system

Abstract

Provide a system. [Solution] means for receiving user input; means for processing received user input; a means for generating appropriate responses through natural language processing; means for returning the generated response to the user; A system including:

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] ---

[0005] With the advancement of modern technology, the technical problems users encounter are becoming more diverse and complex. However, there is a lack of technical support that can respond quickly and appropriately, and users are increasingly spending a lot of time trying to solve problems themselves. Traditional support systems often find it difficult to respond to user inquiries efficiently, and they often cannot expect high-quality support or timely solutions. Therefore, there is a need for a system that can quickly and appropriately solve the diverse technical problems users face. [Means for solving the problem]

[0006] To solve the above-mentioned problems, the present invention provides the following configuration. A system is provided that includes a means for receiving user input, a means for processing the received user input, a means for generating an appropriate response through natural language processing, and a means for returning the generated response to the user. Specifically, a cloud-based natural language generation API is used as a means for processing the received user input, and an optimal response is generated in real time based on the user's input. Furthermore, when processing the user input, information about the user's technical problem is included as part of the data, thereby providing more specific and effective support. This makes it possible to quickly and efficiently resolve technical problems faced by users.

[0007] ---

[0008] "User Input" is textual information about a technical problem or question that a user submits to the system.

[0009] "Means for receiving" refers to the interface or protocol for receiving input information from the user and incorporating it into the system.

[0010] A "processing means" is a function or module that performs a series of data processing processes to analyze received user input and generate an appropriate response.

[0011] "Natural language processing" is a technology that allows computers to understand, analyze, and generate language that humans naturally use, and is used to understand the meaning of user input and generate appropriate responses.

[0012] A "means for generating a response" is an algorithm or software component that generates an appropriate answer based on processed user input.

[0013] "Cloud-based" refers to the use of services or resources hosted on remote servers, which in this case means that the natural language generation API resides in the cloud.

[0014] A "natural language generation API" is an application programming interface (API) that uses natural language processing technology to generate human-understandable text based on input data.

[0015] "Means for sending back" refers to a communication means or interface for sending the generated response to the user. [Brief explanation of the drawings]

[0016] [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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] ---

[0038] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes, including receiving input from the user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. An embodiment of the present invention will be described in detail below.

[0039] System Overview

[0040] This system consists of four main functional blocks.

[0041] 1. A means of receiving user input

[0042] 2. A means of processing received user input

[0043] 3. A means of generating appropriate responses through natural language processing

[0044] 4. A means of sending the generated response back to the user

[0045] Specific Description of the Embodiments

[0046] 1. A means of receiving user input

[0047] A user enters technical problems or questions into a terminal and sends them to a server. The user input is primarily in the form of text, and this input is sent to the server over the Internet.

[0048] 2. A means of processing received user input

[0049] The server receives and analyzes user input. It uses natural language processing (NLP) technology to interpret the user input and determine the appropriate response. Specifically, it uses a cloud-based natural language generation API to analyze the intent of the input and the required response.

[0050] 3. A means of generating appropriate responses through natural language processing

[0051] Based on the analysis results, the server calls a cloud-based natural language generation API to generate an appropriate response that is optimized for the user's question and contains the information necessary to solve the problem.

[0052] 4. A means of sending the generated response back to the user

[0053] The server then returns the generated response to the user. Specifically, it formats the response in JSON format and sends it to the user's device. The user receives it and checks the information needed to solve the problem.

[0054] Specific examples

[0055] For example, if a user types, "My laptop battery is dying quickly. What should I do?" the following steps are performed:

[0056] 1. The question entered by the user on the terminal is sent to the server.

[0057] 2. The server receives the user's question and analyzes its content.

[0058] 3. The server uses a natural language generation API to generate appropriate solutions to the battery issue, such as "close unnecessary background applications, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0059] 4. The server sends the generated response back to the user's device, where the user can review it and take specific action to resolve the battery issue.

[0060] In this way, the present invention provides a concrete means for quickly and efficiently resolving technical problems faced by users.

[0061] The processing flow will be explained below.

[0062] ---

[0063] Step 1:

[0064] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[0065] Step 2:

[0066] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[0067] Step 3:

[0068] The server receives the HTTP POST request and extracts the user's message from it.

[0069] Step 4:

[0070] The server passes the extracted user message to a natural language processing module, which performs initial processing to understand the user's intent and analyze the problem.

[0071] Step 5:

[0072] The server sends a request to a cloud-based natural language generation API through a natural language processing module, which includes the user's message and relevant contextual information.

[0073] Step 6:

[0074] A cloud-based natural language generation API processes the incoming request and generates an appropriate response to the user's question.

[0075] Step 7:

[0076] The server receives the generated response from the cloud-based natural language generation API, and then formats the response to remove unnecessary spaces and line breaks.

[0077] Step 8:

[0078] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[0079] Step 9:

[0080] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0081] Step 10:

[0082] The user checks the response displayed on the terminal and takes specific steps to resolve the problem.

[0083] ---

[0084] These are the specific processing steps in this system, allowing users to receive real-time problem-solving support.

[0085] Example 1

[0086] 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."

[0087] In today's information society, users face a wide variety of technical problems. Systems that can quickly and appropriately resolve these problems are important for improving user convenience. However, conventional systems lack the time and accuracy required to generate responses, making it difficult for many users to resolve their problems efficiently.

[0088] 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.

[0089] In this invention, the server includes means for receiving a user input, means for performing text analysis on the received user input, means for generating an appropriate response based on the analysis result using a natural language processing model, and means for sending the generated response to the user, thereby enabling a fast and highly accurate response to the user input to be provided.

[0090] "User input" is a textual query or information provided by a user to the system.

[0091] The "receiving means" is a function for acquiring input data sent from a user via the Internet.

[0092] "Text analysis" is the process of analyzing received user input to understand its intent and content.

[0093] A "natural language processing model" is an algorithm or technology that understands and analyzes text data and generates appropriate responses in human language.

[0094] "Analysis results" are information obtained as a result of text analysis of received user input.

[0095] The "means for generating a response" is a function that generates an appropriate response to a user's question based on the analysis results.

[0096] The "means for transmitting" is a function for transmitting the generated response to the user's terminal.

[0097] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes, receiving input from the user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. An embodiment of the present invention will be described in detail below.

[0098] Hardware and software used

[0099] The following hardware and software are used to implement this system.

[0100] Device: A device used by a user, such as a computer, smartphone, or tablet.

[0101] Server: Cloud-based server for high-performance data processing.

[0102] Natural language processing models: Open source natural language processing libraries and APIs (e.g., GPT-4(R) from OpenAI(R)).

[0103] Data processing and calculation

[0104] User enters text:

[0105] Users enter their problems or questions in text format into an input form on their device, and this input is sent to a server via the Internet.

[0106] The server receives and parses the input:

[0107] The server receives text data sent by users via the Internet, which is then parsed for text analysis, where a natural language processing model (such as OpenAI's GPT-4) is used to analyze the content and intent of the text.

[0108] Response generation based on analysis results:

[0109] The server then calls a cloud-based natural language generation API based on the analysis results to generate an appropriate response to the user's question. The response is optimized to include the information necessary to solve the problem.

[0110] Send a response to the user:

[0111] The generated response is formatted in JSON and sent to the user's device, where the user can view it on screen and take action to resolve the issue.

[0112] Specific examples

[0113] For example, if a user types, "My laptop battery is dying quickly. What should I do?" the following steps are performed:

[0114] 1. The user enters a question into the terminal and sends it.

[0115] 2. The server receives the user's question and analyzes it using a natural language processing model (e.g., OpenAI's GPT-4).

[0116] 3. Based on the analysis results, the server generates an appropriate solution to the battery problem using a natural language generation API. The response includes specific suggestions such as "close unnecessary applications running in the background, lower the display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0117] 4. The server generates a response and sends it back to the user's device, where the user can view it and take action to resolve the battery issue.

[0118] Prompt Sentence Examples

[0119] Prompt statement:

[0120] User Input: 'My laptop battery keeps dying. What should I do?'

[0121] Response: 'Here are some suggestions to resolve the issue of your battery dying quickly. First, close any unnecessary applications running in the background. Also, reduce the display brightness and turn off Wi-Fi and Bluetooth. Additionally, use a battery diagnostic tool to check the health of your battery and consider a new one.'

[0122] Thus, the present invention provides a specific means for quickly and appropriately resolving technical problems faced by users.

[0123] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0124] Step 1:

[0125] The user provides input

[0126] Input: The user enters a question or problem in text format into an input form on the device.

[0127] What happens: The user types "My laptop battery is dying quickly. What should I do?" and clicks the send button.

[0128] Output: The entered text is sent over the Internet to a server.

[0129] Step 2:

[0130] The server receives the input

[0131] Input: Text data sent by the user over the Internet.

[0132] What happens: The server receives input data from the user, stores it in the database, and forwards it to the next stage of analysis.

[0133] Output: saved text data and raw data ready for analysis.

[0134] Step 3:

[0135] The server parses the input data

[0136] Input: Saved text data.

[0137] How it works: The server uses a natural language processing model (e.g., GPT-4) to analyze the intent and content of the text. For example, it recognizes the input information "My battery is running out soon" as "battery problem."

[0138] Data processing: The input text is tokenized and passed to the analysis engine for semantic analysis.

[0139] Output: The analysis results in the specific information of the user's problem (in this case "battery life problem").

[0140] Step 4:

[0141] The server generates an appropriate response

[0142] Input: Specific information about the analysis results.

[0143] Specific operation: The server uses a natural language generation API (e.g., GPT-4) to generate an appropriate response to the user's question based on the analysis results.

[0144] Data processing: Generate responses based on the analysis results, including specific suggestions to address the identified issues.

[0145] Output: The generated response text (e.g. advice such as "Close unnecessary applications running in the background and reduce the brightness of your display").

[0146] Step 5:

[0147] The server sends a response

[0148] Input: The generated response text.

[0149] Specific operation: The server formats the response text in JSON format and sends it to the user's device.

[0150] Output: The response data sent to the user's device.

[0151] Step 6:

[0152] The user receives and acknowledges the response

[0153] Input: The response data sent by the server.

[0154] Specific behavior: The user's device parses the received response data and displays it on the screen. The user can then confirm the displayed information and take action to resolve the problem.

[0155] Output: Information that allows the user to take specific action to resolve the issue.

[0156] Through these steps, the system of the present invention receives input from users about technical problems, analyzes them, and generates and returns appropriate responses to the users, thereby assisting in quick and effective problem resolution.

[0157] (Application example 1)

[0158] 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."

[0159] In modern electronic payment services, there is a growing need for systems that can quickly and appropriately resolve the wide range of technical issues users face. However, there is a lack of systems that provide solutions to these issues, forcing users to expend a great deal of time and effort. In particular, there are limited means to obtain immediate and effective advice on issues such as balance confirmation and transaction failures.

[0160] 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.

