System

Abstract

To provide a system.SOLUTION: The system includes: means for automatically generating a business document from an instruction; means for checking a grammatical error in the generated business document; means for checking compliance of the generated business document; means for determining whether the generated business document conforms to the standard of a business communication; analyzing the generated business document by using a natural language processing technology; and means for repairing the business document on the basis of the result of analysis.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Creating and reviewing business emails takes time and effort, and also carries the risk of grammatical errors and compliance violations. Efficient methods to solve these issues are needed. [Means for solving the problem]

[0005] This invention automatically generates business emails from short instructions and checks the generated emails for grammatical errors and compliance. Furthermore, it guarantees the quality of the automatically generated business emails, thereby reducing the time required to create emails and ensuring quality. This frees users from the enormous task of creating emails. [Brief explanation of the drawings]

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

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

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

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

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

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

[0012] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, 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), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0014] [First embodiment]

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

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

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

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

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0023] 2, in the data processing device 12, a specific process 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" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process 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.

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

[0025] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0027] "Example 1"

[0028] The present invention is a system that streamlines the creation and review of business emails. Specifically, it receives short instructions from the user and automatically creates business emails based on those instructions. The generated emails are then checked for grammatical errors and compliance violations using the system's internal grammar and compliance check functions.

[0029] "Example 2"

[0030] Furthermore, this embodiment of the present invention has a function to guarantee the quality of the generated business emails. This not only reduces the time required to create emails, but also guarantees quality. Specifically, it checks whether the content of the email conforms to business communication standards and whether appropriate honorific language is used.

[0031] "Example 3"

[0032] Furthermore, this embodiment of the present invention has the function of freeing users from the burden of creating large amounts of emails. Specifically, the system can automatically generate multiple emails at once, allowing users to focus on other tasks. For example, it is possible to generate follow-up emails to all participants at once based on the minutes of a meeting.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The system receives a short instruction from the user. For example, the instruction might be, "Create a follow-up email to all participants based on the meeting minutes."

[0036] Step 2: Based on the received instructions, the system automatically generates a business email, with the appropriate content, recipient, subject, etc.

[0037] Step 3: The generated email is checked for grammatical errors using the system's internal grammar check function.

[0038] Step 4: Furthermore, the generated email is checked for compliance violations using the compliance check function.

[0039] "Example 2"

[0040] Step 1: The system operates a function to ensure the quality of business emails automatically generated. Step 2: Specifically, the system checks whether the content of the email conforms to business communication standards and whether appropriate honorific language is used.

[0041] Step 3: This not only saves time in creating emails but also ensures quality.

[0042] "Example 3"

[0043] Step 1: The system can automatically generate multiple emails at once.

[0044] Step 2: For example, you can use the meeting minutes to generate follow-up emails to all participants at once.

[0045] Step 3: This frees users from the overwhelming task of creating emails, allowing them to focus on other tasks.

[0046] Example 1

[0047] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0048] Traditionally, creating business documents manually required time and effort, and there was a high risk of grammatical errors and non-compliance. Furthermore, the checking process to ensure document quality was also time-consuming, making it difficult to efficiently manage business operations.

[0049] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0050] In this invention, the server includes means for automatically generating business documents from short instructions, means for checking the generated business documents for grammatical errors, means for checking the generated business documents for compliance, means for passing the generated business documents through a grammar check function, means for passing the generated business documents through a compliance check function, and means for providing the final checked business documents to the user. This makes it possible to streamline the generation and review of business documents, shorten document creation time, and ensure quality.

[0051] A "short instruction" is a concise instruction entered by a user, which contains basic information required to generate a business document.

[0052] A "business document" is an official document used for business communication, reporting, guidance, etc.

[0053] "Means for automatic generation" refers to technologies and algorithms for automatically creating business documents based on short instructions from users.

[0054] "Grammar checking measures" refers to techniques and algorithms used to detect and correct grammatical errors in generated business documents.

[0055] "Compliance checking measures" refers to technologies and algorithms used to verify that generated business documents do not violate corporate policies or legal regulations.

[0056] "Means for passing through a grammar checker" refers to the process of inputting the generated business document into a grammar checker to check for grammatical accuracy.

[0057] "Means for passing through compliance check function" refers to the process of inputting generated business documents into the compliance check function to check whether they violate regulations or policies.

[0058] "Final verified business document" refers to a business document that has passed grammar and compliance checks and has been finally verified.

[0059] "Means to provide to users" refers to the technology or algorithms used to display or transmit finalized business documents to users.

[0060] This invention relates to a system that improves the efficiency of creating and reviewing business documents. Specifically, this system receives short instructions from a user, automatically generates business documents based on those instructions, and checks the generated documents for grammatical errors and compliance violations.

[0061] System configuration

[0062] Hardware

[0063] The system consists of a server and a terminal. The server plays a central role in data processing and document generation, while the terminal is used to receive input from users and display the final document.

[0064] software

[0065] The server has installed on it a generative AI model (e.g., a natural language processing model), a grammar checker (e.g., a grammar check API), and a compliance checker (e.g., a compliance management tool). These pieces of software work together to efficiently generate and review business documents.

[0066] Program processing

[0067] The server receives a short instruction from the user, such as "Please send me a meeting reminder." The server inputs this instruction into a generative AI model, which then automatically generates a business document based on the instruction.

[0068] The generated document is checked for grammatical errors and compliance violations using the server's internal grammar and compliance check functions. The grammar check function checks the document's grammatical accuracy and makes corrections as necessary. The compliance check function checks whether the document content violates company policies or legal regulations.

[0069] Specific examples

[0070] For example, if a user inputs the instruction "Please create an email to introduce our new product," the following specific actions will be taken:

[0071] 1. The user enters "Please create an introductory email for our new product" into the input field on the terminal.

[0072] 2. The device sends this instruction to the server.

[0073] 3. The server inputs the instructions into the generative AI model and passes the prompt, "Please create an email to introduce a new product. The product name is 'XYZ Smartwatch' and its main features are long battery life, heart rate monitoring, and GPS functionality."

[0074] 4. The generative AI model generates a business document that looks like this:

[0075] Subject: Introducing our new product "XYZ Smart Watch"

[0076] Dear Customer,

[0077] Thank you for your continued support. We have recently released a new product, the XYZ Smartwatch. The XYZ Smartwatch is a multi-functional smartwatch that comes equipped with a long-lasting battery, heart rate monitoring, and GPS functionality to make your daily life more convenient.

[0078] Please take this opportunity to try it out.

[0079] Thank you very much.

[0080] Sincerely,

[0081] 5. The server runs the generated document through a grammar checker to correct any grammatical errors.

[0082] 6. The server passes the grammar-checked document through a compliance checker to ensure it does not violate corporate policies or legal regulations.

[0083] 7. The server sends the final verified document to the terminal.

[0084] 8. The terminal displays the final confirmed document to the user, and the user confirms the document.

[0085] In this way, the creation and review of business documents is made more efficient, reducing the time required for document creation and ensuring quality.

[0086] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0087] Step 1:

[0088] The user enters a short instruction.

[0089] The user inputs a short instruction into an input field on the terminal, such as "Please create an email to introduce our new product." The input data is the user's instruction text.

[0090] Step 2:

[0091] The terminal sends instructions to the server.

[0092] The terminal transmits instructions entered by the user to the server. The terminal transmits data using an Internet connection. The input data is the user's instruction text, and the output data is the instruction text sent to the server.

[0093] Step 3:

[0094] The server inputs instructions into the generative AI model.

[0095] The server inputs the received instructions into the generative AI model. Specifically, it passes the instructions to the generative AI model as a prompt. The input data is the instruction sent to the server, and the output data is the prompt passed to the generative AI model.

[0096] Step 4:

[0097] A generative AI model generates business documents.

[0098] A generative AI model generates a business document based on a prompt. For example, if a user instructs the model to "create an email introducing a new product," the model generates a document that includes the features and benefits of the new product. The input data is the prompt, and the output data is the generated business document.

[0099] Step 5:

[0100] The server passes the generated document through a grammar checker.

[0101] The server passes the generated document through a grammar checker, which checks the document for grammatical accuracy and makes corrections as necessary. The input data is the generated business document, and the output data is the grammar-checked document.

[0102] Step 6:

[0103] The server passes the grammar-checked document through a compliance check function.

[0104] The server passes the grammar-checked document through a compliance check function, which checks whether the document content violates company policies or legal regulations. The input data is the grammar-checked document, and the output data is the compliance-checked document.

[0105] Step 7:

[0106] The server sends the final verified document to the terminal.

[0107] The server sends the final verified document to the terminal. At this time, the server checks that the document content is grammatically and complies with all applicable standards. The input data is the compliance-checked document, and the output data is the final verified document sent to the terminal.

[0108] Step 8:

[0109] The terminal displays the final verified document to the user.

[0110] The terminal displays the final verified document received from the server to the user. The user checks the displayed document and corrects or submits it as necessary. The input data is the final verified document, and the output data is the document displayed to the user.

[0111] (Application example 1)

[0112] Next, a description will be given of Application Example 1 of Embodiment 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."

[0113] Business communications and report creation within factories are often done manually, which takes time and effort. There is also a high risk of grammatical errors and compliance violations. This reduces work efficiency and makes quality assurance difficult.

[0114] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0115] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for improving the efficiency of business communications and report creation within the factory, means for detecting and correcting grammatical errors in the generated emails, and means for checking for compliance violations in the generated emails. This makes it possible to improve the efficiency of business communications and report creation within the factory, reduce the risk of grammatical errors and compliance violations, and improve business efficiency and quality assurance.

[0116] A "short instruction" is a text that the user enters briefly to indicate the nature of the work or request.

[0117] "Business email" refers to email sent for business purposes such as business communications and reports.

[0118] "Auto-generation" is the process by which a system automatically creates text based on user input.

[0119] "Grammar mistakes" refers to grammatical errors or inappropriate expressions in a sentence.

[0120] "Compliance" refers to following laws, regulations, and a company's internal rules.

[0121] "Inside the factory" refers to the facility or its interior where manufacturing operations take place.

[0122] "Business communication" is the act of conveying information or instructions related to work.

[0123] A "report" is a document that summarizes the progress and results of work.

[0124] "Efficiency" refers to performing tasks and processes more effectively and quickly.

[0125] "Quality assurance" is the process of ensuring that a product or service meets certain quality standards.

[0126] "Detecting and correcting grammatical errors" refers to finding grammatical errors in a sentence and correcting them to the correct expression.

[0127] "Violation of compliance" refers to any act or content that violates laws, regulations, or a company's internal rules.

[0128] To implement the present invention, the following system configuration and program are required.

[0129] System Configuration

[0130] 1. Hardware:

[0131] Computers installed in factory robots

[0132] Network Connection

[0133] 2. Software:

[0134] Python

[0135] OpenAI(R) API

[0136] LanguageTool

[0137] Program processing explanation

[0138] The server receives short instructions from the user and automatically generates business emails based on them. Specifically, it uses a generative AI model (e.g., GPT-3 (registered trademark)) to generate emails based on the user's instructions. The generated emails are then checked for grammatical errors and corrected using LanguageTool. A simple keyword search is also performed to check for compliance violations.

[0139] Specific examples

[0140] When the user enters the instruction "Please generate a status update email for the production line.", the server generates an email like this:

[0141] Example of a generated email

[0142] Dear Team,

[0143] I would like to provide an update on the current status of the production line. We have successfully completed the first phase and are moving on to the next steps. Thank you for your hard work.

[0144] Best regards,

[0145] [Your Name]

[0146] The generated email is checked for grammar errors using LanguageTool, and a compliance check is performed to warn if the email contains, for example, the word "confidential."

[0147] Prompt Sentence Examples

[0148] Please generate a status update email for the production line.

[0149] In this way, business communication and report creation within the factory becomes more efficient, the risk of grammatical errors and compliance violations is reduced, and work efficiency and quality assurance can be improved.

[0150] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0151] Step 1:

[0152] The user inputs a short instruction, such as a prompt phrase like "Please generate a status update email for the production line." This input is sent to the server.

[0153] Step 2:

[0154] The server sends the received prompt to a generative AI model (e.g., GPT-3 (registered trademark)). The generative AI model automatically generates a business email based on the prompt. This generated email is returned to the server.

[0155] Step 3:

[0156] The server sends the generated business email to LanguageTool, which checks for grammatical errors. LanguageTool detects grammatical errors in the email and returns the corrected email to the server.

[0157] Step 4:

[0158] The server sends the corrected email to the compliance check module, which searches for specific keywords (e.g., "confidential") in the email to check for compliance violations. If a violation is detected, the information is returned to the server.

[0159] Step 5:

[0160] The server returns the final email to the user, who can then view it through their device after corrections and compliance checks have been completed.

[0161] Specific actions at each step

[0162] Step 1:

[0163] Input: User types into terminal, "Please generate a status update email for the production line."

[0164] Output: The prompt text entered is sent to the server.

[0165] Step 2:

[0166] Input: The server receives the prompt.

[0167] Data processing: Send prompt text to the generative AI model (GPT-3 (registered trademark)) to generate a business email.

[0168] Output: The generated business email is returned to the server.

[0169] Step 3:

[0170] Input: The server receives a generated business email.

[0171] Data calculation: Send email to LanguageTool to detect and correct grammar errors.

[0172] Output: The modified email is returned to the server.

[0173] Step 4:

[0174] Input: The server receives the modified email.

[0175] Data calculation: Send emails to the compliance check module and search for specific keywords to check for compliance violations.

[0176] Output: Compliance violations or not are returned to the server.

[0177] Step 5:

[0178] Input: The server receives the final email.

[0179] Output: A completed remediation and compliance check email is sent back to the user.

[0180] Example 2

[0181] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0182] Conventional business document creation systems do not adequately check for grammatical errors or compliance when automatically generating documents, and lack functionality to check whether documents conform to business communication standards or use appropriate honorific language. As a result, the quality of the generated documents cannot be guaranteed, and users often have to manually correct them. Furthermore, document creation efficiency is not sufficiently improved, and users are unable to be relieved of the enormous amount of document creation work.

[0183] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0184] In this invention, the server includes means for automatically generating business documents from short instructions, means for checking the generated business documents for grammatical errors, means for checking the generated business documents for compliance, means for verifying whether the generated business documents conform to business communication standards, means for verifying whether the generated business documents use appropriate honorific language, means for analyzing the generated business documents using natural language processing technology, and means for correcting the business documents based on the analysis results. This ensures document quality and eliminates the need for users to manually correct the documents. It also improves the efficiency of document creation, freeing users from the burden of extensive document creation work.

[0185] A "short instruction" is a concise text entered by a user that contains the information necessary to generate a business document.

[0186] "Business documents" are official documents used for business communication, including emails, reports, notices, etc.

[0187] "Auto-generation" is the process by which a system automatically creates a business document based on user input.

[0188] "Grammar errors" are grammatical errors in generated business documents, and refer to errors in sentence structure and word usage.

[0189] "Compliance" refers to checking whether generated business documents comply with laws, regulations, and internal company rules.

[0190] "Business communication standards" refer to the generally accepted format, expression, and etiquette for business documents.

[0191] "Honorific language" refers to polite language used in business documents, and is a form of language used to express respect for the other person.

[0192] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language, and is used to analyze and generate text.

[0193] "Analysis results" refers to information obtained after analyzing business documents generated using natural language processing technology, and includes check results for grammatical errors and compliance.

[0194] "Correction" is the process of correcting errors or inappropriate parts of business documents generated based on the analysis results, thereby improving their quality.

[0195] The present invention relates to a system that automatically generates business documents from short instructions and guarantees the quality of the documents. A specific embodiment of this system will be described below.

[0196] First, the user inputs a prompt using a terminal. The prompt contains instructions for generating a business document for the generative AI model. For example, the user can input a prompt such as, "Please create an email to announce the launch of a new product."

[0197] The device sends the prompt text entered by the user to the server. The server analyzes the received prompt text and inputs it into a generative AI model. For example, GPT-4 (registered trademark) from OpenAI (registered trademark) can be used as the generative AI model.

[0198] The generative AI model generates a business document based on the input prompt. The generated business document is then analyzed by the server using natural language processing technology. For natural language processing, an NLP library such as SpaCy or NLTK can be used.

[0199] The server checks the generated business documents for grammatical errors and compliance, and verifies whether they conform to business communication standards and use appropriate honorific language, thereby ensuring the quality of the generated business documents.

[0200] Based on the analysis results, the server modifies the business document as needed, for example, correcting any honorific errors and adjusting it to conform to business standards.

[0201] Finally, the quality-assured business document is sent from the server to the terminal, which then displays the received business document to the user, who can then check the displayed business document and make further corrections as necessary.

[0202] This system allows users to create high-quality business documents in a short time. For example, if a user inputs the prompt "Please create an email to announce the release of a new product," the following business document will be generated:

[0203] Subject: Announcement of new product release

[0204] Dear Customers,

[0205] We would like to express our sincere gratitude for your continued support.

[0206] We are pleased to announce that we will be releasing a new product, "XYZ."

[0207] Details are as follows:

[0208] Product name:XYZ

[0209] Release date: October 1, 2023

[0210] Price: 10,000 yen

[0211] We appreciate your cooperation.

[0212] Sincerely,

[0213] ABC Co., Ltd.

[0214] In this way, users can efficiently create high-quality business documents.

[0215] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0216] Step 1:

[0217] The user enters a prompt statement.

[0218] The user inputs a prompt sentence into an input field on the terminal, such as "Please create an email to notify you about the release of a new product." The input prompt sentence contains instructions for generating a business document.

[0219] Step 2:

[0220] The terminal sends the prompt to the server.

[0221] The terminal sends the prompt text entered by the user to the server as an HTTP request. The input data is the prompt text, and the output data is the request to the server.

[0222] Step 3:

[0223] The server receives the prompt sentence and inputs it into the generative AI model.

[0224] The server analyzes the prompt sentence received from the terminal and inputs it into a generative AI model (e.g., OpenAI's GPT-4®). The input data is the prompt sentence, and the output data is the input to the generative AI model.

[0225] Step 4:

[0226] A generative AI model generates business documents.

[0227] The generative AI model generates a business document based on the input prompt. The input data is the prompt, and the output data is the generated business document. For example, the following business document is generated:

[0228] Subject: Announcement of new product release

[0229] Dear Customers,

[0230] We would like to express our sincere gratitude for your continued support.

[0231] We are pleased to announce that we will be releasing a new product, "XYZ."

[0232] Details are as follows:

[0233] Product name:XYZ

[0234] Release date: October 1, 2023

[0235] Price: 10,000 yen

[0236] We appreciate your cooperation.

[0237] Sincerely,

[0238] ABC Co., Ltd.

[0239] Step 5:

[0240] The server parses the generated business document using an NLP library.

[0241] The server analyzes the generated business document using natural language processing technology (for example, SpaCy or NLTK). The input data is the generated business document, and the output data is the analysis results. The purpose of the analysis is to check for grammatical errors and compliance, whether the document conforms to business communication standards, and whether appropriate honorific language is used.

[0242] Step 6:

[0243] The server modifies the business document based on the analysis results.

[0244] The server modifies the content of the business document as needed based on the results of the NLP analysis. The input data is the analysis result, and the output data is the modified business document. For example, any errors in honorific language are corrected, and the document is adjusted to conform to business standards.

[0245] Step 7:

[0246] The server transmits the quality-guaranteed business document to the terminal.

[0247] The server sends the modified business document to the terminal as an HTTP response. The input data is the modified business document, and the output data is the response to the terminal.

[0248] Step 8:

[0249] The terminal displays the business document to the user.

[0250] The terminal displays the business document received from the server to the user. The input data is the response from the server, and the output data is the business document displayed to the user. The user can check the displayed business document and make further corrections if necessary.

[0251] (Application example 2)

[0252] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0253] Creating business emails is a time-consuming and labor-intensive task, especially for customer support staff at electronic payment services. It is also important to ensure that the content of the email complies with business communication standards and that appropriate honorific language is used, but doing this manually is inefficient. Furthermore, it is also necessary to guarantee the quality of the generated emails. A system to solve these issues is needed.

[0254] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0255] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for confirming whether the generated business emails conform to business communication standards, and means for confirming whether the generated business emails use appropriate honorific language, thereby reducing the time required to create business emails and ensuring quality.

[0256] "Short instructions" are brief instructions or keywords entered by the user, and are input information that the system uses to automatically generate business emails.

[0257] "Business email" refers to emails intended for official communication within and outside a company or organization, and are used for business communications, customer correspondence, etc.

[0258] "Auto-generation" refers to the process by which a system automatically creates text based on user input, eliminating the need for manual text creation.

[0259] "Grammar errors" refer to grammatical errors or inappropriate expressions within a sentence, and checking these ensures the accuracy of the sentence.

[0260] "Compliance" means checking whether an email conforms to laws, regulations, and a company's internal rules, and it involves checking whether business emails meet these standards.

[0261] "Business communication standards" refer to the manners, formalities, and methods of expression generally expected in business communication, and are used to check whether or not a document complies with these standards.

[0262] "Honorific language" refers to the use of language to show respect to the other person, and this is to check whether appropriate honorific language is used in business emails.

[0263] "Ensuring quality" means making sure that the generated business emails meet certain standards and assuring users of that quality.

[0264] The following system configuration will be described as an embodiment of the present invention.

[0265] System Configuration

[0266] This system consists of a server and a user terminal. The server automatically generates business emails using a generative AI model and performs various checks to ensure their quality. The user terminal provides an interface that allows users to input short instructions and check and edit the generated business emails.

[0267] Hardware and software used

[0268] Hardware: Servers and user devices connected to the Internet (smartphones, PCs, etc.)

[0269] Software: Python, OpenAI (registered trademark) API, web browser

[0270] Data processing and calculation

[0271] 1. User input: The user inputs a short instruction using the user terminal. For example, the user inputs a prompt sentence such as "Please generate a business email that explains to the customer how to use the electronic payment service."

[0272] 2. Email generation: The server uses the OpenAI (registered trademark) API to automatically generate a business email based on the input prompt text.

[0273] 3. Grammar Check: Check the generated business email for grammatical errors using natural language processing technology.

[0274] 4. Compliance check: Check whether the generated business email complies with laws and regulations.

[0275] 5. Quality Assurance: Ensure that generated business emails comply with business communication standards and use appropriate honorific language.

[0276] Specific examples

[0277] The user enters the following prompt text:

[0278] "Generate a business email to explain to customers how to use your electronic payment service."

[0279] The server uses the OpenAI® API to generate a business email like this:

[0280] "Thank you for your support. We would like to explain how to use our electronic payment service. First, please download the app, and then create an account. Please refer to the link below for detailed instructions. Sincerely."

