System

Abstract

To provide a system that enhances the security and reliability of a guardian, while reducing working hours and maximizing communication effect.SOLUTION: A system includes: means for managing a communication notebook for communicating with a guardian; means for receiving contents of the communication notebook transmitted by the guardian; means for analyzing a feeling state of the guardian using a feeling engine on the basis of the contents of the communication notebook; means for generating a reply sentence draft using a prompt sentence for instructing generation of the reply sentence draft and a generative AI model on the basis of the contents of the communication notebook and the feeling state of the guardian; and means for transmitting the generated reply sentence draft to a terminal of a teacher.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

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

[0003] [Patent Document 1] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] Communication with parents in the educational field is important to increase parents' sense of security and trust. However, to communicate smoothly, appropriate speaking and expressive skills are required, which require experience and skill. In addition, creating replies to meet the diverse needs of parents increases the workload of teachers, making it difficult to reduce work hours and improve efficiency. [Means for solving the problem]

[0005] The present invention manages a contact book for communicating with parents and instantly grasps the needs of parents using AI that has learned the speaking techniques of veteran teachers.Then, by providing reply suggestions generated by the AI, it increases parents' sense of security and trust, shortens work hours, and maximizes communication effectiveness. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13]FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15] FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16] FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. [Figure 19] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system according to the embodiment 2 of the second embodiment in the case where an emotion engine is combined. [Figure 20] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when combined with an emotion engine. [Figure 21] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the embodiment 3 of the form example 3 in the case where an emotion engine is combined. [Figure 22] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

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

[0008] do.

[0009] First, the terms used in the following description will be explained.

[0010] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0011] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by the processor.

[0012] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0013] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0014] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0015] [First embodiment]

[0016] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0021] 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 of expression that the user 20 can perceive (e.g., voice 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 voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0024] As shown in Fig. 2, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific process program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0026] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out 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 the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0027] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0028] "Example 1"

[0029] The present invention is a system for managing a notebook for communicating with parents. This system uses AI that has learned the speaking techniques of veteran teachers to instantly grasp the needs of parents. Specifically, the AI ​​analyzes the contents of the notebook from parents and generates an appropriate reply proposal for that content. The generated reply proposal is designed to increase the parents' sense of security and trust, and teachers use it as a reference when replying to parents.

[0030] "Example 2"

[0031] As one aspect of the present invention, reply suggestions generated by AI shorten the work hours of teachers while maximizing the effectiveness of communication. Specifically, by using reply suggestions generated by AI, teachers can significantly reduce the time it takes to compose reply sentences. In addition, since the reply suggestions generated by AI have learned the speaking techniques of veteran teachers, their contents increase the teacher's trust in parents. This facilitates smooth communication between teachers and parents, improving the quality of education.

[0032] "Example 3"

[0033] As one aspect of the present invention, the AI ​​learns the speaking techniques of veteran teachers by using reply sentences used by teachers in the past and feedback from teachers as learning data. Specifically, the AI ​​uses this learning data to generate appropriate reply sentences for various inquiries and requests from parents. This allows teachers to instantly obtain reply sentences to meet the various needs of parents, realizing efficient communication.

[0034] The process flow of each embodiment will be described below.

[0035] "Example 1"

[0036] Step 1: The system receives the contents of the communication book from parents.

[0037] Step 2: The AI ​​analyzes the received content. For this analysis, an AI that has learned the speaking techniques of veteran teachers is used.

[0038] Step 3: The AI ​​instantly identifies the parent's needs and generates appropriate response suggestions.

[0039] Step 4: The generated reply proposal is provided to the teacher, who can use it to respond to the parent.

[0040] "Example 2"

[0041] Step 1: The teacher reviews the reply suggestions generated by the AI.

[0042] Step 2: Teachers can significantly reduce the time it takes to write responses.

[0043] Step 3: Communication between teachers and parents is smooth, improving the quality of education.

[0044] "Example 3"

[0045] Step 1: The AI ​​uses the reply sentences used by teachers in the past and feedback from teachers as learning data.

[0046] Step 2: Based on this learning data, the AI ​​generates appropriate reply sentences for various inquiries and requests from parents.

[0047] Step 3: Teachers can instantly receive response text to address various needs from parents, achieving efficient communication.

[0048] Example 1

[0049] Next, a description will be given of Example 1 of the embodiment 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".

[0050] In the conventional communication book management system, teachers had to manually create replies to each communication with parents, which was time-consuming and labor-intensive. It was also sometimes difficult to properly understand the needs and feelings of parents and write replies that would increase their reassurance and trust. This resulted in issues such as a decrease in the effectiveness of communication and an increase in the workload of teachers.

[0051] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0052] In this invention, the server includes a means for managing a communication notebook for communicating with parents, a means for instantly grasping the needs of parents using artificial intelligence that has learned the speaking skills of veteran teachers, a means for providing reply suggestions generated by the artificial intelligence, a means for receiving the contents of the communication notebook from parents, a means for analyzing the received communication notebook contents using natural language processing technology, a means for generating appropriate reply suggestions based on the analysis results, a means for presenting the generated reply suggestions to the teacher's terminal, and a means for the teacher to create a final reply and send it to the parent's terminal. This makes it possible to appropriately grasp the needs and feelings of parents and to reply quickly and effectively.

[0053] "Guardian" refers to the parent or guardian of a child attending an educational institution, who is responsible for communicating and advising on the child's education and life.

[0054] A "communication notebook" is a means for parents and teachers to exchange information about their children's education and daily life, and is provided in either paper or digital form.

[0055] "Means of management" refers to a system or software that has the functionality to store, organize, search, and display the contents of the address book.

[0056] "Artificial intelligence" refers to computer programs and systems that use technologies such as machine learning and natural language processing to mimic human intelligence and perform certain tasks automatically.

[0057] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language, and is used to analyze and generate text data.

[0058] "Reply proposal" refers to a draft message generated by artificial intelligence to suggest an appropriate reply to a message from a parent.

[0059] "Teachers" refers to teachers and instructors who are responsible for educating children at educational institutions and who have the role of communicating with and consulting with parents.

[0060] A "terminal" is a device that a user uses to access and operate the system, and includes smartphones, tablets, PCs, etc.

[0061] "Means of analysis" refers to systems or software that have the function of analyzing the received communication book contents using natural language processing technology and extracting the needs and feelings of parents.

[0062] "Means for generating" refers to a system or software that has the functionality for generating appropriate reply suggestions based on the analysis results.

[0063] "Means of presentation" refers to a system or software that has the function of displaying the generated reply draft on the teacher's terminal so that the teacher can check and correct it.

[0064] "Means of sending" refers to a system or software that has the function of sending the final reply prepared by the teacher to the parent's device.

[0065] This invention is a system for managing a contact book for communicating with parents, and uses artificial intelligence that has learned the speaking skills of veteran teachers to instantly grasp the needs of parents and generate appropriate reply proposals. This system is implemented using the following hardware and software.

[0066] Hardware and Software Used

[0067] Server: Receives and analyzes the contents of the address book, and generates and sends reply proposals.

[0068] Devices: Devices used by parents and teachers (smartphones, tablets, computers, etc.).

[0069] Generative AI model: Analyzes the contents of the contact list using natural language processing technology and generates reply suggestions. Specifically, Google's BERT and OpenAI's GPT-4 are used.

[0070] Data processing and calculation

[0071] 1. Receiving communication from parents:

[0072] The server receives the contents of the address book sent by the parent from the device. The contents of the address book are stored in the server in text format.

[0073] 2. Analysis of address book contents:

[0074] The server then uses natural language processing technology to analyze the contents of the contact book received. A generative AI model is used for this analysis. The generative AI model analyzes the text data and extracts the needs and emotions of the parents.

[0075] 3. Generate reply suggestions:

[0076] The server generates appropriate reply suggestions based on the analysis results. The generative AI model generates responses that correspond to the needs and feelings of the parent.

[0077] 4. Response suggestions:

[0078] The server sends the generated reply draft to the teacher's terminal, where the teacher can check the reply draft and make corrections if necessary.

[0079] 5. Instructor creates final response:

[0080] The teacher uses the generated reply draft as a reference to create a final reply to the parent / guardian. The final reply is sent from the teacher's terminal to the parent / guardian's terminal via the server.

[0081] Examples

[0082] For example, if a parent writes in the communication book, "I'm worried that my child's grades at school have been dropping recently," the server receives this content and inputs the following prompt sentence into the generative AI model:

[0083] Example prompt:

[0084] "A parent writes: 'I'm worried that my child's grades at school have been dropping recently. Please generate an appropriate response to this.'"

[0085] Based on this prompt, the generative AI model generates the following reply suggestions:

[0086] "We understand that you are concerned about your child's grades. Please rest assured that we are prepared to monitor your child's progress and provide any support they may need, including individualized tutoring and additional learning resources."

[0087] Teachers will use these reply suggestions to create and send a final reply to parents.

[0088] The above is an embodiment of the present invention.

[0089] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0090] Step 1:

[0091] Receiving communication from parents

[0092] The server receives the contents of the address book sent by the guardian from the device. The input is a text message sent by the guardian using the device. The server stores this text message in a database. In concrete terms, when the guardian logs into the address book app on the device, enters a message and presses the send button, the server receives the message and stores it in the database.

[0093] Step 2:

[0094] Analysis of contact list contents

[0095] The server analyzes the received address book contents using natural language processing technology. The input is the text message saved in step 1. The server inputs this text data into a generative AI model to extract the guardian's needs and emotions. In concrete terms, the server inputs the text data into a generative AI model (e.g., GPT-4), and the model analyzes the text to extract the guardian's needs and emotions.

[0096] Step 3:

[0097] Generate reply suggestions

[0098] The server generates an appropriate reply draft based on the analysis results. The input is the needs and feelings of the parent extracted in step 2. The server inputs a prompt text to the generative AI model and generates a reply draft. In concrete terms, the server inputs the prompt text "Contents from the parent's message book: My child's grades at school have been dropping recently, and I'm worried. Please generate an appropriate reply draft in response to this" to the generative AI model, and the model generates an appropriate reply draft.

[0099] Step 4:

[0100] Response suggestions

[0101] The server sends the generated reply draft to the teacher's terminal. The input is the reply draft generated in step 3. The server sends this reply draft to the teacher's terminal so that the teacher can check it. In concrete terms, the server sends the generated reply draft to the teacher's terminal, and the teacher checks the reply draft on the terminal.

[0102] Step 5:

[0103] Instructor creates final reply

[0104] The teacher uses the generated reply draft as a reference to create a final reply to the parent. The input is the reply draft presented in step 4. The teacher checks the reply draft on the terminal, corrects it if necessary, and creates a final reply. In concrete terms, the teacher checks the reply draft on the terminal, corrects it if necessary, creates a final reply, and presses the send button.

[0105] Step 6:

[0106] Sending a final reply

[0107] The server sends the final reply created by the teacher to the parent's terminal. The input is the final reply created by the teacher in step 5. The server sends this final reply to the parent's terminal. In concrete terms, the server sends the final reply created by the teacher to the parent's terminal, and the parent checks the final reply on the terminal.

[0108] (Application example 1)

[0109] Next, a description will be given of 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."

[0110] With the conventional contact book management system, communication with parents was not smooth, and it was difficult to quickly grasp the needs of parents. In addition, it was difficult for store staff to respond appropriately and quickly to inquiries from customers, making it an issue to improve customer satisfaction. This has led to a demand for more efficient work hours and maximizing communication effectiveness.

[0111] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0112] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using a generative AI model that has learned the speaking skills of veteran teachers, a means for providing reply suggestions generated by the generative AI model, a means for analyzing the content of inquiries from customers and generating appropriate reply suggestions, and a means for displaying the generated reply suggestions to store staff. This makes it possible to quickly grasp the needs of parents and customers and provide appropriate replies. This allows for the shortening of work hours and the maximization of communication effectiveness.

[0113] "Parent" refers to the parent or guardian of a child attending an educational institution.

[0114] "Communication" refers to the act of transmitting information and emotions.

[0115] A "communication book" refers to a document or digital tool for exchanging information between parents and educational institutions.

[0116] "Means of management" refers to how information is organized, stored, and updated using systems and tools.

[0117] A "veteran teacher" refers to an educator with many years of experience and a high level of specialized knowledge.

[0118] "Speaking" refers to the skill of conveying information effectively using words.

[0119] A "generative AI model" refers to an algorithm that uses artificial intelligence techniques to generate an output for a specific task.

[0120] "Parent needs" refers to the demands and expectations that parents have.

[0121] "Means of instantaneous understanding" refers to a method for understanding information in a short amount of time and taking appropriate action.

[0122] "Response Draft" means a draft response to a particular inquiry or message.

[0123] "Means of providing" refers to the method of presenting the generated information to the user.

[0124] "Customer" refers to a person who purchases goods or services.

[0125] "Inquiry content" refers to information submitted by a customer or guardian as a question or request.

[0126] "Means of analysis" refers to a method for analyzing input information and understanding its meaning.

[0127] "Store staff" refers to employees working in physical stores.

[0128] "Means of display" refers to the way in which information is visually presented to the user.

[0129] The system for carrying out this invention is configured as follows: First, the server has a means for managing a contact book for communication with parents. This means provides a function for storing the contents of contact from parents in a digital format and updating them as necessary.

[0130] Next, the server uses a generative AI model that has learned the speaking skills of veteran teachers to instantly grasp the needs of parents. This generative AI model analyzes the content of messages from parents and generates appropriate reply proposals based on the content. This analysis and generation process uses artificial intelligence technologies such as OpenAI's API.

[0131] The server further includes a means for providing the generated reply draft, which is capable of presenting the generated reply draft to a staff member of the educational institution so that the staff member can use the reply draft to the parent / guardian as a reference.

[0132] The server also has a means for analyzing the content of customer inquiries and generating appropriate reply suggestions. This means is used to support customer service in physical stores. It receives the content of customer inquiries as input, analyzes them using a generative AI model, and generates appropriate reply suggestions.

[0133] Finally, the server has a means for displaying the generated reply proposal to the store staff. This means displays the generated reply proposal on a terminal such as a smartphone or tablet, enabling the store staff to respond to the customer by referring to it.

[0134] As a concrete example, if a customer inquires, "Please tell me how to return an item," the server inputs the inquiry into the generative AI model and generates an appropriate reply proposal. The generated reply proposal is, "We will guide you through how to return the item. First, please prepare your purchase receipt. Then, bring it to the store together with the item, and a staff member will assist you." This reply proposal is displayed on the terminal of the store staff, who use it as a reference when responding to the customer.

[0135] The following is an example of a prompt sentence:

[0136] Customer Question: How do I return an item? Please reply like a veteran staff member.

[0137] In this way, it becomes possible to quickly grasp the needs of parents and customers and provide appropriate responses, thereby reducing work time and maximizing communication effectiveness.

[0138] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0139] Step 1:

[0140] The user (parent or customer) enters the inquiry.

[0141] Input: Enquiry content (text format)

[0142] Specific operation: A user uses a smartphone or tablet application to input the content of an inquiry. For example, the user inputs, "Please tell me how to return a product."

[0143] Step 2:

[0144] The server receives the query and generates a prompt to input to the generative AI model.

[0145] Input: Enquiry content (text format)

[0146] Output: Prompt statement (text format)

[0147] Specific operation: The server receives the inquiry and converts it into a prompt sentence in a format suitable for the generative AI model. For example, it generates a prompt sentence such as "Customer inquiry: How do I return the product? Please reply like a veteran staff member."

[0148] Step 3:

[0149] The server uses a generative AI model to generate reply suggestions based on the prompt.

[0150] Input: Prompt sentence (text format)

[0151] Output: Reply proposal (text format)

[0152] Specific operation: The server calls the generative AI model (e.g., OpenAI's API) and provides the prompt as input. The generative AI model analyzes the prompt and generates an appropriate reply proposal. For example, it generates a reply proposal that reads, "We will guide you through how to return the product. First, please prepare your purchase receipt. Then, please bring it to the store together with the product, and a staff member will assist you."

[0153] Step 4:

[0154] The server transmits the generated reply text proposal to the terminal.

[0155] Input: Reply proposal (text format)

[0156] Output: Reply proposal (text format)

[0157] Specific operation: The server sends the generated reply text suggestions to the user's terminal, which receives and displays the reply text suggestions.

[0158] Step 5:

[0159] The device displays reply suggestions to the user.

[0160] Input: Reply proposal (text format)

[0161] Output: Displayed reply suggestions (visual display)

[0162] Specific operation: The terminal displays the received reply message on the screen so that the user can confirm it. For example, the following message may be displayed on the smartphone screen: "We will guide you through how to return the product. First, please prepare your purchase receipt. Then, bring it together with the product to the store and a staff member will assist you."

[0163] Step 6:

[0164] The user refers to the generated reply proposal and takes appropriate action with respect to the parent or customer.

[0165] Input: Response suggestions displayed (visual display)

[0166] Output: User's response action

[0167] Specific operation: The user (staff member of the educational institution or the store staff member) responds appropriately to the guardian or customer by referring to the displayed reply text suggestions. For example, the store staff member may explain to the customer, "We will explain how to return the product. First, please prepare the receipt from the time of purchase. Then, please bring it together with the product to the store, and the staff member will assist you."

[0168] Example 2

[0169] Next, a second embodiment of the second embodiment will be described. 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."

[0170] In traditional educational settings, it took a lot of time and effort for teachers to communicate smoothly with parents. In particular, writing replies to emails from parents was a heavy burden for teachers. In addition, the quality of the replies was directly linked to the parents' trust and sense of security, so the content of the replies was required to be of high quality. This increased teachers' work hours and could have an impact on the quality of education.

[0171] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0172] In this invention, the server includes a means for sending emails received by a user to the server, a means for generating a prompt sentence for inputting the email received by the server to the generative AI model, and a means for the server to input the prompt sentence to the generative AI model and generate a reply sentence proposal. This enables teachers to quickly generate high-quality reply sentences to emails from parents. This can significantly reduce the teacher's work time and maximize the effectiveness of communication with parents.

[0173] "Guardian" refers to the parent or guardian of a child or student attending an educational institution.

[0174] "Communication" refers to the exchange of information between teachers and parents.

[0175] A "communication notebook" refers to a means for teachers and parents to share information about children's and students' learning and living situations.

[0176] "Means of management" refers to the method or system for organizing the contents of the contact book and properly storing and updating it.

[0177] A "veteran teacher" is a teacher who has many years of teaching experience and has excellent leadership and communication skills.

[0178] "Speaking" refers to the techniques and methods of effectively conveying information using words.

[0179] "Artificial intelligence" refers to technology that enables computer systems to mimic human intelligence and perform learning and reasoning.

[0180] "Needs" refers to the demands and expectations that parents have.

[0181] "Means of instant identification" refers to methods and systems for quickly understanding parents' needs and responding appropriately.

[0182] "Response draft" refers to a draft response to inquiries or requests from parents.

[0183] "Means for providing" refers to a method or system for presenting the generated reply suggestions to the user.

[0184] "User" refers to the teacher who uses this system.

[0185] "Server" refers to a computer system for processing and storing data.

[0186] "Generative AI model" refers to a model for generating text using artificial intelligence technology.

[0187] A "prompt sentence" refers to an instruction sentence to be input into a generative AI model.

[0188] "Terminal" refers to a device such as a computer or smartphone used by a user.

[0189] "Means for modification" refers to a method or system that allows a user to edit or modify the generated reply proposal.

[0190] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0191] The present invention is a system for enabling teachers to smoothly communicate with parents, and generates reply proposals using artificial intelligence technology. A specific embodiment of this system is described below.

[0192] Hardware and Software Used

[0193] The system uses the following hardware and software:

[0194] Server: A computer system for processing and storing data. For example, a cloud server or an on-premise server is used.

[0195] Terminal: A device such as a computer or smartphone used by a user. Examples include PCs, tablets, and smartphones.

[0196] Generative AI model: A model for generating text using artificial intelligence techniques, such as OpenAI's GPT-4.

[0197] System Operation

[0198] After receiving the email from the parent, the user (teacher) opens a dedicated web application, copies and pastes the received email, and then clicks the "Send" button to send the email to the server.

[0199] The server analyzes the content of the received email and generates a prompt to input to the generative AI model. For example, it generates the following prompt:

[0200] "Parents emailed me saying: 'I'm worried about my child's grades. How can I help?'"

[0201] The server inputs the generated prompt sentence into the generative AI model. The generative AI model generates appropriate reply sentence suggestions based on the prompt sentence. For example, it generates reply sentence suggestions like the following:

[0202] "Thank you for your support. I understand that you are worried about your child's grades. First of all, it is important to create a good learning environment at home. Specifically, I recommend that you set a time each day to study and create an environment where your child can concentrate. Also, please rest assured that we will be providing comprehensive support at school."

[0203] The server then sends the generated reply suggestions to the user's device, where the user can review the reply suggestions through a dedicated interface and make corrections as necessary, for example by adding additional information tailored to the specific situation or fine-tuning the wording.

[0204] The user then sends the revised reply to the parent, thereby achieving quick and effective communication.

[0205] Examples

[0206] For example, if a user receives an email from a parent saying, "I'm worried about my child's grades. How can I help them?", the user sends this email to the server, which generates the following prompt:

[0207] "Parents emailed me saying: 'I'm worried about my child's grades. How can I help?'"

[0208] Based on this prompt, the generative AI model generates the following reply suggestions:

[0209] "Thank you for your support. I understand that you are worried about your child's grades. First of all, it is important to create a good learning environment at home. Specifically, I recommend that you set a time each day to study and create an environment where your child can concentrate. Also, please rest assured that we will be providing comprehensive support at school."

[0210] The user checks the reply draft, modifies it as necessary, and then sends it to the guardian. Through this process, the user can quickly generate a high-quality reply, enabling smooth communication with the guardian.

[0211] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0212] Step 1:

[0213] The user receives an email from a parent.

[0214] Specific operation: A user (teacher) receives an email from a parent in his / her own email account. For example, a parent may receive an email saying, "I'm worried about my child's grades. How can I support him / her?"

[0215] Enter: Email from parent.

[0216] Output: The content of the received email.

[0217] Step 2:

[0218] The user sends the received email to the server.

[0219] Specific operation: A user opens a dedicated web application, copies and pastes the received email, and then clicks the "Send" button to send the email to the server.

[0220] Input: The content of the received email.

[0221] Output: The content of the email sent to the server.

[0222] Step 3:

[0223] The server generates a prompt sentence to input the received email into the generative AI model.

[0224] Specific operation: The server analyzes the contents of the received email and generates a prompt sentence to input to the generative AI model. For example, it creates a prompt sentence such as "Contents of email from parent: 'I'm worried about my child's grades. How can I support him?'"

[0225] Input: The content of the email sent to the server.

[0226] Output: The generated prompt statement.

[0227] Step 4:

[0228] The server inputs the prompt text into the generative AI model and generates reply text suggestions.

[0229] Specific operation: The server inputs the generated prompt sentence into a generative AI model (for example, OpenAI's GPT-4). The generative AI model generates an appropriate reply sentence proposal based on the prompt sentence. For example, it generates a reply sentence proposal that reads, "Thank you for your support. I understand that you are worried about your child's grades. First of all, it is important to create a good learning environment at home. Specifically, I recommend that you decide on a daily study time and create an environment where your child can concentrate. We will also provide comprehensive support at school, so please rest assured."

[0230] Input: The generated prompt statement.

[0231] Output: The generated reply suggestions.

[0232] Step 5:

[0233] The server transmits the generated reply sentence proposal to the user's terminal.

[0234] Specific operation: The server sends the generated reply text suggestions to the user's terminal, and the user can check the reply text suggestions through a dedicated interface.

[0235] Input: The generated reply suggestion.

[0236] Output: Reply proposal sent to the user's device.

[0237] Step 6:

[0238] The user reviews the reply proposal and modifies it if necessary.