[0161] In this invention, the server includes means for receiving user input, means for analyzing the user input, means for generating a response using natural language generation technology, means for sending the generated response to the user, and means for resolving problems related to electronic payments, thereby enabling problems related to electronic payments to be resolved quickly and accurately.

[0162] The "means for receiving user input" refers to a means by which a user can enter textual information about a problem or question relating to an electronic payment and transmit that input to the server.

[0163] The "means for analyzing user input" refers to a means for analyzing received user input and performing processing to identify the problem or generate an appropriate response.

[0164] "Means for generating a response using natural language generation technology" refers to means for generating an appropriate response using natural language processing technology based on analyzed user input.

[0165] The "means for transmitting the generated response to the user" refers to a means for transmitting the generated response to the user's terminal so that the user can check the response.

[0166] "Means for solving problems related to electronic payments" are means for analyzing technical problems related to electronic payments that users face and providing specific solutions.

[0167] MODE FOR CARRYING OUT THE INVENTION

[0168] The present invention relates to a system that allows users to quickly resolve issues related to electronic payments. The system implements a process that receives user input, analyzes it, and uses natural language generation technology to generate and return an appropriate response to the user. Specific embodiments of the present invention are described in detail below.

[0169] System Overview

[0170] The system consists of the following main functional blocks:

[0171] 1. A means of receiving user input

[0172] 2. A way to parse user input

[0173] 3. A means of generating responses using natural language generation technology

[0174] 4. A means of sending the generated response to the user

[0175] 5. Solutions to problems related to electronic payments

[0176] Hardware and software used

[0177] Hardware: User's smartphone and cloud server

[0178] Software: Natural language processing API (e.g., OpenAI GPT-3 (registered trademark)), Flask (Python framework)

[0179] Overview of program processing

[0180] The server receives user input from the smartphone, analyzes the received user input using cloud-based natural language generation technology, generates an appropriate response based on the analysis result, and sends the generated response to the user's smartphone.

[0181] Specific examples

[0182] For example, if a user types the question "My balance isn't showing on my electronic payment app. What should I do?", the steps are as follows:

[0183] 1. Receiving user input: User input is sent to the server via the smartphone.

[0184] 2. User input analysis: The server uses natural language generation technology to analyze the question "My balance is not displayed."

[0185] 3. Response generation: The server uses the OpenAI model to generate a solution such as "Please clear the app cache or log out and log in again. Also, please check your internet connection."

[0186] 4. Response transmission: The generated response is sent to the user's smartphone, allowing the user to take action to resolve the issue.

[0187] Prompt Sentence Examples

[0188] User input: My balance isn't showing up on my electronic payment app. What should I do?

[0189] Please provide a suitable solution.

[0190] The present invention thus provides a concrete means for efficiently and appropriately resolving the technical problems faced by users in relation to electronic payments.

[0191] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0192] Step 1:

[0193] The user inputs problems related to electronic payment via their smartphone. Specifically, the user inputs problems such as insufficient cash or transaction failure in text format, and this input data is sent from the device to the server. The input is the user's question, and the output is the text data sent to the server.

[0194] Step 2:

[0195] The server receives user input. The received data is in text format and is prepared for analysis. In this step, the input is text data from the user and the output is data ready for analysis.

[0196] Step 3:

[0197] The server analyzes the received user input. It uses cloud-based natural language generation technology (specifically, OpenAI's GPT-3 model) to understand the intent of the input text and identify problems. At this step, the input is data ready for analysis, and the output is the analyzed results.

[0198] Step 4:

[0199] The server generates an appropriate response based on the analysis results. It then calls OpenAI's natural language generation API again to generate a solution to the user's identified problem in natural language. The input is the analysis result data, and the output is the generated response text.

[0200] Step 5:

[0201] The server formats the generated response into JSON format and sends it to the user's smartphone. This step has the generated response text as input and the formatted JSON data that is sent to the user's smartphone as output.

[0202] Step 6:

[0203] The user checks the response received on their smartphone and takes specific action based on the content. For example, they follow the on-screen instructions to perform specific problem-solving actions, such as clearing the app cache or logging out and logging back in. In this step, the received response data is the input, and the action to resolve the problem is the output.

[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] ---

[0206] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes: receiving input from a user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the quality of the response can be further improved. An embodiment of the present invention will be described in detail below.

[0207] System Overview

[0208] This system consists of five main functional blocks.

[0209] 1. A means of receiving user input

[0210] 2. A means of processing received user input

[0211] 3. A means of generating appropriate responses through natural language processing

[0212] 4. A means of sending the generated response back to the user

[0213] 5. Emotion engine that recognizes user emotions

[0214] Specific Description of the Embodiments

[0215] 1. A means of receiving user input

[0216] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[0217] 2. A means of processing received user input

[0218] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[0219] The server receives the HTTP POST request and extracts the user's message.

[0220] 3. A means of generating appropriate responses through natural language processing

[0221] The server passes the extracted user message to a natural language processing module to understand the user's intent and analyze the problem, using a cloud-based natural language generation API.

[0222] 4. A means of sending the generated response back to the user

[0223] The server formats the generated response through a natural language processing module, removing unnecessary spaces and line breaks.

[0224] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[0225] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0226] 5. Emotion engine that recognizes user emotions

[0227] When the server analyzes the user's message, it uses an emotion engine to recognize the user's emotion, which extracts emotions from the user's text and adjusts the response based on the emotion.

[0228] The server incorporates the results of the emotion engine into the response generation process to generate an appropriate response that takes into account the user's emotions.

[0229] Specific examples

[0230] For example, if a user types, "My laptop battery keeps dying. What should I do? I'm so worried," the following steps will be performed:

[0231] 1. The question entered by the user on the terminal is sent to the server.

[0232] 2. The server receives the user's question and analyzes its content.

[0233] 3. The emotion engine extracts the emotion of "I'm in trouble" from the user's message.

[0234] 4. The server uses a natural language generation API to generate appropriate, emotion-sensitive solutions to the battery issue, such as "close unnecessary background applications, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0235] 5. The server sends the generated response back to the user's device, where the user can review it and take specific action to resolve the battery issue.

[0236] In this way, the present invention provides a specific means for quickly and appropriately resolving technical problems faced by users, while also realizing responses that take into consideration the feelings of users.

[0237] The processing flow will be explained below.

[0238] ---

[0239] Step 1:

[0240] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[0241] Step 2:

[0242] The device constructs the user's message as an HTTP POST request and sends it to the server over the Internet.

[0243] Step 3:

[0244] The server receives the HTTP POST request and extracts the user's message from the request body.

[0245] Step 4:

[0246] The server passes the extracted user message to the emotion engine, which analyzes the user's emotions. The emotion engine uses natural language processing technology to extract emotions (e.g., troubled, angry, confused, etc.) from the text.

[0247] Step 5:

[0248] The server passes the user's message to the natural language generation API based on the emotion recognition results from the emotion engine, where the emotion recognition results are used as reference information for generating a response.

[0249] Step 6:

[0250] A cloud-based natural language generation API generates an appropriate response based on the user's message and sentiment. The response generated is tailored to the user's sentiment.

[0251] Step 7:

[0252] The server receives the generated response from the cloud-based natural language generation API, and then formats the response to remove unnecessary spaces and line breaks.

[0253] Step 8:

[0254] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[0255] Step 9:

[0256] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0257] Step 10:

[0258] The user checks the response displayed on the device and takes specific steps to resolve the issue, such as closing unnecessary applications running in the background, lowering the display brightness, turning off Wi-Fi and Bluetooth, using the battery diagnostic tool, or replacing the battery.

[0259] ---

[0260] The above are the specific processing steps of this system. In this way, users can receive support for solving problems in real time and receive responses that take their emotions into consideration.

[0261] Example 2

[0262] 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."

[0263] In modern society, users are faced with an increasing number of technical problems, and there is a demand for them to be resolved quickly and accurately. However, conventional systems often provide responses without fully understanding the user's intentions or emotions, which can degrade the quality of the user experience. In particular, when a user is in a difficult situation or in a hurry, not receiving an appropriate response can cause stress. Therefore, a system that can accurately analyze user input, recognize emotions, and provide the most appropriate response is needed.

[0264] 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.

[0265] In this invention, the server includes a means for analyzing user input, a means for performing natural language processing, and a means for recognizing user emotions, which enables the server to accurately understand the user's input and provide an optimal response based on the emotional information.

[0266] "User input" refers to text or questions entered by a user through a terminal.

[0267] "Means for receiving" refers to the function of receiving text entered by a user from a terminal and transmitting that data to a server.

[0268] "Means for analyzing" refers to the analytical function that processes the user's input text received by the server and understands its content and intent.

[0269] "Natural language processing" refers to techniques that allow a server to understand a user's input text and generate a meaningful response in human language.

[0270] "Natural Language Generation API" refers to a cloud-based application programming interface with natural language processing capabilities that generates text.

[0271] An "emotion engine" refers to a software module that extracts emotional information from a user's input text and provides an appropriate response based on the results.

[0272] "Means for generating a response" refers to the server's ability to use natural language processing and an emotion engine to create an appropriate response to a user's question or problem.

[0273] "Means for returning" refers to a function that sends the response generated by the server to the user's terminal so that the user can check the response.

[0274] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes: receiving input from a user, analyzing it, generating an appropriate response using natural language processing technology, and returning it to the user. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to further improve the quality of the response. An embodiment of the present invention will be described in detail below.

[0275] System Overview

[0276] The system consists of seven main functional blocks:

[0277] 1. A means of receiving user input

[0278] 2. A means of sending received user input to the server

[0279] 3. A way to parse user input on the server

[0280] 4. How to process natural language on the server

[0281] 5. How to recognize user emotions on the server

[0282] 6. Means of generating a response on the server

[0283] 7. A means of sending the generated response back to the user

[0284] Specific Description of the Embodiments

[0285] 1. A means of receiving user input

[0286] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[0287] 2. A means of sending received user input to the server

[0288] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[0289] The server receives the HTTP POST request and extracts the user's message.

[0290] 3. A way to parse user input on the server

[0291] The server passes the extracted user message to a natural language processing module to understand the user's intent and analyze the problem, using a cloud-based natural language generation API.

[0292] 4. How to process natural language on the server

[0293] The server obtains a response generated based on the results of the previous analysis using a cloud-based natural language generation API (e.g., a generative AI model).

[0294] 5. How to recognize user emotions on the server

[0295] When the server analyzes the user's message, it uses an emotion engine to recognize the user's emotion, extracting emotions from the user's text and adjusting the response accordingly.

[0296] 6. Means of generating a response on the server

[0297] The server uses the results of the emotion engine and the natural language generation API to generate an optimal response, which takes into account the user's emotions.

[0298] The server will format the generated response, removing unnecessary spaces and line breaks, and the final response will be constructed in JSON format.

[0299] 7. A means of sending the generated response back to the user

[0300] The server sends the formatted response to the terminal over the Internet.

