system

Abstract

We provide the system. [Solution] An input method for receiving text, lists, and tables that need to be modified by the user, A text editing means for modifying text, lists, and tables entered by the aforementioned input means into a business document specification, Display means for displaying text, lists, and tables corrected by the text correction means to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a modern business environment, accurate and professional documents are essential. However, since not all business people have high document creation capabilities, a lot of time and effort are spent on document quality control. To solve this problem, there is a need for a system that efficiently corrects documents and formats them into a form that can be used in business. In the current system, manual correction is required, resulting in a lot of wasted time and effort. Also, it is difficult to maintain the consistency and quality of documents. Therefore, there is a need for a system that automatically corrects the text, lists, and tables input by the user to the business document specifications and provides high-quality documents quickly and efficiently.

Means for Solving the Problems

[0005] The present invention solves the above problems with a system that includes an input means for receiving text, lists, and tables that require correction entered by a user; a text correction means for correcting the text, lists, and tables entered by the input means to conform to business document specifications; and a display means for displaying the text, lists, and tables corrected by the text correction means to the user. Furthermore, by using a natural language processing algorithm to correct the entered text, lists, and tables, the text correction means can generate accurate and high-quality business documents without human intervention. In addition, since the text correction means is implemented by a program executed on a remote server, the load on the terminal can be reduced and the user experience can be improved. The display means displays the corrected text, lists, and tables on the terminal screen, allowing the user to immediately check the results. As a result, users can efficiently create business documents and improve the efficiency and quality of their work.

[0006] An "input means" is a device or interface for a user to input text, lists, or tables that need to be modified into the system.

[0007] A "text correction method" refers to an algorithm or program that automatically corrects text, lists, or tables entered via an input method to conform to business document specifications.

[0008] "Display means" refers to a device or interface used to visually provide users with text, lists, or tables that have been modified by the modification means.

[0009] A "natural language processing algorithm" is an algorithm that enables machines to understand, analyze, and generate human language, and in this invention, it is particularly used for text modification.

[0010] A "remote server" is a server that resides on the cloud or another network and processes requests from a terminal.

[0011] A "terminal" is an information processing device such as a computer, smartphone, or tablet that is operated by a user.

[0012] "Business document specifications" refer to the format and style of expression that are considered appropriate and professional in a business environment.

[0013] "Revision" means altering the original text, list, or table to an appropriate format or content. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results. Specifically, it includes input means, text modification means, and display means.

[0036] System Configuration

[0037] Input means

[0038] Users access the system using a terminal and input text, lists, or tables that need correction. Users input data using input forms or terminal prompts displayed on the terminal screen.

[0039] Text editing methods

[0040] The text correction mechanism receives input data sent from the terminal and performs corrections using a natural language processing algorithm. This correction is carried out by a program running on a remote server, which automatically converts the user's input into a format suitable for business document specifications.

[0041] Display means

[0042] The revised text, lists, and tables are sent back to the terminal and displayed to the user. The terminal displays the results on the screen, allowing the user to confirm the revisions.

[0043] Explanation of the program's processing

[0044] The following is a concrete example of the system's processing.

[0045] User actions

[0046] The user enters "I have received a proposal for a new project, are there any changes?" into the input form on their device. After entering the text, the user clicks the "Submit" button.

[0047] Terminal operation

[0048] The terminal receives user input and passes it to the program. The terminal program then creates an API request to send this text to a remote server.

[0049] Server Operations

[0050] The server processes requests received from the terminal and modifies the text using natural language processing algorithms. Specifically, it uses the API to generate and process requests like the following: "Please modify the following text so that it can be used in a business context: I have received a proposal for a new project, are there any changes I should make?"

[0051] The server generates the corrected text and sends it back to the terminal. For example, the server returns the following corrected text: "We have received your proposal for a new project. Please let us know if you have any changes."

[0052] Terminal display

[0053] The terminal displays the corrected text received from the server on the screen. The user can review it and make further modifications as needed, or use it as is.

[0054] Specific example

[0055] The present invention will be further explained using the following specific examples.

[0056] 1. User input: The user enters "The business meeting will be held on Friday."

[0057] 2. Terminal processing: The terminal sends this input to the server.

[0058] 3. Server processing: The server corrects the sentence to "The business meeting will be held on Friday."

[0059] 4. Display on the device: The corrected text will be displayed on the device.

[0060] As described above, the present invention enables users to easily and quickly create high-quality business documents.

[0061] The following describes the processing flow.

[0062] Step 1:

[0063] The user enters the text, list, or table that needs correction into the input form on their device and clicks the submit button.

[0064] Step 2:

[0065] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[0066] Step 3:

[0067] The device sends an API request to the remote server. The request includes text, lists, and tables that need to be modified.

[0068] Step 4:

[0069] The server analyzes the request received from the terminal and extracts the text contained in the request. Next, it begins correcting the text using a natural language processing algorithm.

[0070] Step 5:

[0071] The server uses a natural language processing algorithm to modify the extracted text to conform to business document specifications. For example, it modifies the text "The business meeting will be held on Friday." to "The business meeting will be held on Friday."

[0072] Step 6:

[0073] The server returns the corrected text to the terminal as an API response. The response includes the corrected text, lists, and tables.

[0074] Step 7:

[0075] The terminal analyzes the response received from the server and retrieves the corrected text. Next, it displays the corrected text to the user.

[0076] Step 8:

[0077] The user reviews the revised text, lists, and tables displayed on the device screen and decides whether to make further revisions as needed or to use them as they are.

[0078] The above describes the specific processing steps for users to modify text, lists, and tables that require correction using a terminal, conforming them to business document specifications. In this way, the present invention supports the efficient and rapid creation of high-quality business documents.

[0079] (Example 1)

[0080] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0081] Creating business documents is a time-consuming task because it requires strict adherence to format and appropriate expression. In particular, revising text, lists, and tables necessitates repeated checks and corrections due to differences in wording and expression. Such work reduces efficiency and hinders quick and accurate business communication. Therefore, there is a need for a system that automatically corrects user-entered text into a format suitable for business documents and displays it quickly.

[0082] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0083] In this invention, the server includes an input means for receiving text that needs to be corrected, entered by a user; a text correction means for correcting the text entered by the input means to conform to business document specifications; and a display means for displaying the text corrected by the text correction means to the user. This makes it possible for users to quickly create high-quality business documents without any effort.

[0084] An "input method" refers to a device or interface for a user to input text.

[0085] A "text correction method" refers to an algorithm or program for correcting input text to a predetermined specification.

[0086] "Display means" refers to a device or interface for visually presenting the modified text to the user.

[0087] "Natural language processing algorithms" refer to technologies that use methods and techniques to process human language using computers.

[0088] A "remote server" is a server located in a remote location that can be accessed via a network.

[0089] An "API request" is a request made to communicate with other software or services in order to use their functions or retrieve data.

[0090] A "generative AI model" is an artificial intelligence model that learns from large amounts of data and generates responses to specific tasks.

[0091] A "prompt" is a specific question or instruction that is input into a generative AI model.

[0092] This invention is a system that modifies text entered by a user according to business document specifications and displays the modified result. The following describes in detail how this system is implemented.

[0093] System Configuration

[0094] This system consists of three main parts: an input means, a text modification means, and a display means.

[0095] Input means

[0096] Users access the system using their own devices and input text that needs correction. Input methods include input forms displayed on the device screen and terminal prompts. This allows users to input information with simple operations. For example, a user might input, "I have received a proposal for a new project, are there any changes I should make?"

[0097] Text editing methods

[0098] The text correction mechanism receives input data sent from the terminal and uses a natural language processing algorithm to correct the text to conform to business document specifications. This process is implemented by a program running on a remote server. A generative AI model is used to automatically convert user input into a format suitable for business documents. Specifically, the server processes the input using prompts such as the following:

[0099] "Please revise the following sentence to make it suitable for business use: 'I have received a proposal for a new project; are there any changes I would like to make?'"

[0100] Display means

[0101] The corrected text is sent back to the device and displayed on the user's screen. The user can then review the changes and make further modifications as needed, or use it as is.

[0102] Specific example

[0103] The embodiments of the present invention will be further clarified by describing specific examples below.

[0104] 1. User input:

[0105] The user enters "The business meeting will be held on Friday." into the input form on their device and clicks the "Submit" button.

[0106] 2. Terminal processing:

[0107] The terminal retrieves user input and creates an API request to send it to the server.

[0108] 3. Server processing:

[0109] The server receives the API request sent from the terminal and uses a natural language processing algorithm to correct the sentence "The business meeting will be held on Friday." to "The business meeting will be held on Friday."

[0110] 4. Displaying the correction results:

[0111] The server sends the corrected text back to the terminal, which displays the corrected version on the user's screen. The user can then review the corrected text and either make further revisions or use it as is.

[0112] This will allow users to quickly create high-quality business documents without hassle. This system will lead to more efficient and effective business communication.

[0113] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0114] Step 1:

[0115] The user enters text.

[0116] The user enters text that needs correction into an input form on their device. For example, they might enter, "I have received a proposal for a new project, are there any changes I need to make?" The input here is text data, and the device receives this text data.

[0117] Step 2:

[0118] The device creates an API request to send input data.

[0119] The terminal receives text data entered by the user and creates an API request to send it to a remote server. Specifically, it includes the entered text in the API request and sends a processing request to the server.

[0120] Step 3:

[0121] The device sends an API request to the server.

[0122] The terminal sends the created API request to the remote server. At this time, the input data remains in text format and includes a prompt message that reads, "Please revise the following text to make it suitable for business use: We have received a proposal for a new project, are there any changes you would like to make?"

[0123] Step 4:

[0124] The server receives the API request and parses the data.

[0125] The server receives API requests sent from the terminal. The received data includes text entered by the user, which the server parses and begins processing for correction.

[0126] Step 5:

[0127] The server executes a natural language processing algorithm.

[0128] The server executes a natural language processing algorithm based on the received text data. Using a generative AI model, it modifies the input text to conform to business document specifications. Specifically, it converts the input text "I have received a proposal for a new project, are there any changes?" to "I have received a proposal for a new project. Please let me know if there are any changes."

[0129] Step 6:

[0130] The server generates the corrected text.

[0131] The text is corrected using a natural language processing algorithm. The generated text is displayed on the server as new data and used for further processing.

[0132] Step 7:

[0133] The server sends the corrected text to the terminal.

[0134] The server returns the corrected text data to the device. The data sent to the device as an API response includes the corrected text.

[0135] Step 8:

[0136] The device receives the correction results.

[0137] The terminal receives the modified text sent from the server. At this time, the terminal analyzes the received data and uses it for the next processing step.

[0138] Step 9:

[0139] The device displays the corrected text to the user.

[0140] The user's device displays the received, corrected text on the screen. The user can review the displayed corrected text and make further corrections if necessary, or use it as is.

[0141] This allows users to efficiently create and modify business documents through a series of processing flows.

[0142] (Application Example 1)

[0143] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0144] In modern factories, communication between the factory floor and management departments is often inefficient. Specifically, reports and messages submitted by factory workers are often informal, making it difficult for management to quickly understand and utilize them for decision-making. Furthermore, the process of generating and promptly sending reports in the appropriate format is often complex and time-consuming. Therefore, there is a need for more efficient communication and faster report creation.

[0145] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0146] In this invention, the server includes an input means for receiving text or data that needs to be corrected, entered by a user; a text correction means for correcting the text or data entered by the input means to conform to business document specifications; a display means for displaying the text or data corrected by the text correction means to the user; and a transmission means for converting the corrected text or data into a report in an appropriate format and sending it to a specific person in charge. This enables reports and messages from the field to be quickly and accurately converted to business document specifications, allowing for appropriate reporting to the management department.

[0147] An "input method" is a means by which a user enters text or data that needs to be corrected into the system.

[0148] A "text correction method" is a method that uses natural language processing algorithms to correct input text or data to conform to business document specifications.

[0149] "Display means" refers to means for displaying text or data that has been modified by text modification means to the user.

[0150] "Transmission method" refers to the means of converting the revised text or data into a report in the appropriate format and sending it to a specific person.

[0151] A "natural language processing algorithm" is an algorithm used to modify input text to conform to business document specifications.

[0152] A "remote server" is a server where text correction is performed, receiving user input and performing natural language processing, and is located in a remote location.

[0153] This invention is a system for streamlining communication and report creation within a factory. The following describes the configurations for implementing this system.

[0154] System Configuration

[0155] The system consists of an input means for receiving texts and data that need correction entered by the user, a text correction means for correcting the entered texts and data to conform to business document specifications, a display means for displaying the corrected texts and data to the user, and a transmission means for converting the corrected texts and data into a report in an appropriate format and sending it to a specific person in charge.

[0156] Hardware and software to be used

[0157] Hardware: Smartphones, remote servers

[0158] Software: Natural language processing algorithms, programs that execute API requests.

[0159] Description of each means

[0160] 1. Input method

[0161] Users use their smartphones to input text or data that needs correction to the system. For example, a field worker might input, "The installation of the new part is complete, but there are problems with its operation."

[0162] 2. Text modification methods

[0163] The terminal receives user input and sends it to a remote server using an API request. The remote server has a natural language processing algorithm implemented to automatically correct the input sentences and data to conform to business document specifications. For example, a prompt message such as "Please correct the following sentence to conform to business document specifications: The installation of the new component is complete, but there are problems with its operation verification" might be used.

[0164] 3. Display means

[0165] The corrected text and data are sent back to the smartphone from the remote server, allowing the user to review the changes. For example, the corrected text might read, "The installation of the new component was completed, but there were problems with its operation. Please check for further action."

[0166] 4. Transmission method

[0167] The corrected text and data are converted into a report in the appropriate format and automatically sent to the designated person or supervisor. For example, a report might be generated with the following content: "Corrected message: Installation of the new component was completed, but there were problems with its operation. Please check on the next steps."

[0168] This allows field reports and messages to be quickly and accurately converted into business document specifications, enabling appropriate reporting to management.

[0169] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0170] Step 1:

[0171] The user uses their smartphone to input text or data that needs correction to the system. For example, they might input, "The installation of the new component is complete, but there are problems with its operation." This input is then sent to the system via the input device.

[0172] Step 2:

[0173] The terminal receives user input, converts the input data into JSON format, and sends it to the remote server as an API request. The input data at this time is the text message: "Installation of the new component is complete, but there are problems with the operation verification."

[0174] Step 3:

[0175] The server receives API requests sent from the terminal and invokes a natural language processing algorithm. The server uses a generative AI model based on the input data to modify the input sentence into a business document specification. This data processing includes parsing the input sentence and appropriately correcting its grammar and vocabulary. For example, it generates a prompt sentence, "Please modify the following sentence into a business document specification: The installation of the new component is complete, but there are problems with its operation verification," and passes it to the algorithm.

[0176] Step 4:

[0177] The server retrieves the corrected sentence using a natural language processing algorithm. The corrected sentence will look something like, "The installation of the new component is complete, but there were problems with its operation. Please check for further action." The server then sends this corrected data back to the terminal.

[0178] Step 5:

[0179] The terminal displays the corrected message received from the server to the user. The user checks the changes on their smartphone screen. For example, the screen might display: "Corrected message: Installation of the new component is complete, but there were problems with its operation. Please check for further action."

[0180] Step 6:

[0181] The system converts the modified text and data into a report in the appropriate format. For example, it might embed the modified text into a fixed report template.

[0182] Step 7:

[0183] Finally, the revised report is automatically sent to the designated person or supervisor. Depending on the sending method, the generated report may be sent via email or other communication tools.