[0239] What happens: The user reviews the reply text sent by the server and makes corrections if necessary, for example adding additional information to suit the specific situation or fine-tuning the wording.

[0240] Input: A reply proposal sent to the user's device.

[0241] Output: The revised reply proposal.

[0242] Step 7:

[0243] The user sends the corrected reply text to the parent.

[0244] Specific operation: The user sends the revised reply to the parent, thereby achieving quick and effective communication.

[0245] Input: Revised reply proposal.

[0246] Output: The reply sent to the parent.

[0247] (Application example 2)

[0248] Next, a description will be given of 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 will be referred to as a "terminal."

[0249] In the conventional system, teachers and staff had to spend a lot of time communicating with parents and customers, which led to a decrease in work efficiency. In addition, the quality of the replies was not consistent, which led to a lack of trust and security. This could lead to a decrease in the quality of education and customer satisfaction.

[0250] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0251] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents by an AI that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the AI, a means for the AI ​​to automatically generate reply proposals in response to inquiries from customers, a means for the AI ​​to provide highly reliable replies that have learned the responses of veteran staff, and a means for facilitating communication with customers and improving customer satisfaction. This makes it possible to reduce the work hours of teachers and staff and maximize the effectiveness of communication.

[0252] A "communication notebook" is a ledger or digital tool for recording and managing information for communicating with parents.

[0253] A "veteran teacher" refers to an educator with many years of experience and a high level of specialized knowledge.

[0254] "Speaking skills" refers to the use of words and expression techniques for effective communication.

[0255] "AI" is an abbreviation for artificial intelligence, a technology that uses machine learning and natural language processing to mimic human intelligence.

[0256] "Parent needs" refers to the information and support that parents seek in education and child-rearing.

[0257] "Response suggestions" refers to documents that suggest appropriate responses to specific inquiries or situations.

[0258] "Customer" refers to a person who purchases or uses a product or service.

[0259] An "Inquiry" is a question or request made for information or assistance.

[0260] "Veteran staff" refers to employees with many years of experience and high levels of specialized knowledge.

[0261] "Reliability" refers to information and services being accurate and functioning as expected.

[0262] "Customer satisfaction" refers to the degree of satisfaction a customer feels toward a product or service.

[0263] "Task time" refers to the time spent performing a particular task.

[0264] "Communication effectiveness" is an indicator that shows how effectively information is transmitted and communication is carried out.

[0265] The system for carrying out this invention is composed of three main components: a server, a terminal, and a user. The server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents by an AI that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the AI, a means for an AI to automatically generate reply proposals in response to inquiries from customers, a means for an AI to provide reliable replies that have learned the responses of veteran staff, and a means for facilitating communication with customers and improving customer satisfaction.

[0266] Hardware and Software Used

[0267] Hardware: Smartphones, servers

[0268] Software: Python, OpenAI API (GPT-3 (registered trademark))

[0269] Data processing and calculation

[0270] The server first receives an inquiry from a parent or customer. It then generates a prompt based on the content of the inquiry. This prompt is input into an AI model that has learned the speaking skills of veteran teachers and staff. The AI ​​model generates an appropriate reply proposal based on the input prompt. The generated reply proposal is sent from the server to the terminal and provided to the user.

[0271] Examples

[0272] For example, if a customer asks "How do I return an item?" the server might generate the following prompt:

[0273] Customer Question: How do I return an item?

[0274] Please reply like a veteran staff member.

[0275] If you feed this prompt into OpenAI's GPT-3 API, it will generate the following reply:

[0276] Hello, customer. We would like to inform you of the return method for your product. First, please fill in the return form that we sent you together with the product and enclose it with the product. After that, please send it to the specified return address and we will proceed with the return procedure. If you have any questions, please feel free to contact us.

[0277] The reply proposals generated in this way are sent from the server to the terminal and provided to the user, which reduces the work time of teachers and staff and maximizes the effectiveness of communication.

[0278] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0279] Step 1:

[0280] The server receives inquiries from parents and customers.

[0281] Input: Inquiries from parents and customers

[0282] Output: Text data of the inquiry

[0283] Specific operation: The server saves the content of inquiries received through interfaces such as inquiry forms and emails as text data.

[0284] Step 2:

[0285] The server generates a prompt sentence based on the received query.

[0286] Input: Text data of inquiry

[0287] Output: Prompt statement

[0288] Specific operation: Based on the inquiry content, the server generates a prompt sentence in the form of "Customer inquiry: [Inquiry content] Please reply like an experienced staff member."

[0289] Step 3:

[0290] The server sends the generated prompt text to OpenAI's GPT-3 API.

[0291] Input: prompt statement

[0292] Output: Request to the GPT-3 API

[0293] What happens: The server formats the generated prompt as an API request and sends it to OpenAI's GPT-3 API.

[0294] Step 4:

[0295] The server receives the reply sentence proposal from the GPT-3 API.

[0296] Input: A request to the GPT-3 API

[0297] Output: Reply proposal

[0298] Specific operation: The server receives the reply sentence proposal returned from the GPT-3 API and stores it as text data.

[0299] Step 5:

[0300] The server transmits the generated reply text proposal to the terminal.

[0301] Input: Reply proposal

[0302] Output: Data sent to the terminal

[0303] Specific operation: The server converts the reply text proposal into an appropriate format and sends it to the user's device.

[0304] Step 6:

[0305] The terminal displays the received reply sentence suggestions to the user.

[0306] Input: Data to send to the terminal

[0307] Output: Reply suggestions shown to the user

[0308] Specific operation: The device displays the received reply proposal on the screen for the user to review.

[0309] Step 7:

[0310] The user checks the displayed reply draft and, if necessary, modifies or sends it.

[0311] Input: A suggested reply that will be displayed to the user

[0312] Output: revised reply proposal or sent reply

[0313] Specific behavior: The user reviews the proposed reply, makes corrections if necessary, and then submits it as the final reply.

[0314] Example 3

[0315] Next, a third embodiment of the third embodiment will be described. 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."

[0316] In the past, teachers had to spend a lot of time writing replies, making it difficult to communicate efficiently. In addition, because the quality of the replies depended on the teacher's experience and skills, parents were often unable to feel reassured or trusted by the replies. This resulted in an increase in the teacher's workload and a decrease in the effectiveness of communication.

[0317] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0318] In this invention, the server includes a means for collecting reply sentences and feedback used by teachers in the past and storing them in a database, a means for training a generative AI model using the collected data, and a means for generating appropriate reply sentences using the generative AI model. This enables teachers to quickly obtain appropriate reply sentences in response to inquiries and requests from parents.

[0319] A "communication book" is a recording medium for communication between parents and teachers, and may include paper or electronic media.

[0320] "Artificial intelligence" is the technology that enables computer systems to mimic human intelligence and learn, reason, and self-correct.

[0321] A "generative AI model" is a type of artificial intelligence that has the ability to generate new data based on a specific dataset.

[0322] A "database" is a system for efficiently storing, managing, and searching data.

[0323] An "interface" is the means by which a user interacts with a system, including input forms and graphical user interfaces (GUIs).

[0324] A "server" is a computer system that provides services to other computers over a network.

[0325] A "terminal" is a computer device that is directly operated by a user, and includes a PC, tablet, smartphone, etc.

[0326] An "inquiry" refers to a question or request that a parent or guardian makes to a teacher.

[0327] A "reply letter" is a letter that a teacher sends to a parent / guardian to answer or provide information.

[0328] "Feedback" refers to evaluations and opinions received from teachers regarding past communication.

[0329] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0330] The present invention provides a system for improving the efficiency of communication with parents and reducing the workload of teachers. A specific embodiment of this system will be described below.

[0331] Hardware and software used

[0332] Hardware: Servers, terminals (PCs, tablets, smartphones)

[0333] Software: Generative AI models (e.g., OpenAI GPT-4), database management systems (e.g., MySQL (registered trademark))

[0334] Server Roles

[0335] The server collects teachers' past reply phrases and feedback and stores them in a database. Specifically, the server extracts data from teachers' email accounts and the school's communication system and stores it in a MySQL database. Next, the server uses the collected data to train a generative AI model (e.g., OpenAI GPT-4). The generative AI model learns teachers' speaking skills and reply patterns and has the ability to generate appropriate reply phrases to inquiries from parents.

[0336] Terminal Roles

[0337] The terminal provides an interface for teachers to input questions and requests from parents. Specifically, the terminal displays an input form through a web browser or a dedicated app, and teachers input the questions into the form. The input data is sent to the server as an HTTP request.

[0338] User Roles

[0339] The user (teacher) uses the device to input inquiries and requests from parents. Once input is complete, the device sends the data to the server. The server uses a generative AI model to generate an appropriate reply text and sends the result back to the user's device. The user checks the generated reply text, makes corrections if necessary, and then sends it back to the parent.

[0340] Examples

[0341] For example, if a parent asks, "My child's grades seem to have dropped recently. How can I support him?", the teacher enters this information into the device. The device sends the entered data to the server, which uses a generative AI model to generate an appropriate reply. The generated reply might be something like, "I understand that you are worried about your child's grades. First of all, I would recommend that you review the learning environment at home and ensure that they set aside regular study time. I would also like to hear about the support system at school."

[0342] In this way, the teacher can quickly and appropriately reply to inquiries from parents. This reduces the workload of the teacher and improves the quality of communication with parents. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0343] Step 1:

[0344] The server collects the teacher's past reply sentences and feedback and stores them in a database. Specifically, the server extracts data from the teacher's email account and the school's communication system and stores it in a MySQL database. The input is the teacher's past reply sentences and feedback, and the output is the data stored in the database.

[0345] Step 2:

[0346] The server trains the generative AI model using the collected data. Specifically, the server reads data from the database and feeds it to the generative AI model (e.g., OpenAI GPT-4). The model learns the teacher's speaking style and reply patterns. The input is the data read from the database, and the output is the trained generative AI model.

[0347] Step 3:

[0348] The terminal provides an interface for teachers to input inquiries and requests from parents. Specifically, the terminal displays an input form through a web browser or a dedicated app, and teachers input the inquiries into the form. The input is the inquiries from parents, and the output is the data entered into the input form.

[0349] Step 4:

[0350] The terminal sends the entered data to the server. Specifically, the terminal sends the entered inquiry content to the server as an HTTP request. The input is the data entered into the input form, and the output is the data sent to the server.

[0351] Step 5:

[0352] The server generates an appropriate reply sentence using a generative AI model. Specifically, the server inputs the received query content into the generative AI model and obtains the generated reply sentence from the model. The input is the query content sent to the server, and the output is the generated reply sentence.

[0353] Step 6:

[0354] The server returns the generated reply text to the terminal. Specifically, the server sends the generated reply text to the terminal as an HTTP response. The input is the generated reply text, and the output is the reply text sent to the terminal.

[0355] Step 7:

[0356] The terminal displays the generated reply text to the teacher. Specifically, the terminal displays the received reply text on the screen so that the teacher can check it. The input is the reply text received from the server, and the output is the reply text displayed on the screen.

[0357] Step 8:

[0358] The user (teacher) checks the generated reply text, makes corrections if necessary, and then replies to the parent. Specifically, the user edits the reply text on the terminal and clicks the send button. The input is the generated reply text and the corrections made by the user, and the output is the final reply text sent to the parent.

[0359] (Application example 3)

[0360] Next, a description will be given of 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 will be referred to as a "terminal."

[0361] In conventional communication systems with parents, teachers had to prepare reply messages individually, which was time-consuming and labor-intensive. In addition, in brick-and-mortar stores, it was difficult for staff to respond quickly and appropriately to customer inquiries, which could lead to a decline in customer satisfaction. There is a need to solve these problems and achieve efficient and effective communication.

[0362] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0363] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents by an AI that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the AI, a means for quickly and appropriately replying to inquiries from customers, a means for proposing optimal replies to customer questions and requests by an AI that has learned from excellent customer service responses in the past, and a means including an application to be installed on a smartphone. This allows teachers to instantly obtain reply proposals to meet various needs from parents, and enables staff at physical stores to quickly and appropriately respond to customers.

[0364] "Guardian" refers to the parent or guardian of a child or student attending an educational institution.

[0365] "Communication" refers to the act of exchanging information and ideas.

[0366] A "communication book" refers to a written or electronic means for parents and teachers to exchange information.

[0367] A "veteran teacher" is a teacher who has many years of experience and possesses excellent teaching and speaking skills.

[0368] "Speaking" refers to the skill of conveying information effectively using words.

[0369] "AI" is an abbreviation for artificial intelligence and refers to the technology that allows machines to imitate human intelligence to learn and make judgments.

[0370] "Need" refers to a particular demand or requirement.

[0371] "Response Suggestion" means a suggested response to an inquiry or request.

[0372] A "system" refers to a combination of multiple elements that perform a specific function.

[0373] "Customer" refers to a person who purchases goods or services.

[0374] "Inquiry" refers to the act of requesting information or clarification.

[0375] "Rapid" means to act very quickly.

[0376] "Appropriate" means appropriate to the situation or purpose.

[0377] "Customer service" refers to the service and interaction provided to customers.

[0378] A "smartphone" is a type of mobile phone that is a multi-function device that can connect to the Internet and use applications.

[0379] "Application" refers to software that provides specific functions or services.

[0380] A system for implementing this invention is configured as follows. First, the server has a means for managing a contact book for communicating with parents. This contact book is a written or electronic means for parents and teachers to exchange information. Next, the server has a means for instantly grasping the needs of parents using AI that has learned the speaking techniques of veteran teachers. This AI learns excellent teaching techniques and speaking techniques from the past, and generates appropriate reply proposals for inquiries and requests from parents.

[0381] Furthermore, the server has a means for quickly and appropriately responding to customer inquiries. This means uses AI that has learned from past excellent customer service responses to suggest optimal responses to customer questions and requests. This enables staff at physical stores to respond to customers quickly and appropriately.

[0382] The system includes an application that is installed on a smartphone. The smartphone is connected to the Internet and can receive generated reply suggestions by communicating with the server. Specifically, when a staff member enters a customer inquiry into the smartphone, the server uses AI to generate an appropriate reply suggestion and sends it to the smartphone.

[0383] The hardware used is a smartphone connected to the Internet. The software uses Python and the OpenAI API. Python is used as the program execution environment, and the OpenAI API is used to generate reply sentence suggestions using an AI model.

[0384] As a concrete example, if a customer asks, "Please tell me more about this product," the staff member enters this inquiry into his smartphone. The server generates the following prompt sentence and inputs it into the AI ​​model.

[0385] Example prompt:

[0386] Customer Inquiry: Can you tell me more about this product?

[0387] Generate an appropriate reply.

[0388] The AI ​​model generates appropriate reply suggestions based on the prompt and sends them to the smartphone via the server. Staff can provide these reply suggestions to customers to respond quickly and appropriately.

[0389] In this manner, the present invention provides for efficient and effective communication with parents and clients.

[0390] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0391] Step 1:

[0392] A user inputs a customer inquiry into a smartphone terminal.

[0393] Input: Customer's inquiry (e.g. "Can you tell me more about this product?")

[0394] Output: The query is sent to the server.

[0395] Step 2:

[0396] The server converts the received query into a prompt.

[0397] Input: Customer inquiry

[0398] Output: Prompt statement (e.g. "Customer inquiry: Tell me more about this product. Generate an appropriate reply.")

[0399] Step 3:

[0400] The server inputs the prompt into a generative AI model to generate appropriate reply suggestions.

[0401] Input: Prompt statement

[0402] Output: Generated reply text (e.g. "This product is made of high-quality materials and is long-lasting.")

[0403] Step 4:

[0404] The server transmits the generated reply text proposal to the smartphone terminal.

[0405] Input: Generated reply suggestions

[0406] Output: A reply proposal is displayed on your smartphone.

[0407] Step 5:

[0408] The user checks the reply proposal displayed on the smartphone terminal and corrects it if necessary.

[0409] Input: Generated reply suggestions

[0410] Output: revised reply proposal (if necessary)

[0411] Step 6:

[0412] The user provides the revised reply proposal to the customer.

[0413] Input: revised reply proposal

[0414] Output: The reply provided to the customer

[0415] In this way, the user can respond quickly and appropriately to inquiries from customers.

[0416] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0417] "Example 1"

[0418] As one embodiment of the present invention, a system is provided in which AI is combined with an emotion engine that recognizes the user's emotions. This system manages a contact book for communicating with parents, and uses AI that has learned the speaking skills of veteran teachers to instantly grasp the needs of parents. Furthermore, the emotion engine analyzes the parent's emotional state and generates a reply proposal based on the results. Specifically, if the AI ​​senses that the parent is worried, it generates a reply proposal that gives a sense of security.

[0419] "Example 2"

[0420] The emotion engine also provides feedback to teachers. Specifically, it analyzes the emotional state of parents and reports the parents' emotional state and its changes to teachers based on the results. This allows teachers to better understand the parents' emotional state and communicate more appropriately.

[0421] "Example 3"

[0422] Furthermore, as another embodiment of the present invention, a system is provided in which an emotion engine analyzes the emotional state of a parent and provides feedback to a teacher based on the result. Specifically, if a parent feels angry, the AI ​​reports the information to the teacher, and the teacher can consider an appropriate response based on the information.

[0423] The process flow of each embodiment will be described below.

[0424] "Example 1"

[0425] Step 1: The AI ​​will manage a communication notebook to communicate with parents.

[0426] Step 2: The AI ​​learns the speaking techniques of veteran teachers and instantly understands the needs of parents.

[0427] Step 3: The emotion engine analyzes the parent's emotional state.

[0428] Step 4: The sentiment engine generates reply suggestions based on the analysis results.

[0429] "Example 2"

[0430] Step 1: The AI ​​will manage a communication notebook to communicate with parents.

[0431] Step 2: The AI ​​learns the speaking techniques of veteran teachers and instantly understands the needs of parents.

[0432] Step 3: The emotion engine analyzes the parent's emotional state.

[0433] Step 4: The emotion engine provides feedback to the teacher based on the analysis results.

[0434] "Example 3"

[0435] Step 1: The AI ​​will manage a communication notebook to communicate with parents.

[0436] Step 2: The AI ​​learns the speaking techniques of veteran teachers and instantly understands the needs of parents.

[0437] Step 3: The emotion engine analyzes the parent's emotional state.

[0438] Step 4: The emotion engine provides feedback to the teacher based on the analysis results.

[0439] Example 1

[0440] Next, a description will be given of Example 1 of the embodiment 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".

[0441] In the conventional communication book system, it was difficult to respond quickly and appropriately to messages from parents, which placed a heavy burden on teachers. In addition, it was not possible to accurately grasp the feelings and needs of parents, which led to a decline in the quality of communication. This made it difficult to gain the reassurance and trust of parents, and there was an issue of communication not being fully effective.

[0442] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0443] In this invention, the server includes a means for managing a contact book for communication with a guardian, a means for receiving the contents of the contact book sent from the guardian, a means for analyzing the emotional state of the guardian using an emotion engine based on the contents of the contact book, a means for generating a reply draft using a prompt sentence instructing to generate a reply draft based on the contents of the contact book and the emotional state of the guardian and a generative AI model, and a means for transmitting the generated reply draft to a teacher's terminal. This makes it possible to rapidly generate an appropriate reply draft according to the needs and emotions of the guardian, reduce the burden on the teacher, and maximize the communication effect.

[0444] "Guardian" refers to a parent or guardian who is responsible for a child's education and life.

[0445] A "communication notebook" is a communication tool that allows parents and teachers to share their children's status and important announcements.

[0446] "Means of management" refers to the systems and methods for storing, organizing, and making accessible the contents of the contact list.

[0447] "Veteran teachers" refer to teachers with many years of teaching experience and excellent communication skills.

[0448] "Speaking skills" refers to the use of words and expression techniques for effective communication.

[0449] "Artificial intelligence" refers to technology that mimics human intelligence through machine learning and data analysis.

[0450] "Needs" refers to the requests and expectations parents have, and the information and support they require.

[0451] "Means of instantaneous understanding" refers to techniques and methods for quickly understanding and responding to parents' needs.

[0452] "Response proposal" refers to a document that suggests an appropriate response to a message from a parent.

[0453] "Means for providing" refers to a system or method for presenting the generated reply proposal to the teacher.

[0454] "Means of receiving" refers to the technology or method by which the server receives the contents of the communication book sent by the parent.

[0455] "Natural language processing technology" refers to computer technology for analyzing and understanding human language.

[0456] "Means of analysis" refers to techniques and methods for analyzing the contents of the address book and extracting important information.

[0457] An "emotion engine" refers to technology for analyzing and recognizing emotions from text and voice.

[0458] "Emotional state" refers to the mental state and feelings felt by the parent.

[0459] "Means of sending" refers to the technology or method for sending the generated reply draft to the teacher's terminal.

[0460] "Terminals" refers to devices such as computers and smartphones used by teachers.

[0461] This invention is a system for managing a contact book for communicating with parents. This system uses artificial intelligence that has learned the speaking skills of veteran teachers to instantly grasp the needs of parents and generate appropriate reply proposals.

[0462] The server receives the contents of the address book sent by the parent from the device. The parent enters a message into the address book application using a smartphone or computer and sends it. The server receives this message and stores it in a database.

[0463] The server then analyzes the contacts received using natural language processing techniques, such as software like Google Cloud Natural Language API and IBM Watson® Natural Language Understanding, to extract important keywords and context from the message content.

[0464] Furthermore, the server uses an emotion engine to analyze the parent's emotional state based on the contents of the contact book. The emotion engine uses Microsoft® Azure® Emotion API or similar. This allows the server to recognize the parent's emotions, such as whether they are worried or relieved.

[0465] Based on the analysis results, the server uses a generative AI model (for example, OpenAI's GPT-4) to generate an appropriate reply proposal. A prompt sentence is input to the generative AI model to generate a reply proposal. For example, if a parent writes in the communication book, "My child seems to be in a bad mood at school recently. Is there something that worries you?", the following prompt sentence is used.

[0466] Sentiment Analysis Result: Worry A parent's note in the communication book: "My child has not been feeling well at school lately. Is there something that is worrying you?" Example prompt: Please generate a response to the message in the communication book from a parent: "My child seems to be in a bad mood at school recently. Is there something that worries you?" The parent's emotion is "worry," so please generate a response that gives a sense of security.

[0467] The generated reply draft is sent to the teacher's device. The teacher checks the reply draft on the device, makes any necessary corrections, and then records it in the communication book and sends a reply to the parent. For example, if the generated reply draft is "Thank you for your concern. We will carefully observe your child's condition and provide support as needed. Please contact us anytime if you have any concerns," the teacher will use this as a reference to record it in the communication book and send a reply to the parent.

[0468] This system makes it possible to quickly generate appropriate reply proposals that correspond to the needs and feelings of parents, reducing the burden on teachers and maximizing the effectiveness of communication.

[0469] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0470] Step 1:

[0471] Receiving communication from parents

[0472] The server receives the contents of the address book sent by the parent from the device. The parent enters a message into the address book application using a smartphone or computer and sends it. The server receives this message and stores it in a database.

[0473] Input: A message sent by the parent or guardian from their device

[0474] Output: Address book messages stored in the database

[0475] Specific operation: A parent types, "My child seems to be in a bad mood at school recently. Is there something that is bothering you?" and presses the send button. The server receives this message and stores it in a database.

[0476] Step 2:

[0477] Analysis of contact list contents

[0478] The server then analyzes the contents of the contacts received using natural language processing technology, using software such as Google Cloud Natural Language API and IBM Watson Natural Language Understanding, to extract important keywords and context from the message content.

[0479] Input: A contact message stored in the database

[0480] Output: Extracted keywords and context information

[0481] Specific operation: The server sends a message to the Google Cloud Natural Language API saying, "Your child seems to be in a bad mood at school recently. Is there something you're worried about?" The API analyzes the message and extracts keywords such as "child," "not in a good mood," and "worry."