[0301] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0302] Specific examples

[0303] For example, if a user types, "My laptop battery keeps dying. What should I do? I'm so worried.", the steps are as follows:

[0304] 1. The user enters the above text into the terminal and presses the send button.

[0305] 2. The device sends this input text to the server as an HTTP POST request.

[0306] 3. The server receives the request and extracts the text content.

[0307] 4. The server uses a natural language processing module to analyze the battery problem and the question.

[0308] 5. The server uses the emotion engine to extract the emotion "troubled."

[0309] 6. The server generates a response suggesting specific battery solutions, such as: "Close unnecessary applications running in the background, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0310] 7. The server sends the generated response in JSON format to the device.

[0311] 8. The device parses the JSON response and displays solutions to the user, such as closing unnecessary applications running in the background, lowering the display brightness, turning off Wi-Fi and Bluetooth, using a battery diagnostic tool, or replacing the battery.

[0312] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0313] System program processing flow

[0314] Step 1:

[0315] The user enters text

[0316] The user types a technical problem or question into the terminal and clicks the send button.

[0317] Input: A user's textual question or problem (e.g., "My laptop battery keeps dying. What should I do? I'm so frustrated.").

[0318] Output: Text data entered into the terminal.

[0319] Step 2:

[0320] The device sends user input to the server

[0321] The terminal constructs the entered user message as an HTTP POST request.

[0322] The terminal transmits the data to a server via the Internet.

[0323] Input: Text data entered into the terminal.

[0324] Output: User message in the form of an HTTP POST request.

[0325] Step 3:

[0326] The server receives and parses the user input

[0327] The server receives the HTTP POST request and extracts the user's message from the request body.

[0328] Input: HTTP POST request.

[0329] Output: The extracted user's message text.

[0330] Step 4:

[0331] The server processes natural language

[0332] The server passes the extracted user messages to a natural language processing module, which analyzes the intent and subject of the text.

[0333] Input: The extracted user's message text.

[0334] Output: Intent and thematic information resulting from the analysis.

[0335] Step 5:

[0336] The server recognizes the user's emotions

[0337] The server uses an emotion engine to extract emotional information from the user's message, for example, determining whether the user is feeling "troubled."

[0338] Input: The user's message text.

[0339] Output: Extracted emotion information.

[0340] Step 6:

[0341] The server generates a response

[0342] The server uses the natural language generation API to generate the optimal response based on the results of the natural language processing module and the emotion engine.

[0343] As specific actions, the server invokes the generative AI model to generate solutions to the battery problem, such as "close unnecessary applications running in the background, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0344] Input: Intention, subject matter information, and emotional information.

[0345] Output: The generated response text.

[0346] Step 7:

[0347] The server formats the generated response

[0348] The server formats the generated response, removing unnecessary spaces and line breaks, and constructs the final response in JSON format.

[0349] Input: The generated response text.

[0350] Output: Pretty-printed JSON response.

[0351] Step 8:

[0352] The server sends the response back to the user

[0353] The server sends a JSON-formatted response to the device over the Internet.

[0354] Input: The response in JSON format.

[0355] Output: Data sent to the terminal.

[0356] Step 9:

[0357] The terminal parses and displays the response

[0358] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0359] Input: The JSON response received from the server.

[0360] Output: The response text that can be displayed to the user.

[0361] Step 10:

[0362] User reviews response and takes action

[0363] The user reviews the response displayed on the device and takes specific action based on the solution provided.

[0364] Input: The response text displayed on the user's terminal.

[0365] Output: User behavior and corresponding actions.

[0366] (Application example 2)

[0367] 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."

[0368] Conventional electronic payment services have difficulty providing prompt and appropriate support for technical problems faced by users. Furthermore, support does not take into consideration the user's feelings, which can lead to a poor user experience. Therefore, a new system is needed that can quickly grasp the user's situation and provide an appropriate solution.

[0369] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0370] In this invention, the server includes means for receiving user input, means for analyzing the user's emotions, means for generating an appropriate response through natural language processing, and means for returning the generated response to the user, thereby enabling technical problems to be resolved quickly and appropriately while taking the user's emotions into consideration.

[0371] "Means for receiving user input" refers to the function by which a terminal or system receives information such as text or voice input by a user and recognizes it as data to be processed.

[0372] The "means for processing received user input" is a function for analyzing received user input information and performing processing to derive an appropriate response based on the content of the information.

[0373] "Means for generating an appropriate response through natural language processing" is a function that uses natural language processing technology to interpret the user's input and generate an appropriate and meaningful response.

[0374] The "means for returning the generated response to the user" is a function for sending the response generated by natural language processing to the user's terminal so that the user can receive and confirm it.

[0375] The "means for analyzing user emotions" is a function that extracts emotions from the user's input and adjusts the content and tone of the response based on those emotions.

[0376] MODE FOR CARRYING OUT THE INVENTION

[0377] System Overview

[0378] This invention is a system that allows users to quickly and appropriately resolve technical problems in electronic payment services. The system aims to generate appropriate responses to problems input by users and to respond in a way that takes into account their emotions.

[0379] Technologies and tools used

[0380] Hardware: Smartphones, smart glasses

[0381] Software: Python®-based server, natural language processing API (e.g., OpenAI's GPT-3), sentiment analysis engine (e.g., IBM Watson® Tone Analyzer)

[0382] Program Description

[0383] The server implements the system using the following means:

[0384] Ways to receive user input:

[0385] It receives text and voice data entered by the user through a smartphone or smart glasses, and sends this data to the server as an HTTP POST request.

[0386] Ways to analyze user sentiment:

[0387] IBM Watson Tone Analyzer is used to extract sentiment from incoming user input, and this sentiment information is used to tailor responses during subsequent natural language processing.

[0388] A means of generating appropriate responses through natural language processing:

[0389] It uses natural language generation APIs like OpenAI's GPT-3 to generate appropriate responses based on the user's text input, taking into account the emotional information extracted earlier.

[0390] A means of sending the generated response back to the user:

[0391] The server generates a response and sends it in JSON format to the user's device, which parses it and displays it to the user.

[0392] Processing flow

[0393] The server receives user input, passes it to IBM Watson Tone Analyzer to analyze emotions, then uses OpenAI's GPT-3 for natural language processing to generate a response that takes the user's emotions into account, and sends this response in JSON format to the user's device for display.

[0394] Specific examples

[0395] For example, if a user enters "My payment has failed due to an error. What should I do?" while using an electronic payment service, the following process will be performed.

[0396] 1. The user enters a question into their smartphone, which is then sent to the server.

[0397] 2. The server receives the question, analyzes it using IBM Watson Tone Analyzer, and extracts the emotion of "troubled."

[0398] 3. The server uses OpenAI's GPT-3 to generate a sentiment-based response, which might say something like, "It looks like you've encountered a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try changing your payment method or contact our support center. We apologize for any inconvenience."

[0399] 4. The server sends the generated response in JSON format to the user's smartphone, where the user confirms the response.

[0400] Prompt Sentence Examples

[0401] Below are some example prompts to input to the generative AI model:

[0402] Please respond appropriately to the following question, taking into consideration the user's feelings.\nUser's question: {{ user_message}}"

[0403] As described above, by combining these means and technologies, we will realize a system that quickly and appropriately resolves technical problems faced by users.

[0404] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0405] Step 1:

[0406] Users use their smartphones or smart glasses to input technical questions about electronic payments. The user's question is sent in text format to the device, which is then sent to the server as an HTTP POST request.

[0407] Input: User's text message

[0408] Output: HTTP POST request

[0409] Step 2:

[0410] The server receives the incoming HTTP POST request and analyzes its contents.

[0411] Input: HTTP POST request (containing the user's text message)

[0412] Output: User's text message

[0413] Step 3:

[0414] The server passes the user's message to IBM Watson Tone Analyzer for sentiment analysis. The sentiment analysis engine detects the tone of the message and extracts the user's emotional information.

[0415] Input: User's text message

[0416] Output: User's emotional state (e.g., troubled, angry, etc.)

[0417] Step 4:

[0418] The server passes the results of the sentiment analysis engine and the user's message to OpenAI GPT-3 to generate an appropriate response. The prompt sentence is used to provide instructions to the generative AI model to generate an emotion-sensitive response.

[0419] Input: User text message, user emotion information

[0420] Output: The response generated by natural language processing

[0421] Step 5:

[0422] The server formats the generated response, removing unnecessary spaces and line breaks, and constructs the response in JSON format.

[0423] Input: A response generated by natural language processing

[0424] Output: Formatted response (JSON format)

[0425] Step 6:

[0426] The server sends the formatted response to the user's terminal, which receives the response, converts it into a format that is displayed to the user, and displays it.

[0427] Input: Formatted response (JSON format)

[0428] Output: A text response in a format that can be viewed by the user

[0429] Specific examples

[0430] For example, the specific processing flow when a user inputs "My payment has not gone through due to an error. What should I do?" is shown below.

[0431] Step 1:

[0432] Enter: "My payment is not going through. What should I do?"

[0433] Output: HTTP POST request

[0434] Step 2:

[0435] Input: HTTP POST request

[0436] Output: "My payment failed due to an error. What should I do?"

[0437] Step 3:

[0438] Enter: "My payment is not going through. What should I do?"

[0439] Output: "I'm in trouble"

[0440] Step 4:

[0441] Input: "My payment is not going through. What should I do?" "I'm in trouble."

[0442] Output: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[0443] Step 5:

[0444] Input: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[0445] Output: JSON response

[0446] Step 6:

[0447] Input: JSON formatted response

[0448] Output: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[0449] 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.

[0450] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0451] 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.

[0452] [Second embodiment]

[0453] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0454] 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.

[0455] 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).

[0456] 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.

[0457] 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.

[0458] 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).

[0459] 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.

[0460] 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.

[0461] 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.

[0462] 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.

[0463] 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.

[0464] 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."

[0465] ---

[0466] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes, including receiving input from the user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. An embodiment of the present invention will be described in detail below.

[0467] System Overview

[0468] This system consists of four main functional blocks.

[0469] 1. A means of receiving user input

[0470] 2. A means of processing received user input

[0471] 3. A means of generating appropriate responses through natural language processing

[0472] 4. A means of sending the generated response back to the user

[0473] Specific Description of the Embodiments

[0474] 1. A means of receiving user input

[0475] A user enters technical problems or questions into a terminal and sends them to a server. The user input is primarily in the form of text, and this input is sent to the server over the Internet.

[0476] 2. A means of processing received user input

[0477] The server receives and analyzes user input. It uses natural language processing (NLP) technology to interpret the user input and determine the appropriate response. Specifically, it uses a cloud-based natural language generation API to analyze the intent of the input and the required response.

[0478] 3. A means of generating appropriate responses through natural language processing

[0479] Based on the analysis results, the server calls a cloud-based natural language generation API to generate an appropriate response that is optimized for the user's question and contains the information necessary to solve the problem.