[0184] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0185] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results in a manner that takes the user's emotions into consideration. Specifically, it includes input means, text modification means, emotion recognition engine, and display means.

[0186] System Configuration

[0187] Input means

[0188] Users access the system using a terminal and input text, lists, or tables that need correction. Users input data using input forms or terminal prompts displayed on the terminal screen.

[0189] Text editing methods

[0190] The text correction mechanism receives input data sent from the terminal and performs corrections using a natural language processing algorithm. This correction is carried out by a program running on a remote server, which automatically converts the user's input into a format suitable for business document specifications.

[0191] Emotion recognition engine

[0192] The emotion recognition engine analyzes emotions based on the text, lists, and tables entered by the user. The engine analyzes the user's emotions from the input data and provides the results to the text editing system. This allows the system to make revisions that take the user's emotions into consideration.

[0193] Display means

[0194] The revised text, lists, and tables are sent back to the terminal and displayed to the user. The terminal displays the results on the screen, allowing the user to confirm the revisions.

[0195] Explanation of the program's processing

[0196] The following is a concrete example of the system's processing.

[0197] User actions

[0198] The user enters "I have received a proposal for a new project, are there any changes?" into the input form on their device. After entering the text, the user clicks the "Submit" button.

[0199] Terminal operation

[0200] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[0201] Server Operations

[0202] The server analyzes the request received from the terminal and extracts the text contained in the request. Next, it uses an emotion recognition engine to obtain the emotion information necessary for correcting the text. If the user's emotion is "anxiety," this information is used and provided to the text correction mechanism.

[0203] Processing of text modification means

[0204] The server uses a natural language processing algorithm to modify the extracted text to conform to business document specifications. During this process, it adjusts the modifications based on sentiment information provided by the sentiment recognition engine. For example, the text "The business meeting will be held on Friday." might be changed to "Please rest assured that the business meeting will be held on Friday."

[0205] Server response

[0206] The server returns the corrected text to the terminal as an API response. The response includes the corrected text, lists, and tables.

[0207] Terminal display

[0208] The terminal analyzes the response received from the server and retrieves the corrected text. Next, it displays the corrected text to the user.

[0209] User verification

[0210] The user reviews the revised text, lists, and tables displayed on the device screen and decides whether to make further revisions as needed or to use them as they are.

[0211] Specific example

[0212] The present invention will be further explained using the following specific examples.

[0213] 1. User input: The user enters "The business meeting will be held on Friday."

[0214] 2. Terminal processing: The terminal sends this input to the server.

[0215] 3. Analysis of the emotion recognition engine: The emotion recognition engine detects that the user is feeling "fatigue".

[0216] 4. Processing of text correction: The server corrects the text to "The business meeting will be held on Friday, so please take appropriate breaks to avoid fatigue."

[0217] 5. Display on the device: The corrected text will be displayed on the device.

[0218] As described above, the present invention enables users to easily and quickly create high-quality business documents, and further provides a service that takes into consideration the user's feelings.

[0219] The following describes the processing flow.

[0220] Step 1:

[0221] The user enters the text, list, or table that needs correction into the input form on their device and clicks the submit button.

[0222] Step 2:

[0223] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[0224] Step 3:

[0225] The device sends an API request to the remote server. The request includes text, lists, or tables that need to be modified.

[0226] Step 4:

[0227] The server parses the request received from the terminal and extracts the text contained in the request. At this stage, the server recognizes that the user has typed, "I have received a proposal for a new project, are there any changes?"

[0228] Step 5:

[0229] The server uses an emotion recognition engine to analyze the user's emotions from the input text. For example, it might analyze that the user is feeling "anxious."

[0230] Step 6:

[0231] The server provides the emotion analysis results (e.g., "anxiety") received from the emotion recognition engine to the text correction means.

[0232] Step 7:

[0233] The server uses natural language processing algorithms to modify text while taking sentiment into account. For example, if the user's sentiment is "anxious," the message "You have received a proposal for a new project, are there any changes?" is changed to "You have received a proposal for a new project. Please let us know if there are any changes, and please rest assured."

[0234] Step 8:

[0235] The server returns the corrected text to the device as an API response. The response includes the corrected text, lists, and tables.

[0236] Step 9:

[0237] The terminal analyzes the response received from the server and retrieves the corrected text. Next, the corrected text is displayed to the user.

[0238] Step 10:

[0239] The user reviews the revised text, lists, and tables displayed on their device screen and decides whether to make further revisions as needed or to use them as they are.

[0240] The above describes the specific processing steps for a user to modify text, lists, and tables that require correction using a terminal, conforming them to business document specifications, and displaying the corrected results in a manner that takes the user's feelings into consideration. In this way, the present invention supports the efficient and rapid creation of high-quality business documents and enables more personalized document delivery by considering the user's feelings.

[0241] (Example 2)

[0242] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0243] Traditional text editing systems provide the functionality to modify text, lists, and tables to conform to business document specifications, but they have a problem in that they cannot adequately consider the user's emotions. User input often contains specific emotions, and ignoring these makes it difficult to accurately convey the user's intent. Therefore, it is necessary to edit text while taking emotions into consideration.

[0244] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0245] In this invention, the server includes an input means for receiving text, lists, and tables that require modification entered by the user; an emotion recognition means for analyzing emotional information contained in the text, lists, and tables entered by the input means; a text modification means for modifying the entered text, lists, and tables based on the emotional information analyzed by the emotion recognition means; and a display means for displaying the text, lists, and tables modified by the text modification means to the user. This makes it possible to modify text in a manner suitable for business document specifications while appropriately considering the user's emotions.

[0246] An "input method" is a means by which a user inputs text, lists, or tables that need to be modified into the system.

[0247] An "emotion recognition tool" is a means for analyzing and extracting emotional information contained in input text, lists, or tables.

[0248] A "text correction method" is a means of correcting input text, lists, and tables into a format suitable for business document specifications, based on emotional information analyzed by an emotion recognition method.

[0249] "Display means" refers to the means of displaying the revised text, list, or table to the user.

[0250] A "generated artificial intelligence model" is an artificial intelligence model used to modify text, and it includes natural language processing algorithms.

[0251] A "remote server" is a server that can be accessed from a remote location via a network, and is where the programs for emotion recognition and text modification are executed.

[0252] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results in a manner that takes the user's emotions into consideration. Specifically, it includes input means, emotion recognition means, text modification means, and display means.

[0253] System Configuration

[0254] Input means

[0255] Users access the system using a terminal and input text, lists, or tables that need correction. Users input using input forms or terminal prompts displayed on the terminal screen. For example, a user might input the sentence, "Could you please provide an update on the project's progress?"

[0256] emotion recognition means

[0257] The server analyzes the emotional information contained in the input text using emotion recognition means. The emotion recognition engine used here can utilize existing services such as IBM Watson® or Microsoft® Azure® Text Analytics. For example, it can detect "anxiety" from the input text.

[0258] Text editing methods

[0259] The server uses natural language processing algorithms to modify input text into business document specifications. This process utilizes generated AI models (e.g., GPT-3® or BERT). It also considers sentiment information provided by sentiment recognition systems to revise the wording to be more appropriate. For example, the question "What is the project's progress?" is changed to "It would be helpful if you could provide an update on the project's progress."

[0260] Display means

[0261] The revised text is sent back to the device and displayed to the user. The device displays the result on the screen, allowing the user to confirm the changes.

[0262] Specific examples of how the program works

[0263] 1. User input: The user enters "The business meeting will be held on Friday."

[0264] 2. Terminal processing: The terminal sends this input to the server.

[0265] 3. Analysis of the emotion recognition engine: The emotion recognition engine detects that the user is feeling "fatigue".

[0266] 4. Processing of text correction: The server corrects the text to "The business meeting will be held on Friday, so please take appropriate breaks to avoid fatigue."

[0267] 5. Display on the device: The corrected text will be displayed on the device.

[0268] Example of a prompt

[0269] The following are examples of specific prompt statements for a generative AI model:

[0270] Prompt message:

[0271] Please revise the following text to conform to business document standards and to be more considerate of the user's feelings.

[0272] Input text: What is the progress of the project?

[0273] Emotion: Anxiety

[0274] Revised version:

[0275] It would be helpful if you could keep us updated on the project's progress.

[0276] As described above, the present invention enables users to easily and quickly create high-quality business documents, and further provides a service that takes into consideration the user's feelings.

[0277] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0278] Step 1:

[0279] The user accesses the system and enters text, lists, or tables that need correction into the input form on the terminal. For example, they might enter "What is the project's progress?". After entering the text, they click the "Submit" button. This action sends the user's input to the terminal.

[0280] Step 2:

[0281] The terminal receives the user's input and stores the text in a local variable. Next, it prepares to convert the input data into an API request format such as JSON format and send it to the remote server. The input here is the text from the user, and the output is the data in the API request format.

[0282] Step 3:

[0283] The terminal sends the formatted API request to the remote server. Specifically, it sends the data as an HTTP POST request. The input for this step is the data in JSON format, and the output is the request sent through the network.

[0284] Step 4:

[0285] The server analyzes the API request received from the terminal and extracts the text data within the request. This extracted data is passed to the next analysis step. The input is the received request data, and the output is the extracted text data.

[0286] Step 5:

[0287] The server uses a sentiment recognition engine to analyze sentiment information from the extracted text data. Sentiment recognition engines here include IBM Watson and Microsoft Azure Text Analytics, etc. Through this analysis, it is detected that the user's sentiment is "uneasy". The input is the text data, and the output is the sentiment information as the analysis result.

[0288] Step 6:

[0289] The server uses a natural language processing algorithm to modify text to conform to business document specifications that reflect sentiment information. Specifically, it uses a generated AI model (e.g., GPT-3) to modify the sentence "What is the project's progress?" to "It would be helpful if you could provide an update on the project's progress." The input is the sentiment information and the original text, and the output is the modified text.

[0290] Step 7:

[0291] The server returns the corrected text to the terminal as an API response. The response data is then formatted again, for example, into JSON format. The input is the corrected text, and the output is the API response returned to the terminal.

[0292] Step 8:

[0293] The terminal analyzes the response received from the server and retrieves the corrected text. Next, this text is displayed on the screen, presenting the result to the user. The input is the API response data, and the output is the corrected text displayed on the screen.

[0294] Step 9:

[0295] The user reviews the revised text, lists, and tables displayed on the terminal screen and decides whether to make further revisions as needed or use them as they are. The input is the displayed result, and the output is the text approved by the user or further revised.

[0296] (Application Example 2)

[0297] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0298] Conventional document editing systems provide the functionality to modify user-inputted text, lists, and tables to conform to business document specifications, but they are insufficient in terms of making revisions that take into account the emotions of the user and the target audience. Furthermore, in certain fields such as the advertising industry, there is a demand not only for documents to conform to business document specifications, but also for documents that are optimized and appropriately consider the emotions of the target audience.

[0299] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for receiving text, lists, and tables that require modification entered by the user; a text modification means for modifying the text, lists, and tables entered by the input means to conform to business document specifications; and a display means for displaying the results of the text, lists, and tables modified by the text modification means in an emotionally sensitive manner to the target audience. This makes it possible to automatically generate business documents and advertisements that take into account the emotions of the target audience, and to provide influential and effective text.

[0300] A "user" is the entity that uses the system to input and modify text, lists, tables, etc.

[0301] "Input method" refers to the interface that allows users to input text, lists, or tables that need to be modified into the system.

[0302] "Text correction means" refers to the part that has the function of automatically correcting text, lists, and tables entered by the input means to conform to business document specifications.

[0303] "Business document specifications" refer to standards for documents that are appropriate for business settings and have a well-structured format and content.

[0304] An "emotion recognition engine" is a technology that analyzes and extracts the emotions of users and target audiences from input text, lists, and tables.

[0305] The "display means" refers to an interface for displaying the revised text, list, or table to the user or target audience.

[0306] The "target audience" is the recipient of the content of advertising texts and business documents.

[0307] The "natural language processing algorithm" is a technology for a computer to understand and process human language.

[0308] The "remote server" is a remote computer that is accessed via the Internet and executes the main processing of the system.

[0309] "Optimization" refers to the process of modifying the text, list, or table so as to be most effective while taking into account the feelings of the target audience.

[0310] The present invention relates to a system for automatically correcting and optimizing business documents such as advertising texts, and particularly to a system that can provide a more effective document by processing user input in consideration of the feelings of the target audience. The system operates in a flow where the user inputs a text, list, or table for which correction and optimization are desired, and it is appropriately corrected and then displayed.

[0311] Configuration of the System

[0312] 1. Overview

[0313] The system is composed of an input means, a text correction means, an emotion recognition engine, and a display means. The data input by the user is processed by these means, and an optimized document is generated.

[0314] 2. Hardware and Software to be Used

[0315] Hardware: Smartphone (iOS or Android®)

[0316] software:

[0317] Frontend: React Native

[0318] Backend: Flask

[0319] Natural Language Processing Library: Hugging Face's Transformers, OpenAI's GPT-3

[0320] Data processing and calculations

[0321] 1. User input

[0322] Users input advertising copy and business documents using a smartphone application. This input uses an input form built with React Native.

[0323] 2. Emotion analysis

[0324] Input data is sent to the backend server. The input data from the frontend is sent to the Flask server as an API request, and sentiment analysis is performed using Hugging Face's Transformers. The analysis results show what emotions the target audience is most likely to have.

[0325] 3. Text correction

[0326] Based on the analysis results, the server uses OpenAI's GPT-3 to optimize the text in a way that takes the target audience's emotions into consideration. This transforms the user's input into effective ad copy and business documents.

[0327] 4.Display

[0328] Once the optimized document is generated, it is sent back from the backend server to the frontend and finally displayed on the user's smartphone. This allows the user to review the revised and optimized document content.

[0329] Specific example

[0330] Consider a scenario where an advertising agency representative tries to optimize the ad copy for a new product, "This TV is very high quality and inexpensive," to suit their target audience. The representative enters this text into an app and submits it. The server analyzes it using an emotion recognition engine and extracts the emotion "positive." Subsequently, an optimized ad copy is generated using GPT-3: "This TV will provide a great viewing experience. Take advantage of this opportunity and purchase it."

[0331] Examples of prompt statements

[0332] "Optimize the following ad copy to make it resonate positively with your target audience: This TV is very high quality and inexpensive."

[0333] As described above, the system of the present invention can optimize user input data based on the sentiment of the target audience and generate effective business documents.

[0334] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0335] Step 1:

[0336] Users input ad copy or business documents that need correction using a smartphone application. They enter the ad copy into the text box on their smartphone and press the submit button. This input data is stored in a local variable on the device.

[0337] Step 2:

[0338] The device prepares to send the data entered by the user to a remote server. This transmission uses an API request, and the entered text data is sent to the server-side endpoint. The input data includes the ad text entered by the user.

[0339] Step 3:

[0340] The server parses the API request received from the terminal and extracts the text data within the request. The input data received by the server is passed to the emotion recognition engine, where emotion analysis is performed. The emotion recognition engine (Hugging Face's Transformers) is used to analyze the emotion of the text and obtain the result. For example, an emotion such as "positive" might be extracted from the input text as the analysis result.

[0341] Step 4:

[0342] Based on the sentiment analysis results, the server uses a natural language processing engine (OpenAI's GPT-3) to generate prompts for modifying and optimizing the input ad copy in a sentiment-conscious manner. A prompt might look like this: "Optimize the following ad copy so that the target audience feels positive: This TV is very high quality and inexpensive." Using these prompts, GPT-3 generates the optimized ad copy.

