system

Abstract

We provide the system. [Solution] A system that includes means for using generative AI to point out typographical errors in the text being sent and provide services such as easy-to-understand advice and text rewriting, and means for displaying the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In Internet search tools, emails, and messenger apps, there are problems such as the sender sending a text containing typos and the recipient spending time grasping the key points from a long text.

Means for Solving the Problems

[0005] A system has been developed that uses generative AI to point out typos in the text input by the sender and provides easy-to-understand advice and text rewriting services, and automatically extracts key points, deadlines, and information of related parties based on the content of the text viewed by the recipient and displays them in a pop-up manner. As a result, the sender can send a text that is easy to understand and has no typos, and the recipient can quickly grasp the key points of the text. [Brief explanation of the drawing]

[0006] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Embodiment 1 of Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2 of Embodiment 2. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Form Example 2. [Figure 15]It is a sequence diagram showing the processing flow of the data processing system in Example 3 of Form Example 3. [Figure 16] It is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Form Example 3. [Figure 17] It is a sequence diagram showing the processing flow of the data processing system in Example 1 of Form Example 1 when combined with an emotion engine. [Figure 18] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. [Figure 19] It is a sequence diagram showing the processing flow of the data processing system in Example 2 of Form Example 2 when combined with an emotion engine. [Figure 20] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 of Form Example 2 when combined with an emotion engine. [Figure 21] It is a sequence diagram showing the processing flow of the data processing system in Example 3 of Form Example 3 when combined with an emotion engine. [Figure 22] It is a sequence diagram showing the processing flow of the data processing system in Application Example 3 of Form Example 3 when combined with an emotion engine. [Figure 23] It is a sequence diagram showing the processing flow of the data processing system in other embodiments.

Embodiments for Carrying Out the Invention

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

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

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

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

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

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0014] [First Embodiment]

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

[0016] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0019] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0023] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

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

[0027] "Example of form 1"

[0028] One embodiment of this system is one that can be integrated into internet search tools, email, and messenger applications. This system uses generative AI to analyze the text entered by the sender and points out typos and grammatical errors. Furthermore, it provides advice to improve the clarity of the text and suggests rewriting it as needed. Specifically, if the sender enters "Please submit the report by tomorrow," the generative AI will suggest rewriting it to a more polite expression such as "Please submit the report by tomorrow."

[0029] "Example of form 2"

[0030] Furthermore, for recipients, there is a feature that analyzes the content of received messages, automatically extracts key points, deadlines, and information about stakeholders, and displays them in a pop-up window. Specifically, if a recipient receives a message that says, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the system will display a pop-up window with the following information: "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C." This allows the recipient to quickly grasp the main points of the message.

[0031] "Example of form 3"

[0032] Furthermore, for recipients, there is a feature that analyzes the content of received messages, automatically extracts key points, deadlines, and information about stakeholders, and displays them in a pop-up window. Specifically, if a recipient receives a message that says, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the system will display a pop-up window with the following information: "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C." This allows the recipient to quickly grasp the main points of the message.

[0033] The following describes the processing flow for each example of the form.

[0034] "Example of form 1"

[0035] Step 1: The sender types the message into an internet search tool, email, or messenger app.

[0036] Step 2: The generative AI analyzes the input text and points out typos and grammatical errors.

[0037] Step 3: The generative AI provides advice to improve the clarity of the text.

[0038] Step 4: If necessary, the generative AI will suggest rewriting the text.

[0039] "Example of form 2"

[0040] Step 1: The recipient receives the message.

[0041] Step 2: The system analyzes the content of the received text.

[0042] Step 3: The system automatically extracts key points, deadlines, and information about stakeholders.

[0043] Step 4: The system will display the extracted information in a pop-up window.

[0044] (Example 1)

[0045] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0046] In modern communication, misunderstandings often arise due to typographical errors, grammatical mistakes, and unclear writing. Furthermore, long texts can bury key points and important information, making them difficult for recipients to understand. There is a need to address these challenges and achieve more effective communication.

[0047] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0048] In this invention, the server includes means for pointing out typographical errors and grammatical errors in transmitted text using generative artificial intelligence and providing services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts on a display device to facilitate the recipient's understanding; and means for analyzing text input by the user and using generative artificial intelligence to detect typographical errors and suggest improvements to the text. This makes it possible to improve the quality of text and clarify information.

[0049] "Generative artificial intelligence" is a technology that uses natural language processing to analyze text and point out typos and grammatical errors, as well as suggest improvements to the text.

[0050] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[0051] "Easy-to-understand advice" refers to suggestions that make the content of a document clearer and easier to understand, thereby facilitating the smooth transmission of information to the recipient.

[0052] A "rewriting service" is a function that improves the expression of a text and corrects it to a more appropriate form.

[0053] A "display device" is a device used to visually display information, and is used by recipients to confirm that information.

[0054] "Key points" refer to the particularly important parts of a text or piece of information, representing the main content that the recipient should understand.

[0055] A "deadline" refers to the date on which a specific action or event should take place, and is important information in schedule management.

[0056] "Stakeholders" refers to individuals or organizations related to a particular document or piece of information, and are those that the recipient of the information should be aware of.

[0057] "Analysis" is the process of thoroughly examining text and data to understand their structure and meaning.

[0058] The following systems are conceivable as embodiments for carrying out this invention.

[0059] The server uses generative artificial intelligence to analyze the text entered by the user. This analysis utilizes natural language processing technology to detect typos and grammatical errors and suggest improvements to the text. Specifically, a general-purpose natural language processing engine can be used as the generative AI model. For example, open-source natural language processing libraries or commercial AI platforms can be used.

[0060] The terminal sends the text entered by the user to the server. A secure communication protocol is used to transmit the data and protect the user's privacy. The server inputs the received text into a generation AI model to create a prompt. An example of a prompt is: "Please analyze the following text, identify any typos or grammatical errors, and provide suggestions for improvement:"

[0061] The generative AI model analyzes the input text and not only points out typos and grammatical errors, but also provides advice to improve the clarity of the writing. For example, if a user inputs "Please submit the report by tomorrow," the generative AI model will suggest rewriting it into a more polite expression such as "Please submit the report by tomorrow."

[0062] In this way, users can improve the quality of their writing and achieve unambiguous communication by utilizing generative artificial intelligence.

[0063] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0064] Step 1:

[0065] Users input text through internet search tools, email, or messenger apps. This entered text becomes the data subject to typographical error checking and suggestions for improving the text.

[0066] Step 2:

[0067] The terminal sends the text entered by the user to the server. This data is transmitted using a secure communication protocol. The input is the user's text, and the output is the secure transmission of data to the server.

[0068] Step 3:

[0069] The server inputs the received text into the generative AI model. Specifically, it creates a prompt message and inputs it to the generative AI model in the format of "Please analyze the following text, point out any typos or grammatical errors, and provide suggestions for improvement:". The input is the user's text, and the output is the prompt message to the generative AI model.

[0070] Step 4:

[0071] The generative AI model analyzes text based on the input prompt sentence. It detects typos and grammatical errors and generates advice and rewriting suggestions to improve the clarity of the text. The input is the prompt sentence, and the output is the analysis result and improvement suggestions.

[0072] Step 5:

[0073] The server sends the analysis results and improvement suggestions obtained from the generated AI model to the terminal. The input is the output of the generated AI model, and the output is the transmission of data to the terminal.

[0074] Step 6:

[0075] The terminal displays analysis results and improvement suggestions received from the server to the user. The user can then use this information to revise their text. The input is data from the server, and the output is information displayed to the user.

[0076] (Application Example 1)

[0077] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0078] In modern communication, typographical errors and inappropriate expressions can hinder information transmission. Furthermore, in customer service roles at physical stores, the ability to instantly select appropriate expressions during conversations with customers is crucial, but there is a lack of technology to support this. To address these challenges, a system is needed that analyzes written and spoken content in real time and suggests appropriate expressions.

[0079] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0080] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services such as easy-to-understand advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and a server that uses speech recognition technology to convert speech into text, generates appropriate expressions using generative AI, and presents them on a display device. This makes it possible to analyze the content of text and audio in real time and suggest appropriate expressions.

[0081] "Generative AI" is an artificial intelligence technology that analyzes input data and generates appropriate sentences and expressions through natural language processing.

[0082] "Typographical errors" refer to mistakes or omissions in text, and are factors that hinder the accurate transmission of information.

[0083] A "pop-up display" refers to a window or message that temporarily appears on the screen to highlight information within the user interface.

[0084] "Speech recognition technology" is a technology that analyzes speech as a digital signal and converts it into corresponding text data.

[0085] A "display device" is hardware used to visually present generated information or data, and includes displays and screens.

[0086] The system for implementing this invention involves a server and a terminal working in conjunction. The server uses generative AI to identify typos and grammatical errors in transmitted text, and provides clearer advice and rewrites the text. Furthermore, it displays key points, deadlines, and relevant parties in pop-ups for longer texts to facilitate the recipient's understanding.

[0087] The device uses speech recognition technology to convert speech into text, generates appropriate expressions using generative AI, and displays them on a display device. Specifically, the generated information is visually presented to the user using a display device such as smart glasses or a smartphone.

[0088] For example, in a physical store, if a user asks, "Does this product come in other colors?", the terminal uses speech recognition technology to convert this question into text and send it to the server. The server then uses generative AI to generate an appropriate response, such as, "This product is available in other colors. Which color would you prefer?", and displays it on the terminal's display.

[0089] An example of a prompt is, "A customer is asking about the color of a product. Please suggest a polite response." By inputting this prompt into a generative AI, an appropriate response will be generated.

[0090] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0091] Step 1:

[0092] The device acquires the user's voice input through the microphone. The input is the voice data spoken by the user. The device converts this voice data into text data using speech recognition technology (e.g., Google® Cloud Speech-to-Text). The output is text data representing the user's speech as a string of characters.

[0093] Step 2:

[0094] The terminal sends the converted text data to the server. The server inputs the received text data into a generative AI model (e.g., OpenAI®'s GPT-3®). The input is text data representing the user's utterance. The server uses the generative AI model to perform data calculations to generate an appropriate response. The output is the text data of the generated appropriate response.

[0095] Step 3:

[0096] The server sends the generated response as text data to the terminal. The terminal displays the received response on a display device (e.g., smart glasses or smartphone display). The input is the text data of the response sent from the server. The terminal processes the data to present the information visually to the user and provides a response that is displayed to the user as output.

[0097] Step 4:

[0098] The user confirms the displayed response and continues the conversation as needed. The user's confirmation triggers the next voice input, and the process from step 1 is repeated. The input is the displayed response, and the output is the user's understanding and next action.

[0099] (Example 2)

[0100] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0101] In modern information and communication, it is difficult for recipients to quickly and accurately understand lengthy information. Furthermore, while it is crucial for senders to provide clear information free from typos and grammatical errors, doing so manually is time-consuming and laborious. To address these challenges, a system is needed that automatically extracts key points, deadlines, and stakeholders, and presents them clearly to the recipient.

[0102] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0103] In this invention, the server includes means for pointing out typographical errors in transmitted information using generative artificial intelligence and providing easy-to-understand advice and information rewriting services; means for displaying the main points, deadlines, and relevant parties of long information on a display device to facilitate the recipient's understanding; and means for analyzing received information and automatically extracting information on main points, deadlines, and relevant parties. As a result, the recipient can quickly grasp the main points of the information, and the sender can provide clear information free from typographical errors.

[0104] "Generative artificial intelligence" is a type of artificial intelligence that uses natural language processing technology to analyze and generate information.

[0105] "Typographical errors" refer to incorrectly written or missing characters in information.

[0106] "Advice" refers to instructions or suggestions provided to improve or facilitate understanding of information.

[0107] "Rewriting information" is the act of modifying information to make its content clearer and easier to understand.

[0108] A "key point" refers to the particularly important or core content of information.

[0109] "Deadline" refers to a specific date, time, or period related to information.

[0110] "Stakeholders" refers to individuals or organizations related to the information.

[0111] A "display device" is a device or interface used to present information visually.

[0112] "Analysis" is the process of breaking down information and understanding its structure and meaning.

[0113] "Extraction" is the act of taking out specific elements or data from information.

[0114] As an embodiment of this invention, the following system is constructed.

[0115] The server analyzes the received information using a generative AI model. A model that utilizes natural language processing technology is suitable for this generative AI model, and specifically, OpenAI's GPT model can be used. The server inputs the received information into the generative AI model and gives it a prompt message such as, "Extract the main points, deadlines, and stakeholders from this text." Based on this prompt message, the generative AI model analyzes the information and extracts the main points, deadlines, and stakeholders.

[0116] The terminal receives analysis results sent from the server and presents them to the user via a display device. Specifically, it uses a pop-up display to visually show information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C." This allows the user to quickly grasp the important parts of the received information.

[0117] Users can provide clear instructions as prompts to input into the generating AI model. For example, by using a prompt such as, "Extract the main points, deadlines, and stakeholders from this document," the system can efficiently extract and provide information to the user. In this way, recipients of the information can quickly understand the important information, and senders can provide clear information free from typos and grammatical errors.

[0118] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0119] Step 1:

[0120] The user receives information via email or messaging apps. The device detects this received information and prepares to send it to the server. The input is the received information, and the output is the transfer of information to the server. Specifically, the device sends information to the server triggered by the receipt of a new message.

[0121] Step 2:

[0122] The server inputs the received information into a generative AI model. This generative AI model utilizes natural language processing technology. The input consists of the received information and the prompt "Extract the main points, deadlines, and stakeholders from this text," and the output is the analysis result. Specifically, the server passes the information to the generative AI model, which then analyzes the information based on the prompt.

[0123] Step 3:

[0124] The server receives the analysis results returned from the generative AI model. The input is the analysis results from the generative AI model, and the output is the transmission of the analysis results to the terminal. Specifically, the server temporarily stores the analysis results in a database and prepares them for transmission to the terminal.

[0125] Step 4:

[0126] The terminal receives analysis results sent from the server and displays them to the user. The input is the analysis results from the server, and the output is a visual presentation of information to the user. Specifically, the terminal uses a pop-up display to show information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C" on the screen.

[0127] This series of processes allows users to quickly grasp the key points of the information they receive.

[0128] (Application Example 2)

[0129] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0130] In today's information society, there is a demand for quick identification of typographical errors and grammatical mistakes in written texts, as well as the ability to quickly grasp key points. However, particularly in factories, there is a lack of efficient means to quickly and accurately understand the contents of work instructions and progress reports. This can lead to delays and misunderstandings in work.

[0131] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0132] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services such as easy-to-understand advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and a server that is installed on machines used in factories to analyze work instructions and progress reports and display the main points. This reduces errors in text and enables quick grasp of key points.

[0133] "Generative AI" is an artificial intelligence technology that identifies typos and grammatical errors in text, provides clearer advice, and rewrites the text.

[0134] "Pop-up display" is a function that automatically displays key points, deadlines, and information about relevant parties on the screen based on the content of the document the recipient is viewing.

[0135] "Machinery used within a factory" refers to devices used in the factory work environment to analyze work instructions and progress reports and display key points.

[0136] A "work instruction sheet" is a document that describes the content and procedures of work within a factory, and is intended to provide specific instructions to workers.

[0137] A "progress report" is a document used to report on the progress of a project or task, and its purpose is to allow stakeholders to understand the current situation.

[0138] The system for implementing this invention consists of three elements: a server, a terminal, and a user. The server uses generative AI to identify typos and grammatical errors in transmitted text, and provides clearer advice and rewrites the text. It also displays the main points, deadlines, and relevant parties in pop-ups for longer texts to facilitate the recipient's understanding. Furthermore, it is installed on machinery used in factories and has the function of analyzing work instructions and progress reports and displaying key points.

[0139] This system is implemented using Python and utilizes natural language processing libraries such as NLTK and spaCy. The server analyzes received text, extracts keywords and recognizes dates, and extracts key points. The extracted information is displayed as a pop-up on the terminal's screen. Specifically, it tokenizes the text, tags it with parts of speech, and extracts key points, primarily focusing on nouns and verbs.

[0140] For example, if a user receives the instruction, "Please complete the assembly of part A by tomorrow. The responsible persons are D and E," the server will display a pop-up message on the terminal with the following information: "Key points: Assembly of part A, Deadline: Tomorrow, Responsible persons: D and E."

[0141] Examples of prompt statements to input into a generative AI model include the following:

[0142] "Please extract the key points, deadlines, and relevant parties from the following text: 'Please complete the assembly of part A by tomorrow. The responsible parties are Mr. D and Mr. E.'"

[0143] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0144] Step 1:

[0145] The server retrieves text received from the user. This input is an instruction, such as, "Please complete the assembly of part A by tomorrow. The responsible persons are Mr. D and Mr. E." The server then prepares this text for natural language processing.

[0146] Step 2:

[0147] The server uses natural language processing libraries such as NLTK and spaCy to tokenize and tag the received text by part of speech. This process classifies the words in the text into their respective parts of speech, identifying elements such as nouns and verbs. This provides the basic data needed for extracting key points.

[0148] Step 3:

[0149] The server extracts keywords and recognizes dates based on the tokenized data. Specifically, it extracts important information, primarily nouns, and identifies date-related information. The output of this step is summary information, such as "Key point: Assemble part A, Due date: Tomorrow, Person in charge: Mr. D, Mr. E."

[0150] Step 4:

[0151] The server sends the extracted summary information to the terminal, which then displays the information as a pop-up. This allows the user to quickly grasp the main points of the instructions. The terminal's display visually shows the main points, deadlines, and relevant parties.

[0152] (Example 3)

[0153] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0154] In today's information society, the exchange of emails and digital documents is increasing, but these documents often contain typos and grammatical errors, and key points and important information can get lost. Therefore, senders are required to create accurate and easy-to-understand documents, and recipients are required to quickly grasp the important information within the document. However, these tasks are time-consuming and difficult to perform efficiently.

[0155] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0156] In this invention, the server includes means for using generative artificial intelligence to identify typographical errors in documents being sent and providing services such as easy-to-understand advice and document rewriting; means for displaying key points, deadlines, and relevant parties in pop-ups for long documents to facilitate the recipient's understanding; and means for analyzing the content of received documents, automatically extracting key points, deadlines, and relevant parties, and presenting them visually. As a result, senders can create accurate and easy-to-understand documents, and recipients can quickly grasp the important information in the document.

[0157] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing techniques to identify typographical errors and omissions in documents, and to rewrite documents.

[0158] A "document" refers to text information created in email or digital format, and is a medium of information exchanged between a sender and a recipient.

[0159] "Typographical errors" refer to spelling mistakes or omissions of inappropriate characters within a document, and are factors that impair the accuracy of the document.

[0160] "Key points" refer to information or topics that are considered particularly important within a document, and are the content that the recipient should quickly understand.

[0161] A "deadline" refers to a specific date and time specified within a document, and is information by which the recipient must take action.

[0162] "Stakeholders" refers to specific individuals or organizations mentioned within a document, who are important parties related to the content of the document.

[0163] A "pop-up" refers to a window that temporarily appears on a computer screen, and is a means of immediately presenting important information to the user.

[0164] "Presenting visually" refers to displaying information graphically on a screen so that users can easily understand it.

[0165] This invention provides a system that enables both the sender and receiver to efficiently process information during email and digital document exchanges. Specific embodiments of this system are described below.

[0166] The server uses generative artificial intelligence to identify typos and grammatical errors in documents entered by the sender, and provides clearer feedback and rewrites the document. This process utilizes natural language processing technology, employing software such as Google Cloud Natural Language API and IBM Watson® Natural Language Understanding. This enables senders to create accurate and effective documents.

[0167] Furthermore, the server analyzes the content of received documents and automatically extracts key points, deadlines, and information about relevant parties. This analysis uses text analysis algorithms to identify important information within the document. The extracted information is visually presented as a pop-up window on the terminal. This allows recipients to quickly grasp the important information in the document.

[0168] For example, if a user receives a document that says, "Please submit a report on the project's progress by tomorrow. The relevant parties are A, B, and C," the server will extract the information "Key points: Project progress report, Deadline: Tomorrow, Relevant parties: A, B, C," and the terminal will display this as a pop-up.

[0169] An example of a prompt for a generative AI model is: "Extract the key points, deadline, and stakeholders from the following text: 'Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C.'"

[0170] In this way, the system provides a means for both the sender and the receiver to streamline the creation and understanding of documents. The flow of a specific process in Example 3 will be explained with reference to Figure 15.

[0171] Step 1:

[0172] The user receives an email.

[0173] The user receives a new email using their email client. The text data of the email is provided as input. The email content is sent to the server as output.

[0174] Step 2:

[0175] The server analyzes the content of the email.

[0176] The server analyzes the text data of received emails using natural language processing techniques. Specifically, it uses a generative AI model to understand the grammatical structure and meaning of the emails. The input is the text data of the emails, and the output is structural information of the analyzed document.

[0177] Step 3:

[0178] The server extracts key points, deadlines, and stakeholders.

[0179] The server automatically extracts key points, deadlines, and relevant information from emails based on the analysis results. It uses text analysis algorithms to identify specific keywords and phrases. Structural information from the analyzed document is used as input, and the extracted key information is generated as output.

[0180] Step 4:

[0181] The device displays information in a pop-up window.

[0182] The terminal receives extracted information sent from the server and displays it to the user as a pop-up window. Specifically, information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C" is visually presented on the screen. The input is the extracted key information, and the output is the visual presentation of that information to the user.

[0183] In this way, the system provides users with a means to quickly grasp important information in emails.