[0480] 4. A means of sending the generated response back to the user

[0481] The server then returns the generated response to the user. Specifically, it formats the response in JSON format and sends it to the user's device. The user receives it and checks the information needed to solve the problem.

[0482] Specific examples

[0483] For example, if a user types, "My laptop battery is dying quickly. What should I do?" the following steps are performed:

[0484] 1. The question entered by the user on the terminal is sent to the server.

[0485] 2. The server receives the user's question and analyzes its content.

[0486] 3. The server uses a natural language generation API to generate appropriate solutions to the battery issue, such as "close unnecessary background applications, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0487] 4. The server sends the generated response back to the user's device, where the user can review it and take specific action to resolve the battery issue.

[0488] In this way, the present invention provides a concrete means for quickly and efficiently resolving technical problems faced by users.

[0489] The processing flow will be explained below.

[0490] ---

[0491] Step 1:

[0492] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[0493] Step 2:

[0494] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[0495] Step 3:

[0496] The server receives the HTTP POST request and extracts the user's message from it.

[0497] Step 4:

[0498] The server passes the extracted user message to a natural language processing module, which performs initial processing to understand the user's intent and analyze the problem.

[0499] Step 5:

[0500] The server sends a request to a cloud-based natural language generation API through a natural language processing module, which includes the user's message and relevant contextual information.

[0501] Step 6:

[0502] A cloud-based natural language generation API processes the incoming request and generates an appropriate response to the user's question.

[0503] Step 7:

[0504] The server receives the generated response from the cloud-based natural language generation API, and then formats the response to remove unnecessary spaces and line breaks.

[0505] Step 8:

[0506] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[0507] Step 9:

[0508] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0509] Step 10:

[0510] The user checks the response displayed on the terminal and takes specific steps to resolve the problem.

[0511] ---

[0512] These are the specific processing steps in this system, allowing users to receive real-time problem-solving support.

[0513] Example 1

[0514] 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."

[0515] In today's information society, users face a wide variety of technical problems. Systems that can quickly and appropriately resolve these problems are important for improving user convenience. However, conventional systems lack the time and accuracy required to generate responses, making it difficult for many users to resolve their problems efficiently.

[0516] 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.

[0517] In this invention, the server includes means for receiving a user input, means for performing text analysis on the received user input, means for generating an appropriate response based on the analysis result using a natural language processing model, and means for sending the generated response to the user, thereby enabling a fast and highly accurate response to the user input to be provided.

[0518] "User input" is a textual query or information provided by a user to the system.

[0519] The "receiving means" is a function for acquiring input data sent from a user via the Internet.

[0520] "Text analysis" is the process of analyzing received user input to understand its intent and content.

[0521] A "natural language processing model" is an algorithm or technology that understands and analyzes text data and generates appropriate responses in human language.

[0522] "Analysis results" are information obtained as a result of text analysis of received user input.

[0523] The "means for generating a response" is a function that generates an appropriate response to a user's question based on the analysis results.

[0524] The "means for transmitting" is a function for transmitting the generated response to the user's terminal.

[0525] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes, receiving input from the user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. An embodiment of the present invention will be described in detail below.

[0526] Hardware and software used

[0527] The following hardware and software are used to implement this system.

[0528] Device: A device used by a user, such as a computer, smartphone, or tablet.

[0529] Server: Cloud-based server for high-performance data processing.

[0530] Natural language processing models: Open source natural language processing libraries and APIs (e.g., OpenAI's GPT-4).

[0531] Data processing and calculation

[0532] User enters text:

[0533] Users enter their problems or questions in text format into an input form on their device, and this input is sent to a server via the Internet.

[0534] The server receives and parses the input:

[0535] The server receives text data sent by users via the Internet, which is then parsed for text analysis, where a natural language processing model (such as OpenAI's GPT-4) is used to analyze the content and intent of the text.

[0536] Response generation based on analysis results:

[0537] The server then calls a cloud-based natural language generation API based on the analysis results to generate an appropriate response to the user's question. The response is optimized to include the information necessary to solve the problem.

[0538] Send a response to the user:

[0539] The generated response is formatted in JSON and sent to the user's device, where the user can view it on screen and take action to resolve the issue.

[0540] Specific examples

[0541] For example, if a user types, "My laptop battery is dying quickly. What should I do?" the following steps are performed:

[0542] 1. The user enters a question into the terminal and sends it.

[0543] 2. The server receives the user's question and analyzes it using a natural language processing model (e.g., OpenAI's GPT-4).

[0544] 3. Based on the analysis results, the server generates an appropriate solution to the battery problem using a natural language generation API. The response includes specific suggestions such as "close unnecessary applications running in the background, lower the display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0545] 4. The server generates a response and sends it back to the user's device, where the user can view it and take action to resolve the battery issue.

[0546] Prompt Sentence Examples

[0547] Prompt statement:

[0548] User Input: 'My laptop battery keeps dying. What should I do?'

[0549] Response: 'Here are some suggestions to resolve the issue of your battery dying quickly. First, close any unnecessary applications running in the background. Also, reduce the display brightness and turn off Wi-Fi and Bluetooth. Additionally, use a battery diagnostic tool to check the health of your battery and consider a new one.'

[0550] Thus, the present invention provides a specific means for quickly and appropriately resolving technical problems faced by users.

[0551] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0552] Step 1:

[0553] The user provides input

[0554] Input: The user enters a question or problem in text format into an input form on the device.

[0555] What happens: The user types "My laptop battery is dying quickly. What should I do?" and clicks the send button.

[0556] Output: The entered text is sent over the Internet to a server.

[0557] Step 2:

[0558] The server receives the input

[0559] Input: Text data sent by the user over the Internet.

[0560] What happens: The server receives input data from the user, stores it in the database, and forwards it to the next stage of analysis.

[0561] Output: saved text data and raw data ready for analysis.

[0562] Step 3:

[0563] The server parses the input data

[0564] Input: Saved text data.

[0565] How it works: The server uses a natural language processing model (e.g., GPT-4) to analyze the intent and content of the text. For example, it recognizes the input information "My battery is running out soon" as "battery problem."

[0566] Data processing: The input text is tokenized and passed to the analysis engine for semantic analysis.

[0567] Output: The analysis results in the specific information of the user's problem (in this case "battery life problem").

[0568] Step 4:

[0569] The server generates an appropriate response

[0570] Input: Specific information about the analysis results.

[0571] Specific operation: The server uses a natural language generation API (e.g., GPT-4) to generate an appropriate response to the user's question based on the analysis results.

[0572] Data processing: Generate responses based on the analysis results, including specific suggestions to address the identified issues.

[0573] Output: The generated response text (e.g. advice such as "Close unnecessary applications running in the background and reduce the brightness of your display").

[0574] Step 5:

[0575] The server sends a response

[0576] Input: The generated response text.

[0577] Specific operation: The server formats the response text in JSON format and sends it to the user's device.

[0578] Output: The response data sent to the user's device.

[0579] Step 6:

[0580] The user receives and acknowledges the response

[0581] Input: The response data sent by the server.

[0582] Specific behavior: The user's device parses the received response data and displays it on the screen. The user can then confirm the displayed information and take action to resolve the problem.

[0583] Output: Information that allows the user to take specific action to resolve the issue.

[0584] Through these steps, the system of the present invention receives input from users about technical problems, analyzes them, and generates and returns appropriate responses to the users, thereby assisting in quick and effective problem resolution.

[0585] (Application example 1)

[0586] 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."

[0587] In modern electronic payment services, there is a growing need for systems that can quickly and appropriately resolve the wide range of technical issues users face. However, there is a lack of systems that provide solutions to these issues, forcing users to expend a great deal of time and effort. In particular, there are limited means to obtain immediate and effective advice on issues such as balance confirmation and transaction failures.

[0588] 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.

[0589] In this invention, the server includes means for receiving user input, means for analyzing the user input, means for generating a response using natural language generation technology, means for sending the generated response to the user, and means for resolving problems related to electronic payments, thereby enabling problems related to electronic payments to be resolved quickly and accurately.

[0590] The "means for receiving user input" refers to a means by which a user can enter textual information about a problem or question relating to an electronic payment and transmit that input to the server.

[0591] The "means for analyzing user input" refers to a means for analyzing received user input and performing processing to identify the problem or generate an appropriate response.

[0592] "Means for generating a response using natural language generation technology" refers to means for generating an appropriate response using natural language processing technology based on analyzed user input.

[0593] The "means for transmitting the generated response to the user" refers to a means for transmitting the generated response to the user's terminal so that the user can check the response.

[0594] "Means for solving problems related to electronic payments" are means for analyzing technical problems related to electronic payments that users face and providing specific solutions.

[0595] MODE FOR CARRYING OUT THE INVENTION

[0596] The present invention relates to a system that allows users to quickly resolve issues related to electronic payments. The system implements a process that receives user input, analyzes it, and uses natural language generation technology to generate and return an appropriate response to the user. Specific embodiments of the present invention are described in detail below.

[0597] System Overview

[0598] The system consists of the following main functional blocks:

[0599] 1. A means of receiving user input

[0600] 2. A way to parse user input

[0601] 3. A means of generating responses using natural language generation technology

[0602] 4. A means of sending the generated response to the user

[0603] 5. Solutions to problems related to electronic payments

[0604] Hardware and software used

[0605] Hardware: User's smartphone and cloud server

[0606] Software: Natural language processing API (e.g., OpenAI GPT-3), Flask (Python framework)

[0607] Overview of program processing

[0608] The server receives user input from the smartphone, analyzes the received user input using cloud-based natural language generation technology, generates an appropriate response based on the analysis result, and sends the generated response to the user's smartphone.

[0609] Specific examples

[0610] For example, if a user types the question "My balance isn't showing on my electronic payment app. What should I do?", the steps are as follows:

[0611] 1. Receiving user input: User input is sent to the server via the smartphone.

[0612] 2. User input analysis: The server uses natural language generation technology to analyze the question "My balance is not displayed."

[0613] 3. Response generation: The server uses the OpenAI model to generate a solution such as "Please clear the app cache or log out and log in again. Also, please check your internet connection."

[0614] 4. Response transmission: The generated response is sent to the user's smartphone, allowing the user to take action to resolve the issue.

[0615] Prompt Sentence Examples

[0616] User input: My balance isn't showing up on my electronic payment app. What should I do?

[0617] Please provide a suitable solution.

[0618] The present invention thus provides a concrete means for efficiently and appropriately resolving the technical problems faced by users in relation to electronic payments.

[0619] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0620] Step 1:

[0621] The user inputs problems related to electronic payment via their smartphone. Specifically, the user inputs problems such as insufficient cash or transaction failure in text format, and this input data is sent from the device to the server. The input is the user's question, and the output is the text data sent to the server.

[0622] Step 2:

[0623] The server receives user input. The received data is in text format and is prepared for analysis. In this step, the input is text data from the user and the output is data ready for analysis.