[0281] The server then checks the generated email for grammatical errors, compliance with business communication standards, and the use of honorific language, providing users with quality-assured emails.

[0282] In this way, the user can quickly create high-quality business emails by simply inputting a few instructions.

[0283] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0284] Step 1:

[0285] The user inputs a short instruction (prompt sentence) using the user terminal.

[0286] Input: Prompt text (e.g., "Please generate a business email to explain to your customers how to use the electronic payment service.")

[0287] Output: The prompt text is sent to the server.

[0288] Step 2:

[0289] Based on the prompt received by the server, a business email is automatically generated using the OpenAI (registered trademark) API.

[0290] Input: prompt statement

[0291] Data processing: Using the OpenAI (registered trademark) API, prompt sentences are input into the generative AI model to generate business emails.

[0292] Output: Generated business email

[0293] Step 3:

[0294] The server checks generated business emails for grammatical errors.

[0295] Input: Generated business email

[0296] Data Computing: Detect grammatical errors using natural language processing techniques.

[0297] Output: A business email with grammar errors corrected

[0298] Step 4:

[0299] The server checks generated business emails for compliance.

[0300] Input: A business email with grammar corrections

[0301] Data calculation: Checks are carried out to ensure compliance with laws and regulations.

[0302] Output: Compliance verified business email

[0303] Step 5:

[0304] Verify that server-generated business emails comply with business communication standards.

[0305] Input: Compliance verified business email

[0306] Data Calculation: Checks are performed to ensure compliance with business communication standards.

[0307] Output: Business emails that meet business communication standards

[0308] Step 6:

[0309] Ensure that proper honorific language is used in business emails generated by the server.

[0310] Input: Business email that meets business communication standards

[0311] Data calculation: Checks are performed to ensure that honorific language is used appropriately.

[0312] Output: A business email with proper use of honorific language

[0313] Step 7:

[0314] The server sends quality-guaranteed business emails to the user terminal.

[0315] Input: A business email with proper use of honorific language

[0316] Output: Quality-guaranteed business emails are sent to the user's terminal.

[0317] Step 8:

[0318] Users can check and edit quality-guaranteed business emails on their devices.

[0319] Input: Quality-guaranteed business email

[0320] Output: The final business email is created.

[0321] Example 3

[0322] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0323] Traditionally, email creation was often done manually, which required time and effort, resulting in reduced work efficiency. Creating emails manually also carries the risk of grammatical errors and compliance violations. Furthermore, creating follow-up emails based on meeting minutes was particularly time-consuming and a burden on users.

[0324] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes means for uploading meeting minutes, means for analyzing the uploaded minutes, means for generating a prompt sentence based on the analysis result, means for automatically generating multiple emails using the generated prompt sentence, and means for providing the generated emails to the user. This enables automation and efficiency of email creation.

[0325] "Meeting minutes" are documents that record what was discussed during a meeting, decisions made, and comments made by participants.

[0326] The "means for uploading" is a function that allows a user to use a terminal to send a meeting minutes file to the system.

[0327] The "means of analysis" refers to the function by which the server converts the contents of the uploaded minutes file into text format and analyzes the contents using a generative AI model.

[0328] The "means for generating prompt sentences" is a function that creates instruction sentences to be input into the generative AI model based on the analysis results.

[0329] "Means for automatically generating emails" refers to a function that uses a generative AI model to create multiple emails based on generated prompt text.

[0330] The "means for providing to the user" is a function for sending the generated email to the user's email client or allowing the user to download it.

[0331] This invention is a system that relieves users from the burden of creating a huge amount of emails. The system has the function of automatically generating multiple emails based on the minutes of a meeting. A specific embodiment of this system is described below.

[0332] Hardware and software used

[0333] Hardware: Servers, devices (PCs, smartphones, etc.)

[0334] Software: Generative AI models (e.g., GPT-4®), email clients (e.g., Outlook, Gmail)

[0335] System Overview

[0336] A user uses a terminal to upload a meeting minutes file to the system. The server receives the uploaded minutes file and analyzes its contents using a generative AI model. Based on the analysis results, the server generates prompts to input into the generative AI model. Using the generated prompts, the server automatically generates multiple follow-up emails. The generated emails are sent to the user's email client or made available for the user to download.

[0337] Specific examples

[0338] For example, if a user uploads minutes stating, "At the meeting on October 1, 2023, we discussed the progress and next steps of the project. The participants were A, B, and C," the server will generate the following prompt:

[0339] Example prompt sentence:

[0340] "Please write a follow-up email to all participants based on the minutes of the following meeting. Minutes: At the meeting on October 1, 2023, we discussed the project progress and next steps. Participants were A, B, and C."

[0341] By inputting this prompt into the generative AI model, the server automatically generates a follow-up email like the one below.

[0342] Example of generated email:

[0343] "Thank you for your feedback during the meeting. Here are our next steps..."

[0344] In this way, the system saves the user the trouble of manually creating an email, and enables the user to carry out business efficiently. The flow of the specific processing in the third embodiment will be described with reference to FIG.

[0345] Step 1:

[0346] A user uploads meeting minutes. Using a terminal, the user accesses the system's web interface and clicks the "Select File" button to select a minutes file (e.g., a PDF or Word file) from local storage. The input is the minutes file, and the output is the minutes file sent to the server.

[0347] Step 2:

[0348] The server receives the minutes and converts them into text format. The server receives the uploaded minutes file and converts it into text format using OCR (Optical Character Recognition) technology. The input is the minutes file and the output is the minutes in text format.

[0349] Step 3:

[0350] The server analyzes the text minutes. The server uses a generative AI model (e.g., GPT-4 (registered trademark)) to analyze the content of the text minutes. Specifically, it extracts the meeting topic, participants, points discussed, etc. The input is the text minutes, and the output is the analysis results.

[0351] Step 4:

[0352] The server generates a prompt based on the analysis results. Based on the analysis results, the server generates a prompt to be input into the generative AI model. For example, a prompt might be generated that reads, "Please write a follow-up email to all participants based on the minutes of the following meeting. Minutes: At the meeting on October 1, 2023, we discussed the project's progress and next steps. Participants were A, B, and C." The input is the analysis results, and the output is the prompt.

[0353] Step 5:

[0354] The server automatically generates multiple emails using the generated prompt text. The server inputs the generated prompt text into a generative AI model, which automatically generates multiple follow-up emails. The generative AI model creates emails with the appropriate format and content based on the prompt text. For example, it generates an email with the content, "Dear Mr. A, thank you for your feedback at the meeting. The next steps are as follows..." The input is the prompt text, and the output is the generated email.

[0355] Step 6:

[0356] The server provides the generated email to the user. The server either sends the generated email to the user's email client or makes it available for the user to download, either by sending the email to the user's email address or by providing a "download" button on the system's web interface. The input is the generated email and the output is the email provided to the user.

[0357] Step 7:

[0358] The user reviews and sends the email. The user reviews the generated email and makes any necessary edits, such as adding a personalized message for a specific participant. The user then uses their email client to send the email to all participants. The input is the generated email and the output is the sent email.

[0359] (Application example 3)

[0360] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0361] At logistics centers, there is a problem of a huge volume of emails being generated regarding shipping status, inventory status, and delivery schedules, which reduces work efficiency. In addition, creating follow-up emails based on meeting minutes and daily reports takes time and effort, so there is a need to improve work efficiency.

[0362] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for generating follow-up emails in bulk based on meeting minutes and daily reports, means for inputting appropriate prompt sentences using a generative AI model, and means for automatically generating emails regarding shipping status, inventory status, and delivery schedules at a logistics center. This makes it possible to improve the efficiency and reduce the time required for email creation work at logistics centers.

[0363] "Short instructions" refer to brief text inputs or commands that the system uses to automatically generate business emails.

[0364] "Business email" refers to email for business purposes, and is used to contact business partners and internal stakeholders.

[0365] "Grammar mistakes" refers to grammatical errors in a sentence, and detecting and correcting these can improve the quality of emails.

[0366] "Compliance" refers to following laws, regulations, and a company's internal rules, and involves checking whether generated business emails comply with these.

[0367] "Meeting minutes" are documents that record the matters discussed and decisions made during a meeting, and are a source of information for generating follow-up emails.

[0368] A "daily report" is a report that records the progress and results of work on a daily basis, and is a source of information for generating follow-up emails.

[0369] A "follow-up email" is an additional communication email sent to relevant parties based on the progress of a meeting or task, informing them of next steps or confirmations.

[0370] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to generate text, automatically generating appropriate email content based on a prompt.

[0371] A "prompt" is a text instruction that is input into a generative AI model, serving as a guideline for the AI ​​to generate emails.

[0372] A "logistics center" is a facility that handles logistics operations such as storing, managing, shipping, and delivering goods, and is a place where efficient business operations are required.

[0373] "Shipping status" refers to the progress and status of product shipments, and is information used to contact relevant parties based on this.

[0374] "Inventory status" refers to the amount and condition of products in stock at the logistics center, and is information used to contact relevant parties based on this information.

[0375] "Delivery schedule" refers to the product delivery plan and timeline, and is information used to contact relevant parties based on this.

[0376] A system for carrying out this invention has the following configuration: A server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for generating follow-up emails in bulk based on meeting minutes and daily reports, means for inputting appropriate prompt sentences using a generative AI model, and means for automatically generating emails regarding shipping status, inventory status, and delivery schedules at a logistics center.

[0377] Hardware and software used

[0378] Hardware: Smartphones, servers

[0379] Software: Python, OpenAI® API

[0380] Data processing and calculation

[0381] 1. Data entry: Users enter text data such as meeting minutes and daily reports using their smartphones or other devices.

[0382] 2. Prompt generation: The server generates a prompt sentence appropriate for the generative AI model based on the input data.

[0383] 3. Email generation: The server uses a generative AI model (e.g., OpenAI's GPT-3®) to automatically generate an email based on the prompt.

[0384] 4. Grammar Check: Check the generated email for grammar errors and correct them if necessary.

[0385] 5. Compliance check: Check whether the generated email complies with laws, regulations, and internal company rules.

[0386] 6. Output: The generated email is displayed on the smartphone application so that the user can check it.

[0387] Specific examples

[0388] Let's take the example of automatically generating follow-up emails regarding shipping status and inventory management after a meeting at a logistics center. The user inputs the minutes of the meeting from a smartphone. For example, the following prompt sentences can be generated:

[0389] Example prompt sentence:

[0390] Minutes of the meeting:

[0391] 1. Check shipping status

[0392] 2. Improved inventory management

[0393] 3. Adjusting delivery schedules

[0394] Use the meeting minutes above to generate follow-up emails to all involved parties.

[0395] The server inputs this prompt into a generative AI model to automatically generate an appropriate follow-up email. The generated email is then checked for grammatical errors and compliance before finally being displayed on the user's smartphone. This improves the efficiency and reduces the time required for email creation at logistics centers.

[0396] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0397] Step 1:

[0398] Users input text data such as meeting minutes or daily reports from their smartphones or other devices. The input data is then sent to the server. Specifically, the user opens the smartphone application, inputs the contents of the minutes or daily reports in text format, and presses the send button.

[0399] Step 2:

[0400] The server analyzes the received text data and generates a prompt sentence suitable for the generative AI model. It processes the input data (minutes and daily reports) to construct an appropriate prompt sentence. Specifically, it analyzes the text data using natural language processing technology, extracts important points, and generates a prompt sentence.

[0401] Step 3:

[0402] The server inputs the generated prompt text into a generative AI model (e.g., GPT-3 (registered trademark) from OpenAI (registered trademark)) to automatically generate appropriate email content. Using the prompt text as input, the generative AI model generates the email body. Specifically, the server calls the API of the generative AI model, sends the prompt text, and retrieves the email content.

[0403] Step 4:

[0404] The server checks the generated email for grammatical errors and corrects them if necessary. Using the generated email as input, it uses a grammar checking tool (e.g., the Grammarly API) to detect and correct grammatical errors. Specifically, it sends the text of the generated email to the grammar checking tool and applies the suggested corrections it receives.

[0405] Step 5:

[0406] The server checks whether the generated email complies with laws, regulations, and the company's internal rules. The generated email is used as input to check compliance using a compliance check tool. Specifically, the content of the email is sent to the compliance check tool, and the evaluation result of compliance is obtained.

[0407] Step 6:

[0408] The server displays the final generated email on the smartphone application so that the user can check it. After corrections and checking are complete, the server sends the email to the user's smartphone as output. Specifically, the content of the email is displayed on the application interface so that the user can check and send it.

[0409] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0410] "Example 1"

[0411] In one embodiment of the present invention, a system is provided that includes an emotion engine that recognizes a user's emotions. The emotion engine analyzes the user's emotions from their tone of voice, facial expressions, and choice of words, and feeds the results back to the system. For example, if the user feels angry, the emotion engine communicates this information to the system, and the system takes this into account when generating a business email.

[0412] "Example 2"

[0413] In addition, the emotion engine adjusts the tone of automatically generated business emails based on the user's emotions. For example, if the user is happy, the tone of the generated email will be bright and positive. Conversely, if the user is sad, the tone of the generated email will be calm. This allows the recipient of the email to more accurately understand the sender's emotions.

[0414] "Example 3"

[0415] The emotion engine also adjusts the timing of email sending based on the user's emotions. For example, if the user feels angry, the emotion engine will communicate that information to the system, which will temporarily postpone sending the email. This allows the user time to calm down and prevents them from sending the wrong email based on emotional judgment.

[0416] The processing flow of each embodiment will be described below.

[0417] "Example 1"

[0418] Step 1: The user boots the system.

[0419] Step 2: The emotion engine analyzes the user's emotions based on their tone of voice, facial expressions, and choice of words.

[0420] Step 3: The emotion engine feeds the analysis results back to the system.

[0421] Step 4: The system takes your feedback into account and generates a business email.

[0422] "Example 2"

[0423] Step 1: The user boots the system.

[0424] Step 2: The emotion engine analyzes the user's emotions.

[0425] Step 3: The sentiment engine adjusts the tone of the email based on the analysis.

[0426] Step 4: The system generates a business email taking into account the adjusted tone.

[0427] "Example 3"

[0428] Step 1: The user boots the system.

[0429] Step 2: The emotion engine analyzes the user's emotions.

[0430] Step 3: The emotion engine adjusts the timing of email sending based on the analysis results.

[0431] Step 4: The system generates business emails taking into account the adjusted sending timing and sends them at the appropriate time.

[0432] Example 1

[0433] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0434] Conventional business email generation systems generate emails without considering the user's emotions, often failing to reflect the appropriate tone or content. They also lack sufficient checks for grammatical errors and compliance violations, making quality assurance difficult. Furthermore, creating emails takes a lot of time, reducing work efficiency.

[0435] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0436] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for analyzing the user's emotions, and means for generating business emails based on the analyzed emotions. This makes it possible to automatically generate business emails with an appropriate tone that reflects the user's emotions, and to efficiently create high-quality emails that are free of grammatical errors and compliance violations.

[0437] A "short command" is a brief command or request that a user enters into the system.

[0438] "Business email" refers to email sent for business purposes such as business communication and information sharing.

[0439] "Means for automatic generation" refers to functions or processes that automatically create business emails based on user instructions.

[0440] "Means for checking grammar errors" refers to the functions and processes that detect and correct grammatical errors in generated business emails.

[0441] "Means for checking compliance" refers to functions and processes that check whether generated business emails violate laws, regulations, or company rules.

[0442] "Means for analyzing user emotions" refers to the functions and processes that recognize and analyze emotions from the user's tone of voice, facial expressions, etc.

[0443] "Means for generating business emails based on analyzed emotions" refers to a function or process for creating business emails taking into account the analyzed emotional information of the user.

[0444] MODE FOR CARRYING OUT THE INVENTION

[0445] This invention is a system that streamlines the creation and proofreading of business emails. It automatically creates business emails based on short user instructions and has the function of checking for grammatical errors and compliance violations. It can also analyze user emotions and generate business emails that reflect the results.

[0446] Hardware and software used

[0447] The system uses the following hardware and software:

[0448] Terminal: A device that allows a user to input instructions. It is equipped with a microphone and a camera to capture the user's tone of voice and facial expressions.

[0449] Server: A central processing unit for automatically generating business emails, checking grammar, compliance, and sentiment analysis.

[0450] Generative AI model: An artificial intelligence model for automatically generating business emails, such as OpenAI's GPT-4.

[0451] Grammar checking tools: Software to detect grammatical errors in generated emails. For example, use Grammarly.

[0452] Compliance checking software: Software that checks whether generated emails violate laws, regulations, or company rules.

[0453] System Operation

[0454] 1. User input:

[0455] A user uses a terminal to input a short instruction to the system, such as "Please send me a reminder email for next week's meeting."

[0456] 2. Emotion analysis:

[0457] The emotion engine analyzes the user's tone of voice and facial expressions via the device's built-in microphone and camera, recognizing whether the user is angry, happy, or calm, and feeding the results back to the server.

[0458] 3. Automatic generation of business emails:

[0459] The server automatically generates business emails using a generative AI model (e.g., OpenAI's GPT-4®) based on instructions received from the user and feedback from the emotion engine. The generated emails take the user's emotions into account.

[0460] 4. Grammar and Compliance Checks:

[0461] The server runs the generated email through an internal grammar checking tool (Grammarly) and compliance checking software to check for grammatical errors and compliance violations.

[0462] 5. User Feedback:

[0463] The server sends emails that pass the check to the terminal and displays them to the user, who can then check the contents of the email and make any necessary corrections.

[0464] Specific examples

[0465] The user prompts the system with the following:

[0466] Please send me a reminder email for next week's meeting.

[0467] An example of how the system works is as follows:

[0468] 1. A user types, "Send me a reminder email for next week's meeting."

[0469] 2. The emotion engine analyzes the user's tone of voice and facial expression and determines that the user is calm.

[0470] 3. The server uses a generative AI model (GPT-4 (registered trademark)) to automatically generate a business email like this:

[0471] Subject: Meeting reminder next week

[0472] Everyone

[0473] This is a reminder of a meeting scheduled for next Monday. Details are below.

[0474] Date and time: Monday, October 16, 2023 10:00 AM

[0475] Location: Conference Room 1

[0476] We look forward to your attendance.

[0477] Thank you very much.

[0478] [User Name]

[0479] 4. The server runs the generated email through a grammar checking tool (Grammarly) to check for grammatical errors, and then uses compliance checking software to check whether the email content violates company policies.

[0480] 5. Emails that pass the check are sent to the terminal and displayed to the user, who can then check the contents of the email and make any necessary corrections.

[0481] In this way, users can efficiently generate and edit business emails that take emotions into account by simply entering a few instructions.

[0482] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0483] Step 1:

[0484] A user uses a terminal to input short instructions to the system, such as "Please send me a reminder email for next week's meeting." The terminal receives this instruction and sends it to the server. The input is the user's instruction, and the output is instruction data for the server.

[0485] Step 2:

[0486] The device uses a built-in microphone and camera to capture the user's tone of voice and facial expressions in real time. The emotion engine analyzes this data and determines whether the user is calm. The analysis results are sent to the server. The input is the user's voice and video data, and the output is analyzed emotional data.

[0487] Step 3:

[0488] The server receives the user's instructions and feedback from the emotion engine, and inputs a prompt sentence into the generative AI model (GPT-4 (registered trademark)). The prompt sentence is as follows: "The user is calm. Please generate a reminder email for next week's meeting." The generative AI model generates a business email based on this prompt sentence. The input is the prompt sentence, and the output is the generated business email.

[0489] Step 4:

[0490] The server runs the generated email through a grammar checking tool (Grammarly) to check for grammatical errors. It then uses compliance checking software to check whether the email content violates company policies. The input is the generated business email, and the output is an email that has been checked for grammar and compliance.

[0491] Step 5:

[0492] The server sends emails that pass the check to the terminal. The terminal displays the email to the user, who checks the content. If necessary, the user corrects the content of the email and prepares it for final sending. The input is the checked business email, and the output is the email displayed to the user.

[0493] In this way, users can efficiently generate and edit business emails that take emotions into account by simply entering a few instructions.

[0494] (Application example 1)

[0495] Next, a description will be given of Application Example 1 of Embodiment 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."

[0496] Conventional business email generation systems were able to generate emails from short instructions and check grammar and compliance, but they were unable to generate emails that took the user's emotions into consideration. This made it difficult to respond appropriately based on the user's emotions, which could lead to a decline in the quality of customer service. Furthermore, there was a lack of concrete measures to improve the efficiency of customer service in physical stores.

[0497] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0498] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for converting the short instructions into text using voice recognition, means for analyzing the user's emotions using a camera, means for generating business emails based on the user's emotions, and means for displaying the generated business emails on a display device. This makes it possible to generate appropriate business emails that take the user's emotions into consideration, thereby improving the quality of customer service in physical stores.

[0499] A "short instruction" is a brief instruction entered by a user, and includes information necessary for generating a business email.

[0500] "Business email" refers to emails intended for business communication and have the appearance of a formal document.

[0501] "Grammar mistakes" refers to grammatical errors or inappropriate expressions in a sentence.

[0502] "Compliance" refers to following laws, regulations, and a company's internal rules, and checking that business emails do not violate these.

[0503] "Speech recognition" is a technology that analyzes a user's voice and converts it into text.

[0504] A "camera" is a device that captures video and is used to capture the user's facial expressions and movements.

[0505] "Emotion analysis" is a technology that analyzes a user's emotions from facial expressions, tone of voice, etc.

[0506] A "display device" is a device for visually displaying the generated business email, and includes smart glasses, displays, etc.

[0507] "User" means an individual or member of an organization who uses the System to generate business email.

[0508] "Automatic generation" is the process by which a system automatically creates business emails based on user instructions.

[0509] The system for implementing this invention uses the following hardware and software: smart glasses, a microphone, and a camera. The software uses Python, the speech_recognition library, the transformers library, and OpenCV.

[0510] The server provides a means for automatically generating business emails from short instructions. Specifically, it uses speech recognition to convert the user's speech into text, and then generates the business email based on the text using a generative AI model (e.g., GPT-3 (registered trademark)). The generated business email is then checked through means for grammar and compliance checks.

[0511] The system also includes a means for analyzing the user's emotions using a camera. The video captured by the camera is analyzed using an emotion analysis model, and the content of business emails is adjusted based on the results. For example, if the user is angry, the system will adjust the content to use more polite language.

[0512] The generated business emails are displayed on the smart glasses' display, which improves the efficiency of customer service in brick-and-mortar stores and allows users to respond quickly and appropriately.

[0513] As a specific example, if a user instructs the system to "check product inventory" and emotion analysis detects "anger," the system will generate a business email like the one below.

[0514] Example prompt sentence:

[0515] User Instructions: Check product availability

[0516] User Emotion: Anger

[0517] Generate proper business emails.