[0482] Step 3:

[0483] Emotional state analysis

[0484] The server uses an emotion engine to analyze the parent's emotional state based on the results of analyzing the contents of the contact book. The emotion engine uses Microsoft Azure Emotion API, etc. This allows the server to recognize the parent's emotions, such as whether they are worried or relieved.

[0485] Input: A contact message stored in the database

[0486] Output: Parsed emotional state

[0487] How it works: The server sends the contents of the contact list to the Microsoft Azure Emotion API, which analyzes the message and recognizes the emotion "worry."

[0488] Step 4:

[0489] Generate reply suggestions

[0490] The server uses a generative AI model (e.g., OpenAI GPT-4) to generate appropriate reply sentence suggestions according to the parent's needs and emotional state. The generative AI model receives a prompt sentence as an input and generates a reply sentence suggestion.

[0491] Input: Extracted keywords, contextual information, analyzed emotional state

[0492] Output: The generated reply suggestions

[0493] Specific operation: The server should generate a reply to the prompt "The parent's message in the message book: 'My child seems to be in a bad mood at school recently. Is there something that worries you?'" The parent's emotion is "worry," so the server should generate a reply that gives a sense of security. " is sent to the generation AI model. The AI ​​model generates a reply suggestion that reads, "Thank you for your concern. We will closely monitor your child's condition and provide support as needed. If you have any concerns, please contact us at any time."

[0494] Step 5:

[0495] Sending and viewing reply suggestions

[0496] The server then sends the generated reply draft to the teacher's device, where the teacher checks the reply draft, makes corrections if necessary, records it in the communication book, and sends it back to the parent.

[0497] Input: Generated reply suggestions

[0498] Output: Response proposal displayed on teacher's device

[0499] Specific operation: The server sends the generated reply draft to the teacher's terminal. The teacher checks the draft on the terminal, which reads, "Thank you for your concern. We will closely monitor your child's condition and provide support as necessary. If you have any concerns, please contact us at any time." The teacher amends the draft as necessary, records it in the communication book, and sends it back to the parent.

[0500] The generative AI model may generate multiple reply drafts. In this case, the generated multiple reply drafts are sent to the teacher's terminal, an operation to select one of the generated multiple reply drafts is accepted from the teacher's terminal, the selected reply draft is recorded in the communication book, and returned to the guardian. Also, an operation to select one of the generated multiple reply drafts and an operation to edit the selected reply draft may be accepted from the teacher's terminal, the selected and edited reply draft is recorded in the communication book, and returned to the guardian.

[0501] (Application example 1)

[0502] Next, a description will be given of 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."

[0503] In conventional communication systems with parents, it was difficult to instantly grasp the needs and emotional state of parents and generate appropriate reply sentences. In addition, when dealing with customers in brick-and-mortar stores, it is necessary to properly analyze customers' questions and emotional state and respond quickly and appropriately, but there was a lack of effective means to achieve this. This resulted in a decline in the quality of communication and made it difficult to improve customer satisfaction.

[0504] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0505] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using AI that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the AI, a means for analyzing customer questions and generating appropriate answer proposals, a means for analyzing the emotional state of customers using an emotion engine, and a means for adjusting a response method based on the analysis results. This makes it possible to instantly grasp the needs and emotional state of parents and customers and take appropriate measures.

[0506] "Guardian" refers to the parent or guardian of a child attending an educational institution.

[0507] "Communication" refers to the act of exchanging information and emotions.

[0508] A "communication book" refers to a document or digital tool for exchanging information between parents and educational institutions.

[0509] A "veteran teacher" is a teacher who has many years of experience and possesses excellent teaching and speaking skills.

[0510] "Speaking" refers to the skill of conveying information effectively using words.

[0511] "AI" stands for artificial intelligence and refers to technology that mimics human intelligence.

[0512] "Needs" refers to a demand or request that is required in a particular situation or condition.

[0513] "Response suggestions" refer to suggestions for appropriate answers or messages to specific questions or situations.

[0514] "Customer" refers to a person who purchases goods or services.

[0515] A "question" is a question asked to seek information or knowledge.

[0516] "Suggested Answer" refers to a suggestion of an appropriate answer to a question.

[0517] An "emotion engine" refers to technology that analyzes emotions and takes appropriate action based on the results.

[0518] "Emotional state" refers to a person's emotional state at a particular moment.

[0519] "Analysis" refers to the act of examining and understanding data or information in detail.

[0520] "Response strategies" refer to the actions or steps to be taken in response to a particular situation or problem.

[0521] "Adaptation" refers to the act of making changes or modifications to suit a specific purpose.

[0522] The following system configuration will be described as an embodiment of the present invention.

[0523] System Configuration

[0524] The system is composed of three main elements: a server, a terminal, and a user. The server manages a contact book for communicating with parents, and instantly grasps the needs of parents using AI that has learned the speaking techniques of veteran teachers. It also has the function of analyzing customer questions and generating appropriate response proposals. Furthermore, it uses an emotion engine to analyze the emotional state of the customer and adjusts the response method based on the results.

[0525] Hardware and Software Used

[0526] Hardware: Smartphones, smart glasses

[0527] Software: Python, OpenAI API, EmotionRecognizer library

[0528] Data processing and calculation

[0529] Server Processing

[0530] The server receives input data from parents and customers and performs the following processes.

[0531] 1. Question analysis: The server analyzes the question entered by the user. Specifically, it uses the OpenAI API to analyze the question and generate appropriate answers.

[0532] 2. Emotion Analysis: The server uses the EmotionRecognizer library to analyze the user's emotional state, thereby understanding what emotional state the user is in.

[0533] 3. Adjusting the response: The server adjusts the appropriate response based on the results of the sentiment analysis. For example, if the user is feeling anxious, it generates a response that reassures the user.

[0534] Terminal handling

[0535] The terminal (smartphone or smart glasses) displays the analysis results and suggested answers sent from the server to the user, allowing the user to quickly check the appropriate response method.

[0536] User Actions

[0537] Users input questions through their terminals and check the suggested answers from the server, which facilitates smooth communication with parents and customers.

[0538] Examples

[0539] For example, if a customer in a physical store asks, "How do I use this product?", the server generates answer suggestions using the following prompt:

[0540] Examples of prompt statements

[0541] Customer Question: How do I use this product? Customer Sentiment: Interest Generate suitable answer suggestions.

[0542] Based on this prompt, the server uses the OpenAI API to generate appropriate response suggestions and uses the EmotionRecognizer library to analyze the customer's emotional state. Based on the analysis results, the server adjusts the optimal response method and sends it to the device. The device displays this information to the user, allowing the user to respond quickly and appropriately.

[0543] This makes it possible to instantly grasp the needs and emotional state of parents and customers and respond appropriately.

[0544] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0545] Step 1:

[0546] The user inputs a question using a device (smartphone or smart glasses).

[0547] Input: User question (e.g. "How do I use this product?")

[0548] Output: The question data is sent to the server.

[0549] Specific operation: The user inputs a question using the input interface of the terminal and presses the send button. The terminal then sends the question data to the server.

[0550] Step 2:

[0551] The server analyzes the received question data.

[0552] Input: Question data submitted by the user

[0553] Output: A prompt based on the question

[0554] Specific operation: The server receives the question data, analyzes the question using the OpenAI API, and generates a prompt based on the analysis result.

[0555] Step 3:

[0556] The server uses the prompt to generate appropriate responses.

[0557] Input: Prompt text (e.g. "Customer question: How do I use this product?")

[0558] Output: Suggested answer (e.g. "This product is very easy to use. First, turn it on, then...")

[0559] Specific operation: The server sends the generated prompt to the OpenAI API, which generates appropriate answer suggestions, which are then returned to the server.

[0560] Step 4:

[0561] The server uses an emotion engine to analyze the user's emotional state.

[0562] Input: User question data

[0563] Output: Emotional state (e.g. "interested")

[0564] Specific operation: The server uses the EmotionRecognizer library to analyze the emotional state from the user's question data. The analysis result is the emotional state.

[0565] Step 5:

[0566] The server adjusts its response based on the emotional state.

[0567] Input: proposed answer, emotional state

[0568] Output: Adjusted answer proposal

[0569] What it does: The server adjusts the response based on the generated answer and the user's emotional state. For example, if the user is feeling anxious, it adds reassuring expressions.

[0570] Step 6:

[0571] The server sends the adjusted answer proposal to the terminal.

[0572] Input: Adjusted answer proposal

[0573] Output: Proposed answers displayed on the terminal

[0574] Specific operation: The server sends the adjusted answer plan to the terminal, which displays the answer plan to the user.

[0575] Step 7:

[0576] The user checks the adjusted answer proposal through the terminal.

[0577] Input: Answer displayed on the device

[0578] Output: User understanding and action

[0579] Specific actions: The user checks the suggested answers displayed on the device screen and takes the necessary action, such as understanding how to use the product and actually using it.

[0580] Example 2

[0581] Next, a second embodiment of the second embodiment will be described. 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."

[0582] Traditionally, communication between teachers and parents required teachers to write individual replies, which was time-consuming and labor-intensive. In addition, it was difficult for teachers to accurately grasp the emotional state of parents, and they were sometimes unable to respond appropriately. This resulted in a decline in the quality of communication and in the inability to fully realize the effectiveness of education.

[0583] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0584] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using artificial intelligence that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the artificial intelligence, a means for receiving replies from parents and analyzing their emotions, and a means for feeding back the results of the emotion analysis to the teacher. This enables teachers to communicate with parents quickly and effectively, shortening their work hours and improving the quality of communication.

[0585] "Means to manage a communication notebook" refers to the function of managing digital or physical tools for exchanging information between teachers and parents.

[0586] "Artificial intelligence that has learned the speaking techniques of veteran teachers" is artificial intelligence that has the ability to learn the communication techniques and methods of expression of experienced teachers and generate sentences based on them.

[0587] "A means of instantly grasping the needs of parents" is a function that analyzes input and inquiries from parents and immediately understands their requests and expectations.

[0588] "Means for providing generated reply suggestions" is a function that presents reply suggestions generated by artificial intelligence to the teacher.

[0589] "Means for receiving responses from parents" refers to a function for receiving messages and feedback sent by parents.

[0590] "Means for performing emotion analysis" is a function for analyzing the content of a received message and determining the emotional state of the sender.

[0591] "Means of providing feedback on the results of emotion analysis to teachers" is a function that reports the results of emotion analysis to teachers and supports appropriate responses.

[0592] The present invention is a system for facilitating communication between teachers and parents, and is implemented as follows.

[0593] First, a user (teacher) uses a terminal (PC or tablet) to input a prompt for a reply to be sent to the parent. For example, the user might input, "Please generate a reply to report to the parent about the student's progress. The student has performed well on recent tests, but he tends to be late in submitting his homework."

[0594] The server receives the prompt sentence. The server uses a generative AI model (e.g., OpenAI's GPT-4) to generate reply sentence suggestions based on the received prompt sentence. The generative AI model has learned the speaking techniques of veteran teachers and generates reliable sentences.

[0595] The generated reply draft is sent from the server to the teacher's device. The teacher checks the draft and makes corrections as necessary. For example, the teacher may change "You achieved very good grades" to "You achieved excellent grades." The corrected reply is then sent from the teacher to the parent.

[0596] The server receives the replies from the parents. The server uses emotion analysis software (e.g., IBM Watson's Natural Language Understanding) to analyze the emotional state of the parents' replies. The analysis results are fed back to the teacher. For example, the teacher may be provided with information such as "the parents feel relieved."

[0597] This system will enable teachers to communicate with parents quickly and effectively, reducing work time and improving the quality of communication.

[0598] As a concrete example, consider a teacher reporting to parents on student progress. The teacher types the following prompt:

[0599] "Generate a response to parents about their student's progress. The student performed well on recent tests, but is often late in turning in his / her homework."

[0600] The server receives this prompt and uses a generative AI model to generate a response suggestion like this:

[0601] "Dear Parents,

[0602] Thank you for your support. I would like to inform you of my child's recent progress. He did very well on the recent test. However, I am concerned that he is often late in turning in his homework. I would appreciate it if you could help him turn in his homework more smoothly in the future.

[0603] We appreciate your continued support."

[0604] In this way, teachers can communicate with parents quickly and effectively, and the emotion engine can analyze the parents' responses and provide feedback to teachers, such as "the parents feel relieved," to help them take further appropriate action.

[0605] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0606] Step 1:

[0607] A user (teacher) uses a terminal (PC or tablet) to input a prompt for a reply message to be sent to the parent. The input prompt is sent to the server. For example, the user might input, "Please generate a reply message to report to the parent about the student's progress. The student has performed well on recent tests, but he tends to be late in turning in his homework."

[0608] Step 2:

[0609] The server receives the prompt sent by the user. The received prompt is passed to the generative AI model. The server analyzes the prompt and processes the data to generate an appropriate reply.

[0610] Step 3:

[0611] The server uses a generative AI model (e.g., OpenAI's GPT-4) to generate reply sentence suggestions based on the received prompt sentence. The generative AI model has learned the speaking techniques of veteran teachers and generates reliable sentences. The generated reply sentence suggestions are temporarily stored in the server.

[0612] Step 4:

[0613] The server transmits the generated reply draft to the teacher's terminal. The transmitted reply draft is displayed on the teacher's terminal. The teacher can check the draft.

[0614] Step 5:

[0615] The user (teacher) checks the reply draft on the terminal and makes corrections as necessary. For example, "You achieved very good grades" is changed to "You achieved excellent grades." The corrected sentence is sent from the terminal to the server.

[0616] Step 6:

[0617] The server receives the corrected reply text sent by the teacher and sends it to the parent / guardian. The parent / guardian can receive the reply text from the teacher.

[0618] Step 7:

[0619] The server receives the reply from the guardian. The received reply is subjected to emotion analysis. The server processes the data to analyze the reply from the guardian.

[0620] Step 8:

[0621] The server uses emotion analysis software (e.g., IBM Watson's Natural Language Understanding) to analyze the emotional state of the parent's reply. The analysis results are temporarily stored on the server.

[0622] Step 9:

[0623] The server feeds back the results of the emotion analysis to the teacher. The fed back information is displayed on the teacher's terminal. For example, information such as "the parent feels relieved" is provided to the teacher. This allows the teacher to understand the parent's emotional state and take appropriate action.

[0624] (Application example 2)

[0625] Next, a description will be given of 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 will be referred to as a "terminal."

[0626] In the conventional system, teachers had to spend a lot of time communicating with parents, which led to a decrease in work efficiency. In addition, in brick-and-mortar stores, it was difficult to respond appropriately to customer inquiries or understand the emotional state of customers, making it difficult to improve customer satisfaction.

[0627] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0628] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using AI that has learned the speaking skills of veteran teachers, a means for providing reply suggestions generated by the AI, a means for generating optimal reply suggestions for inquiries from customers, and a means for analyzing the emotional state of customers and providing feedback to store clerks. This makes it possible to reduce the work hours of teachers and maximize the effectiveness of communication with parents. Also, in physical stores, it is possible to provide appropriate replies to inquiries from customers and grasp the emotional state of customers, thereby improving customer satisfaction.

[0629] A "means for managing a communication notebook" is a function that allows for organizing and storing information for communicating with parents and for accessing it as needed.

[0630] "AI that has learned the speaking techniques of veteran teachers" is an artificial intelligence that learns the communication techniques and speaking styles of experienced teachers and uses that knowledge to respond appropriately to parents and customers.

[0631] "A means of instantly grasping the needs of parents" is a function that enables prompt understanding of inquiries and requests from parents and provides appropriate responses.

[0632] "Means of providing generated reply suggestions" refers to a function that presents reply suggestions generated by AI to users, facilitating communication.

[0633] "A means of generating optimal reply suggestions for customer inquiries" refers to a function in which AI generates and provides optimal reply sentences based on the content of a customer's inquiry.

[0634] "A means of analyzing the customer's emotional state and providing feedback to store associates" is a function that analyzes the customer's emotional state from their words and actions, and conveys the results to store associates, enabling them to respond more appropriately.

[0635] The system for implementing the present invention is composed of three main components: a server, a terminal, and a user. The following describes how each component functions.

[0636] server

[0637] The server includes the following means:

[0638] 1. A means to manage communication notebooks: This function organizes and stores information for communicating with parents and allows them to access it as needed. This allows teachers to efficiently manage communication with parents.

[0639] 2. AI that learned the speaking skills of veteran teachers: This is an AI that learns the communication techniques and speaking styles of experienced teachers and uses them to respond appropriately to parents and customers. This AI is implemented using the OpenAI API.

[0640] 3. A means to instantly understand the needs of parents: This function allows teachers to quickly understand inquiries and requests from parents and respond appropriately. This allows teachers to instantly understand the needs of parents.

[0641] 4. A means of providing generated reply suggestions: This function presents reply suggestions generated by AI to users, facilitating smooth communication.

[0642] 5. A means of generating optimal reply suggestions for customer inquiries: This function enables AI to generate and provide optimal reply sentences based on the content of customer inquiries.

[0643] 6. A means of analyzing the customer's emotional state and providing feedback to store clerks: This function analyzes the customer's emotional state from their words and actions, and conveys the results to store clerks, enabling them to respond more appropriately. The TextBlob library is used for this emotion analysis.

[0644] Terminal

[0645] The terminals are devices such as smartphones and tablets used by teachers and store clerks. Applications that display information provided by the server and allow users to operate the terminals are installed on these terminals.

[0646] User

[0647] The users are teachers or store clerks, and communicate with parents and customers based on the information provided by the server. The users access the server through their terminals to obtain the necessary information.

[0648] Examples

[0649] For example, if a parent asks, "Please tell me how to return an item," the server generates a reply using the following prompt:

[0650] Customer Question: What about returning products?

[0651] Generate the best response text.

[0652] The server sends this prompt to the OpenAI API and provides the generated reply text to the terminal. At the same time, it uses TextBlob to analyze the customer's emotional state and feeds the results back to the store clerk, allowing the store clerk to understand the customer's emotional state and take more appropriate action.

[0653] This system will enable teachers and store clerks to reduce their work hours and maximize the effectiveness of their communication.

[0654] The flow of the identification process in the application example 2 will be described with reference to FIG.

[0655] Step 1:

[0656] The server receives an inquiry from a parent or customer. The input is the inquiry content, and the output is to generate the inquiry content as a prompt sentence. Specifically, the server receives the inquiry content in text format and converts it into a prompt sentence.

[0657] Step 2:

[0658] The server sends the generated prompt text to the OpenAI API. The input is the prompt text, and the output is the reply text proposal generated by the AI. Specifically, the prompt text is sent as an API request, and the reply text proposal is received.

[0659] Step 3:

[0660] The server sends the received reply text suggestions to the terminal. The input is the reply text suggestions generated by the AI, and the output is the reply text suggestions displayed on the terminal. Specifically, the reply text suggestions are sent to the terminal so that the user can view them.

[0661] Step 4:

[0662] The server sends the query to the TextBlob library to analyze the emotional state of the parent or customer. The input is the query, and the output is the emotion analysis result. Specifically, the query is passed to TextBlob and the emotion score is obtained.

[0663] Step 5:

[0664] The server generates feedback based on the emotion analysis result and sends it to the terminal. The input is the emotion analysis result, and the output is a feedback message. Specifically, the server analyzes the emotion analysis result, generates an appropriate feedback message, and sends it to the terminal.

[0665] Step 6:

[0666] The terminal displays the reply draft and the feedback message received from the server to the user. The input is the reply draft and the feedback message, and the output is a screen display that can be viewed by the user. Specifically, the reply draft and the feedback message are displayed on the screen so that the user can confirm them.

[0667] Step 7:

[0668] The user checks the reply draft displayed on the terminal and makes corrections as necessary. The input is the reply draft, and the output is the corrected reply. Specifically, the user checks the reply draft and makes corrections as necessary.

[0669] Step 8:

[0670] The user sends the revised reply to the parent or customer. The input is the revised reply, and the output is the final reply sent to the parent or customer. Specifically, the revised reply is sent by pressing the send button.

[0671] Example 3

[0672] Next, a third embodiment of the third embodiment will be described. 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."

[0673] In the past, teachers had to spend a lot of time and effort writing replies to parents, and it was difficult for them to properly understand the emotional state of the parents. In addition, there was a lack of means to respond quickly and appropriately to the needs of parents, so there was a need for more efficient communication and more effective responses.

[0674] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0675] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using artificial intelligence that has learned the speaking skills of veteran teachers, a means for providing reply suggestions generated by the artificial intelligence, a means for analyzing the content of inquiries from parents and generating appropriate reply sentences, and a means for analyzing the emotional state of parents and providing feedback to teachers based on the results. This enables teachers to respond to inquiries from parents quickly and accurately, and realizes efficient communication and effective responses.

[0676] "Means for managing the communication book" refers to a system or software for recording and organizing communication between parents and teachers.

[0677] "Artificial intelligence that has learned the speaking techniques of veteran teachers" refers to an AI model that uses natural language processing technology to learn teachers' communication styles based on the reply sentences and feedback used in the past by experienced teachers.

[0678] "Means of instantly grasping parents' needs" refers to artificial intelligence technology that analyzes inquiries and requests from parents and quickly understands their content.

[0679] "Means for providing generated reply suggestions" refers to a system or interface for presenting reply suggestions generated by artificial intelligence to teachers.

[0680] "Means of analyzing the content of inquiries from parents and generating an appropriate reply message" refers to artificial intelligence technology for analyzing messages from parents and generating optimal reply messages based on their content.

[0681] "Means of analyzing the emotional state of parents and providing feedback to teachers based on the results" refers to an emotion analysis engine and feedback system for analyzing emotions from parents' messages and reporting the results to teachers.

[0682] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0683] The present invention provides a system for improving the efficiency of communication with parents and reducing the burden on teachers. A specific embodiment of this system will be described below.

[0684] Collecting and preprocessing training data

[0685] The server collects reply sentences used by teachers in the past and feedback from teachers. For this purpose, data sources such as the school's email system and chat logs are used. The collected data is converted into a data frame using Python's pandas library, and preprocessing is performed, such as filling in missing values ​​and deleting unnecessary data.

[0686] Building and training generative AI models

[0687] The server uses the preprocessed data to build a generative AI model. Specifically, it uses TENSORFLOW (registered trademark) and PyTorch to design a neural network model and trains it on the teacher's reply sentences and feedback. A server equipped with a GPU is used to train the model, and training is carried out efficiently through batch processing.

[0688] Receiving inquiries from parents

[0689] The terminal receives inquiries and requests from parents. For example, when a parent sends an inquiry through the school's web portal or email, the content of the inquiry is received by the terminal. The terminal then sends the received inquiry to the server.

[0690] Analyzing inquiries and generating replies

[0691] The server inputs the received inquiry content into the generative AI model and generates an appropriate reply text. Specifically, the inquiry content is tokenized and input into the model. The model generates the optimal reply based on past learning data and sends the result to the terminal.

[0692] Emotion analysis using emotion engine

[0693] The server inputs messages from parents into an emotion engine to analyze their emotional state. Specifically, it uses IBM Watson's Natural Language Understanding and Microsoft Azure's Text Analytics to analyze the tone and keywords of the messages. The analysis results indicate the parent's emotional state, such as whether they are angry.

[0694] Providing feedback to teachers

[0695] The user (teacher) receives the reply text and the emotion analysis results provided by the server. The teacher can use this information to consider an appropriate response to the parent. For example, if the parent is angry, the teacher will try to respond calmly and politely.

[0696] Examples and prompts

[0697] Examples

[0698] The user (teacher) receives an inquiry from a parent saying, "Please tell me why my child's grades are dropping." The device sends this inquiry to the server. The server uses a generative AI model to generate a reply saying, "We apologize for causing you concern about your child's grades. We are considering individual measures based on recent test results and class behavior, and will discuss this in detail at the next interview." and sends it to the device. The user sends this reply to the parent.

[0699] At the same time, the server uses an emotion engine to analyze the parent's emotional state. The analysis result is that the parent is "worried." Based on this emotion analysis result, the user can respond more considerately.