[0624] Step 3:

[0625] The server analyzes the received user input. It uses cloud-based natural language generation technology (specifically, OpenAI's GPT-3 model) to understand the intent of the input text and identify problems. At this step, the input is data ready for analysis, and the output is the analyzed results.

[0626] Step 4:

[0627] The server generates an appropriate response based on the analysis results. It then calls OpenAI's natural language generation API again to generate a solution to the user's identified problem in natural language. The input is the analysis result data, and the output is the generated response text.

[0628] Step 5:

[0629] The server formats the generated response into JSON format and sends it to the user's smartphone. This step has the generated response text as input and the formatted JSON data that is sent to the user's smartphone as output.

[0630] Step 6:

[0631] The user checks the response received on their smartphone and takes specific action based on the content. For example, they follow the on-screen instructions to perform specific problem-solving actions, such as clearing the app cache or logging out and logging back in. In this step, the received response data is the input, and the action to resolve the problem is the output.

[0632] 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.

[0633] ---

[0634] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes: receiving input from a user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the quality of the response can be further improved. An embodiment of the present invention will be described in detail below.

[0635] System Overview

[0636] This system consists of five main functional blocks.

[0637] 1. A means of receiving user input

[0638] 2. A means of processing received user input

[0639] 3. A means of generating appropriate responses through natural language processing

[0640] 4. A means of sending the generated response back to the user

[0641] 5. Emotion engine that recognizes user emotions

[0642] Specific Description of the Embodiments

[0643] 1. A means of receiving user input

[0644] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[0645] 2. A means of processing received user input

[0646] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[0647] The server receives the HTTP POST request and extracts the user's message.

[0648] 3. A means of generating appropriate responses through natural language processing

[0649] The server passes the extracted user message to a natural language processing module to understand the user's intent and analyze the problem, using a cloud-based natural language generation API.

[0650] 4. A means of sending the generated response back to the user

[0651] The server formats the generated response through a natural language processing module, removing unnecessary spaces and line breaks.

[0652] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[0653] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0654] 5. Emotion engine that recognizes user emotions

[0655] When the server analyzes the user's message, it uses an emotion engine to recognize the user's emotion, which extracts emotions from the user's text and adjusts the response based on the emotion.

[0656] The server incorporates the results of the emotion engine into the response generation process to generate an appropriate response that takes into account the user's emotions.

[0657] Specific examples

[0658] For example, if a user types, "My laptop battery keeps dying. What should I do? I'm so worried," the following steps will be performed:

[0659] 1. The question entered by the user on the terminal is sent to the server.

[0660] 2. The server receives the user's question and analyzes its content.

[0661] 3. The emotion engine extracts the emotion of "I'm in trouble" from the user's message.

[0662] 4. The server uses a natural language generation API to generate appropriate, emotion-sensitive solutions to the battery issue, such as "close unnecessary background applications, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0663] 5. The server sends the generated response back to the user's device, where the user can review it and take specific action to resolve the battery issue.

[0664] In this way, the present invention provides a specific means for quickly and appropriately resolving technical problems faced by users, while also realizing responses that take into consideration the feelings of users.

[0665] The processing flow will be explained below.

[0666] ---

[0667] Step 1:

[0668] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[0669] Step 2:

[0670] The device constructs the user's message as an HTTP POST request and sends it to the server over the Internet.

[0671] Step 3:

[0672] The server receives the HTTP POST request and extracts the user's message from the request body.

[0673] Step 4:

[0674] The server passes the extracted user message to the emotion engine, which analyzes the user's emotions. The emotion engine uses natural language processing technology to extract emotions (e.g., troubled, angry, confused, etc.) from the text.

[0675] Step 5:

[0676] The server passes the user's message to the natural language generation API based on the emotion recognition results from the emotion engine, where the emotion recognition results are used as reference information for generating a response.

[0677] Step 6:

[0678] A cloud-based natural language generation API generates an appropriate response based on the user's message and sentiment. The response generated is tailored to the user's sentiment.

[0679] Step 7:

[0680] The server receives the generated response from the cloud-based natural language generation API, and then formats the response to remove unnecessary spaces and line breaks.

[0681] Step 8:

[0682] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[0683] Step 9:

[0684] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0685] Step 10:

[0686] The user checks the response displayed on the device and takes specific steps to resolve the issue, such as closing unnecessary applications running in the background, lowering the display brightness, turning off Wi-Fi and Bluetooth, using the battery diagnostic tool, or replacing the battery.

[0687] ---

[0688] The above are the specific processing steps of this system. In this way, users can receive support for solving problems in real time and receive responses that take their emotions into consideration.

[0689] Example 2

[0690] 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."

[0691] In modern society, users are faced with an increasing number of technical problems, and there is a demand for them to be resolved quickly and accurately. However, conventional systems often provide responses without fully understanding the user's intentions or emotions, which can degrade the quality of the user experience. In particular, when a user is in a difficult situation or in a hurry, not receiving an appropriate response can cause stress. Therefore, a system that can accurately analyze user input, recognize emotions, and provide the most appropriate response is needed.

[0692] 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.

[0693] In this invention, the server includes a means for analyzing user input, a means for performing natural language processing, and a means for recognizing user emotions, which enables the server to accurately understand the user's input and provide an optimal response based on the emotional information.

[0694] "User input" refers to text or questions entered by a user through a terminal.

[0695] "Means for receiving" refers to the function of receiving text entered by a user from a terminal and transmitting that data to a server.

[0696] "Means for analyzing" refers to the analytical function that processes the user's input text received by the server and understands its content and intent.

[0697] "Natural language processing" refers to techniques that allow a server to understand a user's input text and generate a meaningful response in human language.

[0698] "Natural Language Generation API" refers to a cloud-based application programming interface with natural language processing capabilities that generates text.

[0699] An "emotion engine" refers to a software module that extracts emotional information from a user's input text and provides an appropriate response based on the results.

[0700] "Means for generating a response" refers to the server's ability to use natural language processing and an emotion engine to create an appropriate response to a user's question or problem.

[0701] "Means for returning" refers to a function that sends the response generated by the server to the user's terminal so that the user can check the response.

[0702] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes: receiving input from a user, analyzing it, generating an appropriate response using natural language processing technology, and returning it to the user. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to further improve the quality of the response. An embodiment of the present invention will be described in detail below.

[0703] System Overview

[0704] The system consists of seven main functional blocks:

[0705] 1. A means of receiving user input

[0706] 2. A means of sending received user input to the server

[0707] 3. A way to parse user input on the server

[0708] 4. How to process natural language on the server

[0709] 5. How to recognize user emotions on the server

[0710] 6. Means of generating a response on the server

[0711] 7. A means of sending the generated response back to the user

[0712] Specific Description of the Embodiments

[0713] 1. A means of receiving user input

[0714] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[0715] 2. A means of sending received user input to the server

[0716] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[0717] The server receives the HTTP POST request and extracts the user's message.

[0718] 3. A way to parse user input on the server

[0719] The server passes the extracted user message to a natural language processing module to understand the user's intent and analyze the problem, using a cloud-based natural language generation API.

[0720] 4. How to process natural language on the server

[0721] The server obtains a response generated based on the results of the previous analysis using a cloud-based natural language generation API (e.g., a generative AI model).

[0722] 5. How to recognize user emotions on the server

[0723] When the server analyzes the user's message, it uses an emotion engine to recognize the user's emotion, extracting emotions from the user's text and adjusting the response accordingly.

[0724] 6. Means of generating a response on the server

[0725] The server uses the results of the emotion engine and the natural language generation API to generate an optimal response, which takes into account the user's emotions.

[0726] The server will format the generated response, removing unnecessary spaces and line breaks, and the final response will be constructed in JSON format.

[0727] 7. A means of sending the generated response back to the user

[0728] The server sends the formatted response to the terminal over the Internet.

[0729] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0730] Specific examples

[0731] For example, if a user types, "My laptop battery keeps dying. What should I do? I'm so worried.", the steps are as follows:

[0732] 1. The user enters the above text into the terminal and presses the send button.

[0733] 2. The device sends this input text to the server as an HTTP POST request.

[0734] 3. The server receives the request and extracts the text content.

[0735] 4. The server uses a natural language processing module to analyze the battery problem and the question.

[0736] 5. The server uses the emotion engine to extract the emotion "troubled."

[0737] 6. The server generates a response suggesting specific battery solutions, such as: "Close unnecessary applications running in the background, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0738] 7. The server sends the generated response in JSON format to the device.

[0739] 8. The device parses the JSON response and displays solutions to the user, such as closing unnecessary applications running in the background, lowering the display brightness, turning off Wi-Fi and Bluetooth, using a battery diagnostic tool, or replacing the battery.

[0740] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0741] System program processing flow

[0742] Step 1:

[0743] The user enters text

[0744] The user types a technical problem or question into the terminal and clicks the send button.

[0745] Input: A user's textual question or problem (e.g., "My laptop battery keeps dying. What should I do? I'm so frustrated.").

[0746] Output: Text data entered into the terminal.

[0747] Step 2:

[0748] The device sends user input to the server

[0749] The terminal constructs the entered user message as an HTTP POST request.

[0750] The terminal transmits the data to a server via the Internet.

[0751] Input: Text data entered into the terminal.

[0752] Output: User message in the form of an HTTP POST request.

[0753] Step 3:

[0754] The server receives and parses the user input

[0755] The server receives the HTTP POST request and extracts the user's message from the request body.

[0756] Input: HTTP POST request.

[0757] Output: The extracted user's message text.

[0758] Step 4:

[0759] The server processes natural language

[0760] The server passes the extracted user messages to a natural language processing module, which analyzes the intent and subject of the text.

[0761] Input: The extracted user's message text.

[0762] Output: Intent and thematic information resulting from the analysis.

[0763] Step 5:

[0764] The server recognizes the user's emotions

[0765] The server uses an emotion engine to extract emotional information from the user's message, for example, determining whether the user is feeling "troubled."

[0766] Input: The user's message text.

[0767] Output: Extracted emotion information.

[0768] Step 6:

[0769] The server generates a response

[0770] The server uses the natural language generation API to generate the optimal response based on the results of the natural language processing module and the emotion engine.

[0771] As specific actions, the server invokes the generative AI model to generate solutions to the battery problem, such as "close unnecessary applications running in the background, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0772] Input: Intention, subject matter information, and emotional information.

[0773] Output: The generated response text.

[0774] Step 7:

[0775] The server formats the generated response

[0776] The server formats the generated response, removing unnecessary spaces and line breaks, and constructs the final response in JSON format.

[0777] Input: The generated response text.

[0778] Output: Pretty-printed JSON response.

[0779] Step 8:

[0780] The server sends the response back to the user

[0781] The server sends a JSON-formatted response to the device over the Internet.

[0782] Input: The response in JSON format.

[0783] Output: Data sent to the terminal.