[0518] Example of a generated business email:

[0519] Dear customer, we have checked the product inventory and it is currently out of stock. We apologize for any inconvenience caused.

[0520] In this way, it becomes possible to generate appropriate business emails that take into account the user's emotions, thereby improving the quality of customer service in physical stores.

[0521] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0522] Step 1:

[0523] The user puts on the smart glasses and speaks short instructions into the microphone.

[0524] Input: User's voice commands

[0525] Output: Audio data

[0526] Step 2:

[0527] The device uses voice recognition to convert the voice data into text. Specifically, it uses the speech_recognition library to analyze the voice data and generate text data.

[0528] Input: Audio data

[0529] Output: Text data

[0530] Step 3:

[0531] The terminal uses a camera to capture a picture of the user's face and acquires video data.

[0532] Input: User's face video

[0533] Output: Video data

[0534] Step 4:

[0535] The server performs emotion analysis using the video data. Specifically, it analyzes the user's emotions using an emotion analysis model and obtains the results.

[0536] Input: Video data

[0537] Output: Emotion data (e.g., anger, joy, etc.)

[0538] Step 5:

[0539] The server automatically generates business emails using a generative AI model (e.g., GPT-3 (registered trademark)) based on text data and emotion data. A prompt sentence is input into the generative AI model, and an appropriate business email is output.

[0540] Input: Text data, emotion data

[0541] Output: Generated business email

[0542] Step 6:

[0543] The server performs grammar and compliance checks on the generated business emails. Specifically, it uses grammar and compliance check tools to check the quality of the emails.

[0544] Input: Generated business email

[0545] Output: Business emails checked for grammar and compliance

[0546] Step 7:

[0547] The server sends the verified business email to the display device of the smart glasses and displays it to the user.

[0548] Input: Business email checked for grammar and compliance

[0549] Output: Business email displayed on smart glasses

[0550] In this way, users can quickly generate appropriate business emails that take emotions into consideration and respond to customers through smart glasses.

[0551] Example 2

[0552] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0553] Conventional business document creation systems lacked automatic document generation and quality assurance, requiring users to manually edit documents. Furthermore, they lacked the ability to adjust the tone of a document to match the user's emotions, making it difficult to express appropriate emotions to the recipient. This resulted in reduced document creation efficiency and inconsistent quality.

[0554] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0555] In this invention, the server includes means for automatically generating business documents from short instructions, means for checking the generated business documents for grammatical errors, means for checking the generated business documents for conformance with standards, means for assuring the quality of the generated business documents, and means for adjusting the tone of the business documents based on the user's emotions. This improves the efficiency of document creation and reduces variations in quality. Furthermore, by generating documents with an appropriate tone based on the user's emotions, the user's emotions can be more accurately expressed to the recipient.

[0556] "Short instructions" are brief text instructions entered by the user that contain the basic information needed to generate a business document.

[0557] "Business documents" are official documents used for business communications and transactions, including emails, reports, proposals, etc.

[0558] "Grammar errors" refer to grammatical errors or inappropriate expressions in a document that need to be corrected based on correct grammar.

[0559] "Standards conformance" refers to whether the generated business documents conform to industry standards or company standards.

[0560] "Quality assurance" is the process of verifying and ensuring that generated business documents meet certain quality standards.

[0561] "Adjusting tone based on emotion" means analyzing the user's emotional state and appropriately changing the expression and mood of the document accordingly.

[0562] A "generative AI model" is an algorithm or system that uses artificial intelligence technology to generate text, automatically generating business documents based on user instructions.

[0563] A "prompt" is an instruction that a user inputs into a generative AI model, specifying the content and format of the business document to be generated.

[0564] The present invention relates to a system for automatically generating business documents from short instructions and for guaranteeing the quality of the generated documents. A specific embodiment of this system will be described below.

[0565] System configuration

[0566] The system consists of three main components: a server, a terminal, and a user. The server automatically generates business documents using a generative AI model and checks for grammatical errors and conformance to standards. The terminal provides an interface for users to input prompts and review and correct the generated documents.

[0567] Hardware and software used

[0568] Server: A server with high-performance computing capabilities is required. Specifically, a server equipped with a GPU is preferable.

[0569] Generative AI model: For example, GPT-4 (registered trademark) is used as the generative AI model.

[0570] Terminal: A device, such as a computer or smartphone, that allows a user to enter prompt text.

[0571] Software: Generative AI models running on servers, grammar checkers, norm conformance checkers, emotion engines, etc.

[0572] Data processing and calculation

[0573] 1. Data Entry:

[0574] The user inputs a prompt through the terminal interface, for example, "Please create an email to introduce a new product. The product name is 'SuperWidget', and its main features are high-speed processing and low power consumption."

[0575] 2. Send the prompt:

[0576] The terminal sends the prompt sentence entered by the user to the server.

[0577] 3. Business document generation:

[0578] The server inputs the received prompt sentence into a generative AI model (e.g., GPT-4 (registered trademark)) to generate a business document.

[0579] 4. Check for grammar errors:

[0580] The server checks the generated document for grammar errors. It uses a grammar checking tool to detect and correct grammatical errors.

[0581] 5. Normative Conformance Check:

[0582] The server checks the generated document for conformance to industry standards and corporate codes, using a code conformance checking tool to make any necessary corrections.

[0583] 6. Quality Guarantee:

[0584] The server performs grammar and conformance checks, followed by a final quality check, to ensure the quality of the generated document.

[0585] 7. Applying the Emotion Engine:

[0586] The server analyzes the user's emotional data and adjusts the tone of the document using an emotion engine. For example, if the user is happy, the tone of the document will be bright and positive.

[0587] 8. Sending documents:

[0588] The server sends the final business document to the terminal, which displays the received document to the user.

[0589] Specific examples

[0590] If a user wants to create an email introducing a new product, he or she enters the following prompt text:

[0591] Example prompt sentence:

[0592] "Please create an email to introduce a new product. The product name is 'SuperWidget' and its main features are high-speed processing and low power consumption."

[0593] The server receives this prompt and uses a generative AI model to generate a business document like the one below.

[0594] An example of the generated document:

[0595] "Dear customers, we would like to introduce our new product, SuperWidget. SuperWidget is equipped with the latest technology that achieves high-speed processing and low power consumption. Please take this opportunity to try it out."

[0596] In this way, the system processes a series of steps from user input to the generation of the final business document.

[0597] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0598] Step 1:

[0599] The user enters a prompt statement.

[0600] The user inputs a prompt through the device interface. For example, the user might input, "Please create an email introducing a new product. The product name is 'SuperWidget', and its main features are high-speed processing and low power consumption." The input prompt is temporarily stored in the device's memory.

[0601] Step 2:

[0602] The terminal sends the prompt to the server.

[0603] The terminal sends the prompt text entered by the user to the server. The sent prompt text is sent to the server in an appropriate data format such as JSON. The server analyzes the received prompt text and proceeds to the next process.

[0604] Step 3:

[0605] The server generates business documents using the generative AI model.

[0606] The server inputs the received prompt sentence into a generative AI model (e.g., GPT-4 (registered trademark)) to generate a business document. The generative AI model creates a document with appropriate content based on the prompt sentence. The generated document is stored in the server's memory.

[0607] Step 4:

[0608] Server-generated documents are checked for syntax errors.

[0609] The server uses a grammar checker to check the generated document for grammatical errors. The grammar checker detects grammatical errors in the document and makes necessary corrections. The corrected document is saved back in the server's memory.

[0610] Step 5:

[0611] The server checks the generated document for normative conformance.

[0612] The server uses a conformance checker to check whether the generated document conforms to industry standards or company regulations. The conformance checker detects inappropriate expressions or content in the document and makes the necessary corrections. The corrected document is then saved back into the server's memory.

[0613] Step 6:

[0614] The server guarantees the quality of the generated documents.

[0615] The server performs a grammar check and a conformance check to ensure the quality of the generated document, and then a final quality check. Once the quality check is complete, the document is stored in the server's memory.

[0616] Step 7:

[0617] The server applies an emotion engine to adjust the tone of the document.

[0618] The server analyzes the user's emotional data and adjusts the tone of the document using an emotion engine. For example, if the user is happy, the tone of the document will be bright and positive. The adjusted document is then stored in the server's memory.

[0619] Step 8:

[0620] The server sends the final document to the device.

[0621] The server sends the final document after quality checks and tone adjustments to the terminal, which then displays the received document to the user, who can then review the document and make corrections as necessary.

[0622] (Application example 2)

[0623] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0624] Conventional business email generation systems offer features such as automatic email generation, grammar checks, and compliance checks, but lack the ability to adjust the tone of the email based on the user's emotions, making it difficult to convey the appropriate emotion to the recipient. Furthermore, while store staff are required to generate emails quickly and appropriately when dealing with customers, current systems are unable to do this efficiently. Furthermore, the lack of systems compatible with wearable devices such as smart glasses limits their use in physical stores.

[0625] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0626] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking compliance of the generated business emails, means for recognizing a user's emotion, means for adjusting the tone of the business emails based on the user's emotion, means for ensuring the quality of the generated business emails, and means installed in the smart glasses, thereby enabling store staff to quickly generate business emails with an appropriate tone based on the user's emotion when dealing with customers and ensure the quality of the emails.

[0627] "Short instructions" are instructions or information that are briefly entered by the user, and are input data that the system uses to automatically generate business emails.

[0628] "Business email" refers to emails intended for business communication, which require a formal writing style and appropriate honorific language.

[0629] "Grammar mistakes" are grammatical errors in a sentence, and refer to mistakes in the proper use of words and syntax.

[0630] "Compliance" means following laws, regulations, and a company's internal rules, and refers to checking whether business emails comply with these.

[0631] "User emotion" refers to the emotional state of the user using the system, including emotions such as joy, sadness, and anger.

[0632] "Tone" refers to the tone and mood of a sentence or word, and is adjusted based on the user's emotions.

[0633] "Ensuring quality" means checking and guaranteeing that generated business emails meet certain standards.

[0634] "Smart glasses" are a type of wearable device that incorporates a display and sensors into a glasses-type device.

[0635] A "brick and mortar store" is a store that exists in a physical location and where customers visit in person to purchase goods or services.

[0636] As an embodiment of this invention, we provide a system that generates appropriate business emails and messages in real time and sends them to customers when staff at a physical store wear smart glasses and deal with customers.

[0637] System configuration

[0638] The system consists of the following main components:

[0639] 1. Smart glasses: Wearable devices that incorporate a display, camera, and microphone.

[0640] 2. Server: Responsible for email generation, grammar checking, compliance checking, emotion recognition, tone adjustment, and quality assurance.

[0641] 3. User device: Used by store staff wearing smart glasses.

[0642] Program processing

[0643] The server does the following:

[0644] 1. Receiving a short instruction: Receive a short instruction from the user terminal.

[0645] 2. Emotion Recognition: Recognize the user's emotions using the camera and microphone of the smart glasses. For emotion recognition, use "emotion_recognition.EmotionEngine", for example.

[0646] 3. Email generation: Use a generative AI model (e.g., GPT-3 (registered trademark)) to generate business emails based on short instructions and recognized sentiment. Use "email_generator.EmailGenerator" to generate emails.

[0647] 4. Grammar check: Check the generated email for grammar errors. Use "quality_checker.QualityChecker" for grammar check.

[0648] 5. Compliance check: Check whether the generated email complies with laws and regulations.

[0649] 6. Adjust your tone: Adjust the tone of your email based on the user's emotions.

[0650] 7. Quality Assurance: Ensure the quality of the final email generated.

[0651] Specific examples

[0652] For example, if a brick-and-mortar store associate is wearing smart glasses and a customer asks about a new product, they might enter a prompt like this:

[0653] A customer asks about a new product. Your staff is excited. Generate the right business email.

[0654] Based on this prompt, the server recognizes the user's emotion (happiness) and generates a business email with a bright and positive tone. The generated email undergoes grammar and compliance checks and is finally sent to the customer with quality guaranteed.

[0655] This system will enable store staff to respond to customers quickly and appropriately, which is expected to improve customer satisfaction.

[0656] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0657] Step 1:

[0658] A user wears smart glasses and receives questions or requests from customers. The user uses the smart glasses' voice input function to input short instructions, such as "A customer is asking about a new product." This instruction becomes input data for the system.

[0659] Step 2:

[0660] The device converts the user's voice input into text data and sends it to the server. Speech recognition software is used to convert the voice data into text data, which then becomes the input for the next processing step.

[0661] Step 3:

[0662] The server uses the smart glasses' camera and microphone to recognize the user's emotions. It then uses an emotion recognition engine (e.g., emotion_recognition.EmotionEngine) to analyze the user's emotions from their facial expressions and tone of voice. The analysis results are output as the user's emotional state (e.g., joy, sadness).

[0663] Step 4:

[0664] The server generates a business email using a generative AI model (e.g., GPT-3 (registered trademark)) based on the emotion recognition results and text data. A prompt sentence is input into the generative AI model, which generates an appropriate business email. The generated business email becomes the input for the next processing step.

[0665] Step 5:

[0666] The server checks the generated business email for grammatical errors. It uses grammar checking software (e.g. quality_checker.QualityChecker) to detect and correct grammatical errors in the email. The corrected email becomes the input for the next processing step.

[0667] Step 6:

[0668] The server checks the generated business email for compliance. Compliance checking software is used to check whether the email complies with laws and regulations. If the email complies, it proceeds to the next processing step. If it does not comply, corrections are made.

[0669] Step 7:

[0670] The server adjusts the tone of the generated business email based on the user's emotions. Based on the emotion recognition results, the tone of the email can be brightened or calmed. The adjusted email becomes the input for the next processing step.

[0671] Step 8:

[0672] The server ensures the quality of the final business email. Quality assurance software is used to check that the email meets certain standards. If it does, the email is sent to the customer.

[0673] Step 9:

[0674] The terminal receives the final business email sent from the server and displays it to the user, who can then check the generated email through the smart glasses display and send it to their customer if necessary.

[0675] Example 3

[0676] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0677] Conventional business email creation systems can automatically generate emails and check grammar and compliance, but they cannot adjust the timing of email sending based on the user's emotional state, which can lead to incorrect emails being sent due to emotional judgment. Furthermore, there is a lack of efficient ways to relieve users from the enormous task of creating emails.

[0678] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for detecting the user's emotional state, means for adjusting the timing of sending the email based on the user's emotional state, and means for generating emails based on prompt sentences using a generative AI model. This makes it possible to efficiently create emails while taking the user's emotional state into consideration and prevent erroneous emails from being sent due to emotional judgment.

[0679] "Short instructions" refer to instructions entered by the user in a concise format, and are information that the system uses to automatically generate business emails based on these instructions.

[0680] "Business email" refers to email created for the purpose of business communication, with a formal style and content.

[0681] "Grammar errors" refers to grammatical errors in text, and detecting and correcting these can improve the quality of emails.

[0682] "Compliance" refers to following laws, regulations, and a company's internal rules, and involves checking whether the content of an email violates these.

[0683] "User's emotional state" refers to the user's current emotions, and is information for adjusting the timing of sending emails by detecting this.

[0684] An "emotion engine" is a software or hardware system for analyzing emotions from a user's facial expressions, voice, etc.

[0685] A "generative AI model" refers to a model that uses artificial intelligence to generate text, generating appropriate email content based on a prompt.

[0686] A "prompt sentence" is an instruction sentence input to a generative AI model, and is the basic information that the AI ​​uses to generate text.

[0687] The "means for adjusting the timing of sending email" is a function for appropriately changing the timing of sending email based on the emotional state of the user.

[0688] The present invention is a system that relieves users from the burden of creating large amounts of e-mail and enables them to send e-mails efficiently and with consideration for their emotions. A specific embodiment of this system will be described below.

[0689] Hardware and software used

[0690] Hardware: Servers, terminals (PCs, smartphones)

[0691] Software: Generative AI models (e.g., GPT-4®), emotion engines, email clients (e.g., Outlook, Gmail)

[0692] System Overview

[0693] The system automatically generates business emails from short instructions, checks the generated emails for grammatical errors and compliance, and has the ability to detect the user's emotional state and adjust the timing of sending emails based on their emotions.

[0694] System Operation

[0695] 1. The user inputs the meeting minutes data into the terminal.

[0696] After the meeting, the user enters the minutes into a text editor, for example, "At the meeting, the progress of the project was reported and the next task was assigned."

[0697] 2. The device sends the entered minutes data to the server.

[0698] The terminal sends the entered minutes data to the server. When you click the send button, the data is sent to the server using the HTTPS protocol.

[0699] 3. The server generates a prompt for the AI ​​model and generates an email based on the minutes data.

[0700] The server generates a prompt for the generative AI model saying, "Please generate follow-up emails for all participants based on the minutes below," and adds the minutes data.

[0701] The generative AI model generates appropriate follow-up emails based on the prompt text.

[0702] Examples:

[0703] Prompt: "Generate a follow-up email to all participants based on the following minutes: 'The meeting reported on project progress and assigned upcoming tasks.'"

[0704] Generated email: "Hey everyone, based on the meeting minutes, I'd like to let you know the next tasks. We're on track with the project. The next tasks are..."

[0705] 4. The server sends the generated email to the device

[0706] The server sends the generated email to the terminal, and the user checks the generated email using the email client on the terminal.

[0707] 5. The device detects the user's emotional state using an emotion engine.

[0708] The device analyzes the user's facial expressions and voice using an emotion engine. For example, if the user is angry, the emotion engine will detect that information.

[0709] 6. The emotion engine sends the user's emotional state to the server.

[0710] The emotion engine sends the analysis results to the server. If the user is angry, it sends the information that "the user is angry" to the server.

[0711] 7. The server adjusts the timing of sending emails based on the information from the emotion engine.

[0712] The server adjusts the timing of sending emails based on information from the emotion engine. If the user is angry, the server temporarily suspends sending the email.

[0713] 8. The server sends the email

[0714] The server waits for a certain period of time until the user calms down, and then sends the email. The email is sent to all participants.

[0715] In this way, the system can efficiently create emails while taking into account the emotional state of the user, and can prevent erroneous emails from being sent due to emotional judgment. The flow of the identification process in the third embodiment will be described with reference to FIG.

[0716] Step 1:

[0717] The user inputs the minutes data of the meeting into the terminal.

[0718] Input: A user types meeting minutes into a text editor, for example, "At the meeting, project status was reported and next tasks were assigned."

[0719] Data processing: The device stores the entered text data in its internal memory.

[0720] Output: Saved meeting minutes data.

[0721] Step 2:

[0722] The terminal transmits the input minutes data to the server.

[0723] Input: Saved meeting minutes data.

[0724] Data processing: The terminal sends the minutes data to the server using the HTTPS protocol.

[0725] Output: The transcript data sent to the server.

[0726] Step 3:

[0727] The server generates a prompt sentence for the generative AI model and generates an email based on the minutes data.

[0728] Input: Minutes data sent to the server.

[0729] Data processing: The server generates a prompt for the generative AI model saying, "Please generate follow-up emails for all participants based on the minutes below," and adds the minutes data.

[0730] Data calculation: The generative AI model generates appropriate follow-up emails based on the prompt text.

[0731] Output: The generated follow-up email.

[0732] Step 4:

[0733] The server sends the generated email to the terminal.

[0734] Input: The generated follow-up email.

[0735] Data processing: The server sends the generated email to the terminal.

[0736] Output: A follow-up email sent to the device.

[0737] Step 5:

[0738] The device detects the user's emotional state using an emotion engine.

[0739] Input: User facial and voice data.

[0740] Data calculation: The device uses an emotion engine to analyze the user's emotions from their facial expressions and voice. For example, if the user is angry, it will detect that information.

[0741] Output: The detected emotional state of the user.

[0742] Step 6:

[0743] The emotion engine transmits the user's emotional state to the server.

[0744] Input: The detected emotional state of the user.

[0745] Data processing: The emotion engine sends the analysis results to the server. For example, it sends information to the server that "the user is angry."

[0746] Output: The user's emotional state sent to the server.

[0747] Step 7:

[0748] The server adjusts the timing of sending emails based on information from the emotion engine.

[0749] Input: The user's emotional state sent to the server.

[0750] Data calculation: The server adjusts the timing of sending emails based on information from the emotion engine. If the user is angry, the server temporarily suspends sending emails.

[0751] Output: Adjusted email sending timing.

[0752] Step 8:

[0753] The server sends the email.

[0754] Input: The adjusted email send timing.

[0755] Data processing: The server waits a certain period of time until the user calms down, and then sends the email.

[0756] Output: Email sent to all participants.

[0757] (Application example 3)

[0758] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0759] Conventional business email creation systems automatically generate emails and check grammar and compliance, but they do not adjust the timing of email transmissions based on the user's emotional state or automatically generate and send reports based on data within the factory, which increases user stress and the risk of sending emails incorrectly. Additionally, there was a lack of a way to efficiently manage data within the factory and report at the appropriate time.

[0760] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for detecting the user's emotional state using an emotion engine and adjusting the timing of email transmission based on the specific emotional state, means for automatically generating reports based on data collected from various sensors and robots in the factory, and means for sending the generated reports by email. This makes it possible to adjust the timing of email transmission taking the user's emotional state into consideration, making it possible to efficiently manage data in the factory and report at the appropriate time.

[0761] "Short instructions" are instructions or commands entered by the user in a concise format, and are the input information used by the system to automatically generate business emails.

[0762] "Business email" refers to email created for business purposes such as business communications, reports, and requests.

[0763] "Grammar errors" refer to grammatical errors and inappropriate expressions in a sentence, and checking for these can improve the quality of an email.

[0764] "Compliance" means following laws, regulations, and a company's internal rules, and checking whether business emails comply with these.

[0765] An "emotion engine" is a technology that detects the user's emotional state and adjusts the system's behavior based on that information.

[0766] An "emotional state" is an emotion that a user is feeling, such as anger, joy, or sadness.

[0767] "Send timing" refers to the timing of sending emails and reports, and is adjusted based on the user's emotional state.

[0768] A "sensor" is a device that detects physical phenomena and outputs them as data.

[0769] A "robot" is a mechanical device used to automate work within a factory, and is often equipped with various sensors.

[0770] A "report" is a report that summarizes various data within the factory, and can be automatically generated and sent by email.

[0771] "Data" refers to the information collected from sensors and robots, which is used to generate reports.

[0772] A system for carrying out this invention has the following configuration: A server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for detecting the emotional state of a user using an emotion engine and adjusting the timing of sending emails based on the specific emotional state, means for automatically generating reports based on data collected from various sensors and robots in a factory, and means for sending the generated reports by email.

