System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving a sentence input by a user using a terminal; means for transmitting the received sentence to a generative artificial intelligence to generate a proposed modification; means for presenting the generated proposed modification to the user; means for selecting the proposed modification or an original sentence by the user; and means for posting the selected sentence to a communication tool.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Modern communication tools face the challenge of lacking ways for users to improve the quality of their posted text. In particular, in business documents and important communications, typos and grammatical errors can undermine credibility. Furthermore, since there is no function to quickly and effectively correct text, users must correct it themselves each time, which requires time and effort. Furthermore, users lack the freedom to choose whether to adopt the generated corrections or the original text. Given this background, there is a need for a system that improves the quality of text while also increasing user convenience. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, the present invention provides the following means. A system is provided that includes a means for receiving text input by a user using a terminal, a means for transmitting the received text to a generative artificial intelligence (AI) to generate suggested revisions, a means for presenting the generated suggested revisions to the user, a means for the user to select either the suggested revisions or the original text, and a means for posting the selected text to a communication tool. This system allows the user to quickly compare the input text with the generated suggested revisions and select the most appropriate one to post. Furthermore, the generative AI generates suggested revisions to the text using a natural language processing algorithm, thereby improving the quality of the text. Furthermore, by including a means for saving the user's selection information and making it available for later processing, user convenience can be further enhanced. In this way, the present invention can improve the quality and convenience of texts posted by users to communication tools.

[0006] "User" means a person who uses the System to input, modify or post content.

[0007] "Terminal" refers to a device used by a user for input and display.

[0008] A "sentence" is a string of characters and refers to the content that a user intends to post on a communication tool.

[0009] "Generative AI" is AI that generates suggested revisions based on input text, and uses natural language processing algorithms.

[0010] "Natural language processing algorithms" refer to technical methods for understanding and generating human language.

[0011] "Revision proposal" refers to a revised version of a sentence generated by generative artificial intelligence based on the input sentence.

[0012] "Communication Tools" refers to online platforms used by Users to share information with other Users.

[0013] "System" refers to a general term for devices and software that perform a series of processes to correct, select, and post text entered by users.

[0014] "Selection Information" refers to data resulting from a user's decision to post either the proposed revision or the original text in a communication tool. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] MODE FOR CARRYING OUT THE INVENTION

[0037] This paper describes an embodiment of the present invention. Specifically, it relates to a system for improving the quality of texts posted by users to communication tools. This system uses generative artificial intelligence to correct texts entered by users, and helps users select either the suggested corrections or the original text before finally posting.

[0038] System configuration

[0039] 1. Terminal

[0040] A device used to type text, review suggested revisions, and select posts. This includes computers, tablets, smartphones, etc.

[0041] 2. Server

[0042] It is the central part that receives text, sends requests to the generative AI, retrieves and displays suggested revisions, and finally sends the post.

[0043] 3. Generative Artificial Intelligence

[0044] Generates suggested corrections based on received text. Improves the quality of user-entered text by analyzing and correcting text using natural language processing algorithms.

[0045] System Operation

[0046] A user uses a device to type a sentence, for example, "The meeting will be held tomorrow at 10:00 AM."

[0047] The device sends the input text to the server, which then sends a request to the generative artificial intelligence to generate a revision proposal.

[0048] The generative AI analyzes the received text and generates suggested revisions. An example of a suggested revision is "We will hold a meeting tomorrow at 10:00 AM." The generated suggested revisions are sent back to the server.

[0049] After receiving the proposed revisions, the server sends both the original text and the proposed revisions to the user's device, where the user can review the revisions and choose which text to post.

[0050] The user can select either the suggested revision or the original text on the device. For example, the user can select the suggested revision, "We will have a meeting tomorrow at 10:00 AM."

[0051] The device sends the text selected by the user to the server, which receives the selected text and processes it to post it to the communication tool.

[0052] The server then sends the final selected sentence to the communication tool, where it is actually posted. Through this series of operations, users can post high-quality sentences to the communication tool.

[0053] Specific examples

[0054] For example, a user inputs the sentence "The meeting will be held tomorrow at 10:00 AM." and generates a suggested revision. In this case, the generative AI will suggest the revision "The meeting will be held tomorrow at 10:00 AM." After the user confirms this suggested revision, they select the revised sentence and post it to the communication tool. As a result, the posted sentence becomes "The meeting will be held tomorrow at 10:00 AM." Through this process, users can quickly and accurately revise their sentences, achieving high-quality communication.

[0055] This allows users to improve the quality of their writing without any effort on their part. Furthermore, by using generative AI, it can efficiently prevent typos and grammatical errors. Overall, this system can improve the quality of writing in communication tools and enhance the user experience.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] A user inputs a sentence into a terminal, for example, "The meeting will be held tomorrow at 10:00 AM."

[0059] Step 2:

[0060] The user clicks the "Review" button and the entered text is sent to the server.

[0061] Step 3:

[0062] The terminal converts the input text into packets and sends them to the server, which receives the packets.

[0063] Step 4:

[0064] The server analyzes the received text and creates a request to the generative AI, which includes the text entered by the user.

[0065] Step 5:

[0066] The server sends a request to the generative AI, which generates a corrected sentence based on the received sentence.

[0067] Step 6:

[0068] The generative artificial intelligence generates a corrected sentence such as "We will have a meeting tomorrow at 10:00 AM" and sends it back to the server.

[0069] Step 7:

[0070] The server receives the revised sentence from the generative AI and sends data including the original sentence and the revised sentence to the terminal.

[0071] Step 8:

[0072] The device analyzes the data received from the server and displays the original text and the revised text to the user, who can then choose either one.

[0073] Step 9:

[0074] The user selects the corrected text or the original text, and the selection information is sent to the terminal.

[0075] Step 10:

[0076] The device sends the user's selected text to the server, which receives the information.

[0077] Step 11:

[0078] Based on the user's selection information, the server creates an API request to post the selected text to the communication tool.

[0079] Step 12:

[0080] The server sends an API request to the communication tool and actually posts the selected text.

[0081] Step 13:

[0082] The server confirms the success of the posting and notifies the device of the result, which then displays to the user that the posting has been completed.

[0083] Example 1

[0084] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0085] To improve the quality of the text posted by users on communication tools, it is necessary to correct the content of the text so that it is accurate and natural-sounding. However, manual correction is time-consuming and labor-intensive, and it is difficult to completely prevent typos, omissions, and grammatical errors. It is also a significant burden for users to choose appropriate expressions. Therefore, there is a need for a system that can streamline the text correction process and quickly generate and post high-quality text.

[0086] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0087] In this invention, the server includes means for a user to input text using a terminal, means for the terminal to send the input text to the server, means for the server to send the received text to a generative AI model to generate a suggested revision, means for the generative AI model to send the suggested revision to the text to the server, means for the server to send the suggested revision to the terminal, means for the user to select either the suggested revision or the original text, and means for the server to post the selected text to a communication tool. This enables users to efficiently generate accurate and naturally-expressed text without much effort and to quickly post high-quality text to a communication tool.

[0088] "User" means a person who uses the system to input text, review and select suggested revisions, and post them to the communication tool.

[0089] "Device" means the device used by a User to enter text and review and select suggested revisions, including a PC, tablet, or smartphone.

[0090] The "server" is the central part that sends the text received from the device to the generative AI model and sends the generated corrections back to the device.

[0091] A "generative AI model" is an artificial intelligence system that generates suggested revisions based on the text it receives, using natural language processing algorithms to analyze and correct the text.

[0092] "Suggested revisions" are suggested improvements to the text entered by the user, generated by the generative AI model.

[0093] "Source text" refers to the original text entered by the user.

[0094] A "communication tool" is an online platform through which a user ultimately posts selected text, including, for example, a chat application or email system.

[0095] A "means" is a method or process established to achieve a particular purpose.

[0096] This invention relates to a system for improving the quality of text posted by users to communication tools. The system uses a generative AI model to correct text entered by the user, and helps the user select either the suggested correction or the original text for final posting. The components of this system are the device used by the user, a central server, and a generative AI model that corrects the text.

[0097] Terminal

[0098] A terminal is a device on which a user enters text, reviews suggested revisions, and selects a post. This may include a computer, tablet, or smartphone, and provides an interface for the user to enter specific text.

[0099] For example, if a user inputs the sentence "The meeting will be held tomorrow at 10:00 AM," the sentence is sent from the terminal to the server.

[0100] server

[0101] The server is the nerve center that receives the text, sends requests to the generative AI model, retrieves and displays suggested revisions, and finally sends the post. Specifically, it does the following:

[0102] 1. Send the text received from the device to the generative AI model.

[0103] 2. The proposed corrections returned by the generative AI model are sent to the device and displayed to the user.

[0104] 3. Receive the final text selected by the user and post it to the communication tool.

[0105] For example, send the following prompt to a generative AI model:

[0106] "Please revise the following Japanese sentence to make it more natural and accurate. The meeting will be held tomorrow at 10:00 AM."

[0107] Generative AI Models

[0108] The generative AI model generates suggested revisions based on the received text. The generative AI model uses a natural language processing algorithm to analyze the text and generate appropriate suggested revisions. For example, the proposed revision might be, "We'll have a meeting tomorrow at 10:00 AM."

[0109] The generative AI model sends suggested revisions back to the server, which then sends them to the device.

[0110] Specific examples

[0111] The user inputs the sentence "The meeting will be held tomorrow at 10 AM." The device sends this sentence to the server, which then sends a request to the generative AI model. The generative AI model generates a suggested revision, "The meeting will be held tomorrow at 10 AM," and sends this back to the server. The server then sends the suggested revision to the device, and the user reviews and selects the revision. When the user selects the revision, the device sends it to the server, which ultimately posts it to the communication tool.

[0112] This allows users to quickly and accurately correct their writing, resulting in high-quality communication. Furthermore, by utilizing generative AI models, it is possible to efficiently prevent typos, omissions, and grammatical errors.

[0113] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0114] Step 1:

[0115] The user inputs a sentence using the terminal. The user inputs the sentence "The meeting will be held tomorrow at 10:00 AM" into the text input field of the terminal. The input sentence is temporarily saved in the terminal.

[0116] Step 2:

[0117] The terminal sends the input text to the server. Specifically, the terminal uses an HTTP request to send the input text to the server in JSON format. The input is the "text entered by the user" and the output is the "text data sent to the server."

[0118] Step 3:

[0119] The server sends the received text to the generative AI model. The server analyzes the text data and generates a prompt for the generative AI model. For example, the prompt might be in the format "Please revise the following Japanese sentence to make it natural and accurate. The meeting will be held tomorrow at 10:00 AM." The input is the "received text data" and the output is the "prompt to be sent to the generative AI model."

[0120] Step 4:

[0121] The generative AI model analyzes the sent prompt sentence and generates suggested revisions to the sentence. Using a natural language processing algorithm, the generative AI model generates suggested revisions, such as "We will hold a meeting tomorrow at 10:00 AM." The input is the "prompt sentence" and the output is the "generated revisions."

[0122] Step 5:

[0123] The server receives the proposed revisions from the generative AI model and sends them to the device. Specifically, the server sends JSON-formatted data containing the proposed revisions to the device as an HTTP response. The input is the "proposal revisions received from the generative AI model," and the output is the "proposal revision data sent to the device."

[0124] Step 6:

[0125] The user checks the proposed revisions displayed on the terminal and selects either the proposed revisions or the original text. For example, the user selects the proposed revision "We will hold a meeting tomorrow at 10:00 AM." The input is "comparison information between the proposed revisions and the original text," and the output is "user selection information."

[0126] Step 7:

[0127] The terminal sends the text selected by the user to the server. Specifically, it sends JSON format data containing the selected text to the server as an HTTP request. The input is the "text selected by the user" and the output is the "selected data sent to the server."

[0128] Step 8:

[0129] The server finally posts the selected text to the communication tool. The server then sends the selected text data using the API of the appropriate communication tool. For example, using the Slack API, the text "We will have a meeting tomorrow at 10:00 AM" is posted. The input is the "selected text data" and the output is the "text posted to the communication tool."

[0130] This series of steps enables users to quickly and accurately post high-quality text to communication tools.

[0131] (Application example 1)

[0132] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0133] In today's brick-and-mortar stores, it can be difficult for store associates to maintain high-quality communication during customer interactions. While voice recognition technology and generative artificial intelligence (AI) can improve the quality of customer service conversations, efficient methods for utilizing these technologies in stores have yet to be established. Furthermore, there is a lack of interfaces that allow staff to instantly refer to suggested corrections and respond appropriately. This can lead to lower customer satisfaction and inconsistent customer service quality.

[0134] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0135] In this invention, the server includes means for receiving text entered by a user using a terminal, means for transmitting the received text to a generative artificial intelligence (AI) to generate suggested revisions, means for presenting the generated suggested revisions to the user, means for the user to select either the suggested revisions or the original text, means for posting the selected text to a communication tool, means for speech recognition during customer service, means for transmitting the results of speech recognition to the AI ​​to generate suggested revisions, and interface means for displaying and allowing selection of suggested revisions. This enables store staff to instantly receive content of conversations with customers as suggested revisions and respond using appropriate language, thereby improving the quality of customer service.

[0136] "Device" refers to the device on which a user enters text, reviews suggested revisions, and posts, including computers, tablets, and smartphones.

[0137] "Generative AI" refers to an AI system that analyzes a given sentence and generates suggested revisions. It uses natural language processing algorithms.

[0138] "Communication tools" refers to platforms for textual exchange between users, including chat apps and social media.

[0139] "Speech recognition means" refers to technology for converting voice data into text data, including, for example, a microphone and voice recognition software.

[0140] "Interface means" refers to a user interface that allows a user to confirm, select, and input suggested revisions. Specifically, this includes a display and a touch panel.

[0141] MODE FOR CARRYING OUT THE INVENTION

[0142] System Configuration

[0143] This invention provides a system that allows store staff to use smart glasses to improve the quality of their interactions with customers. The system consists of the following components:

[0144] 1. Terminal

[0145] It is a set of smart glasses worn by staff, a device that recognizes voice and displays suggested revisions.

[0146] 2. Server

[0147] It is the central part that receives voice data and sends requests to the generative artificial intelligence to generate suggested revisions.

[0148] 3. Generative Artificial Intelligence

[0149] The system uses natural language processing algorithms to analyze speech recognition results and generate appropriate correction suggestions.

[0150] operation

[0151] 1. Voice Recognition

[0152] The server uses the microphone built into the smart glasses to collect voice data from conversations between customers and staff, and converts this voice data into text data using voice recognition software (e.g., Google's voice recognition API).

[0153] 2. Revision generation

[0154] The text data obtained by speech recognition is sent to a server, which then sends the text data to a generative AI model (e.g., OpenAI's GPT-3) that generates appropriate corrections. The generative AI model uses a natural language processing algorithm.

[0155] 3. Proposal of amendments

[0156] The generated revision suggestions are sent from the server to the smart glasses, where the staff member can check the revision suggestions and the original text on the smart glasses' display and choose which sentence to adopt.

[0157] 4. Final Response

[0158] The staff member continues the conversation with the customer based on the selected sentence. The selected information is saved and can be used for later processing.

[0159] Specific examples

[0160] For example, if a customer asks, "How do I use this product?", here's what the system does:

[0161] Speech recognition result (transcribed): "How do I use this product?"

[0162] Generative AI generated a correction: "Tell me how to use this product."

[0163] The staff member checks the proposed correction on the display of the smart glasses, selects the appropriate sentence, and explains to the customer using the final response, "Please tell me how to use this product."

[0164] Prompt Sentence Examples

[0165] Here's an example prompt to send to a generative AI:

[0166] Improve this sentence: What is the use of this product?

[0167] This allows store staff to maintain high-quality interactions in real time, improving customer satisfaction.

[0168] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0169] Step 1:

[0170] The user puts on the device (smart glasses) and begins interacting with the customer.

[0171] Input: Customer speech.

[0172] Specific operation: The microphone in the smart glasses collects voice data from conversations between customers and staff.

[0173] Output: Audio data.

[0174] Step 2:

[0175] The server receives the voice data and converts it into text data using speech recognition software.

[0176] Input: Audio data sent from smart glasses.

[0177] Specific operation: Converts voice data into text using speech recognition software (e.g., Google's speech recognition API).

[0178] Output: Text data.

[0179] Step 3:

[0180] The server sends the text data to a generative artificial intelligence system, which generates appropriate revision suggestions.

[0181] Input: Text data.

[0182] Specific operation: The server sends the text data to OpenAI's API, and a generative AI model (e.g., GPT-3) generates correction suggestions.

[0183] Output: The proposed amendment text.

[0184] Step 4:

[0185] The server sends the suggested revision text to the smart glasses and displays it to the user.

[0186] Input: Proposed amendment text.

[0187] Specific operation: The server sends the suggested revision text to the user's smart glasses and displays it on the display.

[0188] Output: Correction suggestions displayed on the smart glasses display.

[0189] Step 5:

[0190] The user selects the suggested revision or the original text on the smart glasses display.

[0191] Input: Proposed amendment and original text.

[0192] Specific action: The user chooses whether to accept the suggested revision or the original text through the smart glasses interface.

[0193] Output: The selected text.

[0194] Step 6:

[0195] The server saves the user's choice and uses the selected text in the next response.

[0196] Input: The selected text.

[0197] What happens: The server saves the selection information in a database and reflects the selected text in the user's next interaction.