[0184] (Application Example 3)

[0185] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0186] In today's information society, vast amounts of information are sent and received daily via email and notifications. Among these, information related to electronic transactions, in particular, requires rapid and accurate understanding. However, traditional methods involve time-consuming information organization and verification, potentially leading to the oversight of crucial details. This can result in transaction delays and misunderstandings, posing a significant challenge.

[0187] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0188] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services such as easy-to-understand advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and a server that analyzes information related to electronic transactions, automatically extracts payment due dates, amounts, and trading partner information, and displays this information to the user in a pop-up. This enables the user to quickly grasp important transaction information and take appropriate action.

[0189] "Generative AI" refers to artificial intelligence systems that use natural language processing technology to generate and modify text.

[0190] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[0191] A "pop-up display" is a method of instantly displaying information on a user interface and is used to attract the user's attention.

[0192] "Key points" refer to the particularly important parts of a text or piece of information, and are extracted to aid understanding.

[0193] A "deadline" refers to the date by which a specific action or payment must be completed, and is important in schedule management.

[0194] "Stakeholders" refer to individuals or organizations involved in a particular project or transaction, and are important for information sharing and decision-making.

[0195] "Electronic transactions" refer to commercial transactions conducted via the internet or electronic devices, and are common in modern business.

[0196] The "payment due date" refers to the date on which payment for a transaction should be completed, and is important for contract fulfillment.

[0197] "Amount" refers to the quantity of money to be paid in a transaction or contract, and indicates the terms of the transaction.

[0198] A "business partner" refers to a company or individual that is the counterparty in a commercial transaction, and is important in building business relationships.

[0199] The system for implementing this invention consists of a server and a user terminal. The server uses generative AI to identify typographical errors and grammatical mistakes in the text sent by the user, and provides clearer advice and rewrites the text. Furthermore, the server automatically extracts the main points, deadlines, and information of relevant parties from the received text and displays them as a pop-up on the user terminal. This allows the user to quickly grasp the important information in the text.

[0200] The server also analyzes information related to electronic transactions, extracting payment due dates, amounts, and trading partners. This information is displayed as a pop-up on the user's terminal, allowing the user to instantly verify the transaction details. This helps prevent transaction delays and misunderstandings.

[0201] This system utilizes natural language processing (NLP) technology. Specifically, it uses NLP libraries such as "spaCy" and "NLTK" to analyze text and extract information. User terminals include devices such as smartphones and smart glasses, and are equipped with a user interface for displaying pop-up information.

[0202] For example, if a user receives an email stating, "I have received an invoice. The payment due date is next Friday, and the amount is 100,000 yen. The client is ABC Corporation," the server will extract the information "Payment due date: next Friday, Amount: 100,000 yen, Client: ABC Corporation" and display it as a pop-up on the user's terminal. An example of a prompt to input into the generating AI model would be, "Please extract the payment due date, amount, and client from this email."

[0203] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[0204] Step 1:

[0205] The server receives text data from user terminals, such as emails and notifications. This input data contains information about transactions. The server prepares to use natural language processing techniques to analyze this text data.

[0206] Step 2:

[0207] The server uses the NLP library "spaCy" or "NLTK" to parse the received text data. Specifically, it extracts payment due dates, amounts, and customer information from the text. This process analyzes the grammatical structure of the text and extracts the necessary information by identifying specific keywords and patterns. The input is text data, and the output is a set of extracted information.

[0208] Step 3:

[0209] The server organizes the extracted information and converts it into a data format for transmission to the user's terminal. This format conversion ensures that the information is presented in a way that is easy for the user to understand. The input is a set of extracted information, and the output is the formatted information.

[0210] Step 4:

[0211] The user terminal receives formatted information sent from the server. The terminal then launches a user interface to display this information as a pop-up. Specifically, it displays payment due dates, amounts, and customer information on the screen to attract the user's attention. The input is formatted information, and the output is a pop-up display.

[0212] Step 5:

[0213] Users can quickly grasp transaction information by checking the pop-up displayed on their device. This allows users to take the necessary actions immediately. The input is the information displayed in the pop-up, and the output is the user's understanding and actions.

[0214] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0215] "Example of form 1"

[0216] One embodiment of the present invention involves a system that combines a generative AI with an emotion engine that recognizes the sender's emotions. In this system, when the sender inputs text, the generative AI analyzes the text. Based on the analysis, it points out any typos or grammatical errors and provides advice to improve the clarity of the text. Furthermore, the emotion engine recognizes the sender's emotions and suggests rewriting the text according to those emotions. For example, if it recognizes that the sender is angry, it suggests rewriting the text to appropriately convey that emotion.

[0217] "Example of form 2"

[0218] Furthermore, some recipient-side services also incorporate an emotion engine. In this system, when a recipient receives a message, the system analyzes its content. Based on the analysis, it automatically extracts key points, deadlines, and information about relevant parties, and displays them in a pop-up window. In addition, the emotion engine recognizes the recipient's emotions and extracts and displays information accordingly. For example, if the system recognizes that the recipient is feeling confused, it prioritizes extracting and displaying information that will alleviate that emotion.

[0219] "Example of form 3"

[0220] Furthermore, there are systems that combine generative AI and pop-up displays with emotion engines. These systems simultaneously consider the emotions of both the sender and receiver, supporting communication tailored to each emotion. For example, if the system recognizes that the sender is angry and the receiver is confused, it takes both emotions into consideration and suggests appropriate expressions to the sender while displaying information to aid understanding to the receiver.

[0221] The following describes the processing flow for each example of the form.

[0222] "Example of form 1"

[0223] Step 1: The sender enters the message.

[0224] Step 2: The generative AI analyzes the input text and points out typos and grammatical errors.

[0225] Step 3: The generative AI provides advice to improve the clarity of the text.

[0226] Step 4: The emotion engine recognizes the sender's emotions.

[0227] Step 5: Based on the emotions recognized by the emotion engine, the generative AI suggests rewriting the text.

[0228] "Example of form 2"

[0229] Step 1: The recipient receives the message.

[0230] Step 2: The system analyzes the content of the received message.

[0231] Step 3: The system extracts key points, deadlines, and stakeholders from the analysis results and displays them in a pop-up window.

[0232] Step 4: The emotion engine recognizes the recipient's emotions.

[0233] Step 5: Based on the emotions recognized by the emotion engine, the system extracts and displays information.

[0234] "Example of form 3"

[0235] Step 1: The sender types the message, and the recipient receives the message.

[0236] Step 2: The generative AI analyzes the input text and points out typos and grammatical errors. At the same time, the system analyzes the content of the received message.

[0237] Step 3: The generative AI provides advice to improve the clarity of the text. At the same time, the system extracts key points, deadlines, and stakeholders from the analysis results and displays them in a pop-up window.

[0238] Step 4: The emotion engine simultaneously recognizes the emotions of both the sender and receiver.

[0239] Step 5: Based on the emotions recognized by the emotion engine, the generative AI suggests rewriting the text, and the system extracts and displays the information.

[0240] (Example 1)

[0241] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0242] In modern communication, it is essential that the sender's intended message is conveyed accurately and without misunderstanding. However, misinterpretations such as typos, inappropriate expressions, and misunderstandings of emotions often prevent the message from being conveyed as intended. Furthermore, recipients often struggle to grasp the main points when reading longer texts. To address these challenges, a system is needed to improve the accuracy and communicative power of written communication.

[0243] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0244] In this invention, the server includes means for using generative AI to point out typographical errors in the transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in pop-ups to facilitate the recipient's understanding; and means for using an emotion engine to recognize the sender's emotions and suggest rewriting the text in accordance with those emotions. As a result, the sender's intentions are accurately conveyed and the recipient can easily understand the text.

[0245] "Generative AI" is a type of artificial intelligence that uses natural language processing technology to analyze text, identify typos and grammatical errors, and rewrite sentences.

[0246] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[0247] "Advice" refers to suggestions or proposals offered to improve the clarity and ease of understanding of a piece of writing.

[0248] A "pop-up display" is an information window that is temporarily displayed on the screen, serving as a means of instantly conveying important information to the user.

[0249] An "emotion engine" is a technology that recognizes the sender's emotions from their text and suggests an appropriate response based on those emotions.

[0250] A "rewriting suggestion" is a proposal to change the original text to a more appropriate expression, and is made with the aim of improving the communication power of the text.

[0251] A "main point" refers to the particularly important or core content of a text or piece of information.

[0252] A "deadline" is the date on which a particular action or event is supposed to take place.

[0253] "Stakeholders" refers to individuals or organizations involved in a particular matter or event.

[0254] A description of embodiments for carrying out this invention will be given.

[0255] Users utilize a system integrated into internet search tools, email, and messenger apps. This system includes a program that combines generative AI and an emotion engine. When a user inputs text, the server receives the text and analyzes it using the generative AI. The generative AI utilizes natural language processing technology to detect and point out typos and grammatical errors in the text. It also provides advice to improve the clarity and ease of understanding of the text.

[0256] Furthermore, the server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the emotions in the input text and suggests rewriting the text according to those emotions. For example, if the user inputs "I am very dissatisfied with this matter," the generative AI and emotion engine will suggest something like "I hope for improvement regarding this matter."

[0257] For example, if a user inputs "Please change the meeting time," the server uses a generative AI model to analyze it and suggests a polite expression such as "Could you please change the meeting time?" Furthermore, if the emotion engine recognizes that the user is in a hurry, it will suggest something like, "I'm sorry to bother you, but could you please change the meeting time?"

[0258] An example of a prompt message might be: "Analyze the text entered by the user, point out typos and grammatical errors, and suggest rewrites that reflect the user's emotions."

[0259] The flow of the specific processing in Example 1 will be explained using Figure 17.

[0260] Step 1:

[0261] Users enter text into input fields in internet search tools, email, or messenger apps. This entered text becomes the starting point for system processing.

[0262] Step 2:

[0263] The server receives the text data entered by the user. It then prepares the received text to be passed as input to a generative AI model for analysis.

[0264] Step 3:

[0265] The server uses a generative AI model to analyze the structure and content of the input text. This analysis uses natural language processing techniques to detect typos and grammatical errors within the text. As a result of the analysis, information identifying typos and grammatical errors is output.

[0266] Step 4:

[0267] The server generates advice to improve the clarity of the text based on the analysis results of the AI ​​model. Specifically, it suggests rewriting the text to improve its politeness and clarity. This suggestion is then provided to the user as output.

[0268] Step 5:

[0269] The server uses an emotion engine to recognize emotions from the text entered by the user. The emotion engine analyzes words and expressions in the text to identify the user's emotional state. This emotional information is used to suggest rewriting in the next step.

[0270] Step 6:

[0271] The server suggests appropriate rewritings of the text based on the emotions it recognizes. For example, if anger is detected, it will suggest expressions that alleviate that emotion. These rewriting suggestions are then provided to the user as the final output.

[0272] Step 7:

[0273] The user reviews the suggestions from the server and revises the text as needed. After reviewing the final text, they submit or save it. This ensures that the text accurately conveys the user's intent.

[0274] (Application Example 1)

[0275] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server," and the smart device 14 will be referred to as a "terminal."

[0276] In modern communication, misunderstandings often arise due to typographical errors, grammatical mistakes, and inappropriate expressions. Furthermore, accurately conveying the sender's emotions is difficult, and in face-to-face customer service, appropriate responses tailored to the customer's feelings are crucial. To address these challenges, real-time text analysis and emotion recognition are necessary.

[0277] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following means.

[0278] In this invention, the server includes means for pointing out typos in the text to be transmitted using generative AI and providing easy-to-understand advice and text rewriting services, means for providing a service that displays the key points, deadlines, relevant parties, etc. of a long text in a pop-up window to facilitate the recipient's understanding, means for analyzing the sender's emotion using an emotion recognition engine and proposing text rewriting according to the emotion, and means for converting voice input into text, pointing out errors in the text in real time, and proposing appropriate expressions. As a result, it is possible to reduce misunderstandings in the text and appropriately convey the sender's emotion.

[0279] "Generative AI" is an artificial intelligence technology that analyzes the input text, points out typos, and proposes improvements to the text.

[0280] "Emotion recognition engine" is a technology for analyzing the sender's emotion and proposing appropriate text expressions according to the emotion.

[0281] "Voice input" is an input means for converting voice into text data.

[0282] "Pop-up display" is a means for displaying a small window on the screen to immediately convey important information to the user.

[0283] "Real-time analysis" is a technology that immediately processes the input data and instantaneously provides the results.

[0284] The system for implementing this invention mainly consists of a server and a terminal. The server uses a generative AI model to analyze text input by the user and provides suggestions for correcting typos and suggesting improvements to the text. Specifically, the server uses OpenAI's GPT to analyze the input text data and suggest appropriate expressions. In addition, it uses IBM Watson's Tone Analyzer as an emotion recognition engine to analyze the user's emotions and suggest rewriting the text according to those emotions.

[0285] The terminal is a device such as smart glasses or a smartphone that accepts voice input. The voice input is converted to text using the Google Cloud Speech-to-Text API. The converted text is sent to a server and analyzed in real time. The analysis results are displayed as a pop-up on the terminal's display, providing the user with immediate feedback.

[0286] For example, if a user voice-inputs "This product is cheap," the generative AI will suggest a more polite expression such as "This product is reasonably priced." Also, if the emotion engine recognizes that the customer is dissatisfied, it will suggest an apology such as "We apologize for any inconvenience this may have caused."

[0287] An example of a prompt message might be, "Please suggest an appropriate apology if the customer is dissatisfied." This allows users to communicate more smoothly with customers.

[0288] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[0289] Step 1:

[0290] The user provides voice input to the device. The device uses the Google Cloud Speech-to-Text API to convert the voice data into text data. The input for this step is voice data, and the output is text data.

[0291] Step 2:

[0292] The terminal sends the converted text data to the server. The server analyzes the text data using OpenAI's GPT generative AI model. This analysis provides feedback on typos and grammatical errors, as well as suggestions for improving the text. The input is text data, and the output is feedback on typos and grammatical errors, along with suggestions for improvement.

[0293] Step 3:

[0294] The server uses IBM Watson's Tone Analyzer to analyze user sentiment from text data. The input is text data, and the output is the sentiment analysis result. Based on this result, suggestions for rewriting the text according to the sentiment are made.

[0295] Step 4:

[0296] The server sends the analysis results and improvement suggestions to the terminal. The terminal presents this information to the user as a pop-up display. The input is the analysis results and improvement suggestions, and the output is the feedback display to the user.

[0297] Step 5:

[0298] The user reviews the suggestions displayed on the device and modifies the text as needed. This enables the user to communicate more smoothly with customers. The input is feedback information, and the output is the modified text.

[0299] (Example 2)

[0300] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0301] In modern information society, it is required that recipients efficiently understand a large number of messages and respond appropriately. However, it is difficult to understand long messages or texts containing complex content in a short time, and since information is not provided according to the recipient's emotions, misunderstandings and delays in response may occur. As a result, there are problems such as a decrease in work efficiency and a communication gap.

[0302] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in the second embodiment is realized by the following means.

[0303] In this invention, the server includes means for using generative artificial intelligence to point out typos and missing characters in the text to be transmitted and provide easy-to-understand advice and text rewriting services, means for providing a service that displays the key points, deadlines, related persons, etc. of a long text in a pop-up to facilitate the recipient's understanding, and means for analyzing the recipient's emotions and extracting and displaying information according to the emotions. As a result, the recipient can quickly grasp the key points of the message and obtain appropriate information according to the emotions.

[0304] "Generative artificial intelligence" is an artificial intelligence system that uses natural language processing technology to point out typos and missing characters in a text and propose improvements to the text.

[0305] "Pop-up display" is a visual notification means for immediately displaying important information on the screen that the recipient browses.

[0306] "Emotion analysis" is a technology for analyzing the recipient's emotional state and providing appropriate information based on the emotions.

[0307] "Key points" refer to particularly important information or themes in a text, which are the core parts that the recipient should understand.

[0308] "Deadline" refers to the deadline by which a specific action or response is required, which is the date by which the recipient needs to respond within that deadline.

[0309] "Stakeholders" refer to individuals or organizations related to a specific message or project, and are those with whom information sharing and cooperation are necessary.

[0310] This system's program provides a function that analyzes the content of a message received by the recipient, automatically extracting and displaying key points, deadlines, and information about relevant parties. Furthermore, it can analyze the recipient's emotions and extract and display information accordingly.

[0311] The server analyzes messages using natural language processing techniques. Specifically, it tokenizes text using Python's NLTK library and spaCy, and then analyzes the grammatical structure to extract key points, deadlines, and information about stakeholders. For sentiment analysis, it uses Python's TextBlob and the Google Cloud Natural Language API to determine the recipient's sentiment as positive, negative, or neutral.

[0312] The device displays the extracted information as a pop-up using JavaScript (registered trademark). This allows users to quickly grasp the main points of the message and obtain appropriate information that matches their emotions.

[0313] As a concrete example, if a user receives the message, "Please submit a project progress report by tomorrow. The relevant parties are A, B, and C," the device sends this message to the server. The server analyzes the message using spaCy, extracts "project progress report" as the key point, and recognizes "tomorrow" as the deadline. It also identifies "A, B, and C" as the relevant parties. If the emotion engine determines the user's emotion is "confused," the device will display a pop-up with the information "Key point: Project progress report, Deadline: Tomorrow, Relevant parties: A, B, C," and additional information such as "Here is the report template."

[0314] An example of a prompt to input into a generating AI model is: "Extract the key points, deadline, and stakeholders from the following message: 'Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C.'" By using this prompt, the AI ​​model can extract the necessary information and provide it to the user.

[0315] The flow of the specific processing in Example 2 will be explained using Figure 19.

[0316] Step 1:

[0317] The user receives a message. The terminal prepares to send the received message to the server. The input is the text message received by the user. The output is the message data to be analyzed and sent to the server.

[0318] Step 2:

[0319] The server analyzes received messages using natural language processing techniques. Specifically, it tokenizes text using Python's NLTK library and spaCy, and then analyzes the grammatical structure. The input is message data sent from the terminal. The output is the tokenized text and the analyzed grammatical structure.

[0320] Step 3:

[0321] The server extracts key points, deadlines, and stakeholders from the analyzed data. It uses regular expressions to identify dates and names and extract important keywords. Input consists of tokenized text and parsed grammatical structure. Output is the extracted key points, deadlines, and stakeholders.

[0322] Step 4:

[0323] The server uses a sentiment engine to analyze the sentiment of a message. It uses Python's TextBlob and the Google Cloud Natural Language API to determine whether the message is positive, negative, or neutral. The input is the message data. The output is the analyzed sentiment information.

[0324] Step 5:

[0325] The device displays the extracted information as a pop-up using JavaScript. If the sentiment engine determines that the user is confused, the device prioritizes displaying additional explanations and details. The input consists of extracted key points, deadlines, stakeholders, and sentiment information. The output is the pop-up information displayed to the user.

[0326] (Application Example 2)

[0327] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0328] In modern information and communication, recipients are required to understand large amounts of information quickly and accurately. However, information is often difficult to understand because it is not provided in a way that considers the recipient's emotional state. Furthermore, in transactions and important messages, recipients may experience anxiety or confusion, which hinders quick decision-making. To solve these problems, it is necessary to provide information that takes the recipient's emotions into consideration.

[0329] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0330] In this invention, the server includes means for using generative AI to point out typographical errors in transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in pop-ups to facilitate the recipient's understanding; and means for recognizing the recipient's emotions and extracting and displaying information according to those emotions. As a result, the recipient can quickly and accurately understand the information and obtain appropriate information according to their emotions.

[0331] "Generative AI" refers to artificial intelligence technology that uses natural language processing to generate and modify text.

[0332] "Error detection" is a function that detects incorrect or missing characters in a text and corrects them to their correct form.

[0333] "Easy-to-understand advice" refers to specific suggestions for improvement provided to make the recipient more easily understandable.

[0334] A "text rewriting service" is a service that transforms original text into clearer and more effective expressions.

[0335] The "main point" refers to the most important information or subject matter in a text, and is the core part that the recipient should understand.

[0336] A "deadline" is information that indicates the deadline by which a particular action or event must be completed.

[0337] "Stakeholders" refers to individuals or organizations associated with a particular document or message.

[0338] A "pop-up" is an information window that temporarily appears on the screen and is used to attract the user's attention.

[0339] "Recognizing the receiver's emotions" refers to the technology of determining the emotional state of the receiver from their facial expressions and voice.

[0340] "Information extraction and display" is the process of extracting necessary information from text and presenting it visually to the user.

[0341] The system for implementing this invention operates in a network environment including a server and user terminals. The server uses generative AI to identify typos and grammatical errors in the text sent by the user, and provides clearer advice and rewrites the text. Specifically, it uses Python and the natural language processing library spaCy to analyze and correct the text.

[0342] On the user's device, the system automatically extracts the key points, due date, and relevant information of received messages and displays them as a pop-up. This utilizes front-end technology to receive analysis results from the server and display them on the user interface. Furthermore, it uses TENSORFLOW® to recognize the user's emotions and prioritizes the display of information corresponding to those emotions. For example, if the user is feeling anxious, information regarding the security of the transaction will be prioritized.

[0343] For example, if a user receives the message, "¥10,000 has been withdrawn from your account. Please check," the system will display "Key points: Withdrawal of ¥10,000, Due date: Immediate, Parties involved: Financial institution." If the user is concerned, additional information such as, "This transaction is secure. Please see the support page for details," will be displayed.

[0344] An example of a prompt for the generating AI model is: "Analyze the transaction confirmation message and extract the key points. Also, provide suggestions for providing information that is tailored to the user's emotions."