[0773] System program processing explanation

[0774] The server first receives a short instruction from the user and then automatically generates a business email using a generative AI model. It then uses a natural language processing library (e.g., NLTK or spaCy) to check the generated business email for grammatical errors. It also checks the generated business email for compliance with pre-defined rules and regulations.

[0775] Next, the system uses an emotion engine to detect the user's emotional state. This emotion engine analyzes the user's facial expressions and tone of voice using, for example, a camera or microphone. If the emotional state is "anger," the system temporarily suspends sending the email and waits until the user calms down.

[0776] Furthermore, reports are automatically generated based on data collected from various sensors and robots in the factory. This data is obtained, for example, from temperature sensors and production line robots. An IoT platform (e.g., AWS (registered trademark) IoT or Google (registered trademark) Cloud IoT) is used to collect and analyze the data. The generated reports are automatically sent by email, either periodically or when an abnormality is detected.

[0777] Specific examples

[0778] For example, when a factory manager inputs a short instruction into the system, such as "Please report on this week's production status," the server uses a generative AI model to automatically generate an appropriate business email. This email will be sent only if the manager's emotional state is not "angry," after passing grammar and compliance checks.

[0779] In addition, periodic reports are automatically generated based on data collected from sensors within the factory. These reports, such as "This week's production line utilization rate was 95%. No abnormalities were detected," are sent to the manager via email.

[0780] Prompt Sentence Examples

[0781] The following prompts can be fed to the generative AI model:

[0782] Create a program that generates periodic reports based on data collected from sensors in the factory and emails them to the manager. Also, add a function that detects the user's emotional state and withholds emails if the user is angry.

[0783] By using this prompt sentence, the generative AI model can generate a program to realize the system described above.

[0784] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0785] Step 1:

[0786] The user inputs a short instruction. For example, the user inputs a simple instruction into the terminal, such as "Please report on this week's production status." This input becomes the initial data for the system.

[0787] Step 2:

[0788] The server automatically generates business emails using a generative AI model. The server receives short instructions from the user and inputs them as prompts to the generative AI model. The generative AI model generates appropriate business emails based on these prompts. The output is the generated business email.

[0789] Step 3:

[0790] The server checks the generated business email for grammatical errors. The server uses a natural language processing library (e.g., NLTK or spaCy) to detect and correct grammatical errors in the generated business email. The input is the generated business email, and the output is the business email with the grammatical errors corrected.

[0791] Step 4:

[0792] The server checks the generated business email for compliance. The server checks whether the generated business email complies with pre-defined rules and laws. The input is a business email with grammatical errors corrected, and the output is a business email that has passed the compliance check.

[0793] Step 5:

[0794] The server uses an emotion engine to detect the user's emotional state. The server uses a camera and microphone to analyze the user's facial expressions and tone of voice and inputs the results into the emotion engine. The emotion engine classifies the user's emotional state into categories such as "anger," "joy," and "sadness." The input is the user's facial and voice data, and the output is the user's emotional state.

[0795] Step 6:

[0796] The server adjusts the timing of sending emails based on the user's emotional state. The server determines whether to temporarily suspend sending emails based on the user's emotional state obtained from the emotion engine. For example, if the user is in an "angry" state, the server suspends sending emails and waits until the user calms down. The input is the user's emotional state, and the output is adjusting the timing of sending emails.

[0797] Step 7:

[0798] The server collects data from various sensors and robots in the factory. Using an IoT platform (for example, AWS IoT or Google Cloud IoT), the server collects data from temperature sensors in the factory and robots on the production line. The input is data from the sensors and robots, and the output is the collected data.

[0799] Step 8:

[0800] The server automatically generates reports based on the data collected. The server analyzes the collected data and automatically generates periodic reports and reports when an abnormality occurs. The input is the collected data, and the output is the generated report.

[0801] Step 9:

[0802] The server sends the generated report by email. The server sends the generated report by email to the administrator at the appropriate time. The input is the generated report and the output is the sent email.

[0803] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0804] The data generation model 58 is a so-called generative AI (Artificial Intelligence). Examples of the data generation model 58 include generative AIs such as ChatGPT (registered trademark) (Internet search <URL: https: / / OpenAI (registered trademark).com / blog / chatgpt>). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is input thereto. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summary, etc.

[0805] Other examples of generative AIs include Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0806] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0807] [Second embodiment]

[0808] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0809] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0810] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0811] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0812] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0813] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0814] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0815] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0816] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0817] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0818] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0819] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0820] "Example 1"

[0821] The present invention is a system that streamlines the creation and review of business emails. Specifically, it receives short instructions from the user and automatically creates business emails based on those instructions. The generated emails are then checked for grammatical errors and compliance violations using the system's internal grammar and compliance check functions.

[0822] "Example 2"

[0823] Furthermore, this embodiment of the present invention has a function to guarantee the quality of the generated business emails. This not only reduces the time required to create emails, but also guarantees quality. Specifically, it checks whether the content of the email conforms to business communication standards and whether appropriate honorific language is used.

[0824] "Example 3"

[0825] Furthermore, this embodiment of the present invention has the function of freeing users from the burden of creating large amounts of emails. Specifically, the system can automatically generate multiple emails at once, allowing users to focus on other tasks. For example, it is possible to generate follow-up emails to all participants at once based on the minutes of a meeting.

[0826] The processing flow of each embodiment will be described below.

[0827] "Example 1"

[0828] Step 1: The system receives a short instruction from the user. For example, the instruction might be, "Create a follow-up email to all participants based on the meeting minutes."

[0829] Step 2: Based on the received instructions, the system automatically generates a business email, with the appropriate content, recipient, subject, etc.

[0830] Step 3: The generated email is checked for grammatical errors using the system's internal grammar check function.

[0831] Step 4: Furthermore, the generated email is checked for compliance violations using the compliance check function.

[0832] "Example 2"

[0833] Step 1: The system operates a function to ensure the quality of business emails automatically generated. Step 2: Specifically, the system checks whether the content of the email conforms to business communication standards and whether appropriate honorific language is used.

[0834] Step 3: This not only saves time in creating emails but also ensures quality.

[0835] "Example 3"

[0836] Step 1: The system can automatically generate multiple emails at once.

[0837] Step 2: For example, you can use the meeting minutes to generate follow-up emails to all participants at once.

[0838] Step 3: This frees users from the overwhelming task of creating emails, allowing them to focus on other tasks.

[0839] Example 1

[0840] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0841] Traditionally, creating business documents manually required time and effort, and there was a high risk of grammatical errors and non-compliance. Furthermore, the checking process to ensure document quality was also time-consuming, making it difficult to efficiently manage business operations.

[0842] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0843] In this invention, the server includes means for automatically generating business documents from short instructions, means for checking the generated business documents for grammatical errors, means for checking the generated business documents for compliance, means for passing the generated business documents through a grammar check function, means for passing the generated business documents through a compliance check function, and means for providing the final checked business documents to the user. This makes it possible to streamline the generation and review of business documents, shorten document creation time, and ensure quality.

[0844] A "short instruction" is a concise instruction entered by a user, which contains basic information required to generate a business document.

[0845] A "business document" is an official document used for business communication, reporting, guidance, etc.

[0846] "Means for automatic generation" refers to technologies and algorithms for automatically creating business documents based on short instructions from users.

[0847] "Grammar checking measures" refers to techniques and algorithms used to detect and correct grammatical errors in generated business documents.

[0848] "Compliance checking measures" refers to technologies and algorithms used to verify that generated business documents do not violate corporate policies or legal regulations.

[0849] "Means for passing through a grammar checker" refers to the process of inputting the generated business document into a grammar checker to check for grammatical accuracy.

[0850] "Means for passing through compliance check function" refers to the process of inputting generated business documents into the compliance check function to check whether they violate regulations or policies.

[0851] "Final verified business document" refers to a business document that has passed grammar and compliance checks and has been finally verified.

[0852] "Means to provide to users" refers to the technology or algorithms used to display or transmit finalized business documents to users.

[0853] This invention relates to a system that improves the efficiency of creating and reviewing business documents. Specifically, this system receives short instructions from a user, automatically generates business documents based on those instructions, and checks the generated documents for grammatical errors and compliance violations.

[0854] System configuration

[0855] Hardware

[0856] The system consists of a server and a terminal. The server plays a central role in data processing and document generation, while the terminal is used to receive input from users and display the final document.

[0857] software

[0858] The server has installed on it a generative AI model (e.g., a natural language processing model), a grammar checker (e.g., a grammar check API), and a compliance checker (e.g., a compliance management tool). These pieces of software work together to efficiently generate and review business documents.

[0859] Program processing

[0860] The server receives a short instruction from the user, such as "Please send me a meeting reminder." The server inputs this instruction into a generative AI model, which then automatically generates a business document based on the instruction.

[0861] The generated document is checked for grammatical errors and compliance violations using the server's internal grammar and compliance check functions. The grammar check function checks the document's grammatical accuracy and makes corrections as necessary. The compliance check function checks whether the document content violates company policies or legal regulations.

[0862] Specific examples

[0863] For example, if a user inputs the instruction "Please create an email to introduce our new product," the following specific actions will be taken:

[0864] 1. The user enters "Please create an introductory email for our new product" into the input field on the terminal.

[0865] 2. The device sends this instruction to the server.

[0866] 3. The server inputs the instructions into the generative AI model and passes the prompt, "Please create an email to introduce a new product. The product name is 'XYZ Smartwatch' and its main features are long battery life, heart rate monitoring, and GPS functionality."

[0867] 4. The generative AI model generates a business document that looks like this:

[0868] Subject: Introducing our new product "XYZ Smart Watch"

[0869] Dear Customer,

[0870] Thank you for your continued support. We have recently released a new product, the XYZ Smartwatch. The XYZ Smartwatch is a multi-functional smartwatch that comes equipped with a long-lasting battery, heart rate monitoring, and GPS functionality to make your daily life more convenient.

[0871] Please take this opportunity to try it out.

[0872] Thank you very much.

[0873] Sincerely,

[0874] 5. The server runs the generated document through a grammar checker to correct any grammatical errors.

[0875] 6. The server passes the grammar-checked document through a compliance checker to ensure it does not violate corporate policies or legal regulations.

[0876] 7. The server sends the final verified document to the terminal.

[0877] 8. The terminal displays the final confirmed document to the user, and the user confirms the document.

[0878] In this way, the creation and review of business documents is made more efficient, reducing the time required for document creation and ensuring quality.

[0879] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0880] Step 1:

[0881] The user enters a short instruction.

[0882] The user inputs a short instruction into an input field on the terminal, such as "Please create an email to introduce our new product." The input data is the user's instruction text.

[0883] Step 2:

[0884] The terminal sends instructions to the server.

[0885] The terminal transmits instructions entered by the user to the server. The terminal transmits data using an Internet connection. The input data is the user's instruction text, and the output data is the instruction text sent to the server.

[0886] Step 3:

[0887] The server inputs instructions into the generative AI model.

[0888] The server inputs the received instructions into the generative AI model. Specifically, it passes the instructions to the generative AI model as a prompt. The input data is the instruction sent to the server, and the output data is the prompt passed to the generative AI model.

[0889] Step 4:

[0890] A generative AI model generates business documents.

[0891] A generative AI model generates a business document based on a prompt. For example, if a user instructs the model to "create an email introducing a new product," the model generates a document that includes the features and benefits of the new product. The input data is the prompt, and the output data is the generated business document.

[0892] Step 5:

[0893] The server passes the generated document through a grammar checker.

[0894] The server passes the generated document through a grammar checker, which checks the document for grammatical accuracy and makes corrections as necessary. The input data is the generated business document, and the output data is the grammar-checked document.

[0895] Step 6:

[0896] The server passes the grammar-checked document through a compliance check function.

[0897] The server passes the grammar-checked document through a compliance check function, which checks whether the document content violates company policies or legal regulations. The input data is the grammar-checked document, and the output data is the compliance-checked document.

[0898] Step 7:

[0899] The server sends the final verified document to the terminal.

[0900] The server sends the final verified document to the terminal. At this time, the server checks that the document content is grammatically and complies with all applicable standards. The input data is the compliance-checked document, and the output data is the final verified document sent to the terminal.

[0901] Step 8:

[0902] The terminal displays the final verified document to the user.

[0903] The terminal displays the final verified document received from the server to the user. The user checks the displayed document and corrects or submits it as necessary. The input data is the final verified document, and the output data is the document displayed to the user.

[0904] (Application example 1)

[0905] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0906] Business communications and report creation within factories are often done manually, which takes time and effort. There is also a high risk of grammatical errors and compliance violations. This reduces work efficiency and makes quality assurance difficult.

[0907] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0908] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for improving the efficiency of business communications and report creation within the factory, means for detecting and correcting grammatical errors in the generated emails, and means for checking for compliance violations in the generated emails. This makes it possible to improve the efficiency of business communications and report creation within the factory, reduce the risk of grammatical errors and compliance violations, and improve business efficiency and quality assurance.

[0909] A "short instruction" is a text that the user enters briefly to indicate the nature of the work or request.

[0910] "Business email" refers to email sent for business purposes such as business communications and reports.

[0911] "Auto-generation" is the process by which a system automatically creates text based on user input.

[0912] "Grammar mistakes" refers to grammatical errors or inappropriate expressions in a sentence.

[0913] "Compliance" refers to following laws, regulations, and a company's internal rules.

[0914] "Inside the factory" refers to the facility or its interior where manufacturing operations take place.

[0915] "Business communication" is the act of conveying information or instructions related to work.

[0916] A "report" is a document that summarizes the progress and results of work.

[0917] "Efficiency" refers to performing tasks and processes more effectively and quickly.

[0918] "Quality assurance" is the process of ensuring that a product or service meets certain quality standards.

[0919] "Detecting and correcting grammatical errors" refers to finding grammatical errors in a sentence and correcting them to the correct expression.

[0920] "Violation of compliance" refers to any act or content that violates laws, regulations, or a company's internal rules.

[0921] To implement the present invention, the following system configuration and program are required.

[0922] System Configuration

[0923] 1. Hardware:

[0924] Computers installed in factory robots

[0925] Network Connection

[0926] 2. Software:

[0927] Python

[0928] OpenAI(R) API

[0929] LanguageTool

[0930] Program processing explanation

[0931] The server receives short instructions from the user and automatically generates business emails based on them. Specifically, it uses a generative AI model (e.g., GPT-3 (registered trademark)) to generate emails based on the user's instructions. The generated emails are then checked for grammatical errors and corrected using LanguageTool. A simple keyword search is also performed to check for compliance violations.

[0932] Specific examples

[0933] When the user enters the instruction "Please generate a status update email for the production line.", the server generates an email like this:

[0934] Example of a generated email

[0935] Dear Team,

[0936] I would like to provide an update on the current status of the production line. We have successfully completed the first phase and are moving on to the next steps. Thank you for your hard work.

[0937] Best regards,

[0938] [Your Name]

[0939] The generated email is checked for grammar errors using LanguageTool, and a compliance check is performed to warn if the email contains, for example, the word "confidential."

[0940] Prompt Sentence Examples

[0941] Please generate a status update email for the production line.

[0942] In this way, business communication and report creation within the factory becomes more efficient, the risk of grammatical errors and compliance violations is reduced, and work efficiency and quality assurance can be improved.

[0943] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0944] Step 1:

[0945] The user inputs a short instruction, such as a prompt phrase like "Please generate a status update email for the production line." This input is sent to the server.

[0946] Step 2:

[0947] The server sends the received prompt to a generative AI model (e.g., GPT-3 (registered trademark)). The generative AI model automatically generates a business email based on the prompt. This generated email is returned to the server.

[0948] Step 3:

[0949] The server sends the generated business email to LanguageTool, which checks for grammatical errors. LanguageTool detects grammatical errors in the email and returns the corrected email to the server.

[0950] Step 4:

[0951] The server sends the corrected email to the compliance check module, which searches for specific keywords (e.g., "confidential") in the email to check for compliance violations. If a violation is detected, the information is returned to the server.

[0952] Step 5:

[0953] The server returns the final email to the user, who can then view it through their device after corrections and compliance checks have been completed.

[0954] Specific actions at each step

[0955] Step 1:

[0956] Input: User types into terminal, "Please generate a status update email for the production line."

[0957] Output: The prompt text entered is sent to the server.

[0958] Step 2:

[0959] Input: The server receives the prompt.

[0960] Data processing: Send prompt text to the generative AI model (GPT-3 (registered trademark)) to generate a business email.

[0961] Output: The generated business email is returned to the server.

[0962] Step 3:

[0963] Input: The server receives a generated business email.

[0964] Data calculation: Send email to LanguageTool to detect and correct grammar errors.

[0965] Output: The modified email is returned to the server.

[0966] Step 4:

[0967] Input: The server receives the modified email.

[0968] Data calculation: Send emails to the compliance check module and search for specific keywords to check for compliance violations.

[0969] Output: Compliance violations or not are returned to the server.

[0970] Step 5:

[0971] Input: The server receives the final email.

[0972] Output: A completed remediation and compliance check email is sent back to the user.

[0973] Example 2

[0974] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0975] Conventional business document creation systems do not adequately check for grammatical errors or compliance when automatically generating documents, and lack functionality to check whether documents conform to business communication standards or use appropriate honorific language. As a result, the quality of the generated documents cannot be guaranteed, and users often have to manually correct them. Furthermore, document creation efficiency is not sufficiently improved, and users are unable to be relieved of the enormous amount of document creation work.

[0976] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0977] In this invention, the server includes means for automatically generating business documents from short instructions, means for checking the generated business documents for grammatical errors, means for checking the generated business documents for compliance, means for verifying whether the generated business documents conform to business communication standards, means for verifying whether the generated business documents use appropriate honorific language, means for analyzing the generated business documents using natural language processing technology, and means for correcting the business documents based on the analysis results. This ensures document quality and eliminates the need for users to manually correct the documents. It also improves the efficiency of document creation, freeing users from the burden of extensive document creation work.

[0978] A "short instruction" is a concise text entered by a user that contains the information necessary to generate a business document.

[0979] "Business documents" are official documents used for business communication, including emails, reports, notices, etc.

[0980] "Auto-generation" is the process by which a system automatically creates a business document based on user input.

[0981] "Grammar errors" are grammatical errors in generated business documents, and refer to errors in sentence structure and word usage.

[0982] "Compliance" refers to checking whether generated business documents comply with laws, regulations, and internal company rules.

[0983] "Business communication standards" refer to the generally accepted format, expression, and etiquette for business documents.

[0984] "Honorific language" refers to polite language used in business documents, and is a form of language used to express respect for the other person.

[0985] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language, and is used to analyze and generate text.

[0986] "Analysis results" refers to information obtained after analyzing business documents generated using natural language processing technology, and includes check results for grammatical errors and compliance.

[0987] "Correction" is the process of correcting errors or inappropriate parts of business documents generated based on the analysis results, thereby improving their quality.

[0988] The present invention relates to a system that automatically generates business documents from short instructions and guarantees the quality of the documents. A specific embodiment of this system will be described below.

[0989] First, the user inputs a prompt using a terminal. The prompt contains instructions for generating a business document for the generative AI model. For example, the user can input a prompt such as, "Please create an email to announce the launch of a new product."

[0990] The device sends the prompt text entered by the user to the server. The server analyzes the received prompt text and inputs it into a generative AI model. For example, GPT-4 (registered trademark) from OpenAI (registered trademark) can be used as the generative AI model.

[0991] The generative AI model generates a business document based on the input prompt. The generated business document is then analyzed by the server using natural language processing technology. For natural language processing, an NLP library such as SpaCy or NLTK can be used.

[0992] The server checks the generated business documents for grammatical errors and compliance, and verifies whether they conform to business communication standards and use appropriate honorific language, thereby ensuring the quality of the generated business documents.

[0993] Based on the analysis results, the server modifies the business document as needed, for example, correcting any honorific errors and adjusting it to conform to business standards.

[0994] Finally, the quality-assured business document is sent from the server to the terminal, which then displays the received business document to the user, who can then check the displayed business document and make further corrections as necessary.

[0995] This system allows users to create high-quality business documents in a short time. For example, if a user inputs the prompt "Please create an email to announce the release of a new product," the following business document will be generated:

[0996] Subject: Announcement of new product release

[0997] Dear Customers,

[0998] We would like to express our sincere gratitude for your continued support.

[0999] We are pleased to announce that we will be releasing a new product, "XYZ."

[1000] Details are as follows:

[1001] Product name:XYZ

[1002] Release date: October 1, 2023

[1003] Price: 10,000 yen

[1004] We appreciate your cooperation.

[1005] Sincerely,

[1006] ABC Co., Ltd.

[1007] In this way, users can efficiently create high-quality business documents.

[1008] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1009] Step 1:

[1010] The user enters a prompt statement.

[1011] The user inputs a prompt sentence into an input field on the terminal, such as "Please create an email to notify you about the release of a new product." The input prompt sentence contains instructions for generating a business document.

[1012] Step 2:

[1013] The terminal sends the prompt to the server.

[1014] The terminal sends the prompt text entered by the user to the server as an HTTP request. The input data is the prompt text, and the output data is the request to the server.

[1015] Step 3:

[1016] The server receives the prompt sentence and inputs it into the generative AI model.

[1017] The server analyzes the prompt sentence received from the terminal and inputs it into a generative AI model (e.g., OpenAI's GPT-4®). The input data is the prompt sentence, and the output data is the input to the generative AI model.

[1018] Step 4:

[1019] A generative AI model generates business documents.

[1020] The generative AI model generates a business document based on the input prompt. The input data is the prompt, and the output data is the generated business document. For example, the following business document is generated:

[1021] Subject: Announcement of new product release

[1022] Dear Customers,

[1023] We would like to express our sincere gratitude for your continued support.

[1024] We are pleased to announce that we will be releasing a new product, "XYZ."

[1025] Details are as follows:

[1026] Product name:XYZ

[1027] Release date: October 1, 2023

[1028] Price: 10,000 yen

[1029] We appreciate your cooperation.

[1030] Sincerely,

[1031] ABC Co., Ltd.

[1032] Step 5:

[1033] The server parses the generated business document using an NLP library.

[1034] The server analyzes the generated business document using natural language processing technology (for example, SpaCy or NLTK). The input data is the generated business document, and the output data is the analysis results. The purpose of the analysis is to check for grammatical errors and compliance, whether the document conforms to business communication standards, and whether appropriate honorific language is used.

[1035] Step 6:

[1036] The server modifies the business document based on the analysis results.

[1037] The server modifies the content of the business document as needed based on the results of the NLP analysis. The input data is the analysis result, and the output data is the modified business document. For example, any errors in honorific language are corrected, and the document is adjusted to conform to business standards.

[1038] Step 7:

[1039] The server transmits the quality-guaranteed business document to the terminal.

[1040] The server sends the modified business document to the terminal as an HTTP response. The input data is the modified business document, and the output data is the response to the terminal.