[0198] Output: Selection information stored in the database and text to be used for the next response.

[0199] Step 7:

[0200] The user provides instructions to the customer based on the selected text.

[0201] Input: The selected text.

[0202] What happens: The user explains the final text displayed on the smart glasses to the customer.

[0203] Output: Instructions to the customer.

[0204] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0205] MODE FOR CARRYING OUT THE INVENTION

[0206] This invention relates to a system for improving the quality of text posted by users on communication tools. In particular, it aims to improve the quality of the final post by providing appropriate revision suggestions that are in line with the user's intentions by utilizing generative artificial intelligence and an emotion engine.

[0207] System configuration

[0208] 1. Terminal

[0209] A device used to type text, review suggested revisions, and select posts. This includes computers, tablets, smartphones, etc.

[0210] 2. Server

[0211] It is the central part that receives text, sends requests to the emotion engine and generative AI, retrieves and displays suggested revisions, and finally sends the post.

[0212] 3. Generative Artificial Intelligence

[0213] Generates suggested corrections based on received text. Improves the quality of user-entered text by analyzing and correcting text using natural language processing algorithms.

[0214] 4. Emotion Engine

[0215] It recognizes the emotions in the text entered by the user and provides this information to the generative AI. The emotion engine can then adjust the tone and expression of the text based on the user's emotions.

[0216] System Operation

[0217] A user types a sentence into a terminal, for example, "I'm a little unhappy with this project."

[0218] The device sends the input text to the server, which then sends a request for emotion analysis to the emotion engine after receiving the text.

[0219] The emotion engine analyzes the text and recognizes the user's emotion. In this case, it recognizes the emotion "dissatisfied." The emotion engine then sends the results back to the server.

[0220] Based on the emotion information received from the emotion engine, the server sends a request to the generative AI to generate a revision proposal. The generative AI analyzes the text and generates a revised sentence while adjusting the tone and expression.

[0221] The generative artificial intelligence generates a corrective sentence such as "There are some areas for improvement in this project" and sends it back to the server.

[0222] The server then sends the generated revised text and the revised text adjusted based on the emotion information to the terminal. The user can then review the original text and the revised text and choose which one to post.

[0223] The user selects the corrected text or the original text on the terminal and transmits the selection information to the server.

[0224] The server checks the user's selected text and creates an API request to post it to the communication tool.

[0225] The server sends the selected text to the communication tool, where it is actually posted. Through this series of operations, users can post text in a tone that matches their emotions and of high quality to their communication tool.

[0226] Specific examples

[0227] For example, if a user inputs the sentence, "I'm a little dissatisfied with this project," and revision suggestions are generated, the emotion engine will recognize "dissatisfied." Based on that emotion, the generative AI will generate a revision suggestion in a more positive tone, such as, "There are some areas for improvement in this project." The user can select this revision suggestion and post it in a communication tool, resulting in more appropriate and positive communication.

[0228] This system not only enables users to improve the quality of their writing, but also enables them to communicate effectively based on their own emotions. The combination of an emotion engine and generative AI enables advanced sentence generation and correction that cannot be achieved with conventional methods.

[0229] The processing flow will be explained below.

[0230] MODE FOR CARRYING OUT THE INVENTION (INCLUDING EMOTION ENGINE)

[0231] Processing flow

[0232] Step 1:

[0233] A user types a sentence into a terminal. For example, the user types, "I'm a little unhappy with this project."

[0234] Step 2:

[0235] The user clicks the "Review" button and sends the entered text to the server. The device receives this text and sends a request to the server.

[0236] Step 3:

[0237] The server receives the input text and sends it to the emotion engine for a sentiment analysis request.

[0238] Step 4:

[0239] The emotion engine analyzes the text and recognizes emotions. For example, it detects the emotion "dissatisfied." The detected emotion information is sent back to the server.

[0240] Step 5:

[0241] The server creates a request to the generative AI based on the emotion information received from the emotion engine. The request includes the input text and the recognized emotion information.

[0242] Step 6:

[0243] The server sends a request to the generative AI, which generates revision suggestions based on the received text and emotional information.

[0244] Step 7:

[0245] The generative artificial intelligence generates suggested revisions. For example, it generates positive suggestions such as, "There are some areas for improvement in this project." The generated suggested revisions are sent back to the server.

[0246] Step 8:

[0247] The server receives the generated revision suggestions and sends the original text and the revision suggestions to the user's device, which receives this data and displays it to the user.

[0248] Step 9:

[0249] The user reviews the original text and the suggested revisions displayed on the device and selects which one to adopt. The user selects the revision "This project has some improvements."

[0250] Step 10:

[0251] The user sends the selection information to the terminal, which then sends the selection information to the server.

[0252] Step 11:

[0253] The server receives the user's selection information, confirms the final post content, and creates a request to post the confirmed text to the communication tool.

[0254] Step 12:

[0255] The server sends the selected text to the communication tool and actually posts it.

[0256] Step 13:

[0257] The server confirms the success of the posting and notifies the device of the result, and the device displays a message to the user that the posting has been completed.

[0258] In this way, users can use the emotion engine's emotion analysis and generative AI's correction functions to post high-quality, emotionally appropriate text to communication tools.

[0259] Example 2

[0260] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0261] Conventional systems have been inadequate in improving the quality of text posted by users to communication tools, and have had difficulty correcting text based on emotions. Furthermore, suggestions for corrected text based on natural language processing are limited, often failing to fully express the user's intentions. To address these issues, the present invention aims to provide a high-quality text correction and posting system that takes user emotions into account.

[0262] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0263] In this invention, the server includes means for receiving text entered by a user using a terminal, means for transmitting the received text to an emotion analysis engine to acquire emotion information, means for transmitting the received text to a generative artificial intelligence based on the emotion information to generate a revision proposal, means for presenting the generated revision proposal to the user, means for the user to select either the revision proposal or the original text, and means for posting the selected text to a communication tool. This enables text revision in an appropriate tone according to the user's emotion and effective communication.

[0264] "User" means a person who uses the System to enter text and review, select and submit suggested revisions.

[0265] "Device" means a device on which a User enters text, reviews suggested revisions, and selects the final post, including a PC, tablet, or smartphone.

[0266] The "server" is the central part that receives text, sends requests to the sentiment analysis engine and generative AI, retrieves and displays suggested revisions, and finally sends the post.

[0267] An "emotion analysis engine" is software that analyzes the emotions in text entered by the user and provides that information to generative artificial intelligence.

[0268] "Generative AI" is an AI system that uses natural language processing algorithms to analyze input text and generate suggested revisions.

[0269] A "revision" is a suggested sentence that improves on the original sentence, generated by generative artificial intelligence.

[0270] "Emotional information" is emotional data that the emotion analysis engine recognizes from the text entered by the user.

[0271] A "communication tool" is a platform or software where users ultimately post text.

[0272] "Natural language processing algorithms" are computational techniques for analyzing, understanding, and generating human language.

[0273] "Selection information" is data resulting from the user's selection of the proposed revision or the original text.

[0274] MODE FOR CARRYING OUT THE INVENTION

[0275] This invention relates to a system for improving the quality of text posted by users on communication tools. In particular, it aims to improve the quality of the final post by providing appropriate revision suggestions that are in line with the user's intentions by utilizing generative artificial intelligence and an emotion engine.

[0276] System configuration

[0277] The system of the present invention is comprised of the following major components:

[0278] 1. Device:

[0279] This includes any device on which a user can enter text, review suggested revisions, and select to post, such as a computer, tablet, or smartphone.

[0280] 2. Server:

[0281] The server has the following roles:

[0282] Receiving text

[0283] Sending requests to sentiment analysis engines and generative AI

[0284] Get and view suggested fixes

[0285] Submitting the final post

[0286] 3. Generative AI:

[0287] It receives text entered by the user and generates high-quality text by analyzing and correcting it using natural language processing algorithms.

[0288] 4. Sentiment Analysis Engine:

[0289] It analyzes the emotions of user-input text and provides the results to generative AI, which can then adjust the tone and expression of the text based on the emotional information.

[0290] System Operation

[0291] The user inputs a sentence into the terminal. For example, the user inputs the sentence, "I'm a little dissatisfied with this project." The terminal sends this input sentence to the server.

[0292] The server sends the received text to the emotion analysis engine and requests emotion analysis. The emotion analysis engine analyzes the user's emotion and recognizes the emotion "dissatisfied." The result is then sent back to the server.

[0293] Next, the server requests the generative AI to generate a revision proposal based on the emotional information. The generative AI analyzes and corrects the sentence based on the emotional information, and generates a revision proposal such as "There are several areas for improvement in this project." The revised sentence is then sent back to the server.

[0294] The server sends the generated revised text and a revised text adjusted based on the emotion information to the device. The user can check the original text and the revised text on the device and select which one to post. The user selects the revised text and sends the selection information to the server.

[0295] Finally, the server creates an API request for posting the selected sentence to the communication tool and sends it to the communication tool, thereby enabling the user to post sentences to the communication tool with a tone and high quality that corresponds to the user's emotion.

[0296] Specific examples

[0297] For example, if a user enters the sentence, "I'm a little dissatisfied with this project," the sentiment analysis engine will recognize the emotion of "dissatisfaction." Based on that emotional information, the generative AI will generate a revision suggestion in a more positive tone, such as, "There are some areas for improvement in this project." The user can select this revision suggestion and post it in a communication tool, resulting in more appropriate and positive communication.

[0298] Example prompt sentence:

[0299] "Please revise the following sentence to a more positive tone: I'm a little unhappy with this project."

[0300] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0301] Program processing flow

[0302] Step 1:

[0303] The user types a sentence, for example, "I'm a little unhappy with this project."

[0304] Input: Text typed by the user into the terminal.

[0305] Output: The text data entered by the user.

[0306] Specific actions: The user uses the device to type text into an input field using a keyboard or touch input.

[0307] Step 2:

[0308] The terminal transmits the input text data to the server.

[0309] Input: Text data entered by the user into the terminal.

[0310] Output: The text data sent to the server.

[0311] Specific operation: The terminal sends the input text data to the server using a communication protocol such as an HTTP request.

[0312] Step 3:

[0313] The server sends the received text to an emotion analysis engine to obtain emotion information.

[0314] Input: Received text data.

[0315] Output: Acquired emotion information.

[0316] Specific operation: The server sends a request to the emotion analysis engine via a REST API or similar, and receives emotion information as the analysis result. For example, the emotion "dissatisfied" is analyzed.

[0317] Step 4:

[0318] The server sends the acquired emotional information and the original text data to a generative artificial intelligence (AI) system, which then generates suggested revisions.

[0319] Input: emotion information and original sentence data.

[0320] Output: The generated correction suggestions.

[0321] Specific operation: The server sends the emotion information and the original sentence data to the generative AI, which then generates a correction based on this. For example, the generated correction sentence might be, "There are several areas for improvement in this project."

[0322] Step 5:

[0323] The server transmits the generated corrected text to the terminal.

[0324] Input: The generated corrected sentence.

[0325] Output: The modified statement sent to the terminal.

[0326] Specific operation: The server sends the corrected text to the terminal so that the user can confirm it.

[0327] Step 6:

[0328] The user can review the original and revised text and choose which one to post.

[0329] Input: The original sentence and the generated correction sentence.

[0330] Output: User selection information.

[0331] Specific operation: The user compares the original text with the revised text on the terminal and presses the selection button to confirm the selected information.

[0332] Step 7:

[0333] The text data selected by the user is sent to the server.

[0334] Input: Selected sentence data.

[0335] Output: The selection information sent to the server.

[0336] Specific operation: The user's selection information is sent from the terminal to the server.

[0337] Step 8:

[0338] The server creates and sends an API request to post the selected text to the communication tool.

[0339] Input: User-selected text data.

[0340] Output: Text posted to the communication tool.

[0341] Specific operation: The server sends the selected text to the communication tool, which actually posts it to the platform. For example, it sends a POST request to the specified API endpoint.

[0342] (Application example 2)

[0343] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0344] In modern brick-and-mortar stores, responding appropriately and promptly to customer feedback and inquiries is important to improving the quality of customer service. However, providing appropriate responses that reflect customer emotions can be difficult, which can result in an increase in dissatisfied customers and negatively impact the store's reputation and sales. Therefore, a system that takes emotions into account when responding to customers and replies in an appropriate manner is needed.

[0345] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving content entered by a user using an information processing device, means for sending the received content to a generative artificial intelligence to generate a revision proposal, means for presenting the generated revision proposal to the user, means for the user to select either the revision proposal or the original text, means for posting the selected content to a communication means, means for performing sentiment analysis, and means for using the results of the sentiment analysis when generating a revision proposal. This makes it possible to quickly provide appropriate responses that take sentiment into consideration in response to feedback and inquiries from customers.

[0346] "User" refers to a person who uses an information processing device to input text and then confirm, select, and post it.

[0347] "Information processing device" refers to a device that allows a user to input text, review suggested revisions, and select them, such as a smartphone, tablet, or PC.

[0348] The "receiving means" refers to a function that allows the server to receive the content that the user inputs using the information processing device.

[0349] "Generative AI" refers to AI that generates revision suggestions based on received content. It uses natural language processing technology.

[0350] "Means for generating suggested revisions" refers to the function by which the generative artificial intelligence analyzes the input content and generates appropriate revised sentences.

[0351] "Means for presenting generated revision suggestions" refers to a function for displaying revised sentences generated by the generative artificial intelligence to the user.

[0352] "Means for selection" refers to the functionality that allows the user to select the presented revised text or the original text.

[0353] "Means of communication" refers to the function that allows users to post text of their choice to external communication tools.

[0354] "Means for performing emotion analysis" refers to the function for analyzing the emotion of input text and providing the results to generative artificial intelligence.

[0355] "Means for using the results of sentiment analysis" refers to a function that reflects the results of sentiment analysis when the generative artificial intelligence generates revised sentences based on the results of sentiment analysis.

[0356] System Overview

[0357] The present invention is a system for receiving information entered by a user using an information processing device, and uses the following hardware and software.

[0358] Hardware: Smartphones, tablets, computers

[0359] Software: Generative AI (e.g., OpenAI GPT-3, GPT-4), emotion analysis engine (e.g., IBM Watson Emotion Analysis)

[0360] Program processing

[0361] Information processing device (user terminal)

[0362] A user inputs a sentence using an information processing device. For example, a customer inputs, "It's difficult to understand how to use this product."

[0363] server

[0364] 1. Data Reception

[0365] The server receives the input content sent from the information processing device.

[0366] 2. Emotion analysis

[0367] The received content is sent to a sentiment analysis engine, which analyzes the sentiment of the input content. For example, the sentence "It's hard to understand how to use this product" is analyzed as "dissatisfied."

[0368] 3. Revision generation

[0369] Based on the results of the sentiment analysis, the generative AI is instructed to generate suggested revisions. The generative AI then generates appropriate revisions that reflect the results of the sentiment analysis. For example, the generated revision might read, "There are several areas for improvement in how this product is used."

[0370] 4. Presentation of revised sentences

[0371] The server receives the generated corrections and presents them to the user, who can then choose between the corrections and the original text.

[0372] 5. Submit

[0373] The server receives the content selected by the user and posts it to the specified communication tool using an appropriate communication method.

[0374] Specific examples

[0375] Prompt Sentence Examples

[0376] "Depending on the customer's feelings, please revise the following sentences to make them more positive.

[0377] Input: I'm having trouble understanding how to use this product.

[0378] Emotion: Dissatisfaction

[0379] Output: There are some areas for improvement regarding how this product is used.

[0380] This makes it possible to quickly provide appropriate responses that take emotions into account when interacting with customers. By selecting the correct sentence that best reflects the customer's emotion, users can improve the quality of customer interaction in physical stores.

[0381] Usage example

[0382] For example, suppose a customer complains that "it's difficult to understand how to use this product." A system embodying this invention receives this input, performs sentiment analysis, generates appropriate corrections, and ultimately presents the user with a more positively-toned correction such as "There are some points that need improvement in how to use this product." The user can select this correction and reply to the customer, thereby reducing the customer's dissatisfaction and improving their satisfaction.

[0383] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0384] Step 1:

[0385] The user inputs a sentence using the information processing device. For example, the user inputs a sentence such as "It's difficult to understand how to use this product." The input sentence is sent to the server by the information processing device.

[0386] Step 2:

[0387] The server receives the input content sent from the information processing device. Specifically, the server's communication module receives the input text data and temporarily stores it in a database. At this time, it is confirmed that the transmitted text has been received correctly.

[0388] Step 3:

[0389] The server sends the received text to a sentiment analysis engine, which analyzes the text and identifies the emotion contained within. For example, emotional information such as "dissatisfaction" is analyzed. Data processing to extract this emotional background is performed based on a specific algorithm.

[0390] Step 4:

[0391] The server sends the results of the sentiment analysis to the generative AI, which generates a correction based on the results of the sentiment analysis and the input text. For example, a positive-toned correction such as "There are some points to improve on in how you use this product" is generated. This process requires a prompt sentence to be used by the generative AI model.

[0392] Step 5:

[0393] The server receives the generated revised text and presents it to the user. Specifically, the server sends the generated revised text to an information processing device and displays it for the user to confirm. At this time, both the original text and the revised text are displayed.

[0394] Step 6:

[0395] The user selects either the presented revised sentence or the original sentence. The user selects either the presented revised sentence or the original sentence and transmits the selection information to the server via the information processing device.