[0700] Examples of prompt statements

[0701] "Generate an appropriate response based on the teacher's previous responses and feedback in response to a parent's inquiry such as 'Can you tell me why my child's grades are dropping?'"

[0702] In this way, the system reduces the burden on the teacher and realizes efficient communication. The flow of the specific process in the third embodiment will be described with reference to FIG.

[0703] Step 1:

[0704] The server collects reply sentences used by teachers in the past and feedback from teachers. For this purpose, data sources such as the school's email system and chat logs are used. The collected data is converted into a data frame using Python's pandas library, and preprocessing is performed, such as filling in missing values ​​and deleting unnecessary data. The input is the teacher's reply sentences and feedback, and the output is the preprocessed text data.

[0705] Step 2:

[0706] The server uses the preprocessed data to build a generative AI model. Specifically, it uses TensorFlow and PyTorch to design a neural network model and trains it on the teacher's reply sentences and feedback. A server equipped with a GPU is used to train the model, and training proceeds efficiently through batch processing. The input is the preprocessed text data, and the output is a trained generative AI model.

[0707] Step 3:

[0708] The terminal receives inquiries and requests from parents. For example, when a parent sends an inquiry through the school's web portal or email, the content of the inquiry is received by the terminal. The terminal sends the received inquiry to the server. The input is the inquiry content from the parent, and the output is the transmission of the inquiry data to the server.

[0709] Step 4:

[0710] The server inputs the received inquiry into the generative AI model and generates an appropriate reply. Specifically, the inquiry is tokenized and input into the model. The model generates an optimal reply based on past learning data and sends the result to the device. The input is the inquiry from the parent, and the output is the generated reply.

[0711] Step 5:

[0712] The server inputs messages from parents into an emotion engine to analyze their emotional state. Specifically, it uses IBM Watson's Natural Language Understanding and Microsoft Azure's Text Analytics to analyze the tone and keywords of the messages. The analysis results indicate the parent's emotional state, such as whether they are angry. The input is the message from the parent, and the output is the emotion analysis results.

[0713] Step 6:

[0714] The user (teacher) receives the reply text and emotion analysis results provided by the server. The teacher can consider an appropriate response to the parent based on this information. For example, if the parent is angry, the teacher will try to reply calmly and politely. The input is the reply text from the server and the emotion analysis results, and the output is an appropriate response to the parent.

[0715] (Application example 3)

[0716] Next, a description will be given of 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 will be referred to as a "terminal."

[0717] In the past, communication with parents required a lot of time and effort for teachers to respond individually, and it was difficult to respond quickly and appropriately. It was also difficult to properly grasp the emotional state of parents and respond accordingly. This made it difficult to gain the parents' peace of mind and trust, and reduced the effectiveness of communication.

[0718] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0719] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using AI that has learned the speaking skills of veteran teachers, a means for providing reply text suggestions generated by the AI, a means for analyzing the emotional state of parents using an emotion engine and providing feedback to teachers, a means for using the past response history and feedback of operators as learning data, and a means for providing the generated reply text and emotion analysis results to operators. This makes it possible to quickly and appropriately respond to the needs of parents and increase the sense of security and trust of parents.

[0720] A "means for managing the communication notebook" is a system that centrally manages information for communicating with parents and allows quick access to necessary information.

[0721] "AI that has learned the speaking techniques of veteran teachers" is an artificial intelligence that uses the response sentences and feedback used in the past by experienced teachers as learning data to generate appropriate response sentences in response to inquiries and requests from parents.

[0722] "Means of instantly grasping the needs of parents" refers to technology that analyzes inquiries and requests from parents and quickly understands their content.

[0723] "Means for providing generated reply suggestions" refers to a system that presents reply suggestions generated by AI to teachers or operators.

[0724] The "emotion engine" is a technology that analyzes the parent's emotional state and provides feedback based on the results.

[0725] "Means for analyzing the emotional state of parents and providing feedback to teachers" refers to a system that uses an emotion engine to analyze the emotions of parents and communicates the results to teachers.

[0726] "Method of using past operator response history and feedback as learning data" refers to technology that collects past response history and feedback as data and allows AI to learn based on that.

[0727] "Means of providing the generated reply text and emotion analysis results to the operator" refers to a system that presents the reply text generated by the AI ​​and the results of the emotion engine's analysis to the operator.

[0728] A system for carrying out this invention has the following configuration: The server includes means for managing a contact book for communicating with parents, means for instantly grasping the needs of parents using AI that has learned the speaking techniques of veteran teachers, means for providing reply sentence suggestions generated by the AI, means for analyzing the emotional state of parents using an emotion engine and providing feedback to teachers, means for using past response history and feedback from operators as learning data, and means for providing the generated reply sentences and emotion analysis results to the operator.

[0729] Hardware and Software Used

[0730] Hardware: Smartphones, servers

[0731] Software: OpenAI API, TextBlob

[0732] Data processing and calculation

[0733] 1. Ways to manage your contacts:

[0734] The server centrally manages the contact book for communicating with parents, allowing them to quickly access the necessary information.

[0735] 2. AI that learned the speaking techniques of veteran teachers:

[0736] The server uses the reply sentences and feedback used by veteran teachers in the past as learning data to generate appropriate reply sentences in response to inquiries and requests from parents. It utilizes generative AI models using the OpenAI API.

[0737] 3. How to instantly understand parents' needs:

[0738] The server analyzes inquiries and requests from parents and quickly understands their content, making it possible to instantly grasp the needs of parents.

[0739] 4. Means for providing generated reply suggestions:

[0740] The server then presents the reply text generated by the AI ​​to teachers and operators, enabling them to respond quickly and appropriately.

[0741] 5. Emotion Engine:

[0742] The server analyzes the parent's emotional state and provides feedback based on the results. TextBlob is used for emotion analysis.

[0743] 6. Means of analyzing parents' emotional state and providing feedback to teachers:

[0744] The server uses an emotion engine to analyze the parents' emotions and communicates the results to teachers, who can then consider appropriate responses.

[0745] 7. Using past operator responses and feedback as learning data:

[0746] The server collects past response history and feedback as data, and the AI ​​learns from that data, allowing it to generate more appropriate reply text.

[0747] 8. Means of providing generated reply text and sentiment analysis results to the operator:

[0748] The server presents the reply text generated by the AI ​​and the results of the emotion engine's analysis to the operator, enabling the operator to respond quickly and appropriately.

[0749] Examples

[0750] For example, if a parent asks, "The security alarm keeps ringing. What should I do?" the server processes the inquiry as follows:

[0751] 1. The server uses the OpenAI API to generate an appropriate reply based on the operator's past response history and feedback.

[0752] 2. The generated reply text is, "If the alarm continues to ring, first check the power supply. If the power supply is normal, check the sensor position."

[0753] 3. The server uses TextBlob to perform emotion analysis of the parent's inquiry and quantifies the parent's emotional state.

[0754] 4. The generated reply text and sentiment analysis results are provided to the operator.

[0755] Examples of prompt statements

[0756] Please generate appropriate responses to the following queries:

[0757] Q: My security alarm keeps going off, what should I do?

[0758] Previous reply: If the alarm keeps ringing, please check the power supply first. If the power supply is OK, please check the sensor position.

[0759] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0760] Step 1:

[0761] The server receives inquiries from parents.

[0762] Input: Parental inquiry (e.g. "The security alarm keeps going off. What should I do?")

[0763] Output: Text data of inquiry content

[0764] Step 2:

[0765] The server retrieves the operator's past response history and feedback from a database.

[0766] Input: A query to the database

[0767] Output: A dataset of historical interactions and feedback

[0768] Step 3:

[0769] The server uses the OpenAI API to generate an appropriate response to the parent's inquiry based on the past response history and feedback it has obtained.

[0770] Input: Text data of inquiry contents, past response history and feedback data set

[0771] Output: Generated reply text (e.g. "If the alarm keeps ringing, first check the power supply. If the power supply is normal, check the sensor position.")

[0772] Step 4:

[0773] The server uses TextBlob to perform sentiment analysis of the parent's inquiry.

[0774] Input: Text data of inquiry

[0775] Output: Sentiment analysis results (e.g. optimism, subjectivity)

[0776] Step 5:

[0777] The server provides the generated reply text and the sentiment analysis results to the operator.

[0778] Input: Generated reply text, sentiment analysis results

[0779] Output: Reply text and sentiment analysis results displayed on the operator's terminal

[0780] Step 6:

[0781] The operator takes appropriate action toward the parent based on the reply text and emotion analysis results provided by the server.

[0782] Input: Reply text and sentiment analysis results provided by the server

[0783] Output: Response and response to parents

[0784] Step 7:

[0785] The operator's response history and feedback are stored again in the database and used as learning data for the next call.

[0786] Input: Operator response history and feedback

[0787] Output: Response history and feedback data stored in a database

[0788] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0789] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generative AIs. Data generation model 58 is

[0790] , obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0791] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0792] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0793] [Second embodiment]

[0794] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0795] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0796] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0797] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0798] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0799] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0800] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0801] Fig. 4 shows an example of main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0802] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0803] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0804] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0805] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0806] "Example 1"

[0807] The present invention is a system for managing a notebook for communicating with parents. This system uses AI that has learned the speaking techniques of veteran teachers to instantly grasp the needs of parents. Specifically, the AI ​​analyzes the contents of the notebook from parents and generates an appropriate reply proposal for that content. The generated reply proposal is designed to increase the parents' sense of security and trust, and teachers use it as a reference when replying to parents.

[0808] "Example 2"

[0809] As one aspect of the present invention, reply suggestions generated by AI shorten the work hours of teachers while maximizing the effectiveness of communication. Specifically, by using reply suggestions generated by AI, teachers can significantly reduce the time it takes to compose reply sentences. In addition, since the reply suggestions generated by AI have learned the speaking techniques of veteran teachers, their contents increase the teacher's trust in parents. This facilitates smooth communication between teachers and parents, improving the quality of education.

[0810] "Example 3"

[0811] As one aspect of the present invention, the AI ​​learns the speaking techniques of veteran teachers by using reply sentences used by teachers in the past and feedback from teachers as learning data. Specifically, the AI ​​uses this learning data to generate appropriate reply sentences for various inquiries and requests from parents. This allows teachers to instantly obtain reply sentences to meet the various needs of parents, realizing efficient communication.

[0812] The process flow of each embodiment will be described below.

[0813] "Example 1"

[0814] Step 1: The system receives the contents of the communication book from parents.

[0815] Step 2: The AI ​​analyzes the received content. For this analysis, an AI that has learned the speaking techniques of veteran teachers is used.

[0816] Step 3: The AI ​​instantly identifies the parent's needs and generates appropriate response suggestions.

[0817] Step 4: The generated reply proposal is provided to the teacher, who can use it to respond to the parent.

[0818] "Example 2"

[0819] Step 1: The teacher reviews the reply suggestions generated by the AI.

[0820] Step 2: Teachers can significantly reduce the time it takes to write responses.

[0821] Step 3: Communication between teachers and parents is smooth, improving the quality of education.

[0822] "Example 3"

[0823] Step 1: The AI ​​uses the reply sentences used by teachers in the past and feedback from teachers as learning data.

[0824] Step 2: Based on this learning data, the AI ​​generates appropriate reply sentences for various inquiries and requests from parents.

[0825] Step 3: Teachers can instantly receive response text to address various needs from parents, achieving efficient communication.

[0826] Example 1

[0827] Next, a description will be given of 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 glasses 214 will be referred to as a "terminal".

[0828] In the conventional communication book management system, teachers had to manually create replies to each communication with parents, which was time-consuming and labor-intensive. It was also sometimes difficult to properly understand the needs and feelings of parents and write replies that would increase their reassurance and trust. This resulted in issues such as a decrease in the effectiveness of communication and an increase in the workload of teachers.

[0829] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0830] In this invention, the server includes a means for managing a communication notebook for communicating with parents, a means for instantly grasping the needs of parents using artificial intelligence that has learned the speaking skills of veteran teachers, a means for providing reply suggestions generated by the artificial intelligence, a means for receiving the contents of the communication notebook from parents, a means for analyzing the received communication notebook contents using natural language processing technology, a means for generating appropriate reply suggestions based on the analysis results, a means for presenting the generated reply suggestions to the teacher's terminal, and a means for the teacher to create a final reply and send it to the parent's terminal. This makes it possible to appropriately grasp the needs and feelings of parents and to reply quickly and effectively.

[0831] "Guardian" refers to the parent or guardian of a child attending an educational institution, who is responsible for communicating and advising on the child's education and life.

[0832] A "communication notebook" is a means for parents and teachers to exchange information about their children's education and daily life, and is provided in either paper or digital form.

[0833] "Means of management" refers to a system or software that has the functionality to store, organize, search, and display the contents of the address book.

[0834] "Artificial intelligence" refers to computer programs and systems that use technologies such as machine learning and natural language processing to mimic human intelligence and perform certain tasks automatically.

[0835] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language, and is used to analyze and generate text data.

[0836] "Reply proposal" refers to a draft message generated by artificial intelligence to suggest an appropriate reply to a message from a parent.

[0837] "Teachers" refers to teachers and instructors who are responsible for educating children at educational institutions and who have the role of communicating with and consulting with parents.

[0838] A "terminal" is a device that a user uses to access and operate the system, and includes smartphones, tablets, PCs, etc.

[0839] "Means of analysis" refers to systems or software that have the function of analyzing the received communication book contents using natural language processing technology and extracting the needs and feelings of parents.

[0840] "Means for generating" refers to a system or software that has the functionality for generating appropriate reply suggestions based on the analysis results.

[0841] "Means of presentation" refers to a system or software that has the function of displaying the generated reply draft on the teacher's terminal so that the teacher can check and correct it.

[0842] "Means of sending" refers to a system or software that has the function of sending the final reply prepared by the teacher to the parent's device.

[0843] This invention is a system for managing a contact book for communicating with parents, and uses artificial intelligence that has learned the speaking skills of veteran teachers to instantly grasp the needs of parents and generate appropriate reply proposals. This system is implemented using the following hardware and software.

[0844] Hardware and Software Used

[0845] Server: Receives and analyzes the contents of the address book, and generates and sends reply proposals.

[0846] Devices: Devices used by parents and teachers (smartphones, tablets, computers, etc.).

[0847] Generative AI model: Analyzes the contents of the contact list using natural language processing technology and generates reply suggestions. Specifically, Google's BERT and OpenAI's GPT-4 are used.

[0848] Data processing and calculation

[0849] 1. Receiving communication from parents:

[0850] The server receives the contents of the address book sent by the parent from the device. The contents of the address book are stored in the server in text format.

[0851] 2. Analysis of address book contents:

[0852] The server then uses natural language processing technology to analyze the contents of the contact book received. A generative AI model is used for this analysis. The generative AI model analyzes the text data and extracts the needs and emotions of the parents.

[0853] 3. Generate reply suggestions:

[0854] The server generates appropriate reply suggestions based on the analysis results. The generative AI model generates responses that correspond to the needs and feelings of the parent.

[0855] 4. Response suggestions:

[0856] The server sends the generated reply draft to the teacher's terminal, where the teacher can check the reply draft and make corrections if necessary.

[0857] 5. Instructor creates final response:

[0858] The teacher uses the generated reply draft as a reference to create a final reply to the parent / guardian. The final reply is sent from the teacher's terminal to the parent / guardian's terminal via the server.

[0859] Examples

[0860] For example, if a parent writes in the communication book, "I'm worried that my child's grades at school have been dropping recently," the server receives this content and inputs the following prompt sentence into the generative AI model:

[0861] Example prompt:

[0862] "A parent writes: 'I'm worried that my child's grades at school have been dropping recently. Please generate an appropriate response to this.'"

[0863] Based on this prompt, the generative AI model generates the following reply suggestions:

[0864] "We understand that you are concerned about your child's grades. Please rest assured that we are prepared to monitor your child's progress and provide any support they may need, including individualized tutoring and additional learning resources."

[0865] Teachers will use these reply suggestions to create and send a final reply to parents.

[0866] The above is an embodiment of the present invention.

[0867] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0868] Step 1:

[0869] Receiving communication from parents

[0870] The server receives the contents of the address book sent by the guardian from the device. The input is a text message sent by the guardian using the device. The server stores this text message in a database. In concrete terms, when the guardian logs into the address book app on the device, enters a message and presses the send button, the server receives the message and stores it in the database.

[0871] Step 2:

[0872] Analysis of contact list contents

[0873] The server analyzes the received address book contents using natural language processing technology. The input is the text message saved in step 1. The server inputs this text data into a generative AI model to extract the guardian's needs and emotions. In concrete terms, the server inputs the text data into a generative AI model (e.g., GPT-4), and the model analyzes the text to extract the guardian's needs and emotions.

[0874] Step 3:

[0875] Generate reply suggestions

[0876] The server generates an appropriate reply draft based on the analysis results. The input is the needs and feelings of the parent extracted in step 2. The server inputs a prompt text to the generative AI model and generates a reply draft. In concrete terms, the server inputs the prompt text "Contents from the parent's message book: My child's grades at school have been dropping recently, and I'm worried. Please generate an appropriate reply draft in response to this" to the generative AI model, and the model generates an appropriate reply draft.

[0877] Step 4:

[0878] Response suggestions

[0879] The server sends the generated reply draft to the teacher's terminal. The input is the reply draft generated in step 3. The server sends this reply draft to the teacher's terminal so that the teacher can check it. In concrete terms, the server sends the generated reply draft to the teacher's terminal, and the teacher checks the reply draft on the terminal.

[0880] Step 5:

[0881] Instructor creates final reply

[0882] The teacher uses the generated reply draft as a reference to create a final reply to the parent. The input is the reply draft presented in step 4. The teacher checks the reply draft on the terminal, corrects it if necessary, and creates a final reply. In concrete terms, the teacher checks the reply draft on the terminal, corrects it if necessary, creates a final reply, and presses the send button.

[0883] Step 6:

[0884] Sending a final reply

[0885] The server sends the final reply created by the teacher to the parent's terminal. The input is the final reply created by the teacher in step 5. The server sends this final reply to the parent's terminal. In concrete terms, the server sends the final reply created by the teacher to the parent's terminal, and the parent checks the final reply on the terminal.

[0886] (Application example 1)

[0887] Next, a description will be given of 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 glasses 214 will be referred to as a "terminal".

[0888] With the conventional contact book management system, communication with parents was not smooth, and it was difficult to quickly grasp the needs of parents. In addition, it was difficult for store staff to respond appropriately and quickly to inquiries from customers, making it an issue to improve customer satisfaction. This has led to a demand for more efficient work hours and maximizing communication effectiveness.

[0889] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0890] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using a generative AI model that has learned the speaking skills of veteran teachers, a means for providing reply suggestions generated by the generative AI model, a means for analyzing the content of inquiries from customers and generating appropriate reply suggestions, and a means for displaying the generated reply suggestions to store staff. This makes it possible to quickly grasp the needs of parents and customers and provide appropriate replies. This allows for the shortening of work hours and the maximization of communication effectiveness.

[0891] "Parent" refers to the parent or guardian of a child attending an educational institution.

[0892] "Communication" refers to the act of transmitting information and emotions.

[0893] A "communication book" refers to a document or digital tool for exchanging information between parents and educational institutions.

[0894] "Means of management" refers to how information is organized, stored, and updated using systems and tools.

[0895] A "veteran teacher" refers to an educator with many years of experience and a high level of specialized knowledge.

[0896] "Speaking" refers to the skill of conveying information effectively using words.

[0897] A "generative AI model" refers to an algorithm that uses artificial intelligence techniques to generate an output for a specific task.

[0898] "Parent needs" refers to the demands and expectations that parents have.

[0899] "Means of instantaneous understanding" refers to a method for understanding information in a short amount of time and taking appropriate action.

[0900] "Response Draft" means a draft response to a particular inquiry or message.

[0901] "Means of providing" refers to the method of presenting the generated information to the user.

[0902] "Customer" refers to a person who purchases goods or services.

[0903] "Inquiry content" refers to information submitted by a customer or guardian as a question or request.

[0904] "Means of analysis" refers to a method for analyzing input information and understanding its meaning.

[0905] "Store staff" refers to employees working in physical stores.

[0906] "Means of display" refers to the way in which information is visually presented to the user.

[0907] The system for carrying out this invention is configured as follows: First, the server has a means for managing a contact book for communication with parents. This means provides a function for storing the contents of contact from parents in a digital format and updating them as necessary.

[0908] Next, the server uses a generative AI model that has learned the speaking skills of veteran teachers to instantly grasp the needs of parents. This generative AI model analyzes the content of messages from parents and generates appropriate reply proposals based on the content. This analysis and generation process uses artificial intelligence technologies such as OpenAI's API.

[0909] The server further includes a means for providing the generated reply draft, which is capable of presenting the generated reply draft to a staff member of the educational institution so that the staff member can use the reply draft to the parent / guardian as a reference.

[0910] The server also has a means for analyzing the content of customer inquiries and generating appropriate reply suggestions. This means is used to support customer service in physical stores. It receives the content of customer inquiries as input, analyzes them using a generative AI model, and generates appropriate reply suggestions.

[0911] Finally, the server has a means for displaying the generated reply proposal to the store staff. This means displays the generated reply proposal on a terminal such as a smartphone or tablet, enabling the store staff to respond to the customer by referring to it.

[0912] As a concrete example, if a customer inquires, "Please tell me how to return an item," the server inputs the inquiry into the generative AI model and generates an appropriate reply proposal. The generated reply proposal is, "We will guide you through how to return the item. First, please prepare your purchase receipt. Then, bring it to the store together with the item, and a staff member will assist you." This reply proposal is displayed on the terminal of the store staff, who use it as a reference when responding to the customer.

[0913] The following is an example of a prompt sentence:

[0914] Customer Question: How do I return an item?

[0915] Please reply like a veteran staff member.

[0916] In this way, it becomes possible to quickly grasp the needs of parents and customers and provide appropriate responses, thereby reducing work time and maximizing communication effectiveness.

[0917] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0918] Step 1:

[0919] The user (parent or customer) enters the inquiry.

[0920] Input: Enquiry content (text format)

[0921] Specific operation: A user uses a smartphone or tablet application to input the content of an inquiry. For example, the user inputs, "Please tell me how to return a product."

[0922] Step 2:

[0923] The server receives the query and generates a prompt to input to the generative AI model.

[0924] Input: Enquiry content (text format)

[0925] Output: Prompt statement (text format)

[0926] Specific operation: The server receives the inquiry and converts it into a prompt sentence in a format suitable for the generative AI model. For example, it generates a prompt sentence such as "Customer inquiry: How do I return the product? Please reply like a veteran staff member."

[0927] Step 3:

[0928] The server uses a generative AI model to generate reply suggestions based on the prompt.

[0929] Input: Prompt sentence (text format)

[0930] Output: Reply proposal (text format)

[0931] Specific operation: The server calls the generative AI model (e.g., OpenAI's API) and provides the prompt as input. The generative AI model analyzes the prompt and generates an appropriate reply proposal. For example, it generates a reply proposal that reads, "We will guide you through how to return the product. First, please prepare your purchase receipt. Then, please bring it to the store together with the product, and a staff member will assist you."

[0932] Step 4:

[0933] The server transmits the generated reply text proposal to the terminal.

[0934] Input: Reply proposal (text format)

[0935] Output: Reply proposal (text format)

[0936] Specific operation: The server sends the generated reply text suggestions to the user's terminal, which receives and displays the reply text suggestions.

[0937] Step 5:

[0938] The device displays reply suggestions to the user.

[0939] Input: Reply proposal (text format)

[0940] Output: Displayed reply suggestions (visual display)

[0941] Specific operation: The terminal displays the received reply message on the screen so that the user can confirm it. For example, the following message may be displayed on the smartphone screen: "We will guide you through how to return the product. First, please prepare your purchase receipt. Then, bring it together with the product to the store and a staff member will assist you."