[0345] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[0346] Step 1:

[0347] The server receives text sent by the user. Using this text as input, it uses a generative AI to detect typos and grammatical errors. Specifically, it analyzes the text using the natural language processing library spaCy to identify typos and grammatical errors. The output is a list of the errors and suggested corrections.

[0348] Step 2:

[0349] The server provides the user with suggested revisions generated by a generative AI. The user then revises the text based on these suggestions. The revised text is sent back to the server. The input is the suggested revisions, and the output is the text revised by the user.

[0350] Step 3:

[0351] The server receives the revised text and extracts information on key points, deadlines, and stakeholders. This process involves analyzing the text again using spaCy to identify important information. The input is the revised text, and the output is the extracted information.

[0352] Step 4:

[0353] The server sends the extracted information to the user's terminal. The terminal displays this information as a pop-up on its user interface. The input is the extracted information, and the output is the information visually presented to the user.

[0354] Step 5:

[0355] The device uses TensorFlow to analyze the user's facial expressions and voice in order to recognize the user's emotions. The input is the user's facial expressions and voice data, and the output is the recognized emotional state.

[0356] Step 6:

[0357] The device adjusts the information displayed based on the recognized emotion. For example, if the user is feeling anxious, it prioritizes displaying information related to the security of the transaction. The input is the recognized emotional state, and the output is the adjusted information display.

[0358] (Example 3)

[0359] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0360] In modern information and communication, there are challenges such as errors in transmitted information and difficulty for recipients to quickly grasp the main points of the information. Furthermore, a lack of communication that considers the feelings of both senders and receivers can lead to misunderstandings and inappropriate responses. Systems are needed to address these challenges.

[0361] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0362] In this invention, the server includes means for pointing out errors in transmitted information using generative artificial intelligence and providing easily understandable advice and information correction services; means for displaying the main points, deadlines, and relevant parties of long information on a display device to facilitate the recipient's understanding; and means for analyzing the emotions of the sender and recipient and providing appropriate expressions and information based on that analysis. This improves the accuracy of information, allows recipients to quickly grasp the main points of the information, and enables appropriate communication that responds to emotions.

[0363] "Generative artificial intelligence" is an artificial intelligence technology that uses input information to identify and correct errors and provide advice.

[0364] A "display device" is a device that allows a recipient to visually confirm information.

[0365] "Analyzing emotions" is the process of analyzing the emotional states of both the sender and receiver and using that analysis to determine an appropriate response.

[0366] "Key points" refer to the particularly important or core content of information.

[0367] "Deadline" refers to a specific date, time, or deadline related to information.

[0368] "Stakeholders" refers to individuals or organizations related to the information.

[0369] This invention is a system for improving the transmission and reception processes in information communication. The server uses generative artificial intelligence to identify errors in transmitted information and provides clearer advice and corrections. Specifically, it uses a natural language processing library to analyze input information and detect typos, grammatical errors, and inappropriate expressions. This allows users to improve the accuracy of the information they receive.

[0370] Furthermore, the server extracts the key points, deadlines, and stakeholders of long pieces of information so that recipients can quickly understand them, and displays them as pop-ups on the terminal's display. This process uses natural language processing technology. For example, if a recipient receives the information, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the server extracts and displays the information, "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C."

[0371] The server also analyzes the emotions of both the sender and receiver and provides appropriate expressions and information based on that analysis. It uses an emotion analysis API for this analysis. For example, if the server recognizes that the sender is angry and the receiver is confused, it will suggest appropriate expressions to the sender and provide the receiver with information to aid understanding.

[0372] As a concrete example, an example of a prompt sentence to be input to the generating AI model is shown: "Extract the main points of the message received by the recipient, analyze the sentiment, and suggest an appropriate response." By using this prompt, the system can provide the recipient with information quickly and appropriately. The flow of specific processing in Example 3 will be explained using Figure 21.

[0373] Step 1:

[0374] The user receives information via email or messaging apps. The device prepares to send the received information to the server. The input is the text information received by the user, and the output is the data to be analyzed that is sent to the server.

[0375] Step 2:

[0376] The server uses a natural language processing library to analyze the received information. Specifically, it tokenizes the text data and extracts important keywords and phrases. The input is text data sent from the terminal, and the output is extracted information such as key points, deadlines, and stakeholders.

[0377] Step 3:

[0378] The server uses Google Cloud's sentiment analysis API to analyze the sentiments of both the sender and receiver. The input is the received text data, and the output is the result of the sentiment analysis. Based on the sentiment analysis results, the server determines the appropriate response.

[0379] Step 4:

[0380] The server displays a pop-up on the recipient's device based on the extracted information and sentiment analysis results. The device displays the pop-up, allowing the user to quickly grasp key points, deadlines, and relevant information. The input is the information sent from the server, and the output is the pop-up information displayed on the device.

[0381] Step 5:

[0382] The server inputs a prompt sentence into a generative AI model and generates an appropriate response. The input consists of the prompt sentence and the analysis result, while the output is the generated response. The server provides the generated response to the recipient, facilitating smooth communication.

[0383] (Application Example 3)

[0384] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0385] In today's information society, there is a growing demand for increased efficiency in electronic transactions and communication. However, quickly grasping important transaction information and engaging in appropriate communication that considers emotions is not easy. In particular, there is a need for a system that enables quick understanding of the key points of transaction notifications and supports communication that takes into account the feelings of both the sender and the receiver.

[0386] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0387] In this invention, the server includes means for using generative AI to point out typographical errors in transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in pop-ups to facilitate the recipient's understanding; means for analyzing the emotions of the sender and receiver and supporting emotion-appropriate communication; and means for automatically extracting and displaying the main points of an electronic transaction when a notification regarding the transaction is received. This enables rapid understanding of transaction information and support for emotion-conscious communication.

[0388] "Generative AI" refers to artificial intelligence that uses natural language processing technology to generate and modify text.

[0389] "Error detection" is a function that detects incorrect or missing characters in a text and suggests corrections.

[0390] "Easy-to-understand advice" is a function that provides suggestions for improvement to make the text easier for the recipient to understand.

[0391] A "text rewriting service" is a service that transforms the original text into a clearer and more concise expression.

[0392] "Pop-up display" is a function that displays a small window on the screen to instantly present important information.

[0393] "Automatic extraction of key points, deadlines, and relevant information" refers to a technology that automatically extracts and displays important information from a document.

[0394] "Means of analyzing emotions and supporting emotion-based communication" refers to a function that analyzes the emotions of the sender and receiver and facilitates appropriate communication based on that analysis.

[0395] A "notice regarding electronic transactions" is a message that contains information about electronic transactions.

[0396] "A means of automatically extracting and displaying the key points of a transaction" refers to a function that automatically extracts important information from transaction notifications and presents it to the user.

[0397] The system for implementing this invention mainly consists of a server and a user terminal. The server uses generative AI to identify typos and grammatical errors in the text sent by the user, and provides clearer advice and rewrites the text. The user terminal displays the main points, deadlines, and information about relevant parties in pop-ups to facilitate user understanding. Furthermore, the server analyzes the emotions of the sender and receiver and supports communication that is appropriate to those emotions.

[0398] Specifically, the server uses a natural language processing library (e.g., spaCy) to detect typos and grammatical errors from text and extract key points. For sentiment analysis, a sentiment analysis library (e.g., TextBlob) is used to analyze the emotions of the sender and receiver. A generative AI model (e.g., OpenAI GPT) generates communication suggestions that are appropriate to the emotions.

[0399] For example, when a user receives a notification about an electronic transaction, the server automatically extracts the key points of the transaction (transaction amount, due date, and parties involved) and displays them as a pop-up on the user's terminal. Furthermore, based on sentiment analysis, if the sender appears to be feeling anxious, the server suggests that they should make an effort to provide a more thorough explanation to the user.

[0400] An example of a prompt message is, "Extract the key points of this transaction notification and analyze the sentiment of the sender and recipient."

[0401] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[0402] Step 1:

[0403] The server receives notifications from users regarding electronic transactions. The input is the text data of the transaction notification. Based on this data, a natural language processing library (e.g., spaCy) is used to analyze the sentence structure. The output is the structural information of the analyzed sentence.

[0404] Step 2:

[0405] The server uses the structural information of the analyzed text to extract the key points of the transaction (transaction amount, due date, parties involved). The input is the structural information obtained in step 1. As part of the data processing, specific keywords and phrases are identified and key points are extracted. The output is the extracted key points information.

[0406] Step 3:

[0407] The server analyzes the emotions of the sender and receiver using an emotion analysis library (e.g., TextBlob). The input is the text data of the transaction notification. As a data calculation, it calculates an emotion score from the text and identifies the type of emotion. The output is the emotion information of the sender and receiver.

[0408] Step 4:

[0409] The server uses a generative AI model (e.g., OpenAI GPT) to generate emotion-based communication suggestions. The input is the emotion information obtained in step 3. As a data processing step, it generates appropriate communication phrases based on the emotion information. The output is the generated communication suggestions.

[0410] Step 5:

[0411] The terminal displays key information and communication proposals received from the server as a pop-up. The input consists of the key information obtained in step 2 and the communication proposals obtained in step 4. Specifically, a pop-up window is displayed on the user's screen, immediately presenting the important information. The output is the information presented to the user.

[0412] (Other examples)

[0413] Next, other embodiments will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0414] In modern communication, accuracy in writing, including avoiding typos and using polite language, is highly valued. However, manually correcting these is time-consuming and laborious. Furthermore, it presents the challenge of making it difficult for recipients to quickly grasp the main points and important information of a text.

[0415] The identification processing performed by the identification processing unit 290 of the data processing device 12 in other embodiments is realized by the following means.

[0416] In this invention, the server includes means for tokenizing user-inputted text and detecting typographical errors, means for generating prompt sentences instructing a generation AI model to correct typographical errors and generating suggested corrections, and means for generating prompt sentences that suggest rewriting to improve the politeness of the text. This enables automatic correction of typographical errors and improvement of expression in text, and allows recipients to quickly grasp important information.

[0417] A "generative AI model" is an algorithm or system that uses artificial intelligence technology to automatically generate output based on input data.

[0418] A "prompt statement" is an instruction given to a generative AI model to perform a specific task.

[0419] "Tokenization" is a natural language processing technique that divides text into its smallest units, such as words and phrases.

[0420] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[0421] "Natural language processing" is a general term for technologies and methods used to process human language using computers, and is used for text analysis and generation.

[0422] A "revision proposal" refers to the changes suggested by a generative AI model with the aim of correcting typos, grammatical errors, and improving phrasing.

[0423] The following describes "modes for carrying out the invention."

[0424] ---

[0425] This invention is a system for automatically correcting typographical errors and grammatical mistakes in text entered by a user, thereby improving the politeness of the writing. The system consists of a server, a terminal, and a generative AI model.

[0426] The server receives text entered by the user from the terminal. The received text is tokenized using the natural language processing library NLTK (Natural Language Toolkit). Each tokenized word is compared against a dictionary database to check for typos or grammatical errors.

[0427] If typos or grammatical errors are detected, the server generates a prompt message instructing the GPT-3 generation AI model, OpenAI, to correct them. An example of a prompt message is "Please correct the typos and grammatical errors in the following sentence:", which is generated by continuing with the sentence entered by the user.

[0428] The generative AI model receives the prompt text and generates appropriate revised versions. The server sends these revised versions to the user's terminal and presents them to the user. The user reviews the proposed revisions and improves the text as needed.

[0429] Furthermore, the server generates a prompt message instructing the user to make rewriting suggestions to improve the politeness of the text. An example of such a prompt message might be: "Please rewrite the following text in a more polite manner:"

[0430] When analyzing the content of a document viewed by a recipient, the server uses natural language processing (NLP) techniques to analyze the text and extract key points, deadlines, and information about those involved. Natural language processing libraries such as SpaCy are used for this process. The extracted information is then displayed on the user's terminal.

[0431] In this way, a system is built in which servers, terminals, and users work together to correct typos and improve the neatness of written text.

[0432] The flow of specific processing in other embodiments will be explained using Figure 23.

[0433] Step 1:

[0434] The user enters text using the terminal's input interface. The entered text is sent to the server. The input data is the text created by the user. The output is the text data sent to the server.

[0435] Step 2:

[0436] The server tokenizes the received text using the NLTK natural language processing library. Each tokenized word is then compared against a dictionary database to check for typos or errors. The input is the text data received from the user, and the output is a list of words with typos or errors.

[0437] Step 3:

[0438] If typos or grammatical errors are detected, the server generates a prompt message instructing the OpenAI GPT-3 generation AI model to correct them. A typical example of a prompt message is "Please correct the typos and grammatical errors in the following sentence:", which is generated by continuing with the sentence entered by the user. The input is the sentence with typos and grammatical errors, and the output is the generated prompt message.

[0439] Step 4:

[0440] The generative AI model receives a prompt and generates appropriate corrections. The server sends these corrections to the user's terminal and presents them to the user. The input is the prompt, and the output is text data containing the corrections.

[0441] Step 5:

[0442] The user reviews the suggested revisions and improves the text as needed. The improved text is then sent back to the server. The input is the text data including the suggested revisions, and the output is the text data improved by the user.

[0443] Step 6:

[0444] The server generates a prompt message instructing the user to suggest rewriting the text to improve its politeness. An example of this prompt message might be: "Please rewrite the following sentence using more polite language:" The input is the improved text submitted by the user, and the output is the generated prompt message.

[0445] Step 7:

[0446] The server analyzes the content of the text viewed by the recipient and extracts key points, deadlines, and information about those involved. This process uses natural language processing libraries such as SpaCy. The extracted information is displayed on the user's terminal. The input is the text improved by the user, and the output is the extracted key points, deadlines, and information about those involved.

[0447] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0448] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0449] Other examples of generative AI include Gemini® (registered trademark) (Internet search). <url: https: gemini.google.com ?hl="ja">) are some examples.

[0450] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0451] [Second Embodiment]

[0452] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0453] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0454] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0455] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0456] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0457] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0458] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0459] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0460] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0461] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0462] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0463] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0464] "Example of form 1"

[0465] One embodiment of this system is one that can be integrated into internet search tools, email, and messenger applications. This system uses generative AI to analyze the text entered by the sender and points out typos and grammatical errors. Furthermore, it provides advice to improve the clarity of the text and suggests rewriting it as needed. Specifically, if the sender enters "Please submit the report by tomorrow," the generative AI will suggest rewriting it to a more polite expression such as "Please submit the report by tomorrow."

[0466] "Example of form 2"

[0467] Furthermore, for recipients, there is a feature that analyzes the content of received messages, automatically extracts key points, deadlines, and information about stakeholders, and displays them in a pop-up window. Specifically, if a recipient receives a message that says, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the system will display a pop-up window with the following information: "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C." This allows the recipient to quickly grasp the main points of the message.

[0468] "Example of form 3"

[0469] Furthermore, for recipients, there is a feature that analyzes the content of received messages, automatically extracts key points, deadlines, and information about stakeholders, and displays them in a pop-up window. Specifically, if a recipient receives a message that says, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the system will display a pop-up window with the following information: "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C." This allows the recipient to quickly grasp the main points of the message.

[0470] The following describes the processing flow for each example of the form.

[0471] "Example of form 1"

[0472] Step 1: The sender types the message into an internet search tool, email, or messenger app.

[0473] Step 2: The generative AI analyzes the input text and points out typos and grammatical errors.

[0474] Step 3: The generative AI provides advice to improve the clarity of the text.

[0475] Step 4: If necessary, the generative AI will suggest rewriting the text.

[0476] "Example of form 2"

[0477] Step 1: The recipient receives the message.

[0478] Step 2: The system analyzes the content of the received text.

[0479] Step 3: The system automatically extracts key points, deadlines, and information about stakeholders.

[0480] Step 4: The system will display the extracted information in a pop-up window.

[0481] (Example 1)

[0482] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0483] In modern communication, misunderstandings often arise due to typographical errors, grammatical mistakes, and unclear writing. Furthermore, long texts can bury key points and important information, making them difficult for recipients to understand. There is a need to address these challenges and achieve more effective communication.

[0484] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0485] In this invention, the server includes means for pointing out typographical errors and grammatical errors in transmitted text using generative artificial intelligence and providing services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts on a display device to facilitate the recipient's understanding; and means for analyzing text input by the user and using generative artificial intelligence to detect typographical errors and suggest improvements to the text. This makes it possible to improve the quality of text and clarify information.

[0486] "Generative artificial intelligence" is a technology that uses natural language processing to analyze text and point out typos and grammatical errors, as well as suggest improvements to the text.

[0487] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[0488] "Easy-to-understand advice" refers to suggestions that make the content of a document clearer and easier to understand, thereby facilitating the smooth transmission of information to the recipient.

[0489] A "rewriting service" is a function that improves the expression of a text and corrects it to a more appropriate form.

[0490] A "display device" is a device used to visually display information, and is used by recipients to confirm that information.

[0491] "Key points" refer to the particularly important parts of a text or piece of information, representing the main content that the recipient should understand.

[0492] A "deadline" refers to the date on which a specific action or event should take place, and is important information in schedule management.

[0493] "Stakeholders" refers to individuals or organizations related to a particular document or piece of information, and are those that the recipient of the information should be aware of.

[0494] "Analysis" is the process of thoroughly examining text and data to understand their structure and meaning.

[0495] The following systems are conceivable as embodiments for carrying out this invention.

[0496] The server uses generative artificial intelligence to analyze the text entered by the user. This analysis utilizes natural language processing technology to detect typos and grammatical errors and suggest improvements to the text. Specifically, a general-purpose natural language processing engine can be used as the generative AI model. For example, open-source natural language processing libraries or commercial AI platforms can be used.

[0497] The terminal sends the text entered by the user to the server. A secure communication protocol is used to transmit the data and protect the user's privacy. The server inputs the received text into a generation AI model to create a prompt. An example of a prompt is: "Please analyze the following text, identify any typos or grammatical errors, and provide suggestions for improvement:"

[0498] The generative AI model analyzes the input text and not only points out typos and grammatical errors, but also provides advice to improve the clarity of the writing. For example, if a user inputs "Please submit the report by tomorrow," the generative AI model will suggest rewriting it into a more polite expression such as "Please submit the report by tomorrow."

[0499] In this way, users can improve the quality of their writing and achieve unambiguous communication by utilizing generative artificial intelligence.

[0500] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0501] Step 1:

[0502] Users input text through internet search tools, email, or messenger apps. This entered text becomes the data subject to typographical error checking and suggestions for improving the text.

[0503] Step 2:

[0504] The terminal sends the text entered by the user to the server. This data is transmitted using a secure communication protocol. The input is the user's text, and the output is the secure transmission of data to the server.

[0505] Step 3:

[0506] The server inputs the received text into the generative AI model. Specifically, it creates a prompt message and inputs it to the generative AI model in the format of "Please analyze the following text, point out any typos or grammatical errors, and provide suggestions for improvement:". The input is the user's text, and the output is the prompt message to the generative AI model.

[0507] Step 4:

[0508] The generative AI model analyzes text based on the input prompt sentence. It detects typos and grammatical errors and generates advice and rewriting suggestions to improve the clarity of the text. The input is the prompt sentence, and the output is the analysis result and improvement suggestions.

[0509] Step 5:

[0510] The server sends the analysis results and improvement suggestions obtained from the generated AI model to the terminal. The input is the output of the generated AI model, and the output is the transmission of data to the terminal.

[0511] Step 6:

[0512] The terminal displays analysis results and improvement suggestions received from the server to the user. The user can then use this information to revise their text. The input is data from the server, and the output is information displayed to the user.

[0513] (Application Example 1)

[0514] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0515] In modern communication, typographical errors and inappropriate expressions can hinder information transmission. Furthermore, in customer service roles at physical stores, the ability to instantly select appropriate expressions during conversations with customers is crucial, but there is a lack of technology to support this. To address these challenges, a system is needed that analyzes written and spoken content in real time and suggests appropriate expressions.

[0516] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0517] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services such as easy-to-understand advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and a server that uses speech recognition technology to convert speech into text, generates appropriate expressions using generative AI, and presents them on a display device. This makes it possible to analyze the content of text and audio in real time and suggest appropriate expressions.

[0518] "Generative AI" is an artificial intelligence technology that analyzes input data and generates appropriate sentences and expressions through natural language processing.

[0519] "Typographical errors" refer to mistakes or omissions in text, and are factors that hinder the accurate transmission of information.

[0520] A "pop-up display" refers to a window or message that temporarily appears on the screen to highlight information within the user interface.

[0521] "Speech recognition technology" is a technology that analyzes speech as a digital signal and converts it into corresponding text data.

[0522] A "display device" is hardware used to visually present generated information or data, and includes displays and screens.

[0523] The system for implementing this invention involves a server and a terminal working in conjunction. The server uses generative AI to identify typos and grammatical errors in transmitted text, and provides clearer advice and rewrites the text. Furthermore, it displays key points, deadlines, and relevant parties in pop-ups for longer texts to facilitate the recipient's understanding.

[0524] The device uses speech recognition technology to convert speech into text, generates appropriate expressions using generative AI, and displays them on a display device. Specifically, the generated information is visually presented to the user using a display device such as smart glasses or a smartphone.

[0525] For example, in a physical store, if a user asks, "Does this product come in other colors?", the terminal uses speech recognition technology to convert this question into text and send it to the server. The server then uses generative AI to generate an appropriate response, such as, "This product is available in other colors. Which color would you prefer?", and displays it on the terminal's display.

[0526] An example of a prompt is, "A customer is asking about the color of a product. Please suggest a polite response." By inputting this prompt into a generative AI, an appropriate response will be generated.