[0396] Step 7:

[0397] The server receives the user's selection and posts it to the specified communication tool using the appropriate communication method. Specifically, it generates an API request and sends the selected text to the external communication tool. Through this process, the selected text is sent back to the customer.

[0398] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0399] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0400] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0401] [Second embodiment]

[0402] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0403] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0404] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0405] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0406] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0407] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0408] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0409] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0410] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0411] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0412] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0413] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0414] MODE FOR CARRYING OUT THE INVENTION

[0415] This paper describes an embodiment of the present invention. Specifically, it relates to a system for improving the quality of texts posted by users to communication tools. This system uses generative artificial intelligence to correct texts entered by users, and helps users select either the suggested corrections or the original text before finally posting.

[0416] System configuration

[0417] 1. Terminal

[0418] A device used to type text, review suggested revisions, and select posts. This includes computers, tablets, smartphones, etc.

[0419] 2. Server

[0420] It is the central part that receives text, sends requests to the generative AI, retrieves and displays suggested revisions, and finally sends the post.

[0421] 3. Generative Artificial Intelligence

[0422] Generates suggested corrections based on received text. Improves the quality of user-entered text by analyzing and correcting text using natural language processing algorithms.

[0423] System Operation

[0424] A user uses a device to type a sentence, for example, "The meeting will be held tomorrow at 10:00 AM."

[0425] The device sends the input text to the server, which then sends a request to the generative artificial intelligence to generate a revision proposal.

[0426] The generative AI analyzes the received text and generates suggested revisions. An example of a suggested revision is "We will hold a meeting tomorrow at 10:00 AM." The generated suggested revisions are sent back to the server.

[0427] After receiving the proposed revisions, the server sends both the original text and the proposed revisions to the user's device, where the user can review the revisions and choose which text to post.

[0428] The user can select either the suggested revision or the original text on the device. For example, the user can select the suggested revision, "We will have a meeting tomorrow at 10:00 AM."

[0429] The device sends the text selected by the user to the server, which receives the selected text and processes it to post it to the communication tool.

[0430] The server then sends the final selected sentence to the communication tool, where it is actually posted. Through this series of operations, users can post high-quality sentences to the communication tool.

[0431] Specific examples

[0432] For example, a user inputs the sentence "The meeting will be held tomorrow at 10:00 AM." and generates a suggested revision. In this case, the generative AI will suggest the revision "The meeting will be held tomorrow at 10:00 AM." After the user confirms this suggested revision, they select the revised sentence and post it to the communication tool. As a result, the posted sentence becomes "The meeting will be held tomorrow at 10:00 AM." Through this process, users can quickly and accurately revise their sentences, achieving high-quality communication.

[0433] This allows users to improve the quality of their writing without any effort on their part. Furthermore, by using generative AI, it can efficiently prevent typos and grammatical errors. Overall, this system can improve the quality of writing in communication tools and enhance the user experience.

[0434] The processing flow will be explained below.

[0435] Step 1:

[0436] A user inputs a sentence into a terminal, for example, "The meeting will be held tomorrow at 10:00 AM."

[0437] Step 2:

[0438] The user clicks the "Review" button and the entered text is sent to the server.

[0439] Step 3:

[0440] The terminal converts the input text into packets and sends them to the server, which receives the packets.

[0441] Step 4:

[0442] The server analyzes the received text and creates a request to the generative AI, which includes the text entered by the user.

[0443] Step 5:

[0444] The server sends a request to the generative AI, which generates a corrected sentence based on the received sentence.

[0445] Step 6:

[0446] The generative artificial intelligence generates a corrected sentence such as "We will have a meeting tomorrow at 10:00 AM" and sends it back to the server.

[0447] Step 7:

[0448] The server receives the revised sentence from the generative AI and sends data including the original sentence and the revised sentence to the terminal.

[0449] Step 8:

[0450] The device analyzes the data received from the server and displays the original text and the revised text to the user, who can then choose either one.

[0451] Step 9:

[0452] The user selects the corrected text or the original text, and the selection information is sent to the terminal.

[0453] Step 10:

[0454] The device sends the user's selected text to the server, which receives the information.

[0455] Step 11:

[0456] Based on the user's selection information, the server creates an API request to post the selected text to the communication tool.

[0457] Step 12:

[0458] The server sends an API request to the communication tool and actually posts the selected text.

[0459] Step 13:

[0460] The server confirms the success of the posting and notifies the device of the result, which then displays to the user that the posting has been completed.

[0461] Example 1

[0462] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0463] To improve the quality of the text posted by users on communication tools, it is necessary to correct the content of the text so that it is accurate and natural-sounding. However, manual correction is time-consuming and labor-intensive, and it is difficult to completely prevent typos, omissions, and grammatical errors. It is also a significant burden for users to choose appropriate expressions. Therefore, there is a need for a system that can streamline the text correction process and quickly generate and post high-quality text.

[0464] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0465] In this invention, the server includes means for a user to input text using a terminal, means for the terminal to send the input text to the server, means for the server to send the received text to a generative AI model to generate a suggested revision, means for the generative AI model to send the suggested revision to the text to the server, means for the server to send the suggested revision to the terminal, means for the user to select either the suggested revision or the original text, and means for the server to post the selected text to a communication tool. This enables users to efficiently generate accurate and naturally-expressed text without much effort and to quickly post high-quality text to a communication tool.

[0466] "User" means a person who uses the system to input text, review and select suggested revisions, and post them to the communication tool.

[0467] "Device" means the device used by a User to enter text and review and select suggested revisions, including a PC, tablet, or smartphone.

[0468] The "server" is the central part that sends the text received from the device to the generative AI model and sends the generated corrections back to the device.

[0469] A "generative AI model" is an artificial intelligence system that generates suggested revisions based on the text it receives, using natural language processing algorithms to analyze and correct the text.

[0470] "Suggested revisions" are suggested improvements to the text entered by the user, generated by the generative AI model.

[0471] "Source text" refers to the original text entered by the user.

[0472] A "communication tool" is an online platform through which a user ultimately posts selected text, including, for example, a chat application or email system.

[0473] A "means" is a method or process established to achieve a particular purpose.

[0474] This invention relates to a system for improving the quality of text posted by users to communication tools. The system uses a generative AI model to correct text entered by the user, and helps the user select either the suggested correction or the original text for final posting. The components of this system are the device used by the user, a central server, and a generative AI model that corrects the text.

[0475] Terminal

[0476] A terminal is a device on which a user enters text, reviews suggested revisions, and selects a post. This may include a computer, tablet, or smartphone, and provides an interface for the user to enter specific text.

[0477] For example, if a user inputs the sentence "The meeting will be held tomorrow at 10:00 AM," the sentence is sent from the terminal to the server.

[0478] server

[0479] The server is the nerve center that receives the text, sends requests to the generative AI model, retrieves and displays suggested revisions, and finally sends the post. Specifically, it does the following:

[0480] 1. Send the text received from the device to the generative AI model.

[0481] 2. The proposed corrections returned by the generative AI model are sent to the device and displayed to the user.

[0482] 3. Receive the final text selected by the user and post it to the communication tool.

[0483] For example, send the following prompt to a generative AI model:

[0484] "Please revise the following Japanese sentence to make it more natural and accurate. The meeting will be held tomorrow at 10:00 AM."

[0485] Generative AI Models

[0486] The generative AI model generates suggested revisions based on the received text. The generative AI model uses a natural language processing algorithm to analyze the text and generate appropriate suggested revisions. For example, the proposed revision might be, "We'll have a meeting tomorrow at 10:00 AM."

[0487] The generative AI model sends suggested revisions back to the server, which then sends them to the device.

[0488] Specific examples

[0489] The user inputs the sentence "The meeting will be held tomorrow at 10 AM." The device sends this sentence to the server, which then sends a request to the generative AI model. The generative AI model generates a suggested revision, "The meeting will be held tomorrow at 10 AM," and sends this back to the server. The server then sends the suggested revision to the device, and the user reviews and selects the revision. When the user selects the revision, the device sends it to the server, which ultimately posts it to the communication tool.

[0490] This allows users to quickly and accurately correct their writing, resulting in high-quality communication. Furthermore, by utilizing generative AI models, it is possible to efficiently prevent typos, omissions, and grammatical errors.

[0491] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0492] Step 1:

[0493] The user inputs a sentence using the terminal. The user inputs the sentence "The meeting will be held tomorrow at 10:00 AM" into the text input field of the terminal. The input sentence is temporarily saved in the terminal.

[0494] Step 2:

[0495] The terminal sends the input text to the server. Specifically, the terminal uses an HTTP request to send the input text to the server in JSON format. The input is the "text entered by the user" and the output is the "text data sent to the server."

[0496] Step 3:

[0497] The server sends the received text to the generative AI model. The server analyzes the text data and generates a prompt for the generative AI model. For example, the prompt might be in the format "Please revise the following Japanese sentence to make it natural and accurate. The meeting will be held tomorrow at 10:00 AM." The input is the "received text data" and the output is the "prompt to be sent to the generative AI model."

[0498] Step 4:

[0499] The generative AI model analyzes the sent prompt sentence and generates suggested revisions to the sentence. Using a natural language processing algorithm, the generative AI model generates suggested revisions, such as "We will hold a meeting tomorrow at 10:00 AM." The input is the "prompt sentence" and the output is the "generated revisions."

[0500] Step 5:

[0501] The server receives the proposed revisions from the generative AI model and sends them to the device. Specifically, the server sends JSON-formatted data containing the proposed revisions to the device as an HTTP response. The input is the "proposal revisions received from the generative AI model," and the output is the "proposal revision data sent to the device."

[0502] Step 6:

[0503] The user checks the proposed revisions displayed on the terminal and selects either the proposed revisions or the original text. For example, the user selects the proposed revision "We will hold a meeting tomorrow at 10:00 AM." The input is "comparison information between the proposed revisions and the original text," and the output is "user selection information."

[0504] Step 7:

[0505] The terminal sends the text selected by the user to the server. Specifically, it sends JSON format data containing the selected text to the server as an HTTP request. The input is the "text selected by the user" and the output is the "selected data sent to the server."

[0506] Step 8:

[0507] The server finally posts the selected text to the communication tool. The server then sends the selected text data using the API of the appropriate communication tool. For example, using the Slack API, the text "We will have a meeting tomorrow at 10:00 AM" is posted. The input is the "selected text data" and the output is the "text posted to the communication tool."

[0508] This series of steps enables users to quickly and accurately post high-quality text to communication tools.

[0509] (Application example 1)

[0510] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0511] In today's brick-and-mortar stores, it can be difficult for store associates to maintain high-quality communication during customer interactions. While voice recognition technology and generative artificial intelligence (AI) can improve the quality of customer service conversations, efficient methods for utilizing these technologies in stores have yet to be established. Furthermore, there is a lack of interfaces that allow staff to instantly refer to suggested corrections and respond appropriately. This can lead to lower customer satisfaction and inconsistent customer service quality.

[0512] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0513] In this invention, the server includes means for receiving text entered by a user using a terminal, means for transmitting the received text to a generative artificial intelligence (AI) to generate suggested revisions, means for presenting the generated suggested revisions to the user, means for the user to select either the suggested revisions or the original text, means for posting the selected text to a communication tool, means for speech recognition during customer service, means for transmitting the results of speech recognition to the AI ​​to generate suggested revisions, and interface means for displaying and allowing selection of suggested revisions. This enables store staff to instantly receive content of conversations with customers as suggested revisions and respond using appropriate language, thereby improving the quality of customer service.

[0514] "Device" refers to the device on which a user enters text, reviews suggested revisions, and posts, including computers, tablets, and smartphones.

[0515] "Generative AI" refers to an AI system that analyzes a given sentence and generates suggested revisions. It uses natural language processing algorithms.

[0516] "Communication tools" refers to platforms for textual exchange between users, including chat apps and social media.

[0517] "Speech recognition means" refers to technology for converting voice data into text data, including, for example, a microphone and voice recognition software.

[0518] "Interface means" refers to a user interface that allows a user to confirm, select, and input suggested revisions. Specifically, this includes a display and a touch panel.

[0519] MODE FOR CARRYING OUT THE INVENTION

[0520] System Configuration

[0521] This invention provides a system that allows store staff to use smart glasses to improve the quality of their interactions with customers. The system consists of the following components:

[0522] 1. Terminal

[0523] It is a set of smart glasses worn by staff, a device that recognizes voice and displays suggested revisions.

[0524] 2. Server

[0525] It is the central part that receives voice data and sends requests to the generative artificial intelligence to generate suggested revisions.

[0526] 3. Generative Artificial Intelligence

[0527] The system uses natural language processing algorithms to analyze speech recognition results and generate appropriate correction suggestions.

[0528] operation

[0529] 1. Voice Recognition

[0530] The server uses the microphone built into the smart glasses to collect voice data from conversations between customers and staff, and converts this voice data into text data using voice recognition software (e.g., Google's voice recognition API).

[0531] 2. Revision generation

[0532] The text data obtained by speech recognition is sent to a server, which then sends the text data to a generative AI model (e.g., OpenAI's GPT-3) that generates appropriate corrections. The generative AI model uses a natural language processing algorithm.

[0533] 3. Proposal of amendments

[0534] The generated revision suggestions are sent from the server to the smart glasses, where the staff member can check the revision suggestions and the original text on the smart glasses' display and choose which sentence to adopt.

[0535] 4. Final Response

[0536] The staff member continues the conversation with the customer based on the selected sentence. The selected information is saved and can be used for later processing.

[0537] Specific examples

[0538] For example, if a customer asks, "How do I use this product?", here's what the system does:

[0539] Speech recognition result (transcribed): "How do I use this product?"

[0540] Generative AI generated a correction: "Tell me how to use this product."

[0541] The staff member checks the proposed correction on the display of the smart glasses, selects the appropriate sentence, and explains to the customer using the final response, "Please tell me how to use this product."

[0542] Prompt Sentence Examples

[0543] Here's an example prompt to send to a generative AI:

[0544] Improve this sentence: What is the use of this product?

[0545] This allows store staff to maintain high-quality interactions in real time, improving customer satisfaction.

[0546] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0547] Step 1:

[0548] The user puts on the device (smart glasses) and begins interacting with the customer.

[0549] Input: Customer speech.

[0550] Specific operation: The microphone in the smart glasses collects voice data from conversations between customers and staff.

[0551] Output: Audio data.

[0552] Step 2:

[0553] The server receives the voice data and converts it into text data using speech recognition software.

[0554] Input: Audio data sent from smart glasses.

[0555] Specific operation: Converts voice data into text using speech recognition software (e.g., Google's speech recognition API).

[0556] Output: Text data.

[0557] Step 3:

[0558] The server sends the text data to a generative artificial intelligence system, which generates appropriate revision suggestions.

[0559] Input: Text data.

[0560] Specific operation: The server sends the text data to OpenAI's API, and a generative AI model (e.g., GPT-3) generates correction suggestions.

[0561] Output: The proposed amendment text.

[0562] Step 4:

[0563] The server sends the suggested revision text to the smart glasses and displays it to the user.

[0564] Input: Proposed amendment text.

[0565] Specific operation: The server sends the suggested revision text to the user's smart glasses and displays it on the display.

[0566] Output: Correction suggestions displayed on the smart glasses display.

[0567] Step 5:

[0568] The user selects the suggested revision or the original text on the smart glasses display.

[0569] Input: Proposed amendment and original text.

[0570] Specific action: The user chooses whether to accept the suggested revision or the original text through the smart glasses interface.

[0571] Output: The selected text.

[0572] Step 6:

[0573] The server saves the user's choice and uses the selected text in the next response.

[0574] Input: The selected text.

[0575] What happens: The server saves the selection information in a database and reflects the selected text in the user's next interaction.

[0576] Output: Selection information stored in the database and text to be used for the next response.

[0577] Step 7:

[0578] The user provides instructions to the customer based on the selected text.

[0579] Input: The selected text.

[0580] What happens: The user explains the final text displayed on the smart glasses to the customer.

[0581] Output: Instructions to the customer.

[0582] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0583] MODE FOR CARRYING OUT THE INVENTION

[0584] This invention relates to a system for improving the quality of text posted by users on communication tools. In particular, it aims to improve the quality of the final post by providing appropriate revision suggestions that are in line with the user's intentions by utilizing generative artificial intelligence and an emotion engine.

[0585] System configuration

[0586] 1. Terminal

[0587] A device used to type text, review suggested revisions, and select posts. This includes computers, tablets, smartphones, etc.

[0588] 2. Server

[0589] It is the central part that receives text, sends requests to the emotion engine and generative AI, retrieves and displays suggested revisions, and finally sends the post.

[0590] 3. Generative Artificial Intelligence

[0591] Generates suggested corrections based on received text. Improves the quality of user-entered text by analyzing and correcting text using natural language processing algorithms.

[0592] 4. Emotion Engine

[0593] It recognizes the emotions in the text entered by the user and provides this information to the generative AI. The emotion engine can then adjust the tone and expression of the text based on the user's emotions.

[0594] System Operation

[0595] A user types a sentence into a terminal, for example, "I'm a little unhappy with this project."

[0596] The device sends the input text to the server, which then sends a request for emotion analysis to the emotion engine after receiving the text.

[0597] The emotion engine analyzes the text and recognizes the user's emotion. In this case, it recognizes the emotion "dissatisfied." The emotion engine then sends the results back to the server.