[1041] Step 8:

[1042] The terminal displays the business document to the user.

[1043] The terminal displays the business document received from the server to the user. The input data is the response from the server, and the output data is the business document displayed to the user. The user can check the displayed business document and make further corrections if necessary.

[1044] (Application example 2)

[1045] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1046] Creating business emails is a time-consuming and labor-intensive task, especially for customer support staff at electronic payment services. It is also important to ensure that the content of the email complies with business communication standards and that appropriate honorific language is used, but doing this manually is inefficient. Furthermore, it is also necessary to guarantee the quality of the generated emails. A system to solve these issues is needed.

[1047] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1048] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for confirming whether the generated business emails conform to business communication standards, and means for confirming whether the generated business emails use appropriate honorific language, thereby reducing the time required to create business emails and ensuring quality.

[1049] "Short instructions" are brief instructions or keywords entered by the user, and are input information that the system uses to automatically generate business emails.

[1050] "Business email" refers to emails intended for official communication within and outside a company or organization, and are used for business communications, customer correspondence, etc.

[1051] "Auto-generation" refers to the process by which a system automatically creates text based on user input, eliminating the need for manual text creation.

[1052] "Grammar errors" refer to grammatical errors or inappropriate expressions within a sentence, and checking these ensures the accuracy of the sentence.

[1053] "Compliance" means checking whether an email conforms to laws, regulations, and a company's internal rules, and it involves checking whether business emails meet these standards.

[1054] "Business communication standards" refer to the manners, formalities, and methods of expression generally expected in business communication, and are used to check whether or not a document complies with these standards.

[1055] "Honorific language" refers to the use of language to show respect to the other person, and this is to check whether appropriate honorific language is used in business emails.

[1056] "Ensuring quality" means making sure that the generated business emails meet certain standards and assuring users of that quality.

[1057] The following system configuration will be described as an embodiment of the present invention.

[1058] System Configuration

[1059] This system consists of a server and a user terminal. The server automatically generates business emails using a generative AI model and performs various checks to ensure their quality. The user terminal provides an interface that allows users to input short instructions and check and edit the generated business emails.

[1060] Hardware and software used

[1061] Hardware: Servers and user devices connected to the Internet (smartphones, PCs, etc.)

[1062] Software: Python, OpenAI (registered trademark) API, web browser

[1063] Data processing and calculation

[1064] 1. User input: The user inputs a short instruction using the user terminal. For example, the user inputs a prompt sentence such as "Please generate a business email that explains to the customer how to use the electronic payment service."

[1065] 2. Email generation: The server uses the OpenAI (registered trademark) API to automatically generate a business email based on the input prompt text.

[1066] 3. Grammar Check: Check the generated business email for grammatical errors using natural language processing technology.

[1067] 4. Compliance check: Check whether the generated business email complies with laws and regulations.

[1068] 5. Quality Assurance: Ensure that generated business emails comply with business communication standards and use appropriate honorific language.

[1069] Specific examples

[1070] The user enters the following prompt text:

[1071] "Generate a business email to explain to customers how to use your electronic payment service."

[1072] The server uses the OpenAI® API to generate a business email like this:

[1073] "Thank you for your support. We would like to explain how to use our electronic payment service. First, please download the app, and then create an account. Please refer to the link below for detailed instructions. Sincerely."

[1074] The server then checks the generated email for grammatical errors, compliance with business communication standards, and the use of honorific language, providing users with quality-assured emails.

[1075] In this way, the user can quickly create high-quality business emails by simply inputting a few instructions.

[1076] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1077] Step 1:

[1078] The user inputs a short instruction (prompt sentence) using the user terminal.

[1079] Input: Prompt text (e.g., "Please generate a business email to explain to your customers how to use the electronic payment service.")

[1080] Output: The prompt text is sent to the server.

[1081] Step 2:

[1082] Based on the prompt received by the server, a business email is automatically generated using the OpenAI (registered trademark) API.

[1083] Input: prompt statement

[1084] Data processing: Using the OpenAI (registered trademark) API, prompt sentences are input into the generative AI model to generate business emails.

[1085] Output: Generated business email

[1086] Step 3:

[1087] The server checks generated business emails for grammatical errors.

[1088] Input: Generated business email

[1089] Data Computing: Detect grammatical errors using natural language processing techniques.

[1090] Output: A business email with grammar errors corrected

[1091] Step 4:

[1092] The server checks generated business emails for compliance.

[1093] Input: A business email with grammar corrections

[1094] Data calculation: Checks are carried out to ensure compliance with laws and regulations.

[1095] Output: Compliance verified business email

[1096] Step 5:

[1097] Verify that server-generated business emails comply with business communication standards.

[1098] Input: Compliance verified business email

[1099] Data Calculation: Checks are performed to ensure compliance with business communication standards.

[1100] Output: Business emails that meet business communication standards

[1101] Step 6:

[1102] Ensure that proper honorific language is used in business emails generated by the server.

[1103] Input: Business email that meets business communication standards

[1104] Data calculation: Checks are performed to ensure that honorific language is used appropriately.

[1105] Output: A business email with proper use of honorific language

[1106] Step 7:

[1107] The server sends quality-guaranteed business emails to the user terminal.

[1108] Input: A business email with proper use of honorific language

[1109] Output: Quality-guaranteed business emails are sent to the user's terminal.

[1110] Step 8:

[1111] Users can check and edit quality-guaranteed business emails on their devices.

[1112] Input: Quality-guaranteed business email

[1113] Output: The final business email is created.

[1114] Example 3

[1115] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1116] Traditionally, email creation was often done manually, which required time and effort, resulting in reduced work efficiency. Creating emails manually also carries the risk of grammatical errors and compliance violations. Furthermore, creating follow-up emails based on meeting minutes was particularly time-consuming and a burden on users.

[1117] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes means for uploading meeting minutes, means for analyzing the uploaded minutes, means for generating a prompt sentence based on the analysis result, means for automatically generating multiple emails using the generated prompt sentence, and means for providing the generated emails to the user. This enables automation and efficiency of email creation.

[1118] "Meeting minutes" are documents that record what was discussed during a meeting, decisions made, and comments made by participants.

[1119] The "means for uploading" is a function that allows a user to use a terminal to send a meeting minutes file to the system.

[1120] The "means of analysis" refers to the function by which the server converts the contents of the uploaded minutes file into text format and analyzes the contents using a generative AI model.

[1121] The "means for generating prompt sentences" is a function that creates instruction sentences to be input into the generative AI model based on the analysis results.

[1122] "Means for automatically generating emails" refers to a function that uses a generative AI model to create multiple emails based on generated prompt text.

[1123] The "means for providing to the user" is a function for sending the generated email to the user's email client or allowing the user to download it.

[1124] This invention is a system that relieves users from the burden of creating a huge amount of emails. The system has the function of automatically generating multiple emails based on the minutes of a meeting. A specific embodiment of this system is described below.

[1125] Hardware and software used

[1126] Hardware: Servers, devices (PCs, smartphones, etc.)

[1127] Software: Generative AI models (e.g., GPT-4®), email clients (e.g., Outlook, Gmail)

[1128] System Overview

[1129] A user uses a terminal to upload a meeting minutes file to the system. The server receives the uploaded minutes file and analyzes its contents using a generative AI model. Based on the analysis results, the server generates prompts to input into the generative AI model. Using the generated prompts, the server automatically generates multiple follow-up emails. The generated emails are sent to the user's email client or made available for the user to download.

[1130] Specific examples

[1131] For example, if a user uploads minutes stating, "At the meeting on October 1, 2023, we discussed the progress and next steps of the project. The participants were A, B, and C," the server will generate the following prompt:

[1132] Example prompt sentence:

[1133] "Please write a follow-up email to all participants based on the minutes of the following meeting. Minutes: At the meeting on October 1, 2023, we discussed the project progress and next steps. Participants were A, B, and C."

[1134] By inputting this prompt into the generative AI model, the server automatically generates a follow-up email like the one below.

[1135] Example of generated email:

[1136] "Thank you for your feedback during the meeting. Here are our next steps..."

[1137] In this way, the system saves the user the trouble of manually creating an email, and enables the user to carry out business efficiently. The flow of the specific processing in the third embodiment will be described with reference to FIG.

[1138] Step 1:

[1139] A user uploads meeting minutes. Using a terminal, the user accesses the system's web interface and clicks the "Select File" button to select a minutes file (e.g., a PDF or Word file) from local storage. The input is the minutes file, and the output is the minutes file sent to the server.

[1140] Step 2:

[1141] The server receives the minutes and converts them into text format. The server receives the uploaded minutes file and converts it into text format using OCR (Optical Character Recognition) technology. The input is the minutes file and the output is the minutes in text format.

[1142] Step 3:

[1143] The server analyzes the text minutes. The server uses a generative AI model (e.g., GPT-4 (registered trademark)) to analyze the content of the text minutes. Specifically, it extracts the meeting topic, participants, points discussed, etc. The input is the text minutes, and the output is the analysis results.

[1144] Step 4:

[1145] The server generates a prompt based on the analysis results. Based on the analysis results, the server generates a prompt to be input into the generative AI model. For example, a prompt might be generated that reads, "Please write a follow-up email to all participants based on the minutes of the following meeting. Minutes: At the meeting on October 1, 2023, we discussed the project's progress and next steps. Participants were A, B, and C." The input is the analysis results, and the output is the prompt.

[1146] Step 5:

[1147] The server automatically generates multiple emails using the generated prompt text. The server inputs the generated prompt text into a generative AI model, which automatically generates multiple follow-up emails. The generative AI model creates emails with the appropriate format and content based on the prompt text. For example, it generates an email with the content, "Dear Mr. A, thank you for your feedback at the meeting. The next steps are as follows..." The input is the prompt text, and the output is the generated email.

[1148] Step 6:

[1149] The server provides the generated email to the user. The server either sends the generated email to the user's email client or makes it available for the user to download, either by sending the email to the user's email address or by providing a "download" button on the system's web interface. The input is the generated email and the output is the email provided to the user.

[1150] Step 7:

[1151] The user reviews and sends the email. The user reviews the generated email and makes any necessary edits, such as adding a personalized message for a specific participant. The user then uses their email client to send the email to all participants. The input is the generated email and the output is the sent email.

[1152] (Application example 3)

[1153] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1154] At logistics centers, there is a problem of a huge volume of emails being generated regarding shipping status, inventory status, and delivery schedules, which reduces work efficiency. In addition, creating follow-up emails based on meeting minutes and daily reports takes time and effort, so there is a need to improve work efficiency.

[1155] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for generating follow-up emails in bulk based on meeting minutes and daily reports, means for inputting appropriate prompt sentences using a generative AI model, and means for automatically generating emails regarding shipping status, inventory status, and delivery schedules at a logistics center. This makes it possible to improve the efficiency and reduce the time required for email creation work at logistics centers.

[1156] "Short instructions" refer to brief text inputs or commands that the system uses to automatically generate business emails.

[1157] "Business email" refers to email for business purposes, and is used to contact business partners and internal stakeholders.

[1158] "Grammar mistakes" refers to grammatical errors in a sentence, and detecting and correcting these can improve the quality of emails.

[1159] "Compliance" refers to following laws, regulations, and a company's internal rules, and involves checking whether generated business emails comply with these.

[1160] "Meeting minutes" are documents that record the matters discussed and decisions made during a meeting, and are a source of information for generating follow-up emails.

[1161] A "daily report" is a report that records the progress and results of work on a daily basis, and is a source of information for generating follow-up emails.

[1162] A "follow-up email" is an additional communication email sent to relevant parties based on the progress of a meeting or task, informing them of next steps or confirmations.

[1163] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to generate text, automatically generating appropriate email content based on a prompt.

[1164] A "prompt" is a text instruction that is input into a generative AI model, serving as a guideline for the AI ​​to generate emails.

[1165] A "logistics center" is a facility that handles logistics operations such as storing, managing, shipping, and delivering goods, and is a place where efficient business operations are required.

[1166] "Shipping status" refers to the progress and status of product shipments, and is information used to contact relevant parties based on this.

[1167] "Inventory status" refers to the amount and condition of products in stock at the logistics center, and is information used to contact relevant parties based on this information.

[1168] "Delivery schedule" refers to the product delivery plan and timeline, and is information used to contact relevant parties based on this.

[1169] A system for carrying out this invention has the following configuration: A server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for generating follow-up emails in bulk based on meeting minutes and daily reports, means for inputting appropriate prompt sentences using a generative AI model, and means for automatically generating emails regarding shipping status, inventory status, and delivery schedules at a logistics center.

[1170] Hardware and software used

[1171] Hardware: Smartphones, servers

[1172] Software: Python, OpenAI® API

[1173] Data processing and calculation

[1174] 1. Data entry: Users enter text data such as meeting minutes and daily reports using their smartphones or other devices.

[1175] 2. Prompt generation: The server generates a prompt sentence appropriate for the generative AI model based on the input data.

[1176] 3. Email generation: The server uses a generative AI model (e.g., OpenAI's GPT-3®) to automatically generate an email based on the prompt.

[1177] 4. Grammar Check: Check the generated email for grammar errors and correct them if necessary.

[1178] 5. Compliance check: Check whether the generated email complies with laws, regulations, and internal company rules.

[1179] 6. Output: The generated email is displayed on the smartphone application so that the user can check it.

[1180] Specific examples

[1181] Let's take the example of automatically generating follow-up emails regarding shipping status and inventory management after a meeting at a logistics center. The user inputs the minutes of the meeting from a smartphone. For example, the following prompt sentences can be generated:

[1182] Example prompt sentence:

[1183] Minutes of the meeting:

[1184] 1. Check shipping status

[1185] 2. Improved inventory management

[1186] 3. Adjusting delivery schedules

[1187] Use the meeting minutes above to generate follow-up emails to all involved parties.

[1188] The server inputs this prompt into a generative AI model to automatically generate an appropriate follow-up email. The generated email is then checked for grammatical errors and compliance before finally being displayed on the user's smartphone. This improves the efficiency and reduces the time required for email creation at logistics centers.

[1189] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1190] Step 1:

[1191] Users input text data such as meeting minutes or daily reports from their smartphones or other devices. The input data is then sent to the server. Specifically, the user opens the smartphone application, inputs the contents of the minutes or daily reports in text format, and presses the send button.

[1192] Step 2:

[1193] The server analyzes the received text data and generates a prompt sentence suitable for the generative AI model. It processes the input data (minutes and daily reports) to construct an appropriate prompt sentence. Specifically, it analyzes the text data using natural language processing technology, extracts important points, and generates a prompt sentence.

[1194] Step 3:

[1195] The server inputs the generated prompt text into a generative AI model (e.g., GPT-3 (registered trademark) from OpenAI (registered trademark)) to automatically generate appropriate email content. Using the prompt text as input, the generative AI model generates the email body. Specifically, the server calls the API of the generative AI model, sends the prompt text, and retrieves the email content.

[1196] Step 4:

[1197] The server checks the generated email for grammatical errors and corrects them if necessary. Using the generated email as input, it uses a grammar checking tool (e.g., the Grammarly API) to detect and correct grammatical errors. Specifically, it sends the text of the generated email to the grammar checking tool and applies the suggested corrections it receives.

[1198] Step 5:

[1199] The server checks whether the generated email complies with laws, regulations, and the company's internal rules. The generated email is used as input to check compliance using a compliance check tool. Specifically, the content of the email is sent to the compliance check tool, and the evaluation result of compliance is obtained.

[1200] Step 6:

[1201] The server displays the final generated email on the smartphone application so that the user can check it. After corrections and checking are complete, the server sends the email to the user's smartphone as output. Specifically, the content of the email is displayed on the application interface so that the user can check and send it.

[1202] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1203] "Example 1"

[1204] In one embodiment of the present invention, a system is provided that includes an emotion engine that recognizes a user's emotions. The emotion engine analyzes the user's emotions from their tone of voice, facial expressions, and choice of words, and feeds the results back to the system. For example, if the user feels angry, the emotion engine communicates this information to the system, and the system takes this into account when generating a business email.

[1205] "Example 2"

[1206] In addition, the emotion engine adjusts the tone of automatically generated business emails based on the user's emotions. For example, if the user is happy, the tone of the generated email will be bright and positive. Conversely, if the user is sad, the tone of the generated email will be calm. This allows the recipient of the email to more accurately understand the sender's emotions.

[1207] "Example 3"

[1208] The emotion engine also adjusts the timing of email sending based on the user's emotions. For example, if the user feels angry, the emotion engine will communicate that information to the system, which will temporarily postpone sending the email. This allows the user time to calm down and prevents them from sending the wrong email based on emotional judgment.

[1209] The processing flow of each embodiment will be described below.

[1210] "Example 1"

[1211] Step 1: The user boots the system.

[1212] Step 2: The emotion engine analyzes the user's emotions based on their tone of voice, facial expressions, and choice of words.

[1213] Step 3: The emotion engine feeds the analysis results back to the system.

[1214] Step 4: The system takes your feedback into account and generates a business email.

[1215] "Example 2"

[1216] Step 1: The user boots the system.

[1217] Step 2: The emotion engine analyzes the user's emotions.

[1218] Step 3: The sentiment engine adjusts the tone of the email based on the analysis.

[1219] Step 4: The system generates a business email taking into account the adjusted tone.

[1220] "Example 3"

[1221] Step 1: The user boots the system.

[1222] Step 2: The emotion engine analyzes the user's emotions.

[1223] Step 3: The emotion engine adjusts the timing of email sending based on the analysis results.

[1224] Step 4: The system generates business emails taking into account the adjusted sending timing and sends them at the appropriate time.

[1225] Example 1

[1226] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1227] Conventional business email generation systems generate emails without considering the user's emotions, often failing to reflect the appropriate tone or content. They also lack sufficient checks for grammatical errors and compliance violations, making quality assurance difficult. Furthermore, creating emails takes a lot of time, reducing work efficiency.

[1228] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1229] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for analyzing the user's emotions, and means for generating business emails based on the analyzed emotions. This makes it possible to automatically generate business emails with an appropriate tone that reflects the user's emotions, and to efficiently create high-quality emails that are free of grammatical errors and compliance violations.

[1230] A "short command" is a brief command or request that a user enters into the system.

[1231] "Business email" refers to email sent for business purposes such as business communication and information sharing.

[1232] "Means for automatic generation" refers to functions or processes that automatically create business emails based on user instructions.

[1233] "Means for checking grammar errors" refers to the functions and processes that detect and correct grammatical errors in generated business emails.

[1234] "Means for checking compliance" refers to functions and processes that check whether generated business emails violate laws, regulations, or company rules.

[1235] "Means for analyzing user emotions" refers to the functions and processes that recognize and analyze emotions from the user's tone of voice, facial expressions, etc.

[1236] "Means for generating business emails based on analyzed emotions" refers to a function or process for creating business emails taking into account the analyzed emotional information of the user.

[1237] MODE FOR CARRYING OUT THE INVENTION

[1238] This invention is a system that streamlines the creation and proofreading of business emails. It automatically creates business emails based on short user instructions and has the function of checking for grammatical errors and compliance violations. It can also analyze user emotions and generate business emails that reflect the results.

[1239] Hardware and software used

[1240] The system uses the following hardware and software:

[1241] Terminal: A device that allows a user to input instructions. It is equipped with a microphone and a camera to capture the user's tone of voice and facial expressions.

[1242] Server: A central processing unit for automatically generating business emails, checking grammar, compliance, and sentiment analysis.

[1243] Generative AI model: An artificial intelligence model for automatically generating business emails, such as OpenAI's GPT-4.

[1244] Grammar checking tools: Software to detect grammatical errors in generated emails. For example, use Grammarly.

[1245] Compliance checking software: Software that checks whether generated emails violate laws, regulations, or company rules.

[1246] System Operation

[1247] 1. User input:

[1248] A user uses a terminal to input a short instruction to the system, such as "Please send me a reminder email for next week's meeting."

[1249] 2. Emotion analysis:

[1250] The emotion engine analyzes the user's tone of voice and facial expressions via the device's built-in microphone and camera, recognizing whether the user is angry, happy, or calm, and feeding the results back to the server.

[1251] 3. Automatic generation of business emails:

[1252] The server automatically generates business emails using a generative AI model (e.g., OpenAI's GPT-4®) based on instructions received from the user and feedback from the emotion engine. The generated emails take the user's emotions into account.

[1253] 4. Grammar and Compliance Checks:

[1254] The server runs the generated email through an internal grammar checking tool (Grammarly) and compliance checking software to check for grammatical errors and compliance violations.

[1255] 5. User Feedback:

[1256] The server sends emails that pass the check to the terminal and displays them to the user, who can then check the contents of the email and make any necessary corrections.

[1257] Specific examples

[1258] The user prompts the system with the following:

[1259] Please send me a reminder email for next week's meeting.

[1260] An example of how the system works is as follows:

[1261] 1. A user types, "Send me a reminder email for next week's meeting."

[1262] 2. The emotion engine analyzes the user's tone of voice and facial expression and determines that the user is calm.

[1263] 3. The server uses a generative AI model (GPT-4 (registered trademark)) to automatically generate a business email like this:

[1264] Subject: Meeting reminder next week

[1265] Everyone

[1266] This is a reminder of a meeting scheduled for next Monday. Details are below.

[1267] Date and time: Monday, October 16, 2023 10:00 AM

[1268] Location: Conference Room 1

[1269] We look forward to your attendance.

[1270] Thank you very much.

[1271] [User Name]

[1272] 4. The server runs the generated email through a grammar checking tool (Grammarly) to check for grammatical errors, and then uses compliance checking software to check whether the email content violates company policies.

[1273] 5. Emails that pass the check are sent to the terminal and displayed to the user, who can then check the contents of the email and make any necessary corrections.

[1274] In this way, users can efficiently generate and edit business emails that take emotions into account by simply entering a few instructions.

[1275] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1276] Step 1:

[1277] A user uses a terminal to input short instructions to the system, such as "Please send me a reminder email for next week's meeting." The terminal receives this instruction and sends it to the server. The input is the user's instruction, and the output is instruction data for the server.

[1278] Step 2:

[1279] The device uses a built-in microphone and camera to capture the user's tone of voice and facial expressions in real time. The emotion engine analyzes this data and determines whether the user is calm. The analysis results are sent to the server. The input is the user's voice and video data, and the output is analyzed emotional data.

[1280] Step 3:

[1281] The server receives the user's instructions and feedback from the emotion engine, and inputs a prompt sentence into the generative AI model (GPT-4 (registered trademark)). The prompt sentence is as follows: "The user is calm. Please generate a reminder email for next week's meeting." The generative AI model generates a business email based on this prompt sentence. The input is the prompt sentence, and the output is the generated business email.