[0527] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0528] Step 1:

[0529] The device acquires the user's voice input through the microphone. The input is the voice data spoken by the user. The device converts this voice data into text data using speech recognition technology (e.g., Google Cloud Speech-to-Text). The output is text data that represents the user's speech as a string of characters.

[0530] Step 2:

[0531] The terminal sends the converted text data to the server. The server inputs the received text data into a generative AI model (e.g., OpenAI's GPT-3). The input is text data representing the user's utterance. The server uses the generative AI model to perform data calculations to generate an appropriate response. The output is the text data of the generated appropriate response.

[0532] Step 3:

[0533] The server sends the generated response as text data to the terminal. The terminal displays the received response on a display device (e.g., smart glasses or smartphone display). The input is the text data of the response sent from the server. The terminal processes the data to present the information visually to the user and provides a response that is displayed to the user as output.

[0534] Step 4:

[0535] The user confirms the displayed response and continues the conversation as needed. The user's confirmation triggers the next voice input, and the process from step 1 is repeated. The input is the displayed response, and the output is the user's understanding and next action.

[0536] (Example 2)

[0537] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0538] In modern information and communication, it is difficult for recipients to quickly and accurately understand lengthy information. Furthermore, while it is crucial for senders to provide clear information free from typos and grammatical errors, doing so manually is time-consuming and laborious. To address these challenges, a system is needed that automatically extracts key points, deadlines, and stakeholders, and presents them clearly to the recipient.

[0539] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0540] In this invention, the server includes means for pointing out typographical errors in transmitted information using generative artificial intelligence and providing easy-to-understand advice and information rewriting services; means for displaying the main points, deadlines, and relevant parties of long information on a display device to facilitate the recipient's understanding; and means for analyzing received information and automatically extracting information on main points, deadlines, and relevant parties. As a result, the recipient can quickly grasp the main points of the information, and the sender can provide clear information free from typographical errors.

[0541] "Generative artificial intelligence" is a type of artificial intelligence that uses natural language processing technology to analyze and generate information.

[0542] "Typographical errors" refer to incorrectly written or missing characters in information.

[0543] "Advice" refers to instructions or suggestions provided to improve or facilitate understanding of information.

[0544] "Rewriting information" is the act of modifying information to make its content clearer and easier to understand.

[0545] A "key point" refers to the particularly important or core content of information.

[0546] "Deadline" refers to a specific date, time, or period related to information.

[0547] "Stakeholders" refers to individuals or organizations related to the information.

[0548] A "display device" is a device or interface used to present information visually.

[0549] "Analysis" is the process of breaking down information and understanding its structure and meaning.

[0550] "Extraction" is the act of taking out specific elements or data from information.

[0551] As an embodiment of this invention, the following system is constructed.

[0552] The server analyzes the received information using a generative AI model. A model that utilizes natural language processing technology is suitable for this generative AI model, and specifically, OpenAI's GPT model can be used. The server inputs the received information into the generative AI model and gives it a prompt message such as, "Extract the main points, deadlines, and stakeholders from this text." Based on this prompt message, the generative AI model analyzes the information and extracts the main points, deadlines, and stakeholders.

[0553] The terminal receives analysis results sent from the server and presents them to the user via a display device. Specifically, it uses a pop-up display to visually show information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C." This allows the user to quickly grasp the important parts of the received information.

[0554] Users can provide clear instructions as prompts to input into the generating AI model. For example, by using a prompt such as, "Extract the main points, deadlines, and stakeholders from this document," the system can efficiently extract and provide information to the user. In this way, recipients of the information can quickly understand the important information, and senders can provide clear information free from typos and grammatical errors.

[0555] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0556] Step 1:

[0557] The user receives information via email or messaging apps. The device detects this received information and prepares to send it to the server. The input is the received information, and the output is the transfer of information to the server. Specifically, the device sends information to the server triggered by the receipt of a new message.

[0558] Step 2:

[0559] The server inputs the received information into a generative AI model. This generative AI model utilizes natural language processing technology. The input consists of the received information and the prompt "Extract the main points, deadlines, and stakeholders from this text," and the output is the analysis result. Specifically, the server passes the information to the generative AI model, which then analyzes the information based on the prompt.

[0560] Step 3:

[0561] The server receives the analysis results returned from the generative AI model. The input is the analysis results from the generative AI model, and the output is the transmission of the analysis results to the terminal. Specifically, the server temporarily stores the analysis results in a database and prepares them for transmission to the terminal.

[0562] Step 4:

[0563] The terminal receives analysis results sent from the server and displays them to the user. The input is the analysis results from the server, and the output is a visual presentation of information to the user. Specifically, the terminal uses a pop-up display to show information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C" on the screen.

[0564] This series of processes allows users to quickly grasp the key points of the information they receive.

[0565] (Application Example 2)

[0566] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0567] In today's information society, there is a demand for quick identification of typographical errors and grammatical mistakes in written texts, as well as the ability to quickly grasp key points. However, particularly in factories, there is a lack of efficient means to quickly and accurately understand the contents of work instructions and progress reports. This can lead to delays and misunderstandings in work.

[0568] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0569] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services such as easy-to-understand advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and a server that is installed on machines used in factories to analyze work instructions and progress reports and display the main points. This reduces errors in text and enables quick grasp of key points.

[0570] "Generative AI" is an artificial intelligence technology that identifies typos and grammatical errors in text, provides clearer advice, and rewrites the text.

[0571] "Pop-up display" is a function that automatically displays key points, deadlines, and information about relevant parties on the screen based on the content of the document the recipient is viewing.

[0572] "Machinery used within a factory" refers to devices used in the factory work environment to analyze work instructions and progress reports and display key points.

[0573] A "work instruction sheet" is a document that describes the content and procedures of work within a factory, and is intended to provide specific instructions to workers.

[0574] A "progress report" is a document used to report on the progress of a project or task, and its purpose is to allow stakeholders to understand the current situation.

[0575] The system for implementing this invention consists of three elements: a server, a terminal, and a user. The server uses generative AI to identify typos and grammatical errors in transmitted text, and provides clearer advice and rewrites the text. It also displays the main points, deadlines, and relevant parties in pop-ups for longer texts to facilitate the recipient's understanding. Furthermore, it is installed on machinery used in factories and has the function of analyzing work instructions and progress reports and displaying key points.

[0576] This system is implemented using Python and utilizes natural language processing libraries such as NLTK and spaCy. The server analyzes received text, extracts keywords and recognizes dates, and extracts key points. The extracted information is displayed as a pop-up on the terminal's screen. Specifically, it tokenizes the text, tags it with parts of speech, and extracts key points, primarily focusing on nouns and verbs.

[0577] For example, if a user receives the instruction, "Please complete the assembly of part A by tomorrow. The responsible persons are D and E," the server will display a pop-up message on the terminal with the following information: "Key points: Assembly of part A, Deadline: Tomorrow, Responsible persons: D and E."

[0578] Examples of prompt statements to input into a generative AI model include the following:

[0579] "Please extract the key points, deadlines, and relevant parties from the following text: 'Please complete the assembly of part A by tomorrow. The responsible parties are Mr. D and Mr. E.'"

[0580] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0581] Step 1:

[0582] The server retrieves text received from the user. This input is an instruction, such as, "Please complete the assembly of part A by tomorrow. The responsible persons are Mr. D and Mr. E." The server then prepares this text for natural language processing.

[0583] Step 2:

[0584] The server uses natural language processing libraries such as NLTK and spaCy to tokenize and tag the received text by part of speech. This process classifies the words in the text into their respective parts of speech, identifying elements such as nouns and verbs. This provides the basic data needed for extracting key points.

[0585] Step 3:

[0586] The server extracts keywords and recognizes dates based on the tokenized data. Specifically, it extracts important information, primarily nouns, and identifies date-related information. The output of this step is summary information, such as "Key point: Assemble part A, Due date: Tomorrow, Person in charge: Mr. D, Mr. E."

[0587] Step 4:

[0588] The server sends the extracted summary information to the terminal, which then displays the information as a pop-up. This allows the user to quickly grasp the main points of the instructions. The terminal's display visually shows the main points, deadlines, and relevant parties.

[0589] (Example 3)

[0590] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0591] In today's information society, the exchange of emails and digital documents is increasing, but these documents often contain typos and grammatical errors, and key points and important information can get lost. Therefore, senders are required to create accurate and easy-to-understand documents, and recipients are required to quickly grasp the important information within the document. However, these tasks are time-consuming and difficult to perform efficiently.

[0592] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0593] In this invention, the server includes means for using generative artificial intelligence to identify typographical errors in documents being sent and providing services such as easy-to-understand advice and document rewriting; means for displaying key points, deadlines, and relevant parties in pop-ups for long documents to facilitate the recipient's understanding; and means for analyzing the content of received documents, automatically extracting key points, deadlines, and relevant parties, and presenting them visually. As a result, senders can create accurate and easy-to-understand documents, and recipients can quickly grasp the important information in the document.

[0594] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing techniques to identify typographical errors and omissions in documents, and to rewrite documents.

[0595] A "document" refers to text information created in email or digital format, and is a medium of information exchanged between a sender and a recipient.

[0596] "Typographical errors" refer to spelling mistakes or omissions of inappropriate characters within a document, and are factors that impair the accuracy of the document.

[0597] "Key points" refer to information or topics that are considered particularly important within a document, and are the content that the recipient should quickly understand.

[0598] A "deadline" refers to a specific date and time specified within a document, and is information by which the recipient must take action.

[0599] "Stakeholders" refers to specific individuals or organizations mentioned within a document, who are important parties related to the content of the document.

[0600] A "pop-up" refers to a window that temporarily appears on a computer screen, and is a means of immediately presenting important information to the user.

[0601] "Presenting visually" refers to displaying information graphically on a screen so that users can easily understand it.

[0602] This invention provides a system that enables both the sender and receiver to efficiently process information during email and digital document exchanges. Specific embodiments of this system are described below.

[0603] The server uses generative artificial intelligence to identify typos and grammatical errors in documents entered by the sender, and provides clearer feedback and rewrites the document. This process utilizes natural language processing technology, employing software such as Google Cloud Natural Language API and IBM Watson Natural Language Understanding. This enables senders to create accurate and effective documents.

[0604] Furthermore, the server analyzes the content of received documents and automatically extracts key points, deadlines, and information about relevant parties. This analysis uses text analysis algorithms to identify important information within the document. The extracted information is visually presented as a pop-up window on the terminal. This allows recipients to quickly grasp the important information in the document.

[0605] For example, if a user receives a document that says, "Please submit a report on the project's progress by tomorrow. The relevant parties are A, B, and C," the server will extract the information "Key points: Project progress report, Deadline: Tomorrow, Relevant parties: A, B, C," and the terminal will display this as a pop-up.

[0606] An example of a prompt for a generative AI model is: "Extract the key points, deadline, and stakeholders from the following text: 'Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C.'"

[0607] In this way, the system provides a means for both the sender and the receiver to streamline the creation and understanding of documents. The flow of a specific process in Example 3 will be explained with reference to Figure 15.

[0608] Step 1:

[0609] The user receives an email.

[0610] The user receives a new email using their email client. The text data of the email is provided as input. The email content is sent to the server as output.

[0611] Step 2:

[0612] The server analyzes the content of the email.

[0613] The server analyzes the text data of received emails using natural language processing techniques. Specifically, it uses a generative AI model to understand the grammatical structure and meaning of the emails. The input is the text data of the emails, and the output is structural information of the analyzed document.

[0614] Step 3:

[0615] The server extracts key points, deadlines, and stakeholders.

[0616] The server automatically extracts key points, deadlines, and relevant information from emails based on the analysis results. It uses text analysis algorithms to identify specific keywords and phrases. Structural information from the analyzed document is used as input, and the extracted key information is generated as output.

[0617] Step 4:

[0618] The device displays information in a pop-up window.

[0619] The terminal receives extracted information sent from the server and displays it to the user as a pop-up window. Specifically, information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C" is visually presented on the screen. The input is the extracted key information, and the output is the visual presentation of that information to the user.

[0620] In this way, the system provides users with a means to quickly grasp important information in emails.

[0621] (Application Example 3)

[0622] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0623] In today's information society, vast amounts of information are sent and received daily via email and notifications. Among these, information related to electronic transactions, in particular, requires rapid and accurate understanding. However, traditional methods involve time-consuming information organization and verification, potentially leading to the oversight of crucial details. This can result in transaction delays and misunderstandings, posing a significant challenge.

[0624] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0625] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services such as easy-to-understand advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and a server that analyzes information related to electronic transactions, automatically extracts payment due dates, amounts, and trading partner information, and displays this information to the user in a pop-up. This enables the user to quickly grasp important transaction information and take appropriate action.

[0626] "Generative AI" refers to artificial intelligence systems that use natural language processing technology to generate and modify text.

[0627] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[0628] A "pop-up display" is a method of instantly displaying information on a user interface and is used to attract the user's attention.

[0629] "Key points" refer to the particularly important parts of a text or piece of information, and are extracted to aid understanding.

[0630] A "deadline" refers to the date by which a specific action or payment must be completed, and is important in schedule management.

[0631] "Stakeholders" refer to individuals or organizations involved in a particular project or transaction, and are important for information sharing and decision-making.

[0632] "Electronic transactions" refer to commercial transactions conducted via the internet or electronic devices, and are common in modern business.

[0633] The "payment due date" refers to the date on which payment for a transaction should be completed, and is important for contract fulfillment.

[0634] "Amount" refers to the quantity of money to be paid in a transaction or contract, and indicates the terms of the transaction.

[0635] A "business partner" refers to a company or individual that is the counterparty in a commercial transaction, and is important in building business relationships.

[0636] The system for implementing this invention consists of a server and a user terminal. The server uses generative AI to identify typographical errors and grammatical mistakes in the text sent by the user, and provides clearer advice and rewrites the text. Furthermore, the server automatically extracts the main points, deadlines, and information of relevant parties from the received text and displays them as a pop-up on the user terminal. This allows the user to quickly grasp the important information in the text.

[0637] The server also analyzes information related to electronic transactions, extracting payment due dates, amounts, and trading partners. This information is displayed as a pop-up on the user's terminal, allowing the user to instantly verify the transaction details. This helps prevent transaction delays and misunderstandings.

[0638] This system utilizes natural language processing (NLP) technology. Specifically, it uses NLP libraries such as "spaCy" and "NLTK" to analyze text and extract information. User terminals include devices such as smartphones and smart glasses, and are equipped with a user interface for displaying pop-up information.

[0639] For example, if a user receives an email stating, "I have received an invoice. The payment due date is next Friday, and the amount is 100,000 yen. The client is ABC Corporation," the server will extract the information "Payment due date: next Friday, Amount: 100,000 yen, Client: ABC Corporation" and display it as a pop-up on the user's terminal. An example of a prompt to input into the generating AI model would be, "Please extract the payment due date, amount, and client from this email."

[0640] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[0641] Step 1:

[0642] The server receives text data from user terminals, such as emails and notifications. This input data contains information about transactions. The server prepares to use natural language processing techniques to analyze this text data.

[0643] Step 2:

[0644] The server uses the NLP library "spaCy" or "NLTK" to parse the received text data. Specifically, it extracts payment due dates, amounts, and customer information from the text. This process analyzes the grammatical structure of the text and extracts the necessary information by identifying specific keywords and patterns. The input is text data, and the output is a set of extracted information.

[0645] Step 3:

[0646] The server organizes the extracted information and converts it into a data format for transmission to the user's terminal. This format conversion ensures that the information is presented in a way that is easy for the user to understand. The input is a set of extracted information, and the output is the formatted information.

[0647] Step 4:

[0648] The user terminal receives formatted information sent from the server. The terminal then launches a user interface to display this information as a pop-up. Specifically, it displays payment due dates, amounts, and customer information on the screen to attract the user's attention. The input is formatted information, and the output is a pop-up display.

[0649] Step 5:

[0650] Users can quickly grasp transaction information by checking the pop-up displayed on their device. This allows users to take the necessary actions immediately. The input is the information displayed in the pop-up, and the output is the user's understanding and actions.

[0651] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0652] "Example of form 1"

[0653] One embodiment of the present invention involves a system that combines a generative AI with an emotion engine that recognizes the sender's emotions. In this system, when the sender inputs text, the generative AI analyzes the text. Based on the analysis, it points out any typos or grammatical errors and provides advice to improve the clarity of the text. Furthermore, the emotion engine recognizes the sender's emotions and suggests rewriting the text according to those emotions. For example, if it recognizes that the sender is angry, it suggests rewriting the text to appropriately convey that emotion.

[0654] "Example of form 2"

[0655] Furthermore, some recipient-side services also incorporate an emotion engine. In this system, when a recipient receives a message, the system analyzes its content. Based on the analysis, it automatically extracts key points, deadlines, and information about relevant parties, and displays them in a pop-up window. In addition, the emotion engine recognizes the recipient's emotions and extracts and displays information accordingly. For example, if the system recognizes that the recipient is feeling confused, it prioritizes extracting and displaying information that will alleviate that emotion.

[0656] "Example of form 3"

[0657] Furthermore, there are systems that combine generative AI and pop-up displays with emotion engines. These systems simultaneously consider the emotions of both the sender and receiver, supporting communication tailored to each emotion. For example, if the system recognizes that the sender is angry and the receiver is confused, it takes both emotions into consideration and suggests appropriate expressions to the sender while displaying information to aid understanding to the receiver.

[0658] The following describes the processing flow for each example of the form.

[0659] "Example of form 1"

[0660] Step 1: The sender enters the message.

[0661] Step 2: The generative AI analyzes the input text and points out typos and grammatical errors.

[0662] Step 3: The generative AI provides advice to improve the clarity of the text.

[0663] Step 4: The emotion engine recognizes the sender's emotions.

[0664] Step 5: Based on the emotions recognized by the emotion engine, the generative AI suggests rewriting the text.

[0665] "Example of form 2"

[0666] Step 1: The recipient receives the message.

[0667] Step 2: The system analyzes the content of the received message.

[0668] Step 3: The system extracts key points, deadlines, and stakeholders from the analysis results and displays them in a pop-up window.

[0669] Step 4: The emotion engine recognizes the recipient's emotions.

[0670] Step 5: Based on the emotions recognized by the emotion engine, the system extracts and displays information.

[0671] "Example of form 3"

[0672] Step 1: The sender types the message, and the recipient receives the message.

[0673] Step 2: The generative AI analyzes the input text and points out typos and grammatical errors. At the same time, the system analyzes the content of the received message.

[0674] Step 3: The generative AI provides advice to improve the clarity of the text. At the same time, the system extracts key points, deadlines, and stakeholders from the analysis results and displays them in a pop-up window.

[0675] Step 4: The emotion engine simultaneously recognizes the emotions of both the sender and receiver.

[0676] Step 5: Based on the emotions recognized by the emotion engine, the generative AI suggests rewriting the text, and the system extracts and displays the information.

[0677] (Example 1)

[0678] Next, we will describe Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0679] In modern communication, it is essential that the sender's intended message is conveyed accurately and without misunderstanding. However, misinterpretations such as typos, inappropriate expressions, and misunderstandings of emotions often prevent the message from being conveyed as intended. Furthermore, recipients often struggle to grasp the main points when reading longer texts. To address these challenges, a system is needed to improve the accuracy and communicative power of written communication.

[0680] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0681] In this invention, the server includes means for using generative AI to point out typographical errors in the transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in pop-ups to facilitate the recipient's understanding; and means for using an emotion engine to recognize the sender's emotions and suggest rewriting the text in accordance with those emotions. As a result, the sender's intentions are accurately conveyed and the recipient can easily understand the text.

[0682] "Generative AI" is a type of artificial intelligence that uses natural language processing technology to analyze text, identify typos and grammatical errors, and rewrite sentences.

[0683] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[0684] "Advice" refers to suggestions or proposals offered to improve the clarity and ease of understanding of a piece of writing.

[0685] A "pop-up display" is an information window that is temporarily displayed on the screen, serving as a means of instantly conveying important information to the user.

[0686] An "emotion engine" is a technology that recognizes the sender's emotions from their text and suggests an appropriate response based on those emotions.

[0687] A "rewriting suggestion" is a proposal to change the original text to a more appropriate expression, and is made with the aim of improving the communication power of the text.

[0688] A "main point" refers to the particularly important or core content of a text or piece of information.

[0689] A "deadline" is the date on which a particular action or event is supposed to take place.

[0690] "Stakeholders" refers to individuals or organizations involved in a particular matter or event.

[0691] A description of embodiments for carrying out this invention will be given.

[0692] Users utilize a system integrated into internet search tools, email, and messenger apps. This system includes a program that combines generative AI and an emotion engine. When a user inputs text, the server receives the text and analyzes it using the generative AI. The generative AI utilizes natural language processing technology to detect and point out typos and grammatical errors in the text. It also provides advice to improve the clarity and ease of understanding of the text.

[0693] Furthermore, the server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the emotions in the input text and suggests rewriting the text according to those emotions. For example, if the user inputs "I am very dissatisfied with this matter," the generative AI and emotion engine will suggest something like "I hope for improvement regarding this matter."

[0694] For example, if a user inputs "Please change the meeting time," the server uses a generative AI model to analyze it and suggests a polite expression such as "Could you please change the meeting time?" Furthermore, if the emotion engine recognizes that the user is in a hurry, it will suggest something like, "I'm sorry to bother you, but could you please change the meeting time?"

[0695] An example of a prompt message might be: "Analyze the text entered by the user, point out typos and grammatical errors, and suggest rewrites that reflect the user's emotions."

[0696] The flow of the specific processing in Example 1 will be explained using Figure 17.