[0598] Based on the emotion information received from the emotion engine, the server sends a request to the generative AI to generate a revision proposal. The generative AI analyzes the text and generates a revised sentence while adjusting the tone and expression.

[0599] The generative artificial intelligence generates a corrective sentence such as "There are some areas for improvement in this project" and sends it back to the server.

[0600] The server then sends the generated revised text and the revised text adjusted based on the emotion information to the terminal. The user can then review the original text and the revised text and choose which one to post.

[0601] The user selects the corrected text or the original text on the terminal and transmits the selection information to the server.

[0602] The server checks the user's selected text and creates an API request to post it to the communication tool.

[0603] The server sends the selected text to the communication tool, where it is actually posted. Through this series of operations, users can post text in a tone that matches their emotions and of high quality to their communication tool.

[0604] Specific examples

[0605] For example, if a user inputs the sentence, "I'm a little dissatisfied with this project," and revision suggestions are generated, the emotion engine will recognize "dissatisfied." Based on that emotion, the generative AI will generate a revision suggestion in a more positive tone, such as, "There are some areas for improvement in this project." The user can select this revision suggestion and post it in a communication tool, resulting in more appropriate and positive communication.

[0606] This system not only enables users to improve the quality of their writing, but also enables them to communicate effectively based on their own emotions. The combination of an emotion engine and generative AI enables advanced sentence generation and correction that cannot be achieved with conventional methods.

[0607] The processing flow will be explained below.

[0608] MODE FOR CARRYING OUT THE INVENTION (INCLUDING EMOTION ENGINE)

[0609] Processing flow

[0610] Step 1:

[0611] A user types a sentence into a terminal. For example, the user types, "I'm a little unhappy with this project."

[0612] Step 2:

[0613] The user clicks the "Review" button and sends the entered text to the server. The device receives this text and sends a request to the server.

[0614] Step 3:

[0615] The server receives the input text and sends it to the emotion engine for a sentiment analysis request.

[0616] Step 4:

[0617] The emotion engine analyzes the text and recognizes emotions. For example, it detects the emotion "dissatisfied." The detected emotion information is sent back to the server.

[0618] Step 5:

[0619] The server creates a request to the generative AI based on the emotion information received from the emotion engine. The request includes the input text and the recognized emotion information.

[0620] Step 6:

[0621] The server sends a request to the generative AI, which generates revision suggestions based on the received text and emotional information.

[0622] Step 7:

[0623] The generative artificial intelligence generates suggested revisions. For example, it generates positive suggestions such as, "There are some areas for improvement in this project." The generated suggested revisions are sent back to the server.

[0624] Step 8:

[0625] The server receives the generated revision suggestions and sends the original text and the revision suggestions to the user's device, which receives this data and displays it to the user.

[0626] Step 9:

[0627] The user reviews the original text and the suggested revisions displayed on the device and selects which one to adopt. The user selects the revision "This project has some improvements."

[0628] Step 10:

[0629] The user sends the selection information to the terminal, which then sends the selection information to the server.

[0630] Step 11:

[0631] The server receives the user's selection information, confirms the final post content, and creates a request to post the confirmed text to the communication tool.

[0632] Step 12:

[0633] The server sends the selected text to the communication tool and actually posts it.

[0634] Step 13:

[0635] The server confirms the success of the posting and notifies the device of the result, and the device displays a message to the user that the posting has been completed.

[0636] In this way, users can use the emotion engine's emotion analysis and generative AI's correction functions to post high-quality, emotionally appropriate text to communication tools.

[0637] Example 2

[0638] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0639] Conventional systems have been inadequate in improving the quality of text posted by users to communication tools, and have had difficulty correcting text based on emotions. Furthermore, suggestions for corrected text based on natural language processing are limited, often failing to fully express the user's intentions. To address these issues, the present invention aims to provide a high-quality text correction and posting system that takes user emotions into account.

[0640] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0641] In this invention, the server includes means for receiving text entered by a user using a terminal, means for transmitting the received text to an emotion analysis engine to acquire emotion information, means for transmitting the received text to a generative artificial intelligence based on the emotion information to generate a revision proposal, means for presenting the generated revision proposal to the user, means for the user to select either the revision proposal or the original text, and means for posting the selected text to a communication tool. This enables text revision in an appropriate tone according to the user's emotion and effective communication.

[0642] "User" means a person who uses the System to enter text and review, select and submit suggested revisions.

[0643] "Device" means a device on which a User enters text, reviews suggested revisions, and selects the final post, including a PC, tablet, or smartphone.

[0644] The "server" is the central part that receives text, sends requests to the sentiment analysis engine and generative AI, retrieves and displays suggested revisions, and finally sends the post.

[0645] An "emotion analysis engine" is software that analyzes the emotions in text entered by the user and provides that information to generative artificial intelligence.

[0646] "Generative AI" is an AI system that uses natural language processing algorithms to analyze input text and generate suggested revisions.

[0647] A "revision" is a suggested sentence that improves on the original sentence, generated by generative artificial intelligence.

[0648] "Emotional information" is emotional data that the emotion analysis engine recognizes from the text entered by the user.

[0649] A "communication tool" is a platform or software where users ultimately post text.

[0650] "Natural language processing algorithms" are computational techniques for analyzing, understanding, and generating human language.

[0651] "Selection information" is data resulting from the user's selection of the proposed revision or the original text.

[0652] MODE FOR CARRYING OUT THE INVENTION

[0653] This invention relates to a system for improving the quality of text posted by users on communication tools. In particular, it aims to improve the quality of the final post by providing appropriate revision suggestions that are in line with the user's intentions by utilizing generative artificial intelligence and an emotion engine.

[0654] System configuration

[0655] The system of the present invention is comprised of the following major components:

[0656] 1. Device:

[0657] This includes any device on which a user can enter text, review suggested revisions, and select to post, such as a computer, tablet, or smartphone.

[0658] 2. Server:

[0659] The server has the following roles:

[0660] Receiving text

[0661] Sending requests to sentiment analysis engines and generative AI

[0662] Get and view suggested fixes

[0663] Submitting the final post

[0664] 3. Generative AI:

[0665] It receives text entered by the user and generates high-quality text by analyzing and correcting it using natural language processing algorithms.

[0666] 4. Sentiment Analysis Engine:

[0667] It analyzes the emotions of user-input text and provides the results to generative AI, which can then adjust the tone and expression of the text based on the emotional information.

[0668] System Operation

[0669] The user inputs a sentence into the terminal. For example, the user inputs the sentence, "I'm a little dissatisfied with this project." The terminal sends this input sentence to the server.

[0670] The server sends the received text to the emotion analysis engine and requests emotion analysis. The emotion analysis engine analyzes the user's emotion and recognizes the emotion "dissatisfied." The result is then sent back to the server.

[0671] Next, the server requests the generative AI to generate a revision proposal based on the emotional information. The generative AI analyzes and corrects the sentence based on the emotional information, and generates a revision proposal such as "There are several areas for improvement in this project." The revised sentence is then sent back to the server.

[0672] The server sends the generated revised text and a revised text adjusted based on the emotion information to the device. The user can check the original text and the revised text on the device and select which one to post. The user selects the revised text and sends the selection information to the server.

[0673] Finally, the server creates an API request for posting the selected sentence to the communication tool and sends it to the communication tool, thereby enabling the user to post sentences to the communication tool with a tone and high quality that corresponds to the user's emotion.

[0674] Specific examples

[0675] For example, if a user enters the sentence, "I'm a little dissatisfied with this project," the sentiment analysis engine will recognize the emotion of "dissatisfaction." Based on that emotional information, the generative AI will generate a revision suggestion in a more positive tone, such as, "There are some areas for improvement in this project." The user can select this revision suggestion and post it in a communication tool, resulting in more appropriate and positive communication.

[0676] Example prompt sentence:

[0677] "Please revise the following sentence to a more positive tone: I'm a little unhappy with this project."

[0678] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0679] Program processing flow

[0680] Step 1:

[0681] The user types a sentence, for example, "I'm a little unhappy with this project."

[0682] Input: Text typed by the user into the terminal.

[0683] Output: The text data entered by the user.

[0684] Specific actions: The user uses the device to type text into an input field using a keyboard or touch input.

[0685] Step 2:

[0686] The terminal transmits the input text data to the server.

[0687] Input: Text data entered by the user into the terminal.

[0688] Output: The text data sent to the server.

[0689] Specific operation: The terminal sends the input text data to the server using a communication protocol such as an HTTP request.

[0690] Step 3:

[0691] The server sends the received text to an emotion analysis engine to obtain emotion information.

[0692] Input: Received text data.

[0693] Output: Acquired emotion information.

[0694] Specific operation: The server sends a request to the emotion analysis engine via a REST API or similar, and receives emotion information as the analysis result. For example, the emotion "dissatisfied" is analyzed.

[0695] Step 4:

[0696] The server sends the acquired emotional information and the original text data to a generative artificial intelligence (AI) system, which then generates suggested revisions.

[0697] Input: emotion information and original sentence data.

[0698] Output: The generated correction suggestions.

[0699] Specific operation: The server sends the emotion information and the original sentence data to the generative AI, which then generates a correction based on this. For example, the generated correction sentence might be, "There are several areas for improvement in this project."

[0700] Step 5:

[0701] The server transmits the generated corrected text to the terminal.

[0702] Input: The generated corrected sentence.

[0703] Output: The modified statement sent to the terminal.

[0704] Specific operation: The server sends the corrected text to the terminal so that the user can confirm it.

[0705] Step 6:

[0706] The user can review the original and revised text and choose which one to post.

[0707] Input: The original sentence and the generated correction sentence.

[0708] Output: User selection information.

[0709] Specific operation: The user compares the original text with the revised text on the terminal and presses the selection button to confirm the selected information.

[0710] Step 7:

[0711] The text data selected by the user is sent to the server.

[0712] Input: Selected sentence data.

[0713] Output: The selection information sent to the server.

[0714] Specific operation: The user's selection information is sent from the terminal to the server.

[0715] Step 8:

[0716] The server creates and sends an API request to post the selected text to the communication tool.

[0717] Input: User-selected text data.

[0718] Output: Text posted to the communication tool.

[0719] Specific operation: The server sends the selected text to the communication tool, which actually posts it to the platform. For example, it sends a POST request to the specified API endpoint.

[0720] (Application example 2)

[0721] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0722] In modern brick-and-mortar stores, responding appropriately and promptly to customer feedback and inquiries is important to improving the quality of customer service. However, providing appropriate responses that reflect customer emotions can be difficult, which can result in an increase in dissatisfied customers and negatively impact the store's reputation and sales. Therefore, a system that takes emotions into account when responding to customers and replies in an appropriate manner is needed.

[0723] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving content entered by a user using an information processing device, means for sending the received content to a generative artificial intelligence to generate a revision proposal, means for presenting the generated revision proposal to the user, means for the user to select either the revision proposal or the original text, means for posting the selected content to a communication means, means for performing sentiment analysis, and means for using the results of the sentiment analysis when generating a revision proposal. This makes it possible to quickly provide appropriate responses that take sentiment into consideration in response to feedback and inquiries from customers.

[0724] "User" refers to a person who uses an information processing device to input text and then confirm, select, and post it.

[0725] "Information processing device" refers to a device that allows a user to input text, review suggested revisions, and select them, such as a smartphone, tablet, or PC.

[0726] The "receiving means" refers to a function that allows the server to receive the content that the user inputs using the information processing device.

[0727] "Generative AI" refers to AI that generates revision suggestions based on received content. It uses natural language processing technology.

[0728] "Means for generating suggested revisions" refers to the function by which the generative artificial intelligence analyzes the input content and generates appropriate revised sentences.

[0729] "Means for presenting generated revision suggestions" refers to a function for displaying revised sentences generated by the generative artificial intelligence to the user.

[0730] "Means for selection" refers to the functionality that allows the user to select the presented revised text or the original text.

[0731] "Means of communication" refers to the function that allows users to post text of their choice to external communication tools.

[0732] "Means for performing emotion analysis" refers to the function for analyzing the emotion of input text and providing the results to generative artificial intelligence.

[0733] "Means for using the results of sentiment analysis" refers to a function that reflects the results of sentiment analysis when the generative artificial intelligence generates revised sentences based on the results of sentiment analysis.

[0734] System Overview

[0735] The present invention is a system for receiving information entered by a user using an information processing device, and uses the following hardware and software.

[0736] Hardware: Smartphones, tablets, computers

[0737] Software: Generative AI (e.g., OpenAI GPT-3, GPT-4), emotion analysis engine (e.g., IBM Watson Emotion Analysis)

[0738] Program processing

[0739] Information processing device (user terminal)

[0740] A user inputs a sentence using an information processing device. For example, a customer inputs, "It's difficult to understand how to use this product."

[0741] server

[0742] 1. Data Reception

[0743] The server receives the input content sent from the information processing device.

[0744] 2. Emotion analysis

[0745] The received content is sent to a sentiment analysis engine, which analyzes the sentiment of the input content. For example, the sentence "It's hard to understand how to use this product" is analyzed as "dissatisfied."

[0746] 3. Revision generation

[0747] Based on the results of the sentiment analysis, the generative AI is instructed to generate suggested revisions. The generative AI then generates appropriate revisions that reflect the results of the sentiment analysis. For example, the generated revision might read, "There are several areas for improvement in how this product is used."

[0748] 4. Presentation of revised sentences

[0749] The server receives the generated corrections and presents them to the user, who can then choose between the corrections and the original text.

[0750] 5. Submit

[0751] The server receives the content selected by the user and posts it to the specified communication tool using an appropriate communication method.

[0752] Specific examples

[0753] Prompt Sentence Examples

[0754] "Depending on the customer's feelings, please revise the following sentences to make them more positive.

[0755] Input: I'm having trouble understanding how to use this product.

[0756] Emotion: Dissatisfaction

[0757] Output: There are some areas for improvement regarding how this product is used.

[0758] This makes it possible to quickly provide appropriate responses that take emotions into account when interacting with customers. By selecting the correct sentence that best reflects the customer's emotion, users can improve the quality of customer interaction in physical stores.

[0759] Usage example

[0760] For example, suppose a customer complains that "it's difficult to understand how to use this product." A system embodying this invention receives this input, performs sentiment analysis, generates appropriate corrections, and ultimately presents the user with a more positively-toned correction such as "There are some points that need improvement in how to use this product." The user can select this correction and reply to the customer, thereby reducing the customer's dissatisfaction and improving their satisfaction.

[0761] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0762] Step 1:

[0763] The user inputs a sentence using the information processing device. For example, the user inputs a sentence such as "It's difficult to understand how to use this product." The input sentence is sent to the server by the information processing device.

[0764] Step 2:

[0765] The server receives the input content sent from the information processing device. Specifically, the server's communication module receives the input text data and temporarily stores it in a database. At this time, it is confirmed that the transmitted text has been received correctly.

[0766] Step 3:

[0767] The server sends the received text to a sentiment analysis engine, which analyzes the text and identifies the emotion contained within. For example, emotional information such as "dissatisfaction" is analyzed. Data processing to extract this emotional background is performed based on a specific algorithm.

[0768] Step 4:

[0769] The server sends the results of the sentiment analysis to the generative AI, which generates a correction based on the results of the sentiment analysis and the input text. For example, a positive-toned correction such as "There are some points to improve on in how you use this product" is generated. This process requires a prompt sentence to be used by the generative AI model.

[0770] Step 5:

[0771] The server receives the generated revised text and presents it to the user. Specifically, the server sends the generated revised text to an information processing device and displays it for the user to confirm. At this time, both the original text and the revised text are displayed.

[0772] Step 6:

[0773] The user selects either the presented revised sentence or the original sentence. The user selects either the presented revised sentence or the original sentence and transmits the selection information to the server via the information processing device.

[0774] Step 7:

[0775] The server receives the user's selection and posts it to the specified communication tool using the appropriate communication method. Specifically, it generates an API request and sends the selected text to the external communication tool. Through this process, the selected text is sent back to the customer.

[0776] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0777] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0778] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0779] [Third embodiment]

[0780] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0781] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0782] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0783] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0784] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0785] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0786] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0787] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0788] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0789] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0790] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0791] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0792] MODE FOR CARRYING OUT THE INVENTION

[0793] This paper describes an embodiment of the present invention. Specifically, it relates to a system for improving the quality of texts posted by users to communication tools. This system uses generative artificial intelligence to correct texts entered by users, and helps users select either the suggested corrections or the original text before finally posting.

[0794] System configuration

[0795] 1. Terminal

[0796] A device used to type text, review suggested revisions, and select posts. This includes computers, tablets, smartphones, etc.

[0797] 2. Server

[0798] It is the central part that receives text, sends requests to the generative AI, retrieves and displays suggested revisions, and finally sends the post.

[0799] 3. Generative Artificial Intelligence

[0800] Generates suggested corrections based on received text. Improves the quality of user-entered text by analyzing and correcting text using natural language processing algorithms.

[0801] System Operation

[0802] A user uses a device to type a sentence, for example, "The meeting will be held tomorrow at 10:00 AM."

[0803] The device sends the input text to the server, which then sends a request to the generative artificial intelligence to generate a revision proposal.

[0804] The generative AI analyzes the received text and generates suggested revisions. An example of a suggested revision is "We will hold a meeting tomorrow at 10:00 AM." The generated suggested revisions are sent back to the server.

[0805] After receiving the proposed revisions, the server sends both the original text and the proposed revisions to the user's device, where the user can review the revisions and choose which text to post.