[0784] Step 9:

[0785] The terminal parses and displays the response

[0786] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0787] Input: The JSON response received from the server.

[0788] Output: The response text that can be displayed to the user.

[0789] Step 10:

[0790] User reviews response and takes action

[0791] The user reviews the response displayed on the device and takes specific action based on the solution provided.

[0792] Input: The response text displayed on the user's terminal.

[0793] Output: User behavior and corresponding actions.

[0794] (Application example 2)

[0795] 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."

[0796] Conventional electronic payment services have difficulty providing prompt and appropriate support for technical problems faced by users. Furthermore, support does not take into consideration the user's feelings, which can lead to a poor user experience. Therefore, a new system is needed that can quickly grasp the user's situation and provide an appropriate solution.

[0797] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0798] In this invention, the server includes means for receiving user input, means for analyzing the user's emotions, means for generating an appropriate response through natural language processing, and means for returning the generated response to the user, thereby enabling technical problems to be resolved quickly and appropriately while taking the user's emotions into consideration.

[0799] "Means for receiving user input" refers to the function by which a terminal or system receives information such as text or voice input by a user and recognizes it as data to be processed.

[0800] The "means for processing received user input" is a function for analyzing received user input information and performing processing to derive an appropriate response based on the content of the information.

[0801] "Means for generating an appropriate response through natural language processing" is a function that uses natural language processing technology to interpret the user's input and generate an appropriate and meaningful response.

[0802] The "means for returning the generated response to the user" is a function for sending the response generated by natural language processing to the user's terminal so that the user can receive and confirm it.

[0803] The "means for analyzing user emotions" is a function that extracts emotions from the user's input and adjusts the content and tone of the response based on those emotions.

[0804] MODE FOR CARRYING OUT THE INVENTION

[0805] System Overview

[0806] This invention is a system that allows users to quickly and appropriately resolve technical problems in electronic payment services. The system aims to generate appropriate responses to problems input by users and to respond in a way that takes into account their emotions.

[0807] Technologies and tools used

[0808] Hardware: Smartphones, smart glasses

[0809] Software: Python-based server, natural language processing API (e.g., OpenAI's GPT-3), sentiment analysis engine (e.g., IBM Watson Tone Analyzer)

[0810] Program Description

[0811] The server implements the system using the following means:

[0812] Ways to receive user input:

[0813] It receives text and voice data entered by the user through a smartphone or smart glasses, and sends this data to the server as an HTTP POST request.

[0814] Ways to analyze user sentiment:

[0815] IBM Watson Tone Analyzer is used to extract sentiment from incoming user input, and this sentiment information is used to tailor responses during subsequent natural language processing.

[0816] A means of generating appropriate responses through natural language processing:

[0817] It uses natural language generation APIs like OpenAI's GPT-3 to generate appropriate responses based on the user's text input, taking into account the emotional information extracted earlier.

[0818] A means of sending the generated response back to the user:

[0819] The server generates a response and sends it in JSON format to the user's device, which parses it and displays it to the user.

[0820] Processing flow

[0821] The server receives user input, passes it to IBM Watson Tone Analyzer to analyze emotions, then uses OpenAI's GPT-3 for natural language processing to generate a response that takes the user's emotions into account, and sends this response in JSON format to the user's device for display.

[0822] Specific examples

[0823] For example, if a user enters "My payment has failed due to an error. What should I do?" while using an electronic payment service, the following process will be performed.

[0824] 1. The user enters a question into their smartphone, which is then sent to the server.

[0825] 2. The server receives the question, analyzes it using IBM Watson Tone Analyzer, and extracts the emotion of "troubled."

[0826] 3. The server uses OpenAI's GPT-3 to generate a sentiment-based response, which might say something like, "It looks like you've encountered a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try changing your payment method or contact our support center. We apologize for any inconvenience."

[0827] 4. The server sends the generated response in JSON format to the user's smartphone, where the user confirms the response.

[0828] Prompt Sentence Examples

[0829] Below are some example prompts to input to the generative AI model:

[0830] Please respond appropriately to the following question, taking into consideration the user's feelings.\nUser's question: {{ user_message}}"

[0831] As described above, by combining these means and technologies, we will realize a system that quickly and appropriately resolves technical problems faced by users.

[0832] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0833] Step 1:

[0834] Users use their smartphones or smart glasses to input technical questions about electronic payments. The user's question is sent in text format to the device, which is then sent to the server as an HTTP POST request.

[0835] Input: User's text message

[0836] Output: HTTP POST request

[0837] Step 2:

[0838] The server receives the incoming HTTP POST request and analyzes its contents.

[0839] Input: HTTP POST request (containing the user's text message)

[0840] Output: User's text message

[0841] Step 3:

[0842] The server passes the user's message to IBM Watson Tone Analyzer for sentiment analysis. The sentiment analysis engine detects the tone of the message and extracts the user's emotional information.

[0843] Input: User's text message

[0844] Output: User's emotional state (e.g., troubled, angry, etc.)

[0845] Step 4:

[0846] The server passes the results of the sentiment analysis engine and the user's message to OpenAI GPT-3 to generate an appropriate response. The prompt sentence is used to provide instructions to the generative AI model to generate an emotion-sensitive response.

[0847] Input: User text message, user emotion information

[0848] Output: The response generated by natural language processing

[0849] Step 5:

[0850] The server formats the generated response, removing unnecessary spaces and line breaks, and constructs the response in JSON format.

[0851] Input: A response generated by natural language processing

[0852] Output: Formatted response (JSON format)

[0853] Step 6:

[0854] The server sends the formatted response to the user's terminal, which receives the response, converts it into a format that is displayed to the user, and displays it.

[0855] Input: Formatted response (JSON format)

[0856] Output: A text response in a format that can be viewed by the user

[0857] Specific examples

[0858] For example, the specific processing flow when a user inputs "My payment has not gone through due to an error. What should I do?" is shown below.

[0859] Step 1:

[0860] Enter: "My payment is not going through. What should I do?"

[0861] Output: HTTP POST request

[0862] Step 2:

[0863] Input: HTTP POST request

[0864] Output: "My payment failed due to an error. What should I do?"

[0865] Step 3:

[0866] Enter: "My payment is not going through. What should I do?"

[0867] Output: "I'm in trouble"

[0868] Step 4:

[0869] Input: "My payment is not going through. What should I do?" "I'm in trouble."

[0870] Output: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[0871] Step 5:

[0872] Input: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[0873] Output: JSON response

[0874] Step 6:

[0875] Input: JSON formatted response

[0876] Output: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[0877] 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.

[0878] 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.

[0879] 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.

[0880] [Third embodiment]

[0881] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0882] 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.

[0883] 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).

[0884] 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.

[0885] 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.

[0886] 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).

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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."

[0893] ---

[0894] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes, including receiving input from the user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. An embodiment of the present invention will be described in detail below.

[0895] System Overview

[0896] This system consists of four main functional blocks.

[0897] 1. A means of receiving user input

[0898] 2. A means of processing received user input

[0899] 3. A means of generating appropriate responses through natural language processing

[0900] 4. A means of sending the generated response back to the user

[0901] Specific Description of the Embodiments

[0902] 1. A means of receiving user input

[0903] A user enters technical problems or questions into a terminal and sends them to a server. The user input is primarily in the form of text, and this input is sent to the server over the Internet.

[0904] 2. A means of processing received user input

[0905] The server receives and analyzes user input. It uses natural language processing (NLP) technology to interpret the user input and determine the appropriate response. Specifically, it uses a cloud-based natural language generation API to analyze the intent of the input and the required response.

[0906] 3. A means of generating appropriate responses through natural language processing

[0907] Based on the analysis results, the server calls a cloud-based natural language generation API to generate an appropriate response that is optimized for the user's question and contains the information necessary to solve the problem.

[0908] 4. A means of sending the generated response back to the user

[0909] The server then returns the generated response to the user. Specifically, it formats the response in JSON format and sends it to the user's device. The user receives it and checks the information needed to solve the problem.

[0910] Specific examples

[0911] For example, if a user types, "My laptop battery is dying quickly. What should I do?" the following steps are performed:

[0912] 1. The question entered by the user on the terminal is sent to the server.

[0913] 2. The server receives the user's question and analyzes its content.

[0914] 3. The server uses a natural language generation API to generate appropriate solutions to the battery issue, such as "close unnecessary background applications, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0915] 4. The server sends the generated response back to the user's device, where the user can review it and take specific action to resolve the battery issue.

[0916] In this way, the present invention provides a concrete means for quickly and efficiently resolving technical problems faced by users.

[0917] The processing flow will be explained below.

[0918] ---

[0919] Step 1:

[0920] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[0921] Step 2:

[0922] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[0923] Step 3:

[0924] The server receives the HTTP POST request and extracts the user's message from it.

[0925] Step 4:

[0926] The server passes the extracted user message to a natural language processing module, which performs initial processing to understand the user's intent and analyze the problem.

[0927] Step 5:

[0928] The server sends a request to a cloud-based natural language generation API through a natural language processing module, which includes the user's message and relevant contextual information.

[0929] Step 6:

[0930] A cloud-based natural language generation API processes the incoming request and generates an appropriate response to the user's question.

[0931] Step 7:

[0932] The server receives the generated response from the cloud-based natural language generation API, and then formats the response to remove unnecessary spaces and line breaks.

[0933] Step 8:

[0934] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[0935] Step 9:

[0936] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[0937] Step 10:

[0938] The user checks the response displayed on the terminal and takes specific steps to resolve the problem.

[0939] ---

[0940] These are the specific processing steps in this system, allowing users to receive real-time problem-solving support.

[0941] Example 1

[0942] 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."

[0943] In today's information society, users face a wide variety of technical problems. Systems that can quickly and appropriately resolve these problems are important for improving user convenience. However, conventional systems lack the time and accuracy required to generate responses, making it difficult for many users to resolve their problems efficiently.

[0944] 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.

[0945] In this invention, the server includes means for receiving a user input, means for performing text analysis on the received user input, means for generating an appropriate response based on the analysis result using a natural language processing model, and means for sending the generated response to the user, thereby enabling a fast and highly accurate response to the user input to be provided.

[0946] "User input" is a textual query or information provided by a user to the system.

[0947] The "receiving means" is a function for acquiring input data sent from a user via the Internet.

[0948] "Text analysis" is the process of analyzing received user input to understand its intent and content.

[0949] A "natural language processing model" is an algorithm or technology that understands and analyzes text data and generates appropriate responses in human language.

[0950] "Analysis results" are information obtained as a result of text analysis of received user input.

[0951] The "means for generating a response" is a function that generates an appropriate response to a user's question based on the analysis results.

[0952] The "means for transmitting" is a function for transmitting the generated response to the user's terminal.

[0953] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes, receiving input from the user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. An embodiment of the present invention will be described in detail below.

[0954] Hardware and software used

[0955] The following hardware and software are used to implement this system.