[0343] Step 5:

[0344] The optimized ad copy generated by the server is sent to the device as an API response. The output data here is the modified and optimized ad copy.

[0345] Step 6:

[0346] The device analyzes the received API response and extracts optimized ad copy. The extracted optimized ad copy is then displayed to the user. The user can review the displayed optimized ad copy and either make further modifications as needed or use it as is.

[0347] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0348] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0349] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0350] [Second Embodiment]

[0351] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0352] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0353] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0354] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0355] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0356] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0357] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0358] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0359] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0360] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0361] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0362] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0363] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results. Specifically, it includes input means, text modification means, and display means.

[0364] System Configuration

[0365] Input means

[0366] Users access the system using a terminal and input text, lists, or tables that need correction. Users input data using input forms or terminal prompts displayed on the terminal screen.

[0367] Text editing methods

[0368] The text correction mechanism receives input data sent from the terminal and performs corrections using a natural language processing algorithm. This correction is carried out by a program running on a remote server, which automatically converts the user's input into a format suitable for business document specifications.

[0369] Display means

[0370] The revised text, lists, and tables are sent back to the terminal and displayed to the user. The terminal displays the results on the screen, allowing the user to confirm the revisions.

[0371] Explanation of the program's processing

[0372] The following is a concrete example of the system's processing.

[0373] User actions

[0374] The user enters "I have received a proposal for a new project, are there any changes?" into the input form on their device. After entering the text, the user clicks the "Submit" button.

[0375] Terminal operation

[0376] The terminal receives user input and passes it to the program. The terminal program then creates an API request to send this text to a remote server.

[0377] Server Operations

[0378] The server processes requests received from the terminal and modifies the text using natural language processing algorithms. Specifically, it uses the API to generate and process requests like the following: "Please modify the following text so that it can be used in a business context: I have received a proposal for a new project, are there any changes I should make?"

[0379] The server generates the corrected text and sends it back to the terminal. For example, the server returns the following corrected text: "We have received your proposal for a new project. Please let us know if you have any changes."

[0380] Terminal display

[0381] The terminal displays the corrected text received from the server on the screen. The user can review it and make further modifications as needed, or use it as is.

[0382] Specific example

[0383] The present invention will be further explained using the following specific examples.

[0384] 1. User input: The user enters "The business meeting will be held on Friday."

[0385] 2. Terminal processing: The terminal sends this input to the server.

[0386] 3. Server processing: The server corrects the sentence to "The business meeting will be held on Friday."

[0387] 4. Display on the device: The corrected text will be displayed on the device.

[0388] As described above, the present invention enables users to easily and quickly create high-quality business documents.

[0389] The following describes the processing flow.

[0390] Step 1:

[0391] The user enters the text, list, or table that needs correction into the input form on their device and clicks the submit button.

[0392] Step 2:

[0393] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[0394] Step 3:

[0395] The device sends an API request to the remote server. The request includes text, lists, and tables that need to be modified.

[0396] Step 4:

[0397] The server analyzes the request received from the terminal and extracts the text contained in the request. Next, it begins correcting the text using a natural language processing algorithm.

[0398] Step 5:

[0399] The server uses a natural language processing algorithm to modify the extracted text to conform to business document specifications. For example, it modifies the text "The business meeting will be held on Friday." to "The business meeting will be held on Friday."

[0400] Step 6:

[0401] The server returns the corrected text to the terminal as an API response. The response includes the corrected text, lists, and tables.

[0402] Step 7:

[0403] The terminal analyzes the response received from the server and retrieves the corrected text. Next, it displays the corrected text to the user.

[0404] Step 8:

[0405] The user reviews the revised text, lists, and tables displayed on the device screen and decides whether to make further revisions as needed or to use them as they are.

[0406] The above describes the specific processing steps for users to modify text, lists, and tables that require correction using a terminal, conforming them to business document specifications. In this way, the present invention supports the efficient and rapid creation of high-quality business documents.

[0407] (Example 1)

[0408] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0409] Creating business documents is a time-consuming task because it requires strict adherence to format and appropriate expression. In particular, revising text, lists, and tables necessitates repeated checks and corrections due to differences in wording and expression. Such work reduces efficiency and hinders quick and accurate business communication. Therefore, there is a need for a system that automatically corrects user-entered text into a format suitable for business documents and displays it quickly.

[0410] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0411] In this invention, the server includes an input means for receiving text that needs to be corrected, entered by a user; a text correction means for correcting the text entered by the input means to conform to business document specifications; and a display means for displaying the text corrected by the text correction means to the user. This makes it possible for users to quickly create high-quality business documents without any effort.

[0412] An "input method" refers to a device or interface for a user to input text.

[0413] A "text correction method" refers to an algorithm or program for correcting input text to a predetermined specification.

[0414] "Display means" refers to a device or interface for visually presenting the modified text to the user.

[0415] "Natural language processing algorithms" refer to technologies that use methods and techniques to process human language using computers.

[0416] A "remote server" is a server located in a remote location that can be accessed via a network.

[0417] An "API request" is a request made to communicate with other software or services in order to use their functions or retrieve data.

[0418] A "generative AI model" is an artificial intelligence model that learns from large amounts of data and generates responses to specific tasks.

[0419] A "prompt" is a specific question or instruction that is input into a generative AI model.

[0420] This invention is a system that modifies text entered by a user according to business document specifications and displays the modified result. The following describes in detail how this system is implemented.

[0421] System Configuration

[0422] This system consists of three main parts: an input means, a text modification means, and a display means.

[0423] Input means

[0424] Users access the system using their own devices and input text that needs correction. Input methods include input forms displayed on the device screen and terminal prompts. This allows users to input information with simple operations. For example, a user might input, "I have received a proposal for a new project, are there any changes I should make?"

[0425] Text editing methods

[0426] The text correction mechanism receives input data sent from the terminal and uses a natural language processing algorithm to correct the text to conform to business document specifications. This process is implemented by a program running on a remote server. A generative AI model is used to automatically convert user input into a format suitable for business documents. Specifically, the server processes the input using prompts such as the following:

[0427] "Please revise the following sentence to make it suitable for business use: 'I have received a proposal for a new project; are there any changes I would like to make?'"

[0428] Display means

[0429] The corrected text is sent back to the device and displayed on the user's screen. The user can then review the changes and make further modifications as needed, or use it as is.

[0430] Specific example

[0431] The embodiments of the present invention will be further clarified by describing specific examples below.

[0432] 1. User input:

[0433] The user enters "The business meeting will be held on Friday." into the input form on their device and clicks the "Submit" button.

[0434] 2. Terminal processing:

[0435] The terminal retrieves user input and creates an API request to send it to the server.

[0436] 3. Server processing:

[0437] The server receives the API request sent from the terminal and uses a natural language processing algorithm to correct the sentence "The business meeting will be held on Friday." to "The business meeting will be held on Friday."

[0438] 4. Displaying the correction results:

[0439] The server sends the corrected text back to the terminal, which displays the corrected version on the user's screen. The user can then review the corrected text and either make further revisions or use it as is.

[0440] This will allow users to quickly create high-quality business documents without hassle. This system will lead to more efficient and effective business communication.

[0441] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0442] Step 1:

[0443] The user enters text.

[0444] The user enters text that needs correction into an input form on their device. For example, they might enter, "I have received a proposal for a new project, are there any changes I need to make?" The input here is text data, and the device receives this text data.

[0445] Step 2:

[0446] The device creates an API request to send input data.

[0447] The terminal receives text data entered by the user and creates an API request to send it to a remote server. Specifically, it includes the entered text in the API request and sends a processing request to the server.

[0448] Step 3:

[0449] The device sends an API request to the server.

[0450] The terminal sends the created API request to the remote server. At this time, the input data remains in text format and includes a prompt message that reads, "Please revise the following text to make it suitable for business use: We have received a proposal for a new project, are there any changes you would like to make?"

[0451] Step 4:

[0452] The server receives the API request and parses the data.

[0453] The server receives API requests sent from the terminal. The received data includes text entered by the user, which the server parses and begins processing for correction.

[0454] Step 5:

[0455] The server executes a natural language processing algorithm.

[0456] The server executes a natural language processing algorithm based on the received text data. Using a generative AI model, it modifies the input text to conform to business document specifications. Specifically, it converts the input text "I have received a proposal for a new project, are there any changes?" to "I have received a proposal for a new project. Please let me know if there are any changes."

[0457] Step 6:

[0458] The server generates the corrected text.

[0459] The text is corrected using a natural language processing algorithm. The generated text is displayed on the server as new data and used for further processing.

[0460] Step 7:

[0461] The server sends the corrected text to the terminal.

[0462] The server returns the corrected text data to the device. The data sent to the device as an API response includes the corrected text.

[0463] Step 8:

[0464] The device receives the correction results.

[0465] The terminal receives the modified text sent from the server. At this time, the terminal analyzes the received data and uses it for the next processing step.

[0466] Step 9:

[0467] The device displays the corrected text to the user.

[0468] The user's device displays the received, corrected text on the screen. The user can review the displayed corrected text and make further corrections if necessary, or use it as is.

[0469] This allows users to efficiently create and modify business documents through a series of processing flows.

[0470] (Application Example 1)

[0471] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0472] In modern factories, communication between the factory floor and management departments is often inefficient. Specifically, reports and messages submitted by factory workers are often informal, making it difficult for management to quickly understand and utilize them for decision-making. Furthermore, the process of generating and promptly sending reports in the appropriate format is often complex and time-consuming. Therefore, there is a need for more efficient communication and faster report creation.

[0473] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0474] In this invention, the server includes an input means for receiving text or data that needs to be corrected, entered by a user; a text correction means for correcting the text or data entered by the input means to conform to business document specifications; a display means for displaying the text or data corrected by the text correction means to the user; and a transmission means for converting the corrected text or data into a report in an appropriate format and sending it to a specific person in charge. This enables reports and messages from the field to be quickly and accurately converted to business document specifications, allowing for appropriate reporting to the management department.

[0475] An "input method" is a means by which a user enters text or data that needs to be corrected into the system.

[0476] A "text correction method" is a method that uses natural language processing algorithms to correct input text or data to conform to business document specifications.

[0477] "Display means" refers to means for displaying text or data that has been modified by text modification means to the user.

[0478] "Transmission method" refers to the means of converting the revised text or data into a report in the appropriate format and sending it to a specific person.

[0479] A "natural language processing algorithm" is an algorithm used to modify input text to conform to business document specifications.

[0480] A "remote server" is a server where text correction is performed, receiving user input and performing natural language processing, and is located in a remote location.

[0481] This invention is a system for streamlining communication and report creation within a factory. The following describes the configurations for implementing this system.

[0482] System Configuration

[0483] The system consists of an input means for receiving texts and data that need correction entered by the user, a text correction means for correcting the entered texts and data to conform to business document specifications, a display means for displaying the corrected texts and data to the user, and a transmission means for converting the corrected texts and data into a report in an appropriate format and sending it to a specific person in charge.

[0484] Hardware and software to be used

[0485] Hardware: Smartphones, remote servers

[0486] Software: Natural language processing algorithms, programs that execute API requests.

[0487] Description of each means

[0488] 1. Input method

[0489] Users use their smartphones to input text or data that needs correction to the system. For example, a field worker might input, "The installation of the new part is complete, but there are problems with its operation."

[0490] 2. Text modification methods

[0491] The terminal receives user input and sends it to a remote server using an API request. The remote server has a natural language processing algorithm implemented to automatically correct the input sentences and data to conform to business document specifications. For example, a prompt message such as "Please correct the following sentence to conform to business document specifications: The installation of the new component is complete, but there are problems with its operation verification" might be used.

[0492] 3. Display means

[0493] The corrected text and data are sent back to the smartphone from the remote server, allowing the user to review the changes. For example, the corrected text might read, "The installation of the new component was completed, but there were problems with its operation. Please check for further action."

[0494] 4. Transmission method

[0495] The corrected text and data are converted into a report in the appropriate format and automatically sent to the designated person or supervisor. For example, a report might be generated with the following content: "Corrected message: Installation of the new component was completed, but there were problems with its operation. Please check on the next steps."

[0496] This allows field reports and messages to be quickly and accurately converted into business document specifications, enabling appropriate reporting to management.

[0497] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0498] Step 1:

[0499] The user uses their smartphone to input text or data that needs correction to the system. For example, they might input, "The installation of the new component is complete, but there are problems with its operation." This input is then sent to the system via the input device.

[0500] Step 2:

[0501] The terminal receives user input, converts the input data into JSON format, and sends it to the remote server as an API request. The input data at this time is the text message: "Installation of the new component is complete, but there are problems with the operation verification."

[0502] Step 3:

[0503] The server receives API requests sent from the terminal and invokes a natural language processing algorithm. The server uses a generative AI model based on the input data to modify the input sentence into a business document specification. This data processing includes parsing the input sentence and appropriately correcting its grammar and vocabulary. For example, it generates a prompt sentence, "Please modify the following sentence into a business document specification: The installation of the new component is complete, but there are problems with its operation verification," and passes it to the algorithm.

[0504] Step 4:

[0505] The server retrieves the corrected sentence using a natural language processing algorithm. The corrected sentence will look something like, "The installation of the new component is complete, but there were problems with its operation. Please check for further action." The server then sends this corrected data back to the terminal.

[0506] Step 5:

[0507] The terminal displays the corrected message received from the server to the user. The user checks the changes on their smartphone screen. For example, the screen might display: "Corrected message: Installation of the new component is complete, but there were problems with its operation. Please check for further action."

[0508] Step 6:

[0509] The system converts the modified text and data into a report in the appropriate format. For example, it might embed the modified text into a fixed report template.

[0510] Step 7:

[0511] Finally, the revised report is automatically sent to the designated person or supervisor. Depending on the sending method, the generated report may be sent via email or other communication tools.

[0512] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0513] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results in a manner that takes the user's emotions into consideration. Specifically, it includes input means, text modification means, emotion recognition engine, and display means.

[0514] System Configuration

[0515] Input means

[0516] Users access the system using a terminal and input text, lists, or tables that need correction. Users input data using input forms or terminal prompts displayed on the terminal screen.

[0517] Text editing methods

[0518] The text correction mechanism receives input data sent from the terminal and performs corrections using a natural language processing algorithm. This correction is carried out by a program running on a remote server, which automatically converts the user's input into a format suitable for business document specifications.

[0519] Emotion recognition engine

[0520] The emotion recognition engine analyzes emotions based on the text, lists, and tables entered by the user. The engine analyzes the user's emotions from the input data and provides the results to the text editing system. This allows the system to make revisions that take the user's emotions into consideration.

[0521] Display means

[0522] The revised text, lists, and tables are sent back to the terminal and displayed to the user. The terminal displays the results on the screen, allowing the user to confirm the revisions.

[0523] Explanation of the program's processing

[0524] The following is a concrete example of the system's processing.

[0525] User actions

[0526] The user enters "I have received a proposal for a new project, are there any changes?" into the input form on their device. After entering the text, the user clicks the "Submit" button.

[0527] Terminal operation

[0528] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[0529] Server Operations

[0530] The server analyzes the request received from the terminal and extracts the text contained in the request. Next, it uses an emotion recognition engine to obtain the emotion information necessary for correcting the text. If the user's emotion is "anxiety," this information is used and provided to the text correction mechanism.