[0942] Step 6:

[0943] The user refers to the generated reply proposal and takes appropriate action with respect to the parent or customer.

[0944] Input: Response suggestions displayed (visual display)

[0945] Output: User's response action

[0946] Specific operation: The user (staff member of the educational institution or the store staff member) responds appropriately to the guardian or customer by referring to the displayed reply text suggestions. For example, the store staff member may explain to the customer, "We will explain how to return the product. First, please prepare the receipt from the time of purchase. Then, please bring it together with the product to the store, and the staff member will assist you."

[0947] Example 2

[0948] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0949] In traditional educational settings, it took a lot of time and effort for teachers to communicate smoothly with parents. In particular, writing replies to emails from parents was a heavy burden for teachers. In addition, the quality of the replies was directly linked to the parents' trust and sense of security, so the content of the replies was required to be of high quality. This increased teachers' work hours and could have an impact on the quality of education.

[0950] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0951] In this invention, the server includes a means for sending emails received by a user to the server, a means for generating a prompt sentence for inputting the email received by the server to the generative AI model, and a means for the server to input the prompt sentence to the generative AI model and generate a reply sentence proposal. This enables teachers to quickly generate high-quality reply sentences to emails from parents. This can significantly reduce the teacher's work time and maximize the effectiveness of communication with parents.

[0952] "Guardian" refers to the parent or guardian of a child or student attending an educational institution.

[0953] "Communication" refers to the exchange of information between teachers and parents.

[0954] A "communication notebook" refers to a means for teachers and parents to share information about children's and students' learning and living situations.

[0955] "Means of management" refers to the method or system for organizing the contents of the contact book and properly storing and updating it.

[0956] A "veteran teacher" is a teacher who has many years of teaching experience and has excellent leadership and communication skills.

[0957] "Speaking" refers to the techniques and methods of effectively conveying information using words.

[0958] "Artificial intelligence" refers to technology that enables computer systems to mimic human intelligence and perform learning and reasoning.

[0959] "Needs" refers to the demands and expectations that parents have.

[0960] "Means of instant identification" refers to methods and systems for quickly understanding parents' needs and responding appropriately.

[0961] "Response draft" refers to a draft response to inquiries or requests from parents.

[0962] "Means for providing" refers to a method or system for presenting the generated reply suggestions to the user.

[0963] "User" refers to the teacher who uses this system.

[0964] "Server" refers to a computer system for processing and storing data.

[0965] "Generative AI model" refers to a model for generating text using artificial intelligence technology.

[0966] A "prompt sentence" refers to an instruction sentence to be input into a generative AI model.

[0967] "Terminal" refers to a device such as a computer or smartphone used by a user.

[0968] "Means for modification" refers to a method or system that allows a user to edit or modify the generated reply proposal.

[0969] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0970] The present invention is a system for enabling teachers to smoothly communicate with parents, and generates reply proposals using artificial intelligence technology. A specific embodiment of this system is described below.

[0971] Hardware and Software Used

[0972] The system uses the following hardware and software:

[0973] Server: A computer system for processing and storing data. For example, a cloud server or an on-premise server is used.

[0974] Terminal: A device such as a computer or smartphone used by a user. Examples include PCs, tablets, and smartphones.

[0975] Generative AI model: A model for generating text using artificial intelligence techniques, such as OpenAI's GPT-4.

[0976] System Operation

[0977] After receiving the email from the parent, the user (teacher) opens a dedicated web application, copies and pastes the received email, and then clicks the "Send" button to send the email to the server.

[0978] The server analyzes the content of the received email and generates a prompt to input to the generative AI model. For example, it generates the following prompt:

[0979] "Parents emailed me saying: 'I'm worried about my child's grades. How can I help?'"

[0980] The server inputs the generated prompt sentence into the generative AI model. The generative AI model generates appropriate reply sentence suggestions based on the prompt sentence. For example, it generates reply sentence suggestions like the following:

[0981] "Thank you for your support. I understand that you are worried about your child's grades. First of all, it is important to create a good learning environment at home. Specifically, I recommend that you set a time each day to study and create an environment where your child can concentrate. Also, please rest assured that we will be providing comprehensive support at school."

[0982] The server then sends the generated reply suggestions to the user's device, where the user can review the reply suggestions through a dedicated interface and make corrections as necessary, for example by adding additional information tailored to the specific situation or fine-tuning the wording.

[0983] The user then sends the revised reply to the parent, thereby achieving quick and effective communication.

[0984] Examples

[0985] For example, if a user receives an email from a parent saying, "I'm worried about my child's grades. How can I help them?", the user sends this email to the server, which generates the following prompt:

[0986] "Parents emailed me saying: 'I'm worried about my child's grades. How can I help?'"

[0987] Based on this prompt, the generative AI model generates the following reply suggestions:

[0988] "Thank you for your support. I understand that you are worried about your child's grades. First of all, it is important to create a good learning environment at home. Specifically, I recommend that you set a time each day to study and create an environment where your child can concentrate. Also, please rest assured that we will be providing comprehensive support at school."

[0989] The user checks the reply draft, modifies it as necessary, and then sends it to the guardian. Through this process, the user can quickly generate a high-quality reply, enabling smooth communication with the guardian.

[0990] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0991] Step 1:

[0992] The user receives an email from a parent.

[0993] Specific operation: A user (teacher) receives an email from a parent in his / her own email account. For example, a parent may receive an email saying, "I'm worried about my child's grades. How can I support him / her?"

[0994] Enter: Email from parent.

[0995] Output: The content of the received email.

[0996] Step 2:

[0997] The user sends the received email to the server.

[0998] Specific operation: A user opens a dedicated web application, copies and pastes the received email, and then clicks the "Send" button to send the email to the server.

[0999] Input: The content of the received email.

[1000] Output: The content of the email sent to the server.

[1001] Step 3:

[1002] The server generates a prompt sentence to input the received email into the generative AI model.

[1003] Specific operation: The server analyzes the contents of the received email and generates a prompt sentence to input to the generative AI model. For example, it creates a prompt sentence such as "Contents of email from parent: 'I'm worried about my child's grades. How can I support him?'"

[1004] Input: The content of the email sent to the server.

[1005] Output: The generated prompt statement.

[1006] Step 4:

[1007] The server inputs the prompt text into the generative AI model and generates reply text suggestions.

[1008] Specific operation: The server inputs the generated prompt sentence into a generative AI model (for example, OpenAI's GPT-4). The generative AI model generates an appropriate reply sentence proposal based on the prompt sentence. For example, it generates a reply sentence proposal that reads, "Thank you for your support. I understand that you are worried about your child's grades. First of all, it is important to create a good learning environment at home. Specifically, I recommend that you decide on a daily study time and create an environment where your child can concentrate. We will also provide comprehensive support at school, so please rest assured."

[1009] Input: The generated prompt statement.

[1010] Output: The generated reply suggestions.

[1011] Step 5:

[1012] The server transmits the generated reply sentence proposal to the user's terminal.

[1013] Specific operation: The server sends the generated reply text suggestions to the user's terminal, and the user can check the reply text suggestions through a dedicated interface.

[1014] Input: The generated reply suggestion.

[1015] Output: Reply proposal sent to the user's device.

[1016] Step 6:

[1017] The user reviews the reply proposal and modifies it if necessary.

[1018] What happens: The user reviews the reply text sent by the server and makes corrections if necessary, for example adding additional information to suit the specific situation or fine-tuning the wording.

[1019] Input: A reply proposal sent to the user's device.

[1020] Output: The revised reply proposal.

[1021] Step 7:

[1022] The user sends the corrected reply text to the parent.

[1023] Specific operation: The user sends the revised reply to the parent, thereby achieving quick and effective communication.

[1024] Input: Revised reply proposal.

[1025] Output: The reply sent to the parent.

[1026] (Application example 2)

[1027] Next, a description will be given of 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 glasses 214 will be referred to as a "terminal".

[1028] In the conventional system, teachers and staff had to spend a lot of time communicating with parents and customers, which led to a decrease in work efficiency. In addition, the quality of the replies was not consistent, which led to a lack of trust and security. This could lead to a decrease in the quality of education and customer satisfaction.

[1029] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1030] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents by an AI that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the AI, a means for the AI ​​to automatically generate reply proposals in response to inquiries from customers, a means for the AI ​​to provide highly reliable replies that have learned the responses of veteran staff, and a means for facilitating communication with customers and improving customer satisfaction. This makes it possible to reduce the work hours of teachers and staff and maximize the effectiveness of communication.

[1031] A "communication notebook" is a ledger or digital tool for recording and managing information for communicating with parents.

[1032] A "veteran teacher" refers to an educator with many years of experience and a high level of specialized knowledge.

[1033] "Speaking skills" refers to the use of words and expression techniques for effective communication.

[1034] "AI" is an abbreviation for artificial intelligence, a technology that uses machine learning and natural language processing to mimic human intelligence.

[1035] "Parent needs" refers to the information and support that parents seek in education and child-rearing.

[1036] "Response suggestions" refers to documents that suggest appropriate responses to specific inquiries or situations.

[1037] "Customer" refers to a person who purchases or uses a product or service.

[1038] An "Inquiry" is a question or request made for information or assistance.

[1039] "Veteran staff" refers to employees with many years of experience and high levels of specialized knowledge.

[1040] "Reliability" refers to information and services being accurate and functioning as expected.

[1041] "Customer satisfaction" refers to the degree of satisfaction a customer feels toward a product or service.

[1042] "Task time" refers to the time spent performing a particular task.

[1043] "Communication effectiveness" is an indicator that shows how effectively information is transmitted and communication is carried out.

[1044] The system for carrying out this invention is composed of three main components: a server, a terminal, and a user. The server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents by an AI that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the AI, a means for an AI to automatically generate reply proposals in response to inquiries from customers, a means for an AI to provide reliable replies that have learned the responses of veteran staff, and a means for facilitating communication with customers and improving customer satisfaction.

[1045] Hardware and Software Used

[1046] Hardware: Smartphones, servers

[1047] Software: Python, OpenAI API (GPT-3)

[1048] Data processing and calculation

[1049] The server first receives an inquiry from a parent or customer. It then generates a prompt based on the content of the inquiry. This prompt is input into an AI model that has learned the speaking skills of veteran teachers and staff. The AI ​​model generates an appropriate reply proposal based on the input prompt. The generated reply proposal is sent from the server to the terminal and provided to the user.

[1050] Examples

[1051] For example, if a customer asks "How do I return an item?" the server might generate the following prompt:

[1052] Customer Question: How do I return an item?

[1053] Please reply like a veteran staff member.

[1054] If you feed this prompt into OpenAI's GPT-3 API, it will generate the following reply:

[1055] Hello, customer. We would like to inform you of the return method for your product. First, please fill in the return form that we sent you together with the product and enclose it with the product. After that, please send it to the specified return address and we will proceed with the return procedure. If you have any questions, please feel free to contact us.

[1056] The reply proposals generated in this way are sent from the server to the terminal and provided to the user, which reduces the work time of teachers and staff and maximizes the effectiveness of communication.

[1057] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1058] Step 1:

[1059] The server receives inquiries from parents and customers.

[1060] Input: Inquiries from parents and customers

[1061] Output: Text data of the inquiry

[1062] Specific operation: The server saves the content of inquiries received through interfaces such as inquiry forms and emails as text data.

[1063] Step 2:

[1064] The server generates a prompt sentence based on the received query.

[1065] Input: Text data of inquiry

[1066] Output: Prompt statement

[1067] Specific operation: Based on the inquiry content, the server generates a prompt sentence in the form of "Customer inquiry: [Inquiry content] Please reply like an experienced staff member."

[1068] Step 3:

[1069] The server sends the generated prompt text to OpenAI's GPT-3 API.

[1070] Input: prompt statement

[1071] Output: Request to the GPT-3 API

[1072] What happens: The server formats the generated prompt as an API request and sends it to OpenAI's GPT-3 API.

[1073] Step 4:

[1074] The server receives the reply sentence proposal from the GPT-3 API.

[1075] Input: A request to the GPT-3 API

[1076] Output: Reply proposal

[1077] Specific operation: The server receives the reply sentence proposal returned from the GPT-3 API and stores it as text data.

[1078] Step 5:

[1079] The server transmits the generated reply text proposal to the terminal.

[1080] Input: Reply proposal

[1081] Output: Data sent to the terminal

[1082] Specific operation: The server converts the reply text proposal into an appropriate format and sends it to the user's device.

[1083] Step 6:

[1084] The terminal displays the received reply sentence suggestions to the user.

[1085] Input: Data to send to the terminal

[1086] Output: Reply suggestions shown to the user

[1087] Specific operation: The device displays the received reply proposal on the screen for the user to review.

[1088] Step 7:

[1089] The user checks the displayed reply draft and, if necessary, modifies or sends it.

[1090] Input: A suggested reply that will be displayed to the user

[1091] Output: revised reply proposal or sent reply

[1092] Specific behavior: The user reviews the proposed reply, makes corrections if necessary, and then submits it as the final reply.

[1093] Example 3

[1094] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1095] In the past, teachers had to spend a lot of time writing replies, making it difficult to communicate efficiently. In addition, because the quality of the replies depended on the teacher's experience and skills, parents were often unable to feel reassured or trusted by the replies. This resulted in an increase in the teacher's workload and a decrease in the effectiveness of communication.

[1096] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1097] In this invention, the server includes a means for collecting reply sentences and feedback used by teachers in the past and storing them in a database, a means for training a generative AI model using the collected data, and a means for generating appropriate reply sentences using the generative AI model. This enables teachers to quickly obtain appropriate reply sentences in response to inquiries and requests from parents.

[1098] A "communication book" is a recording medium for communication between parents and teachers, and may include paper or electronic media.

[1099] "Artificial intelligence" is the technology that enables computer systems to mimic human intelligence and learn, reason, and self-correct.

[1100] A "generative AI model" is a type of artificial intelligence that has the ability to generate new data based on a specific dataset.

[1101] A "database" is a system for efficiently storing, managing, and searching data.

[1102] An "interface" is the means by which a user interacts with a system, including input forms and graphical user interfaces (GUIs).

[1103] A "server" is a computer system that provides services to other computers over a network.

[1104] A "terminal" is a computer device that is directly operated by a user, and includes a PC, tablet, smartphone, etc.

[1105] An "inquiry" refers to a question or request that a parent or guardian makes to a teacher.

[1106] A "reply letter" is a letter that a teacher sends to a parent / guardian to answer or provide information.

[1107] "Feedback" refers to evaluations and opinions received from teachers regarding past communication.

[1108] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1109] The present invention provides a system for improving the efficiency of communication with parents and reducing the workload of teachers. A specific embodiment of this system will be described below.

[1110] Hardware and software used

[1111] Hardware: Servers, terminals (PCs, tablets, smartphones)

[1112] Software: Generative AI models (e.g. OpenAI GPT-4), database management systems (e.g. MySQL)

[1113] Server Roles

[1114] The server collects teachers' past reply phrases and feedback and stores them in a database. Specifically, the server extracts data from teachers' email accounts and the school's communication system and stores it in a MySQL database. Next, the server uses the collected data to train a generative AI model (e.g., OpenAI GPT-4). The generative AI model learns teachers' speaking skills and reply patterns and has the ability to generate appropriate reply phrases to inquiries from parents.

[1115] Terminal Roles

[1116] The terminal provides an interface for teachers to input questions and requests from parents. Specifically, the terminal displays an input form through a web browser or a dedicated app, and teachers input the questions into the form. The input data is sent to the server as an HTTP request.

[1117] User Roles

[1118] The user (teacher) uses the device to input inquiries and requests from parents. Once input is complete, the device sends the data to the server. The server uses a generative AI model to generate an appropriate reply text and sends the result back to the user's device. The user checks the generated reply text, makes corrections if necessary, and then sends it back to the parent.

[1119] Examples

[1120] For example, if a parent asks, "My child's grades seem to have dropped recently. How can I support him?", the teacher enters this information into the device. The device sends the entered data to the server, which uses a generative AI model to generate an appropriate reply. The generated reply might be something like, "I understand that you are worried about your child's grades. First of all, I would recommend that you review the learning environment at home and ensure that they set aside regular study time. I would also like to hear about the support system at school."

[1121] In this way, the teacher can quickly and appropriately reply to inquiries from parents. This reduces the workload of the teacher and improves the quality of communication with parents. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1122] Step 1:

[1123] The server collects the teacher's past reply sentences and feedback and stores them in a database. Specifically, the server extracts data from the teacher's email account and the school's communication system and stores it in a MySQL database. The input is the teacher's past reply sentences and feedback, and the output is the data stored in the database.

[1124] Step 2:

[1125] The server trains the generative AI model using the collected data. Specifically, the server reads data from the database and feeds it to the generative AI model (e.g., OpenAI GPT-4). The model learns the teacher's speaking style and reply patterns. The input is the data read from the database, and the output is the trained generative AI model.

[1126] Step 3:

[1127] The terminal provides an interface for teachers to input inquiries and requests from parents. Specifically, the terminal displays an input form through a web browser or a dedicated app, and teachers input the inquiries into the form. The input is the inquiries from parents, and the output is the data entered into the input form.

[1128] Step 4:

[1129] The terminal sends the entered data to the server. Specifically, the terminal sends the entered inquiry content to the server as an HTTP request. The input is the data entered into the input form, and the output is the data sent to the server.

[1130] Step 5:

[1131] The server generates an appropriate reply sentence using a generative AI model. Specifically, the server inputs the received query content into the generative AI model and obtains the generated reply sentence from the model. The input is the query content sent to the server, and the output is the generated reply sentence.

[1132] Step 6:

[1133] The server returns the generated reply text to the terminal. Specifically, the server sends the generated reply text to the terminal as an HTTP response. The input is the generated reply text, and the output is the reply text sent to the terminal.

[1134] Step 7:

[1135] The terminal displays the generated reply text to the teacher. Specifically, the terminal displays the received reply text on the screen so that the teacher can check it. The input is the reply text received from the server, and the output is the reply text displayed on the screen.

[1136] Step 8:

[1137] The user (teacher) checks the generated reply text, makes corrections if necessary, and then replies to the parent. Specifically, the user edits the reply text on the terminal and clicks the send button. The input is the generated reply text and the corrections made by the user, and the output is the final reply text sent to the parent.

[1138] (Application example 3)

[1139] Next, a description will be given of 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 glasses 214 will be referred to as a "terminal".

[1140] In conventional communication systems with parents, teachers had to prepare reply messages individually, which was time-consuming and labor-intensive. In addition, in brick-and-mortar stores, it was difficult for staff to respond quickly and appropriately to customer inquiries, which could lead to a decline in customer satisfaction. There is a need to solve these problems and achieve efficient and effective communication.

[1141] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1142] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents by an AI that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the AI, a means for quickly and appropriately replying to inquiries from customers, a means for proposing optimal replies to customer questions and requests by an AI that has learned from excellent customer service responses in the past, and a means including an application to be installed on a smartphone. This allows teachers to instantly obtain reply proposals to meet various needs from parents, and enables staff at physical stores to quickly and appropriately respond to customers.

[1143] "Guardian" refers to the parent or guardian of a child or student attending an educational institution.

[1144] "Communication" refers to the act of exchanging information and ideas.

[1145] A "communication book" refers to a written or electronic means for parents and teachers to exchange information.

[1146] A "veteran teacher" is a teacher who has many years of experience and possesses excellent teaching and speaking skills.

[1147] "Speaking" refers to the skill of conveying information effectively using words.

[1148] "AI" is an abbreviation for artificial intelligence and refers to the technology that allows machines to imitate human intelligence to learn and make judgments.

[1149] "Need" refers to a particular demand or requirement.

[1150] "Response Suggestion" means a suggested response to an inquiry or request.

[1151] A "system" refers to a combination of multiple elements that perform a specific function.

[1152] "Customer" refers to a person who purchases goods or services.

[1153] "Inquiry" refers to the act of requesting information or clarification.

[1154] "Rapid" means to act very quickly.

[1155] "Appropriate" means appropriate to the situation or purpose.

[1156] "Customer service" refers to the service and interaction provided to customers.

[1157] A "smartphone" is a type of mobile phone that is a multi-function device that can connect to the Internet and use applications.

[1158] "Application" refers to software that provides specific functions or services.

[1159] A system for implementing this invention is configured as follows. First, the server has a means for managing a contact book for communicating with parents. This contact book is a written or electronic means for parents and teachers to exchange information. Next, the server has a means for instantly grasping the needs of parents using AI that has learned the speaking techniques of veteran teachers. This AI learns excellent teaching techniques and speaking techniques from the past, and generates appropriate reply proposals for inquiries and requests from parents.

[1160] Furthermore, the server has a means for quickly and appropriately responding to customer inquiries. This means uses AI that has learned from past excellent customer service responses to suggest optimal responses to customer questions and requests. This enables staff at physical stores to respond to customers quickly and appropriately.

[1161] The system includes an application that is installed on a smartphone. The smartphone is connected to the Internet and can receive generated reply suggestions by communicating with the server. Specifically, when a staff member enters a customer inquiry into the smartphone, the server uses AI to generate an appropriate reply suggestion and sends it to the smartphone.

[1162] The hardware used is a smartphone connected to the Internet. The software uses Python and the OpenAI API. Python is used as the program execution environment, and the OpenAI API is used to generate reply sentence suggestions using an AI model.

[1163] As a concrete example, if a customer asks, "Please tell me more about this product," the staff member enters this inquiry into his smartphone. The server generates the following prompt sentence and inputs it into the AI ​​model.

[1164] Example prompt:

[1165] Customer Inquiry: Can you tell me more about this product?

[1166] Generate an appropriate reply.

[1167] The AI ​​model generates appropriate reply suggestions based on the prompt and sends them to the smartphone via the server. Staff can provide these reply suggestions to customers to respond quickly and appropriately.

[1168] In this manner, the present invention provides for efficient and effective communication with parents and clients.

[1169] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1170] Step 1:

[1171] A user inputs a customer inquiry into a smartphone terminal.

[1172] Input: Customer's inquiry (e.g. "Can you tell me more about this product?")

[1173] Output: The query is sent to the server.

[1174] Step 2:

[1175] The server converts the received query into a prompt.

[1176] Input: Customer inquiry

[1177] Output: Prompt statement (e.g. "Customer inquiry: Tell me more about this product. Generate an appropriate reply.")

[1178] Step 3:

[1179] The server inputs the prompt into a generative AI model to generate appropriate reply suggestions.

[1180] Input: Prompt statement

[1181] Output: Generated reply text (e.g. "This product is made of high-quality materials and is long-lasting.")

[1182] Step 4:

[1183] The server transmits the generated reply text proposal to the smartphone terminal.

[1184] Input: Generated reply suggestions

[1185] Output: A reply proposal is displayed on your smartphone.

[1186] Step 5:

[1187] The user checks the reply proposal displayed on the smartphone terminal and corrects it if necessary.

[1188] Input: Generated reply suggestions

[1189] Output: revised reply proposal (if necessary)

[1190] Step 6:

[1191] The user provides the revised reply proposal to the customer.

[1192] Input: revised reply proposal

[1193] Output: The reply provided to the customer

[1194] In this way, the user can respond quickly and appropriately to inquiries from customers.

[1195] In addition, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1196] "Example 1"

[1197] As one embodiment of the present invention, a system is provided in which AI is combined with an emotion engine that recognizes the user's emotions. This system manages a contact book for communicating with parents, and uses AI that has learned the speaking skills of veteran teachers to instantly grasp the needs of parents. Furthermore, the emotion engine analyzes the parent's emotional state and generates a reply proposal based on the results. Specifically, if the AI ​​senses that the parent is worried, it generates a reply proposal that gives a sense of security.

[1198] "Example 2"

[1199] The emotion engine also provides feedback to teachers. Specifically, it analyzes the emotional state of parents and reports the parents' emotional state and its changes to teachers based on the results. This allows teachers to better understand the parents' emotional state and communicate more appropriately.