[0956] Device: A device used by a user, such as a computer, smartphone, or tablet.

[0957] Server: Cloud-based server for high-performance data processing.

[0958] Natural language processing models: Open source natural language processing libraries and APIs (e.g., OpenAI's GPT-4).

[0959] Data processing and calculation

[0960] User enters text:

[0961] Users enter their problems or questions in text format into an input form on their device, and this input is sent to a server via the Internet.

[0962] The server receives and parses the input:

[0963] The server receives text data sent by users via the Internet, which is then parsed for text analysis, where a natural language processing model (such as OpenAI's GPT-4) is used to analyze the content and intent of the text.

[0964] Response generation based on analysis results:

[0965] The server then calls a cloud-based natural language generation API based on the analysis results to generate an appropriate response to the user's question. The response is optimized to include the information necessary to solve the problem.

[0966] Send a response to the user:

[0967] The generated response is formatted in JSON and sent to the user's device, where the user can view it on screen and take action to resolve the issue.

[0968] Specific examples

[0969] For example, if a user types, "My laptop battery is dying quickly. What should I do?" the following steps are performed:

[0970] 1. The user enters a question into the terminal and sends it.

[0971] 2. The server receives the user's question and analyzes it using a natural language processing model (e.g., OpenAI's GPT-4).

[0972] 3. Based on the analysis results, the server generates an appropriate solution to the battery problem using a natural language generation API. The response includes specific suggestions such as "close unnecessary applications running in the background, lower the display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[0973] 4. The server generates a response and sends it back to the user's device, where the user can view it and take action to resolve the battery issue.

[0974] Prompt Sentence Examples

[0975] Prompt statement:

[0976] User Input: 'My laptop battery keeps dying. What should I do?'

[0977] Response: 'Here are some suggestions to resolve the issue of your battery dying quickly. First, close any unnecessary applications running in the background. Also, reduce the display brightness and turn off Wi-Fi and Bluetooth. Additionally, use a battery diagnostic tool to check the health of your battery and consider a new one.'

[0978] Thus, the present invention provides a specific means for quickly and appropriately resolving technical problems faced by users.

[0979] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0980] Step 1:

[0981] The user provides input

[0982] Input: The user enters a question or problem in text format into an input form on the device.

[0983] What happens: The user types "My laptop battery is dying quickly. What should I do?" and clicks the send button.

[0984] Output: The entered text is sent over the Internet to a server.

[0985] Step 2:

[0986] The server receives the input

[0987] Input: Text data sent by the user over the Internet.

[0988] What happens: The server receives input data from the user, stores it in the database, and forwards it to the next stage of analysis.

[0989] Output: saved text data and raw data ready for analysis.

[0990] Step 3:

[0991] The server parses the input data

[0992] Input: Saved text data.

[0993] How it works: The server uses a natural language processing model (e.g., GPT-4) to analyze the intent and content of the text. For example, it recognizes the input information "My battery is running out soon" as "battery problem."

[0994] Data processing: The input text is tokenized and passed to the analysis engine for semantic analysis.

[0995] Output: The analysis results in the specific information of the user's problem (in this case "battery life problem").

[0996] Step 4:

[0997] The server generates an appropriate response

[0998] Input: Specific information about the analysis results.

[0999] Specific operation: The server uses a natural language generation API (e.g., GPT-4) to generate an appropriate response to the user's question based on the analysis results.

[1000] Data processing: Generate responses based on the analysis results, including specific suggestions to address the identified issues.

[1001] Output: The generated response text (e.g. advice such as "Close unnecessary applications running in the background and reduce the brightness of your display").

[1002] Step 5:

[1003] The server sends a response

[1004] Input: The generated response text.

[1005] Specific operation: The server formats the response text in JSON format and sends it to the user's device.

[1006] Output: The response data sent to the user's device.

[1007] Step 6:

[1008] The user receives and acknowledges the response

[1009] Input: The response data sent by the server.

[1010] Specific behavior: The user's device parses the received response data and displays it on the screen. The user can then confirm the displayed information and take action to resolve the problem.

[1011] Output: Information that allows the user to take specific action to resolve the issue.

[1012] Through these steps, the system of the present invention receives input from users about technical problems, analyzes them, and generates and returns appropriate responses to the users, thereby assisting in quick and effective problem resolution.

[1013] (Application example 1)

[1014] 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."

[1015] In modern electronic payment services, there is a growing need for systems that can quickly and appropriately resolve the wide range of technical issues users face. However, there is a lack of systems that provide solutions to these issues, forcing users to expend a great deal of time and effort. In particular, there are limited means to obtain immediate and effective advice on issues such as balance confirmation and transaction failures.

[1016] 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.

[1017] In this invention, the server includes means for receiving user input, means for analyzing the user input, means for generating a response using natural language generation technology, means for sending the generated response to the user, and means for resolving problems related to electronic payments, thereby enabling problems related to electronic payments to be resolved quickly and accurately.

[1018] The "means for receiving user input" refers to a means by which a user can enter textual information about a problem or question relating to an electronic payment and transmit that input to the server.

[1019] The "means for analyzing user input" refers to a means for analyzing received user input and performing processing to identify the problem or generate an appropriate response.

[1020] "Means for generating a response using natural language generation technology" refers to means for generating an appropriate response using natural language processing technology based on analyzed user input.

[1021] The "means for transmitting the generated response to the user" refers to a means for transmitting the generated response to the user's terminal so that the user can check the response.

[1022] "Means for solving problems related to electronic payments" are means for analyzing technical problems related to electronic payments that users face and providing specific solutions.

[1023] MODE FOR CARRYING OUT THE INVENTION

[1024] The present invention relates to a system that allows users to quickly resolve issues related to electronic payments. The system implements a process that receives user input, analyzes it, and uses natural language generation technology to generate and return an appropriate response to the user. Specific embodiments of the present invention are described in detail below.

[1025] System Overview

[1026] The system consists of the following main functional blocks:

[1027] 1. A means of receiving user input

[1028] 2. A way to parse user input

[1029] 3. A means of generating responses using natural language generation technology

[1030] 4. A means of sending the generated response to the user

[1031] 5. Solutions to problems related to electronic payments

[1032] Hardware and software used

[1033] Hardware: User's smartphone and cloud server

[1034] Software: Natural language processing API (e.g., OpenAI GPT-3), Flask (Python framework)

[1035] Overview of program processing

[1036] The server receives user input from the smartphone, analyzes the received user input using cloud-based natural language generation technology, generates an appropriate response based on the analysis result, and sends the generated response to the user's smartphone.

[1037] Specific examples

[1038] For example, if a user types the question "My balance isn't showing on my electronic payment app. What should I do?", the steps are as follows:

[1039] 1. Receiving user input: User input is sent to the server via the smartphone.

[1040] 2. User input analysis: The server uses natural language generation technology to analyze the question "My balance is not displayed."

[1041] 3. Response generation: The server uses the OpenAI model to generate a solution such as "Please clear the app cache or log out and log in again. Also, please check your internet connection."

[1042] 4. Response transmission: The generated response is sent to the user's smartphone, allowing the user to take action to resolve the issue.

[1043] Prompt Sentence Examples

[1044] User input: My balance isn't showing up on my electronic payment app. What should I do?

[1045] Please provide a suitable solution.

[1046] The present invention thus provides a concrete means for efficiently and appropriately resolving the technical problems faced by users in relation to electronic payments.

[1047] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1048] Step 1:

[1049] The user inputs problems related to electronic payment via their smartphone. Specifically, the user inputs problems such as insufficient cash or transaction failure in text format, and this input data is sent from the device to the server. The input is the user's question, and the output is the text data sent to the server.

[1050] Step 2:

[1051] The server receives user input. The received data is in text format and is prepared for analysis. In this step, the input is text data from the user and the output is data ready for analysis.

[1052] Step 3:

[1053] The server analyzes the received user input. It uses cloud-based natural language generation technology (specifically, OpenAI's GPT-3 model) to understand the intent of the input text and identify problems. At this step, the input is data ready for analysis, and the output is the analyzed results.

[1054] Step 4:

[1055] The server generates an appropriate response based on the analysis results. It then calls OpenAI's natural language generation API again to generate a solution to the user's identified problem in natural language. The input is the analysis result data, and the output is the generated response text.

[1056] Step 5:

[1057] The server formats the generated response into JSON format and sends it to the user's smartphone. This step has the generated response text as input and the formatted JSON data that is sent to the user's smartphone as output.

[1058] Step 6:

[1059] The user checks the response received on their smartphone and takes specific action based on the content. For example, they follow the on-screen instructions to perform specific problem-solving actions, such as clearing the app cache or logging out and logging back in. In this step, the received response data is the input, and the action to resolve the problem is the output.

[1060] 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.

[1061] ---

[1062] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes: receiving input from a user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the quality of the response can be further improved. An embodiment of the present invention will be described in detail below.

[1063] System Overview

[1064] This system consists of five main functional blocks.

[1065] 1. A means of receiving user input

[1066] 2. A means of processing received user input

[1067] 3. A means of generating appropriate responses through natural language processing

[1068] 4. A means of sending the generated response back to the user

[1069] 5. Emotion engine that recognizes user emotions

[1070] Specific Description of the Embodiments

[1071] 1. A means of receiving user input

[1072] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[1073] 2. A means of processing received user input

[1074] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[1075] The server receives the HTTP POST request and extracts the user's message.

[1076] 3. A means of generating appropriate responses through natural language processing

[1077] The server passes the extracted user message to a natural language processing module to understand the user's intent and analyze the problem, using a cloud-based natural language generation API.

[1078] 4. A means of sending the generated response back to the user

[1079] The server formats the generated response through a natural language processing module, removing unnecessary spaces and line breaks.

[1080] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[1081] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[1082] 5. Emotion engine that recognizes user emotions

[1083] When the server analyzes the user's message, it uses an emotion engine to recognize the user's emotion, which extracts emotions from the user's text and adjusts the response based on the emotion.

[1084] The server incorporates the results of the emotion engine into the response generation process to generate an appropriate response that takes into account the user's emotions.

[1085] Specific examples

[1086] For example, if a user types, "My laptop battery keeps dying. What should I do? I'm so worried," the following steps will be performed:

[1087] 1. The question entered by the user on the terminal is sent to the server.

[1088] 2. The server receives the user's question and analyzes its content.

[1089] 3. The emotion engine extracts the emotion of "I'm in trouble" from the user's message.

[1090] 4. The server uses a natural language generation API to generate appropriate, emotion-sensitive solutions to the battery issue, such as "close unnecessary background applications, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[1091] 5. The server sends the generated response back to the user's device, where the user can review it and take specific action to resolve the battery issue.

[1092] In this way, the present invention provides a specific means for quickly and appropriately resolving technical problems faced by users, while also realizing responses that take into consideration the feelings of users.

[1093] The processing flow will be explained below.

[1094] ---

[1095] Step 1:

[1096] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[1097] Step 2:

[1098] The device constructs the user's message as an HTTP POST request and sends it to the server over the Internet.

