server. The server passes the received prompt message to a generation AI model, which generates information based on the prompt message. The generated information is sent from the server to the terminal and displayed to the user.

[1395] This system allows users to quickly obtain detailed information on specific topics. Furthermore, by utilizing generative AI models, it becomes possible to provide information tailored to the user's level of understanding, offering optimal learning support for individual learners.

[1396] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1397] Step 1:

[1398] The user enters a prompt using the terminal. For example, they might enter a specific question such as, "Tell me about the main events of the French Revolution." The entered prompt is then ready to be sent to the server through the terminal's interface.

[1399] Step 2:

[1400] The terminal sends the prompt text entered by the user to the server. Here, the terminal converts the prompt text into the appropriate data format and sends the data to the server using a communication protocol. The input is the prompt text, and the output is the transmission to the server.

[1401] Specific actions:

[1402] The terminal receives user input, converts the data into packets, and sends them to the server over the network.

[1403] Step 3: The server passes the prompt message to the AI ​​model.

[1404] The server parses the received prompt message and prepares it for the generative AI model. The server converts the prompt message into a format that the generative AI model can understand. The server inputs the prompt message into the generative AI model and waits for the model to process the information.

[1405] Step 4: The generative AI model generates information based on the prompt.

[1406] The generative AI model receives a prompt as input and generates relevant information. The model uses natural language processing techniques to generate the best possible answer to the user's question. Specifically, the model references a large dataset, extracts relevant information, and generates the answer in natural language.

[1407] Step 5: The server receives the generated information and sends it to the terminal.

[1408] The server receives the information returned from the generated AI model and sends it to the user's terminal. The server formats the information appropriately and sends the data to the terminal using a communication protocol. The server verifies the accuracy of the information and retrieves additional information as needed.

[1409] Step 6: The device displays information to the user.

[1410] The device displays information received from the server to the user. Specifically, it displays information generated on the device's screen, making it easy for the user to read and review. The user can then proceed with their learning based on the displayed information.

[1411] (Application Example 2)

[1412] Next, we will describe application example 2 of form 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".

[1413] Modern learners are required to acquire information on specific topics and subjects quickly and efficiently. However, traditional education systems face challenges in providing information tailored to individual learners' interests and levels of understanding, as well as in enabling real-time information acquisition. Furthermore, the lack of sufficient learning support utilizing portable information terminals and visual display devices means that learners cannot obtain in-depth information the moment they become interested.

[1414] 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.

[1415] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for installing the interactive program on a portable information terminal or visual display device, converting the user's voice input into text, acquiring information using a generative AI model, and displaying the results, and means for the interactive program to provide information in real time based on the user's interests. This makes it possible for learners to obtain in-depth information the moment they become interested.

[1416] Artificial intelligence is a technology in which computer systems imitate human intelligence to learn and solve problems.

[1417] An "interactive program" is software that enables communication with users using natural language, providing information and answering questions.

[1418] A "portable information terminal" is a portable electronic device used for acquiring information and communicating.

[1419] A "visual display device" is a device used to visually display information and to confirm information.

[1420] A "generative AI model" is an algorithm that uses artificial intelligence technology to generate new information or content based on input data.

[1421] "Real-time" refers to a state where information processing and communication occur instantly, and results are obtained without delay.

[1422] "Converting user voice input to text" is the process of converting a user's spoken words into text information using speech recognition technology.

[1423] The system for implementing this invention is centered around an interactive program using artificial intelligence. The server receives voice input from the user and uses speech recognition software to convert it into text. Specifically, speech recognition technologies such as the Google Speech-to-Text API can be used. The converted text is input into a generative AI model (e.g., OpenAI GPT-3) to generate information in response to the user's request.

[1424] The generated information is displayed on portable information terminals and visual display devices. This allows users to obtain information of interest in real time. For example, if a user uses their smartphone to voice-input "Tell me about the Napoleonic Wars," the information will be displayed immediately.

[1425] This system provides information based on the user's interests, allowing learners to gain in-depth information the moment they become interested. An example of a prompt would be, "Please tell me more about the plot and themes of Shakespeare's 'Hamlet'."

[1426] In this way, the invention can provide information to learners efficiently and effectively, and support the acquisition of knowledge.

[1427] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1428] Step 1:

[1429] The user inputs their question by voice into a portable information terminal or visual display device. The voice input is acquired through the terminal's microphone.

[1430] Step 2:

[1431] The device converts the acquired audio data into text data using speech recognition software (e.g., Google Speech-to-Text API). In this step, the audio waveform is analyzed and the corresponding string is generated. The input is audio data, and the output is text data.

[1432] Step 3:

[1433] The server sends the converted text data to a generating AI model (e.g., OpenAI GPT-3). Here, the server inputs the text data as a prompt into the AI ​​model, which then generates the relevant information. The input is text data, and the output is the generated information.

[1434] Step 4:

[1435] The server sends information obtained from the generated AI model to the terminal. The terminal visually displays the received information to the user. Here, the information is displayed on the screen for the user to review. The input is the generated information, and the output is the visual display.

[1436] Step 5:

[1437] The user can review the displayed information and ask further questions if necessary. At this step, the user can return to step 1 by entering a new question via voice input.

[1438] (Example 3)

[1439] Next, we will describe Embodiment 3 of Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1440] Traditional interactive programs have faced challenges in providing appropriate information tailored to the learner's level of understanding, hindering efficient knowledge acquisition. Furthermore, they lack the ability to automatically generate appropriate answers to learners' questions, limiting the effectiveness of the learning process.