[0806] The user can select either the suggested revision or the original text on the device. For example, the user can select the suggested revision, "We will have a meeting tomorrow at 10:00 AM."

[0807] The device sends the text selected by the user to the server, which receives the selected text and processes it to post it to the communication tool.

[0808] The server then sends the final selected sentence to the communication tool, where it is actually posted. Through this series of operations, users can post high-quality sentences to the communication tool.

[0809] Specific examples

[0810] For example, a user inputs the sentence "The meeting will be held tomorrow at 10:00 AM." and generates a suggested revision. In this case, the generative AI will suggest the revision "The meeting will be held tomorrow at 10:00 AM." After the user confirms this suggested revision, they select the revised sentence and post it to the communication tool. As a result, the posted sentence becomes "The meeting will be held tomorrow at 10:00 AM." Through this process, users can quickly and accurately revise their sentences, achieving high-quality communication.

[0811] This allows users to improve the quality of their writing without any effort on their part. Furthermore, by using generative AI, it can efficiently prevent typos and grammatical errors. Overall, this system can improve the quality of writing in communication tools and enhance the user experience.

[0812] The processing flow will be explained below.

[0813] Step 1:

[0814] A user inputs a sentence into a terminal, for example, "The meeting will be held tomorrow at 10:00 AM."

[0815] Step 2:

[0816] The user clicks the "Review" button and the entered text is sent to the server.

[0817] Step 3:

[0818] The terminal converts the input text into packets and sends them to the server, which receives the packets.

[0819] Step 4:

[0820] The server analyzes the received text and creates a request to the generative AI, which includes the text entered by the user.

[0821] Step 5:

[0822] The server sends a request to the generative AI, which generates a corrected sentence based on the received sentence.

[0823] Step 6:

[0824] The generative artificial intelligence generates a corrected sentence such as "We will have a meeting tomorrow at 10:00 AM" and sends it back to the server.

[0825] Step 7:

[0826] The server receives the revised sentence from the generative AI and sends data including the original sentence and the revised sentence to the terminal.

[0827] Step 8:

[0828] The device analyzes the data received from the server and displays the original text and the revised text to the user, who can then choose either one.

[0829] Step 9:

[0830] The user selects the corrected text or the original text, and the selection information is sent to the terminal.

[0831] Step 10:

[0832] The device sends the user's selected text to the server, which receives the information.

[0833] Step 11:

[0834] Based on the user's selection information, the server creates an API request to post the selected text to the communication tool.

[0835] Step 12:

[0836] The server sends an API request to the communication tool and actually posts the selected text.

[0837] Step 13:

[0838] The server confirms the success of the posting and notifies the device of the result, which then displays to the user that the posting has been completed.

[0839] Example 1

[0840] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0841] To improve the quality of the text posted by users on communication tools, it is necessary to correct the content of the text so that it is accurate and natural-sounding. However, manual correction is time-consuming and labor-intensive, and it is difficult to completely prevent typos, omissions, and grammatical errors. It is also a significant burden for users to choose appropriate expressions. Therefore, there is a need for a system that can streamline the text correction process and quickly generate and post high-quality text.

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

[0843] In this invention, the server includes means for a user to input text using a terminal, means for the terminal to send the input text to the server, means for the server to send the received text to a generative AI model to generate a suggested revision, means for the generative AI model to send the suggested revision to the text to the server, means for the server to send the suggested revision to the terminal, means for the user to select either the suggested revision or the original text, and means for the server to post the selected text to a communication tool. This enables users to efficiently generate accurate and naturally-expressed text without much effort and to quickly post high-quality text to a communication tool.

[0844] "User" means a person who uses the system to input text, review and select suggested revisions, and post them to the communication tool.

[0845] "Device" means the device used by a User to enter text and review and select suggested revisions, including a PC, tablet, or smartphone.

[0846] The "server" is the central part that sends the text received from the device to the generative AI model and sends the generated corrections back to the device.

[0847] A "generative AI model" is an artificial intelligence system that generates suggested revisions based on the text it receives, using natural language processing algorithms to analyze and correct the text.

[0848] "Suggested revisions" are suggested improvements to the text entered by the user, generated by the generative AI model.

[0849] "Source text" refers to the original text entered by the user.

[0850] A "communication tool" is an online platform through which a user ultimately posts selected text, including, for example, a chat application or email system.

[0851] A "means" is a method or process established to achieve a particular purpose.

[0852] This invention relates to a system for improving the quality of text posted by users to communication tools. The system uses a generative AI model to correct text entered by the user, and helps the user select either the suggested correction or the original text for final posting. The components of this system are the device used by the user, a central server, and a generative AI model that corrects the text.

[0853] Terminal

[0854] A terminal is a device on which a user enters text, reviews suggested revisions, and selects a post. This may include a computer, tablet, or smartphone, and provides an interface for the user to enter specific text.

[0855] For example, if a user inputs the sentence "The meeting will be held tomorrow at 10:00 AM," the sentence is sent from the terminal to the server.

[0856] server

[0857] The server is the nerve center that receives the text, sends requests to the generative AI model, retrieves and displays suggested revisions, and finally sends the post. Specifically, it does the following:

[0858] 1. Send the text received from the device to the generative AI model.

[0859] 2. The proposed corrections returned by the generative AI model are sent to the device and displayed to the user.

[0860] 3. Receive the final text selected by the user and post it to the communication tool.

[0861] For example, send the following prompt to a generative AI model:

[0862] "Please revise the following Japanese sentence to make it more natural and accurate. The meeting will be held tomorrow at 10:00 AM."

[0863] Generative AI Models

[0864] The generative AI model generates suggested revisions based on the received text. The generative AI model uses a natural language processing algorithm to analyze the text and generate appropriate suggested revisions. For example, the proposed revision might be, "We'll have a meeting tomorrow at 10:00 AM."

[0865] The generative AI model sends suggested revisions back to the server, which then sends them to the device.

[0866] Specific examples

[0867] The user inputs the sentence "The meeting will be held tomorrow at 10 AM." The device sends this sentence to the server, which then sends a request to the generative AI model. The generative AI model generates a suggested revision, "The meeting will be held tomorrow at 10 AM," and sends this back to the server. The server then sends the suggested revision to the device, and the user reviews and selects the revision. When the user selects the revision, the device sends it to the server, which ultimately posts it to the communication tool.

[0868] This allows users to quickly and accurately correct their writing, resulting in high-quality communication. Furthermore, by utilizing generative AI models, it is possible to efficiently prevent typos, omissions, and grammatical errors.

[0869] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0870] Step 1:

[0871] The user inputs a sentence using the terminal. The user inputs the sentence "The meeting will be held tomorrow at 10:00 AM" into the text input field of the terminal. The input sentence is temporarily saved in the terminal.

[0872] Step 2:

[0873] The terminal sends the input text to the server. Specifically, the terminal uses an HTTP request to send the input text to the server in JSON format. The input is the "text entered by the user" and the output is the "text data sent to the server."

[0874] Step 3:

[0875] The server sends the received text to the generative AI model. The server analyzes the text data and generates a prompt for the generative AI model. For example, the prompt might be in the format "Please revise the following Japanese sentence to make it natural and accurate. The meeting will be held tomorrow at 10:00 AM." The input is the "received text data" and the output is the "prompt to be sent to the generative AI model."

[0876] Step 4:

[0877] The generative AI model analyzes the sent prompt sentence and generates suggested revisions to the sentence. Using a natural language processing algorithm, the generative AI model generates suggested revisions, such as "We will hold a meeting tomorrow at 10:00 AM." The input is the "prompt sentence" and the output is the "generated revisions."

[0878] Step 5:

[0879] The server receives the proposed revisions from the generative AI model and sends them to the device. Specifically, the server sends JSON-formatted data containing the proposed revisions to the device as an HTTP response. The input is the "proposal revisions received from the generative AI model," and the output is the "proposal revision data sent to the device."

[0880] Step 6:

[0881] The user checks the proposed revisions displayed on the terminal and selects either the proposed revisions or the original text. For example, the user selects the proposed revision "We will hold a meeting tomorrow at 10:00 AM." The input is "comparison information between the proposed revisions and the original text," and the output is "user selection information."

[0882] Step 7:

[0883] The terminal sends the text selected by the user to the server. Specifically, it sends JSON format data containing the selected text to the server as an HTTP request. The input is the "text selected by the user" and the output is the "selected data sent to the server."

[0884] Step 8:

[0885] The server finally posts the selected text to the communication tool. The server then sends the selected text data using the API of the appropriate communication tool. For example, using the Slack API, the text "We will have a meeting tomorrow at 10:00 AM" is posted. The input is the "selected text data" and the output is the "text posted to the communication tool."

[0886] This series of steps enables users to quickly and accurately post high-quality text to communication tools.

[0887] (Application example 1)

[0888] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0889] In today's brick-and-mortar stores, it can be difficult for store associates to maintain high-quality communication during customer interactions. While voice recognition technology and generative artificial intelligence (AI) can improve the quality of customer service conversations, efficient methods for utilizing these technologies in stores have yet to be established. Furthermore, there is a lack of interfaces that allow staff to instantly refer to suggested corrections and respond appropriately. This can lead to lower customer satisfaction and inconsistent customer service quality.

[0890] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0891] In this invention, the server includes means for receiving text entered by a user using a terminal, means for transmitting the received text to a generative artificial intelligence (AI) to generate suggested revisions, means for presenting the generated suggested revisions to the user, means for the user to select either the suggested revisions or the original text, means for posting the selected text to a communication tool, means for speech recognition during customer service, means for transmitting the results of speech recognition to the AI ​​to generate suggested revisions, and interface means for displaying and allowing selection of suggested revisions. This enables store staff to instantly receive content of conversations with customers as suggested revisions and respond using appropriate language, thereby improving the quality of customer service.

[0892] "Device" refers to the device on which a user enters text, reviews suggested revisions, and posts, including computers, tablets, and smartphones.

[0893] "Generative AI" refers to an AI system that analyzes a given sentence and generates suggested revisions. It uses natural language processing algorithms.

[0894] "Communication tools" refers to platforms for textual exchange between users, including chat apps and social media.

[0895] "Speech recognition means" refers to technology for converting voice data into text data, including, for example, a microphone and voice recognition software.

[0896] "Interface means" refers to a user interface that allows a user to confirm, select, and input suggested revisions. Specifically, this includes a display and a touch panel.

[0897] MODE FOR CARRYING OUT THE INVENTION

[0898] System Configuration

[0899] This invention provides a system that allows store staff to use smart glasses to improve the quality of their interactions with customers. The system consists of the following components:

[0900] 1. Terminal

[0901] It is a set of smart glasses worn by staff, a device that recognizes voice and displays suggested revisions.

[0902] 2. Server

[0903] It is the central part that receives voice data and sends requests to the generative artificial intelligence to generate suggested revisions.

[0904] 3. Generative Artificial Intelligence

[0905] The system uses natural language processing algorithms to analyze speech recognition results and generate appropriate correction suggestions.

[0906] operation

[0907] 1. Voice Recognition

[0908] The server uses the microphone built into the smart glasses to collect voice data from conversations between customers and staff, and converts this voice data into text data using voice recognition software (e.g., Google's voice recognition API).

[0909] 2. Revision generation

[0910] The text data obtained by speech recognition is sent to a server, which then sends the text data to a generative AI model (e.g., OpenAI's GPT-3) that generates appropriate corrections. The generative AI model uses a natural language processing algorithm.

[0911] 3. Proposal of amendments

[0912] The generated revision suggestions are sent from the server to the smart glasses, where the staff member can check the revision suggestions and the original text on the smart glasses' display and choose which sentence to adopt.

[0913] 4. Final Response

[0914] The staff member continues the conversation with the customer based on the selected sentence. The selected information is saved and can be used for later processing.

[0915] Specific examples

[0916] For example, if a customer asks, "How do I use this product?", here's what the system does:

[0917] Speech recognition result (transcribed): "How do I use this product?"

[0918] Generative AI generated a correction: "Tell me how to use this product."

[0919] The staff member checks the proposed correction on the display of the smart glasses, selects the appropriate sentence, and explains to the customer using the final response, "Please tell me how to use this product."

[0920] Prompt Sentence Examples

[0921] Here's an example prompt to send to a generative AI:

[0922] Improve this sentence: What is the use of this product?

[0923] This allows store staff to maintain high-quality interactions in real time, improving customer satisfaction.

[0924] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0925] Step 1:

[0926] The user puts on the device (smart glasses) and begins interacting with the customer.

[0927] Input: Customer speech.

[0928] Specific operation: The microphone in the smart glasses collects voice data from conversations between customers and staff.

[0929] Output: Audio data.

[0930] Step 2:

[0931] The server receives the voice data and converts it into text data using speech recognition software.

[0932] Input: Audio data sent from smart glasses.

[0933] Specific operation: Converts voice data into text using speech recognition software (e.g., Google's speech recognition API).

[0934] Output: Text data.

[0935] Step 3:

[0936] The server sends the text data to a generative artificial intelligence system, which generates appropriate revision suggestions.

[0937] Input: Text data.

[0938] Specific operation: The server sends the text data to OpenAI's API, and a generative AI model (e.g., GPT-3) generates correction suggestions.

[0939] Output: The proposed amendment text.

[0940] Step 4:

[0941] The server sends the suggested revision text to the smart glasses and displays it to the user.

[0942] Input: Proposed amendment text.

[0943] Specific operation: The server sends the suggested revision text to the user's smart glasses and displays it on the display.

[0944] Output: Correction suggestions displayed on the smart glasses display.

[0945] Step 5:

[0946] The user selects the suggested revision or the original text on the smart glasses display.

[0947] Input: Proposed amendment and original text.

[0948] Specific action: The user chooses whether to accept the suggested revision or the original text through the smart glasses interface.

[0949] Output: The selected text.

[0950] Step 6:

[0951] The server saves the user's choice and uses the selected text in the next response.

[0952] Input: The selected text.

[0953] What happens: The server saves the selection information in a database and reflects the selected text in the user's next interaction.

[0954] Output: Selection information stored in the database and text to be used for the next response.

[0955] Step 7:

[0956] The user provides instructions to the customer based on the selected text.

[0957] Input: The selected text.

[0958] What happens: The user explains the final text displayed on the smart glasses to the customer.

[0959] Output: Instructions to the customer.

[0960] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0961] MODE FOR CARRYING OUT THE INVENTION

[0962] This invention relates to a system for improving the quality of text posted by users on communication tools. In particular, it aims to improve the quality of the final post by providing appropriate revision suggestions that are in line with the user's intentions by utilizing generative artificial intelligence and an emotion engine.

[0963] System configuration

[0964] 1. Terminal

[0965] A device used to type text, review suggested revisions, and select posts. This includes computers, tablets, smartphones, etc.

[0966] 2. Server

[0967] It is the central part that receives text, sends requests to the emotion engine and generative AI, retrieves and displays suggested revisions, and finally sends the post.

[0968] 3. Generative Artificial Intelligence

[0969] Generates suggested corrections based on received text. Improves the quality of user-entered text by analyzing and correcting text using natural language processing algorithms.

[0970] 4. Emotion Engine

[0971] It recognizes the emotions in the text entered by the user and provides this information to the generative AI. The emotion engine can then adjust the tone and expression of the text based on the user's emotions.

[0972] System Operation

[0973] A user types a sentence into a terminal, for example, "I'm a little unhappy with this project."

[0974] The device sends the input text to the server, which then sends a request for emotion analysis to the emotion engine after receiving the text.

[0975] The emotion engine analyzes the text and recognizes the user's emotion. In this case, it recognizes the emotion "dissatisfied." The emotion engine then sends the results back to the server.

[0976] Based on the emotion information received from the emotion engine, the server sends a request to the generative AI to generate a revision proposal. The generative AI analyzes the text and generates a revised sentence while adjusting the tone and expression.

[0977] The generative artificial intelligence generates a corrective sentence such as "There are some areas for improvement in this project" and sends it back to the server.

[0978] The server then sends the generated revised text and the revised text adjusted based on the emotion information to the terminal. The user can then review the original text and the revised text and choose which one to post.

[0979] The user selects the corrected text or the original text on the terminal and transmits the selection information to the server.

[0980] The server checks the user's selected text and creates an API request to post it to the communication tool.

[0981] The server sends the selected text to the communication tool, where it is actually posted. Through this series of operations, users can post text in a tone that matches their emotions and of high quality to their communication tool.

[0982] Specific examples

[0983] For example, if a user inputs the sentence, "I'm a little dissatisfied with this project," and revision suggestions are generated, the emotion engine will recognize "dissatisfied." Based on that emotion, the generative AI will generate a revision suggestion in a more positive tone, such as, "There are some areas for improvement in this project." The user can select this revision suggestion and post it in a communication tool, resulting in more appropriate and positive communication.

[0984] This system not only enables users to improve the quality of their writing, but also enables them to communicate effectively based on their own emotions. The combination of an emotion engine and generative AI enables advanced sentence generation and correction that cannot be achieved with conventional methods.

[0985] The processing flow will be explained below.

[0986] MODE FOR CARRYING OUT THE INVENTION (INCLUDING EMOTION ENGINE)

[0987] Processing flow

[0988] Step 1:

[0989] A user types a sentence into a terminal. For example, the user types, "I'm a little unhappy with this project."