[0531] Processing of text modification means

[0532] The server uses a natural language processing algorithm to modify the extracted text to conform to business document specifications. During this process, it adjusts the modifications based on sentiment information provided by the sentiment recognition engine. For example, the text "The business meeting will be held on Friday." might be changed to "Please rest assured that the business meeting will be held on Friday."

[0533] Server response

[0534] The server returns the corrected text to the terminal as an API response. The response includes the corrected text, lists, and tables.

[0535] Terminal display

[0536] The terminal analyzes the response received from the server and retrieves the corrected text. Next, it displays the corrected text to the user.

[0537] User verification

[0538] The user reviews the revised text, lists, and tables displayed on the device screen and decides whether to make further revisions as needed or to use them as they are.

[0539] Specific example

[0540] The present invention will be further explained using the following specific examples.

[0541] 1. User input: The user enters "The business meeting will be held on Friday."

[0542] 2. Terminal processing: The terminal sends this input to the server.

[0543] 3. Analysis of the emotion recognition engine: The emotion recognition engine detects that the user is feeling "fatigue".

[0544] 4. Processing of text correction: The server corrects the text to "The business meeting will be held on Friday, so please take appropriate breaks to avoid fatigue."

[0545] 5. Display on the device: The corrected text will be displayed on the device.

[0546] As described above, the present invention enables users to easily and quickly create high-quality business documents, and further provides a service that takes into consideration the user's feelings.

[0547] The following describes the processing flow.

[0548] Step 1:

[0549] The user enters the text, list, or table that needs correction into the input form on their device and clicks the submit button.

[0550] Step 2:

[0551] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[0552] Step 3:

[0553] The device sends an API request to the remote server. The request includes text, lists, or tables that need to be modified.

[0554] Step 4:

[0555] The server parses the request received from the terminal and extracts the text contained in the request. At this stage, the server recognizes that the user has typed, "I have received a proposal for a new project, are there any changes?"

[0556] Step 5:

[0557] The server uses an emotion recognition engine to analyze the user's emotions from the input text. For example, it might analyze that the user is feeling "anxious."

[0558] Step 6:

[0559] The server provides the emotion analysis results (e.g., "anxiety") received from the emotion recognition engine to the text correction means.

[0560] Step 7:

[0561] The server uses natural language processing algorithms to modify text while taking sentiment into account. For example, if the user's sentiment is "anxious," the message "You have received a proposal for a new project, are there any changes?" is changed to "You have received a proposal for a new project. Please let us know if there are any changes, and please rest assured."

[0562] Step 8:

[0563] The server returns the corrected text to the device as an API response. The response includes the corrected text, lists, and tables.

[0564] Step 9:

[0565] The terminal analyzes the response received from the server and retrieves the corrected text. Next, the corrected text is displayed to the user.

[0566] Step 10:

[0567] The user reviews the revised text, lists, and tables displayed on their device screen and decides whether to make further revisions as needed or to use them as they are.

[0568] The above describes the specific processing steps for a user to modify text, lists, and tables that require correction using a terminal, conforming them to business document specifications, and displaying the corrected results in a manner that takes the user's feelings into consideration. In this way, the present invention supports the efficient and rapid creation of high-quality business documents and enables more personalized document delivery by considering the user's feelings.

[0569] (Example 2)

[0570] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0571] Traditional text editing systems provide the functionality to modify text, lists, and tables to conform to business document specifications, but they have a problem in that they cannot adequately consider the user's emotions. User input often contains specific emotions, and ignoring these makes it difficult to accurately convey the user's intent. Therefore, it is necessary to edit text while taking emotions into consideration.

[0572] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0573] In this invention, the server includes an input means for receiving text, lists, and tables that require modification entered by the user; an emotion recognition means for analyzing emotional information contained in the text, lists, and tables entered by the input means; a text modification means for modifying the entered text, lists, and tables based on the emotional information analyzed by the emotion recognition means; and a display means for displaying the text, lists, and tables modified by the text modification means to the user. This makes it possible to modify text in a manner suitable for business document specifications while appropriately considering the user's emotions.

[0574] An "input method" is a means by which a user inputs text, lists, or tables that need to be modified into the system.

[0575] An "emotion recognition tool" is a means for analyzing and extracting emotional information contained in input text, lists, or tables.

[0576] A "text correction method" is a means of correcting input text, lists, and tables into a format suitable for business document specifications, based on emotional information analyzed by an emotion recognition method.

[0577] "Display means" refers to the means of displaying the revised text, list, or table to the user.

[0578] A "generated artificial intelligence model" is an artificial intelligence model used to modify text, and it includes natural language processing algorithms.

[0579] A "remote server" is a server that can be accessed from a remote location via a network, and is where the programs for emotion recognition and text modification are executed.

[0580] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results in a manner that takes the user's emotions into consideration. Specifically, it includes input means, emotion recognition means, text modification means, and display means.

[0581] System Configuration

[0582] Input means

[0583] Users access the system using a terminal and input text, lists, or tables that need correction. Users input using input forms or terminal prompts displayed on the terminal screen. For example, a user might input the sentence, "Could you please provide an update on the project's progress?"

[0584] emotion recognition means

[0585] The server analyzes the emotional information contained in the input text using emotion recognition tools. The emotion recognition engine used here can utilize existing services such as IBM Watson or Microsoft Azure Text Analytics. For example, it can detect "anxiety" from the input text.

[0586] Text editing methods

[0587] The server uses natural language processing algorithms to modify input text into business document specifications. This process utilizes generated AI models (e.g., GPT-3 or BERT). It also considers sentiment information provided by sentiment recognition systems to revise the wording to be more appropriate. For example, the question "What is the project's progress?" is changed to "It would be helpful if you could provide an update on the project's progress."

[0588] Display means

[0589] The revised text is sent back to the device and displayed to the user. The device displays the result on the screen, allowing the user to confirm the changes.

[0590] Specific examples of how the program works

[0591] 1. User input: The user enters "The business meeting will be held on Friday."

[0592] 2. Terminal processing: The terminal sends this input to the server.

[0593] 3. Analysis of the emotion recognition engine: The emotion recognition engine detects that the user is feeling "fatigue".

[0594] 4. Processing of text correction: The server corrects the text to "The business meeting will be held on Friday, so please take appropriate breaks to avoid fatigue."

[0595] 5. Display on the device: The corrected text will be displayed on the device.

[0596] Example of a prompt

[0597] The following are examples of specific prompt statements for a generative AI model:

[0598] Prompt message:

[0599] Please revise the following text to conform to business document standards and to be more considerate of the user's feelings.

[0600] Input text: What is the progress of the project?

[0601] Emotion: Anxiety

[0602] Revised version:

[0603] It would be helpful if you could keep us updated on the project's progress.

[0604] As described above, the present invention enables users to easily and quickly create high-quality business documents, and further provides a service that takes into consideration the user's feelings.

[0605] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0606] Step 1:

[0607] The user accesses the system and enters text, lists, or tables that need correction into the input form on the terminal. For example, they might enter "What is the project's progress?". After entering the text, they click the "Submit" button. This action sends the user's input to the terminal.

[0608] Step 2:

[0609] The terminal receives user input and stores the text in a local variable. Next, it converts the input data into an API request format, such as JSON, and prepares to send it to the remote server. Here, the input is the text from the user, and the output is the data in the API request format.

[0610] Step 3:

[0611] The terminal sends the formatted API request to the remote server. Specifically, it sends the data as an HTTP POST request. The input for this step is data in JSON format, and the output is a request sent over the network.

[0612] Step 4:

[0613] The server parses the API request received from the terminal and extracts the text data within the request. This extracted data is then passed to the next parsing step. The input is the received request data, and the output is the extracted text data.

[0614] Step 5:

[0615] The server uses an emotion recognition engine to analyze emotional information from the extracted text data. This emotion recognition engine includes IBM Watson and Microsoft Azure Text Analytics, among others. This analysis detects that the user's emotion is "anxiety." The input is text data, and the output is the emotional information resulting from the analysis.

[0616] Step 6:

[0617] The server uses a natural language processing algorithm to modify text to conform to business document specifications that reflect sentiment information. Specifically, it uses a generated AI model (e.g., GPT-3) to modify the sentence "What is the project's progress?" to "It would be helpful if you could provide an update on the project's progress." The input is the sentiment information and the original text, and the output is the modified text.

[0618] Step 7:

[0619] The server returns the corrected text to the terminal as an API response. The response data is then formatted again, for example, into JSON format. The input is the corrected text, and the output is the API response returned to the terminal.

[0620] Step 8:

[0621] The terminal analyzes the response received from the server and retrieves the corrected text. Next, this text is displayed on the screen, presenting the result to the user. The input is the API response data, and the output is the corrected text displayed on the screen.

[0622] Step 9:

[0623] The user reviews the revised text, lists, and tables displayed on the terminal screen and decides whether to make further revisions as needed or use them as they are. The input is the displayed result, and the output is the text approved by the user or further revised.

[0624] (Application Example 2)

[0625] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0626] Conventional document editing systems provide the functionality to modify user-inputted text, lists, and tables to conform to business document specifications, but they are insufficient in terms of making revisions that take into account the emotions of the user and the target audience. Furthermore, in certain fields such as the advertising industry, there is a demand not only for documents to conform to business document specifications, but also for documents that are optimized and appropriately consider the emotions of the target audience.

[0627] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for receiving text, lists, and tables that require modification entered by the user; a text modification means for modifying the text, lists, and tables entered by the input means to conform to business document specifications; and a display means for displaying the results of the text, lists, and tables modified by the text modification means in an emotionally sensitive manner to the target audience. This makes it possible to automatically generate business documents and advertisements that take into account the emotions of the target audience, and to provide influential and effective text.

[0628] A "user" is the entity that uses the system to input and modify text, lists, tables, etc.

[0629] "Input method" refers to the interface that allows users to input text, lists, or tables that need to be modified into the system.

[0630] "Text correction means" refers to the part that has the function of automatically correcting text, lists, and tables entered by the input means to conform to business document specifications.

[0631] "Business document specifications" refer to standards for documents that are appropriate for business settings and have a well-structured format and content.

[0632] An "emotion recognition engine" is a technology that analyzes and extracts the emotions of users and target audiences from input text, lists, and tables.

[0633] "Display means" refers to an interface for displaying modified text, lists, or tables to users or target audiences.

[0634] "Target audience" refers to the recipients of the content of advertisements and business documents.

[0635] A "natural language processing algorithm" is a technology that enables computers to understand and process human language.

[0636] A "remote server" is a remote computer that is accessed via the internet and performs the primary processing of a system.

[0637] "Optimization" refers to the process of revising text, lists, and tables to make them as effective as possible while taking into account the emotions of the target audience.

[0638] This invention relates to a system for automatically modifying and optimizing business documents such as advertising copy, and is particularly capable of providing more effective documents by processing user input with consideration for the emotions of the target audience. The system operates by having the user input text, lists, or tables that they wish to modify or optimize, and then appropriately modifying and displaying them.

[0639] System Configuration

[0640] 1. Overview

[0641] The system consists of input means, text correction means, emotion recognition engine, and display means. Data entered by the user is processed by these means, and an optimized document is generated.

[0642] 2. Hardware and software to be used

[0643] Hardware: Smartphone (iOS or Android)

[0644] software:

[0645] Frontend: React Native

[0646] Backend: Flask

[0647] Natural Language Processing Libraries: Hugging Face's Transformers, OpenAI's GPT-3

[0648] Data processing and calculations

[0649] 1. User input

[0650] Users input advertising copy and business documents using a smartphone application. This input uses an input form built with React Native.

[0651] 2. Emotion analysis

[0652] Input data is sent to the backend server. The input data from the frontend is sent to the Flask server as an API request, and sentiment analysis is performed using Hugging Face's Transformers. The analysis results show what emotions the target audience is most likely to have.

[0653] 3. Text correction

[0654] Based on the analysis results, the server uses OpenAI's GPT-3 to optimize the text in a way that takes the target audience's emotions into consideration. This transforms the user's input into effective ad copy and business documents.

[0655] 4.Display

[0656] Once the optimized document is generated, it is sent back from the backend server to the frontend and finally displayed on the user's smartphone. This allows the user to review the revised and optimized document content.

[0657] Specific example

[0658] Consider a scenario where an advertising agency representative tries to optimize the ad copy for a new product, "This TV is very high quality and inexpensive," to suit their target audience. The representative enters this text into an app and submits it. The server analyzes it using an emotion recognition engine and extracts the emotion "positive." Subsequently, an optimized ad copy is generated using GPT-3: "This TV will provide a great viewing experience. Take advantage of this opportunity and purchase it."

[0659] Examples of prompt statements

[0660] "Optimize the following ad copy to make it resonate positively with your target audience: This TV is very high quality and inexpensive."

[0661] As described above, the system of the present invention can optimize user input data based on the sentiment of the target audience and generate effective business documents.

[0662] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0663] Step 1:

[0664] Users input ad copy or business documents that need correction using a smartphone application. They enter the ad copy into the text box on their smartphone and press the submit button. This input data is stored in a local variable on the device.

[0665] Step 2:

[0666] The device prepares to send the data entered by the user to a remote server. This transmission uses an API request, and the entered text data is sent to the server-side endpoint. The input data includes the ad text entered by the user.

[0667] Step 3:

[0668] The server parses the API request received from the terminal and extracts the text data within the request. The input data received by the server is passed to the emotion recognition engine, where emotion analysis is performed. The emotion recognition engine (Hugging Face's Transformers) is used to analyze the emotion of the text and obtain the result. For example, an emotion such as "positive" might be extracted from the input text as the analysis result.

[0669] Step 4:

[0670] Based on the sentiment analysis results, the server uses a natural language processing engine (OpenAI's GPT-3) to generate prompts for modifying and optimizing the input ad copy in a sentiment-conscious manner. A prompt might look like this: "Optimize the following ad copy so that the target audience feels positive: This TV is very high quality and inexpensive." Using these prompts, GPT-3 generates the optimized ad copy.

[0671] Step 5:

[0672] The optimized ad copy generated by the server is sent to the device as an API response. The output data here is the modified and optimized ad copy.

[0673] Step 6:

[0674] The device analyzes the received API response and extracts optimized ad copy. The extracted optimized ad copy is then displayed to the user. The user can review the displayed optimized ad copy and either make further modifications as needed or use it as is.

[0675] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0676] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0677] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0678] [Third Embodiment]

[0679] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0680] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0681] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0682] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0683] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0684] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0685] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0686] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0687] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0688] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0689] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0690] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0691] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results. Specifically, it includes input means, text modification means, and display means.

[0692] System Configuration

[0693] Input means

[0694] Users access the system using a terminal and input text, lists, or tables that need correction. Users input data using input forms or terminal prompts displayed on the terminal screen.

[0695] Text editing methods

[0696] The text correction mechanism receives input data sent from the terminal and performs corrections using a natural language processing algorithm. This correction is carried out by a program running on a remote server, which automatically converts the user's input into a format suitable for business document specifications.

[0697] Display means

[0698] The revised text, lists, and tables are sent back to the terminal and displayed to the user. The terminal displays the results on the screen, allowing the user to confirm the revisions.

[0699] Explanation of the program's processing

[0700] The following is a concrete example of the system's processing.

[0701] User actions

[0702] The user enters "I have received a proposal for a new project, are there any changes?" into the input form on their device. After entering the text, the user clicks the "Submit" button.

[0703] Terminal operation

[0704] The terminal receives user input and passes it to the program. The terminal program then creates an API request to send this text to a remote server.