[0697] Step 1:

[0698] Users enter text into input fields in internet search tools, email, or messenger apps. This entered text becomes the starting point for system processing.

[0699] Step 2:

[0700] The server receives the text data entered by the user. It then prepares the received text to be passed as input to a generative AI model for analysis.

[0701] Step 3:

[0702] The server uses a generative AI model to analyze the structure and content of the input text. This analysis uses natural language processing techniques to detect typos and grammatical errors within the text. As a result of the analysis, information identifying typos and grammatical errors is output.

[0703] Step 4:

[0704] The server generates advice to improve the clarity of the text based on the analysis results of the AI ​​model. Specifically, it suggests rewriting the text to improve its politeness and clarity. This suggestion is then provided to the user as output.

[0705] Step 5:

[0706] The server uses an emotion engine to recognize emotions from the text entered by the user. The emotion engine analyzes words and expressions in the text to identify the user's emotional state. This emotional information is used to suggest rewriting in the next step.

[0707] Step 6:

[0708] The server suggests appropriate rewritings of the text based on the emotions it recognizes. For example, if anger is detected, it will suggest expressions that alleviate that emotion. These rewriting suggestions are then provided to the user as the final output.

[0709] Step 7:

[0710] The user reviews the suggestions from the server and revises the text as needed. After reviewing the final text, they submit or save it. This ensures that the text accurately conveys the user's intent.

[0711] (Application Example 1)

[0712] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0713] In modern communication, misunderstandings often arise due to typographical errors, grammatical mistakes, and inappropriate expressions. Furthermore, accurately conveying the sender's emotions is difficult, and in face-to-face customer service, appropriate responses tailored to the customer's feelings are crucial. To address these challenges, real-time text analysis and emotion recognition are necessary.

[0714] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0715] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services for easier understanding advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; a server that uses an emotion recognition engine to analyze the sender's emotions and proposes text rewriting appropriate to those emotions; and a server that converts voice input into text, identifies errors in the text in real time, and proposes appropriate expressions. This reduces misunderstandings of the text and makes it possible to appropriately convey the sender's emotions.

[0716] "Generative AI" is an artificial intelligence technology that analyzes input text and provides suggestions for improving it, such as pointing out typos and grammatical errors.

[0717] An "emotion recognition engine" is a technology that analyzes the sender's emotions and suggests appropriate written expressions that correspond to those emotions.

[0718] "Voice input" is an input method for converting speech into text data.

[0719] A "pop-up display" is a method of displaying a small window on the screen to instantly convey important information to the user.

[0720] "Real-time analysis" is a technology that processes input data instantly and provides results immediately.

[0721] The system for implementing this invention mainly consists of a server and a terminal. The server uses a generative AI model to analyze text input by the user and provides suggestions for correcting typos and suggesting improvements to the text. Specifically, the server uses OpenAI's GPT to analyze the input text data and suggest appropriate expressions. In addition, it uses IBM Watson's Tone Analyzer as an emotion recognition engine to analyze the user's emotions and suggest rewriting the text according to those emotions.

[0722] The terminal is a device such as smart glasses or a smartphone that accepts voice input. The voice input is converted to text using the Google Cloud Speech-to-Text API. The converted text is sent to a server and analyzed in real time. The analysis results are displayed as a pop-up on the terminal's display, providing the user with immediate feedback.

[0723] For example, if a user voice-inputs "This product is cheap," the generative AI will suggest a more polite expression such as "This product is reasonably priced." Also, if the emotion engine recognizes that the customer is dissatisfied, it will suggest an apology such as "We apologize for any inconvenience this may have caused."

[0724] An example of a prompt message might be, "Please suggest an appropriate apology if the customer is dissatisfied." This allows users to communicate more smoothly with customers.

[0725] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[0726] Step 1:

[0727] The user provides voice input to the device. The device uses the Google Cloud Speech-to-Text API to convert the voice data into text data. The input for this step is voice data, and the output is text data.

[0728] Step 2:

[0729] The terminal sends the converted text data to the server. The server analyzes the text data using OpenAI's GPT generative AI model. This analysis provides feedback on typos and grammatical errors, as well as suggestions for improving the text. The input is text data, and the output is feedback on typos and grammatical errors, along with suggestions for improvement.

[0730] Step 3:

[0731] The server uses IBM Watson's Tone Analyzer to analyze user sentiment from text data. The input is text data, and the output is the sentiment analysis result. Based on this result, suggestions for rewriting the text according to the sentiment are made.

[0732] Step 4:

[0733] The server sends the analysis results and improvement suggestions to the terminal. The terminal presents this information to the user as a pop-up display. The input is the analysis results and improvement suggestions, and the output is the feedback display to the user.

[0734] Step 5:

[0735] The user reviews the suggestions displayed on the device and modifies the text as needed. This enables the user to communicate more smoothly with customers. The input is feedback information, and the output is the modified text.

[0736] (Example 2)

[0737] Next, we will describe Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0738] In today's information society, recipients are required to efficiently understand and appropriately respond to a large volume of messages. However, it is difficult to understand long messages or complex texts in a short amount of time, and information is not provided in a way that suits the recipient's emotions, which can lead to misunderstandings and delayed responses. This results in challenges such as decreased work efficiency and communication breakdowns.

[0739] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0740] In this invention, the server includes means for using generative artificial intelligence to point out typographical errors in the transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and means for analyzing the recipient's emotions and extracting and displaying information according to those emotions. As a result, the recipient can quickly grasp the main points of the message and obtain appropriate information according to their emotions.

[0741] "Generative artificial intelligence" refers to an artificial intelligence system that uses natural language processing technology to identify typographical errors and grammatical mistakes in text and suggests improvements to the text.

[0742] A "pop-up display" is a visual notification method that instantly displays important information on the recipient's screen.

[0743] "Emotional analysis" is a technology that analyzes the emotional state of a recipient and provides appropriate information based on those emotions.

[0744] The "main point" refers to particularly important information or the main theme within a text, representing the core part that the recipient should understand.

[0745] A "deadline" refers to the period by which a specific action or response is required, and the date by which the recipient must take action.

[0746] "Stakeholders" refer to individuals or organizations related to a specific message or project, and are those with whom information sharing and cooperation are necessary.

[0747] This system's program provides a function that analyzes the content of a message received by the recipient, automatically extracting and displaying key points, deadlines, and information about relevant parties. Furthermore, it can analyze the recipient's emotions and extract and display information accordingly.

[0748] The server analyzes messages using natural language processing techniques. Specifically, it tokenizes text using Python's NLTK library and spaCy, and then analyzes the grammatical structure to extract key points, deadlines, and information about stakeholders. For sentiment analysis, it uses Python's TextBlob and the Google Cloud Natural Language API to determine the recipient's sentiment as positive, negative, or neutral.

[0749] The device displays the extracted information as a pop-up using JavaScript. This allows users to quickly grasp the main points of the message and receive appropriate information tailored to their emotions.

[0750] As a concrete example, if a user receives the message, "Please submit a project progress report by tomorrow. The relevant parties are A, B, and C," the device sends this message to the server. The server analyzes the message using spaCy, extracts "project progress report" as the key point, and recognizes "tomorrow" as the deadline. It also identifies "A, B, and C" as the relevant parties. If the emotion engine determines the user's emotion is "confused," the device will display a pop-up with the information "Key point: Project progress report, Deadline: Tomorrow, Relevant parties: A, B, C," and additional information such as "Here is the report template."

[0751] An example of a prompt to input into a generating AI model is: "Extract the key points, deadline, and stakeholders from the following message: 'Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C.'" By using this prompt, the AI ​​model can extract the necessary information and provide it to the user.

[0752] The flow of the specific processing in Example 2 will be explained using Figure 19.

[0753] Step 1:

[0754] The user receives a message. The terminal prepares to send the received message to the server. The input is the text message received by the user. The output is the message data to be analyzed and sent to the server.

[0755] Step 2:

[0756] The server analyzes received messages using natural language processing techniques. Specifically, it tokenizes text using Python's NLTK library and spaCy, and then analyzes the grammatical structure. The input is message data sent from the terminal. The output is the tokenized text and the analyzed grammatical structure.

[0757] Step 3:

[0758] The server extracts key points, deadlines, and stakeholders from the analyzed data. It uses regular expressions to identify dates and names and extract important keywords. Input consists of tokenized text and parsed grammatical structure. Output is the extracted key points, deadlines, and stakeholders.

[0759] Step 4:

[0760] The server uses a sentiment engine to analyze the sentiment of a message. It uses Python's TextBlob and the Google Cloud Natural Language API to determine whether the message is positive, negative, or neutral. The input is the message data. The output is the analyzed sentiment information.

[0761] Step 5:

[0762] The device displays the extracted information as a pop-up using JavaScript. If the sentiment engine determines that the user is confused, the device prioritizes displaying additional explanations and details. The input consists of extracted key points, deadlines, stakeholders, and sentiment information. The output is the pop-up information displayed to the user.

[0763] (Application Example 2)

[0764] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0765] In modern information and communication, recipients are required to understand large amounts of information quickly and accurately. However, information is often difficult to understand because it is not provided in a way that considers the recipient's emotional state. Furthermore, in transactions and important messages, recipients may experience anxiety or confusion, which hinders quick decision-making. To solve these problems, it is necessary to provide information that takes the recipient's emotions into consideration.

[0766] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0767] In this invention, the server includes means for using generative AI to point out typographical errors in transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in pop-ups to facilitate the recipient's understanding; and means for recognizing the recipient's emotions and extracting and displaying information according to those emotions. As a result, the recipient can quickly and accurately understand the information and obtain appropriate information according to their emotions.

[0768] "Generative AI" refers to artificial intelligence technology that uses natural language processing to generate and modify text.

[0769] "Error detection" is a function that detects incorrect or missing characters in a text and corrects them to their correct form.

[0770] "Easy-to-understand advice" refers to specific suggestions for improvement provided to make the recipient more easily understandable.

[0771] A "text rewriting service" is a service that transforms original text into clearer and more effective expressions.

[0772] The "main point" refers to the most important information or subject matter in a text, and is the core part that the recipient should understand.

[0773] A "deadline" is information that indicates the deadline by which a particular action or event must be completed.

[0774] "Stakeholders" refers to individuals or organizations associated with a particular document or message.

[0775] A "pop-up" is an information window that temporarily appears on the screen and is used to attract the user's attention.

[0776] "Recognizing the receiver's emotions" refers to the technology of determining the emotional state of the receiver from their facial expressions and voice.

[0777] "Information extraction and display" is the process of extracting necessary information from text and presenting it visually to the user.

[0778] The system for implementing this invention operates in a network environment including a server and user terminals. The server uses generative AI to identify typos and grammatical errors in the text sent by the user, and provides clearer advice and rewrites the text. Specifically, it uses Python and the natural language processing library spaCy to analyze and correct the text.

[0779] On the user's device, the system automatically extracts the key points, due date, and relevant information of received messages and displays them in a pop-up window. This utilizes front-end technology to receive analysis results from the server and display them on the user interface. Furthermore, TensorFlow is used to recognize the user's emotions and prioritize the display of information corresponding to those emotions. For example, if the user is feeling anxious, information regarding the security of the transaction will be prioritized.

[0780] For example, if a user receives the message, "¥10,000 has been withdrawn from your account. Please check," the system will display "Key points: Withdrawal of ¥10,000, Due date: Immediate, Parties involved: Financial institution." If the user is concerned, additional information such as, "This transaction is secure. Please see the support page for details," will be displayed.

[0781] An example of a prompt for the generating AI model is: "Analyze the transaction confirmation message and extract the key points. Also, provide suggestions for providing information that is tailored to the user's emotions."

[0782] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[0783] Step 1:

[0784] The server receives text sent by the user. Using this text as input, it uses a generative AI to detect typos and grammatical errors. Specifically, it analyzes the text using the natural language processing library spaCy to identify typos and grammatical errors. The output is a list of the errors and suggested corrections.

[0785] Step 2:

[0786] The server provides the user with suggested revisions generated by a generative AI. The user then revises the text based on these suggestions. The revised text is sent back to the server. The input is the suggested revisions, and the output is the text revised by the user.

[0787] Step 3:

[0788] The server receives the revised text and extracts information on key points, deadlines, and stakeholders. This process involves analyzing the text again using spaCy to identify important information. The input is the revised text, and the output is the extracted information.

[0789] Step 4:

[0790] The server sends the extracted information to the user's terminal. The terminal displays this information as a pop-up on its user interface. The input is the extracted information, and the output is the information visually presented to the user.

[0791] Step 5:

[0792] The device uses TensorFlow to analyze the user's facial expressions and voice in order to recognize the user's emotions. The input is the user's facial expressions and voice data, and the output is the recognized emotional state.

[0793] Step 6:

[0794] The device adjusts the information displayed based on the recognized emotion. For example, if the user is feeling anxious, it prioritizes displaying information related to the security of the transaction. The input is the recognized emotional state, and the output is the adjusted information display.

[0795] (Example 3)

[0796] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0797] In modern information and communication, there are challenges such as errors in transmitted information and difficulty for recipients to quickly grasp the main points of the information. Furthermore, a lack of communication that considers the feelings of both senders and receivers can lead to misunderstandings and inappropriate responses. Systems are needed to address these challenges.

[0798] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0799] In this invention, the server includes means for pointing out errors in transmitted information using generative artificial intelligence and providing easily understandable advice and information correction services; means for displaying the main points, deadlines, and relevant parties of long information on a display device to facilitate the recipient's understanding; and means for analyzing the emotions of the sender and recipient and providing appropriate expressions and information based on that analysis. This improves the accuracy of information, allows recipients to quickly grasp the main points of the information, and enables appropriate communication that responds to emotions.

[0800] "Generative artificial intelligence" is an artificial intelligence technology that uses input information to identify and correct errors and provide advice.

[0801] A "display device" is a device that allows a recipient to visually confirm information.

[0802] "Analyzing emotions" is the process of analyzing the emotional states of both the sender and receiver and using that analysis to determine an appropriate response.

[0803] "Key points" refer to the particularly important or core content of information.

[0804] "Deadline" refers to a specific date, time, or deadline related to information.

[0805] "Stakeholders" refers to individuals or organizations related to the information.

[0806] This invention is a system for improving the transmission and reception processes in information communication. The server uses generative artificial intelligence to identify errors in transmitted information and provides clearer advice and corrections. Specifically, it uses a natural language processing library to analyze input information and detect typos, grammatical errors, and inappropriate expressions. This allows users to improve the accuracy of the information they receive.

[0807] Furthermore, the server extracts the key points, deadlines, and stakeholders of long pieces of information so that recipients can quickly understand them, and displays them as pop-ups on the terminal's display. This process uses natural language processing technology. For example, if a recipient receives the information, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the server extracts and displays the information, "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C."

[0808] The server also analyzes the emotions of both the sender and receiver and provides appropriate expressions and information based on that analysis. It uses an emotion analysis API for this analysis. For example, if the server recognizes that the sender is angry and the receiver is confused, it will suggest appropriate expressions to the sender and provide the receiver with information to aid understanding.

[0809] As a concrete example, an example of a prompt sentence to be input to the generating AI model is shown: "Extract the main points of the message received by the recipient, analyze the sentiment, and suggest an appropriate response." By using this prompt, the system can provide the recipient with information quickly and appropriately. The flow of specific processing in Example 3 will be explained using Figure 21.

[0810] Step 1:

[0811] The user receives information via email or messaging apps. The device prepares to send the received information to the server. The input is the text information received by the user, and the output is the data to be analyzed that is sent to the server.

[0812] Step 2:

[0813] The server uses a natural language processing library to analyze the received information. Specifically, it tokenizes the text data and extracts important keywords and phrases. The input is text data sent from the terminal, and the output is extracted information such as key points, deadlines, and stakeholders.

[0814] Step 3:

[0815] The server uses Google Cloud's sentiment analysis API to analyze the sentiments of both the sender and receiver. The input is the received text data, and the output is the result of the sentiment analysis. Based on the sentiment analysis results, the server determines the appropriate response.

[0816] Step 4:

[0817] The server displays a pop-up on the recipient's device based on the extracted information and sentiment analysis results. The device displays the pop-up, allowing the user to quickly grasp key points, deadlines, and relevant information. The input is the information sent from the server, and the output is the pop-up information displayed on the device.

[0818] Step 5:

[0819] The server inputs a prompt sentence into a generative AI model and generates an appropriate response. The input consists of the prompt sentence and the analysis result, while the output is the generated response. The server provides the generated response to the recipient, facilitating smooth communication.

[0820] (Application Example 3)

[0821] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0822] In today's information society, there is a growing demand for increased efficiency in electronic transactions and communication. However, quickly grasping important transaction information and engaging in appropriate communication that considers emotions is not easy. In particular, there is a need for a system that enables quick understanding of the key points of transaction notifications and supports communication that takes into account the feelings of both the sender and the receiver.

[0823] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[0824] In this invention, the server includes means for using generative AI to point out typographical errors in transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in pop-ups to facilitate the recipient's understanding; means for analyzing the emotions of the sender and receiver and supporting emotion-appropriate communication; and means for automatically extracting and displaying the main points of an electronic transaction when a notification regarding the transaction is received. This enables rapid understanding of transaction information and support for emotion-conscious communication.

[0825] "Generative AI" refers to artificial intelligence that uses natural language processing technology to generate and modify text.

[0826] "Error detection" is a function that detects incorrect or missing characters in a text and suggests corrections.

[0827] "Easy-to-understand advice" is a function that provides suggestions for improvement to make the text easier for the recipient to understand.

[0828] A "text rewriting service" is a service that transforms the original text into a clearer and more concise expression.

[0829] "Pop-up display" is a function that displays a small window on the screen to instantly present important information.

[0830] "Automatic extraction of key points, deadlines, and relevant information" refers to a technology that automatically extracts and displays important information from a document.

[0831] "Means of analyzing emotions and supporting emotion-based communication" refers to a function that analyzes the emotions of the sender and receiver and facilitates appropriate communication based on that analysis.

[0832] A "notice regarding electronic transactions" is a message that contains information about electronic transactions.

[0833] "A means of automatically extracting and displaying the key points of a transaction" refers to a function that automatically extracts important information from transaction notifications and presents it to the user.

[0834] The system for implementing this invention mainly consists of a server and a user terminal. The server uses generative AI to identify typos and grammatical errors in the text sent by the user, and provides clearer advice and rewrites the text. The user terminal displays the main points, deadlines, and information about relevant parties in pop-ups to facilitate user understanding. Furthermore, the server analyzes the emotions of the sender and receiver and supports communication that is appropriate to those emotions.

[0835] Specifically, the server uses a natural language processing library (e.g., spaCy) to detect typos and grammatical errors from text and extract key points. For sentiment analysis, a sentiment analysis library (e.g., TextBlob) is used to analyze the emotions of the sender and receiver. A generative AI model (e.g., OpenAI GPT) generates communication suggestions that are appropriate to the emotions.

[0836] For example, when a user receives a notification about an electronic transaction, the server automatically extracts the key points of the transaction (transaction amount, due date, and parties involved) and displays them as a pop-up on the user's terminal. Furthermore, based on sentiment analysis, if the sender appears to be feeling anxious, the server suggests that they should make an effort to provide a more thorough explanation to the user.

[0837] An example of a prompt message is, "Extract the key points of this transaction notification and analyze the sentiment of the sender and recipient."

[0838] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[0839] Step 1:

[0840] The server receives notifications from users regarding electronic transactions. The input is the text data of the transaction notification. Based on this data, a natural language processing library (e.g., spaCy) is used to analyze the sentence structure. The output is the structural information of the analyzed sentence.

[0841] Step 2:

[0842] The server uses the structural information of the analyzed text to extract the key points of the transaction (transaction amount, due date, parties involved). The input is the structural information obtained in step 1. As part of the data processing, specific keywords and phrases are identified and key points are extracted. The output is the extracted key points information.

[0843] Step 3:

[0844] The server analyzes the emotions of the sender and receiver using an emotion analysis library (e.g., TextBlob). The input is the text data of the transaction notification. As a data calculation, it calculates an emotion score from the text and identifies the type of emotion. The output is the emotion information of the sender and receiver.

[0845] Step 4:

[0846] The server uses a generative AI model (e.g., OpenAI GPT) to generate emotion-based communication suggestions. The input is the emotion information obtained in step 3. As a data processing step, it generates appropriate communication phrases based on the emotion information. The output is the generated communication suggestions.

[0847] Step 5:

[0848] The terminal displays key information and communication proposals received from the server as a pop-up. The input consists of the key information obtained in step 2 and the communication proposals obtained in step 4. Specifically, a pop-up window is displayed on the user's screen, immediately presenting the important information. The output is the information presented to the user.

[0849] (Other examples)

[0850] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[0851] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0852] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0853] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[0854] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0855] [Third Embodiment]

[0856] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0857] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0858] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0859] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0860] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0861] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0862] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0863] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0864] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0865] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0866] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0867] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[0868] "Example of form 1"

[0869] One embodiment of this system is one that can be integrated into internet search tools, email, and messenger applications. This system uses generative AI to analyze the text entered by the sender and points out typos and grammatical errors. Furthermore, it provides advice to improve the clarity of the text and suggests rewriting it as needed. Specifically, if the sender enters "Please submit the report by tomorrow," the generative AI will suggest rewriting it to a more polite expression such as "Please submit the report by tomorrow."

[0870] "Example of form 2"

[0871] Furthermore, for recipients, there is a feature that analyzes the content of received messages, automatically extracts key points, deadlines, and information about stakeholders, and displays them in a pop-up window. Specifically, if a recipient receives a message that says, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the system will display a pop-up window with the following information: "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C." This allows the recipient to quickly grasp the main points of the message.