[0990] Step 2:

[0991] The user clicks the "Review" button and sends the entered text to the server. The device receives this text and sends a request to the server.

[0992] Step 3:

[0993] The server receives the input text and sends it to the emotion engine for a sentiment analysis request.

[0994] Step 4:

[0995] The emotion engine analyzes the text and recognizes emotions. For example, it detects the emotion "dissatisfied." The detected emotion information is sent back to the server.

[0996] Step 5:

[0997] The server creates a request to the generative AI based on the emotion information received from the emotion engine. The request includes the input text and the recognized emotion information.

[0998] Step 6:

[0999] The server sends a request to the generative AI, which generates revision suggestions based on the received text and emotional information.

[1000] Step 7:

[1001] The generative artificial intelligence generates suggested revisions. For example, it generates positive suggestions such as, "There are some areas for improvement in this project." The generated suggested revisions are sent back to the server.

[1002] Step 8:

[1003] The server receives the generated revision suggestions and sends the original text and the revision suggestions to the user's device, which receives this data and displays it to the user.

[1004] Step 9:

[1005] The user reviews the original text and the suggested revisions displayed on the device and selects which one to adopt. The user selects the revision "This project has some improvements."

[1006] Step 10:

[1007] The user sends the selection information to the terminal, which then sends the selection information to the server.

[1008] Step 11:

[1009] The server receives the user's selection information, confirms the final post content, and creates a request to post the confirmed text to the communication tool.

[1010] Step 12:

[1011] The server sends the selected text to the communication tool and actually posts it.

[1012] Step 13:

[1013] The server confirms the success of the posting and notifies the device of the result, and the device displays a message to the user that the posting has been completed.

[1014] In this way, users can use the emotion engine's emotion analysis and generative AI's correction functions to post high-quality, emotionally appropriate text to communication tools.

[1015] Example 2

[1016] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1017] Conventional systems have been inadequate in improving the quality of text posted by users to communication tools, and have had difficulty correcting text based on emotions. Furthermore, suggestions for corrected text based on natural language processing are limited, often failing to fully express the user's intentions. To address these issues, the present invention aims to provide a high-quality text correction and posting system that takes user emotions into account.

[1018] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1019] In this invention, the server includes means for receiving text entered by a user using a terminal, means for transmitting the received text to an emotion analysis engine to acquire emotion information, means for transmitting the received text to a generative artificial intelligence based on the emotion information to generate a revision proposal, means for presenting the generated revision proposal to the user, means for the user to select either the revision proposal or the original text, and means for posting the selected text to a communication tool. This enables text revision in an appropriate tone according to the user's emotion and effective communication.

[1020] "User" means a person who uses the System to enter text and review, select and submit suggested revisions.

[1021] "Device" means a device on which a User enters text, reviews suggested revisions, and selects the final post, including a PC, tablet, or smartphone.

[1022] The "server" is the central part that receives text, sends requests to the sentiment analysis engine and generative AI, retrieves and displays suggested revisions, and finally sends the post.

[1023] An "emotion analysis engine" is software that analyzes the emotions in text entered by the user and provides that information to generative artificial intelligence.

[1024] "Generative AI" is an AI system that uses natural language processing algorithms to analyze input text and generate suggested revisions.

[1025] A "revision" is a suggested sentence that improves on the original sentence, generated by generative artificial intelligence.

[1026] "Emotional information" is emotional data that the emotion analysis engine recognizes from the text entered by the user.

[1027] A "communication tool" is a platform or software where users ultimately post text.

[1028] "Natural language processing algorithms" are computational techniques for analyzing, understanding, and generating human language.

[1029] "Selection information" is data resulting from the user's selection of the proposed revision or the original text.

[1030] MODE FOR CARRYING OUT THE INVENTION

[1031] This invention relates to a system for improving the quality of text posted by users on communication tools. In particular, it aims to improve the quality of the final post by providing appropriate revision suggestions that are in line with the user's intentions by utilizing generative artificial intelligence and an emotion engine.

[1032] System configuration

[1033] The system of the present invention is comprised of the following major components:

[1034] 1. Device:

[1035] This includes any device on which a user can enter text, review suggested revisions, and select to post, such as a computer, tablet, or smartphone.

[1036] 2. Server:

[1037] The server has the following roles:

[1038] Receiving text

[1039] Sending requests to sentiment analysis engines and generative AI

[1040] Get and view suggested fixes

[1041] Submitting the final post

[1042] 3. Generative AI:

[1043] It receives text entered by the user and generates high-quality text by analyzing and correcting it using natural language processing algorithms.

[1044] 4. Sentiment Analysis Engine:

[1045] It analyzes the emotions of user-input text and provides the results to generative AI, which can then adjust the tone and expression of the text based on the emotional information.

[1046] System Operation

[1047] The user inputs a sentence into the terminal. For example, the user inputs the sentence, "I'm a little dissatisfied with this project." The terminal sends this input sentence to the server.

[1048] The server sends the received text to the emotion analysis engine and requests emotion analysis. The emotion analysis engine analyzes the user's emotion and recognizes the emotion "dissatisfied." The result is then sent back to the server.

[1049] Next, the server requests the generative AI to generate a revision proposal based on the emotional information. The generative AI analyzes and corrects the sentence based on the emotional information, and generates a revision proposal such as "There are several areas for improvement in this project." The revised sentence is then sent back to the server.

[1050] The server sends the generated revised text and a revised text adjusted based on the emotion information to the device. The user can check the original text and the revised text on the device and select which one to post. The user selects the revised text and sends the selection information to the server.

[1051] Finally, the server creates an API request for posting the selected sentence to the communication tool and sends it to the communication tool, thereby enabling the user to post sentences to the communication tool with a tone and high quality that corresponds to the user's emotion.

[1052] Specific examples

[1053] For example, if a user enters the sentence, "I'm a little dissatisfied with this project," the sentiment analysis engine will recognize the emotion of "dissatisfaction." Based on that emotional information, the generative AI will generate a revision suggestion in a more positive tone, such as, "There are some areas for improvement in this project." The user can select this revision suggestion and post it in a communication tool, resulting in more appropriate and positive communication.

[1054] Example prompt sentence:

[1055] "Please revise the following sentence to a more positive tone: I'm a little unhappy with this project."

[1056] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1057] Program processing flow

[1058] Step 1:

[1059] The user types a sentence, for example, "I'm a little unhappy with this project."

[1060] Input: Text typed by the user into the terminal.

[1061] Output: The text data entered by the user.

[1062] Specific actions: The user uses the device to type text into an input field using a keyboard or touch input.

[1063] Step 2:

[1064] The terminal transmits the input text data to the server.

[1065] Input: Text data entered by the user into the terminal.

[1066] Output: The text data sent to the server.

[1067] Specific operation: The terminal sends the input text data to the server using a communication protocol such as an HTTP request.

[1068] Step 3:

[1069] The server sends the received text to an emotion analysis engine to obtain emotion information.

[1070] Input: Received text data.

[1071] Output: Acquired emotion information.

[1072] Specific operation: The server sends a request to the emotion analysis engine via a REST API or similar, and receives emotion information as the analysis result. For example, the emotion "dissatisfied" is analyzed.

[1073] Step 4:

[1074] The server sends the acquired emotional information and the original text data to a generative artificial intelligence (AI) system, which then generates suggested revisions.

[1075] Input: emotion information and original sentence data.

[1076] Output: The generated correction suggestions.

[1077] Specific operation: The server sends the emotion information and the original sentence data to the generative AI, which then generates a correction based on this. For example, the generated correction sentence might be, "There are several areas for improvement in this project."

[1078] Step 5:

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

[1080] Input: The generated corrected sentence.

[1081] Output: The modified statement sent to the terminal.

[1082] Specific operation: The server sends the corrected text to the terminal so that the user can confirm it.

[1083] Step 6:

[1084] The user can review the original and revised text and choose which one to post.

[1085] Input: The original sentence and the generated correction sentence.

[1086] Output: User selection information.

[1087] Specific operation: The user compares the original text with the revised text on the terminal and presses the selection button to confirm the selected information.

[1088] Step 7:

[1089] The text data selected by the user is sent to the server.

[1090] Input: Selected sentence data.

[1091] Output: The selection information sent to the server.

[1092] Specific operation: The user's selection information is sent from the terminal to the server.

[1093] Step 8:

[1094] The server creates and sends an API request to post the selected text to the communication tool.

[1095] Input: User-selected text data.

[1096] Output: Text posted to the communication tool.

[1097] Specific operation: The server sends the selected text to the communication tool, which actually posts it to the platform. For example, it sends a POST request to the specified API endpoint.

[1098] (Application example 2)

[1099] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1100] In modern brick-and-mortar stores, responding appropriately and promptly to customer feedback and inquiries is important to improving the quality of customer service. However, providing appropriate responses that reflect customer emotions can be difficult, which can result in an increase in dissatisfied customers and negatively impact the store's reputation and sales. Therefore, a system that takes emotions into account when responding to customers and replies in an appropriate manner is needed.

[1101] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving content entered by a user using an information processing device, means for sending the received content to a generative artificial intelligence to generate a revision proposal, means for presenting the generated revision proposal to the user, means for the user to select either the revision proposal or the original text, means for posting the selected content to a communication means, means for performing sentiment analysis, and means for using the results of the sentiment analysis when generating a revision proposal. This makes it possible to quickly provide appropriate responses that take sentiment into consideration in response to feedback and inquiries from customers.

[1102] "User" refers to a person who uses an information processing device to input text and then confirm, select, and post it.

[1103] "Information processing device" refers to a device that allows a user to input text, review suggested revisions, and select them, such as a smartphone, tablet, or PC.

[1104] The "receiving means" refers to a function that allows the server to receive the content that the user inputs using the information processing device.

[1105] "Generative AI" refers to AI that generates revision suggestions based on received content. It uses natural language processing technology.

[1106] "Means for generating suggested revisions" refers to the function by which the generative artificial intelligence analyzes the input content and generates appropriate revised sentences.

[1107] "Means for presenting generated revision suggestions" refers to a function for displaying revised sentences generated by the generative artificial intelligence to the user.

[1108] "Means for selection" refers to the functionality that allows the user to select the presented revised text or the original text.

[1109] "Means of communication" refers to the function that allows users to post text of their choice to external communication tools.

[1110] "Means for performing emotion analysis" refers to the function for analyzing the emotion of input text and providing the results to generative artificial intelligence.

[1111] "Means for using the results of sentiment analysis" refers to a function that reflects the results of sentiment analysis when the generative artificial intelligence generates revised sentences based on the results of sentiment analysis.

[1112] System Overview

[1113] The present invention is a system for receiving information entered by a user using an information processing device, and uses the following hardware and software.

[1114] Hardware: Smartphones, tablets, computers

[1115] Software: Generative AI (e.g., OpenAI GPT-3, GPT-4), emotion analysis engine (e.g., IBM Watson Emotion Analysis)

[1116] Program processing

[1117] Information processing device (user terminal)

[1118] A user inputs a sentence using an information processing device. For example, a customer inputs, "It's difficult to understand how to use this product."

[1119] server

[1120] 1. Data Reception

[1121] The server receives the input content sent from the information processing device.

[1122] 2. Emotion analysis

[1123] The received content is sent to a sentiment analysis engine, which analyzes the sentiment of the input content. For example, the sentence "It's hard to understand how to use this product" is analyzed as "dissatisfied."

[1124] 3. Revision generation

[1125] Based on the results of the sentiment analysis, the generative AI is instructed to generate suggested revisions. The generative AI then generates appropriate revisions that reflect the results of the sentiment analysis. For example, the generated revision might read, "There are several areas for improvement in how this product is used."

[1126] 4. Presentation of revised sentences

[1127] The server receives the generated corrections and presents them to the user, who can then choose between the corrections and the original text.

[1128] 5. Submit

[1129] The server receives the content selected by the user and posts it to the specified communication tool using an appropriate communication method.

[1130] Specific examples

[1131] Prompt Sentence Examples

[1132] "Depending on the customer's feelings, please revise the following sentences to make them more positive.

[1133] Input: I'm having trouble understanding how to use this product.

[1134] Emotion: Dissatisfaction

[1135] Output: There are some areas for improvement regarding how this product is used.

[1136] This makes it possible to quickly provide appropriate responses that take emotions into account when interacting with customers. By selecting the correct sentence that best reflects the customer's emotion, users can improve the quality of customer interaction in physical stores.

[1137] Usage example

[1138] For example, suppose a customer complains that "it's difficult to understand how to use this product." A system embodying this invention receives this input, performs sentiment analysis, generates appropriate corrections, and ultimately presents the user with a more positively-toned correction such as "There are some points that need improvement in how to use this product." The user can select this correction and reply to the customer, thereby reducing the customer's dissatisfaction and improving their satisfaction.

[1139] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1140] Step 1:

[1141] The user inputs a sentence using the information processing device. For example, the user inputs a sentence such as "It's difficult to understand how to use this product." The input sentence is sent to the server by the information processing device.

[1142] Step 2:

[1143] The server receives the input content sent from the information processing device. Specifically, the server's communication module receives the input text data and temporarily stores it in a database. At this time, it is confirmed that the transmitted text has been received correctly.

[1144] Step 3:

[1145] The server sends the received text to a sentiment analysis engine, which analyzes the text and identifies the emotion contained within. For example, emotional information such as "dissatisfaction" is analyzed. Data processing to extract this emotional background is performed based on a specific algorithm.

[1146] Step 4:

[1147] The server sends the results of the sentiment analysis to the generative AI, which generates a correction based on the results of the sentiment analysis and the input text. For example, a positive-toned correction such as "There are some points to improve on in how you use this product" is generated. This process requires a prompt sentence to be used by the generative AI model.

[1148] Step 5:

[1149] The server receives the generated revised text and presents it to the user. Specifically, the server sends the generated revised text to an information processing device and displays it for the user to confirm. At this time, both the original text and the revised text are displayed.

[1150] Step 6:

[1151] The user selects either the presented revised sentence or the original sentence. The user selects either the presented revised sentence or the original sentence and transmits the selection information to the server via the information processing device.

[1152] Step 7:

[1153] The server receives the user's selection and posts it to the specified communication tool using the appropriate communication method. Specifically, it generates an API request and sends the selected text to the external communication tool. Through this process, the selected text is sent back to the customer.

[1154] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1155] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1156] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1157] [Fourth embodiment]

[1158] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1159] 7, a 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.

[1160] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1161] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1162] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1163] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1164] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1165] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1166] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1167] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1168] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1169] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1170] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1171] MODE FOR CARRYING OUT THE INVENTION

[1172] This paper describes an embodiment of the present invention. Specifically, it relates to a system for improving the quality of texts posted by users to communication tools. This system uses generative artificial intelligence to correct texts entered by users, and helps users select either the suggested corrections or the original text before finally posting.

[1173] System configuration

[1174] 1. Terminal

[1175] A device used to type text, review suggested revisions, and select posts. This includes computers, tablets, smartphones, etc.

[1176] 2. Server

[1177] It is the central part that receives text, sends requests to the generative AI, retrieves and displays suggested revisions, and finally sends the post.

[1178] 3. Generative Artificial Intelligence

[1179] Generates suggested corrections based on received text. Improves the quality of user-entered text by analyzing and correcting text using natural language processing algorithms.

[1180] System Operation

[1181] A user uses a device to type a sentence, for example, "The meeting will be held tomorrow at 10:00 AM."

[1182] The device sends the input text to the server, which then sends a request to the generative artificial intelligence to generate a revision proposal.

[1183] The generative AI analyzes the received text and generates suggested revisions. An example of a suggested revision is "We will hold a meeting tomorrow at 10:00 AM." The generated suggested revisions are sent back to the server.

[1184] After receiving the proposed revisions, the server sends both the original text and the proposed revisions to the user's device, where the user can review the revisions and choose which text to post.

[1185] The user can select either the suggested revision or the original text on the device. For example, the user can select the suggested revision, "We will have a meeting tomorrow at 10:00 AM."

[1186] The device sends the text selected by the user to the server, which receives the selected text and processes it to post it to the communication tool.

[1187] The server then sends the final selected sentence to the communication tool, where it is actually posted. Through this series of operations, users can post high-quality sentences to the communication tool.

[1188] Specific examples

[1189] For example, a user inputs the sentence "The meeting will be held tomorrow at 10:00 AM." and generates a suggested revision. In this case, the generative AI will suggest the revision "The meeting will be held tomorrow at 10:00 AM." After the user confirms this suggested revision, they select the revised sentence and post it to the communication tool. As a result, the posted sentence becomes "The meeting will be held tomorrow at 10:00 AM." Through this process, users can quickly and accurately revise their sentences, achieving high-quality communication.

[1190] This allows users to improve the quality of their writing without any effort on their part. Furthermore, by using generative AI, it can efficiently prevent typos and grammatical errors. Overall, this system can improve the quality of writing in communication tools and enhance the user experience.

[1191] The processing flow will be explained below.

[1192] Step 1:

[1193] A user inputs a sentence into a terminal, for example, "The meeting will be held tomorrow at 10:00 AM."

[1194] Step 2:

[1195] The user clicks the "Review" button and the entered text is sent to the server.

[1196] Step 3:

[1197] The terminal converts the input text into packets and sends them to the server, which receives the packets.

[1198] Step 4:

[1199] The server analyzes the received text and creates a request to the generative AI, which includes the text entered by the user.

[1200] Step 5:

[1201] The server sends a request to the generative AI, which generates a corrected sentence based on the received sentence.