[0705] Server Operations

[0706] The server processes requests received from the terminal and modifies the text using natural language processing algorithms. Specifically, it uses the API to generate and process requests like the following: "Please modify the following text so that it can be used in a business context: I have received a proposal for a new project, are there any changes I should make?"

[0707] The server generates the corrected text and sends it back to the terminal. For example, the server returns the following corrected text: "We have received your proposal for a new project. Please let us know if you have any changes."

[0708] Terminal display

[0709] The terminal displays the corrected text received from the server on the screen. The user can review it and make further modifications as needed, or use it as is.

[0710] Specific example

[0711] The present invention will be further explained using the following specific examples.

[0712] 1. User input: The user enters "The business meeting will be held on Friday."

[0713] 2. Terminal processing: The terminal sends this input to the server.

[0714] 3. Server processing: The server corrects the sentence to "The business meeting will be held on Friday."

[0715] 4. Display on the device: The corrected text will be displayed on the device.

[0716] As described above, the present invention enables users to easily and quickly create high-quality business documents.

[0717] The following describes the processing flow.

[0718] Step 1:

[0719] The user enters the text, list, or table that needs correction into the input form on their device and clicks the submit button.

[0720] Step 2:

[0721] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[0722] Step 3:

[0723] The device sends an API request to the remote server. The request includes text, lists, and tables that need to be modified.

[0724] Step 4:

[0725] The server analyzes the request received from the terminal and extracts the text contained in the request. Next, it begins correcting the text using a natural language processing algorithm.

[0726] Step 5:

[0727] The server uses a natural language processing algorithm to modify the extracted text to conform to business document specifications. For example, it modifies the text "The business meeting will be held on Friday." to "The business meeting will be held on Friday."

[0728] Step 6:

[0729] The server returns the corrected text to the terminal as an API response. The response includes the corrected text, lists, and tables.

[0730] Step 7:

[0731] The terminal analyzes the response received from the server and retrieves the corrected text. Next, it displays the corrected text to the user.

[0732] Step 8:

[0733] The user reviews the revised text, lists, and tables displayed on the device screen and decides whether to make further revisions as needed or to use them as they are.

[0734] The above describes the specific processing steps for users to modify text, lists, and tables that require correction using a terminal, conforming them to business document specifications. In this way, the present invention supports the efficient and rapid creation of high-quality business documents.

[0735] (Example 1)

[0736] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0737] Creating business documents is a time-consuming task because it requires strict adherence to format and appropriate expression. In particular, revising text, lists, and tables necessitates repeated checks and corrections due to differences in wording and expression. Such work reduces efficiency and hinders quick and accurate business communication. Therefore, there is a need for a system that automatically corrects user-entered text into a format suitable for business documents and displays it quickly.

[0738] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0739] In this invention, the server includes an input means for receiving text that needs to be corrected, entered by a user; a text correction means for correcting the text entered by the input means to conform to business document specifications; and a display means for displaying the text corrected by the text correction means to the user. This makes it possible for users to quickly create high-quality business documents without any effort.

[0740] An "input method" refers to a device or interface for a user to input text.

[0741] A "text correction method" refers to an algorithm or program for correcting input text to a predetermined specification.

[0742] "Display means" refers to a device or interface for visually presenting the modified text to the user.

[0743] "Natural language processing algorithms" refer to technologies that use methods and techniques to process human language using computers.

[0744] A "remote server" is a server located in a remote location that can be accessed via a network.

[0745] An "API request" is a request made to communicate with other software or services in order to use their functions or retrieve data.

[0746] A "generative AI model" is an artificial intelligence model that learns from large amounts of data and generates responses to specific tasks.

[0747] A "prompt" is a specific question or instruction that is input into a generative AI model.

[0748] This invention is a system that modifies text entered by a user according to business document specifications and displays the modified result. The following describes in detail how this system is implemented.

[0749] System Configuration

[0750] This system consists of three main parts: an input means, a text modification means, and a display means.

[0751] Input means

[0752] Users access the system using their own devices and input text that needs correction. Input methods include input forms displayed on the device screen and terminal prompts. This allows users to input information with simple operations. For example, a user might input, "I have received a proposal for a new project, are there any changes I should make?"

[0753] Text editing methods

[0754] The text correction mechanism receives input data sent from the terminal and uses a natural language processing algorithm to correct the text to conform to business document specifications. This process is implemented by a program running on a remote server. A generative AI model is used to automatically convert user input into a format suitable for business documents. Specifically, the server processes the input using prompts such as the following:

[0755] "Please revise the following sentence to make it suitable for business use: 'I have received a proposal for a new project; are there any changes I would like to make?'"

[0756] Display means

[0757] The corrected text is sent back to the device and displayed on the user's screen. The user can then review the changes and make further modifications as needed, or use it as is.

[0758] Specific example

[0759] The embodiments of the present invention will be further clarified by describing specific examples below.

[0760] 1. User input:

[0761] The user enters "The business meeting will be held on Friday." into the input form on their device and clicks the "Submit" button.

[0762] 2. Terminal processing:

[0763] The terminal retrieves user input and creates an API request to send it to the server.

[0764] 3. Server processing:

[0765] The server receives the API request sent from the terminal and uses a natural language processing algorithm to correct the sentence "The business meeting will be held on Friday." to "The business meeting will be held on Friday."

[0766] 4. Displaying the correction results:

[0767] The server sends the corrected text back to the terminal, which displays the corrected version on the user's screen. The user can then review the corrected text and either make further revisions or use it as is.

[0768] This will allow users to quickly create high-quality business documents without hassle. This system will lead to more efficient and effective business communication.

[0769] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0770] Step 1:

[0771] The user enters text.

[0772] The user enters text that needs correction into an input form on their device. For example, they might enter, "I have received a proposal for a new project, are there any changes I need to make?" The input here is text data, and the device receives this text data.

[0773] Step 2:

[0774] The device creates an API request to send input data.

[0775] The terminal receives text data entered by the user and creates an API request to send it to a remote server. Specifically, it includes the entered text in the API request and sends a processing request to the server.

[0776] Step 3:

[0777] The device sends an API request to the server.

[0778] The terminal sends the created API request to the remote server. At this time, the input data remains in text format and includes a prompt message that reads, "Please revise the following text to make it suitable for business use: We have received a proposal for a new project, are there any changes you would like to make?"

[0779] Step 4:

[0780] The server receives the API request and parses the data.

[0781] The server receives API requests sent from the terminal. The received data includes text entered by the user, which the server parses and begins processing for correction.

[0782] Step 5:

[0783] The server executes a natural language processing algorithm.

[0784] The server executes a natural language processing algorithm based on the received text data. Using a generative AI model, it modifies the input text to conform to business document specifications. Specifically, it converts the input text "I have received a proposal for a new project, are there any changes?" to "I have received a proposal for a new project. Please let me know if there are any changes."

[0785] Step 6:

[0786] The server generates the corrected text.

[0787] The text is corrected using a natural language processing algorithm. The generated text is displayed on the server as new data and used for further processing.

[0788] Step 7:

[0789] The server sends the corrected text to the terminal.

[0790] The server returns the corrected text data to the device. The data sent to the device as an API response includes the corrected text.

[0791] Step 8:

[0792] The device receives the correction results.

[0793] The terminal receives the modified text sent from the server. At this time, the terminal analyzes the received data and uses it for the next processing step.

[0794] Step 9:

[0795] The device displays the corrected text to the user.

[0796] The user's device displays the received, corrected text on the screen. The user can review the displayed corrected text and make further corrections if necessary, or use it as is.

[0797] This allows users to efficiently create and modify business documents through a series of processing flows.

[0798] (Application Example 1)

[0799] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0800] In modern factories, communication between the factory floor and management departments is often inefficient. Specifically, reports and messages submitted by factory workers are often informal, making it difficult for management to quickly understand and utilize them for decision-making. Furthermore, the process of generating and promptly sending reports in the appropriate format is often complex and time-consuming. Therefore, there is a need for more efficient communication and faster report creation.

[0801] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0802] In this invention, the server includes an input means for receiving text or data that needs to be corrected, entered by a user; a text correction means for correcting the text or data entered by the input means to conform to business document specifications; a display means for displaying the text or data corrected by the text correction means to the user; and a transmission means for converting the corrected text or data into a report in an appropriate format and sending it to a specific person in charge. This enables reports and messages from the field to be quickly and accurately converted to business document specifications, allowing for appropriate reporting to the management department.

[0803] An "input method" is a means by which a user enters text or data that needs to be corrected into the system.

[0804] A "text correction method" is a method that uses natural language processing algorithms to correct input text or data to conform to business document specifications.

[0805] "Display means" refers to means for displaying text or data that has been modified by text modification means to the user.

[0806] "Transmission method" refers to the means of converting the revised text or data into a report in the appropriate format and sending it to a specific person.

[0807] A "natural language processing algorithm" is an algorithm used to modify input text to conform to business document specifications.

[0808] A "remote server" is a server where text correction is performed, receiving user input and performing natural language processing, and is located in a remote location.

[0809] This invention is a system for streamlining communication and report creation within a factory. The following describes the configurations for implementing this system.

[0810] System Configuration

[0811] The system consists of an input means for receiving texts and data that need correction entered by the user, a text correction means for correcting the entered texts and data to conform to business document specifications, a display means for displaying the corrected texts and data to the user, and a transmission means for converting the corrected texts and data into a report in an appropriate format and sending it to a specific person in charge.

[0812] Hardware and software to be used

[0813] Hardware: Smartphones, remote servers

[0814] Software: Natural language processing algorithms, programs that execute API requests.

[0815] Description of each means

[0816] 1. Input method

[0817] Users use their smartphones to input text or data that needs correction to the system. For example, a field worker might input, "The installation of the new part is complete, but there are problems with its operation."

[0818] 2. Text modification methods

[0819] The terminal receives user input and sends it to a remote server using an API request. The remote server has a natural language processing algorithm implemented to automatically correct the input sentences and data to conform to business document specifications. For example, a prompt message such as "Please correct the following sentence to conform to business document specifications: The installation of the new component is complete, but there are problems with its operation verification" might be used.

[0820] 3. Display means

[0821] The corrected text and data are sent back to the smartphone from the remote server, allowing the user to review the changes. For example, the corrected text might read, "The installation of the new component was completed, but there were problems with its operation. Please check for further action."

[0822] 4. Transmission method

[0823] The corrected text and data are converted into a report in the appropriate format and automatically sent to the designated person or supervisor. For example, a report might be generated with the following content: "Corrected message: Installation of the new component was completed, but there were problems with its operation. Please check on the next steps."

[0824] This allows field reports and messages to be quickly and accurately converted into business document specifications, enabling appropriate reporting to management.

[0825] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0826] Step 1:

[0827] The user uses their smartphone to input text or data that needs correction to the system. For example, they might input, "The installation of the new component is complete, but there are problems with its operation." This input is then sent to the system via the input device.

[0828] Step 2:

[0829] The terminal receives user input, converts the input data into JSON format, and sends it to the remote server as an API request. The input data at this time is the text message: "Installation of the new component is complete, but there are problems with the operation verification."

[0830] Step 3:

[0831] The server receives API requests sent from the terminal and invokes a natural language processing algorithm. The server uses a generative AI model based on the input data to modify the input sentence into a business document specification. This data processing includes parsing the input sentence and appropriately correcting its grammar and vocabulary. For example, it generates a prompt sentence, "Please modify the following sentence into a business document specification: The installation of the new component is complete, but there are problems with its operation verification," and passes it to the algorithm.

[0832] Step 4:

[0833] The server retrieves the corrected sentence using a natural language processing algorithm. The corrected sentence will look something like, "The installation of the new component is complete, but there were problems with its operation. Please check for further action." The server then sends this corrected data back to the terminal.

[0834] Step 5:

[0835] The terminal displays the corrected message received from the server to the user. The user checks the changes on their smartphone screen. For example, the screen might display: "Corrected message: Installation of the new component is complete, but there were problems with its operation. Please check for further action."

[0836] Step 6:

[0837] The system converts the modified text and data into a report in the appropriate format. For example, it might embed the modified text into a fixed report template.

[0838] Step 7:

[0839] Finally, the revised report is automatically sent to the designated person or supervisor. Depending on the sending method, the generated report may be sent via email or other communication tools.

[0840] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0841] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results in a manner that takes the user's emotions into consideration. Specifically, it includes input means, text modification means, emotion recognition engine, and display means.

[0842] System Configuration

[0843] Input means

[0844] Users access the system using a terminal and input text, lists, or tables that need correction. Users input data using input forms or terminal prompts displayed on the terminal screen.

[0845] Text editing methods

[0846] The text correction mechanism receives input data sent from the terminal and performs corrections using a natural language processing algorithm. This correction is carried out by a program running on a remote server, which automatically converts the user's input into a format suitable for business document specifications.

[0847] Emotion recognition engine

[0848] The emotion recognition engine analyzes emotions based on the text, lists, and tables entered by the user. The engine analyzes the user's emotions from the input data and provides the results to the text editing system. This allows the system to make revisions that take the user's emotions into consideration.

[0849] Display means

[0850] The revised text, lists, and tables are sent back to the terminal and displayed to the user. The terminal displays the results on the screen, allowing the user to confirm the revisions.

[0851] Explanation of the program's processing

[0852] The following is a concrete example of the system's processing.

[0853] User actions

[0854] The user enters "I have received a proposal for a new project, are there any changes?" into the input form on their device. After entering the text, the user clicks the "Submit" button.

[0855] Terminal operation

[0856] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[0857] Server Operations

[0858] The server analyzes the request received from the terminal and extracts the text contained in the request. Next, it uses an emotion recognition engine to obtain the emotion information necessary for correcting the text. If the user's emotion is "anxiety," this information is used and provided to the text correction mechanism.

[0859] Processing of text modification means

[0860] The server uses a natural language processing algorithm to modify the extracted text to conform to business document specifications. During this process, it adjusts the modifications based on sentiment information provided by the sentiment recognition engine. For example, the text "The business meeting will be held on Friday." might be changed to "Please rest assured that the business meeting will be held on Friday."

[0861] Server response

[0862] The server returns the corrected text to the terminal as an API response. The response includes the corrected text, lists, and tables.

[0863] Terminal display

[0864] The terminal analyzes the response received from the server and retrieves the corrected text. Next, it displays the corrected text to the user.

[0865] User verification

[0866] The user reviews the revised text, lists, and tables displayed on the device screen and decides whether to make further revisions as needed or to use them as they are.

[0867] Specific example

[0868] The present invention will be further explained using the following specific examples.

[0869] 1. User input: The user enters "The business meeting will be held on Friday."

[0870] 2. Terminal processing: The terminal sends this input to the server.

[0871] 3. Analysis of the emotion recognition engine: The emotion recognition engine detects that the user is feeling "fatigue".

[0872] 4. Processing of text correction: The server corrects the text to "The business meeting will be held on Friday, so please take appropriate breaks to avoid fatigue."

[0873] 5. Display on the device: The corrected text will be displayed on the device.

[0874] As described above, the present invention enables users to easily and quickly create high-quality business documents, and further provides a service that takes into consideration the user's feelings.

[0875] The following describes the processing flow.

[0876] Step 1:

[0877] The user enters the text, list, or table that needs correction into the input form on their device and clicks the submit button.

[0878] Step 2:

[0879] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[0880] Step 3:

[0881] The device sends an API request to the remote server. The request includes text, lists, or tables that need to be modified.

[0882] Step 4:

[0883] The server parses the request received from the terminal and extracts the text contained in the request. At this stage, the server recognizes that the user has typed, "I have received a proposal for a new project, are there any changes?"