[0872] "Example of form 3"

[0873] Furthermore, for recipients, there is a feature that analyzes the content of received messages, automatically extracts key points, deadlines, and information about stakeholders, and displays them in a pop-up window. Specifically, if a recipient receives a message that says, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the system will display a pop-up window with the following information: "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C." This allows the recipient to quickly grasp the main points of the message.

[0874] The following describes the processing flow for each example of the form.

[0875] "Example of form 1"

[0876] Step 1: The sender types the message into an internet search tool, email, or messenger app.

[0877] Step 2: The generative AI analyzes the input text and points out typos and grammatical errors.

[0878] Step 3: The generative AI provides advice to improve the clarity of the text.

[0879] Step 4: If necessary, the generative AI will suggest rewriting the text.

[0880] "Example of form 2"

[0881] Step 1: The recipient receives the message.

[0882] Step 2: The system analyzes the content of the received text.

[0883] Step 3: The system automatically extracts key points, deadlines, and information about stakeholders.

[0884] Step 4: The system will display the extracted information in a pop-up window.

[0885] (Example 1)

[0886] Next, we will describe Embodiment 1 of Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0887] In modern communication, misunderstandings often arise due to typographical errors, grammatical mistakes, and unclear writing. Furthermore, long texts can bury key points and important information, making them difficult for recipients to understand. There is a need to address these challenges and achieve more effective communication.

[0888] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0889] In this invention, the server includes means for pointing out typographical errors and grammatical errors in transmitted text using generative artificial intelligence and providing services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts on a display device to facilitate the recipient's understanding; and means for analyzing text input by the user and using generative artificial intelligence to detect typographical errors and suggest improvements to the text. This makes it possible to improve the quality of text and clarify information.

[0890] "Generative artificial intelligence" is a technology that uses natural language processing to analyze text and point out typos and grammatical errors, as well as suggest improvements to the text.

[0891] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[0892] "Easy-to-understand advice" refers to suggestions that make the content of a document clearer and easier to understand, thereby facilitating the smooth transmission of information to the recipient.

[0893] A "rewriting service" is a function that improves the expression of a text and corrects it to a more appropriate form.

[0894] A "display device" is a device used to visually display information, and is used by recipients to confirm that information.

[0895] "Key points" refer to the particularly important parts of a text or piece of information, representing the main content that the recipient should understand.

[0896] A "deadline" refers to the date on which a specific action or event should take place, and is important information in schedule management.

[0897] "Stakeholders" refers to individuals or organizations related to a particular document or piece of information, and are those that the recipient of the information should be aware of.

[0898] "Analysis" is the process of thoroughly examining text and data to understand their structure and meaning.

[0899] The following systems are conceivable as embodiments for carrying out this invention.

[0900] The server uses generative artificial intelligence to analyze the text entered by the user. This analysis utilizes natural language processing technology to detect typos and grammatical errors and suggest improvements to the text. Specifically, a general-purpose natural language processing engine can be used as the generative AI model. For example, open-source natural language processing libraries or commercial AI platforms can be used.

[0901] The terminal sends the text entered by the user to the server. A secure communication protocol is used to transmit the data and protect the user's privacy. The server inputs the received text into a generation AI model to create a prompt. An example of a prompt is: "Please analyze the following text, identify any typos or grammatical errors, and provide suggestions for improvement:"

[0902] The generative AI model analyzes the input text and not only points out typos and grammatical errors, but also provides advice to improve the clarity of the writing. For example, if a user inputs "Please submit the report by tomorrow," the generative AI model will suggest rewriting it into a more polite expression such as "Please submit the report by tomorrow."

[0903] In this way, users can improve the quality of their writing and achieve unambiguous communication by utilizing generative artificial intelligence.

[0904] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0905] Step 1:

[0906] Users input text through internet search tools, email, or messenger apps. This entered text becomes the data subject to typographical error checking and suggestions for improving the text.

[0907] Step 2:

[0908] The terminal sends the text entered by the user to the server. This data is transmitted using a secure communication protocol. The input is the user's text, and the output is the secure transmission of data to the server.

[0909] Step 3:

[0910] The server inputs the received text into the generative AI model. Specifically, it creates a prompt message and inputs it to the generative AI model in the format of "Please analyze the following text, point out any typos or grammatical errors, and provide suggestions for improvement:". The input is the user's text, and the output is the prompt message to the generative AI model.

[0911] Step 4:

[0912] The generative AI model analyzes text based on the input prompt sentence. It detects typos and grammatical errors and generates advice and rewriting suggestions to improve the clarity of the text. The input is the prompt sentence, and the output is the analysis result and improvement suggestions.

[0913] Step 5:

[0914] The server sends the analysis results and improvement suggestions obtained from the generated AI model to the terminal. The input is the output of the generated AI model, and the output is the transmission of data to the terminal.

[0915] Step 6:

[0916] The terminal displays analysis results and improvement suggestions received from the server to the user. The user can then use this information to revise their text. The input is data from the server, and the output is information displayed to the user.

[0917] (Application Example 1)

[0918] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0919] In modern communication, typographical errors and inappropriate expressions can hinder information transmission. Furthermore, in customer service roles at physical stores, the ability to instantly select appropriate expressions during conversations with customers is crucial, but there is a lack of technology to support this. To address these challenges, a system is needed that analyzes written and spoken content in real time and suggests appropriate expressions.

[0920] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0921] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services such as easy-to-understand advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and a server that uses speech recognition technology to convert speech into text, generates appropriate expressions using generative AI, and presents them on a display device. This makes it possible to analyze the content of text and audio in real time and suggest appropriate expressions.

[0922] "Generative AI" is an artificial intelligence technology that analyzes input data and generates appropriate sentences and expressions through natural language processing.

[0923] "Typographical errors" refer to mistakes or omissions in text, and are factors that hinder the accurate transmission of information.

[0924] A "pop-up display" refers to a window or message that temporarily appears on the screen to highlight information within the user interface.

[0925] "Speech recognition technology" is a technology that analyzes speech as a digital signal and converts it into corresponding text data.

[0926] A "display device" is hardware used to visually present generated information or data, and includes displays and screens.

[0927] The system for implementing this invention involves a server and a terminal working in conjunction. The server uses generative AI to identify typos and grammatical errors in transmitted text, and provides clearer advice and rewrites the text. Furthermore, it displays key points, deadlines, and relevant parties in pop-ups for longer texts to facilitate the recipient's understanding.

[0928] The device uses speech recognition technology to convert speech into text, generates appropriate expressions using generative AI, and displays them on a display device. Specifically, the generated information is visually presented to the user using a display device such as smart glasses or a smartphone.

[0929] For example, in a physical store, if a user asks, "Does this product come in other colors?", the terminal uses speech recognition technology to convert this question into text and send it to the server. The server then uses generative AI to generate an appropriate response, such as, "This product is available in other colors. Which color would you prefer?", and displays it on the terminal's display.

[0930] An example of a prompt is, "A customer is asking about the color of a product. Please suggest a polite response." By inputting this prompt into a generative AI, an appropriate response will be generated.

[0931] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0932] Step 1:

[0933] The device acquires the user's voice input through the microphone. The input is the voice data spoken by the user. The device converts this voice data into text data using speech recognition technology (e.g., Google Cloud Speech-to-Text). The output is text data that represents the user's speech as a string of characters.

[0934] Step 2:

[0935] The terminal sends the converted text data to the server. The server inputs the received text data into a generative AI model (e.g., OpenAI's GPT-3). The input is text data representing the user's utterance. The server uses the generative AI model to perform data calculations to generate an appropriate response. The output is the text data of the generated appropriate response.

[0936] Step 3:

[0937] The server sends the generated response as text data to the terminal. The terminal displays the received response on a display device (e.g., smart glasses or smartphone display). The input is the text data of the response sent from the server. The terminal processes the data to present the information visually to the user and provides a response that is displayed to the user as output.

[0938] Step 4:

[0939] The user confirms the displayed response and continues the conversation as needed. The user's confirmation triggers the next voice input, and the process from step 1 is repeated. The input is the displayed response, and the output is the user's understanding and next action.

[0940] (Example 2)

[0941] Next, we will describe Example 2 of the morphological example. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0942] In modern information and communication, it is difficult for recipients to quickly and accurately understand lengthy information. Furthermore, while it is crucial for senders to provide clear information free from typos and grammatical errors, doing so manually is time-consuming and laborious. To address these challenges, a system is needed that automatically extracts key points, deadlines, and stakeholders, and presents them clearly to the recipient.

[0943] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0944] In this invention, the server includes means for pointing out typographical errors in transmitted information using generative artificial intelligence and providing easy-to-understand advice and information rewriting services; means for displaying the main points, deadlines, and relevant parties of long information on a display device to facilitate the recipient's understanding; and means for analyzing received information and automatically extracting information on main points, deadlines, and relevant parties. As a result, the recipient can quickly grasp the main points of the information, and the sender can provide clear information free from typographical errors.

[0945] "Generative artificial intelligence" is a type of artificial intelligence that uses natural language processing technology to analyze and generate information.

[0946] "Typographical errors" refer to incorrectly written or missing characters in information.

[0947] "Advice" refers to instructions or suggestions provided to improve or facilitate understanding of information.

[0948] "Rewriting information" is the act of modifying information to make its content clearer and easier to understand.

[0949] A "key point" refers to the particularly important or core content of information.

[0950] "Deadline" refers to a specific date, time, or period related to information.

[0951] "Stakeholders" refers to individuals or organizations related to the information.

[0952] A "display device" is a device or interface used to present information visually.

[0953] "Analysis" is the process of breaking down information and understanding its structure and meaning.

[0954] "Extraction" is the act of taking out specific elements or data from information.

[0955] As an embodiment of this invention, the following system is constructed.

[0956] The server analyzes the received information using a generative AI model. A model that utilizes natural language processing technology is suitable for this generative AI model, and specifically, OpenAI's GPT model can be used. The server inputs the received information into the generative AI model and gives it a prompt message such as, "Extract the main points, deadlines, and stakeholders from this text." Based on this prompt message, the generative AI model analyzes the information and extracts the main points, deadlines, and stakeholders.

[0957] The terminal receives analysis results sent from the server and presents them to the user via a display device. Specifically, it uses a pop-up display to visually show information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C." This allows the user to quickly grasp the important parts of the received information.

[0958] Users can provide clear instructions as prompts to input into the generating AI model. For example, by using a prompt such as, "Extract the main points, deadlines, and stakeholders from this document," the system can efficiently extract and provide information to the user. In this way, recipients of the information can quickly understand the important information, and senders can provide clear information free from typos and grammatical errors.

[0959] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0960] Step 1:

[0961] The user receives information via email or messaging apps. The device detects this received information and prepares to send it to the server. The input is the received information, and the output is the transfer of information to the server. Specifically, the device sends information to the server triggered by the receipt of a new message.

[0962] Step 2:

[0963] The server inputs the received information into a generative AI model. This generative AI model utilizes natural language processing technology. The input consists of the received information and the prompt "Extract the main points, deadlines, and stakeholders from this text," and the output is the analysis result. Specifically, the server passes the information to the generative AI model, which then analyzes the information based on the prompt.

[0964] Step 3:

[0965] The server receives the analysis results returned from the generative AI model. The input is the analysis results from the generative AI model, and the output is the transmission of the analysis results to the terminal. Specifically, the server temporarily stores the analysis results in a database and prepares them for transmission to the terminal.

[0966] Step 4:

[0967] The terminal receives analysis results sent from the server and displays them to the user. The input is the analysis results from the server, and the output is a visual presentation of information to the user. Specifically, the terminal uses a pop-up display to show information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C" on the screen.

[0968] This series of processes allows users to quickly grasp the key points of the information they receive.

[0969] (Application Example 2)

[0970] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0971] In today's information society, there is a demand for quick identification of typographical errors and grammatical mistakes in written texts, as well as the ability to quickly grasp key points. However, particularly in factories, there is a lack of efficient means to quickly and accurately understand the contents of work instructions and progress reports. This can lead to delays and misunderstandings in work.

[0972] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0973] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services such as easy-to-understand advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and a server that is installed on machines used in factories to analyze work instructions and progress reports and display the main points. This reduces errors in text and enables quick grasp of key points.

[0974] "Generative AI" is an artificial intelligence technology that identifies typos and grammatical errors in text, provides clearer advice, and rewrites the text.

[0975] "Pop-up display" is a function that automatically displays key points, deadlines, and information about relevant parties on the screen based on the content of the document the recipient is viewing.

[0976] "Machinery used within a factory" refers to devices used in the factory work environment to analyze work instructions and progress reports and display key points.

[0977] A "work instruction sheet" is a document that describes the content and procedures of work within a factory, and is intended to provide specific instructions to workers.

[0978] A "progress report" is a document used to report on the progress of a project or task, and its purpose is to allow stakeholders to understand the current situation.

[0979] The system for implementing this invention consists of three elements: a server, a terminal, and a user. The server uses generative AI to identify typos and grammatical errors in transmitted text, and provides clearer advice and rewrites the text. It also displays the main points, deadlines, and relevant parties in pop-ups for longer texts to facilitate the recipient's understanding. Furthermore, it is installed on machinery used in factories and has the function of analyzing work instructions and progress reports and displaying key points.

[0980] This system is implemented using Python and utilizes natural language processing libraries such as NLTK and spaCy. The server analyzes received text, extracts keywords and recognizes dates, and extracts key points. The extracted information is displayed as a pop-up on the terminal's screen. Specifically, it tokenizes the text, tags it with parts of speech, and extracts key points, primarily focusing on nouns and verbs.

[0981] For example, if a user receives the instruction, "Please complete the assembly of part A by tomorrow. The responsible persons are D and E," the server will display a pop-up message on the terminal with the following information: "Key points: Assembly of part A, Deadline: Tomorrow, Responsible persons: D and E."

[0982] Examples of prompt statements to input into a generative AI model include the following:

[0983] "Please extract the key points, deadlines, and relevant parties from the following text: 'Please complete the assembly of part A by tomorrow. The responsible parties are Mr. D and Mr. E.'"

[0984] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0985] Step 1:

[0986] The server retrieves text received from the user. This input is an instruction, such as, "Please complete the assembly of part A by tomorrow. The responsible persons are Mr. D and Mr. E." The server then prepares this text for natural language processing.

[0987] Step 2:

[0988] The server uses natural language processing libraries such as NLTK and spaCy to tokenize and tag the received text by part of speech. This process classifies the words in the text into their respective parts of speech, identifying elements such as nouns and verbs. This provides the basic data needed for extracting key points.

[0989] Step 3:

[0990] The server extracts keywords and recognizes dates based on the tokenized data. Specifically, it extracts important information, primarily nouns, and identifies date-related information. The output of this step is summary information, such as "Key point: Assemble part A, Due date: Tomorrow, Person in charge: Mr. D, Mr. E."

[0991] Step 4:

[0992] The server sends the extracted summary information to the terminal, which then displays the information as a pop-up. This allows the user to quickly grasp the main points of the instructions. The terminal's display visually shows the main points, deadlines, and relevant parties.

[0993] (Example 3)

[0994] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0995] In today's information society, the exchange of emails and digital documents is increasing, but these documents often contain typos and grammatical errors, and key points and important information can get lost. Therefore, senders are required to create accurate and easy-to-understand documents, and recipients are required to quickly grasp the important information within the document. However, these tasks are time-consuming and difficult to perform efficiently.

[0996] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[0997] In this invention, the server includes means for using generative artificial intelligence to identify typographical errors in documents being sent and providing services such as easy-to-understand advice and document rewriting; means for displaying key points, deadlines, and relevant parties in pop-ups for long documents to facilitate the recipient's understanding; and means for analyzing the content of received documents, automatically extracting key points, deadlines, and relevant parties, and presenting them visually. As a result, senders can create accurate and easy-to-understand documents, and recipients can quickly grasp the important information in the document.

[0998] "Generative artificial intelligence" is an artificial intelligence technology that uses natural language processing techniques to identify typographical errors and omissions in documents, and to rewrite documents.

[0999] A "document" refers to text information created in email or digital format, and is a medium of information exchanged between a sender and a recipient.

[1000] "Typographical errors" refer to spelling mistakes or omissions of inappropriate characters within a document, and are factors that impair the accuracy of the document.

[1001] "Key points" refer to information or topics that are considered particularly important within a document, and are the content that the recipient should quickly understand.

[1002] A "deadline" refers to a specific date and time specified within a document, and is information by which the recipient must take action.

[1003] "Stakeholders" refers to specific individuals or organizations mentioned within a document, who are important parties related to the content of the document.

[1004] A "pop-up" refers to a window that temporarily appears on a computer screen, and is a means of immediately presenting important information to the user.

[1005] "Presenting visually" refers to displaying information graphically on a screen so that users can easily understand it.

[1006] This invention provides a system that enables both the sender and receiver to efficiently process information during email and digital document exchanges. Specific embodiments of this system are described below.

[1007] The server uses generative artificial intelligence to identify typos and grammatical errors in documents entered by the sender, and provides clearer feedback and rewrites the document. This process utilizes natural language processing technology, employing software such as Google Cloud Natural Language API and IBM Watson Natural Language Understanding. This enables senders to create accurate and effective documents.

[1008] Furthermore, the server analyzes the content of received documents and automatically extracts key points, deadlines, and information about relevant parties. This analysis uses text analysis algorithms to identify important information within the document. The extracted information is visually presented as a pop-up window on the terminal. This allows recipients to quickly grasp the important information in the document.

[1009] For example, if a user receives a document that says, "Please submit a report on the project's progress by tomorrow. The relevant parties are A, B, and C," the server will extract the information "Key points: Project progress report, Deadline: Tomorrow, Relevant parties: A, B, C," and the terminal will display this as a pop-up.

[1010] An example of a prompt for a generative AI model is: "Extract the key points, deadline, and stakeholders from the following text: 'Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C.'"

[1011] In this way, the system provides a means for both the sender and the receiver to streamline the creation and understanding of documents. The flow of a specific process in Example 3 will be explained with reference to Figure 15.

[1012] Step 1:

[1013] The user receives an email.

[1014] The user receives a new email using their email client. The text data of the email is provided as input. The email content is sent to the server as output.

[1015] Step 2:

[1016] The server analyzes the content of the email.

[1017] The server analyzes the text data of received emails using natural language processing techniques. Specifically, it uses a generative AI model to understand the grammatical structure and meaning of the emails. The input is the text data of the emails, and the output is structural information of the analyzed document.

[1018] Step 3:

[1019] The server extracts key points, deadlines, and stakeholders.

[1020] The server automatically extracts key points, deadlines, and relevant information from emails based on the analysis results. It uses text analysis algorithms to identify specific keywords and phrases. Structural information from the analyzed document is used as input, and the extracted key information is generated as output.

[1021] Step 4:

[1022] The device displays information in a pop-up window.

[1023] The terminal receives extracted information sent from the server and displays it to the user as a pop-up window. Specifically, information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C" is visually presented on the screen. The input is the extracted key information, and the output is the visual presentation of that information to the user.

[1024] In this way, the system provides users with a means to quickly grasp important information in emails.

[1025] (Application Example 3)

[1026] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1027] In today's information society, vast amounts of information are sent and received daily via email and notifications. Among these, information related to electronic transactions, in particular, requires rapid and accurate understanding. However, traditional methods involve time-consuming information organization and verification, potentially leading to the oversight of crucial details. This can result in transaction delays and misunderstandings, posing a significant challenge.

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

[1029] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services such as easy-to-understand advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and a server that analyzes information related to electronic transactions, automatically extracts payment due dates, amounts, and trading partner information, and displays this information to the user in a pop-up. This enables the user to quickly grasp important transaction information and take appropriate action.

[1030] "Generative AI" refers to artificial intelligence systems that use natural language processing technology to generate and modify text.

[1031] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[1032] A "pop-up display" is a method of instantly displaying information on a user interface and is used to attract the user's attention.

[1033] "Key points" refer to the particularly important parts of a text or piece of information, and are extracted to aid understanding.

[1034] A "deadline" refers to the date by which a specific action or payment must be completed, and is important in schedule management.

[1035] "Stakeholders" refer to individuals or organizations involved in a particular project or transaction, and are important for information sharing and decision-making.

[1036] "Electronic transactions" refer to commercial transactions conducted via the internet or electronic devices, and are common in modern business.

[1037] The "payment due date" refers to the date on which payment for a transaction should be completed, and is important for contract fulfillment.

[1038] "Amount" refers to the quantity of money to be paid in a transaction or contract, and indicates the terms of the transaction.

[1039] A "business partner" refers to a company or individual that is the counterparty in a commercial transaction, and is important in building business relationships.

[1040] The system for implementing this invention consists of a server and a user terminal. The server uses generative AI to identify typographical errors and grammatical mistakes in the text sent by the user, and provides clearer advice and rewrites the text. Furthermore, the server automatically extracts the main points, deadlines, and information of relevant parties from the received text and displays them as a pop-up on the user terminal. This allows the user to quickly grasp the important information in the text.

[1041] The server also analyzes information related to electronic transactions, extracting payment due dates, amounts, and trading partners. This information is displayed as a pop-up on the user's terminal, allowing the user to instantly verify the transaction details. This helps prevent transaction delays and misunderstandings.

[1042] This system utilizes natural language processing (NLP) technology. Specifically, it uses NLP libraries such as "spaCy" and "NLTK" to analyze text and extract information. User terminals include devices such as smartphones and smart glasses, and are equipped with a user interface for displaying pop-up information.