[1202] Step 6:

[1203] The generative artificial intelligence generates a corrected sentence such as "We will have a meeting tomorrow at 10:00 AM" and sends it back to the server.

[1204] Step 7:

[1205] The server receives the revised sentence from the generative AI and sends data including the original sentence and the revised sentence to the terminal.

[1206] Step 8:

[1207] The device analyzes the data received from the server and displays the original text and the revised text to the user, who can then choose either one.

[1208] Step 9:

[1209] The user selects the corrected text or the original text, and the selection information is sent to the terminal.

[1210] Step 10:

[1211] The device sends the user's selected text to the server, which receives the information.

[1212] Step 11:

[1213] Based on the user's selection information, the server creates an API request to post the selected text to the communication tool.

[1214] Step 12:

[1215] The server sends an API request to the communication tool and actually posts the selected text.

[1216] Step 13:

[1217] The server confirms the success of the posting and notifies the device of the result, which then displays to the user that the posting has been completed.

[1218] Example 1

[1219] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1220] To improve the quality of the text posted by users on communication tools, it is necessary to correct the content of the text so that it is accurate and natural-sounding. However, manual correction is time-consuming and labor-intensive, and it is difficult to completely prevent typos, omissions, and grammatical errors. It is also a significant burden for users to choose appropriate expressions. Therefore, there is a need for a system that can streamline the text correction process and quickly generate and post high-quality text.

[1221] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1222] In this invention, the server includes means for a user to input text using a terminal, means for the terminal to send the input text to the server, means for the server to send the received text to a generative AI model to generate a suggested revision, means for the generative AI model to send the suggested revision to the text to the server, means for the server to send the suggested revision to the terminal, means for the user to select either the suggested revision or the original text, and means for the server to post the selected text to a communication tool. This enables users to efficiently generate accurate and naturally-expressed text without much effort and to quickly post high-quality text to a communication tool.

[1223] "User" means a person who uses the system to input text, review and select suggested revisions, and post them to the communication tool.

[1224] "Device" means the device used by a User to enter text and review and select suggested revisions, including a PC, tablet, or smartphone.

[1225] The "server" is the central part that sends the text received from the device to the generative AI model and sends the generated corrections back to the device.

[1226] A "generative AI model" is an artificial intelligence system that generates suggested revisions based on the text it receives, using natural language processing algorithms to analyze and correct the text.

[1227] "Suggested revisions" are suggested improvements to the text entered by the user, generated by the generative AI model.

[1228] "Source text" refers to the original text entered by the user.

[1229] A "communication tool" is an online platform through which a user ultimately posts selected text, including, for example, a chat application or email system.

[1230] A "means" is a method or process established to achieve a particular purpose.

[1231] This invention relates to a system for improving the quality of text posted by users to communication tools. The system uses a generative AI model to correct text entered by the user, and helps the user select either the suggested correction or the original text for final posting. The components of this system are the device used by the user, a central server, and a generative AI model that corrects the text.

[1232] Terminal

[1233] A terminal is a device on which a user enters text, reviews suggested revisions, and selects a post. This may include a computer, tablet, or smartphone, and provides an interface for the user to enter specific text.

[1234] For example, if a user inputs the sentence "The meeting will be held tomorrow at 10:00 AM," the sentence is sent from the terminal to the server.

[1235] server

[1236] The server is the nerve center that receives the text, sends requests to the generative AI model, retrieves and displays suggested revisions, and finally sends the post. Specifically, it does the following:

[1237] 1. Send the text received from the device to the generative AI model.

[1238] 2. The proposed corrections returned by the generative AI model are sent to the device and displayed to the user.

[1239] 3. Receive the final text selected by the user and post it to the communication tool.

[1240] For example, send the following prompt to a generative AI model:

[1241] "Please revise the following Japanese sentence to make it more natural and accurate. The meeting will be held tomorrow at 10:00 AM."

[1242] Generative AI Models

[1243] The generative AI model generates suggested revisions based on the received text. The generative AI model uses a natural language processing algorithm to analyze the text and generate appropriate suggested revisions. For example, the proposed revision might be, "We'll have a meeting tomorrow at 10:00 AM."

[1244] The generative AI model sends suggested revisions back to the server, which then sends them to the device.

[1245] Specific examples

[1246] The user inputs the sentence "The meeting will be held tomorrow at 10 AM." The device sends this sentence to the server, which then sends a request to the generative AI model. The generative AI model generates a suggested revision, "The meeting will be held tomorrow at 10 AM," and sends this back to the server. The server then sends the suggested revision to the device, and the user reviews and selects the revision. When the user selects the revision, the device sends it to the server, which ultimately posts it to the communication tool.

[1247] This allows users to quickly and accurately correct their writing, resulting in high-quality communication. Furthermore, by utilizing generative AI models, it is possible to efficiently prevent typos, omissions, and grammatical errors.

[1248] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1249] Step 1:

[1250] The user inputs a sentence using the terminal. The user inputs the sentence "The meeting will be held tomorrow at 10:00 AM" into the text input field of the terminal. The input sentence is temporarily saved in the terminal.

[1251] Step 2:

[1252] The terminal sends the input text to the server. Specifically, the terminal uses an HTTP request to send the input text to the server in JSON format. The input is the "text entered by the user" and the output is the "text data sent to the server."

[1253] Step 3:

[1254] The server sends the received text to the generative AI model. The server analyzes the text data and generates a prompt for the generative AI model. For example, the prompt might be in the format "Please revise the following Japanese sentence to make it natural and accurate. The meeting will be held tomorrow at 10:00 AM." The input is the "received text data" and the output is the "prompt to be sent to the generative AI model."

[1255] Step 4:

[1256] The generative AI model analyzes the sent prompt sentence and generates suggested revisions to the sentence. Using a natural language processing algorithm, the generative AI model generates suggested revisions, such as "We will hold a meeting tomorrow at 10:00 AM." The input is the "prompt sentence" and the output is the "generated revisions."

[1257] Step 5:

[1258] The server receives the proposed revisions from the generative AI model and sends them to the device. Specifically, the server sends JSON-formatted data containing the proposed revisions to the device as an HTTP response. The input is the "proposal revisions received from the generative AI model," and the output is the "proposal revision data sent to the device."

[1259] Step 6:

[1260] The user checks the proposed revisions displayed on the terminal and selects either the proposed revisions or the original text. For example, the user selects the proposed revision "We will hold a meeting tomorrow at 10:00 AM." The input is "comparison information between the proposed revisions and the original text," and the output is "user selection information."

[1261] Step 7:

[1262] The terminal sends the text selected by the user to the server. Specifically, it sends JSON format data containing the selected text to the server as an HTTP request. The input is the "text selected by the user" and the output is the "selected data sent to the server."

[1263] Step 8:

[1264] The server finally posts the selected text to the communication tool. The server then sends the selected text data using the API of the appropriate communication tool. For example, using the Slack API, the text "We will have a meeting tomorrow at 10:00 AM" is posted. The input is the "selected text data" and the output is the "text posted to the communication tool."

[1265] This series of steps enables users to quickly and accurately post high-quality text to communication tools.

[1266] (Application example 1)

[1267] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1268] In today's brick-and-mortar stores, it can be difficult for store associates to maintain high-quality communication during customer interactions. While voice recognition technology and generative artificial intelligence (AI) can improve the quality of customer service conversations, efficient methods for utilizing these technologies in stores have yet to be established. Furthermore, there is a lack of interfaces that allow staff to instantly refer to suggested corrections and respond appropriately. This can lead to lower customer satisfaction and inconsistent customer service quality.

[1269] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1270] In this invention, the server includes means for receiving text entered by a user using a terminal, means for transmitting the received text to a generative artificial intelligence (AI) to generate suggested revisions, means for presenting the generated suggested revisions to the user, means for the user to select either the suggested revisions or the original text, means for posting the selected text to a communication tool, means for speech recognition during customer service, means for transmitting the results of speech recognition to the AI ​​to generate suggested revisions, and interface means for displaying and allowing selection of suggested revisions. This enables store staff to instantly receive content of conversations with customers as suggested revisions and respond using appropriate language, thereby improving the quality of customer service.

[1271] "Device" refers to the device on which a user enters text, reviews suggested revisions, and posts, including computers, tablets, and smartphones.

[1272] "Generative AI" refers to an AI system that analyzes a given sentence and generates suggested revisions. It uses natural language processing algorithms.

[1273] "Communication tools" refers to platforms for textual exchange between users, including chat apps and social media.

[1274] "Speech recognition means" refers to technology for converting voice data into text data, including, for example, a microphone and voice recognition software.

[1275] "Interface means" refers to a user interface that allows a user to confirm, select, and input suggested revisions. Specifically, this includes a display and a touch panel.

[1276] MODE FOR CARRYING OUT THE INVENTION

[1277] System Configuration

[1278] This invention provides a system that allows store staff to use smart glasses to improve the quality of their interactions with customers. The system consists of the following components:

[1279] 1. Terminal

[1280] It is a set of smart glasses worn by staff, a device that recognizes voice and displays suggested revisions.

[1281] 2. Server

[1282] It is the central part that receives voice data and sends requests to the generative artificial intelligence to generate suggested revisions.

[1283] 3. Generative Artificial Intelligence

[1284] The system uses natural language processing algorithms to analyze speech recognition results and generate appropriate correction suggestions.

[1285] operation

[1286] 1. Voice Recognition

[1287] The server uses the microphone built into the smart glasses to collect voice data from conversations between customers and staff, and converts this voice data into text data using voice recognition software (e.g., Google's voice recognition API).

[1288] 2. Revision generation

[1289] The text data obtained by speech recognition is sent to a server, which then sends the text data to a generative AI model (e.g., OpenAI's GPT-3) that generates appropriate corrections. The generative AI model uses a natural language processing algorithm.

[1290] 3. Proposal of amendments

[1291] The generated revision suggestions are sent from the server to the smart glasses, where the staff member can check the revision suggestions and the original text on the smart glasses' display and choose which sentence to adopt.

[1292] 4. Final Response

[1293] The staff member continues the conversation with the customer based on the selected sentence. The selected information is saved and can be used for later processing.

[1294] Specific examples

[1295] For example, if a customer asks, "How do I use this product?", here's what the system does:

[1296] Speech recognition result (transcribed): "How do I use this product?"

[1297] Generative AI generated a correction: "Tell me how to use this product."

[1298] The staff member checks the proposed correction on the display of the smart glasses, selects the appropriate sentence, and explains to the customer using the final response, "Please tell me how to use this product."

[1299] Prompt Sentence Examples

[1300] Here's an example prompt to send to a generative AI:

[1301] Improve this sentence: What is the use of this product?

[1302] This allows store staff to maintain high-quality interactions in real time, improving customer satisfaction.

[1303] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1304] Step 1:

[1305] The user puts on the device (smart glasses) and begins interacting with the customer.

[1306] Input: Customer speech.

[1307] Specific operation: The microphone in the smart glasses collects voice data from conversations between customers and staff.

[1308] Output: Audio data.

[1309] Step 2:

[1310] The server receives the voice data and converts it into text data using speech recognition software.

[1311] Input: Audio data sent from smart glasses.

[1312] Specific operation: Converts voice data into text using speech recognition software (e.g., Google's speech recognition API).

[1313] Output: Text data.

[1314] Step 3:

[1315] The server sends the text data to a generative artificial intelligence system, which generates appropriate revision suggestions.

[1316] Input: Text data.

[1317] Specific operation: The server sends the text data to OpenAI's API, and a generative AI model (e.g., GPT-3) generates correction suggestions.

[1318] Output: The proposed amendment text.

[1319] Step 4:

[1320] The server sends the suggested revision text to the smart glasses and displays it to the user.

[1321] Input: Proposed amendment text.

[1322] Specific operation: The server sends the suggested revision text to the user's smart glasses and displays it on the display.

[1323] Output: Correction suggestions displayed on the smart glasses display.

[1324] Step 5:

[1325] The user selects the suggested revision or the original text on the smart glasses display.

[1326] Input: Proposed amendment and original text.

[1327] Specific action: The user chooses whether to accept the suggested revision or the original text through the smart glasses interface.

[1328] Output: The selected text.

[1329] Step 6:

[1330] The server saves the user's choice and uses the selected text in the next response.

[1331] Input: The selected text.

[1332] What happens: The server saves the selection information in a database and reflects the selected text in the user's next interaction.

[1333] Output: Selection information stored in the database and text to be used for the next response.

[1334] Step 7:

[1335] The user provides instructions to the customer based on the selected text.

[1336] Input: The selected text.

[1337] What happens: The user explains the final text displayed on the smart glasses to the customer.

[1338] Output: Instructions to the customer.

[1339] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1340] MODE FOR CARRYING OUT THE INVENTION

[1341] This invention relates to a system for improving the quality of text posted by users on communication tools. In particular, it aims to improve the quality of the final post by providing appropriate revision suggestions that are in line with the user's intentions by utilizing generative artificial intelligence and an emotion engine.

[1342] System configuration

[1343] 1. Terminal

[1344] A device used to type text, review suggested revisions, and select posts. This includes computers, tablets, smartphones, etc.

[1345] 2. Server

[1346] It is the central part that receives text, sends requests to the emotion engine and generative AI, retrieves and displays suggested revisions, and finally sends the post.

[1347] 3. Generative Artificial Intelligence

[1348] Generates suggested corrections based on received text. Improves the quality of user-entered text by analyzing and correcting text using natural language processing algorithms.

[1349] 4. Emotion Engine

[1350] It recognizes the emotions in the text entered by the user and provides this information to the generative AI. The emotion engine can then adjust the tone and expression of the text based on the user's emotions.

[1351] System Operation

[1352] A user types a sentence into a terminal, for example, "I'm a little unhappy with this project."

[1353] The device sends the input text to the server, which then sends a request for emotion analysis to the emotion engine after receiving the text.

[1354] The emotion engine analyzes the text and recognizes the user's emotion. In this case, it recognizes the emotion "dissatisfied." The emotion engine then sends the results back to the server.

[1355] Based on the emotion information received from the emotion engine, the server sends a request to the generative AI to generate a revision proposal. The generative AI analyzes the text and generates a revised sentence while adjusting the tone and expression.

[1356] The generative artificial intelligence generates a corrective sentence such as "There are some areas for improvement in this project" and sends it back to the server.

[1357] The server then sends the generated revised text and the revised text adjusted based on the emotion information to the terminal. The user can then review the original text and the revised text and choose which one to post.

[1358] The user selects the corrected text or the original text on the terminal and transmits the selection information to the server.

[1359] The server checks the user's selected text and creates an API request to post it to the communication tool.

[1360] The server sends the selected text to the communication tool, where it is actually posted. Through this series of operations, users can post text in a tone that matches their emotions and of high quality to their communication tool.

[1361] Specific examples

[1362] For example, if a user inputs the sentence, "I'm a little dissatisfied with this project," and revision suggestions are generated, the emotion engine will recognize "dissatisfied." Based on that emotion, the generative AI will generate a revision suggestion in a more positive tone, such as, "There are some areas for improvement in this project." The user can select this revision suggestion and post it in a communication tool, resulting in more appropriate and positive communication.

[1363] This system not only enables users to improve the quality of their writing, but also enables them to communicate effectively based on their own emotions. The combination of an emotion engine and generative AI enables advanced sentence generation and correction that cannot be achieved with conventional methods.

[1364] The processing flow will be explained below.

[1365] MODE FOR CARRYING OUT THE INVENTION (INCLUDING EMOTION ENGINE)

[1366] Processing flow

[1367] Step 1:

[1368] A user types a sentence into a terminal. For example, the user types, "I'm a little unhappy with this project."

[1369] Step 2:

[1370] The user clicks the "Review" button and sends the entered text to the server. The device receives this text and sends a request to the server.

[1371] Step 3:

[1372] The server receives the input text and sends it to the emotion engine for a sentiment analysis request.

[1373] Step 4:

[1374] The emotion engine analyzes the text and recognizes emotions. For example, it detects the emotion "dissatisfied." The detected emotion information is sent back to the server.

[1375] Step 5:

[1376] The server creates a request to the generative AI based on the emotion information received from the emotion engine. The request includes the input text and the recognized emotion information.

[1377] Step 6:

[1378] The server sends a request to the generative AI, which generates revision suggestions based on the received text and emotional information.

[1379] Step 7:

[1380] The generative artificial intelligence generates suggested revisions. For example, it generates positive suggestions such as, "There are some areas for improvement in this project." The generated suggested revisions are sent back to the server.

[1381] Step 8:

[1382] The server receives the generated revision suggestions and sends the original text and the revision suggestions to the user's device, which receives this data and displays it to the user.

[1383] Step 9:

[1384] The user reviews the original text and the suggested revisions displayed on the device and selects which one to adopt. The user selects the revision "This project has some improvements."

[1385] Step 10:

[1386] The user sends the selection information to the terminal, which then sends the selection information to the server.

[1387] Step 11:

[1388] The server receives the user's selection information, confirms the final post content, and creates a request to post the confirmed text to the communication tool.

[1389] Step 12:

[1390] The server sends the selected text to the communication tool and actually posts it.

[1391] Step 13:

[1392] The server confirms the success of the posting and notifies the device of the result, and the device displays a message to the user that the posting has been completed.

[1393] In this way, users can use the emotion engine's emotion analysis and generative AI's correction functions to post high-quality, emotionally appropriate text to communication tools.