[0884] Step 5:

[0885] The server uses an emotion recognition engine to analyze the user's emotions from the input text. For example, it might analyze that the user is feeling "anxious."

[0886] Step 6:

[0887] The server provides the emotion analysis results (e.g., "anxiety") received from the emotion recognition engine to the text correction means.

[0888] Step 7:

[0889] The server uses natural language processing algorithms to modify text while taking sentiment into account. For example, if the user's sentiment is "anxious," the message "You have received a proposal for a new project, are there any changes?" is changed to "You have received a proposal for a new project. Please let us know if there are any changes, and please rest assured."

[0890] Step 8:

[0891] The server returns the corrected text to the device as an API response. The response includes the corrected text, lists, and tables.

[0892] Step 9:

[0893] The terminal analyzes the response received from the server and retrieves the corrected text. Next, the corrected text is displayed to the user.

[0894] Step 10:

[0895] The user reviews the revised text, lists, and tables displayed on their device screen and decides whether to make further revisions as needed or to use them as they are.

[0896] The above describes the specific processing steps for a user to modify text, lists, and tables that require correction using a terminal, conforming them to business document specifications, and displaying the corrected results in a manner that takes the user's feelings into consideration. In this way, the present invention supports the efficient and rapid creation of high-quality business documents and enables more personalized document delivery by considering the user's feelings.

[0897] (Example 2)

[0898] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0899] Traditional text editing systems provide the functionality to modify text, lists, and tables to conform to business document specifications, but they have a problem in that they cannot adequately consider the user's emotions. User input often contains specific emotions, and ignoring these makes it difficult to accurately convey the user's intent. Therefore, it is necessary to edit text while taking emotions into consideration.

[0900] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0901] In this invention, the server includes an input means for receiving text, lists, and tables that require modification entered by the user; an emotion recognition means for analyzing emotional information contained in the text, lists, and tables entered by the input means; a text modification means for modifying the entered text, lists, and tables based on the emotional information analyzed by the emotion recognition means; and a display means for displaying the text, lists, and tables modified by the text modification means to the user. This makes it possible to modify text in a manner suitable for business document specifications while appropriately considering the user's emotions.

[0902] An "input method" is a means by which a user inputs text, lists, or tables that need to be modified into the system.

[0903] An "emotion recognition tool" is a means for analyzing and extracting emotional information contained in input text, lists, or tables.

[0904] A "text correction method" is a means of correcting input text, lists, and tables into a format suitable for business document specifications, based on emotional information analyzed by an emotion recognition method.

[0905] "Display means" refers to the means of displaying the revised text, list, or table to the user.

[0906] A "generated artificial intelligence model" is an artificial intelligence model used to modify text, and it includes natural language processing algorithms.

[0907] A "remote server" is a server that can be accessed from a remote location via a network, and is where the programs for emotion recognition and text modification are executed.

[0908] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results in a manner that takes the user's emotions into consideration. Specifically, it includes input means, emotion recognition means, text modification means, and display means.

[0909] System Configuration

[0910] Input means

[0911] Users access the system using a terminal and input text, lists, or tables that need correction. Users input using input forms or terminal prompts displayed on the terminal screen. For example, a user might input the sentence, "Could you please provide an update on the project's progress?"

[0912] emotion recognition means

[0913] The server analyzes the emotional information contained in the input text using emotion recognition tools. The emotion recognition engine used here can utilize existing services such as IBM Watson or Microsoft Azure Text Analytics. For example, it can detect "anxiety" from the input text.

[0914] Text editing methods

[0915] The server uses natural language processing algorithms to modify input text into business document specifications. This process utilizes generated AI models (e.g., GPT-3 or BERT). It also considers sentiment information provided by sentiment recognition systems to revise the wording to be more appropriate. For example, the question "What is the project's progress?" is changed to "It would be helpful if you could provide an update on the project's progress."

[0916] Display means

[0917] The revised text is sent back to the device and displayed to the user. The device displays the result on the screen, allowing the user to confirm the changes.

[0918] Specific examples of how the program works

[0919] 1. User input: The user enters "The business meeting will be held on Friday."

[0920] 2. Terminal processing: The terminal sends this input to the server.

[0921] 3. Analysis of the emotion recognition engine: The emotion recognition engine detects that the user is feeling "fatigue".

[0922] 4. Processing of text correction: The server corrects the text to "The business meeting will be held on Friday, so please take appropriate breaks to avoid fatigue."

[0923] 5. Display on the device: The corrected text will be displayed on the device.

[0924] Example of a prompt

[0925] The following are examples of specific prompt statements for a generative AI model:

[0926] Prompt message:

[0927] Please revise the following text to conform to business document standards and to be more considerate of the user's feelings.

[0928] Input text: What is the progress of the project?

[0929] Emotion: Anxiety

[0930] Revised version:

[0931] It would be helpful if you could keep us updated on the project's progress.

[0932] As described above, the present invention enables users to easily and quickly create high-quality business documents, and further provides a service that takes into consideration the user's feelings.

[0933] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0934] Step 1:

[0935] The user accesses the system and enters text, lists, or tables that need correction into the input form on the terminal. For example, they might enter "What is the project's progress?". After entering the text, they click the "Submit" button. This action sends the user's input to the terminal.

[0936] Step 2:

[0937] The terminal receives user input and stores the text in a local variable. Next, it converts the input data into an API request format, such as JSON, and prepares to send it to the remote server. Here, the input is the text from the user, and the output is the data in the API request format.

[0938] Step 3:

[0939] The terminal sends the formatted API request to the remote server. Specifically, it sends the data as an HTTP POST request. The input for this step is data in JSON format, and the output is a request sent over the network.

[0940] Step 4:

[0941] The server parses the API request received from the terminal and extracts the text data within the request. This extracted data is then passed to the next parsing step. The input is the received request data, and the output is the extracted text data.

[0942] Step 5:

[0943] The server uses an emotion recognition engine to analyze emotional information from the extracted text data. This emotion recognition engine includes IBM Watson and Microsoft Azure Text Analytics, among others. This analysis detects that the user's emotion is "anxiety." The input is text data, and the output is the emotional information resulting from the analysis.

[0944] Step 6:

[0945] The server uses a natural language processing algorithm to modify text to conform to business document specifications that reflect sentiment information. Specifically, it uses a generated AI model (e.g., GPT-3) to modify the sentence "What is the project's progress?" to "It would be helpful if you could provide an update on the project's progress." The input is the sentiment information and the original text, and the output is the modified text.

[0946] Step 7:

[0947] The server returns the corrected text to the terminal as an API response. The response data is then formatted again, for example, into JSON format. The input is the corrected text, and the output is the API response returned to the terminal.

[0948] Step 8:

[0949] The terminal analyzes the response received from the server and retrieves the corrected text. Next, this text is displayed on the screen, presenting the result to the user. The input is the API response data, and the output is the corrected text displayed on the screen.

[0950] Step 9:

[0951] The user reviews the revised text, lists, and tables displayed on the terminal screen and decides whether to make further revisions as needed or use them as they are. The input is the displayed result, and the output is the text approved by the user or further revised.

[0952] (Application Example 2)

[0953] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0954] Conventional document editing systems provide the functionality to modify user-inputted text, lists, and tables to conform to business document specifications, but they are insufficient in terms of making revisions that take into account the emotions of the user and the target audience. Furthermore, in certain fields such as the advertising industry, there is a demand not only for documents to conform to business document specifications, but also for documents that are optimized and appropriately consider the emotions of the target audience.

[0955] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for receiving text, lists, and tables that require modification entered by the user; a text modification means for modifying the text, lists, and tables entered by the input means to conform to business document specifications; and a display means for displaying the results of the text, lists, and tables modified by the text modification means in an emotionally sensitive manner to the target audience. This makes it possible to automatically generate business documents and advertisements that take into account the emotions of the target audience, and to provide influential and effective text.

[0956] A "user" is the entity that uses the system to input and modify text, lists, tables, etc.

[0957] "Input method" refers to the interface that allows users to input text, lists, or tables that need to be modified into the system.

[0958] "Text correction means" refers to the part that has the function of automatically correcting text, lists, and tables entered by the input means to conform to business document specifications.

[0959] "Business document specifications" refer to standards for documents that are appropriate for business settings and have a well-structured format and content.

[0960] An "emotion recognition engine" is a technology that analyzes and extracts the emotions of users and target audiences from input text, lists, and tables.

[0961] "Display means" refers to an interface for displaying modified text, lists, or tables to users or target audiences.

[0962] "Target audience" refers to the recipients of the content of advertisements and business documents.

[0963] A "natural language processing algorithm" is a technology that enables computers to understand and process human language.

[0964] A "remote server" is a remote computer that is accessed via the internet and performs the primary processing of a system.

[0965] "Optimization" refers to the process of revising text, lists, and tables to make them as effective as possible while taking into account the emotions of the target audience.

[0966] This invention relates to a system for automatically modifying and optimizing business documents such as advertising copy, and is particularly capable of providing more effective documents by processing user input with consideration for the emotions of the target audience. The system operates by having the user input text, lists, or tables that they wish to modify or optimize, and then appropriately modifying and displaying them.

[0967] System Configuration

[0968] 1. Overview

[0969] The system consists of input means, text correction means, emotion recognition engine, and display means. Data entered by the user is processed by these means, and an optimized document is generated.

[0970] 2. Hardware and software to be used

[0971] Hardware: Smartphone (iOS or Android)

[0972] software:

[0973] Frontend: React Native

[0974] Backend: Flask

[0975] Natural Language Processing Libraries: Hugging Face's Transformers, OpenAI's GPT-3

[0976] Data processing and calculations

[0977] 1. User input

[0978] Users input advertising copy and business documents using a smartphone application. This input uses an input form built with React Native.

[0979] 2. Emotion analysis

[0980] Input data is sent to the backend server. The input data from the frontend is sent to the Flask server as an API request, and sentiment analysis is performed using Hugging Face's Transformers. The analysis results show what emotions the target audience is most likely to have.

[0981] 3. Text correction

[0982] Based on the analysis results, the server uses OpenAI's GPT-3 to optimize the text in a way that takes the target audience's emotions into consideration. This transforms the user's input into effective ad copy and business documents.

[0983] 4.Display

[0984] Once the optimized document is generated, it is sent back from the backend server to the frontend and finally displayed on the user's smartphone. This allows the user to review the revised and optimized document content.

[0985] Specific example

[0986] Consider a scenario where an advertising agency representative tries to optimize the ad copy for a new product, "This TV is very high quality and inexpensive," to suit their target audience. The representative enters this text into an app and submits it. The server analyzes it using an emotion recognition engine and extracts the emotion "positive." Subsequently, an optimized ad copy is generated using GPT-3: "This TV will provide a great viewing experience. Take advantage of this opportunity and purchase it."

[0987] Examples of prompt statements

[0988] "Optimize the following ad copy to make it resonate positively with your target audience: This TV is very high quality and inexpensive."

[0989] As described above, the system of the present invention can optimize user input data based on the sentiment of the target audience and generate effective business documents.

[0990] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0991] Step 1:

[0992] Users input ad copy or business documents that need correction using a smartphone application. They enter the ad copy into the text box on their smartphone and press the submit button. This input data is stored in a local variable on the device.

[0993] Step 2:

[0994] The device prepares to send the data entered by the user to a remote server. This transmission uses an API request, and the entered text data is sent to the server-side endpoint. The input data includes the ad text entered by the user.

[0995] Step 3:

[0996] The server parses the API request received from the terminal and extracts the text data within the request. The input data received by the server is passed to the emotion recognition engine, where emotion analysis is performed. The emotion recognition engine (Hugging Face's Transformers) is used to analyze the emotion of the text and obtain the result. For example, an emotion such as "positive" might be extracted from the input text as the analysis result.

[0997] Step 4:

[0998] Based on the sentiment analysis results, the server uses a natural language processing engine (OpenAI's GPT-3) to generate prompts for modifying and optimizing the input ad copy in a sentiment-conscious manner. A prompt might look like this: "Optimize the following ad copy so that the target audience feels positive: This TV is very high quality and inexpensive." Using these prompts, GPT-3 generates the optimized ad copy.

[0999] Step 5:

[1000] The optimized ad copy generated by the server is sent to the device as an API response. The output data here is the modified and optimized ad copy.

[1001] Step 6:

[1002] The device analyzes the received API response and extracts optimized ad copy. The extracted optimized ad copy is then displayed to the user. The user can review the displayed optimized ad copy and either make further modifications as needed or use it as is.

[1003] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1004] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1005] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1006] [Fourth Embodiment]

[1007] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1008] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1009] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1010] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1011] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1012] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1013] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1014] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1015] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1016] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1017] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1018] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1019] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1020] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results. Specifically, it includes input means, text modification means, and display means.

[1021] System Configuration

[1022] Input means

[1023] Users access the system using a terminal and input text, lists, or tables that need correction. Users input data using input forms or terminal prompts displayed on the terminal screen.

[1024] Text editing methods

[1025] The text correction mechanism receives input data sent from the terminal and performs corrections using a natural language processing algorithm. This correction is carried out by a program running on a remote server, which automatically converts the user's input into a format suitable for business document specifications.

[1026] Display means

[1027] The revised text, lists, and tables are sent back to the terminal and displayed to the user. The terminal displays the results on the screen, allowing the user to confirm the revisions.

[1028] Explanation of the program's processing

[1029] The following is a concrete example of the system's processing.

[1030] User actions

[1031] The user enters "I have received a proposal for a new project, are there any changes?" into the input form on their device. After entering the text, the user clicks the "Submit" button.

[1032] Terminal operation

[1033] The terminal receives user input and passes it to the program. The terminal program then creates an API request to send this text to a remote server.

[1034] Server Operations

[1035] The server processes requests received from the terminal and modifies the text using natural language processing algorithms. Specifically, it uses the API to generate and process requests like the following: "Please modify the following text so that it can be used in a business context: I have received a proposal for a new project, are there any changes I should make?"

[1036] The server generates the corrected text and sends it back to the terminal. For example, the server returns the following corrected text: "We have received your proposal for a new project. Please let us know if you have any changes."

[1037] Terminal display

[1038] The terminal displays the corrected text received from the server on the screen. The user can review it and make further modifications as needed, or use it as is.

[1039] Specific example

[1040] The present invention will be further explained using the following specific examples.

[1041] 1. User input: The user enters "The business meeting will be held on Friday."

[1042] 2. Terminal processing: The terminal sends this input to the server.

[1043] 3. Server processing: The server corrects the sentence to "The business meeting will be held on Friday."

[1044] 4. Display on the device: The corrected text will be displayed on the device.

[1045] As described above, the present invention enables users to easily and quickly create high-quality business documents.

[1046] The following describes the processing flow.

[1047] Step 1:

[1048] The user enters the text, list, or table that needs correction into the input form on their device and clicks the submit button.

[1049] Step 2:

[1050] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[1051] Step 3:

[1052] The device sends an API request to the remote server. The request includes text, lists, and tables that need to be modified.

[1053] Step 4:

[1054] The server analyzes the request received from the terminal and extracts the text contained in the request. Next, it begins correcting the text using a natural language processing algorithm.

[1055] Step 5:

[1056] The server uses a natural language processing algorithm to modify the extracted text to conform to business document specifications. For example, it modifies the text "The business meeting will be held on Friday." to "The business meeting will be held on Friday."

[1057] Step 6:

[1058] The server returns the corrected text to the terminal as an API response. The response includes the corrected text, lists, and tables.