[1282] Step 4:

[1283] The server runs the generated email through a grammar checking tool (Grammarly) to check for grammatical errors. It then uses compliance checking software to check whether the email content violates company policies. The input is the generated business email, and the output is an email that has been checked for grammar and compliance.

[1284] Step 5:

[1285] The server sends emails that pass the check to the terminal. The terminal displays the email to the user, who checks the content. If necessary, the user corrects the content of the email and prepares it for final sending. The input is the checked business email, and the output is the email displayed to the user.

[1286] In this way, users can efficiently generate and edit business emails that take emotions into account by simply entering a few instructions.

[1287] (Application example 1)

[1288] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1289] Conventional business email generation systems were able to generate emails from short instructions and check grammar and compliance, but they were unable to generate emails that took the user's emotions into consideration. This made it difficult to respond appropriately based on the user's emotions, which could lead to a decline in the quality of customer service. Furthermore, there was a lack of concrete measures to improve the efficiency of customer service in physical stores.

[1290] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1291] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for converting the short instructions into text using voice recognition, means for analyzing the user's emotions using a camera, means for generating business emails based on the user's emotions, and means for displaying the generated business emails on a display device. This makes it possible to generate appropriate business emails that take the user's emotions into consideration, thereby improving the quality of customer service in physical stores.

[1292] A "short instruction" is a brief instruction entered by a user, and includes information necessary for generating a business email.

[1293] "Business email" refers to emails intended for business communication and have the appearance of a formal document.

[1294] "Grammar mistakes" refers to grammatical errors or inappropriate expressions in a sentence.

[1295] "Compliance" refers to following laws, regulations, and a company's internal rules, and checking that business emails do not violate these.

[1296] "Speech recognition" is a technology that analyzes a user's voice and converts it into text.

[1297] A "camera" is a device that captures video and is used to capture the user's facial expressions and movements.

[1298] "Emotion analysis" is a technology that analyzes a user's emotions from facial expressions, tone of voice, etc.

[1299] A "display device" is a device for visually displaying the generated business email, and includes smart glasses, displays, etc.

[1300] "User" means an individual or member of an organization who uses the System to generate business email.

[1301] "Automatic generation" is the process by which a system automatically creates business emails based on user instructions.

[1302] The system for implementing this invention uses the following hardware and software: smart glasses, a microphone, and a camera. The software uses Python, the speech_recognition library, the transformers library, and OpenCV.

[1303] The server provides a means for automatically generating business emails from short instructions. Specifically, it uses speech recognition to convert the user's speech into text, and then generates the business email based on the text using a generative AI model (e.g., GPT-3 (registered trademark)). The generated business email is then checked through means for grammar and compliance checks.

[1304] The system also includes a means for analyzing the user's emotions using a camera. The video captured by the camera is analyzed using an emotion analysis model, and the content of business emails is adjusted based on the results. For example, if the user is angry, the system will adjust the content to use more polite language.

[1305] The generated business emails are displayed on the smart glasses' display, which improves the efficiency of customer service in brick-and-mortar stores and allows users to respond quickly and appropriately.

[1306] As a specific example, if a user instructs the system to "check product inventory" and emotion analysis detects "anger," the system will generate a business email like the one below.

[1307] Example prompt sentence:

[1308] User Instructions: Check product availability

[1309] User Emotion: Anger

[1310] Generate proper business emails.

[1311] Example of a generated business email:

[1312] Dear customer, we have checked the product inventory and it is currently out of stock. We apologize for any inconvenience caused.

[1313] In this way, it becomes possible to generate appropriate business emails that take into account the user's emotions, thereby improving the quality of customer service in physical stores.

[1314] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1315] Step 1:

[1316] The user puts on the smart glasses and speaks short instructions into the microphone.

[1317] Input: User's voice commands

[1318] Output: Audio data

[1319] Step 2:

[1320] The device uses voice recognition to convert the voice data into text. Specifically, it uses the speech_recognition library to analyze the voice data and generate text data.

[1321] Input: Audio data

[1322] Output: Text data

[1323] Step 3:

[1324] The terminal uses a camera to capture a picture of the user's face and acquires video data.

[1325] Input: User's face video

[1326] Output: Video data

[1327] Step 4:

[1328] The server performs emotion analysis using the video data. Specifically, it analyzes the user's emotions using an emotion analysis model and obtains the results.

[1329] Input: Video data

[1330] Output: Emotion data (e.g., anger, joy, etc.)

[1331] Step 5:

[1332] The server automatically generates business emails using a generative AI model (e.g., GPT-3 (registered trademark)) based on text data and emotion data. A prompt sentence is input into the generative AI model, and an appropriate business email is output.

[1333] Input: Text data, emotion data

[1334] Output: Generated business email

[1335] Step 6:

[1336] The server performs grammar and compliance checks on the generated business emails. Specifically, it uses grammar and compliance check tools to check the quality of the emails.

[1337] Input: Generated business email

[1338] Output: Business emails checked for grammar and compliance

[1339] Step 7:

[1340] The server sends the verified business email to the display device of the smart glasses and displays it to the user.

[1341] Input: Business email checked for grammar and compliance

[1342] Output: Business email displayed on smart glasses

[1343] In this way, users can quickly generate appropriate business emails that take emotions into consideration and respond to customers through smart glasses.

[1344] Example 2

[1345] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1346] Conventional business document creation systems lacked automatic document generation and quality assurance, requiring users to manually edit documents. Furthermore, they lacked the ability to adjust the tone of a document to match the user's emotions, making it difficult to express appropriate emotions to the recipient. This resulted in reduced document creation efficiency and inconsistent quality.

[1347] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1348] In this invention, the server includes means for automatically generating business documents from short instructions, means for checking the generated business documents for grammatical errors, means for checking the generated business documents for conformance with standards, means for assuring the quality of the generated business documents, and means for adjusting the tone of the business documents based on the user's emotions. This improves the efficiency of document creation and reduces variations in quality. Furthermore, by generating documents with an appropriate tone based on the user's emotions, the user's emotions can be more accurately expressed to the recipient.

[1349] "Short instructions" are brief text instructions entered by the user that contain the basic information needed to generate a business document.

[1350] "Business documents" are official documents used for business communications and transactions, including emails, reports, proposals, etc.

[1351] "Grammar errors" refer to grammatical errors or inappropriate expressions in a document that need to be corrected based on correct grammar.

[1352] "Standards conformance" refers to whether the generated business documents conform to industry standards or company standards.

[1353] "Quality assurance" is the process of verifying and ensuring that generated business documents meet certain quality standards.

[1354] "Adjusting tone based on emotion" means analyzing the user's emotional state and appropriately changing the expression and mood of the document accordingly.

[1355] A "generative AI model" is an algorithm or system that uses artificial intelligence technology to generate text, automatically generating business documents based on user instructions.

[1356] A "prompt" is an instruction that a user inputs into a generative AI model, specifying the content and format of the business document to be generated.

[1357] The present invention relates to a system for automatically generating business documents from short instructions and for guaranteeing the quality of the generated documents. A specific embodiment of this system will be described below.

[1358] System configuration

[1359] The system consists of three main components: a server, a terminal, and a user. The server automatically generates business documents using a generative AI model and checks for grammatical errors and conformance to standards. The terminal provides an interface for users to input prompts and review and correct the generated documents.

[1360] Hardware and software used

[1361] Server: A server with high-performance computing capabilities is required. Specifically, a server equipped with a GPU is preferable.

[1362] Generative AI model: For example, GPT-4 (registered trademark) is used as the generative AI model.

[1363] Terminal: A device, such as a computer or smartphone, that allows a user to enter prompt text.

[1364] Software: Generative AI models running on servers, grammar checkers, norm conformance checkers, emotion engines, etc.

[1365] Data processing and calculation

[1366] 1. Data Entry:

[1367] The user inputs a prompt through the terminal interface, for example, "Please create an email to introduce a new product. The product name is 'SuperWidget', and its main features are high-speed processing and low power consumption."

[1368] 2. Send the prompt:

[1369] The terminal sends the prompt sentence entered by the user to the server.

[1370] 3. Business document generation:

[1371] The server inputs the received prompt sentence into a generative AI model (e.g., GPT-4 (registered trademark)) to generate a business document.

[1372] 4. Check for grammar errors:

[1373] The server checks the generated document for grammar errors. It uses a grammar checking tool to detect and correct grammatical errors.

[1374] 5. Normative Conformance Check:

[1375] The server checks the generated document for conformance to industry standards and corporate codes, using a code conformance checking tool to make any necessary corrections.

[1376] 6. Quality Guarantee:

[1377] The server performs grammar and conformance checks, followed by a final quality check, to ensure the quality of the generated document.

[1378] 7. Applying the Emotion Engine:

[1379] The server analyzes the user's emotional data and adjusts the tone of the document using an emotion engine. For example, if the user is happy, the tone of the document will be bright and positive.

[1380] 8. Sending documents:

[1381] The server sends the final business document to the terminal, which displays the received document to the user.

[1382] Specific examples

[1383] If a user wants to create an email introducing a new product, he or she enters the following prompt text:

[1384] Example prompt sentence:

[1385] "Please create an email to introduce a new product. The product name is 'SuperWidget' and its main features are high-speed processing and low power consumption."

[1386] The server receives this prompt and uses a generative AI model to generate a business document like the one below.

[1387] An example of the generated document:

[1388] "Dear customers, we would like to introduce our new product, SuperWidget. SuperWidget is equipped with the latest technology that achieves high-speed processing and low power consumption. Please take this opportunity to try it out."

[1389] In this way, the system processes a series of steps from user input to the generation of the final business document.

[1390] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1391] Step 1:

[1392] The user enters a prompt statement.

[1393] The user inputs a prompt through the device interface. For example, the user might input, "Please create an email introducing a new product. The product name is 'SuperWidget', and its main features are high-speed processing and low power consumption." The input prompt is temporarily stored in the device's memory.

[1394] Step 2:

[1395] The terminal sends the prompt to the server.

[1396] The terminal sends the prompt text entered by the user to the server. The sent prompt text is sent to the server in an appropriate data format such as JSON. The server analyzes the received prompt text and proceeds to the next process.

[1397] Step 3:

[1398] The server generates business documents using the generative AI model.

[1399] The server inputs the received prompt sentence into a generative AI model (e.g., GPT-4 (registered trademark)) to generate a business document. The generative AI model creates a document with appropriate content based on the prompt sentence. The generated document is stored in the server's memory.

[1400] Step 4:

[1401] Server-generated documents are checked for syntax errors.

[1402] The server uses a grammar checker to check the generated document for grammatical errors. The grammar checker detects grammatical errors in the document and makes necessary corrections. The corrected document is saved back in the server's memory.

[1403] Step 5:

[1404] The server checks the generated document for normative conformance.

[1405] The server uses a conformance checker to check whether the generated document conforms to industry standards or company regulations. The conformance checker detects inappropriate expressions or content in the document and makes the necessary corrections. The corrected document is then saved back into the server's memory.

[1406] Step 6:

[1407] The server guarantees the quality of the generated documents.

[1408] The server performs a grammar check and a conformance check to ensure the quality of the generated document, and then a final quality check. Once the quality check is complete, the document is stored in the server's memory.

[1409] Step 7:

[1410] The server applies an emotion engine to adjust the tone of the document.

[1411] The server analyzes the user's emotional data and adjusts the tone of the document using an emotion engine. For example, if the user is happy, the tone of the document will be bright and positive. The adjusted document is then stored in the server's memory.

[1412] Step 8:

[1413] The server sends the final document to the device.

[1414] The server sends the final document after quality checks and tone adjustments to the terminal, which then displays the received document to the user, who can then review the document and make corrections as necessary.

[1415] (Application example 2)

[1416] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1417] Conventional business email generation systems offer features such as automatic email generation, grammar checks, and compliance checks, but lack the ability to adjust the tone of the email based on the user's emotions, making it difficult to convey the appropriate emotion to the recipient. Furthermore, while store staff are required to generate emails quickly and appropriately when dealing with customers, current systems are unable to do this efficiently. Furthermore, the lack of systems compatible with wearable devices such as smart glasses limits their use in physical stores.

[1418] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1419] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking compliance of the generated business emails, means for recognizing a user's emotion, means for adjusting the tone of the business emails based on the user's emotion, means for ensuring the quality of the generated business emails, and means installed in the smart glasses, thereby enabling store staff to quickly generate business emails with an appropriate tone based on the user's emotion when dealing with customers and ensure the quality of the emails.

[1420] "Short instructions" are instructions or information that are briefly entered by the user, and are input data that the system uses to automatically generate business emails.

[1421] "Business email" refers to emails intended for business communication, which require a formal writing style and appropriate honorific language.

[1422] "Grammar mistakes" are grammatical errors in a sentence, and refer to mistakes in the proper use of words and syntax.

[1423] "Compliance" means following laws, regulations, and a company's internal rules, and refers to checking whether business emails comply with these.

[1424] "User emotion" refers to the emotional state of the user using the system, including emotions such as joy, sadness, and anger.

[1425] "Tone" refers to the tone and mood of a sentence or word, and is adjusted based on the user's emotions.

[1426] "Ensuring quality" means checking and guaranteeing that generated business emails meet certain standards.

[1427] "Smart glasses" are a type of wearable device that incorporates a display and sensors into a glasses-type device.

[1428] A "brick and mortar store" is a store that exists in a physical location and where customers visit in person to purchase goods or services.

[1429] As an embodiment of this invention, we provide a system that generates appropriate business emails and messages in real time and sends them to customers when staff at a physical store wear smart glasses and deal with customers.

[1430] System configuration

[1431] The system consists of the following main components:

[1432] 1. Smart glasses: Wearable devices that incorporate a display, camera, and microphone.

[1433] 2. Server: Responsible for email generation, grammar checking, compliance checking, emotion recognition, tone adjustment, and quality assurance.

[1434] 3. User device: Used by store staff wearing smart glasses.

[1435] Program processing

[1436] The server does the following:

[1437] 1. Receiving a short instruction: Receive a short instruction from the user terminal.

[1438] 2. Emotion Recognition: Recognize the user's emotions using the camera and microphone of the smart glasses. For emotion recognition, use "emotion_recognition.EmotionEngine", for example.

[1439] 3. Email generation: Use a generative AI model (e.g., GPT-3 (registered trademark)) to generate business emails based on short instructions and recognized sentiment. Use "email_generator.EmailGenerator" to generate emails.

[1440] 4. Grammar check: Check the generated email for grammar errors. Use "quality_checker.QualityChecker" for grammar check.

[1441] 5. Compliance check: Check whether the generated email complies with laws and regulations.

[1442] 6. Adjust your tone: Adjust the tone of your email based on the user's emotions.

[1443] 7. Quality Assurance: Ensure the quality of the final email generated.

[1444] Specific examples

[1445] For example, if a brick-and-mortar store associate is wearing smart glasses and a customer asks about a new product, they might enter a prompt like this:

[1446] A customer asks about a new product. Your staff is excited. Generate the right business email.

[1447] Based on this prompt, the server recognizes the user's emotion (happiness) and generates a business email with a bright and positive tone. The generated email undergoes grammar and compliance checks and is finally sent to the customer with quality guaranteed.

[1448] This system will enable store staff to respond to customers quickly and appropriately, which is expected to improve customer satisfaction.

[1449] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1450] Step 1:

[1451] A user wears smart glasses and receives questions or requests from customers. The user uses the smart glasses' voice input function to input short instructions, such as "A customer is asking about a new product." This instruction becomes input data for the system.

[1452] Step 2:

[1453] The device converts the user's voice input into text data and sends it to the server. Speech recognition software is used to convert the voice data into text data, which then becomes the input for the next processing step.

[1454] Step 3:

[1455] The server uses the smart glasses' camera and microphone to recognize the user's emotions. It then uses an emotion recognition engine (e.g., emotion_recognition.EmotionEngine) to analyze the user's emotions from their facial expressions and tone of voice. The analysis results are output as the user's emotional state (e.g., joy, sadness).

[1456] Step 4:

[1457] The server generates a business email using a generative AI model (e.g., GPT-3 (registered trademark)) based on the emotion recognition results and text data. A prompt sentence is input into the generative AI model, which generates an appropriate business email. The generated business email becomes the input for the next processing step.

[1458] Step 5:

[1459] The server checks the generated business email for grammatical errors. It uses grammar checking software (e.g. quality_checker.QualityChecker) to detect and correct grammatical errors in the email. The corrected email becomes the input for the next processing step.

[1460] Step 6:

[1461] The server checks the generated business email for compliance. Compliance checking software is used to check whether the email complies with laws and regulations. If the email complies, it proceeds to the next processing step. If it does not comply, corrections are made.

[1462] Step 7:

[1463] The server adjusts the tone of the generated business email based on the user's emotions. Based on the emotion recognition results, the tone of the email can be brightened or calmed. The adjusted email becomes the input for the next processing step.

[1464] Step 8:

[1465] The server ensures the quality of the final business email. Quality assurance software is used to check that the email meets certain standards. If it does, the email is sent to the customer.

[1466] Step 9:

[1467] The terminal receives the final business email sent from the server and displays it to the user, who can then check the generated email through the smart glasses display and send it to their customer if necessary.

[1468] Example 3

[1469] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1470] Conventional business email creation systems can automatically generate emails and check grammar and compliance, but they cannot adjust the timing of email sending based on the user's emotional state, which can lead to incorrect emails being sent due to emotional judgment. Furthermore, there is a lack of efficient ways to relieve users from the enormous task of creating emails.

[1471] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for detecting the user's emotional state, means for adjusting the timing of sending the email based on the user's emotional state, and means for generating emails based on prompt sentences using a generative AI model. This makes it possible to efficiently create emails while taking the user's emotional state into consideration and prevent erroneous emails from being sent due to emotional judgment.

[1472] "Short instructions" refer to instructions entered by the user in a concise format, and are information that the system uses to automatically generate business emails based on these instructions.

[1473] "Business email" refers to email created for the purpose of business communication, with a formal style and content.

[1474] "Grammar errors" refers to grammatical errors in text, and detecting and correcting these can improve the quality of emails.

[1475] "Compliance" refers to following laws, regulations, and a company's internal rules, and involves checking whether the content of an email violates these.

[1476] "User's emotional state" refers to the user's current emotions, and is information for adjusting the timing of sending emails by detecting this.

[1477] An "emotion engine" is a software or hardware system for analyzing emotions from a user's facial expressions, voice, etc.

[1478] A "generative AI model" refers to a model that uses artificial intelligence to generate text, generating appropriate email content based on a prompt.

[1479] A "prompt sentence" is an instruction sentence input to a generative AI model, and is the basic information that the AI ​​uses to generate text.

[1480] The "means for adjusting the timing of sending email" is a function for appropriately changing the timing of sending email based on the emotional state of the user.

[1481] The present invention is a system that relieves users from the burden of creating large amounts of e-mail and enables them to send e-mails efficiently and with consideration for their emotions. A specific embodiment of this system will be described below.

[1482] Hardware and software used

[1483] Hardware: Servers, terminals (PCs, smartphones)

[1484] Software: Generative AI models (e.g., GPT-4®), emotion engines, email clients (e.g., Outlook, Gmail)

[1485] System Overview

[1486] The system automatically generates business emails from short instructions, checks the generated emails for grammatical errors and compliance, and has the ability to detect the user's emotional state and adjust the timing of sending emails based on their emotions.

[1487] System Operation

[1488] 1. The user inputs the meeting minutes data into the terminal.

[1489] After the meeting, the user enters the minutes into a text editor, for example, "At the meeting, the progress of the project was reported and the next task was assigned."

[1490] 2. The device sends the entered minutes data to the server.

[1491] The terminal sends the entered minutes data to the server. When you click the send button, the data is sent to the server using the HTTPS protocol.

[1492] 3. The server generates a prompt for the AI ​​model and generates an email based on the minutes data.

[1493] The server generates a prompt for the generative AI model saying, "Please generate follow-up emails for all participants based on the minutes below," and adds the minutes data.

[1494] The generative AI model generates appropriate follow-up emails based on the prompt text.

[1495] Examples:

[1496] Prompt: "Generate a follow-up email to all participants based on the following minutes: 'The meeting reported on project progress and assigned upcoming tasks.'"

[1497] Generated email: "Hey everyone, based on the meeting minutes, I'd like to let you know the next tasks. We're on track with the project. The next tasks are..."

[1498] 4. The server sends the generated email to the device

[1499] The server sends the generated email to the terminal, and the user checks the generated email using the email client on the terminal.

[1500] 5. The device detects the user's emotional state using an emotion engine.

[1501] The device analyzes the user's facial expressions and voice using an emotion engine. For example, if the user is angry, the emotion engine will detect that information.

[1502] 6. The emotion engine sends the user's emotional state to the server.

[1503] The emotion engine sends the analysis results to the server. If the user is angry, it sends the information that "the user is angry" to the server.

[1504] 7. The server adjusts the timing of sending emails based on the information from the emotion engine.

[1505] The server adjusts the timing of sending emails based on information from the emotion engine. If the user is angry, the server temporarily suspends sending the email.

[1506] 8. The server sends the email

[1507] The server waits for a certain period of time until the user calms down, and then sends the email. The email is sent to all participants.

[1508] In this way, the system can efficiently create emails while taking into account the emotional state of the user, and can prevent erroneous emails from being sent due to emotional judgment. The flow of the identification process in the third embodiment will be described with reference to FIG.

[1509] Step 1:

[1510] The user inputs the minutes data of the meeting into the terminal.

[1511] Input: A user types meeting minutes into a text editor, for example, "At the meeting, project status was reported and next tasks were assigned."

[1512] Data processing: The device stores the entered text data in its internal memory.

[1513] Output: Saved meeting minutes data.

[1514] Step 2:

[1515] The terminal transmits the input minutes data to the server.

[1516] Input: Saved meeting minutes data.

[1517] Data processing: The terminal sends the minutes data to the server using the HTTPS protocol.

[1518] Output: The transcript data sent to the server.

[1519] Step 3:

[1520] The server generates a prompt sentence for the generative AI model and generates an email based on the minutes data.

[1521] Input: Minutes data sent to the server.

[1522] Data processing: The server generates a prompt for the generative AI model saying, "Please generate follow-up emails for all participants based on the minutes below," and adds the minutes data.

[1523] Data calculation: The generative AI model generates appropriate follow-up emails based on the prompt text.

[1524] Output: The generated follow-up email.

[1525] Step 4:

[1526] The server sends the generated email to the terminal.

[1527] Input: The generated follow-up email.

[1528] Data processing: The server sends the generated email to the terminal.

[1529] Output: A follow-up email sent to the device.

[1530] Step 5:

[1531] The device detects the user's emotional state using an emotion engine.

[1532] Input: User facial and voice data.