[1200] "Example 3"

[1201] Furthermore, as another embodiment of the present invention, a system is provided in which an emotion engine analyzes the emotional state of a parent and provides feedback to a teacher based on the result. Specifically, if a parent feels angry, the AI ​​reports the information to the teacher, and the teacher can consider an appropriate response based on the information.

[1202] The process flow of each embodiment will be described below.

[1203] "Example 1"

[1204] Step 1: The AI ​​will manage a communication notebook to communicate with parents.

[1205] Step 2: The AI ​​learns the speaking techniques of veteran teachers and instantly understands the needs of parents.

[1206] Step 3: The emotion engine analyzes the parent's emotional state.

[1207] Step 4: The sentiment engine generates reply suggestions based on the analysis results.

[1208] "Example 2"

[1209] Step 1: The AI ​​will manage a communication notebook to communicate with parents.

[1210] Step 2: The AI ​​learns the speaking techniques of veteran teachers and instantly understands the needs of parents.

[1211] Step 3: The emotion engine analyzes the parent's emotional state.

[1212] Step 4: The emotion engine provides feedback to the teacher based on the analysis results.

[1213] "Example 3"

[1214] Step 1: The AI ​​will manage a communication notebook to communicate with parents.

[1215] Step 2: The AI ​​learns the speaking techniques of veteran teachers and instantly understands the needs of parents.

[1216] Step 3: The emotion engine analyzes the parent's emotional state.

[1217] Step 4: The emotion engine provides feedback to the teacher based on the analysis results.

[1218] Example 1

[1219] Next, a description will be given of 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 glasses 214 will be referred to as a "terminal".

[1220] In the conventional communication book system, it was difficult to respond quickly and appropriately to messages from parents, which placed a heavy burden on teachers. In addition, it was not possible to accurately grasp the feelings and needs of parents, which led to a decline in the quality of communication. This made it difficult to gain the reassurance and trust of parents, and there was an issue of communication not being fully effective.

[1221] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1222] In this invention, the server includes a means for managing a contact book for communication with a guardian, a means for receiving the contents of the contact book sent from the guardian, a means for analyzing the emotional state of the guardian using an emotion engine based on the contents of the contact book, a means for generating a reply draft using a prompt sentence instructing to generate a reply draft based on the contents of the contact book and the emotional state of the guardian and a generative AI model, and a means for transmitting the generated reply draft to a teacher's terminal. This makes it possible to rapidly generate an appropriate reply draft according to the needs and emotions of the guardian, reduce the burden on the teacher, and maximize the communication effect.

[1223] "Guardian" refers to a parent or guardian who is responsible for a child's education and life.

[1224] A "communication notebook" is a communication tool that allows parents and teachers to share their children's status and important announcements.

[1225] "Means of management" refers to the systems and methods for storing, organizing, and making accessible the contents of the contact list.

[1226] "Veteran teachers" refer to teachers with many years of teaching experience and excellent communication skills.

[1227] "Speaking skills" refers to the use of words and expression techniques for effective communication.

[1228] "Artificial intelligence" refers to technology that mimics human intelligence through machine learning and data analysis.

[1229] "Needs" refers to the requests and expectations parents have, and the information and support they require.

[1230] "Means of instantaneous understanding" refers to techniques and methods for quickly understanding and responding to parents' needs.

[1231] "Response proposal" refers to a document that suggests an appropriate response to a message from a parent.

[1232] "Means for providing" refers to a system or method for presenting the generated reply proposal to the teacher.

[1233] "Means of receiving" refers to the technology or method by which the server receives the contents of the communication book sent by the parent.

[1234] "Natural language processing technology" refers to computer technology for analyzing and understanding human language.

[1235] "Means of analysis" refers to techniques and methods for analyzing the contents of the address book and extracting important information.

[1236] An "emotion engine" refers to technology for analyzing and recognizing emotions from text and voice.

[1237] "Emotional state" refers to the mental state and feelings felt by the parent.

[1238] "Means of sending" refers to the technology or method for sending the generated reply draft to the teacher's terminal.

[1239] "Terminals" refers to devices such as computers and smartphones used by teachers.

[1240] This invention is a system for managing a contact book for communicating with parents. This system uses artificial intelligence that has learned the speaking skills of veteran teachers to instantly grasp the needs of parents and generate appropriate reply proposals.

[1241] The server receives the contents of the address book sent by the parent from the device. The parent enters a message into the address book application using a smartphone or computer and sends it. The server receives this message and stores it in a database.

[1242] The server then analyzes the contacts received using natural language processing techniques, such as software like Google Cloud Natural Language API and IBM Watson® Natural Language Understanding, to extract important keywords and context from the message content.

[1243] Furthermore, the server uses an emotion engine to analyze the parent's emotional state based on the contents of the contact book. The emotion engine uses Microsoft® Azure® Emotion API or similar. This allows the server to recognize the parent's emotions, such as whether they are worried or relieved.

[1244] Based on the analysis results, the server uses a generative AI model (for example, OpenAI's GPT-4) to generate an appropriate reply proposal. A prompt sentence is input to the generative AI model to generate a reply proposal. For example, if a parent writes in the communication book, "My child seems to be in a bad mood at school recently. Is there something that worries you?", the following prompt sentence is used.

[1245] Sentiment Analysis Result: Worry A parent's note in the communication book: "My child has not been feeling well at school lately. Is there something that is worrying you?" Example prompt: Please generate a response to the message in the communication book from a parent: "My child seems to be in a bad mood at school recently. Is there something that worries you?" The parent's emotion is "worry," so please generate a response that gives a sense of security.

[1246] The generated reply draft is sent to the teacher's device. The teacher checks the reply draft on the device, makes any necessary corrections, and then records it in the communication book and sends a reply to the parent. For example, if the generated reply draft is "Thank you for your concern. We will carefully observe your child's condition and provide support as needed. Please contact us anytime if you have any concerns," the teacher will use this as a reference to record it in the communication book and send a reply to the parent.

[1247] This system makes it possible to quickly generate appropriate reply proposals that correspond to the needs and feelings of parents, reducing the burden on teachers and maximizing the effectiveness of communication.

[1248] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1249] Step 1:

[1250] Receiving communication from parents

[1251] The server receives the contents of the address book sent by the parent from the device. The parent enters a message into the address book application using a smartphone or computer and sends it. The server receives this message and stores it in a database.

[1252] Input: A message sent by the parent or guardian from their device

[1253] Output: Address book messages stored in the database

[1254] Specific operation: A parent types, "My child seems to be in a bad mood at school recently. Is there something that is bothering you?" and presses the send button. The server receives this message and stores it in a database.

[1255] Step 2:

[1256] Analysis of contact list contents

[1257] The server then analyzes the contents of the contacts received using natural language processing technology, using software such as Google Cloud Natural Language API and IBM Watson Natural Language Understanding, to extract important keywords and context from the message content.

[1258] Input: A contact message stored in the database

[1259] Output: Extracted keywords and context information

[1260] Specific operation: The server sends a message to the Google Cloud Natural Language API saying, "Your child seems to be in a bad mood at school recently. Is there something you're worried about?" The API analyzes the message and extracts keywords such as "child," "not in a good mood," and "worry."

[1261] Step 3:

[1262] Emotional state analysis

[1263] The server uses an emotion engine to analyze the parent's emotional state based on the results of analyzing the contents of the contact book. The emotion engine uses Microsoft Azure Emotion API, etc. This allows the server to recognize the parent's emotions, such as whether they are worried or relieved.

[1264] Input: A contact message stored in the database

[1265] Output: Parsed emotional state

[1266] How it works: The server sends the contents of the contact list to the Microsoft Azure Emotion API, which analyzes the message and recognizes the emotion "worry."

[1267] Step 4:

[1268] Generate reply suggestions

[1269] The server uses a generative AI model (e.g., OpenAI GPT-4) to generate appropriate reply sentence suggestions according to the parent's needs and emotional state. The generative AI model receives a prompt sentence as an input and generates a reply sentence suggestion.

[1270] Input: Extracted keywords, contextual information, analyzed emotional state

[1271] Output: The generated reply suggestions

[1272] Specific operation: The server should generate a reply to the prompt "The parent's message in the message book: 'My child seems to be in a bad mood at school recently. Is there something that worries you?'" The parent's emotion is "worry," so the server should generate a reply that gives a sense of security. " is sent to the generation AI model. The AI ​​model generates a reply suggestion that reads, "Thank you for your concern. We will closely monitor your child's condition and provide support as needed. If you have any concerns, please contact us at any time."

[1273] Step 5:

[1274] Sending and viewing reply suggestions

[1275] The server then sends the generated reply draft to the teacher's device, where the teacher checks the reply draft, makes corrections if necessary, records it in the communication book, and sends it back to the parent.

[1276] Input: Generated reply suggestions

[1277] Output: Response proposal displayed on teacher's device

[1278] Specific operation: The server sends the generated reply draft to the teacher's terminal. The teacher checks the draft on the terminal, which reads, "Thank you for your concern. We will closely monitor your child's condition and provide support as necessary. If you have any concerns, please contact us at any time." The teacher amends the draft as necessary, records it in the communication book, and sends it back to the parent.

[1279] The generative AI model may generate multiple reply drafts. In this case, the generated multiple reply drafts are sent to the teacher's terminal, an operation to select one of the generated multiple reply drafts is accepted from the teacher's terminal, the selected reply draft is recorded in the communication book, and returned to the guardian. Also, an operation to select one of the generated multiple reply drafts and an operation to edit the selected reply draft may be accepted from the teacher's terminal, the selected and edited reply draft is recorded in the communication book, and returned to the guardian.

[1280] (Application example 1)

[1281] Next, a description will be given of 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 glasses 214 will be referred to as a "terminal".

[1282] In conventional communication systems with parents, it was difficult to instantly grasp the needs and emotional state of parents and generate appropriate reply sentences. In addition, when dealing with customers in brick-and-mortar stores, it is necessary to properly analyze customers' questions and emotional state and respond quickly and appropriately, but there was a lack of effective means to achieve this. This resulted in a decline in the quality of communication and made it difficult to improve customer satisfaction.

[1283] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1284] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using AI that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the AI, a means for analyzing customer questions and generating appropriate answer proposals, a means for analyzing the emotional state of customers using an emotion engine, and a means for adjusting a response method based on the analysis results. This makes it possible to instantly grasp the needs and emotional state of parents and customers and take appropriate measures.

[1285] "Guardian" refers to the parent or guardian of a child attending an educational institution.

[1286] "Communication" refers to the act of exchanging information and emotions.

[1287] A "communication book" refers to a document or digital tool for exchanging information between parents and educational institutions.

[1288] A "veteran teacher" is a teacher who has many years of experience and possesses excellent teaching and speaking skills.

[1289] "Speaking" refers to the skill of conveying information effectively using words.

[1290] "AI" stands for artificial intelligence and refers to technology that mimics human intelligence.

[1291] "Needs" refers to a demand or request that is required in a particular situation or condition.

[1292] "Response suggestions" refer to suggestions for appropriate answers or messages to specific questions or situations.

[1293] "Customer" refers to a person who purchases goods or services.

[1294] A "question" is a question asked to seek information or knowledge.

[1295] "Suggested Answer" refers to a suggestion of an appropriate answer to a question.

[1296] An "emotion engine" refers to technology that analyzes emotions and takes appropriate action based on the results.

[1297] "Emotional state" refers to a person's emotional state at a particular moment.

[1298] "Analysis" refers to the act of examining and understanding data or information in detail.

[1299] "Response strategies" refer to the actions or steps to be taken in response to a particular situation or problem.

[1300] "Adaptation" refers to the act of making changes or modifications to suit a specific purpose.

[1301] The following system configuration will be described as an embodiment of the present invention.

[1302] System Configuration

[1303] The system is composed of three main elements: a server, a terminal, and a user. The server manages a contact book for communicating with parents, and instantly grasps the needs of parents using AI that has learned the speaking techniques of veteran teachers. It also has the function of analyzing customer questions and generating appropriate response proposals. Furthermore, it uses an emotion engine to analyze the emotional state of the customer and adjusts the response method based on the results.

[1304] Hardware and Software Used

[1305] Hardware: Smartphones, smart glasses

[1306] Software: Python, OpenAI API, EmotionRecognizer library

[1307] Data processing and calculation

[1308] Server Processing

[1309] The server receives input data from parents and customers and performs the following processes.

[1310] 1. Question analysis: The server analyzes the question entered by the user. Specifically, it uses the OpenAI API to analyze the question and generate appropriate answers.

[1311] 2. Emotion Analysis: The server uses the EmotionRecognizer library to analyze the user's emotional state, thereby understanding what emotional state the user is in.

[1312] 3. Adjusting the response: The server adjusts the appropriate response based on the results of the sentiment analysis. For example, if the user is feeling anxious, it generates a response that reassures the user.

[1313] Terminal handling

[1314] The terminal (smartphone or smart glasses) displays the analysis results and suggested answers sent from the server to the user, allowing the user to quickly check the appropriate response method.

[1315] User Actions

[1316] Users input questions through their terminals and check the suggested answers from the server, which facilitates smooth communication with parents and customers.

[1317] Examples

[1318] For example, if a customer in a physical store asks, "How do I use this product?", the server generates answer suggestions using the following prompt:

[1319] Examples of prompt statements

[1320] Customer Question: How do I use this product?

[1321] Customer Sentiment: Interest

[1322] Generate suitable answer suggestions.

[1323] Based on this prompt, the server uses the OpenAI API to generate appropriate response suggestions and uses the EmotionRecognizer library to analyze the customer's emotional state. Based on the analysis results, the server adjusts the optimal response method and sends it to the device. The device displays this information to the user, allowing the user to respond quickly and appropriately.

[1324] This makes it possible to instantly grasp the needs and emotional state of parents and customers and respond appropriately.

[1325] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1326] Step 1:

[1327] The user inputs a question using a device (smartphone or smart glasses).

[1328] Input: User question (e.g. "How do I use this product?")

[1329] Output: The question data is sent to the server.

[1330] Specific operation: The user inputs a question using the input interface of the terminal and presses the send button. The terminal then sends the question data to the server.

[1331] Step 2:

[1332] The server analyzes the received question data.

[1333] Input: Question data submitted by the user

[1334] Output: A prompt based on the question

[1335] Specific operation: The server receives the question data, analyzes the question using the OpenAI API, and generates a prompt based on the analysis result.

[1336] Step 3:

[1337] The server uses the prompt to generate appropriate responses.

[1338] Input: Prompt text (e.g. "Customer question: How do I use this product?")

[1339] Output: Suggested answer (e.g. "This product is very easy to use. First, turn it on, then...")

[1340] Specific operation: The server sends the generated prompt to the OpenAI API, which generates appropriate answer suggestions, which are then returned to the server.

[1341] Step 4:

[1342] The server uses an emotion engine to analyze the user's emotional state.

[1343] Input: User question data

[1344] Output: Emotional state (e.g. "interested")

[1345] Specific operation: The server uses the EmotionRecognizer library to analyze the emotional state from the user's question data. The analysis result is the emotional state.

[1346] Step 5:

[1347] The server adjusts its response based on the emotional state.

[1348] Input: proposed answer, emotional state

[1349] Output: Adjusted answer proposal

[1350] What it does: The server adjusts the response based on the generated answer and the user's emotional state. For example, if the user is feeling anxious, it adds reassuring expressions.

[1351] Step 6:

[1352] The server sends the adjusted answer proposal to the terminal.

[1353] Input: Adjusted answer proposal

[1354] Output: Proposed answers displayed on the terminal

[1355] Specific operation: The server sends the adjusted answer plan to the terminal, which displays the answer plan to the user.

[1356] Step 7:

[1357] The user checks the adjusted answer proposal through the terminal.

[1358] Input: Answer displayed on the device

[1359] Output: User understanding and action

[1360] Specific actions: The user checks the suggested answers displayed on the device screen and takes the necessary action, such as understanding how to use the product and actually using it.

[1361] Example 2

[1362] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[1363] Traditionally, communication between teachers and parents required teachers to write individual replies, which was time-consuming and labor-intensive. In addition, it was difficult for teachers to accurately grasp the emotional state of parents, and they were sometimes unable to respond appropriately. This resulted in a decline in the quality of communication and in the inability to fully realize the effectiveness of education.

[1364] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1365] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using artificial intelligence that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the artificial intelligence, a means for receiving replies from parents and analyzing their emotions, and a means for feeding back the results of the emotion analysis to the teacher. This enables teachers to communicate with parents quickly and effectively, shortening their work hours and improving the quality of communication.

[1366] "Means to manage a communication notebook" refers to the function of managing digital or physical tools for exchanging information between teachers and parents.

[1367] "Artificial intelligence that has learned the speaking techniques of veteran teachers" is artificial intelligence that has the ability to learn the communication techniques and methods of expression of experienced teachers and generate sentences based on them.

[1368] "A means of instantly grasping the needs of parents" is a function that analyzes input and inquiries from parents and immediately understands their requests and expectations.

[1369] "Means for providing generated reply suggestions" is a function that presents reply suggestions generated by artificial intelligence to the teacher.

[1370] "Means for receiving responses from parents" refers to a function for receiving messages and feedback sent by parents.

[1371] "Means for performing emotion analysis" is a function for analyzing the content of a received message and determining the emotional state of the sender.

[1372] "Means of providing feedback on the results of emotion analysis to teachers" is a function that reports the results of emotion analysis to teachers and supports appropriate responses.

[1373] The present invention is a system for facilitating communication between teachers and parents, and is implemented as follows.

[1374] First, a user (teacher) uses a terminal (PC or tablet) to input a prompt for a reply to be sent to the parent. For example, the user might input, "Please generate a reply to report to the parent about the student's progress. The student has performed well on recent tests, but he tends to be late in submitting his homework."

[1375] The server receives the prompt sentence. The server uses a generative AI model (e.g., OpenAI's GPT-4) to generate reply sentence suggestions based on the received prompt sentence. The generative AI model has learned the speaking techniques of veteran teachers and generates reliable sentences.

[1376] The generated reply draft is sent from the server to the teacher's device. The teacher checks the draft and makes corrections as necessary. For example, the teacher may change "You achieved very good grades" to "You achieved excellent grades." The corrected reply is then sent from the teacher to the parent.

[1377] The server receives the replies from the parents. The server uses emotion analysis software (e.g., IBM Watson's Natural Language Understanding) to analyze the emotional state of the parents' replies. The analysis results are fed back to the teacher. For example, the teacher may be provided with information such as "the parents feel relieved."

[1378] This system will enable teachers to communicate with parents quickly and effectively, reducing work time and improving the quality of communication.

[1379] As a concrete example, consider a teacher reporting to parents on student progress. The teacher types the following prompt:

[1380] "Generate a response to parents about their student's progress. The student performed well on recent tests, but is often late in turning in his / her homework."

[1381] The server receives this prompt and uses a generative AI model to generate a response suggestion like this:

[1382] "Dear Parents,

[1383] Thank you for your support. I would like to inform you of my child's recent progress. He did very well on the recent test. However, I am concerned that he is often late in turning in his homework. I would appreciate it if you could help him turn in his homework more smoothly in the future.

[1384] We appreciate your continued support."

[1385] In this way, teachers can communicate with parents quickly and effectively, and the emotion engine can analyze the parents' responses and provide feedback to teachers, such as "the parents feel relieved," to help them take further appropriate action.

[1386] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1387] Step 1:

[1388] A user (teacher) uses a terminal (PC or tablet) to input a prompt for a reply message to be sent to the parent. The input prompt is sent to the server. For example, the user might input, "Please generate a reply message to report to the parent about the student's progress. The student has performed well on recent tests, but he tends to be late in turning in his homework."

[1389] Step 2:

[1390] The server receives the prompt sent by the user. The received prompt is passed to the generative AI model. The server analyzes the prompt and processes the data to generate an appropriate reply.

[1391] Step 3:

[1392] The server uses a generative AI model (e.g., OpenAI's GPT-4) to generate reply sentence suggestions based on the received prompt sentence. The generative AI model has learned the speaking techniques of veteran teachers and generates reliable sentences. The generated reply sentence suggestions are temporarily stored in the server.

[1393] Step 4:

[1394] The server transmits the generated reply draft to the teacher's terminal. The transmitted reply draft is displayed on the teacher's terminal. The teacher can check the draft.

[1395] Step 5:

[1396] The user (teacher) checks the reply draft on the terminal and makes corrections as necessary. For example, "You achieved very good grades" is changed to "You achieved excellent grades." The corrected sentence is sent from the terminal to the server.

[1397] Step 6:

[1398] The server receives the corrected reply text sent by the teacher and sends it to the parent / guardian. The parent / guardian can receive the reply text from the teacher.

[1399] Step 7:

[1400] The server receives the reply from the guardian. The received reply is subjected to emotion analysis. The server processes the data to analyze the reply from the guardian.

[1401] Step 8:

[1402] The server uses emotion analysis software (e.g., IBM Watson's Natural Language Understanding) to analyze the emotional state of the parent's reply. The analysis results are temporarily stored on the server.

[1403] Step 9:

[1404] The server feeds back the results of the emotion analysis to the teacher. The fed back information is displayed on the teacher's terminal. For example, information such as "the parent feels relieved" is provided to the teacher. This allows the teacher to understand the parent's emotional state and take appropriate action.

[1405] (Application example 2)

[1406] Next, a description will be given of 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 glasses 214 will be referred to as a "terminal".

[1407] In the conventional system, teachers had to spend a lot of time communicating with parents, which led to a decrease in work efficiency. In addition, in brick-and-mortar stores, it was difficult to respond appropriately to customer inquiries or understand the emotional state of customers, making it difficult to improve customer satisfaction.

[1408] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1409] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using AI that has learned the speaking skills of veteran teachers, a means for providing reply suggestions generated by the AI, a means for generating optimal reply suggestions for inquiries from customers, and a means for analyzing the emotional state of customers and providing feedback to store clerks. This makes it possible to reduce the work hours of teachers and maximize the effectiveness of communication with parents. Also, in physical stores, it is possible to provide appropriate replies to inquiries from customers and grasp the emotional state of customers, thereby improving customer satisfaction.

[1410] A "means for managing a communication notebook" is a function that allows for organizing and storing information for communicating with parents and for accessing it as needed.

[1411] "AI that has learned the speaking techniques of veteran teachers" is an artificial intelligence that learns the communication techniques and speaking styles of experienced teachers and uses that knowledge to respond appropriately to parents and customers.

[1412] "A means of instantly grasping the needs of parents" is a function that enables prompt understanding of inquiries and requests from parents and provides appropriate responses.

[1413] "Means of providing generated reply suggestions" refers to a function that presents reply suggestions generated by AI to users, facilitating communication.

[1414] "A means of generating optimal reply suggestions for customer inquiries" refers to a function in which AI generates and provides optimal reply sentences based on the content of a customer's inquiry.

[1415] "A means of analyzing the customer's emotional state and providing feedback to store associates" is a function that analyzes the customer's emotional state from their words and actions, and conveys the results to store associates, enabling them to respond more appropriately.

[1416] The system for implementing the present invention is composed of three main components: a server, a terminal, and a user. The following describes how each component functions.

[1417] server

[1418] The server includes the following means:

[1419] 1. A means to manage communication notebooks: This function organizes and stores information for communicating with parents and allows them to access it as needed. This allows teachers to efficiently manage communication with parents.

[1420] 2. AI that learned the speaking skills of veteran teachers: This is an AI that learns the communication techniques and speaking styles of experienced teachers and uses them to respond appropriately to parents and customers. This AI is implemented using the OpenAI API.

[1421] 3. A means to instantly understand the needs of parents: This function allows teachers to quickly understand inquiries and requests from parents and respond appropriately. This allows teachers to instantly understand the needs of parents.

[1422] 4. A means of providing generated reply suggestions: This function presents reply suggestions generated by AI to users, facilitating smooth communication.

[1423] 5. A means of generating optimal reply suggestions for customer inquiries: This function enables AI to generate and provide optimal reply sentences based on the content of customer inquiries.