[1043] For example, if a user receives an email stating, "I have received an invoice. The payment due date is next Friday, and the amount is 100,000 yen. The client is ABC Corporation," the server will extract the information "Payment due date: next Friday, Amount: 100,000 yen, Client: ABC Corporation" and display it as a pop-up on the user's terminal. An example of a prompt to input into the generating AI model would be, "Please extract the payment due date, amount, and client from this email."

[1044] The flow of the specific processing in Application Example 3 will be explained using Figure 16.

[1045] Step 1:

[1046] The server receives text data from user terminals, such as emails and notifications. This input data contains information about transactions. The server prepares to use natural language processing techniques to analyze this text data.

[1047] Step 2:

[1048] The server uses the NLP library "spaCy" or "NLTK" to parse the received text data. Specifically, it extracts payment due dates, amounts, and customer information from the text. This process analyzes the grammatical structure of the text and extracts the necessary information by identifying specific keywords and patterns. The input is text data, and the output is a set of extracted information.

[1049] Step 3:

[1050] The server organizes the extracted information and converts it into a data format for transmission to the user's terminal. This format conversion ensures that the information is presented in a way that is easy for the user to understand. The input is a set of extracted information, and the output is the formatted information.

[1051] Step 4:

[1052] The user terminal receives formatted information sent from the server. The terminal then launches a user interface to display this information as a pop-up. Specifically, it displays payment due dates, amounts, and customer information on the screen to attract the user's attention. The input is formatted information, and the output is a pop-up display.

[1053] Step 5:

[1054] Users can quickly grasp transaction information by checking the pop-up displayed on their device. This allows users to take the necessary actions immediately. The input is the information displayed in the pop-up, and the output is the user's understanding and actions.

[1055] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1056] "Example of form 1"

[1057] One embodiment of the present invention involves a system that combines a generative AI with an emotion engine that recognizes the sender's emotions. In this system, when the sender inputs text, the generative AI analyzes the text. Based on the analysis, it points out any typos or grammatical errors and provides advice to improve the clarity of the text. Furthermore, the emotion engine recognizes the sender's emotions and suggests rewriting the text according to those emotions. For example, if it recognizes that the sender is angry, it suggests rewriting the text to appropriately convey that emotion.

[1058] "Example of form 2"

[1059] Furthermore, some recipient-side services also incorporate an emotion engine. In this system, when a recipient receives a message, the system analyzes its content. Based on the analysis, it automatically extracts key points, deadlines, and information about relevant parties, and displays them in a pop-up window. In addition, the emotion engine recognizes the recipient's emotions and extracts and displays information accordingly. For example, if the system recognizes that the recipient is feeling confused, it prioritizes extracting and displaying information that will alleviate that emotion.

[1060] "Example of form 3"

[1061] Furthermore, there are systems that combine generative AI and pop-up displays with emotion engines. These systems simultaneously consider the emotions of both the sender and receiver, supporting communication tailored to each emotion. For example, if the system recognizes that the sender is angry and the receiver is confused, it takes both emotions into consideration and suggests appropriate expressions to the sender while displaying information to aid understanding to the receiver.

[1062] The following describes the processing flow for each example of the form.

[1063] "Example of form 1"

[1064] Step 1: The sender enters the message.

[1065] Step 2: The generative AI analyzes the input text and points out typos and grammatical errors.

[1066] Step 3: The generative AI provides advice to improve the clarity of the text.

[1067] Step 4: The emotion engine recognizes the sender's emotions.

[1068] Step 5: Based on the emotions recognized by the emotion engine, the generative AI suggests rewriting the text.

[1069] "Example of form 2"

[1070] Step 1: The recipient receives the message.

[1071] Step 2: The system analyzes the content of the received message.

[1072] Step 3: The system extracts key points, deadlines, and stakeholders from the analysis results and displays them in a pop-up window.

[1073] Step 4: The emotion engine recognizes the recipient's emotions.

[1074] Step 5: Based on the emotions recognized by the emotion engine, the system extracts and displays information.

[1075] "Example of form 3"

[1076] Step 1: The sender types the message, and the recipient receives the message.

[1077] Step 2: The generative AI analyzes the input text and points out typos and grammatical errors. At the same time, the system analyzes the content of the received message.

[1078] Step 3: The generative AI provides advice to improve the clarity of the text. At the same time, the system extracts key points, deadlines, and stakeholders from the analysis results and displays them in a pop-up window.

[1079] Step 4: The emotion engine simultaneously recognizes the emotions of both the sender and receiver.

[1080] Step 5: Based on the emotions recognized by the emotion engine, the generative AI suggests rewriting the text, and the system extracts and displays the information.

[1081] (Example 1)

[1082] Next, we will describe Embodiment 1 of Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1083] In modern communication, it is essential that the sender's intended message is conveyed accurately and without misunderstanding. However, misinterpretations such as typos, inappropriate expressions, and misunderstandings of emotions often prevent the message from being conveyed as intended. Furthermore, recipients often struggle to grasp the main points when reading longer texts. To address these challenges, a system is needed to improve the accuracy and communicative power of written communication.

[1084] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1085] In this invention, the server includes means for using generative AI to point out typographical errors in the transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in pop-ups to facilitate the recipient's understanding; and means for using an emotion engine to recognize the sender's emotions and suggest rewriting the text in accordance with those emotions. As a result, the sender's intentions are accurately conveyed and the recipient can easily understand the text.

[1086] "Generative AI" is a type of artificial intelligence that uses natural language processing technology to analyze text, identify typos and grammatical errors, and rewrite sentences.

[1087] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[1088] "Advice" refers to suggestions or proposals offered to improve the clarity and ease of understanding of a piece of writing.

[1089] A "pop-up display" is an information window that is temporarily displayed on the screen, serving as a means of instantly conveying important information to the user.

[1090] An "emotion engine" is a technology that recognizes the sender's emotions from their text and suggests an appropriate response based on those emotions.

[1091] A "rewriting suggestion" is a proposal to change the original text to a more appropriate expression, and is made with the aim of improving the communication power of the text.

[1092] A "main point" refers to the particularly important or core content of a text or piece of information.

[1093] A "deadline" is the date on which a particular action or event is supposed to take place.

[1094] "Stakeholders" refers to individuals or organizations involved in a particular matter or event.

[1095] A description of embodiments for carrying out this invention will be given.

[1096] Users utilize a system integrated into internet search tools, email, and messenger apps. This system includes a program that combines generative AI and an emotion engine. When a user inputs text, the server receives the text and analyzes it using the generative AI. The generative AI utilizes natural language processing technology to detect and point out typos and grammatical errors in the text. It also provides advice to improve the clarity and ease of understanding of the text.

[1097] Furthermore, the server uses an emotion engine to recognize the user's emotions. The emotion engine analyzes the emotions in the input text and suggests rewriting the text according to those emotions. For example, if the user inputs "I am very dissatisfied with this matter," the generative AI and emotion engine will suggest something like "I hope for improvement regarding this matter."

[1098] For example, if a user inputs "Please change the meeting time," the server uses a generative AI model to analyze it and suggests a polite expression such as "Could you please change the meeting time?" Furthermore, if the emotion engine recognizes that the user is in a hurry, it will suggest something like, "I'm sorry to bother you, but could you please change the meeting time?"

[1099] An example of a prompt message might be: "Analyze the text entered by the user, point out typos and grammatical errors, and suggest rewrites that reflect the user's emotions."

[1100] The flow of the specific processing in Example 1 will be explained using Figure 17.

[1101] Step 1:

[1102] Users enter text into input fields in internet search tools, email, or messenger apps. This entered text becomes the starting point for system processing.

[1103] Step 2:

[1104] The server receives the text data entered by the user. It then prepares the received text to be passed as input to a generative AI model for analysis.

[1105] Step 3:

[1106] The server uses a generative AI model to analyze the structure and content of the input text. This analysis uses natural language processing techniques to detect typos and grammatical errors within the text. As a result of the analysis, information identifying typos and grammatical errors is output.

[1107] Step 4:

[1108] The server generates advice to improve the clarity of the text based on the analysis results of the AI ​​model. Specifically, it suggests rewriting the text to improve its politeness and clarity. This suggestion is then provided to the user as output.

[1109] Step 5:

[1110] The server uses an emotion engine to recognize emotions from the text entered by the user. The emotion engine analyzes words and expressions in the text to identify the user's emotional state. This emotional information is used to suggest rewriting in the next step.

[1111] Step 6:

[1112] The server suggests appropriate rewritings of the text based on the emotions it recognizes. For example, if anger is detected, it will suggest expressions that alleviate that emotion. These rewriting suggestions are then provided to the user as the final output.

[1113] Step 7:

[1114] The user reviews the suggestions from the server and revises the text as needed. After reviewing the final text, they submit or save it. This ensures that the text accurately conveys the user's intent.

[1115] (Application Example 1)

[1116] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1117] In modern communication, misunderstandings often arise due to typographical errors, grammatical mistakes, and inappropriate expressions. Furthermore, accurately conveying the sender's emotions is difficult, and in face-to-face customer service, appropriate responses tailored to the customer's feelings are crucial. To address these challenges, real-time text analysis and emotion recognition are necessary.

[1118] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1119] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services for easier understanding advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; a server that uses an emotion recognition engine to analyze the sender's emotions and proposes text rewriting appropriate to those emotions; and a server that converts voice input into text, identifies errors in the text in real time, and proposes appropriate expressions. This reduces misunderstandings of the text and makes it possible to appropriately convey the sender's emotions.

[1120] "Generative AI" is an artificial intelligence technology that analyzes input text and provides suggestions for improving it, such as pointing out typos and grammatical errors.

[1121] An "emotion recognition engine" is a technology that analyzes the sender's emotions and suggests appropriate written expressions that correspond to those emotions.

[1122] "Voice input" is an input method for converting speech into text data.

[1123] A "pop-up display" is a method of displaying a small window on the screen to instantly convey important information to the user.

[1124] "Real-time analysis" is a technology that processes input data instantly and provides results immediately.

[1125] The system for implementing this invention mainly consists of a server and a terminal. The server uses a generative AI model to analyze text input by the user and provides suggestions for correcting typos and suggesting improvements to the text. Specifically, the server uses OpenAI's GPT to analyze the input text data and suggest appropriate expressions. In addition, it uses IBM Watson's Tone Analyzer as an emotion recognition engine to analyze the user's emotions and suggest rewriting the text according to those emotions.

[1126] The terminal is a device such as smart glasses or a smartphone that accepts voice input. The voice input is converted to text using the Google Cloud Speech-to-Text API. The converted text is sent to a server and analyzed in real time. The analysis results are displayed as a pop-up on the terminal's display, providing the user with immediate feedback.

[1127] For example, if a user voice-inputs "This product is cheap," the generative AI will suggest a more polite expression such as "This product is reasonably priced." Also, if the emotion engine recognizes that the customer is dissatisfied, it will suggest an apology such as "We apologize for any inconvenience this may have caused."

[1128] An example of a prompt message might be, "Please suggest an appropriate apology if the customer is dissatisfied." This allows users to communicate more smoothly with customers.

[1129] The flow of a specific process in Application Example 1 will be explained using Figure 18.

[1130] Step 1:

[1131] The user provides voice input to the device. The device uses the Google Cloud Speech-to-Text API to convert the voice data into text data. The input for this step is voice data, and the output is text data.

[1132] Step 2:

[1133] The terminal sends the converted text data to the server. The server analyzes the text data using OpenAI's GPT generative AI model. This analysis provides feedback on typos and grammatical errors, as well as suggestions for improving the text. The input is text data, and the output is feedback on typos and grammatical errors, along with suggestions for improvement.

[1134] Step 3:

[1135] The server uses IBM Watson's Tone Analyzer to analyze user sentiment from text data. The input is text data, and the output is the sentiment analysis result. Based on this result, suggestions for rewriting the text according to the sentiment are made.

[1136] Step 4:

[1137] The server sends the analysis results and improvement suggestions to the terminal. The terminal presents this information to the user as a pop-up display. The input is the analysis results and improvement suggestions, and the output is the feedback display to the user.

[1138] Step 5:

[1139] The user reviews the suggestions displayed on the device and modifies the text as needed. This enables the user to communicate more smoothly with customers. The input is feedback information, and the output is the modified text.

[1140] (Example 2)

[1141] Next, we will describe Example 2 of the morphological example. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1142] In today's information society, recipients are required to efficiently understand and appropriately respond to a large volume of messages. However, it is difficult to understand long messages or complex texts in a short amount of time, and information is not provided in a way that suits the recipient's emotions, which can lead to misunderstandings and delayed responses. This results in challenges such as decreased work efficiency and communication breakdowns.

[1143] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1144] In this invention, the server includes means for using generative artificial intelligence to point out typographical errors in the transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and means for analyzing the recipient's emotions and extracting and displaying information according to those emotions. As a result, the recipient can quickly grasp the main points of the message and obtain appropriate information according to their emotions.

[1145] "Generative artificial intelligence" refers to an artificial intelligence system that uses natural language processing technology to identify typographical errors and grammatical mistakes in text and suggests improvements to the text.

[1146] A "pop-up display" is a visual notification method that instantly displays important information on the recipient's screen.

[1147] "Emotional analysis" is a technology that analyzes the emotional state of a recipient and provides appropriate information based on those emotions.

[1148] The "main point" refers to particularly important information or the main theme within a text, representing the core part that the recipient should understand.

[1149] A "deadline" refers to the period by which a specific action or response is required, and the date by which the recipient must take action.

[1150] "Stakeholders" refer to individuals or organizations related to a specific message or project, and are those with whom information sharing and cooperation are necessary.

[1151] This system's program provides a function that analyzes the content of a message received by the recipient, automatically extracting and displaying key points, deadlines, and information about relevant parties. Furthermore, it can analyze the recipient's emotions and extract and display information accordingly.

[1152] The server analyzes messages using natural language processing techniques. Specifically, it tokenizes text using Python's NLTK library and spaCy, and then analyzes the grammatical structure to extract key points, deadlines, and information about stakeholders. For sentiment analysis, it uses Python's TextBlob and the Google Cloud Natural Language API to determine the recipient's sentiment as positive, negative, or neutral.

[1153] The device displays the extracted information as a pop-up using JavaScript. This allows users to quickly grasp the main points of the message and receive appropriate information tailored to their emotions.

[1154] As a concrete example, if a user receives the message, "Please submit a project progress report by tomorrow. The relevant parties are A, B, and C," the device sends this message to the server. The server analyzes the message using spaCy, extracts "project progress report" as the key point, and recognizes "tomorrow" as the deadline. It also identifies "A, B, and C" as the relevant parties. If the emotion engine determines the user's emotion is "confused," the device will display a pop-up with the information "Key point: Project progress report, Deadline: Tomorrow, Relevant parties: A, B, C," and additional information such as "Here is the report template."

[1155] An example of a prompt to input into a generating AI model is: "Extract the key points, deadline, and stakeholders from the following message: 'Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C.'" By using this prompt, the AI ​​model can extract the necessary information and provide it to the user.

[1156] The flow of the specific processing in Example 2 will be explained using Figure 19.

[1157] Step 1:

[1158] The user receives a message. The terminal prepares to send the received message to the server. The input is the text message received by the user. The output is the message data to be analyzed and sent to the server.

[1159] Step 2:

[1160] The server analyzes received messages using natural language processing techniques. Specifically, it tokenizes text using Python's NLTK library and spaCy, and then analyzes the grammatical structure. The input is message data sent from the terminal. The output is the tokenized text and the analyzed grammatical structure.

[1161] Step 3:

[1162] The server extracts key points, deadlines, and stakeholders from the analyzed data. It uses regular expressions to identify dates and names and extract important keywords. Input consists of tokenized text and parsed grammatical structure. Output is the extracted key points, deadlines, and stakeholders.

[1163] Step 4:

[1164] The server uses a sentiment engine to analyze the sentiment of a message. It uses Python's TextBlob and the Google Cloud Natural Language API to determine whether the message is positive, negative, or neutral. The input is the message data. The output is the analyzed sentiment information.

[1165] Step 5:

[1166] The device displays the extracted information as a pop-up using JavaScript. If the sentiment engine determines that the user is confused, the device prioritizes displaying additional explanations and details. The input consists of extracted key points, deadlines, stakeholders, and sentiment information. The output is the pop-up information displayed to the user.

[1167] (Application Example 2)

[1168] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1169] In modern information and communication, recipients are required to understand large amounts of information quickly and accurately. However, information is often difficult to understand because it is not provided in a way that considers the recipient's emotional state. Furthermore, in transactions and important messages, recipients may experience anxiety or confusion, which hinders quick decision-making. To solve these problems, it is necessary to provide information that takes the recipient's emotions into consideration.

[1170] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1171] In this invention, the server includes means for using generative AI to point out typographical errors in transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in pop-ups to facilitate the recipient's understanding; and means for recognizing the recipient's emotions and extracting and displaying information according to those emotions. As a result, the recipient can quickly and accurately understand the information and obtain appropriate information according to their emotions.

[1172] "Generative AI" refers to artificial intelligence technology that uses natural language processing to generate and modify text.

[1173] "Error detection" is a function that detects incorrect or missing characters in a text and corrects them to their correct form.

[1174] "Easy-to-understand advice" refers to specific suggestions for improvement provided to make the recipient more easily understandable.

[1175] A "text rewriting service" is a service that transforms original text into clearer and more effective expressions.

[1176] The "main point" refers to the most important information or subject matter in a text, and is the core part that the recipient should understand.

[1177] A "deadline" is information that indicates the deadline by which a particular action or event must be completed.

[1178] "Stakeholders" refers to individuals or organizations associated with a particular document or message.

[1179] A "pop-up" is an information window that temporarily appears on the screen and is used to attract the user's attention.

[1180] "Recognizing the receiver's emotions" refers to the technology of determining the emotional state of the receiver from their facial expressions and voice.

[1181] "Information extraction and display" is the process of extracting necessary information from text and presenting it visually to the user.

[1182] The system for implementing this invention operates in a network environment including a server and user terminals. The server uses generative AI to identify typos and grammatical errors in the text sent by the user, and provides clearer advice and rewrites the text. Specifically, it uses Python and the natural language processing library spaCy to analyze and correct the text.

[1183] On the user's device, the system automatically extracts the key points, due date, and relevant information of received messages and displays them in a pop-up window. This utilizes front-end technology to receive analysis results from the server and display them on the user interface. Furthermore, TensorFlow is used to recognize the user's emotions and prioritize the display of information corresponding to those emotions. For example, if the user is feeling anxious, information regarding the security of the transaction will be prioritized.

[1184] For example, if a user receives the message, "¥10,000 has been withdrawn from your account. Please check," the system will display "Key points: Withdrawal of ¥10,000, Due date: Immediate, Parties involved: Financial institution." If the user is concerned, additional information such as, "This transaction is secure. Please see the support page for details," will be displayed.

[1185] An example of a prompt for the generating AI model is: "Analyze the transaction confirmation message and extract the key points. Also, provide suggestions for providing information that is tailored to the user's emotions."

[1186] The flow of a specific process in Application Example 2 will be explained using Figure 20.

[1187] Step 1:

[1188] The server receives text sent by the user. Using this text as input, it uses a generative AI to detect typos and grammatical errors. Specifically, it analyzes the text using the natural language processing library spaCy to identify typos and grammatical errors. The output is a list of the errors and suggested corrections.

[1189] Step 2:

[1190] The server provides the user with suggested revisions generated by a generative AI. The user then revises the text based on these suggestions. The revised text is sent back to the server. The input is the suggested revisions, and the output is the text revised by the user.

[1191] Step 3:

[1192] The server receives the revised text and extracts information on key points, deadlines, and stakeholders. This process involves analyzing the text again using spaCy to identify important information. The input is the revised text, and the output is the extracted information.

[1193] Step 4:

[1194] The server sends the extracted information to the user's terminal. The terminal displays this information as a pop-up on its user interface. The input is the extracted information, and the output is the information visually presented to the user.

[1195] Step 5:

[1196] The device uses TensorFlow to analyze the user's facial expressions and voice in order to recognize the user's emotions. The input is the user's facial expressions and voice data, and the output is the recognized emotional state.

[1197] Step 6:

[1198] The device adjusts the information displayed based on the recognized emotion. For example, if the user is feeling anxious, it prioritizes displaying information related to the security of the transaction. The input is the recognized emotional state, and the output is the adjusted information display.

[1199] (Example 3)

[1200] Next, we will describe Embodiment 3 of Embodiment Example 3. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1201] In modern information and communication, there are challenges such as errors in transmitted information and difficulty for recipients to quickly grasp the main points of the information. Furthermore, a lack of communication that considers the feelings of both senders and receivers can lead to misunderstandings and inappropriate responses. Systems are needed to address these challenges.

[1202] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means.

[1203] In this invention, the server includes means for pointing out errors in transmitted information using generative artificial intelligence and providing easily understandable advice and information correction services; means for displaying the main points, deadlines, and relevant parties of long information on a display device to facilitate the recipient's understanding; and means for analyzing the emotions of the sender and recipient and providing appropriate expressions and information based on that analysis. This improves the accuracy of information, allows recipients to quickly grasp the main points of the information, and enables appropriate communication that responds to emotions.

[1204] "Generative artificial intelligence" is an artificial intelligence technology that uses input information to identify and correct errors and provide advice.

[1205] A "display device" is a device that allows a recipient to visually confirm information.

[1206] "Analyzing emotions" is the process of analyzing the emotional states of both the sender and receiver and using that analysis to determine an appropriate response.

[1207] "Key points" refer to the particularly important or core content of information.

[1208] "Deadline" refers to a specific date, time, or deadline related to information.

[1209] "Stakeholders" refers to individuals or organizations related to the information.