[1533] Data calculation: The device uses an emotion engine to analyze the user's emotions from their facial expressions and voice. For example, if the user is angry, it will detect that information.

[1534] Output: The detected emotional state of the user.

[1535] Step 6:

[1536] The emotion engine transmits the user's emotional state to the server.

[1537] Input: The detected emotional state of the user.

[1538] Data processing: The emotion engine sends the analysis results to the server. For example, it sends information to the server that "the user is angry."

[1539] Output: The user's emotional state sent to the server.

[1540] Step 7:

[1541] The server adjusts the timing of sending emails based on information from the emotion engine.

[1542] Input: The user's emotional state sent to the server.

[1543] Data calculation: The server adjusts the timing of sending emails based on information from the emotion engine. If the user is angry, the server temporarily suspends sending emails.

[1544] Output: Adjusted email sending timing.

[1545] Step 8:

[1546] The server sends the email.

[1547] Input: The adjusted email send timing.

[1548] Data processing: The server waits a certain period of time until the user calms down, and then sends the email.

[1549] Output: Email sent to all participants.

[1550] (Application example 3)

[1551] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1552] Conventional business email creation systems automatically generate emails and check grammar and compliance, but they do not adjust the timing of email transmissions based on the user's emotional state or automatically generate and send reports based on data within the factory, which increases user stress and the risk of sending emails incorrectly. Additionally, there was a lack of a way to efficiently manage data within the factory and report at the appropriate time.

[1553] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for detecting the user's emotional state using an emotion engine and adjusting the timing of email transmission based on the specific emotional state, means for automatically generating reports based on data collected from various sensors and robots in the factory, and means for sending the generated reports by email. This makes it possible to adjust the timing of email transmission taking the user's emotional state into consideration, making it possible to efficiently manage data in the factory and report at the appropriate time.

[1554] "Short instructions" are instructions or commands entered by the user in a concise format, and are the input information used by the system to automatically generate business emails.

[1555] "Business email" refers to email created for business purposes such as business communications, reports, and requests.

[1556] "Grammar errors" refer to grammatical errors and inappropriate expressions in a sentence, and checking for these can improve the quality of an email.

[1557] "Compliance" means following laws, regulations, and a company's internal rules, and checking whether business emails comply with these.

[1558] An "emotion engine" is a technology that detects the user's emotional state and adjusts the system's behavior based on that information.

[1559] An "emotional state" is an emotion that a user is feeling, such as anger, joy, or sadness.

[1560] "Send timing" refers to the timing of sending emails and reports, and is adjusted based on the user's emotional state.

[1561] A "sensor" is a device that detects physical phenomena and outputs them as data.

[1562] A "robot" is a mechanical device used to automate work within a factory, and is often equipped with various sensors.

[1563] A "report" is a report that summarizes various data within the factory, and can be automatically generated and sent by email.

[1564] "Data" refers to the information collected from sensors and robots, which is used to generate reports.

[1565] A system for carrying out this invention has the following configuration: A server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for detecting the emotional state of a user using an emotion engine and adjusting the timing of sending emails based on the specific emotional state, means for automatically generating reports based on data collected from various sensors and robots in a factory, and means for sending the generated reports by email.

[1566] System program processing explanation

[1567] The server first receives a short instruction from the user and then automatically generates a business email using a generative AI model. It then uses a natural language processing library (e.g., NLTK or spaCy) to check the generated business email for grammatical errors. It also checks the generated business email for compliance with pre-defined rules and regulations.

[1568] Next, the system uses an emotion engine to detect the user's emotional state. This emotion engine analyzes the user's facial expressions and tone of voice using, for example, a camera or microphone. If the emotional state is "anger," the system temporarily suspends sending the email and waits until the user calms down.

[1569] Furthermore, reports are automatically generated based on data collected from various sensors and robots in the factory. This data is obtained, for example, from temperature sensors and production line robots. An IoT platform (e.g., AWS IoT or Google Cloud IoT) is used to collect and analyze the data. The generated reports are automatically sent by email, either periodically or when an abnormality is detected.

[1570] Specific examples

[1571] For example, when a factory manager inputs a short instruction into the system, such as "Please report on this week's production status," the server uses a generative AI model to automatically generate an appropriate business email. This email will be sent only if the manager's emotional state is not "angry," after passing grammar and compliance checks.

[1572] In addition, periodic reports are automatically generated based on data collected from sensors within the factory. These reports, such as "This week's production line utilization rate was 95%. No abnormalities were detected," are sent to the manager via email.

[1573] Prompt Sentence Examples

[1574] The following prompts can be fed to the generative AI model:

[1575] Create a program that generates periodic reports based on data collected from sensors in the factory and emails them to the manager. Also, add a function that detects the user's emotional state and withholds emails if the user is angry.

[1576] By using this prompt sentence, the generative AI model can generate a program to realize the system described above.

[1577] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1578] Step 1:

[1579] The user inputs a short instruction. For example, the user inputs a simple instruction into the terminal, such as "Please report on this week's production status." This input becomes the initial data for the system.

[1580] Step 2:

[1581] The server automatically generates business emails using a generative AI model. The server receives short instructions from the user and inputs them as prompts to the generative AI model. The generative AI model generates appropriate business emails based on these prompts. The output is the generated business email.

[1582] Step 3:

[1583] The server checks the generated business email for grammatical errors. The server uses a natural language processing library (e.g., NLTK or spaCy) to detect and correct grammatical errors in the generated business email. The input is the generated business email, and the output is the business email with the grammatical errors corrected.

[1584] Step 4:

[1585] The server checks the generated business email for compliance. The server checks whether the generated business email complies with pre-defined rules and laws. The input is a business email with grammatical errors corrected, and the output is a business email that has passed the compliance check.

[1586] Step 5:

[1587] The server uses an emotion engine to detect the user's emotional state. The server uses a camera and microphone to analyze the user's facial expressions and tone of voice and inputs the results into the emotion engine. The emotion engine classifies the user's emotional state into categories such as "anger," "joy," and "sadness." The input is the user's facial and voice data, and the output is the user's emotional state.

[1588] Step 6:

[1589] The server adjusts the timing of sending emails based on the user's emotional state. The server determines whether to temporarily suspend sending emails based on the user's emotional state obtained from the emotion engine. For example, if the user is in an "angry" state, the server suspends sending emails and waits until the user calms down. The input is the user's emotional state, and the output is adjusting the timing of sending emails.

[1590] Step 7:

[1591] The server collects data from various sensors and robots in the factory. Using an IoT platform (for example, AWS IoT or Google Cloud IoT), the server collects data from temperature sensors in the factory and robots on the production line. The input is data from the sensors and robots, and the output is the collected data.

[1592] Step 8:

[1593] The server automatically generates reports based on the data collected. The server analyzes the collected data and automatically generates periodic reports and reports when an abnormality occurs. The input is the collected data, and the output is the generated report.

[1594] Step 9:

[1595] The server sends the generated report by email. The server sends the generated report by email to the administrator at the appropriate time. The input is the generated report and the output is the sent email.

[1596] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1597] The data generation model 58 is a so-called generative AI (Artificial Intelligence). Examples of the data generation model 58 include generative AIs such as ChatGPT (registered trademark) (Internet search <URL: https: / / OpenAI (registered trademark).com / blog / chatgpt>). The data generation model 58 is obtained by causing a neural network to perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is input. The data generation model 58 infers the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summary, etc.

[1598] Other examples of generative AIs include Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1599] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1600] [Third embodiment]

[1601] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1602] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1603] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1604] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1605] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1606] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1607] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1608] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1609] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1610] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1611] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1612] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1613] "Example 1"

[1614] The present invention is a system that streamlines the creation and review of business emails. Specifically, it receives short instructions from the user and automatically creates business emails based on those instructions. The generated emails are then checked for grammatical errors and compliance violations using the system's internal grammar and compliance check functions.

[1615] "Example 2"

[1616] Furthermore, this embodiment of the present invention has a function to guarantee the quality of the generated business emails. This not only reduces the time required to create emails, but also guarantees quality. Specifically, it checks whether the content of the email conforms to business communication standards and whether appropriate honorific language is used.

[1617] "Example 3"

[1618] Furthermore, this embodiment of the present invention has the function of freeing users from the burden of creating large amounts of emails. Specifically, the system can automatically generate multiple emails at once, allowing users to focus on other tasks. For example, it is possible to generate follow-up emails to all participants at once based on the minutes of a meeting.

[1619] The processing flow of each embodiment will be described below.

[1620] "Example 1"

[1621] Step 1: The system receives a short instruction from the user. For example, the instruction might be, "Create a follow-up email to all participants based on the meeting minutes."

[1622] Step 2: Based on the received instructions, the system automatically generates a business email, with the appropriate content, recipient, subject, etc.

[1623] Step 3: The generated email is checked for grammatical errors using the system's internal grammar check function.

[1624] Step 4: Furthermore, the generated email is checked for compliance violations using the compliance check function.

[1625] "Example 2"

[1626] Step 1: The system operates a function to ensure the quality of business emails automatically generated. Step 2: Specifically, the system checks whether the content of the email conforms to business communication standards and whether appropriate honorific language is used.

[1627] Step 3: This not only saves time in creating emails but also ensures quality.

[1628] "Example 3"

[1629] Step 1: The system can automatically generate multiple emails at once.

[1630] Step 2: For example, you can use the meeting minutes to generate follow-up emails to all participants at once.

[1631] Step 3: This frees users from the overwhelming task of creating emails, allowing them to focus on other tasks.

[1632] Example 1

[1633] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1634] Traditionally, creating business documents manually required time and effort, and there was a high risk of grammatical errors and non-compliance. Furthermore, the checking process to ensure document quality was also time-consuming, making it difficult to efficiently manage business operations.

[1635] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1636] In this invention, the server includes means for automatically generating business documents from short instructions, means for checking the generated business documents for grammatical errors, means for checking the generated business documents for compliance, means for passing the generated business documents through a grammar check function, means for passing the generated business documents through a compliance check function, and means for providing the final checked business documents to the user. This makes it possible to streamline the generation and review of business documents, shorten document creation time, and ensure quality.

[1637] A "short instruction" is a concise instruction entered by a user, which contains basic information required to generate a business document.

[1638] A "business document" is an official document used for business communication, reporting, guidance, etc.

[1639] "Means for automatic generation" refers to technologies and algorithms for automatically creating business documents based on short instructions from users.

[1640] "Grammar checking measures" refers to techniques and algorithms used to detect and correct grammatical errors in generated business documents.

[1641] "Compliance checking measures" refers to technologies and algorithms used to verify that generated business documents do not violate corporate policies or legal regulations.

[1642] "Means for passing through a grammar checker" refers to the process of inputting the generated business document into a grammar checker to check for grammatical accuracy.

[1643] "Means for passing through compliance check function" refers to the process of inputting generated business documents into the compliance check function to check whether they violate regulations or policies.

[1644] "Final verified business document" refers to a business document that has passed grammar and compliance checks and has been finally verified.

[1645] "Means to provide to users" refers to the technology or algorithms used to display or transmit finalized business documents to users.

[1646] This invention relates to a system that improves the efficiency of creating and reviewing business documents. Specifically, this system receives short instructions from a user, automatically generates business documents based on those instructions, and checks the generated documents for grammatical errors and compliance violations.

[1647] System configuration

[1648] Hardware

[1649] The system consists of a server and a terminal. The server plays a central role in data processing and document generation, while the terminal is used to receive input from users and display the final document.

[1650] software

[1651] The server has installed on it a generative AI model (e.g., a natural language processing model), a grammar checker (e.g., a grammar check API), and a compliance checker (e.g., a compliance management tool). These pieces of software work together to efficiently generate and review business documents.

[1652] Program processing

[1653] The server receives a short instruction from the user, such as "Please send me a meeting reminder." The server inputs this instruction into a generative AI model, which then automatically generates a business document based on the instruction.

[1654] The generated document is checked for grammatical errors and compliance violations using the server's internal grammar and compliance check functions. The grammar check function checks the document's grammatical accuracy and makes corrections as necessary. The compliance check function checks whether the document content violates company policies or legal regulations.

[1655] Specific examples

[1656] For example, if a user inputs the instruction "Please create an email to introduce our new product," the following specific actions will be taken:

[1657] 1. The user enters "Please create an introductory email for our new product" into the input field on the terminal.

[1658] 2. The device sends this instruction to the server.

[1659] 3. The server inputs the instructions into the generative AI model and passes the prompt, "Please create an email to introduce a new product. The product name is 'XYZ Smartwatch' and its main features are long battery life, heart rate monitoring, and GPS functionality."

[1660] 4. The generative AI model generates a business document that looks like this:

[1661] Subject: Introducing our new product "XYZ Smart Watch"

[1662] Dear Customer,

[1663] Thank you for your continued support. We have recently released a new product, the XYZ Smartwatch. The XYZ Smartwatch is a multi-functional smartwatch that comes equipped with a long-lasting battery, heart rate monitoring, and GPS functionality to make your daily life more convenient.

[1664] Please take this opportunity to try it out.

[1665] Thank you very much.

[1666] Sincerely,

[1667] 5. The server runs the generated document through a grammar checker to correct any grammatical errors.

[1668] 6. The server passes the grammar-checked document through a compliance checker to ensure it does not violate corporate policies or legal regulations.

[1669] 7. The server sends the final verified document to the terminal.

[1670] 8. The terminal displays the final confirmed document to the user, and the user confirms the document.

[1671] In this way, the creation and review of business documents is made more efficient, reducing the time required for document creation and ensuring quality.

[1672] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1673] Step 1:

[1674] The user enters a short instruction.

[1675] The user inputs a short instruction into an input field on the terminal, such as "Please create an email to introduce our new product." The input data is the user's instruction text.

[1676] Step 2:

[1677] The terminal sends instructions to the server.

[1678] The terminal transmits instructions entered by the user to the server. The terminal transmits data using an Internet connection. The input data is the user's instruction text, and the output data is the instruction text sent to the server.

[1679] Step 3:

[1680] The server inputs instructions into the generative AI model.

[1681] The server inputs the received instructions into the generative AI model. Specifically, it passes the instructions to the generative AI model as a prompt. The input data is the instruction sent to the server, and the output data is the prompt passed to the generative AI model.

[1682] Step 4:

[1683] A generative AI model generates business documents.

[1684] A generative AI model generates a business document based on a prompt. For example, if a user instructs the model to "create an email introducing a new product," the model generates a document that includes the features and benefits of the new product. The input data is the prompt, and the output data is the generated business document.

[1685] Step 5:

[1686] The server passes the generated document through a grammar checker.

[1687] The server passes the generated document through a grammar checker, which checks the document for grammatical accuracy and makes corrections as necessary. The input data is the generated business document, and the output data is the grammar-checked document.

[1688] Step 6:

[1689] The server passes the grammar-checked document through a compliance check function.

[1690] The server passes the grammar-checked document through a compliance check function, which checks whether the document content violates company policies or legal regulations. The input data is the grammar-checked document, and the output data is the compliance-checked document.

[1691] Step 7:

[1692] The server sends the final verified document to the terminal.

[1693] The server sends the final verified document to the terminal. At this time, the server checks that the document content is grammatically and complies with all applicable standards. The input data is the compliance-checked document, and the output data is the final verified document sent to the terminal.

[1694] Step 8:

[1695] The terminal displays the final verified document to the user.

[1696] The terminal displays the final verified document received from the server to the user. The user checks the displayed document and corrects or submits it as necessary. The input data is the final verified document, and the output data is the document displayed to the user.

[1697] (Application example 1)

[1698] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1699] Business communications and report creation within factories are often done manually, which takes time and effort. There is also a high risk of grammatical errors and compliance violations. This reduces work efficiency and makes quality assurance difficult.

[1700] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1701] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for improving the efficiency of business communications and report creation within the factory, means for detecting and correcting grammatical errors in the generated emails, and means for checking for compliance violations in the generated emails. This makes it possible to improve the efficiency of business communications and report creation within the factory, reduce the risk of grammatical errors and compliance violations, and improve business efficiency and quality assurance.

[1702] A "short instruction" is a text that the user enters briefly to indicate the nature of the work or request.

[1703] "Business email" refers to email sent for business purposes such as business communications and reports.

[1704] "Auto-generation" is the process by which a system automatically creates text based on user input.

[1705] "Grammar mistakes" refers to grammatical errors or inappropriate expressions in a sentence.

[1706] "Compliance" refers to following laws, regulations, and a company's internal rules.

[1707] "Inside the factory" refers to the facility or its interior where manufacturing operations take place.

[1708] "Business communication" is the act of conveying information or instructions related to work.

[1709] A "report" is a document that summarizes the progress and results of work.

[1710] "Efficiency" refers to performing tasks and processes more effectively and quickly.

[1711] "Quality assurance" is the process of ensuring that a product or service meets certain quality standards.

[1712] "Detecting and correcting grammatical errors" refers to finding grammatical errors in a sentence and correcting them to the correct expression.

[1713] "Violation of compliance" refers to any act or content that violates laws, regulations, or a company's internal rules.

[1714] To implement the present invention, the following system configuration and program are required.

[1715] System Configuration

[1716] 1. Hardware:

[1717] Computers installed in factory robots

[1718] Network Connection

[1719] 2. Software:

[1720] Python

[1721] OpenAI(R) API

[1722] LanguageTool

[1723] Program processing explanation

[1724] The server receives short instructions from the user and automatically generates business emails based on them. Specifically, it uses a generative AI model (e.g., GPT-3 (registered trademark)) to generate emails based on the user's instructions. The generated emails are then checked for grammatical errors and corrected using LanguageTool. A simple keyword search is also performed to check for compliance violations.

[1725] Specific examples

[1726] When the user enters the instruction "Please generate a status update email for the production line.", the server generates an email like this:

[1727] Example of a generated email

[1728] Dear Team,

[1729] I would like to provide an update on the current status of the production line. We have successfully completed the first phase and are moving on to the next steps. Thank you for your hard work.

[1730] Best regards,

[1731] [Your Name]

[1732] The generated email is checked for grammar errors using LanguageTool, and a compliance check is performed to warn if the email contains, for example, the word "confidential."

[1733] Prompt Sentence Examples

[1734] Please generate a status update email for the production line.

[1735] In this way, business communication and report creation within the factory becomes more efficient, the risk of grammatical errors and compliance violations is reduced, and work efficiency and quality assurance can be improved.

[1736] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1737] Step 1:

[1738] The user inputs a short instruction, such as a prompt phrase like "Please generate a status update email for the production line." This input is sent to the server.

[1739] Step 2:

[1740] The server sends the received prompt to a generative AI model (e.g., GPT-3 (registered trademark)). The generative AI model automatically generates a business email based on the prompt. This generated email is returned to the server.

[1741] Step 3:

[1742] The server sends the generated business email to LanguageTool, which checks for grammatical errors. LanguageTool detects grammatical errors in the email and returns the corrected email to the server.

[1743] Step 4:

[1744] The server sends the corrected email to the compliance check module, which searches for specific keywords (e.g., "confidential") in the email to check for compliance violations. If a violation is detected, the information is returned to the server.

[1745] Step 5:

[1746] The server returns the final email to the user, who can then view it through their device after corrections and compliance checks have been completed.

[1747] Specific actions at each step

[1748] Step 1:

[1749] Input: User types into terminal, "Please generate a status update email for the production line."

[1750] Output: The prompt text entered is sent to the server.

[1751] Step 2:

[1752] Input: The server receives the prompt.

[1753] Data processing: Send prompt text to the generative AI model (GPT-3 (registered trademark)) to generate a business email.

[1754] Output: The generated business email is returned to the server.

[1755] Step 3:

[1756] Input: The server receives a generated business email.

[1757] Data calculation: Send email to LanguageTool to detect and correct grammar errors.

[1758] Output: The modified email is returned to the server.

[1759] Step 4:

[1760] Input: The server receives the modified email.

[1761] Data calculation: Send emails to the compliance check module and search for specific keywords to check for compliance violations.

[1762] Output: Compliance violations or not are returned to the server.

[1763] Step 5:

[1764] Input: The server receives the final email.

[1765] Output: A completed remediation and compliance check email is sent back to the user.

[1766] Example 2

[1767] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1768] Conventional business document creation systems do not adequately check for grammatical errors or compliance when automatically generating documents, and lack functionality to check whether documents conform to business communication standards or use appropriate honorific language. As a result, the quality of the generated documents cannot be guaranteed, and users often have to manually correct them. Furthermore, document creation efficiency is not sufficiently improved, and users are unable to be relieved of the enormous amount of document creation work.

[1769] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1770] In this invention, the server includes means for automatically generating business documents from short instructions, means for checking the generated business documents for grammatical errors, means for checking the generated business documents for compliance, means for verifying whether the generated business documents conform to business communication standards, means for verifying whether the generated business documents use appropriate honorific language, means for analyzing the generated business documents using natural language processing technology, and means for correcting the business documents based on the analysis results. This ensures document quality and eliminates the need for users to manually correct the documents. It also improves the efficiency of document creation, freeing users from the burden of extensive document creation work.

[1771] A "short instruction" is a concise text entered by a user that contains the information necessary to generate a business document.

[1772] "Business documents" are official documents used for business communication, including emails, reports, notices, etc.

[1773] "Auto-generation" is the process by which a system automatically creates a business document based on user input.

[1774] "Grammar errors" are grammatical errors in generated business documents, and refer to errors in sentence structure and word usage.

[1775] "Compliance" refers to checking whether generated business documents comply with laws, regulations, and internal company rules.

[1776] "Business communication standards" refer to the generally accepted format, expression, and etiquette for business documents.

[1777] "Honorific language" refers to polite language used in business documents, and is a form of language used to express respect for the other person.

[1778] "Natural language processing technology" is a technology that enables computers to understand, analyze, and generate human language, and is used to analyze and generate text.

[1779] "Analysis results" refers to information obtained after analyzing business documents generated using natural language processing technology, and includes check results for grammatical errors and compliance.

[1780] "Correction" is the process of correcting errors or inappropriate parts of business documents generated based on the analysis results, thereby improving their quality.

[1781] The present invention relates to a system that automatically generates business documents from short instructions and guarantees the quality of the documents. A specific embodiment of this system will be described below.

[1782] First, the user inputs a prompt using a terminal. The prompt contains instructions for generating a business document for the generative AI model. For example, the user can input a prompt such as, "Please create an email to announce the launch of a new product."

[1783] The device sends the prompt text entered by the user to the server. The server analyzes the received prompt text and inputs it into a generative AI model. For example, GPT-4 (registered trademark) from OpenAI (registered trademark) can be used as the generative AI model.

[1784] The generative AI model generates a business document based on the input prompt. The generated business document is then analyzed by the server using natural language processing technology. For natural language processing, an NLP library such as SpaCy or NLTK can be used.