[1424] 6. A means of analyzing the customer's emotional state and providing feedback to store clerks: This function analyzes the customer's emotional state from their words and actions, and conveys the results to store clerks, enabling them to respond more appropriately. The TextBlob library is used for this emotion analysis.

[1425] Terminal

[1426] The terminals are devices such as smartphones and tablets used by teachers and store clerks. Applications that display information provided by the server and allow users to operate the terminals are installed on these terminals.

[1427] User

[1428] The users are teachers or store clerks, and communicate with parents and customers based on the information provided by the server. The users access the server through their terminals to obtain the necessary information.

[1429] Examples

[1430] For example, if a parent asks, "Please tell me how to return an item," the server generates a reply using the following prompt:

[1431] Customer Question: What about returning products?

[1432] Generate the best response text.

[1433] The server sends this prompt to the OpenAI API and provides the generated reply text to the terminal. At the same time, it uses TextBlob to analyze the customer's emotional state and feeds the results back to the store clerk, allowing the store clerk to understand the customer's emotional state and take more appropriate action.

[1434] This system will enable teachers and store clerks to reduce their work hours and maximize the effectiveness of their communication.

[1435] The flow of the identification process in the application example 2 will be described with reference to FIG.

[1436] Step 1:

[1437] The server receives an inquiry from a parent or customer. The input is the inquiry content, and the output is to generate the inquiry content as a prompt sentence. Specifically, the server receives the inquiry content in text format and converts it into a prompt sentence.

[1438] Step 2:

[1439] The server sends the generated prompt text to the OpenAI API. The input is the prompt text, and the output is the reply text proposal generated by the AI. Specifically, the prompt text is sent as an API request, and the reply text proposal is received.

[1440] Step 3:

[1441] The server sends the received reply text suggestions to the terminal. The input is the reply text suggestions generated by the AI, and the output is the reply text suggestions displayed on the terminal. Specifically, the reply text suggestions are sent to the terminal so that the user can view them.

[1442] Step 4:

[1443] The server sends the query to the TextBlob library to analyze the emotional state of the parent or customer. The input is the query, and the output is the emotion analysis result. Specifically, the query is passed to TextBlob and the emotion score is obtained.

[1444] Step 5:

[1445] The server generates feedback based on the emotion analysis result and sends it to the terminal. The input is the emotion analysis result, and the output is a feedback message. Specifically, the server analyzes the emotion analysis result, generates an appropriate feedback message, and sends it to the terminal.

[1446] Step 6:

[1447] The terminal displays the reply draft and the feedback message received from the server to the user. The input is the reply draft and the feedback message, and the output is a screen display that can be viewed by the user. Specifically, the reply draft and the feedback message are displayed on the screen so that the user can confirm them.

[1448] Step 7:

[1449] The user checks the reply draft displayed on the terminal and makes corrections as necessary. The input is the reply draft, and the output is the corrected reply. Specifically, the user checks the reply draft and makes corrections as necessary.

[1450] Step 8:

[1451] The user sends the revised reply to the parent or customer. The input is the revised reply, and the output is the final reply sent to the parent or customer. Specifically, the revised reply is sent by pressing the send button.

[1452] Example 3

[1453] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1454] In the past, teachers had to spend a lot of time and effort writing replies to parents, and it was difficult for them to properly understand the emotional state of the parents. In addition, there was a lack of means to respond quickly and appropriately to the needs of parents, so there was a need for more efficient communication and more effective responses.

[1455] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1456] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using artificial intelligence that has learned the speaking skills of veteran teachers, a means for providing reply suggestions generated by the artificial intelligence, a means for analyzing the content of inquiries from parents and generating appropriate reply sentences, and a means for analyzing the emotional state of parents and providing feedback to teachers based on the results. This enables teachers to respond to inquiries from parents quickly and accurately, and realizes efficient communication and effective responses.

[1457] "Means for managing the communication book" refers to a system or software for recording and organizing communication between parents and teachers.

[1458] "Artificial intelligence that has learned the speaking techniques of veteran teachers" refers to an AI model that uses natural language processing technology to learn teachers' communication styles based on the reply sentences and feedback used in the past by experienced teachers.

[1459] "Means of instantly grasping parents' needs" refers to artificial intelligence technology that analyzes inquiries and requests from parents and quickly understands their content.

[1460] "Means for providing generated reply suggestions" refers to a system or interface for presenting reply suggestions generated by artificial intelligence to teachers.

[1461] "Means of analyzing the content of inquiries from parents and generating an appropriate reply message" refers to artificial intelligence technology for analyzing messages from parents and generating optimal reply messages based on their content.

[1462] "Means of analyzing the emotional state of parents and providing feedback to teachers based on the results" refers to an emotion analysis engine and feedback system for analyzing emotions from parents' messages and reporting the results to teachers.

[1463] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1464] The present invention provides a system for improving the efficiency of communication with parents and reducing the burden on teachers. A specific embodiment of this system will be described below.

[1465] Collecting and preprocessing training data

[1466] The server collects reply sentences used by teachers in the past and feedback from teachers. For this purpose, data sources such as the school's email system and chat logs are used. The collected data is converted into a data frame using Python's pandas library, and preprocessing is performed, such as filling in missing values ​​and deleting unnecessary data.

[1467] Building and training generative AI models

[1468] The server uses the preprocessed data to build a generative AI model. Specifically, it uses TensorFlow and PyTorch to design a neural network model and trains it on the teacher's reply sentences and feedback. A GPU-equipped server is used to train the model, and learning is carried out efficiently through batch processing.

[1469] Receiving inquiries from parents

[1470] The terminal receives inquiries and requests from parents. For example, when a parent sends an inquiry through the school's web portal or email, the content of the inquiry is received by the terminal. The terminal then sends the received inquiry to the server.

[1471] Analyzing inquiries and generating replies

[1472] The server inputs the received inquiry content into the generative AI model and generates an appropriate reply text. Specifically, the inquiry content is tokenized and input into the model. The model generates the optimal reply based on past learning data and sends the result to the terminal.

[1473] Emotion analysis using emotion engine

[1474] The server inputs messages from parents into an emotion engine to analyze their emotional state. Specifically, it uses IBM Watson's Natural Language Understanding and Microsoft Azure's Text Analytics to analyze the tone and keywords of the messages. The analysis results indicate the parent's emotional state, such as whether they are angry.

[1475] Providing feedback to teachers

[1476] The user (teacher) receives the reply text and the emotion analysis results provided by the server. The teacher can use this information to consider an appropriate response to the parent. For example, if the parent is angry, the teacher will try to respond calmly and politely.

[1477] Examples and prompts

[1478] Examples

[1479] The user (teacher) receives an inquiry from a parent saying, "Please tell me why my child's grades are dropping." The device sends this inquiry to the server. The server uses a generative AI model to generate a reply saying, "We apologize for causing you concern about your child's grades. We are considering individual measures based on recent test results and class behavior, and will discuss this in detail at the next interview." and sends it to the device. The user sends this reply to the parent.

[1480] At the same time, the server uses an emotion engine to analyze the parent's emotional state. The analysis result is that the parent is "worried." Based on this emotion analysis result, the user can respond more considerately.

[1481] Examples of prompt statements

[1482] "Generate an appropriate response based on the teacher's previous responses and feedback in response to a parent's inquiry such as 'Can you tell me why my child's grades are dropping?'"

[1483] In this way, the system reduces the burden on the teacher and realizes efficient communication. The flow of the specific process in the third embodiment will be described with reference to FIG.

[1484] Step 1:

[1485] The server collects reply sentences used by teachers in the past and feedback from teachers. For this purpose, data sources such as the school's email system and chat logs are used. The collected data is converted into a data frame using Python's pandas library, and preprocessing is performed, such as filling in missing values ​​and deleting unnecessary data. The input is the teacher's reply sentences and feedback, and the output is the preprocessed text data.

[1486] Step 2:

[1487] The server uses the preprocessed data to build a generative AI model. Specifically, it uses TensorFlow and PyTorch to design a neural network model and trains it on the teacher's reply sentences and feedback. A server equipped with a GPU is used to train the model, and training proceeds efficiently through batch processing. The input is the preprocessed text data, and the output is a trained generative AI model.

[1488] Step 3:

[1489] The terminal receives inquiries and requests from parents. For example, when a parent sends an inquiry through the school's web portal or email, the content of the inquiry is received by the terminal. The terminal sends the received inquiry to the server. The input is the inquiry content from the parent, and the output is the transmission of the inquiry data to the server.

[1490] Step 4:

[1491] The server inputs the received inquiry into the generative AI model and generates an appropriate reply. Specifically, the inquiry is tokenized and input into the model. The model generates an optimal reply based on past learning data and sends the result to the device. The input is the inquiry from the parent, and the output is the generated reply.

[1492] Step 5:

[1493] The server inputs messages from parents into an emotion engine to analyze their emotional state. Specifically, it uses IBM Watson's Natural Language Understanding and Microsoft Azure's Text Analytics to analyze the tone and keywords of the messages. The analysis results indicate the parent's emotional state, such as whether they are angry. The input is the message from the parent, and the output is the emotion analysis results.

[1494] Step 6:

[1495] The user (teacher) receives the reply text and emotion analysis results provided by the server. The teacher can consider an appropriate response to the parent based on this information. For example, if the parent is angry, the teacher will try to reply calmly and politely. The input is the reply text from the server and the emotion analysis results, and the output is an appropriate response to the parent.

[1496] (Application example 3)

[1497] Next, a description will be given of 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 glasses 214 will be referred to as a "terminal".

[1498] In the past, communication with parents required a lot of time and effort for teachers to respond individually, and it was difficult to respond quickly and appropriately. It was also difficult to properly grasp the emotional state of parents and respond accordingly. This made it difficult to gain the parents' peace of mind and trust, and reduced the effectiveness of communication.

[1499] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1500] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using AI that has learned the speaking skills of veteran teachers, a means for providing reply text suggestions generated by the AI, a means for analyzing the emotional state of parents using an emotion engine and providing feedback to teachers, a means for using the past response history and feedback of operators as learning data, and a means for providing the generated reply text and emotion analysis results to operators. This makes it possible to quickly and appropriately respond to the needs of parents and increase the sense of security and trust of parents.

[1501] A "means for managing the communication notebook" is a system that centrally manages information for communicating with parents and allows quick access to necessary information.

[1502] "AI that has learned the speaking techniques of veteran teachers" is an artificial intelligence that uses the response sentences and feedback used in the past by experienced teachers as learning data to generate appropriate response sentences in response to inquiries and requests from parents.

[1503] "Means of instantly grasping the needs of parents" refers to technology that analyzes inquiries and requests from parents and quickly understands their content.

[1504] "Means for providing generated reply suggestions" refers to a system that presents reply suggestions generated by AI to teachers or operators.

[1505] The "emotion engine" is a technology that analyzes the parent's emotional state and provides feedback based on the results.

[1506] "Means for analyzing the emotional state of parents and providing feedback to teachers" refers to a system that uses an emotion engine to analyze the emotions of parents and communicates the results to teachers.

[1507] "Method of using past operator response history and feedback as learning data" refers to technology that collects past response history and feedback as data and allows AI to learn based on that.

[1508] "Means of providing the generated reply text and emotion analysis results to the operator" refers to a system that presents the reply text generated by the AI ​​and the results of the emotion engine's analysis to the operator.

[1509] A system for carrying out this invention has the following configuration: The server includes means for managing a contact book for communicating with parents, means for instantly grasping the needs of parents using AI that has learned the speaking techniques of veteran teachers, means for providing reply sentence suggestions generated by the AI, means for analyzing the emotional state of parents using an emotion engine and providing feedback to teachers, means for using past response history and feedback from operators as learning data, and means for providing the generated reply sentences and emotion analysis results to the operator.

[1510] Hardware and Software Used

[1511] Hardware: Smartphones, servers

[1512] Software: OpenAI API, TextBlob

[1513] Data processing and calculation

[1514] 1. Ways to manage your contacts:

[1515] The server centrally manages the contact book for communicating with parents, allowing them to quickly access the necessary information.

[1516] 2. AI that learned the speaking techniques of veteran teachers:

[1517] The server uses the reply sentences and feedback used by veteran teachers in the past as learning data to generate appropriate reply sentences in response to inquiries and requests from parents. It utilizes generative AI models using the OpenAI API.

[1518] 3. How to instantly understand parents' needs:

[1519] The server analyzes inquiries and requests from parents and quickly understands their content, making it possible to instantly grasp the needs of parents.

[1520] 4. Means for providing generated reply suggestions:

[1521] The server then presents the reply text generated by the AI ​​to teachers and operators, enabling them to respond quickly and appropriately.

[1522] 5. Emotion Engine:

[1523] The server analyzes the parent's emotional state and provides feedback based on the results. TextBlob is used for emotion analysis.

[1524] 6. Means of analyzing parents' emotional state and providing feedback to teachers:

[1525] The server uses an emotion engine to analyze the parents' emotions and communicates the results to teachers, who can then consider appropriate responses.

[1526] 7. Using past operator responses and feedback as learning data:

[1527] The server collects past response history and feedback as data, and the AI ​​learns from that data, allowing it to generate more appropriate reply text.

[1528] 8. Means of providing generated reply text and sentiment analysis results to the operator:

[1529] The server presents the reply text generated by the AI ​​and the results of the emotion engine's analysis to the operator, enabling the operator to respond quickly and appropriately.

[1530] Examples

[1531] For example, if a parent asks, "The security alarm keeps ringing. What should I do?" the server processes the inquiry as follows:

[1532] 1. The server uses the OpenAI API to generate an appropriate reply based on the operator's past response history and feedback.

[1533] 2. The generated reply text is, "If the alarm continues to ring, first check the power supply. If the power supply is normal, check the sensor position."

[1534] 3. The server uses TextBlob to perform emotion analysis of the parent's inquiry and quantifies the parent's emotional state.

[1535] 4. The generated reply text and sentiment analysis results are provided to the operator.

[1536] Examples of prompt statements

[1537] Please generate appropriate responses to the following queries:

[1538] Q: My security alarm keeps going off, what should I do?

[1539] Previous reply: If the alarm keeps ringing, please check the power supply first. If the power supply is OK, please check the sensor position.

[1540] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1541] Step 1:

[1542] The server receives inquiries from parents.

[1543] Input: Parental inquiry (e.g. "The security alarm keeps going off. What should I do?")

[1544] Output: Text data of inquiry content

[1545] Step 2:

[1546] The server retrieves the operator's past response history and feedback from a database.

[1547] Input: A query to the database

[1548] Output: A dataset of historical interactions and feedback

[1549] Step 3:

[1550] The server uses the OpenAI API to generate an appropriate response to the parent's inquiry based on the past response history and feedback it has obtained.

[1551] Input: Text data of inquiry contents, past response history and feedback data set

[1552] Output: Generated reply text (e.g. "If the alarm keeps ringing, first check the power supply. If the power supply is normal, check the sensor position.")

[1553] Step 4:

[1554] The server uses TextBlob to perform sentiment analysis of the parent's inquiry.

[1555] Input: Text data of inquiry

[1556] Output: Sentiment analysis results (e.g. optimism, subjectivity)

[1557] Step 5:

[1558] The server provides the generated reply text and the sentiment analysis results to the operator.

[1559] Input: Generated reply text, sentiment analysis results

[1560] Output: Reply text and sentiment analysis results displayed on the operator's terminal

[1561] Step 6:

[1562] The operator takes appropriate action toward the parent based on the reply text and emotion analysis results provided by the server.

[1563] Input: Reply text and sentiment analysis results provided by the server

[1564] Output: Response and response to parents

[1565] Step 7:

[1566] The operator's response history and feedback are stored again in the database and used as learning data for the next call.

[1567] Input: Operator response history and feedback

[1568] Output: Response history and feedback data stored in a database

[1569] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1570] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generative AIs. Data generation model 58 is

[1571] , obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1572] Another example of generative AI is Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1573] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1574] [Third embodiment]

[1575] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1576] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1577] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[1578] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1579] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[1580] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1581] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1582] Fig. 6 shows an example of main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1583] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1584] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1585] In the headset type terminal 314, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1586] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1587] "Example 1"

[1588] The present invention is a system for managing a notebook for communicating with parents. This system uses AI that has learned the speaking techniques of veteran teachers to instantly grasp the needs of parents. Specifically, the AI ​​analyzes the contents of the notebook from parents and generates an appropriate reply proposal for that content. The generated reply proposal is designed to increase the parents' sense of security and trust, and teachers use it as a reference when replying to parents.

[1589] "Example 2"

[1590] As one aspect of the present invention, reply suggestions generated by AI shorten the work hours of teachers while maximizing the effectiveness of communication. Specifically, by using reply suggestions generated by AI, teachers can significantly reduce the time it takes to compose reply sentences. In addition, since the reply suggestions generated by AI have learned the speaking techniques of veteran teachers, their contents increase the teacher's trust in parents. This facilitates smooth communication between teachers and parents, improving the quality of education.

[1591] "Example 3"

[1592] As one aspect of the present invention, the AI ​​learns the speaking techniques of veteran teachers by using reply sentences used by teachers in the past and feedback from teachers as learning data. Specifically, the AI ​​uses this learning data to generate appropriate reply sentences for various inquiries and requests from parents. This allows teachers to instantly obtain reply sentences to meet the various needs of parents, realizing efficient communication.

[1593] The process flow of each embodiment will be described below.

[1594] "Example 1"

[1595] Step 1: The system receives the contents of the communication book from parents.

[1596] Step 2: The AI ​​analyzes the received content. For this analysis, an AI that has learned the speaking techniques of veteran teachers is used.

[1597] Step 3: The AI ​​instantly identifies the parent's needs and generates appropriate response suggestions.

[1598] Step 4: The generated reply proposal is provided to the teacher, who can use it to respond to the parent.

[1599] "Example 2"

[1600] Step 1: The teacher reviews the reply suggestions generated by the AI.

[1601] Step 2: Teachers can significantly reduce the time it takes to write responses.

[1602] Step 3: Communication between teachers and parents is smooth, improving the quality of education.

[1603] "Example 3"

[1604] Step 1: The AI ​​uses the reply sentences used by teachers in the past and feedback from teachers as learning data.

[1605] Step 2: Based on this learning data, the AI ​​generates appropriate reply sentences for various inquiries and requests from parents.

[1606] Step 3: Teachers can instantly receive response text to address various needs from parents, achieving efficient communication.

[1607] Example 1

[1608] Next, a description will be given of Example 1 of the embodiment 1. 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".

[1609] In the conventional communication book management system, teachers had to manually create replies to each communication with parents, which was time-consuming and labor-intensive. It was also sometimes difficult to properly understand the needs and feelings of parents and write replies that would increase their reassurance and trust. This resulted in issues such as a decrease in the effectiveness of communication and an increase in the workload of teachers.

[1610] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1611] In this invention, the server includes a means for managing a communication notebook for communicating with parents, a means for instantly grasping the needs of parents using artificial intelligence that has learned the speaking skills of veteran teachers, a means for providing reply suggestions generated by the artificial intelligence, a means for receiving the contents of the communication notebook from parents, a means for analyzing the received communication notebook contents using natural language processing technology, a means for generating appropriate reply suggestions based on the analysis results, a means for presenting the generated reply suggestions to the teacher's terminal, and a means for the teacher to create a final reply and send it to the parent's terminal. This makes it possible to appropriately grasp the needs and feelings of parents and to reply quickly and effectively.

[1612] "Guardian" refers to the parent or guardian of a child attending an educational institution, who is responsible for communicating and advising on the child's education and life.

[1613] A "communication notebook" is a means for parents and teachers to exchange information about their children's education and daily life, and is provided in either paper or digital form.

[1614] "Means of management" refers to a system or software that has the functionality to store, organize, search, and display the contents of the address book.

[1615] "Artificial intelligence" refers to computer programs and systems that use technologies such as machine learning and natural language processing to mimic human intelligence and perform certain tasks automatically.

[1616] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language, and is used to analyze and generate text data.

[1617] "Reply proposal" refers to a draft message generated by artificial intelligence to suggest an appropriate reply to a message from a parent.

[1618] "Teachers" refers to teachers and instructors who are responsible for educating children at educational institutions and who have the role of communicating with and consulting with parents.

[1619] A "terminal" is a device that a user uses to access and operate the system, and includes smartphones, tablets, PCs, etc.

[1620] "Means of analysis" refers to systems or software that have the function of analyzing the received communication book contents using natural language processing technology and extracting the needs and feelings of parents.

[1621] "Means for generating" refers to a system or software that has the functionality for generating appropriate reply suggestions based on the analysis results.

[1622] "Means of presentation" refers to a system or software that has the function of displaying the generated reply draft on the teacher's terminal so that the teacher can check and correct it.

[1623] "Means of sending" refers to a system or software that has the function of sending the final reply prepared by the teacher to the parent's device.

[1624] This invention is a system for managing a contact book for communicating with parents, and uses artificial intelligence that has learned the speaking skills of veteran teachers to instantly grasp the needs of parents and generate appropriate reply proposals. This system is implemented using the following hardware and software.

[1625] Hardware and Software Used

[1626] Server: Receives and analyzes the contents of the address book, and generates and sends reply proposals.

[1627] Devices: Devices used by parents and teachers (smartphones, tablets, computers, etc.).

[1628] Generative AI model: Analyzes the contents of the contact list using natural language processing technology and generates reply suggestions. Specifically, Google's BERT and OpenAI's GPT-4 are used.

[1629] Data processing and calculation

[1630] 1. Receiving communication from parents:

[1631] The server receives the contents of the address book sent by the parent from the device. The contents of the address book are stored in the server in text format.

[1632] 2. Analysis of address book contents:

[1633] The server then uses natural language processing technology to analyze the contents of the contact book received. A generative AI model is used for this analysis. The generative AI model analyzes the text data and extracts the needs and emotions of the parents.

[1634] 3. Generate reply suggestions:

[1635] The server generates appropriate reply suggestions based on the analysis results. The generative AI model generates responses that correspond to the needs and feelings of the parent.

[1636] 4. Response suggestions:

[1637] The server sends the generated reply draft to the teacher's terminal, where the teacher can check the reply draft and make corrections if necessary.

[1638] 5. Instructor creates final response:

[1639] The teacher uses the generated reply draft as a reference to create a final reply to the parent / guardian. The final reply is sent from the teacher's terminal to the parent / guardian's terminal via the server.

[1640] Examples

[1641] For example, if a parent writes in the communication book, "I'm worried that my child's grades at school have been dropping recently," the server receives this content and inputs the following prompt sentence into the generative AI model:

[1642] Example prompt:

[1643] "A parent writes: 'I'm worried that my child's grades at school have been dropping recently. Please generate an appropriate response to this.'"

[1644] Based on this prompt, the generative AI model generates the following reply suggestions:

[1645] "We understand that you are concerned about your child's grades. Please rest assured that we are prepared to monitor your child's progress and provide any support they may need, including individualized tutoring and additional learning resources."

[1646] Teachers will use these reply suggestions to create and send a final reply to parents.

[1647] The above is an embodiment of the present invention.

[1648] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1649] Step 1:

[1650] Receiving communication from parents

[1651] The server receives the contents of the address book sent by the guardian from the device. The input is a text message sent by the guardian using the device. The server stores this text message in a database. In concrete terms, when the guardian logs into the address book app on the device, enters a message and presses the send button, the server receives the message and stores it in the database.

[1652] Step 2:

[1653] Analysis of contact list contents

[1654] The server analyzes the received address book contents using natural language processing technology. The input is the text message saved in step 1. The server inputs this text data into a generative AI model to extract the guardian's needs and emotions. In concrete terms, the server inputs the text data into a generative AI model (e.g., GPT-4), and the model analyzes the text to extract the guardian's needs and emotions.