[1059] Step 7:

[1060] The terminal analyzes the response received from the server and retrieves the corrected text. Next, it displays the corrected text to the user.

[1061] Step 8:

[1062] The user reviews the revised text, lists, and tables displayed on the device screen and decides whether to make further revisions as needed or to use them as they are.

[1063] The above describes the specific processing steps for users to modify text, lists, and tables that require correction using a terminal, conforming them to business document specifications. In this way, the present invention supports the efficient and rapid creation of high-quality business documents.

[1064] (Example 1)

[1065] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1066] Creating business documents is a time-consuming task because it requires strict adherence to format and appropriate expression. In particular, revising text, lists, and tables necessitates repeated checks and corrections due to differences in wording and expression. Such work reduces efficiency and hinders quick and accurate business communication. Therefore, there is a need for a system that automatically corrects user-entered text into a format suitable for business documents and displays it quickly.

[1067] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1068] In this invention, the server includes an input means for receiving text that needs to be corrected, entered by a user; a text correction means for correcting the text entered by the input means to conform to business document specifications; and a display means for displaying the text corrected by the text correction means to the user. This makes it possible for users to quickly create high-quality business documents without any effort.

[1069] An "input method" refers to a device or interface for a user to input text.

[1070] A "text correction method" refers to an algorithm or program for correcting input text to a predetermined specification.

[1071] "Display means" refers to a device or interface for visually presenting the modified text to the user.

[1072] "Natural language processing algorithms" refer to technologies that use methods and techniques to process human language using computers.

[1073] A "remote server" is a server located in a remote location that can be accessed via a network.

[1074] An "API request" is a request made to communicate with other software or services in order to use their functions or retrieve data.

[1075] A "generative AI model" is an artificial intelligence model that learns from large amounts of data and generates responses to specific tasks.

[1076] A "prompt" is a specific question or instruction that is input into a generative AI model.

[1077] This invention is a system that modifies text entered by a user according to business document specifications and displays the modified result. The following describes in detail how this system is implemented.

[1078] System Configuration

[1079] This system consists of three main parts: an input means, a text modification means, and a display means.

[1080] Input means

[1081] Users access the system using their own devices and input text that needs correction. Input methods include input forms displayed on the device screen and terminal prompts. This allows users to input information with simple operations. For example, a user might input, "I have received a proposal for a new project, are there any changes I should make?"

[1082] Text editing methods

[1083] The text correction mechanism receives input data sent from the terminal and uses a natural language processing algorithm to correct the text to conform to business document specifications. This process is implemented by a program running on a remote server. A generative AI model is used to automatically convert user input into a format suitable for business documents. Specifically, the server processes the input using prompts such as the following:

[1084] "Please revise the following sentence to make it suitable for business use: 'I have received a proposal for a new project; are there any changes I would like to make?'"

[1085] Display means

[1086] The corrected text is sent back to the device and displayed on the user's screen. The user can then review the changes and make further modifications as needed, or use it as is.

[1087] Specific example

[1088] The embodiments of the present invention will be further clarified by describing specific examples below.

[1089] 1. User input:

[1090] The user enters "The business meeting will be held on Friday." into the input form on their device and clicks the "Submit" button.

[1091] 2. Terminal processing:

[1092] The terminal retrieves user input and creates an API request to send it to the server.

[1093] 3. Server processing:

[1094] The server receives the API request sent from the terminal and uses a natural language processing algorithm to correct the sentence "The business meeting will be held on Friday." to "The business meeting will be held on Friday."

[1095] 4. Displaying the correction results:

[1096] The server sends the corrected text back to the terminal, which displays the corrected version on the user's screen. The user can then review the corrected text and either make further revisions or use it as is.

[1097] This will allow users to quickly create high-quality business documents without hassle. This system will lead to more efficient and effective business communication.

[1098] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1099] Step 1:

[1100] The user enters text.

[1101] The user enters text that needs correction into an input form on their device. For example, they might enter, "I have received a proposal for a new project, are there any changes I need to make?" The input here is text data, and the device receives this text data.

[1102] Step 2:

[1103] The device creates an API request to send input data.

[1104] The terminal receives text data entered by the user and creates an API request to send it to a remote server. Specifically, it includes the entered text in the API request and sends a processing request to the server.

[1105] Step 3:

[1106] The device sends an API request to the server.

[1107] The terminal sends the created API request to the remote server. At this time, the input data remains in text format and includes a prompt message that reads, "Please revise the following text to make it suitable for business use: We have received a proposal for a new project, are there any changes you would like to make?"

[1108] Step 4:

[1109] The server receives the API request and parses the data.

[1110] The server receives API requests sent from the terminal. The received data includes text entered by the user, which the server parses and begins processing for correction.

[1111] Step 5:

[1112] The server executes a natural language processing algorithm.

[1113] The server executes a natural language processing algorithm based on the received text data. Using a generative AI model, it modifies the input text to conform to business document specifications. Specifically, it converts the input text "I have received a proposal for a new project, are there any changes?" to "I have received a proposal for a new project. Please let me know if there are any changes."

[1114] Step 6:

[1115] The server generates the corrected text.

[1116] The text is corrected using a natural language processing algorithm. The generated text is displayed on the server as new data and used for further processing.

[1117] Step 7:

[1118] The server sends the corrected text to the terminal.

[1119] The server returns the corrected text data to the device. The data sent to the device as an API response includes the corrected text.

[1120] Step 8:

[1121] The device receives the correction results.

[1122] The terminal receives the modified text sent from the server. At this time, the terminal analyzes the received data and uses it for the next processing step.

[1123] Step 9:

[1124] The device displays the corrected text to the user.

[1125] The user's device displays the received, corrected text on the screen. The user can review the displayed corrected text and make further corrections if necessary, or use it as is.

[1126] This allows users to efficiently create and modify business documents through a series of processing flows.

[1127] (Application Example 1)

[1128] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1129] In modern factories, communication between the factory floor and management departments is often inefficient. Specifically, reports and messages submitted by factory workers are often informal, making it difficult for management to quickly understand and utilize them for decision-making. Furthermore, the process of generating and promptly sending reports in the appropriate format is often complex and time-consuming. Therefore, there is a need for more efficient communication and faster report creation.

[1130] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1131] In this invention, the server includes an input means for receiving text or data that needs to be corrected, entered by a user; a text correction means for correcting the text or data entered by the input means to conform to business document specifications; a display means for displaying the text or data corrected by the text correction means to the user; and a transmission means for converting the corrected text or data into a report in an appropriate format and sending it to a specific person in charge. This enables reports and messages from the field to be quickly and accurately converted to business document specifications, allowing for appropriate reporting to the management department.

[1132] An "input method" is a means by which a user enters text or data that needs to be corrected into the system.

[1133] A "text correction method" is a method that uses natural language processing algorithms to correct input text or data to conform to business document specifications.

[1134] "Display means" refers to means for displaying text or data that has been modified by text modification means to the user.

[1135] "Transmission method" refers to the means of converting the revised text or data into a report in the appropriate format and sending it to a specific person.

[1136] A "natural language processing algorithm" is an algorithm used to modify input text to conform to business document specifications.

[1137] A "remote server" is a server where text correction is performed, receiving user input and performing natural language processing, and is located in a remote location.

[1138] This invention is a system for streamlining communication and report creation within a factory. The following describes the configurations for implementing this system.

[1139] System Configuration

[1140] The system consists of an input means for receiving texts and data that need correction entered by the user, a text correction means for correcting the entered texts and data to conform to business document specifications, a display means for displaying the corrected texts and data to the user, and a transmission means for converting the corrected texts and data into a report in an appropriate format and sending it to a specific person in charge.

[1141] Hardware and software to be used

[1142] Hardware: Smartphones, remote servers

[1143] Software: Natural language processing algorithms, programs that execute API requests.

[1144] Description of each means

[1145] 1. Input method

[1146] Users use their smartphones to input text or data that needs correction to the system. For example, a field worker might input, "The installation of the new part is complete, but there are problems with its operation."

[1147] 2. Text modification methods

[1148] The terminal receives user input and sends it to a remote server using an API request. The remote server has a natural language processing algorithm implemented to automatically correct the input sentences and data to conform to business document specifications. For example, a prompt message such as "Please correct the following sentence to conform to business document specifications: The installation of the new component is complete, but there are problems with its operation verification" might be used.

[1149] 3. Display means

[1150] The corrected text and data are sent back to the smartphone from the remote server, allowing the user to review the changes. For example, the corrected text might read, "The installation of the new component was completed, but there were problems with its operation. Please check for further action."

[1151] 4. Transmission method

[1152] The corrected text and data are converted into a report in the appropriate format and automatically sent to the designated person or supervisor. For example, a report might be generated with the following content: "Corrected message: Installation of the new component was completed, but there were problems with its operation. Please check on the next steps."

[1153] This allows field reports and messages to be quickly and accurately converted into business document specifications, enabling appropriate reporting to management.

[1154] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1155] Step 1:

[1156] The user uses their smartphone to input text or data that needs correction to the system. For example, they might input, "The installation of the new component is complete, but there are problems with its operation." This input is then sent to the system via the input device.

[1157] Step 2:

[1158] The terminal receives user input, converts the input data into JSON format, and sends it to the remote server as an API request. The input data at this time is the text message: "Installation of the new component is complete, but there are problems with the operation verification."

[1159] Step 3:

[1160] The server receives API requests sent from the terminal and invokes a natural language processing algorithm. The server uses a generative AI model based on the input data to modify the input sentence into a business document specification. This data processing includes parsing the input sentence and appropriately correcting its grammar and vocabulary. For example, it generates a prompt sentence, "Please modify the following sentence into a business document specification: The installation of the new component is complete, but there are problems with its operation verification," and passes it to the algorithm.

[1161] Step 4:

[1162] The server retrieves the corrected sentence using a natural language processing algorithm. The corrected sentence will look something like, "The installation of the new component is complete, but there were problems with its operation. Please check for further action." The server then sends this corrected data back to the terminal.

[1163] Step 5:

[1164] The terminal displays the corrected message received from the server to the user. The user checks the changes on their smartphone screen. For example, the screen might display: "Corrected message: Installation of the new component is complete, but there were problems with its operation. Please check for further action."

[1165] Step 6:

[1166] The system converts the modified text and data into a report in the appropriate format. For example, it might embed the modified text into a fixed report template.

[1167] Step 7:

[1168] Finally, the revised report is automatically sent to the designated person or supervisor. Depending on the sending method, the generated report may be sent via email or other communication tools.

[1169] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1170] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results in a manner that takes the user's emotions into consideration. Specifically, it includes input means, text modification means, emotion recognition engine, and display means.

[1171] System Configuration

[1172] Input means

[1173] Users access the system using a terminal and input text, lists, or tables that need correction. Users input data using input forms or terminal prompts displayed on the terminal screen.

[1174] Text editing methods

[1175] The text correction mechanism receives input data sent from the terminal and performs corrections using a natural language processing algorithm. This correction is carried out by a program running on a remote server, which automatically converts the user's input into a format suitable for business document specifications.

[1176] Emotion recognition engine

[1177] The emotion recognition engine analyzes emotions based on the text, lists, and tables entered by the user. The engine analyzes the user's emotions from the input data and provides the results to the text editing system. This allows the system to make revisions that take the user's emotions into consideration.

[1178] Display means

[1179] The revised text, lists, and tables are sent back to the terminal and displayed to the user. The terminal displays the results on the screen, allowing the user to confirm the revisions.

[1180] Explanation of the program's processing

[1181] The following is a concrete example of the system's processing.

[1182] User actions

[1183] The user enters "I have received a proposal for a new project, are there any changes?" into the input form on their device. After entering the text, the user clicks the "Submit" button.

[1184] Terminal operation

[1185] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[1186] Server Operations

[1187] The server analyzes the request received from the terminal and extracts the text contained in the request. Next, it uses an emotion recognition engine to obtain the emotion information necessary for correcting the text. If the user's emotion is "anxiety," this information is used and provided to the text correction mechanism.

[1188] Processing of text modification means

[1189] The server uses a natural language processing algorithm to modify the extracted text to conform to business document specifications. During this process, it adjusts the modifications based on sentiment information provided by the sentiment recognition engine. For example, the text "The business meeting will be held on Friday." might be changed to "Please rest assured that the business meeting will be held on Friday."

[1190] Server response

[1191] The server returns the corrected text to the terminal as an API response. The response includes the corrected text, lists, and tables.

[1192] Terminal display

[1193] The terminal analyzes the response received from the server and retrieves the corrected text. Next, it displays the corrected text to the user.

[1194] User verification

[1195] The user reviews the revised text, lists, and tables displayed on the device screen and decides whether to make further revisions as needed or to use them as they are.

[1196] Specific example

[1197] The present invention will be further explained using the following specific examples.

[1198] 1. User input: The user enters "The business meeting will be held on Friday."

[1199] 2. Terminal processing: The terminal sends this input to the server.

[1200] 3. Analysis of the emotion recognition engine: The emotion recognition engine detects that the user is feeling "fatigue".

[1201] 4. Processing of text correction: The server corrects the text to "The business meeting will be held on Friday, so please take appropriate breaks to avoid fatigue."

[1202] 5. Display on the device: The corrected text will be displayed on the device.

[1203] As described above, the present invention enables users to easily and quickly create high-quality business documents, and further provides a service that takes into consideration the user's feelings.

[1204] The following describes the processing flow.

[1205] Step 1:

[1206] The user enters the text, list, or table that needs correction into the input form on their device and clicks the submit button.

[1207] Step 2:

[1208] The terminal receives user input and stores the text in a local variable. Next, it prepares an API request to send the input data to a remote server.

[1209] Step 3:

[1210] The device sends an API request to the remote server. The request includes text, lists, or tables that need to be modified.

[1211] Step 4:

[1212] The server parses the request received from the terminal and extracts the text contained in the request. At this stage, the server recognizes that the user has typed, "I have received a proposal for a new project, are there any changes?"

[1213] Step 5:

[1214] The server uses an emotion recognition engine to analyze the user's emotions from the input text. For example, it might analyze that the user is feeling "anxious."

[1215] Step 6:

[1216] The server provides the emotion analysis results (e.g., "anxiety") received from the emotion recognition engine to the text correction means.

[1217] Step 7:

[1218] The server uses natural language processing algorithms to modify text while taking sentiment into account. For example, if the user's sentiment is "anxious," the message "You have received a proposal for a new project, are there any changes?" is changed to "You have received a proposal for a new project. Please let us know if there are any changes, and please rest assured."

[1219] Step 8:

[1220] The server returns the corrected text to the device as an API response. The response includes the corrected text, lists, and tables.

[1221] Step 9:

[1222] The terminal analyzes the response received from the server and retrieves the corrected text. Next, the corrected text is displayed to the user.

[1223] Step 10:

[1224] The user reviews the revised text, lists, and tables displayed on their device screen and decides whether to make further revisions as needed or to use them as they are.

[1225] The above describes the specific processing steps for a user to modify text, lists, and tables that require correction using a terminal, conforming them to business document specifications, and displaying the corrected results in a manner that takes the user's feelings into consideration. In this way, the present invention supports the efficient and rapid creation of high-quality business documents and enables more personalized document delivery by considering the user's feelings.

[1226] (Example 2)

[1227] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1228] Traditional text editing systems provide the functionality to modify text, lists, and tables to conform to business document specifications, but they have a problem in that they cannot adequately consider the user's emotions. User input often contains specific emotions, and ignoring these makes it difficult to accurately convey the user's intent. Therefore, it is necessary to edit text while taking emotions into consideration.