[1210] This invention is a system for improving the transmission and reception processes in information communication. The server uses generative artificial intelligence to identify errors in transmitted information and provides clearer advice and corrections. Specifically, it uses a natural language processing library to analyze input information and detect typos, grammatical errors, and inappropriate expressions. This allows users to improve the accuracy of the information they receive.

[1211] Furthermore, the server extracts the key points, deadlines, and stakeholders of long pieces of information so that recipients can quickly understand them, and displays them as pop-ups on the terminal's display. This process uses natural language processing technology. For example, if a recipient receives the information, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the server extracts and displays the information, "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C."

[1212] The server also analyzes the emotions of both the sender and receiver and provides appropriate expressions and information based on that analysis. It uses an emotion analysis API for this analysis. For example, if the server recognizes that the sender is angry and the receiver is confused, it will suggest appropriate expressions to the sender and provide the receiver with information to aid understanding.

[1213] As a concrete example, an example of a prompt sentence to be input to the generating AI model is shown: "Extract the main points of the message received by the recipient, analyze the sentiment, and suggest an appropriate response." By using this prompt, the system can provide the recipient with information quickly and appropriately. The flow of specific processing in Example 3 will be explained using Figure 21.

[1214] Step 1:

[1215] The user receives information via email or messaging apps. The device prepares to send the received information to the server. The input is the text information received by the user, and the output is the data to be analyzed that is sent to the server.

[1216] Step 2:

[1217] The server uses a natural language processing library to analyze the received information. Specifically, it tokenizes the text data and extracts important keywords and phrases. The input is text data sent from the terminal, and the output is extracted information such as key points, deadlines, and stakeholders.

[1218] Step 3:

[1219] The server uses Google Cloud's sentiment analysis API to analyze the sentiments of both the sender and receiver. The input is the received text data, and the output is the result of the sentiment analysis. Based on the sentiment analysis results, the server determines the appropriate response.

[1220] Step 4:

[1221] The server displays a pop-up on the recipient's device based on the extracted information and sentiment analysis results. The device displays the pop-up, allowing the user to quickly grasp key points, deadlines, and relevant information. The input is the information sent from the server, and the output is the pop-up information displayed on the device.

[1222] Step 5:

[1223] The server inputs a prompt sentence into a generative AI model and generates an appropriate response. The input consists of the prompt sentence and the analysis result, while the output is the generated response. The server provides the generated response to the recipient, facilitating smooth communication.

[1224] (Application Example 3)

[1225] Next, we will describe application example 3 of form example 3. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1226] In today's information society, there is a growing demand for increased efficiency in electronic transactions and communication. However, quickly grasping important transaction information and engaging in appropriate communication that considers emotions is not easy. In particular, there is a need for a system that enables quick understanding of the key points of transaction notifications and supports communication that takes into account the feelings of both the sender and the receiver.

[1227] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means.

[1228] In this invention, the server includes means for using generative AI to point out typographical errors in transmitted text and provide services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts in pop-ups to facilitate the recipient's understanding; means for analyzing the emotions of the sender and receiver and supporting emotion-appropriate communication; and means for automatically extracting and displaying the main points of an electronic transaction when a notification regarding the transaction is received. This enables rapid understanding of transaction information and support for emotion-conscious communication.

[1229] "Generative AI" refers to artificial intelligence that uses natural language processing technology to generate and modify text.

[1230] "Error detection" is a function that detects incorrect or missing characters in a text and suggests corrections.

[1231] "Easy-to-understand advice" is a function that provides suggestions for improvement to make the text easier for the recipient to understand.

[1232] A "text rewriting service" is a service that transforms the original text into a clearer and more concise expression.

[1233] "Pop-up display" is a function that displays a small window on the screen to instantly present important information.

[1234] "Automatic extraction of key points, deadlines, and relevant information" refers to a technology that automatically extracts and displays important information from a document.

[1235] "Means of analyzing emotions and supporting emotion-based communication" refers to a function that analyzes the emotions of the sender and receiver and facilitates appropriate communication based on that analysis.

[1236] A "notice regarding electronic transactions" is a message that contains information about electronic transactions.

[1237] "A means of automatically extracting and displaying the key points of a transaction" refers to a function that automatically extracts important information from transaction notifications and presents it to the user.

[1238] The system for implementing this invention mainly consists of a server and a user terminal. The server uses generative AI to identify typos and grammatical errors in the text sent by the user, and provides clearer advice and rewrites the text. The user terminal displays the main points, deadlines, and information about relevant parties in pop-ups to facilitate user understanding. Furthermore, the server analyzes the emotions of the sender and receiver and supports communication that is appropriate to those emotions.

[1239] Specifically, the server uses a natural language processing library (e.g., spaCy) to detect typos and grammatical errors from text and extract key points. For sentiment analysis, a sentiment analysis library (e.g., TextBlob) is used to analyze the emotions of the sender and receiver. A generative AI model (e.g., OpenAI GPT) generates communication suggestions that are appropriate to the emotions.

[1240] For example, when a user receives a notification about an electronic transaction, the server automatically extracts the key points of the transaction (transaction amount, due date, and parties involved) and displays them as a pop-up on the user's terminal. Furthermore, based on sentiment analysis, if the sender appears to be feeling anxious, the server suggests that they should make an effort to provide a more thorough explanation to the user.

[1241] An example of a prompt message is, "Extract the key points of this transaction notification and analyze the sentiment of the sender and recipient."

[1242] The flow of the specific processing in Application Example 3 will be explained using Figure 22.

[1243] Step 1:

[1244] The server receives notifications from users regarding electronic transactions. The input is the text data of the transaction notification. Based on this data, a natural language processing library (e.g., spaCy) is used to analyze the sentence structure. The output is the structural information of the analyzed sentence.

[1245] Step 2:

[1246] The server uses the structural information of the analyzed text to extract the key points of the transaction (transaction amount, due date, parties involved). The input is the structural information obtained in step 1. As part of the data processing, specific keywords and phrases are identified and key points are extracted. The output is the extracted key points information.

[1247] Step 3:

[1248] The server analyzes the emotions of the sender and receiver using an emotion analysis library (e.g., TextBlob). The input is the text data of the transaction notification. As a data calculation, it calculates an emotion score from the text and identifies the type of emotion. The output is the emotion information of the sender and receiver.

[1249] Step 4:

[1250] The server uses a generative AI model (e.g., OpenAI GPT) to generate emotion-based communication suggestions. The input is the emotion information obtained in step 3. As a data processing step, it generates appropriate communication phrases based on the emotion information. The output is the generated communication suggestions.

[1251] Step 5:

[1252] The terminal displays key information and communication proposals received from the server as a pop-up. The input consists of the key information obtained in step 2 and the communication proposals obtained in step 4. Specifically, a pop-up window is displayed on the user's screen, immediately presenting the important information. The output is the information presented to the user.

[1253] (Other examples)

[1254] Since this is the same as the specific processing described in the other embodiments of the first embodiment above, the explanation will be omitted.

[1255] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1256] The data generation model 58 is a form of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1257] Other examples of generative AI include Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) are some examples.

[1258] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1259] [Fourth Embodiment]

[1260] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1261] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1262] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1263] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1264] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1265] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1266] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1267] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1268] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1269] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1270] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1271] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1272] Next, the identification process performed by the identification processing unit 290 of the data processing device 12 will be described.

[1273] "Example of form 1"

[1274] One embodiment of this system is one that can be integrated into internet search tools, email, and messenger applications. This system uses generative AI to analyze the text entered by the sender and points out typos and grammatical errors. Furthermore, it provides advice to improve the clarity of the text and suggests rewriting it as needed. Specifically, if the sender enters "Please submit the report by tomorrow," the generative AI will suggest rewriting it to a more polite expression such as "Please submit the report by tomorrow."

[1275] "Example of form 2"

[1276] Furthermore, for recipients, there is a feature that analyzes the content of received messages, automatically extracts key points, deadlines, and information about stakeholders, and displays them in a pop-up window. Specifically, if a recipient receives a message that says, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the system will display a pop-up window with the following information: "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C." This allows the recipient to quickly grasp the main points of the message.

[1277] "Example of form 3"

[1278] Furthermore, for recipients, there is a feature that analyzes the content of received messages, automatically extracts key points, deadlines, and information about stakeholders, and displays them in a pop-up window. Specifically, if a recipient receives a message that says, "Please submit a report on the project progress by tomorrow. The stakeholders are A, B, and C," the system will display a pop-up window with the following information: "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: A, B, C." This allows the recipient to quickly grasp the main points of the message.

[1279] The following describes the processing flow for each example of the form.

[1280] "Example of form 1"

[1281] Step 1: The sender types the message into an internet search tool, email, or messenger app.

[1282] Step 2: The generative AI analyzes the input text and points out typos and grammatical errors.

[1283] Step 3: The generative AI provides advice to improve the clarity of the text.

[1284] Step 4: If necessary, the generative AI will suggest rewriting the text.

[1285] "Example of form 2"

[1286] Step 1: The recipient receives the message.

[1287] Step 2: The system analyzes the content of the received text.

[1288] Step 3: The system automatically extracts key points, deadlines, and information about stakeholders.

[1289] Step 4: The system will display the extracted information in a pop-up window.

[1290] (Example 1)

[1291] Next, we will describe Embodiment 1 of Example Form 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1292] In modern communication, misunderstandings often arise due to typographical errors, grammatical mistakes, and unclear writing. Furthermore, long texts can bury key points and important information, making them difficult for recipients to understand. There is a need to address these challenges and achieve more effective communication.

[1293] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1294] In this invention, the server includes means for pointing out typographical errors and grammatical errors in transmitted text using generative artificial intelligence and providing services such as easy-to-understand advice and text rewriting; means for displaying the main points, deadlines, and relevant parties of long texts on a display device to facilitate the recipient's understanding; and means for analyzing text input by the user and using generative artificial intelligence to detect typographical errors and suggest improvements to the text. This makes it possible to improve the quality of text and clarify information.

[1295] "Generative artificial intelligence" is a technology that uses natural language processing to analyze text and point out typos and grammatical errors, as well as suggest improvements to the text.

[1296] "Typographical errors" refer to incorrect or missing characters in a text, and are factors that impair the accuracy of the writing.

[1297] "Easy-to-understand advice" refers to suggestions that make the content of a document clearer and easier to understand, thereby facilitating the smooth transmission of information to the recipient.

[1298] A "rewriting service" is a function that improves the expression of a text and corrects it to a more appropriate form.

[1299] A "display device" is a device used to visually display information, and is used by recipients to confirm that information.

[1300] "Key points" refer to the particularly important parts of a text or piece of information, representing the main content that the recipient should understand.

[1301] A "deadline" refers to the date on which a specific action or event should take place, and is important information in schedule management.

[1302] "Stakeholders" refers to individuals or organizations related to a particular document or piece of information, and are those that the recipient of the information should be aware of.

[1303] "Analysis" is the process of thoroughly examining text and data to understand their structure and meaning.

[1304] The following systems are conceivable as embodiments for carrying out this invention.

[1305] The server uses generative artificial intelligence to analyze the text entered by the user. This analysis utilizes natural language processing technology to detect typos and grammatical errors and suggest improvements to the text. Specifically, a general-purpose natural language processing engine can be used as the generative AI model. For example, open-source natural language processing libraries or commercial AI platforms can be used.

[1306] The terminal sends the text entered by the user to the server. A secure communication protocol is used to transmit the data and protect the user's privacy. The server inputs the received text into a generation AI model to create a prompt. An example of a prompt is: "Please analyze the following text, identify any typos or grammatical errors, and provide suggestions for improvement:"

[1307] The generative AI model analyzes the input text and not only points out typos and grammatical errors, but also provides advice to improve the clarity of the writing. For example, if a user inputs "Please submit the report by tomorrow," the generative AI model will suggest rewriting it into a more polite expression such as "Please submit the report by tomorrow."

[1308] In this way, users can improve the quality of their writing and achieve unambiguous communication by utilizing generative artificial intelligence.

[1309] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1310] Step 1:

[1311] Users input text through internet search tools, email, or messenger apps. This entered text becomes the data subject to typographical error checking and suggestions for improving the text.

[1312] Step 2:

[1313] The terminal sends the text entered by the user to the server. This data is transmitted using a secure communication protocol. The input is the user's text, and the output is the secure transmission of data to the server.

[1314] Step 3:

[1315] The server inputs the received text into the generative AI model. Specifically, it creates a prompt message and inputs it to the generative AI model in the format of "Please analyze the following text, point out any typos or grammatical errors, and provide suggestions for improvement:". The input is the user's text, and the output is the prompt message to the generative AI model.

[1316] Step 4:

[1317] The generative AI model analyzes text based on the input prompt sentence. It detects typos and grammatical errors and generates advice and rewriting suggestions to improve the clarity of the text. The input is the prompt sentence, and the output is the analysis result and improvement suggestions.

[1318] Step 5:

[1319] The server sends the analysis results and improvement suggestions obtained from the generated AI model to the terminal. The input is the output of the generated AI model, and the output is the transmission of data to the terminal.

[1320] Step 6:

[1321] The terminal displays analysis results and improvement suggestions received from the server to the user. The user can then use this information to revise their text. The input is data from the server, and the output is information displayed to the user.

[1322] (Application Example 1)

[1323] Next, we will describe Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1324] In modern communication, typographical errors and inappropriate expressions can hinder information transmission. Furthermore, in customer service roles at physical stores, the ability to instantly select appropriate expressions during conversations with customers is crucial, but there is a lack of technology to support this. To address these challenges, a system is needed that analyzes written and spoken content in real time and suggests appropriate expressions.

[1325] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1326] This invention includes a server that uses generative AI to identify typographical errors in transmitted text and provides services such as easy-to-understand advice and text rewriting; a server that displays the main points, deadlines, and relevant parties of long texts in a pop-up to facilitate the recipient's understanding; and a server that uses speech recognition technology to convert speech into text, generates appropriate expressions using generative AI, and presents them on a display device. This makes it possible to analyze the content of text and audio in real time and suggest appropriate expressions.

[1327] "Generative AI" is an artificial intelligence technology that analyzes input data and generates appropriate sentences and expressions through natural language processing.

[1328] "Typographical errors" refer to mistakes or omissions in text, and are factors that hinder the accurate transmission of information.

[1329] A "pop-up display" refers to a window or message that temporarily appears on the screen to highlight information within the user interface.

[1330] "Speech recognition technology" is a technology that analyzes speech as a digital signal and converts it into corresponding text data.

[1331] A "display device" is hardware used to visually present generated information or data, and includes displays and screens.

[1332] The system for implementing this invention involves a server and a terminal working in conjunction. The server uses generative AI to identify typos and grammatical errors in transmitted text, and provides clearer advice and rewrites the text. Furthermore, it displays key points, deadlines, and relevant parties in pop-ups for longer texts to facilitate the recipient's understanding.

[1333] The device uses speech recognition technology to convert speech into text, generates appropriate expressions using generative AI, and displays them on a display device. Specifically, the generated information is visually presented to the user using a display device such as smart glasses or a smartphone.

[1334] For example, in a physical store, if a user asks, "Does this product come in other colors?", the terminal uses speech recognition technology to convert this question into text and send it to the server. The server then uses generative AI to generate an appropriate response, such as, "This product is available in other colors. Which color would you prefer?", and displays it on the terminal's display.

[1335] An example of a prompt is, "A customer is asking about the color of a product. Please suggest a polite response." By inputting this prompt into a generative AI, an appropriate response will be generated.

[1336] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1337] Step 1:

[1338] The device acquires the user's voice input through the microphone. The input is the voice data spoken by the user. The device converts this voice data into text data using speech recognition technology (e.g., Google Cloud Speech-to-Text). The output is text data that represents the user's speech as a string of characters.

[1339] Step 2:

[1340] The terminal sends the converted text data to the server. The server inputs the received text data into a generative AI model (e.g., OpenAI's GPT-3). The input is text data representing the user's utterance. The server uses the generative AI model to perform data calculations to generate an appropriate response. The output is the text data of the generated appropriate response.

[1341] Step 3:

[1342] The server sends the generated response as text data to the terminal. The terminal displays the received response on a display device (e.g., smart glasses or smartphone display). The input is the text data of the response sent from the server. The terminal processes the data to present the information visually to the user and provides a response that is displayed to the user as output.

[1343] Step 4:

[1344] The user confirms the displayed response and continues the conversation as needed. The user's confirmation triggers the next voice input, and the process from step 1 is repeated. The input is the displayed response, and the output is the user's understanding and next action.

[1345] (Example 2)

[1346] Next, we will describe Example 2 of the morphological example. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1347] In modern information and communication, it is difficult for recipients to quickly and accurately understand lengthy information. Furthermore, while it is crucial for senders to provide clear information free from typos and grammatical errors, doing so manually is time-consuming and laborious. To address these challenges, a system is needed that automatically extracts key points, deadlines, and stakeholders, and presents them clearly to the recipient.

[1348] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1349] In this invention, the server includes means for pointing out typographical errors in transmitted information using generative artificial intelligence and providing easy-to-understand advice and information rewriting services; means for displaying the main points, deadlines, and relevant parties of long information on a display device to facilitate the recipient's understanding; and means for analyzing received information and automatically extracting information on main points, deadlines, and relevant parties. As a result, the recipient can quickly grasp the main points of the information, and the sender can provide clear information free from typographical errors.

[1350] "Generative artificial intelligence" is a type of artificial intelligence that uses natural language processing technology to analyze and generate information.

[1351] "Typographical errors" refer to incorrectly written or missing characters in information.

[1352] "Advice" refers to instructions or suggestions provided to improve or facilitate understanding of information.

[1353] "Rewriting information" is the act of modifying information to make its content clearer and easier to understand.

[1354] A "key point" refers to the particularly important or core content of information.

[1355] "Deadline" refers to a specific date, time, or period related to information.

[1356] "Stakeholders" refers to individuals or organizations related to the information.

[1357] A "display device" is a device or interface used to present information visually.

[1358] "Analysis" is the process of breaking down information and understanding its structure and meaning.

[1359] "Extraction" is the act of taking out specific elements or data from information.

[1360] As an embodiment of this invention, the following system is constructed.

[1361] The server analyzes the received information using a generative AI model. A model that utilizes natural language processing technology is suitable for this generative AI model, and specifically, OpenAI's GPT model can be used. The server inputs the received information into the generative AI model and gives it a prompt message such as, "Extract the main points, deadlines, and stakeholders from this text." Based on this prompt message, the generative AI model analyzes the information and extracts the main points, deadlines, and stakeholders.

[1362] The terminal receives analysis results sent from the server and presents them to the user via a display device. Specifically, it uses a pop-up display to visually show information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C." This allows the user to quickly grasp the important parts of the received information.

[1363] Users can provide clear instructions as prompts to input into the generating AI model. For example, by using a prompt such as, "Extract the main points, deadlines, and stakeholders from this document," the system can efficiently extract and provide information to the user. In this way, recipients of the information can quickly understand the important information, and senders can provide clear information free from typos and grammatical errors.

[1364] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1365] Step 1:

[1366] The user receives information via email or messaging apps. The device detects this received information and prepares to send it to the server. The input is the received information, and the output is the transfer of information to the server. Specifically, the device sends information to the server triggered by the receipt of a new message.

[1367] Step 2:

[1368] The server inputs the received information into a generative AI model. This generative AI model utilizes natural language processing technology. The input consists of the received information and the prompt "Extract the main points, deadlines, and stakeholders from this text," and the output is the analysis result. Specifically, the server passes the information to the generative AI model, which then analyzes the information based on the prompt.

[1369] Step 3:

[1370] The server receives the analysis results returned from the generative AI model. The input is the analysis results from the generative AI model, and the output is the transmission of the analysis results to the terminal. Specifically, the server temporarily stores the analysis results in a database and prepares them for transmission to the terminal.

[1371] Step 4:

[1372] The terminal receives analysis results sent from the server and displays them to the user. The input is the analysis results from the server, and the output is a visual presentation of information to the user. Specifically, the terminal uses a pop-up display to show information such as "Key points: Project progress report, Deadline: Tomorrow, Stakeholders: Person A, Person B, Person C" on the screen.

[1373] This series of processes allows users to quickly grasp the key points of the information they receive.

[1374] (Application Example 2)

[1375] Next, we will describe application example 2 of form example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1376] In today's information society, there is a demand for quick identification of typographical errors and grammatical mistakes in written texts, as well as the ab...

Claims

1. A system equipped with a processor, The aforementioned processor, The text entered by the user is tokenized, and typos and grammatical errors are detected. Based on the results of the detection of typographical errors, a prompt message is generated to instruct the generation AI model to correct the typographical errors, and by inputting this prompt message into the generation AI model, a corrected version corresponding to the typographical errors is generated. Based on the aforementioned proposed revision or the text entered by the user, prompt sentences are generated to convert the text into polite language or improve its style, and by inputting these prompt sentences into the generation AI model, suggestions for rewriting the text are generated. The document based on the aforementioned rewriting proposal will be analyzed, and key points, dates, and information on relevant parties will be extracted from the document. The extracted key points, dates, and information of relevant parties are displayed as a pop-up on the user's terminal. The extracted information is displayed on the user's device. The extracted information consists of key points, dates, and information about relevant parties extracted from the aforementioned document. The processor, in response to the display of the text on the user's terminal, displays the key points, deadlines, and relevant information as a pop-up. system.

2. The aforementioned processor analyzes the content of the document viewed by the recipient, extracts key points, deadlines, and information about the parties involved, The system according to claim 1, wherein the document viewed by the recipient is a document based on the rewriting proposal generated by the processor.

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