[1655] Step 3:

[1656] Generate reply suggestions

[1657] The server generates an appropriate reply draft based on the analysis results. The input is the needs and feelings of the parent extracted in step 2. The server inputs a prompt text to the generative AI model and generates a reply draft. In concrete terms, the server inputs the prompt text "Contents from the parent's message book: My child's grades at school have been dropping recently, and I'm worried. Please generate an appropriate reply draft in response to this" to the generative AI model, and the model generates an appropriate reply draft.

[1658] Step 4:

[1659] Response suggestions

[1660] The server sends the generated reply draft to the teacher's terminal. The input is the reply draft generated in step 3. The server sends this reply draft to the teacher's terminal so that the teacher can check it. In concrete terms, the server sends the generated reply draft to the teacher's terminal, and the teacher checks the reply draft on the terminal.

[1661] Step 5:

[1662] Instructor creates final reply

[1663] The teacher uses the generated reply draft as a reference to create a final reply to the parent. The input is the reply draft presented in step 4. The teacher checks the reply draft on the terminal, corrects it if necessary, and creates a final reply. In concrete terms, the teacher checks the reply draft on the terminal, corrects it if necessary, creates a final reply, and presses the send button.

[1664] Step 6:

[1665] Sending a final reply

[1666] The server sends the final reply created by the teacher to the parent's terminal. The input is the final reply created by the teacher in step 5. The server sends this final reply to the parent's terminal. In concrete terms, the server sends the final reply created by the teacher to the parent's terminal, and the parent checks the final reply on the terminal.

[1667] (Application example 1)

[1668] Next, a description will be given of 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 headset type terminal 314 will be referred to as a "terminal".

[1669] With the conventional contact book management system, communication with parents was not smooth, and it was difficult to quickly grasp the needs of parents. In addition, it was difficult for store staff to respond appropriately and quickly to inquiries from customers, making it an issue to improve customer satisfaction. This has led to a demand for more efficient work hours and maximizing communication effectiveness.

[1670] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1671] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents using a generative AI model that has learned the speaking skills of veteran teachers, a means for providing reply suggestions generated by the generative AI model, a means for analyzing the content of inquiries from customers and generating appropriate reply suggestions, and a means for displaying the generated reply suggestions to store staff. This makes it possible to quickly grasp the needs of parents and customers and provide appropriate replies. This allows for the shortening of work hours and the maximization of communication effectiveness.

[1672] "Parent" refers to the parent or guardian of a child attending an educational institution.

[1673] "Communication" refers to the act of transmitting information and emotions.

[1674] A "communication book" refers to a document or digital tool for exchanging information between parents and educational institutions.

[1675] "Means of management" refers to how information is organized, stored, and updated using systems and tools.

[1676] A "veteran teacher" refers to an educator with many years of experience and a high level of specialized knowledge.

[1677] "Speaking" refers to the skill of conveying information effectively using words.

[1678] A "generative AI model" refers to an algorithm that uses artificial intelligence techniques to generate an output for a specific task.

[1679] "Parent needs" refers to the demands and expectations that parents have.

[1680] "Means of instantaneous understanding" refers to a method for understanding information in a short amount of time and taking appropriate action.

[1681] "Response Draft" means a draft response to a particular inquiry or message.

[1682] "Means of providing" refers to the method of presenting the generated information to the user.

[1683] "Customer" refers to a person who purchases goods or services.

[1684] "Inquiry content" refers to information submitted by a customer or guardian as a question or request.

[1685] "Means of analysis" refers to a method for analyzing input information and understanding its meaning.

[1686] "Store staff" refers to employees working in physical stores.

[1687] "Means of display" refers to the way in which information is visually presented to the user.

[1688] The system for carrying out this invention is configured as follows: First, the server has a means for managing a contact book for communication with parents. This means provides a function for storing the contents of contact from parents in a digital format and updating them as necessary.

[1689] Next, the server uses a generative AI model that has learned the speaking skills of veteran teachers to instantly grasp the needs of parents. This generative AI model analyzes the content of messages from parents and generates appropriate reply proposals based on the content. This analysis and generation process uses artificial intelligence technologies such as OpenAI's API.

[1690] The server further includes a means for providing the generated reply draft, which is capable of presenting the generated reply draft to a staff member of the educational institution so that the staff member can use the reply draft to the parent / guardian as a reference.

[1691] The server also has a means for analyzing the content of customer inquiries and generating appropriate reply suggestions. This means is used to support customer service in physical stores. It receives the content of customer inquiries as input, analyzes them using a generative AI model, and generates appropriate reply suggestions.

[1692] Finally, the server has a means for displaying the generated reply proposal to the store staff. This means displays the generated reply proposal on a terminal such as a smartphone or tablet, enabling the store staff to respond to the customer by referring to it.

[1693] As a concrete example, if a customer inquires, "Please tell me how to return an item," the server inputs the inquiry into the generative AI model and generates an appropriate reply proposal. The generated reply proposal is, "We will guide you through how to return the item. First, please prepare your purchase receipt. Then, bring it to the store together with the item, and a staff member will assist you." This reply proposal is displayed on the terminal of the store staff, who use it as a reference when responding to the customer.

[1694] The following is an example of a prompt sentence:

[1695] Customer Question: How do I return an item?

[1696] Please reply like a veteran staff member.

[1697] In this way, it becomes possible to quickly grasp the needs of parents and customers and provide appropriate responses, thereby reducing work time and maximizing communication effectiveness.

[1698] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1699] Step 1:

[1700] The user (parent or customer) enters the inquiry.

[1701] Input: Enquiry content (text format)

[1702] Specific operation: A user uses a smartphone or tablet application to input the content of an inquiry. For example, the user inputs, "Please tell me how to return a product."

[1703] Step 2:

[1704] The server receives the query and generates a prompt to input to the generative AI model.

[1705] Input: Enquiry content (text format)

[1706] Output: Prompt statement (text format)

[1707] Specific operation: The server receives the inquiry and converts it into a prompt sentence in a format suitable for the generative AI model. For example, it generates a prompt sentence such as "Customer inquiry: How do I return the product? Please reply like a veteran staff member."

[1708] Step 3:

[1709] The server uses a generative AI model to generate reply suggestions based on the prompt.

[1710] Input: Prompt sentence (text format)

[1711] Output: Reply proposal (text format)

[1712] Specific operation: The server calls the generative AI model (e.g., OpenAI's API) and provides the prompt as input. The generative AI model analyzes the prompt and generates an appropriate reply proposal. For example, it generates a reply proposal that reads, "We will guide you through how to return the product. First, please prepare your purchase receipt. Then, please bring it to the store together with the product, and a staff member will assist you."

[1713] Step 4:

[1714] The server transmits the generated reply text proposal to the terminal.

[1715] Input: Reply proposal (text format)

[1716] Output: Reply proposal (text format)

[1717] Specific operation: The server sends the generated reply text suggestions to the user's terminal, which receives and displays the reply text suggestions.

[1718] Step 5:

[1719] The device displays reply suggestions to the user.

[1720] Input: Reply proposal (text format)

[1721] Output: Displayed reply suggestions (visual display)

[1722] Specific operation: The terminal displays the received reply message on the screen so that the user can confirm it. For example, the following message may be displayed on the smartphone screen: "We will guide you through how to return the product. First, please prepare your purchase receipt. Then, bring it together with the product to the store and a staff member will assist you."

[1723] Step 6:

[1724] The user refers to the generated reply proposal and takes appropriate action with respect to the parent or customer.

[1725] Input: Response suggestions displayed (visual display)

[1726] Output: User's response action

[1727] Specific operation: The user (staff member of the educational institution or the store staff member) responds appropriately to the guardian or customer by referring to the displayed reply text suggestions. For example, the store staff member may explain to the customer, "We will explain how to return the product. First, please prepare the receipt from the time of purchase. Then, please bring it together with the product to the store, and the staff member will assist you."

[1728] Example 2

[1729] Next, a second embodiment of the second form will be described. 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".

[1730] In traditional educational settings, it took a lot of time and effort for teachers to communicate smoothly with parents. In particular, writing replies to emails from parents was a heavy burden for teachers. In addition, the quality of the replies was directly linked to the parents' trust and sense of security, so the content of the replies was required to be of high quality. This increased teachers' work hours and could have an impact on the quality of education.

[1731] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1732] In this invention, the server includes a means for sending emails received by a user to the server, a means for generating a prompt sentence for inputting the email received by the server to the generative AI model, and a means for the server to input the prompt sentence to the generative AI model and generate a reply sentence proposal. This enables teachers to quickly generate high-quality reply sentences to emails from parents. This can significantly reduce the teacher's work time and maximize the effectiveness of communication with parents.

[1733] "Guardian" refers to the parent or guardian of a child or student attending an educational institution.

[1734] "Communication" refers to the exchange of information between teachers and parents.

[1735] A "communication notebook" refers to a means for teachers and parents to share information about children's and students' learning and living situations.

[1736] "Means of management" refers to the method or system for organizing the contents of the contact book and properly storing and updating it.

[1737] A "veteran teacher" is a teacher who has many years of teaching experience and has excellent leadership and communication skills.

[1738] "Speaking" refers to the techniques and methods of effectively conveying information using words.

[1739] "Artificial intelligence" refers to technology that enables computer systems to mimic human intelligence and perform learning and reasoning.

[1740] "Needs" refers to the demands and expectations that parents have.

[1741] "Means of instant identification" refers to methods and systems for quickly understanding parents' needs and responding appropriately.

[1742] "Response draft" refers to a draft response to inquiries or requests from parents.

[1743] "Means for providing" refers to a method or system for presenting the generated reply suggestions to the user.

[1744] "User" refers to the teacher who uses this system.

[1745] "Server" refers to a computer system for processing and storing data.

[1746] "Generative AI model" refers to a model for generating text using artificial intelligence technology.

[1747] A "prompt sentence" refers to an instruction sentence to be input into a generative AI model.

[1748] "Terminal" refers to a device such as a computer or smartphone used by a user.

[1749] "Means for modification" refers to a method or system that allows a user to edit or modify the generated reply proposal.

[1750] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1751] The present invention is a system for enabling teachers to smoothly communicate with parents, and generates reply proposals using artificial intelligence technology. A specific embodiment of this system is described below.

[1752] Hardware and Software Used

[1753] The system uses the following hardware and software:

[1754] Server: A computer system for processing and storing data. For example, a cloud server or an on-premise server is used.

[1755] Terminal: A device such as a computer or smartphone used by a user. Examples include PCs, tablets, and smartphones.

[1756] Generative AI model: A model for generating text using artificial intelligence techniques, such as OpenAI's GPT-4.

[1757] System Operation

[1758] After receiving the email from the parent, the user (teacher) opens a dedicated web application, copies and pastes the received email, and then clicks the "Send" button to send the email to the server.

[1759] The server analyzes the content of the received email and generates a prompt to input to the generative AI model. For example, it generates the following prompt:

[1760] "Parents emailed me saying: 'I'm worried about my child's grades. How can I help?'"

[1761] The server inputs the generated prompt sentence into the generative AI model. The generative AI model generates appropriate reply sentence suggestions based on the prompt sentence. For example, it generates reply sentence suggestions like the following:

[1762] "Thank you for your support. I understand that you are worried about your child's grades. First of all, it is important to create a good learning environment at home. Specifically, I recommend that you set a time each day to study and create an environment where your child can concentrate. Also, please rest assured that we will be providing comprehensive support at school."

[1763] The server then sends the generated reply suggestions to the user's device, where the user can review the reply suggestions through a dedicated interface and make corrections as necessary, for example by adding additional information tailored to the specific situation or fine-tuning the wording.

[1764] The user then sends the revised reply to the parent, thereby achieving quick and effective communication.

[1765] Examples

[1766] For example, if a user receives an email from a parent saying, "I'm worried about my child's grades. How can I help them?", the user sends this email to the server, which generates the following prompt:

[1767] "Parents emailed me saying: 'I'm worried about my child's grades. How can I help?'"

[1768] Based on this prompt, the generative AI model generates the following reply suggestions:

[1769] "Thank you for your support. I understand that you are worried about your child's grades. First of all, it is important to create a good learning environment at home. Specifically, I recommend that you set a time each day to study and create an environment where your child can concentrate. Also, please rest assured that we will be providing comprehensive support at school."

[1770] The user checks the reply draft, modifies it as necessary, and then sends it to the guardian. Through this process, the user can quickly generate a high-quality reply, enabling smooth communication with the guardian.

[1771] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1772] Step 1:

[1773] The user receives an email from a parent.

[1774] Specific operation: A user (teacher) receives an email from a parent in his / her own email account. For example, a parent may receive an email saying, "I'm worried about my child's grades. How can I support him / her?"

[1775] Enter: Email from parent.

[1776] Output: The content of the received email.

[1777] Step 2:

[1778] The user sends the received email to the server.

[1779] Specific operation: A user opens a dedicated web application, copies and pastes the received email, and then clicks the "Send" button to send the email to the server.

[1780] Input: The content of the received email.

[1781] Output: The content of the email sent to the server.

[1782] Step 3:

[1783] The server generates a prompt sentence to input the received email into the generative AI model.

[1784] Specific operation: The server analyzes the contents of the received email and generates a prompt sentence to input to the generative AI model. For example, it creates a prompt sentence such as "Contents of email from parent: 'I'm worried about my child's grades. How can I support him?'"

[1785] Input: The content of the email sent to the server.

[1786] Output: The generated prompt statement.

[1787] Step 4:

[1788] The server inputs the prompt text into the generative AI model and generates reply text suggestions.

[1789] Specific operation: The server inputs the generated prompt sentence into a generative AI model (for example, OpenAI's GPT-4). The generative AI model generates an appropriate reply sentence proposal based on the prompt sentence. For example, it generates a reply sentence proposal that reads, "Thank you for your support. I understand that you are worried about your child's grades. First of all, it is important to create a good learning environment at home. Specifically, I recommend that you decide on a daily study time and create an environment where your child can concentrate. We will also provide comprehensive support at school, so please rest assured."

[1790] Input: The generated prompt statement.

[1791] Output: The generated reply suggestions.

[1792] Step 5:

[1793] The server transmits the generated reply sentence proposal to the user's terminal.

[1794] Specific operation: The server sends the generated reply text suggestions to the user's terminal, and the user can check the reply text suggestions through a dedicated interface.

[1795] Input: The generated reply suggestion.

[1796] Output: Reply proposal sent to the user's device.

[1797] Step 6:

[1798] The user reviews the reply proposal and modifies it if necessary.

[1799] What happens: The user reviews the reply text sent by the server and makes corrections as necessary, for example adding additional information appropriate to the specific situation or fine-tuning the wording.

[1800] Input: A reply proposal sent to the user's device.

[1801] Output: The revised reply proposal.

[1802] Step 7:

[1803] The user sends the corrected reply text to the parent.

[1804] Specific operation: The user sends the revised reply to the parent, thereby achieving quick and effective communication.

[1805] Input: Revised reply proposal.

[1806] Output: The reply sent to the parent.

[1807] (Application example 2)

[1808] Next, a description will be given of 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 headset type terminal 314 will be referred to as a "terminal".

[1809] In the conventional system, teachers and staff had to spend a lot of time communicating with parents and customers, which led to a decrease in work efficiency. In addition, the quality of the replies was not consistent, which led to a lack of trust and security. This could lead to a decrease in the quality of education and customer satisfaction.

[1810] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1811] In this invention, the server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents by an AI that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the AI, a means for the AI ​​to automatically generate reply proposals in response to inquiries from customers, a means for the AI ​​to provide highly reliable replies that have learned the responses of veteran staff, and a means for facilitating communication with customers and improving customer satisfaction. This makes it possible to reduce the work hours of teachers and staff and maximize the effectiveness of communication.

[1812] A "communication notebook" is a ledger or digital tool for recording and managing information for communicating with parents.

[1813] A "veteran teacher" refers to an educator with many years of experience and a high level of specialized knowledge.

[1814] "Speaking skills" refers to the use of words and expression techniques for effective communication.

[1815] "AI" is an abbreviation for artificial intelligence, a technology that uses machine learning and natural language processing to mimic human intelligence.

[1816] "Parent needs" refers to the information and support that parents seek in education and child-rearing.

[1817] "Response suggestions" refers to documents that suggest appropriate responses to specific inquiries or situations.

[1818] "Customer" refers to a person who purchases or uses a product or service.

[1819] An "Inquiry" is a question or request made for information or assistance.

[1820] "Veteran staff" refers to employees with many years of experience and high levels of specialized knowledge.

[1821] "Reliability" refers to information and services being accurate and functioning as expected.

[1822] "Customer satisfaction" refers to the degree of satisfaction a customer feels toward a product or service.

[1823] "Task time" refers to the time spent performing a particular task.

[1824] "Communication effectiveness" is an indicator that shows how effectively information is transmitted and communication is carried out.

[1825] The system for carrying out this invention is composed of three main components: a server, a terminal, and a user. The server includes a means for managing a contact book for communicating with parents, a means for instantly grasping the needs of parents by an AI that has learned the speaking skills of veteran teachers, a means for providing reply proposals generated by the AI, a means for an AI to automatically generate reply proposals in response to inquiries from customers, a means for an AI to provide reliable replies that have learned the responses of veteran staff, and a means for facilitating communication with customers and improving customer satisfaction.

[1826] Hardware and Software Used

[1827] Hardware: Smartphones, servers

[1828] Software: Python, OpenAI API (GPT-3)

[1829] Data processing and calculation

[1830] The server first receives an inquiry from a parent or customer. It then generates a prompt based on the content of the inquiry. This prompt is input into an AI model that has learned the speaking skills of veteran teachers and staff. The AI ​​model generates an appropriate reply proposal based on the input prompt. The generated reply proposal is sent from the server to the terminal and provided to the user.

[1831] Examples

[1832] For example, if a customer asks "How do I return an item?" the server might generate the following prompt:

[1833] Customer Question: How do I return an item?

[1834] Please reply like a veteran staff member.

[1835] If you feed this prompt into OpenAI's GPT-3 API, it will generate the following reply:

[1836] Hello, customer. We would like to inform you of the return method for your product. First, please fill in the return form that we sent you together with the product and enclose it with the product. After that, please send it to the specified return address and we will proceed with the return procedure. If you have any questions, please feel free to contact us.

[1837] The reply proposals generated in this way are sent from the server to the terminal and provided to the user, which reduces the work time of teachers and staff and maximizes the effectiveness of communication.

[1838] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1839] Step 1:

[1840] The server receives inquiries from parents and customers.

[1841] Input: Inquiries from parents and customers

[1842] Output: Text data of the inquiry

[1843] Specific operation: The server saves the content of inquiries received through interfaces such as inquiry forms and emails as text data.

[1844] Step 2:

[1845] The server generates a prompt sentence based on the received query.

[1846] Input: Text data of inquiry

[1847] Output: Prompt statement

[1848] Specific operation: Based on the inquiry content, the server generates a prompt sentence in the form of "Customer inquiry: [Inquiry content] Please reply like an experienced staff member."

[1849] Step 3:

[1850] The server sends the generated prompt text to OpenAI's GPT-3 API.

[1851] Input: prompt statement

[1852] Output: Request to the GPT-3 API

[1853] What happens: The server formats the generated prompt as an API request and sends it to OpenAI's GPT-3 API.

[1854] Step 4:

[1855] The server receives the reply sentence proposal from the GPT-3 API.

[1856] Input: A request to the GPT-3 API

[1857] Output: Reply proposal

[1858] Specific operation: The server receives the reply sentence proposal returned from the GPT-3 API and stores it as text data.

[1859] Step 5:

[1860] The server transmits the generated reply text proposal to the terminal.

[1861] Input: Reply proposal

[1862] Output: Data sent to the terminal

[1863] Specific operation: The server converts the reply text proposal into an appropriate format and sends it to the user's device.

[1864] Step 6:

[1865] The terminal displays the received reply sentence suggestions to the user.

[1866] Input: Data to send to the terminal

[1867] Output: Reply suggestions shown to the user

[1868] Specific operation: The device displays the received reply proposal on the screen for the user to review.

[1869] Step 7:

[1870] The user checks the displayed reply draft and, if necessary, modifies or sends it.

[1871] Input: A suggested reply that will be displayed to the user

[1872] Output: revised reply proposal or sent reply

[1873] Specific behavior: The user reviews the proposed reply, makes corrections if necessary, and then submits it as the final reply.

[1874] Example 3

[1875] Next, a third embodiment of the third embodiment will be described. 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".

[1876] In the past, teachers had to spend a lot of time writing replies, making it difficult to communicate efficiently. In addition, because the quality of the replies depended on the teacher's experience and skills, parents were often unable to feel reassured or trusted by the replies. This resulted in an increase in the teacher's workload and a decrease in the effectiveness of communication.

[1877] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1878] In this invention, the server includes a means for collecting reply sentences and feedback used by teachers in the past and storing them in a database, a means for training a generative AI model using the collected data, and a means for generating appropriate reply sentences using the generative AI model. This enables teachers to quickly obtain appropriate reply sentences in response to inquiries and requests from parents.

[1879] A "communication book" is a recording medium for communication between parents and teachers, and may include paper or electronic media.

[1880] "Artificial intelligence" is the technology that enables computer systems to mimic human intelligence and learn, reason, and self-correct.

[1881] A "generative AI model" is a type of artificial intelligence that has the ability to generate new data based on a specific dataset.

[1882] A "database" is a system for efficiently storing, managing, and searching data.

[1883] An "interface" is the means by which a user interacts with a system, including input forms and graphical user interfaces (GUIs).

[1884] A "server" is a computer system that provides services to other computers over a network.

[1885] A "terminal" is a computer device that is directly operated by a user, and includes a PC, tablet, smartphone, etc.

[1886] An "inquiry" refers to a question or request that a parent or guardian makes to a teacher.

[1887] A "reply letter" is a letter that a teacher sends to a parent / guardian to answer or provide information.

[1888] "Feedback" refers to evaluations and opinions received from teachers regarding past communication.

[1889] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1890] The present invention provides a system for improving the efficiency of communication with parents and reducing the workload of teachers. A specific embodiment of this system will be described below.

[1891] Hardware and software used

[1892] Hardware: Servers, terminals (PCs, tablets, smartphones)

[1893] Software: Generative AI models (e.g. OpenAI GPT-4), database management systems (e.g. MySQL)

[1894] Server Roles

[1895] The server collects teachers' past reply phrases and feedback and stores them in a database. Specifically, the server extracts data from teachers' email accounts and the school's communication system and stores it in a MySQL database. Next, the server uses the collected data to train a generative AI model (e.g., OpenAI GPT-4). The generative AI model learns teachers' speaking skills and reply patterns and has the ability to generate appropriate reply phrases to inquiries from parents.

[1896] Terminal Roles

[1897] The terminal provides an interface for teachers to input questions and requests from parents. Specifically, the terminal displays an input form through a web browser or a dedicated app, and teachers input the questions into the form. The input data is sent to the server as an HTTP request.

[1898] User Roles

[1899] The user (teacher) uses the device to input inquiries and requests from parents. Once input is complete, the device sends the data to the server. The server uses a genera...

Claims

1. A means of managing a communication notebook for communicating with parents; A means for receiving the contents of the communication book sent by the guardian; means for analyzing an emotional state of the guardian using an emotion engine based on the contents of the contact book; A means for generating a reply draft using a prompt sentence instructing the generation of a reply draft based on the contents of the communication book and the emotional state of the guardian and a generative AI model; A means for transmitting the generated reply draft to a teacher's terminal; A system including:

2. The generating means generates a plurality of reply sentence suggestions; The transmitting means transmits the generated reply sentence suggestions to a teacher's terminal; The system according to claim 1 , further comprising a means for accepting an operation of selecting one of the generated reply drafts from the teacher's terminal, and recording the selected reply draft in the communication notebook.

3. The system described in claim 2, wherein the recording means accepts, from the teacher's terminal, an operation of selecting one of the generated reply drafts and an operation of editing the selected reply draft, and records the selected, edited reply draft in the communication notebook.

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