[1229] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1230] In this invention, the server includes an input means for receiving text, lists, and tables that require modification entered by the user; an emotion recognition means for analyzing emotional information contained in the text, lists, and tables entered by the input means; a text modification means for modifying the entered text, lists, and tables based on the emotional information analyzed by the emotion recognition means; and a display means for displaying the text, lists, and tables modified by the text modification means to the user. This makes it possible to modify text in a manner suitable for business document specifications while appropriately considering the user's emotions.

[1231] An "input method" is a means by which a user inputs text, lists, or tables that need to be modified into the system.

[1232] An "emotion recognition tool" is a means for analyzing and extracting emotional information contained in input text, lists, or tables.

[1233] A "text correction method" is a means of correcting input text, lists, and tables into a format suitable for business document specifications, based on emotional information analyzed by an emotion recognition method.

[1234] "Display means" refers to the means of displaying the revised text, list, or table to the user.

[1235] A "generated artificial intelligence model" is an artificial intelligence model used to modify text, and it includes natural language processing algorithms.

[1236] A "remote server" is a server that can be accessed from a remote location via a network, and is where the programs for emotion recognition and text modification are executed.

[1237] This invention relates to a system that receives text, lists, or tables that require modification from a user, modifies the text to conform to business document specifications, and displays the modified results in a manner that takes the user's emotions into consideration. Specifically, it includes input means, emotion recognition means, text modification means, and display means.

[1238] System Configuration

[1239] Input means

[1240] Users access the system using a terminal and input text, lists, or tables that need correction. Users input using input forms or terminal prompts displayed on the terminal screen. For example, a user might input the sentence, "Could you please provide an update on the project's progress?"

[1241] emotion recognition means

[1242] The server analyzes the emotional information contained in the input text using emotion recognition tools. The emotion recognition engine used here can utilize existing services such as IBM Watson or Microsoft Azure Text Analytics. For example, it can detect "anxiety" from the input text.

[1243] Text editing methods

[1244] The server uses natural language processing algorithms to modify input text into business document specifications. This process utilizes generated AI models (e.g., GPT-3 or BERT). It also considers sentiment information provided by sentiment recognition systems to revise the wording to be more appropriate. For example, the question "What is the project's progress?" is changed to "It would be helpful if you could provide an update on the project's progress."

[1245] Display means

[1246] The revised text is sent back to the device and displayed to the user. The device displays the result on the screen, allowing the user to confirm the changes.

[1247] Specific examples of how the program works

[1248] 1. User input: The user enters "The business meeting will be held on Friday."

[1249] 2. Terminal processing: The terminal sends this input to the server.

[1250] 3. Analysis of the emotion recognition engine: The emotion recognition engine detects that the user is feeling "fatigue".

[1251] 4. Processing of text correction: The server corrects the text to "The business meeting will be held on Friday, so please take appropriate breaks to avoid fatigue."

[1252] 5. Display on the device: The corrected text will be displayed on the device.

[1253] Example of a prompt

[1254] The following are examples of specific prompt statements for a generative AI model:

[1255] Prompt message:

[1256] Please revise the following text to conform to business document standards and to be more considerate of the user's feelings.

[1257] Input text: What is the progress of the project?

[1258] Emotion: Anxiety

[1259] Revised version:

[1260] It would be helpful if you could keep us updated on the project's progress.

[1261] As described above, the present invention enables users to easily and quickly create high-quality business documents, and further provides a service that takes into consideration the user's feelings.

[1262] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1263] Step 1:

[1264] The user accesses the system and enters text, lists, or tables that need correction into the input form on the terminal. For example, they might enter "What is the project's progress?". After entering the text, they click the "Submit" button. This action sends the user's input to the terminal.

[1265] Step 2:

[1266] The terminal receives user input and stores the text in a local variable. Next, it converts the input data into an API request format, such as JSON, and prepares to send it to the remote server. Here, the input is the text from the user, and the output is the data in the API request format.

[1267] Step 3:

[1268] The terminal sends the formatted API request to the remote server. Specifically, it sends the data as an HTTP POST request. The input for this step is data in JSON format, and the output is a request sent over the network.

[1269] Step 4:

[1270] The server parses the API request received from the terminal and extracts the text data within the request. This extracted data is then passed to the next parsing step. The input is the received request data, and the output is the extracted text data.

[1271] Step 5:

[1272] The server uses an emotion recognition engine to analyze emotional information from the extracted text data. This emotion recognition engine includes IBM Watson and Microsoft Azure Text Analytics, among others. This analysis detects that the user's emotion is "anxiety." The input is text data, and the output is the emotional information resulting from the analysis.

[1273] Step 6:

[1274] The server uses a natural language processing algorithm to modify text to conform to business document specifications that reflect sentiment information. Specifically, it uses a generated AI model (e.g., GPT-3) to modify the sentence "What is the project's progress?" to "It would be helpful if you could provide an update on the project's progress." The input is the sentiment information and the original text, and the output is the modified text.

[1275] Step 7:

[1276] The server returns the corrected text to the terminal as an API response. The response data is then formatted again, for example, into JSON format. The input is the corrected text, and the output is the API response returned to the terminal.

[1277] Step 8:

[1278] The terminal analyzes the response received from the server and retrieves the corrected text. Next, this text is displayed on the screen, presenting the result to the user. The input is the API response data, and the output is the corrected text displayed on the screen.

[1279] Step 9:

[1280] The user reviews the revised text, lists, and tables displayed on the terminal screen and decides whether to make further revisions as needed or use them as they are. The input is the displayed result, and the output is the text approved by the user or further revised.

[1281] (Application Example 2)

[1282] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1283] Conventional document editing systems provide the functionality to modify user-inputted text, lists, and tables to conform to business document specifications, but they are insufficient in terms of making revisions that take into account the emotions of the user and the target audience. Furthermore, in certain fields such as the advertising industry, there is a demand not only for documents to conform to business document specifications, but also for documents that are optimized and appropriately consider the emotions of the target audience.

[1284] In Application Example 2, the specific processing performed by the specific processing unit 290 of the data processing device 12 is realized by the following means. In this invention, the server includes an input means for receiving text, lists, and tables that require modification entered by the user; a text modification means for modifying the text, lists, and tables entered by the input means to conform to business document specifications; and a display means for displaying the results of the text, lists, and tables modified by the text modification means in an emotionally sensitive manner to the target audience. This makes it possible to automatically generate business documents and advertisements that take into account the emotions of the target audience, and to provide influential and effective text.

[1285] A "user" is the entity that uses the system to input and modify text, lists, tables, etc.

[1286] "Input method" refers to the interface that allows users to input text, lists, or tables that need to be modified into the system.

[1287] "Text correction means" refers to the part that has the function of automatically correcting text, lists, and tables entered by the input means to conform to business document specifications.

[1288] "Business document specifications" refer to standards for documents that are appropriate for business settings and have a well-structured format and content.

[1289] An "emotion recognition engine" is a technology that analyzes and extracts the emotions of users and target audiences from input text, lists, and tables.

[1290] "Display means" refers to an interface for displaying modified text, lists, or tables to users or target audiences.

[1291] "Target audience" refers to the recipients of the content of advertisements and business documents.

[1292] A "natural language processing algorithm" is a technology that enables computers to understand and process human language.

[1293] A "remote server" is a remote computer that is accessed via the internet and performs the primary processing of a system.

[1294] "Optimization" refers to the process of revising text, lists, and tables to make them as effective as possible while taking into account the emotions of the target audience.

[1295] This invention relates to a system for automatically modifying and optimizing business documents such as advertising copy, and is particularly capable of providing more effective documents by processing user input with consideration for the emotions of the target audience. The system operates by having the user input text, lists, or tables that they wish to modify or optimize, and then appropriately modifying and displaying them.

[1296] System Configuration

[1297] 1. Overview

[1298] The system consists of input means, text correction means, emotion recognition engine, and display means. Data entered by the user is processed by these means, and an optimized document is generated.

[1299] 2. Hardware and software to be used

[1300] Hardware: Smartphone (iOS or Android)

[1301] software:

[1302] Frontend: React Native

[1303] Backend: Flask

[1304] Natural Language Processing Libraries: Hugging Face's Transformers, OpenAI's GPT-3

[1305] Data processing and calculations

[1306] 1. User input

[1307] Users input advertising copy and business documents using a smartphone application. This input uses an input form built with React Native.

[1308] 2. Emotion analysis

[1309] Input data is sent to the backend server. The input data from the frontend is sent to the Flask server as an API request, and sentiment analysis is performed using Hugging Face's Transformers. The analysis results show what emotions the target audience is most likely to have.

[1310] 3. Text correction

[1311] Based on the analysis results, the server uses OpenAI's GPT-3 to optimize the text in a way that takes the target audience's emotions into consideration. This transforms the user's input into effective ad copy and business documents.

[1312] 4.Display

[1313] Once the optimized document is generated, it is sent back from the backend server to the frontend and finally displayed on the user's smartphone. This allows the user to review the revised and optimized document content.

[1314] Specific example

[1315] Consider a scenario where an advertising agency representative tries to optimize the ad copy for a new product, "This TV is very high quality and inexpensive," to suit their target audience. The representative enters this text into an app and submits it. The server analyzes it using an emotion recognition engine and extracts the emotion "positive." Subsequently, an optimized ad copy is generated using GPT-3: "This TV will provide a great viewing experience. Take advantage of this opportunity and purchase it."

[1316] Examples of prompt statements

[1317] "Optimize the following ad copy to make it resonate positively with your target audience: This TV is very high quality and inexpensive."

[1318] As described above, the system of the present invention can optimize user input data based on the sentiment of the target audience and generate effective business documents.

[1319] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1320] Step 1:

[1321] Users input ad copy or business documents that need correction using a smartphone application. They enter the ad copy into the text box on their smartphone and press the submit button. This input data is stored in a local variable on the device.

[1322] Step 2:

[1323] The device prepares to send the data entered by the user to a remote server. This transmission uses an API request, and the entered text data is sent to the server-side endpoint. The input data includes the ad text entered by the user.

[1324] Step 3:

[1325] The server parses the API request received from the terminal and extracts the text data within the request. The input data received by the server is passed to the emotion recognition engine, where emotion analysis is performed. The emotion recognition engine (Hugging Face's Transformers) is used to analyze the emotion of the text and obtain the result. For example, an emotion such as "positive" might be extracted from the input text as the analysis result.

[1326] Step 4:

[1327] Based on the sentiment analysis results, the server uses a natural language processing engine (OpenAI's GPT-3) to generate prompts for modifying and optimizing the input ad copy in a sentiment-conscious manner. A prompt might look like this: "Optimize the following ad copy so that the target audience feels positive: This TV is very high quality and inexpensive." Using these prompts, GPT-3 generates the optimized ad copy.

[1328] Step 5:

[1329] The optimized ad copy generated by the server is sent to the device as an API response. The output data here is the modified and optimized ad copy.

[1330] Step 6:

[1331] The device analyzes the received API response and extracts optimized ad copy. The extracted optimized ad copy is then displayed to the user. The user can review the displayed optimized ad copy and either make further modifications as needed or use it as is.

[1332] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1333] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of the data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1334] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1335] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1336] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1337] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1338] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1339] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1340] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1341] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1342] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1343] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1344] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1345] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1346] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1347] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1348] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1349] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1350] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1351] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1352] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[1353] The following is further disclosed regarding the embodiments described above.

[1354] (Claim 1)

[1355] An input method for receiving text, lists, and tables that need to be modified by the user,

[1356] A text editing means for modifying text, lists, and tables entered by the aforementioned input means into a business document specification,

[1357] Display means for displaying text, lists, and tables corrected by the text correction means to the user,

[1358] A system that includes this.

[1359] (Claim 2)

[1360] The system according to claim 1, wherein the text correction means corrects the input text or list / table using a natural language processing algorithm.

[1361] (Claim 3)

[1362] The system according to claim 1, wherein the text modification means is implemented by a program executed on a remote server.

[1363] (Claim 4)

[1364] The system according to claim 1, wherein the display means displays the modified text or list / table on the terminal screen.

[1365] (Claim 5)

[1366] The system according to claim 2, wherein the natural language processing algorithm modifies text, lists, and tables using a specific API.

[1367] "Example 1"

[1368] (Claim 1)

[1369] An input method for receiving text that needs correction entered by the user,

[1370] A text editing means for modifying the text entered by the aforementioned input means into a business document specification,

[1371] A display means for displaying the text corrected by the text correction means to the user,

[1372] ...

[1373] A system that includes this.

[1374] (Claim 2)

[1375] The system according to claim 1, wherein the text correction means corrects the input text using a natural language processing algorithm.

[1376] (Claim 3)

[1377] The system according to claim 1, wherein the text modification means is implemented by a program executed on a remote server.

[1378] "Application Example 1"

[1379] (Claim 1)

[1380] An input method for receiving text or data that needs correction entered by the user,

[1381] A text editing means for modifying sentences and data entered by the aforementioned input means into a business document specification,

[1382] A display means for displaying the text or data corrected by the text correction means to the user,

[1383] A means of sending the corrected text and data into a report in the appropriate format and to a specific person in charge,

[1384] A system that includes this.

[1385] (Claim 2)

[1386] The system according to claim 1, wherein the text correction means corrects the input sentence or data using a natural language processing algorithm.

[1387] (Claim 3)

[1388] The system according to claim 1, wherein the text modification means is implemented by a program executed on a remote server.

[1389] "Example 2 of combining an emotion engine"

[1390] (Claim 1)

[1391] An input method for receiving text, lists, and tables that need to be modified by the user,

[1392] An emotion recognition means for analyzing emotion information contained in text, lists, or tables input by the aforementioned input means,

[1393] A text editing means for modifying the input text, list, or table based on the emotional information analyzed by the emotion recognition means,

[1394] Display means for displaying text, lists, and tables corrected by the text correction means to the user,

[1395] A system that includes this.

[1396] (Claim 2)

[1397] The system according to claim 1, wherein the text correction means performs the correction using a generated artificial intelligence model.

[1398] (Claim 3)

[1399] The system according to claim 1, wherein the emotion recognition means and the text modification means are implemented by a program executed on a remote server.

[1400] "Application example 2 when combining with an emotional engine"

[1401] (Claim 1)

[1402] An input method for receiving text, lists, and tables that need to be modified by the user,

[1403] A text editing means for modifying text, lists, and tables entered by the aforementioned input means into a business document specification,

[1404] A display means for displaying to a target audience the results of optimizing the text, lists, and tables corrected by the aforementioned text correction means in a way that takes sentiment into consideration,

[1405] A system that includes this.

[1406] (Claim 2)

[1407] The system according to claim 1, wherein the text correction means corrects the input text or list / table using a natural language processing algorithm and an emotion recognition engine.

[1408] (Claim 3)

[1409] The system according to claim 1, wherein the text modification means is implemented by a program executed on a remote server. [Explanation of symbols]

[1410] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input method for receiving text, lists, and tables that need to be modified by the user, A text editing means for modifying text, lists, and tables entered by the aforementioned input means into a business document specification, Display means for displaying text, lists, and tables corrected by the text correction means to the user, A system that includes this.

2. The system according to claim 1, wherein the text correction means corrects the input text or list / table using a natural language processing algorithm.

3. The system according to claim 1, wherein the text modification means is implemented by a program executed on a remote server.

4. The system according to claim 1, wherein the display means displays the modified text, list, or table on the terminal screen.

5. The system according to claim 2, wherein the natural language processing algorithm modifies text, lists, and tables using a specific API.

Images