[1441] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1442] In this invention, the server includes means for providing an interactive program using artificial intelligence, means for determining the learner's level of understanding and generating prompt sentences to provide information according to that level of understanding, and means for generating answers based on the prompt sentences using a generation AI model. This enables the provision of appropriate information according to the learner's level of understanding and the automatic generation of answers.

[1443] Artificial intelligence is a technology in which computer systems imitate human intellectual activity, performing tasks such as learning, reasoning, and problem-solving.

[1444] An "interactive program" is software that provides information or answers questions through dialogue with the user.

[1445] The "field of education and training" is the area in which activities are carried out for learners to acquire knowledge and skills.

[1446] A "learner" is an individual whose purpose is to acquire knowledge and skills.

[1447] A "prompt sentence" is an instruction sentence input into a generative AI model, and it contains information that forms the basis of the generated response.

[1448] A "generative AI model" is an artificial intelligence technology that generates natural language responses based on a prompt.

[1449] "Comprehension level" is an indicator that shows how well a learner understands a particular piece of knowledge or skill.

[1450] The embodiment for carrying out this invention is centered on an interactive program using artificial intelligence. The server receives input from the user and generates an appropriate response using a generative AI model. Specifically, the server receives a question sent from the user's terminal and analyzes its content. Based on the analysis results, it determines the user's level of understanding and generates a prompt sentence corresponding to that level of understanding.

[1451] The generated prompt is sent to a generative AI model. This model generates a natural language response based on the prompt. The generated response is returned to the user's terminal via the server. This allows the user to efficiently obtain information tailored to their level of understanding.

[1452] The hardware used includes a server and a user terminal, while the software includes a generative AI model. The generative AI model generates responses from prompt sentences using natural language processing techniques.

[1453] For example, if a user asks, "How do I find the solutions to a quadratic equation?", the server analyzes this question and, if it determines that the user is a beginner, generates a prompt such as, "Please explain the basic methods for solving quadratic equations." Based on this prompt, the AI ​​model generates an answer such as, "There are several ways to find the solutions to a quadratic equation, including factorization, completing the square, and using the quadratic formula," and provides it to the user.

[1454] In this way, the invention enables the provision of information tailored to the learner's level of understanding, thereby supporting efficient learning. The flow of the specific processing in Example 3 will be explained using Figure 15.

[1455] Step 1:

[1456] The user enters a question through their terminal. For example, they might enter a question like, "How do I find the solutions to a quadratic equation?" This input is then sent to the server.

[1457] Step 2:

[1458] The server receives questions from users and analyzes their content. Natural language processing techniques are used for the analysis to extract the intent and keywords of the questions. Based on these analysis results, data is generated to determine the user's level of understanding.

[1459] Step 3:

[1460] The server determines the user's level of understanding based on the analysis results. This determination takes into account past interaction data and the complexity of the questions. Using this determination, the server generates prompts appropriate to the user's level of understanding. For example, for a beginner, it might generate a prompt such as "Please explain the basic methods for solving quadratic equations."

[1461] Step 4:

[1462] The server sends the generated prompt to the generation AI model. The generation AI model receives the prompt as input and generates a natural language response based on it. During this generation process, data calculations are performed according to the content of the prompt.

[1463] Step 5:

[1464] The AI ​​model generates an answer which is then returned to the server. The server receives this answer and sends it to the user's device. The user can then view this answer through their device. For example, an answer such as, "There are several ways to find the solutions to a quadratic equation, including factorization, completing the square, and using the quadratic formula," might be provided.

[1465] This series of processes allows users to efficiently obtain information tailored to their level of understanding.

[1466] (Application Example 3)

[1467] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1468] Traditional education systems have faced challenges in providing optimal learning materials based on individual learners' comprehension levels and learning histories, and in generating appropriate answers to learners' questions immediately. This can hinder learners' efficient learning.

[1469] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1470] In this invention, the server includes means for analyzing the learner's past learning history using an interactive program with artificial intelligence and recommending the most suitable learning materials; means for instantly generating answers to questions from the learner and providing additional information to deepen understanding; and means for generating answers to questions from the learner using a generative AI model. This enables the provision of optimal learning materials tailored to the learner's individual level of understanding and prompt and appropriate answers to questions.

[1471] "Artificial intelligence" is a technology in which computer systems imitate human intelligence and perform learning, reasoning, and problem-solving.

[1472] An "interactive program" is software that provides information and answers questions through dialogue with the user using natural language.

[1473] The "field of education a...

Claims

1. A system comprising a data processing device capable of communicating with a terminal used by a learner, The data processing device comprises a processor, storage, database, and communication interface. The aforementioned processor, The terminal receives input data indicating the learner's question or request via the aforementioned communication interface. By analyzing the aforementioned input data, the subject or topic corresponding to the aforementioned question or request is identified. Information regarding the identified subject or topic is obtained from the database, The learner's level of understanding is evaluated by analyzing the learner's past questions or past interaction data. Based on the acquired information and the evaluated level of understanding, prompt statements are created to cause the generative AI model to generate answers to the questions or requests. The aforementioned prompt sentence is a sentence for adjusting the level of detail or method of explanation of the information included in the answer according to the level of understanding. The prompt statement is input to the generation AI model, The response output from the AI ​​model is transmitted to the terminal via the communication interface. system.

2. The system according to claim 1, wherein the processor analyzes the audio data or text data contained in the input data received from the terminal to determine the emotional state of the learner, and adjusts the method of expressing the response according to the determined emotional state.

3. The system according to claim 1, wherein the processor creates a prompt statement to include information of a first level of detail in the answer when the level of understanding is a first level of understanding, and creates a prompt statement to include information of a second level of detail that is higher than the first level of detail in the answer when the level of understanding is a second level of understanding that is higher than the first level of understanding.

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