[1785] The server checks the generated business documents for grammatical errors and compliance, and verifies whether they conform to business communication standards and use appropriate honorific language, thereby ensuring the quality of the generated business documents.

[1786] Based on the analysis results, the server modifies the business document as needed, for example, correcting any honorific errors and adjusting it to conform to business standards.

[1787] Finally, the quality-assured business document is sent from the server to the terminal, which then displays the received business document to the user, who can then check the displayed business document and make further corrections as necessary.

[1788] This system allows users to create high-quality business documents in a short time. For example, if a user inputs the prompt "Please create an email to announce the release of a new product," the following business document will be generated:

[1789] Subject: Announcement of new product release

[1790] Dear Customers,

[1791] We would like to express our sincere gratitude for your continued support.

[1792] We are pleased to announce that we will be releasing a new product, "XYZ."

[1793] Details are as follows:

[1794] Product name:XYZ

[1795] Release date: October 1, 2023

[1796] Price: 10,000 yen

[1797] We appreciate your cooperation.

[1798] Sincerely,

[1799] ABC Co., Ltd.

[1800] In this way, users can efficiently create high-quality business documents.

[1801] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1802] Step 1:

[1803] The user enters a prompt statement.

[1804] The user inputs a prompt sentence into an input field on the terminal, such as "Please create an email to notify you about the release of a new product." The input prompt sentence contains instructions for generating a business document.

[1805] Step 2:

[1806] The terminal sends the prompt to the server.

[1807] The terminal sends the prompt text entered by the user to the server as an HTTP request. The input data is the prompt text, and the output data is the request to the server.

[1808] Step 3:

[1809] The server receives the prompt sentence and inputs it into the generative AI model.

[1810] The server analyzes the prompt sentence received from the terminal and inputs it into a generative AI model (e.g., OpenAI's GPT-4®). The input data is the prompt sentence, and the output data is the input to the generative AI model.

[1811] Step 4:

[1812] A generative AI model generates business documents.

[1813] The generative AI model generates a business document based on the input prompt. The input data is the prompt, and the output data is the generated business document. For example, the following business document is generated:

[1814] Subject: Announcement of new product release

[1815] Dear Customers,

[1816] We would like to express our sincere gratitude for your continued support.

[1817] We are pleased to announce that we will be releasing a new product, "XYZ."

[1818] Details are as follows:

[1819] Product name:XYZ

[1820] Release date: October 1, 2023

[1821] Price: 10,000 yen

[1822] We appreciate your cooperation.

[1823] Sincerely,

[1824] ABC Co., Ltd.

[1825] Step 5:

[1826] The server parses the generated business document using an NLP library.

[1827] The server analyzes the generated business document using natural language processing technology (for example, SpaCy or NLTK). The input data is the generated business document, and the output data is the analysis results. The purpose of the analysis is to check for grammatical errors and compliance, whether the document conforms to business communication standards, and whether appropriate honorific language is used.

[1828] Step 6:

[1829] The server modifies the business document based on the analysis results.

[1830] The server modifies the content of the business document as needed based on the results of the NLP analysis. The input data is the analysis result, and the output data is the modified business document. For example, any errors in honorific language are corrected, and the document is adjusted to conform to business standards.

[1831] Step 7:

[1832] The server transmits the quality-guaranteed business document to the terminal.

[1833] The server sends the modified business document to the terminal as an HTTP response. The input data is the modified business document, and the output data is the response to the terminal.

[1834] Step 8:

[1835] The terminal displays the business document to the user.

[1836] The terminal displays the business document received from the server to the user. The input data is the response from the server, and the output data is the business document displayed to the user. The user can check the displayed business document and make further corrections if necessary.

[1837] (Application example 2)

[1838] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1839] Creating business emails is a time-consuming and labor-intensive task, especially for customer support staff at electronic payment services. It is also important to ensure that the content of the email complies with business communication standards and that appropriate honorific language is used, but doing this manually is inefficient. Furthermore, it is also necessary to guarantee the quality of the generated emails. A system to solve these issues is needed.

[1840] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1841] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for confirming whether the generated business emails conform to business communication standards, and means for confirming whether the generated business emails use appropriate honorific language, thereby reducing the time required to create business emails and ensuring quality.

[1842] "Short instructions" are brief instructions or keywords entered by the user, and are input information that the system uses to automatically generate business emails.

[1843] "Business email" refers to emails intended for official communication within and outside a company or organization, and are used for business communications, customer correspondence, etc.

[1844] "Auto-generation" refers to the process by which a system automatically creates text based on user input, eliminating the need for manual text creation.

[1845] "Grammar errors" refer to grammatical errors or inappropriate expressions within a sentence, and checking these ensures the accuracy of the sentence.

[1846] "Compliance" means checking whether an email conforms to laws, regulations, and a company's internal rules, and it involves checking whether business emails meet these standards.

[1847] "Business communication standards" refer to the manners, formalities, and methods of expression generally expected in business communication, and are used to check whether or not a document complies with these standards.

[1848] "Honorific language" refers to the use of language to show respect to the other person, and this is to check whether appropriate honorific language is used in business emails.

[1849] "Ensuring quality" means making sure that the generated business emails meet certain standards and assuring users of that quality.

[1850] The following system configuration will be described as an embodiment of the present invention.

[1851] System Configuration

[1852] This system consists of a server and a user terminal. The server automatically generates business emails using a generative AI model and performs various checks to ensure their quality. The user terminal provides an interface that allows users to input short instructions and check and edit the generated business emails.

[1853] Hardware and software used

[1854] Hardware: Servers and user devices connected to the Internet (smartphones, PCs, etc.)

[1855] Software: Python, OpenAI (registered trademark) API, web browser

[1856] Data processing and calculation

[1857] 1. User input: The user inputs a short instruction using the user terminal. For example, the user inputs a prompt sentence such as "Please generate a business email that explains to the customer how to use the electronic payment service."

[1858] 2. Email generation: The server uses the OpenAI (registered trademark) API to automatically generate a business email based on the input prompt text.

[1859] 3. Grammar Check: Check the generated business email for grammatical errors using natural language processing technology.

[1860] 4. Compliance check: Check whether the generated business email complies with laws and regulations.

[1861] 5. Quality Assurance: Ensure that generated business emails comply with business communication standards and use appropriate honorific language.

[1862] Specific examples

[1863] The user enters the following prompt text:

[1864] "Generate a business email to explain to customers how to use your electronic payment service."

[1865] The server uses the OpenAI® API to generate a business email like this:

[1866] "Thank you for your support. We would like to explain how to use our electronic payment service. First, please download the app, and then create an account. Please refer to the link below for detailed instructions. Sincerely."

[1867] The server then checks the generated email for grammatical errors, compliance with business communication standards, and the use of honorific language, providing users with quality-assured emails.

[1868] In this way, the user can quickly create high-quality business emails by simply inputting a few instructions.

[1869] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1870] Step 1:

[1871] The user inputs a short instruction (prompt sentence) using the user terminal.

[1872] Input: Prompt text (e.g., "Please generate a business email to explain to your customers how to use the electronic payment service.")

[1873] Output: The prompt text is sent to the server.

[1874] Step 2:

[1875] Based on the prompt received by the server, a business email is automatically generated using the OpenAI (registered trademark) API.

[1876] Input: prompt statement

[1877] Data processing: Using the OpenAI (registered trademark) API, prompt sentences are input into the generative AI model to generate business emails.

[1878] Output: Generated business email

[1879] Step 3:

[1880] The server checks generated business emails for grammatical errors.

[1881] Input: Generated business email

[1882] Data Computing: Detect grammatical errors using natural language processing techniques.

[1883] Output: A business email with grammar errors corrected

[1884] Step 4:

[1885] The server checks generated business emails for compliance.

[1886] Input: A business email with grammar corrections

[1887] Data calculation: Checks are carried out to ensure compliance with laws and regulations.

[1888] Output: Compliance verified business email

[1889] Step 5:

[1890] Verify that server-generated business emails comply with business communication standards.

[1891] Input: Compliance verified business email

[1892] Data Calculation: Checks are performed to ensure compliance with business communication standards.

[1893] Output: Business emails that meet business communication standards

[1894] Step 6:

[1895] Ensure that proper honorific language is used in business emails generated by the server.

[1896] Input: Business email that meets business communication standards

[1897] Data calculation: Checks are performed to ensure that honorific language is used appropriately.

[1898] Output: A business email with proper use of honorific language

[1899] Step 7:

[1900] The server sends quality-guaranteed business emails to the user terminal.

[1901] Input: A business email with proper use of honorific language

[1902] Output: Quality-guaranteed business emails are sent to the user's terminal.

[1903] Step 8:

[1904] Users can check and edit quality-guaranteed business emails on their devices.

[1905] Input: Quality-guaranteed business email

[1906] Output: The final business email is created.

[1907] Example 3

[1908] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1909] Traditionally, email creation was often done manually, which required time and effort, resulting in reduced work efficiency. Creating emails manually also carries the risk of grammatical errors and compliance violations. Furthermore, creating follow-up emails based on meeting minutes was particularly time-consuming and a burden on users.

[1910] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes means for uploading meeting minutes, means for analyzing the uploaded minutes, means for generating a prompt sentence based on the analysis result, means for automatically generating multiple emails using the generated prompt sentence, and means for providing the generated emails to the user. This enables automation and efficiency of email creation.

[1911] "Meeting minutes" are documents that record what was discussed during a meeting, decisions made, and comments made by participants.

[1912] The "means for uploading" is a function that allows a user to use a terminal to send a meeting minutes file to the system.

[1913] The "means of analysis" refers to the function by which the server converts the contents of the uploaded minutes file into text format and analyzes the contents using a generative AI model.

[1914] The "means for generating prompt sentences" is a function that creates instruction sentences to be input into the generative AI model based on the analysis results.

[1915] "Means for automatically generating emails" refers to a function that uses a generative AI model to create multiple emails based on generated prompt text.

[1916] The "means for providing to the user" is a function for sending the generated email to the user's email client or allowing the user to download it.

[1917] This invention is a system that relieves users from the burden of creating a huge amount of emails. The system has the function of automatically generating multiple emails based on the minutes of a meeting. A specific embodiment of this system is described below.

[1918] Hardware and software used

[1919] Hardware: Servers, devices (PCs, smartphones, etc.)

[1920] Software: Generative AI models (e.g., GPT-4®), email clients (e.g., Outlook, Gmail)

[1921] System Overview

[1922] A user uses a terminal to upload a meeting minutes file to the system. The server receives the uploaded minutes file and analyzes its contents using a generative AI model. Based on the analysis results, the server generates prompts to input into the generative AI model. Using the generated prompts, the server automatically generates multiple follow-up emails. The generated emails are sent to the user's email client or made available for the user to download.

[1923] Specific examples

[1924] For example, if a user uploads minutes stating, "At the meeting on October 1, 2023, we discussed the progress and next steps of the project. The participants were A, B, and C," the server will generate the following prompt:

[1925] Example prompt sentence:

[1926] "Please write a follow-up email to all participants based on the minutes of the following meeting. Minutes: At the meeting on October 1, 2023, we discussed the project progress and next steps. Participants were A, B, and C."

[1927] By inputting this prompt into the generative AI model, the server automatically generates a follow-up email like the one below.

[1928] Example of generated email:

[1929] "Thank you for your feedback during the meeting. Here are our next steps..."

[1930] In this way, the system saves the user the trouble of manually creating an email, and enables the user to carry out business efficiently. The flow of the specific processing in the third embodiment will be described with reference to FIG.

[1931] Step 1:

[1932] A user uploads meeting minutes. Using a terminal, the user accesses the system's web interface and clicks the "Select File" button to select a minutes file (e.g., a PDF or Word file) from local storage. The input is the minutes file, and the output is the minutes file sent to the server.

[1933] Step 2:

[1934] The server receives the minutes and converts them into text format. The server receives the uploaded minutes file and converts it into text format using OCR (Optical Character Recognition) technology. The input is the minutes file and the output is the minutes in text format.

[1935] Step 3:

[1936] The server analyzes the text minutes. The server uses a generative AI model (e.g., GPT-4 (registered trademark)) to analyze the content of the text minutes. Specifically, it extracts the meeting topic, participants, points discussed, etc. The input is the text minutes, and the output is the analysis results.

[1937] Step 4:

[1938] The server generates a prompt based on the analysis results. Based on the analysis results, the server generates a prompt to be input into the generative AI model. For example, a prompt might be generated that reads, "Please write a follow-up email to all participants based on the minutes of the following meeting. Minutes: At the meeting on October 1, 2023, we discussed the project's progress and next steps. Participants were A, B, and C." The input is the analysis results, and the output is the prompt.

[1939] Step 5:

[1940] The server automatically generates multiple emails using the generated prompt text. The server inputs the generated prompt text into a generative AI model, which automatically generates multiple follow-up emails. The generative AI model creates emails with the appropriate format and content based on the prompt text. For example, it generates an email with the content, "Dear Mr. A, thank you for your feedback at the meeting. The next steps are as follows..." The input is the prompt text, and the output is the generated email.

[1941] Step 6:

[1942] The server provides the generated email to the user. The server either sends the generated email to the user's email client or makes it available for the user to download, either by sending the email to the user's email address or by providing a "download" button on the system's web interface. The input is the generated email and the output is the email provided to the user.

[1943] Step 7:

[1944] The user reviews and sends the email. The user reviews the generated email and makes any necessary edits, such as adding a personalized message for a specific participant. The user then uses their email client to send the email to all participants. The input is the generated email and the output is the sent email.

[1945] (Application example 3)

[1946] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1947] At logistics centers, there is a problem of a huge volume of emails being generated regarding shipping status, inventory status, and delivery schedules, which reduces work efficiency. In addition, creating follow-up emails based on meeting minutes and daily reports takes time and effort, so there is a need to improve work efficiency.

[1948] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for generating follow-up emails in bulk based on meeting minutes and daily reports, means for inputting appropriate prompt sentences using a generative AI model, and means for automatically generating emails regarding shipping status, inventory status, and delivery schedules at a logistics center. This makes it possible to improve the efficiency and reduce the time required for email creation work at logistics centers.

[1949] "Short instructions" refer to brief text inputs or commands that the system uses to automatically generate business emails.

[1950] "Business email" refers to email for business purposes, and is used to contact business partners and internal stakeholders.

[1951] "Grammar mistakes" refers to grammatical errors in a sentence, and detecting and correcting these can improve the quality of emails.

[1952] "Compliance" refers to following laws, regulations, and a company's internal rules, and involves checking whether generated business emails comply with these.

[1953] "Meeting minutes" are documents that record the matters discussed and decisions made during a meeting, and are a source of information for generating follow-up emails.

[1954] A "daily report" is a report that records the progress and results of work on a daily basis, and is a source of information for generating follow-up emails.

[1955] A "follow-up email" is an additional communication email sent to relevant parties based on the progress of a meeting or task, informing them of next steps or confirmations.

[1956] A "generative AI model" refers to an algorithm or system that uses artificial intelligence to generate text, automatically generating appropriate email content based on a prompt.

[1957] A "prompt" is a text instruction that is input into a generative AI model, serving as a guideline for the AI ​​to generate emails.

[1958] A "logistics center" is a facility that handles logistics operations such as storing, managing, shipping, and delivering goods, and is a place where efficient business operations are required.

[1959] "Shipping status" refers to the progress and status of product shipments, and is information used to contact relevant parties based on this.

[1960] "Inventory status" refers to the amount and condition of products in stock at the logistics center, and is information used to contact relevant parties based on this information.

[1961] "Delivery schedule" refers to the product delivery plan and timeline, and is information used to contact relevant parties based on this.

[1962] A system for carrying out this invention has the following configuration: A server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for generating follow-up emails in bulk based on meeting minutes and daily reports, means for inputting appropriate prompt sentences using a generative AI model, and means for automatically generating emails regarding shipping status, inventory status, and delivery schedules at a logistics center.

[1963] Hardware and software used

[1964] Hardware: Smartphones, servers

[1965] Software: Python, OpenAI® API

[1966] Data processing and calculation

[1967] 1. Data entry: Users enter text data such as meeting minutes and daily reports using their smartphones or other devices.

[1968] 2. Prompt generation: The server generates a prompt sentence appropriate for the generative AI model based on the input data.

[1969] 3. Email generation: The server uses a generative AI model (e.g., OpenAI's GPT-3®) to automatically generate an email based on the prompt.

[1970] 4. Grammar Check: Check the generated email for grammar errors and correct them if necessary.

[1971] 5. Compliance check: Check whether the generated email complies with laws, regulations, and internal company rules.

[1972] 6. Output: The generated email is displayed on the smartphone application so that the user can check it.

[1973] Specific examples

[1974] Let's take the example of automatically generating follow-up emails regarding shipping status and inventory management after a meeting at a logistics center. The user inputs the minutes of the meeting from a smartphone. For example, the following prompt sentences can be generated:

[1975] Example prompt sentence:

[1976] Minutes of the meeting:

[1977] 1. Check shipping status

[1978] 2. Improved inventory management

[1979] 3. Adjusting delivery schedules

[1980] Use the meeting minutes above to generate follow-up emails to all involved parties.

[1981] The server inputs this prompt into a generative AI model to automatically generate an appropriate follow-up email. The generated email is then checked for grammatical errors and compliance before finally being displayed on the user's smartphone. This improves the efficiency and reduces the time required for email creation at logistics centers.

[1982] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1983] Step 1:

[1984] Users input text data such as meeting minutes or daily reports from their smartphones or other devices. The input data is then sent to the server. Specifically, the user opens the smartphone application, inputs the contents of the minutes or daily reports in text format, and presses the send button.

[1985] Step 2:

[1986] The server analyzes the received text data and generates a prompt sentence suitable for the generative AI model. It processes the input data (minutes and daily reports) to construct an appropriate prompt sentence. Specifically, it analyzes the text data using natural language processing technology, extracts important points, and generates a prompt sentence.

[1987] Step 3:

[1988] The server inputs the generated prompt text into a generative AI model (e.g., GPT-3 (registered trademark) from OpenAI (registered trademark)) to automatically generate appropriate email content. Using the prompt text as input, the generative AI model generates the email body. Specifically, the server calls the API of the generative AI model, sends the prompt text, and retrieves the email content.

[1989] Step 4:

[1990] The server checks the generated email for grammatical errors and corrects them if necessary. Using the generated email as input, it uses a grammar checking tool (e.g., the Grammarly API) to detect and correct grammatical errors. Specifically, it sends the text of the generated email to the grammar checking tool and applies the suggested corrections it receives.

[1991] Step 5:

[1992] The server checks whether the generated email complies with laws, regulations, and the company's internal rules. The generated email is used as input to check compliance using a compliance check tool. Specifically, the content of the email is sent to the compliance check tool, and the evaluation result of compliance is obtained.

[1993] Step 6:

[1994] The server displays the final generated email on the smartphone application so that the user can check it. After corrections and checking are complete, the server sends the email to the user's smartphone as output. Specifically, the content of the email is displayed on the application interface so that the user can check and send it.

[1995] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1996] "Example 1"

[1997] In one embodiment of the present invention, a system is provided that includes an emotion engine that recognizes a user's emotions. The emotion engine analyzes the user's emotions from their tone of voice, facial expressions, and choice of words, and feeds the results back to the system. For example, if the user feels angry, the emotion engine communicates this information to the system, and the system takes this into account when generating a business email.

[1998] "Example 2"

[1999] In addition, the emotion engine adjusts the tone of automatically generated business emails based on the user's emotions. For example, if the user is happy, the tone of the generated email will be bright and positive. Conversely, if the user is sad, the tone of the generated email will be calm. This allows the recipient of the email to more accurately understand the sender's emotions.

[2000] "Example 3"

[2001] The emotion engine also adjusts the timing of email sending based on the user's emotions. For example, if the user feels angry, the emotion engine will communicate that information to the system, which will temporarily postpone sending the email. This allows the user time to calm down and prevents them from sending the wrong email based on emotional judgment.

[2002] The processing flow of each embodiment will be described below.

[2003] "Example 1"

[2004] Step 1: The user boots the system.

[2005] Step 2: The emotion engine analyzes the user's emotions based on their tone of voice, facial expressions, and choice of words.

[2006] Step 3: The emotion engine feeds the analysis results back to the system.

[2007] Step 4: The system takes your feedback into account and generates a business email.

[2008] "Example 2"

[2009] Step 1: The user boots the system.

[2010] Step 2: The emotion engine analyzes the user's emotions.

[2011] Step 3: The sentiment engine adjusts the tone of the email based on the analysis.

[2012] Step 4: The system generates a business email taking into account the adjusted tone.

[2013] "Example 3"

[2014] Step 1: The user boots the system.

[2015] Step 2: The emotion engine analyzes the user's emotions.

[2016] Step 3: The emotion engine adjusts the timing of email sending based on the analysis results.

[2017] Step 4: The system generates business emails taking into account the adjusted sending timing and sends them at the appropriate time.

[2018] Example 1

[2019] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[2020] Conventional business email generation systems generate emails without considering the user's emotions, often failing to reflect the appropriate tone or content. They also lack sufficient checks for grammatical errors and compliance violations, making quality assurance difficult. Furthermore, creating emails takes a lot of time, reducing work efficiency.

[2021] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[2022] In this invention, the server includes means for automatically generating business emails from short instructions, means for checking the generated business emails for grammatical errors, means for checking the generated business emails for compliance, means for analyzing the user's emotions, and means for generating business emails based on the analyzed emotions. This makes it possible to automatically generate business emails with an appropriate tone that reflects the user's emotions, and to efficiently create high-quality emails that are free of grammatical errors and compliance violations.

[2023] A "short command" is a brief command or request that a user enters into the system.

[2024] "Business email" refers to email sent for business purposes such as business communication and information sharing.

[2025] "Means for automatic generation" refers to functions or processes that automatically create business emails based on user in...

Claims

1. A means for automatically generating a business document from the instructions; A means for checking the generated business document for grammatical errors; A means for checking the generated business documents for compliance; A means for verifying that the generated business documents comply with business communication standards; and A means for checking whether appropriate honorific language is used in the generated business documents; A means for analyzing the generated business document using natural language processing technology; means for amending the business document based on the analysis results; A system including:

2. A means to automatically generate business emails from instructions; A means to check generated business emails for grammatical errors; A means of checking the compliance of generated business emails; A means of verifying that generated business emails comply with business communication standards; and A means to check whether appropriate honorific language is used in generated business emails, Including system.

3. A means to upload meeting minutes; A means for analyzing the uploaded minutes; A means for generating a prompt sentence based on the analysis result; A means for automatically generating a plurality of emails using the generated prompt text; a means for providing the generated email to a user; A system including:

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