[1394] Example 2

[1395] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1396] Conventional systems have been inadequate in improving the quality of text posted by users to communication tools, and have had difficulty correcting text based on emotions. Furthermore, suggestions for corrected text based on natural language processing are limited, often failing to fully express the user's intentions. To address these issues, the present invention aims to provide a high-quality text correction and posting system that takes user emotions into account.

[1397] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1398] In this invention, the server includes means for receiving text entered by a user using a terminal, means for transmitting the received text to an emotion analysis engine to acquire emotion information, means for transmitting the received text to a generative artificial intelligence based on the emotion information to generate a revision proposal, means for presenting the generated revision proposal to the user, means for the user to select either the revision proposal or the original text, and means for posting the selected text to a communication tool. This enables text revision in an appropriate tone according to the user's emotion and effective communication.

[1399] "User" means a person who uses the System to enter text and review, select and submit suggested revisions.

[1400] "Device" means a device on which a User enters text, reviews suggested revisions, and selects the final post, including a PC, tablet, or smartphone.

[1401] The "server" is the central part that receives text, sends requests to the sentiment analysis engine and generative AI, retrieves and displays suggested revisions, and finally sends the post.

[1402] An "emotion analysis engine" is software that analyzes the emotions in text entered by the user and provides that information to generative artificial intelligence.

[1403] "Generative AI" is an AI system that uses natural language processing algorithms to analyze input text and generate suggested revisions.

[1404] A "revision" is a suggested sentence that improves on the original sentence, generated by generative artificial intelligence.

[1405] "Emotional information" is emotional data that the emotion analysis engine recognizes from the text entered by the user.

[1406] A "communication tool" is a platform or software where users ultimately post text.

[1407] "Natural language processing algorithms" are computational techniques for analyzing, understanding, and generating human language.

[1408] "Selection information" is data resulting from the user's selection of the proposed revision or the original text.

[1409] MODE FOR CARRYING OUT THE INVENTION

[1410] This invention relates to a system for improving the quality of text posted by users on communication tools. In particular, it aims to improve the quality of the final post by providing appropriate revision suggestions that are in line with the user's intentions by utilizing generative artificial intelligence and an emotion engine.

[1411] System configuration

[1412] The system of the present invention is comprised of the following major components:

[1413] 1. Device:

[1414] This includes any device on which a user can enter text, review suggested revisions, and select to post, such as a computer, tablet, or smartphone.

[1415] 2. Server:

[1416] The server has the following roles:

[1417] Receiving text

[1418] Sending requests to sentiment analysis engines and generative AI

[1419] Get and view suggested fixes

[1420] Submitting the final post

[1421] 3. Generative AI:

[1422] It receives text entered by the user and generates high-quality text by analyzing and correcting it using natural language processing algorithms.

[1423] 4. Sentiment Analysis Engine:

[1424] It analyzes the emotions of user-input text and provides the results to generative AI, which can then adjust the tone and expression of the text based on the emotional information.

[1425] System Operation

[1426] The user inputs a sentence into the terminal. For example, the user inputs the sentence, "I'm a little dissatisfied with this project." The terminal sends this input sentence to the server.

[1427] The server sends the received text to the emotion analysis engine and requests emotion analysis. The emotion analysis engine analyzes the user's emotion and recognizes the emotion "dissatisfied." The result is then sent back to the server.

[1428] Next, the server requests the generative AI to generate a revision proposal based on the emotional information. The generative AI analyzes and corrects the sentence based on the emotional information, and generates a revision proposal such as "There are several areas for improvement in this project." The revised sentence is then sent back to the server.

[1429] The server sends the generated revised text and a revised text adjusted based on the emotion information to the device. The user can check the original text and the revised text on the device and select which one to post. The user selects the revised text and sends the selection information to the server.

[1430] Finally, the server creates an API request for posting the selected sentence to the communication tool and sends it to the communication tool, thereby enabling the user to post sentences to the communication tool with a tone and high quality that corresponds to the user's emotion.

[1431] Specific examples

[1432] For example, if a user enters the sentence, "I'm a little dissatisfied with this project," the sentiment analysis engine will recognize the emotion of "dissatisfaction." Based on that emotional information, the generative AI will generate a revision suggestion in a more positive tone, such as, "There are some areas for improvement in this project." The user can select this revision suggestion and post it in a communication tool, resulting in more appropriate and positive communication.

[1433] Example prompt sentence:

[1434] "Please revise the following sentence to a more positive tone: I'm a little unhappy with this project."

[1435] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1436] Program processing flow

[1437] Step 1:

[1438] The user types a sentence, for example, "I'm a little unhappy with this project."

[1439] Input: Text typed by the user into the terminal.

[1440] Output: The text data entered by the user.

[1441] Specific actions: The user uses the device to type text into an input field using a keyboard or touch input.

[1442] Step 2:

[1443] The terminal transmits the input text data to the server.

[1444] Input: Text data entered by the user into the terminal.

[1445] Output: The text data sent to the server.

[1446] Specific operation: The terminal sends the input text data to the server using a communication protocol such as an HTTP request.

[1447] Step 3:

[1448] The server sends the received text to an emotion analysis engine to obtain emotion information.

[1449] Input: Received text data.

[1450] Output: Acquired emotion information.

[1451] Specific operation: The server sends a request to the emotion analysis engine via a REST API or similar, and receives emotion information as the analysis result. For example, the emotion "dissatisfied" is analyzed.

[1452] Step 4:

[1453] The server sends the acquired emotional information and the original text data to a generative artificial intelligence (AI) system, which then generates suggested revisions.

[1454] Input: emotion information and original sentence data.

[1455] Output: The generated correction suggestions.

[1456] Specific operation: The server sends the emotion information and the original sentence data to the generative AI, which then generates a correction based on this. For example, the generated correction sentence might be, "There are several areas for improvement in this project."

[1457] Step 5:

[1458] The server transmits the generated corrected text to the terminal.

[1459] Input: The generated corrected sentence.

[1460] Output: The modified statement sent to the terminal.

[1461] Specific operation: The server sends the corrected text to the terminal so that the user can confirm it.

[1462] Step 6:

[1463] The user can review the original and revised text and choose which one to post.

[1464] Input: The original sentence and the generated correction sentence.

[1465] Output: User selection information.

[1466] Specific operation: The user compares the original text with the revised text on the terminal and presses the selection button to confirm the selected information.

[1467] Step 7:

[1468] The text data selected by the user is sent to the server.

[1469] Input: Selected sentence data.

[1470] Output: The selection information sent to the server.

[1471] Specific operation: The user's selection information is sent from the terminal to the server.

[1472] Step 8:

[1473] The server creates and sends an API request to post the selected text to the communication tool.

[1474] Input: User-selected text data.

[1475] Output: Text posted to the communication tool.

[1476] Specific operation: The server sends the selected text to the communication tool, which actually posts it to the platform. For example, it sends a POST request to the specified API endpoint.

[1477] (Application example 2)

[1478] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1479] In modern brick-and-mortar stores, responding appropriately and promptly to customer feedback and inquiries is important to improving the quality of customer service. However, providing appropriate responses that reflect customer emotions can be difficult, which can result in an increase in dissatisfied customers and negatively impact the store's reputation and sales. Therefore, a system that takes emotions into account when responding to customers and replies in an appropriate manner is needed.

[1480] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving content entered by a user using an information processing device, means for sending the received content to a generative artificial intelligence to generate a revision proposal, means for presenting the generated revision proposal to the user, means for the user to select either the revision proposal or the original text, means for posting the selected content to a communication means, means for performing sentiment analysis, and means for using the results of the sentiment analysis when generating a revision proposal. This makes it possible to quickly provide appropriate responses that take sentiment into consideration in response to feedback and inquiries from customers.

[1481] "User" refers to a person who uses an information processing device to input text and then confirm, select, and post it.

[1482] "Information processing device" refers to a device that allows a user to input text, review suggested revisions, and select them, such as a smartphone, tablet, or PC.

[1483] The "receiving means" refers to a function that allows the server to receive the content that the user inputs using the information processing device.

[1484] "Generative AI" refers to AI that generates revision suggestions based on received content. It uses natural language processing technology.

[1485] "Means for generating suggested revisions" refers to the function by which the generative artificial intelligence analyzes the input content and generates appropriate revised sentences.

[1486] "Means for presenting generated revision suggestions" refers to a function for displaying revised sentences generated by the generative artificial intelligence to the user.

[1487] "Means for selection" refers to the functionality that allows the user to select the presented revised text or the original text.

[1488] "Means of communication" refers to the function that allows users to post text of their choice to external communication tools.

[1489] "Means for performing emotion analysis" refers to the function for analyzing the emotion of input text and providing the results to generative artificial intelligence.

[1490] "Means for using the results of sentiment analysis" refers to a function that reflects the results of sentiment analysis when the generative artificial intelligence generates revised sentences based on the results of sentiment analysis.

[1491] System Overview

[1492] The present invention is a system for receiving information entered by a user using an information processing device, and uses the following hardware and software.

[1493] Hardware: Smartphones, tablets, computers

[1494] Software: Generative AI (e.g., OpenAI GPT-3, GPT-4), emotion analysis engine (e.g., IBM Watson Emotion Analysis)

[1495] Program processing

[1496] Information processing device (user terminal)

[1497] A user inputs a sentence using an information processing device. For example, a customer inputs, "It's difficult to understand how to use this product."

[1498] server

[1499] 1. Data Reception

[1500] The server receives the input content sent from the information processing device.

[1501] 2. Emotion analysis

[1502] The received content is sent to a sentiment analysis engine, which analyzes the sentiment of the input content. For example, the sentence "It's hard to understand how to use this product" is analyzed as "dissatisfied."

[1503] 3. Revision generation

[1504] Based on the results of the sentiment analysis, the generative AI is instructed to generate suggested revisions. The generative AI then generates appropriate revisions that reflect the results of the sentiment analysis. For example, the generated revision might read, "There are several areas for improvement in how this product is used."

[1505] 4. Presentation of revised sentences

[1506] The server receives the generated corrections and presents them to the user, who can then choose between the corrections and the original text.

[1507] 5. Submit

[1508] The server receives the content selected by the user and posts it to the specified communication tool using an appropriate communication method.

[1509] Specific examples

[1510] Prompt Sentence Examples

[1511] "Depending on the customer's feelings, please revise the following sentences to make them more positive.

[1512] Input: I'm having trouble understanding how to use this product.

[1513] Emotion: Dissatisfaction

[1514] Output: There are some areas for improvement regarding how this product is used.

[1515] This makes it possible to quickly provide appropriate responses that take emotions into account when interacting with customers. By selecting the correct sentence that best reflects the customer's emotion, users can improve the quality of customer interaction in physical stores.

[1516] Usage example

[1517] For example, suppose a customer complains that "it's difficult to understand how to use this product." A system embodying this invention receives this input, performs sentiment analysis, generates appropriate corrections, and ultimately presents the user with a more positively-toned correction such as "There are some points that need improvement in how to use this product." The user can select this correction and reply to the customer, thereby reducing the customer's dissatisfaction and improving their satisfaction.

[1518] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1519] Step 1:

[1520] The user inputs a sentence using the information processing device. For example, the user inputs a sentence such as "It's difficult to understand how to use this product." The input sentence is sent to the server by the information processing device.

[1521] Step 2:

[1522] The server receives the input content sent from the information processing device. Specifically, the server's communication module receives the input text data and temporarily stores it in a database. At this time, it is confirmed that the transmitted text has been received correctly.

[1523] Step 3:

[1524] The server sends the received text to a sentiment analysis engine, which analyzes the text and identifies the emotion contained within. For example, emotional information such as "dissatisfaction" is analyzed. Data processing to extract this emotional background is performed based on a specific algorithm.

[1525] Step 4:

[1526] The server sends the results of the sentiment analysis to the generative AI, which generates a correction based on the results of the sentiment analysis and the input text. For example, a positive-toned correction such as "There are some points to improve on in how you use this product" is generated. This process requires a prompt sentence to be used by the generative AI model.

[1527] Step 5:

[1528] The server receives the generated revised text and presents it to the user. Specifically, the server sends the generated revised text to an information processing device and displays it for the user to confirm. At this time, both the original text and the revised text are displayed.

[1529] Step 6:

[1530] The user selects either the presented revised sentence or the original sentence. The user selects either the presented revised sentence or the original sentence and transmits the selection information to the server via the information processing device.

[1531] Step 7:

[1532] The server receives the user's selection and posts it to the specified communication tool using the appropriate communication method. Specifically, it generates an API request and sends the selected text to the external communication tool. Through this process, the selected text is sent back to the customer.

[1533] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1534] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1535] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1536] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1537] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1538] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1539] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1540] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1541] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1542] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1543] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1544] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1545] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1546] 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.

[1547] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1548] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1549] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1550] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1551] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1552] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1553] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1554] The following is further disclosed regarding the above embodiment.

[1555] (Claim 1)

[1556] means for receiving text input by a user using a terminal;

[1557] A means for transmitting the received text to a generative artificial intelligence to generate suggested revisions;

[1558] a means for presenting the generated revision suggestions to a user;

[1559] A means for the user to choose between the suggested revision and the original text;

[1560] a means for posting the selected text to a communication tool;

[1561] A system including:

[1562] (Claim 2)

[1563] The system of claim 1, wherein the generative artificial intelligence uses a natural language processing algorithm to generate suggested revisions to the sentence.

[1564] (Claim 3)

[1565] 10. The system of claim 1, further comprising means for storing user selections for later use.

[1566] "Example 1"

[1567] (Claim 1)

[1568] A means for a user to input text using a terminal;

[1569] A means for transmitting input text from the terminal to a server;

[1570] A means for the server to send the received sentence to a generative AI model to generate a correction suggestion;

[1571] A means for the generative AI model to send suggested revisions to the text to a server;

[1572] A means for the server to send the proposed revision to the terminal;

[1573] A means for the user to choose between the suggested revision and the original text;

[1574] A means for the server to post the selected sentence to the communication tool;

[1575] A system including:

[1576] (Claim 2)

[1577] 10. The system of claim 1, wherein the generative AI model uses a natural language processing algorithm to generate suggested revisions to the sentence.

[1578] (Claim 3)

[1579] 10. The system of claim 1, further comprising means for storing user selections for later use.

[1580] "Application Example 1"

[1581] (Claim 1)

[1582] means for receiving text input by a user using a terminal;

[1583] A means for transmitting the received text to a generative artificial intelligence to generate suggested revisions;

[1584] a means for presenting the generated revision suggestions to a user;

[1585] A means for the user to choose between the suggested revision and the original text;

[1586] a means for posting the selected text to a communication tool;

[1587] A voice recognition means for customer service;

[1588] A means for transmitting the speech recognition results to a generative artificial intelligence to generate revision suggestions;

[1589] an interface means for displaying and selecting suggested revisions;

[1590] A system including:

[1591] (Claim 2)

[1592] The system of claim 1, wherein the generative artificial intelligence uses a natural language processing algorithm to generate suggested revisions to sentences and apply them to customer service support.

[1593] (Claim 3)

[1594] 2. The system according to claim 1, further comprising means for saving user selection information and making it available for later processing, and means for streamlining responses when serving customers.

[1595] "Example 2: Combining Emotion Engines"

[1596] (Claim 1)

[1597] means for receiving text input by a user using a terminal;

[1598] A means for transmitting the received text to a sentiment analysis engine to obtain sentiment information;

[1599] A means for sending the received text based on the emotional information to a generative artificial intelligence to generate a revision proposal;

[1600] a means for presenting the generated revision suggestions to a user;

[1601] A means for the user to choose between the suggested revision and the original text;

[1602] a means for posting the selected text to a communication tool;

[1603] A system including:

[1604] (Claim 2)

[1605] The system of claim 1, wherein the generative artificial intelligence uses a natural language processing algorithm to generate suggested revisions to the sentence.

[1606] (Claim 3)

[1607] The system of claim 1, wherein the sentiment analysis engine recognizes the sentiment of the text entered by the user and provides the results to the generative artificial intelligence.

[1608] (Claim 4)

[1609] 10. The system of claim 1, further comprising means for storing user selections for later use.

[1610] "Application example 2 when combining emotion engines"

[1611] (Claim 1)

[1612] A means for receiving content input by a user using an information processing device;

[1613] a means for transmitting the received content to a generative artificial intelligence to generate a revision;

[1614] a means for presenting the generated revision suggestions to a user;

[1615] A means for the user to choose between the suggested revision and the original text;

[1616] means for posting the selected content to a communication means;

[1617] a means for performing sentiment analysis;

[1618] a means for using the results of the sentiment analysis in generating the revision suggestions;

[1619] A system including:

[1620] (Claim 2)

[1621] The system of claim 1, wherein the generative artificial intelligence generates suggested revisions to the content using natural language processing techniques.

[1622] (Claim 3)

[1623] 10. The system of claim 1, further comprising means for storing user selections for later use. [Explanation of symbols]

[1624] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving text input by a user using a terminal; A means for transmitting the received text to a generative artificial intelligence to generate suggested revisions; a means for presenting the generated revision suggestions to a user; A means for the user to choose between the suggested revision and the original text; a means for posting the selected text to a communication tool; A system including:

2. 10. The system of claim 1, wherein the generative artificial intelligence uses a natural language processing algorithm to generate suggested revisions to the sentence.

3. 2. The system of claim 1, further comprising means for storing user selections for later use.

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