[1099] Step 3:

[1100] The server receives the HTTP POST request and extracts the user's message from the request body.

[1101] Step 4:

[1102] The server passes the extracted user message to the emotion engine, which analyzes the user's emotions. The emotion engine uses natural language processing technology to extract emotions (e.g., troubled, angry, confused, etc.) from the text.

[1103] Step 5:

[1104] The server passes the user's message to the natural language generation API based on the emotion recognition results from the emotion engine, where the emotion recognition results are used as reference information for generating a response.

[1105] Step 6:

[1106] A cloud-based natural language generation API generates an appropriate response based on the user's message and sentiment. The response generated is tailored to the user's sentiment.

[1107] Step 7:

[1108] The server receives the generated response from the cloud-based natural language generation API, and then formats the response to remove unnecessary spaces and line breaks.

[1109] Step 8:

[1110] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[1111] Step 9:

[1112] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[1113] Step 10:

[1114] The user checks the response displayed on the device and takes specific steps to resolve the issue, such as closing unnecessary applications running in the background, lowering the display brightness, turning off Wi-Fi and Bluetooth, using the battery diagnostic tool, or replacing the battery.

[1115] ---

[1116] The above are the specific processing steps of this system. In this way, users can receive support for solving problems in real time and receive responses that take their emotions into consideration.

[1117] Example 2

[1118] 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."

[1119] In modern society, users are faced with an increasing number of technical problems, and there is a demand for them to be resolved quickly and accurately. However, conventional systems often provide responses without fully understanding the user's intentions or emotions, which can degrade the quality of the user experience. In particular, when a user is in a difficult situation or in a hurry, not receiving an appropriate response can cause stress. Therefore, a system that can accurately analyze user input, recognize emotions, and provide the most appropriate response is needed.

[1120] 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.

[1121] In this invention, the server includes a means for analyzing user input, a means for performing natural language processing, and a means for recognizing user emotions, which enables the server to accurately understand the user's input and provide an optimal response based on the emotional information.

[1122] "User input" refers to text or questions entered by a user through a terminal.

[1123] "Means for receiving" refers to the function of receiving text entered by a user from a terminal and transmitting that data to a server.

[1124] "Means for analyzing" refers to the analytical function that processes the user's input text received by the server and understands its content and intent.

[1125] "Natural language processing" refers to techniques that allow a server to understand a user's input text and generate a meaningful response in human language.

[1126] "Natural Language Generation API" refers to a cloud-based application programming interface with natural language processing capabilities that generates text.

[1127] An "emotion engine" refers to a software module that extracts emotional information from a user's input text and provides an appropriate response based on the results.

[1128] "Means for generating a response" refers to the server's ability to use natural language processing and an emotion engine to create an appropriate response to a user's question or problem.

[1129] "Means for returning" refers to a function that sends the response generated by the server to the user's terminal so that the user can check the response.

[1130] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes: receiving input from a user, analyzing it, generating an appropriate response using natural language processing technology, and returning it to the user. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to further improve the quality of the response. An embodiment of the present invention will be described in detail below.

[1131] System Overview

[1132] The system consists of seven main functional blocks:

[1133] 1. A means of receiving user input

[1134] 2. A means of sending received user input to the server

[1135] 3. A way to parse user input on the server

[1136] 4. How to process natural language on the server

[1137] 5. How to recognize user emotions on the server

[1138] 6. Means of generating a response on the server

[1139] 7. A means of sending the generated response back to the user

[1140] Specific Description of the Embodiments

[1141] 1. A means of receiving user input

[1142] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[1143] 2. A means of sending received user input to the server

[1144] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[1145] The server receives the HTTP POST request and extracts the user's message.

[1146] 3. A way to parse user input on the server

[1147] The server passes the extracted user message to a natural language processing module to understand the user's intent and analyze the problem, using a cloud-based natural language generation API.

[1148] 4. How to process natural language on the server

[1149] The server obtains a response generated based on the results of the previous analysis using a cloud-based natural language generation API (e.g., a generative AI model).

[1150] 5. How to recognize user emotions on the server

[1151] When the server analyzes the user's message, it uses an emotion engine to recognize the user's emotion, extracting emotions from the user's text and adjusting the response accordingly.

[1152] 6. Means of generating a response on the server

[1153] The server uses the results of the emotion engine and the natural language generation API to generate an optimal response, which takes into account the user's emotions.

[1154] The server will format the generated response, removing unnecessary spaces and line breaks, and the final response will be constructed in JSON format.

[1155] 7. A means of sending the generated response back to the user

[1156] The server sends the formatted response to the terminal over the Internet.

[1157] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[1158] Specific examples

[1159] For example, if a user types, "My laptop battery keeps dying. What should I do? I'm so worried.", the steps are as follows:

[1160] 1. The user enters the above text into the terminal and presses the send button.

[1161] 2. The device sends this input text to the server as an HTTP POST request.

[1162] 3. The server receives the request and extracts the text content.

[1163] 4. The server uses a natural language processing module to analyze the battery problem and the question.

[1164] 5. The server uses the emotion engine to extract the emotion "troubled."

[1165] 6. The server generates a response suggesting specific battery solutions, such as: "Close unnecessary applications running in the background, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[1166] 7. The server sends the generated response in JSON format to the device.

[1167] 8. The device parses the JSON response and displays solutions to the user, such as closing unnecessary applications running in the background, lowering the display brightness, turning off Wi-Fi and Bluetooth, using a battery diagnostic tool, or replacing the battery.

[1168] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1169] System program processing flow

[1170] Step 1:

[1171] The user enters text

[1172] The user types a technical problem or question into the terminal and clicks the send button.

[1173] Input: A user's textual question or problem (e.g., "My laptop battery keeps dying. What should I do? I'm so frustrated.").

[1174] Output: Text data entered into the terminal.

[1175] Step 2:

[1176] The device sends user input to the server

[1177] The terminal constructs the entered user message as an HTTP POST request.

[1178] The terminal transmits the data to a server via the Internet.

[1179] Input: Text data entered into the terminal.

[1180] Output: User message in the form of an HTTP POST request.

[1181] Step 3:

[1182] The server receives and parses the user input

[1183] The server receives the HTTP POST request and extracts the user's message from the request body.

[1184] Input: HTTP POST request.

[1185] Output: The extracted user's message text.

[1186] Step 4:

[1187] The server processes natural language

[1188] The server passes the extracted user messages to a natural language processing module, which analyzes the intent and subject of the text.

[1189] Input: The extracted user's message text.

[1190] Output: Intent and thematic information resulting from the analysis.

[1191] Step 5:

[1192] The server recognizes the user's emotions

[1193] The server uses an emotion engine to extract emotional information from the user's message, for example, determining whether the user is feeling "troubled."

[1194] Input: The user's message text.

[1195] Output: Extracted emotion information.

[1196] Step 6:

[1197] The server generates a response

[1198] The server uses the natural language generation API to generate the optimal response based on the results of the natural language processing module and the emotion engine.

[1199] As specific actions, the server invokes the generative AI model to generate solutions to the battery problem, such as "close unnecessary applications running in the background, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[1200] Input: Intention, subject matter information, and emotional information.

[1201] Output: The generated response text.

[1202] Step 7:

[1203] The server formats the generated response

[1204] The server formats the generated response, removing unnecessary spaces and line breaks, and constructs the final response in JSON format.

[1205] Input: The generated response text.

[1206] Output: Pretty-printed JSON response.

[1207] Step 8:

[1208] The server sends the response back to the user

[1209] The server sends a JSON-formatted response to the device over the Internet.

[1210] Input: The response in JSON format.

[1211] Output: Data sent to the terminal.

[1212] Step 9:

[1213] The terminal parses and displays the response

[1214] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[1215] Input: The JSON response received from the server.

[1216] Output: The response text that can be displayed to the user.

[1217] Step 10:

[1218] User reviews response and takes action

[1219] The user reviews the response displayed on the device and takes specific action based on the solution provided.

[1220] Input: The response text displayed on the user's terminal.

[1221] Output: User behavior and corresponding actions.

[1222] (Application example 2)

[1223] 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."

[1224] Conventional electronic payment services have difficulty providing prompt and appropriate support for technical problems faced by users. Furthermore, support does not take into consideration the user's feelings, which can lead to a poor user experience. Therefore, a new system is needed that can quickly grasp the user's situation and provide an appropriate solution.

[1225] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1226] In this invention, the server includes means for receiving user input, means for analyzing the user's emotions, means for generating an appropriate response through natural language processing, and means for returning the generated response to the user, thereby enabling technical problems to be resolved quickly and appropriately while taking the user's emotions into consideration.

[1227] "Means for receiving user input" refers to the function by which a terminal or system receives information such as text or voice input by a user and recognizes it as data to be processed.

[1228] The "means for processing received user input" is a function for analyzing received user input information and performing processing to derive an appropriate response based on the content of the information.

[1229] "Means for generating an appropriate response through natural language processing" is a function that uses natural language processing technology to interpret the user's input and generate an appropriate and meaningful response.

[1230] The "means for returning the generated response to the user" is a function for sending the response generated by natural language processing to the user's terminal so that the user can receive and confirm it.

[1231] The "means for analyzing user emotions" is a function that extracts emotions from the user's input and adjusts the content and tone of the response based on those emotions.

[1232] MODE FOR CARRYING OUT THE INVENTION

[1233] System Overview

[1234] This invention is a system that allows users to quickly and appropriately resolve technical problems in electronic payment services. The system aims to generate appropriate responses to problems input by users and to respond in a way that takes into account their emotions.

[1235] Technologies and tools used

[1236] Hardware: Smartphones, smart glasses

[1237] Software: Python-based server, natural language processing API (e.g., OpenAI's GPT-3), sentiment analysis engine (e.g., IBM Watson Tone Analyzer)

[1238] Program Description

[1239] The server implements the system using the following means:

[1240] Ways to receive user input:

[1241] It receives text and voice data entered by the user through a smartphone or smart glasses, and sends this data to the server as an HTTP POST request.

[1242] Ways to analyze user sentiment:

[1243] IBM Watson Tone Analyzer is used to extract sentiment from incoming user input, and this sentiment information is used to tailor responses during subsequent natural language processing.

[1244] A means of generating appropriate responses through natural language processing:

[1245] It uses natural language generation APIs like OpenAI's GPT-3 to generate appropriate responses based on the user's text input, taking into account the emotional information extracted earlier.

[1246] A means of sending the generated response back to the user:

[1247] The server generates a response and sends it in JSON format to the user's device, which parses it and displays it to the user.

[1248] Processing flow

[1249] The server receives user input, passes it to IBM Watson Tone Analyzer to analyze emotions, then uses OpenAI's GPT-3 for natural language processing to generate a response that takes the user's emotions into account, and sends this response in JSON format to the user's device for display.

[1250] Specific examples

[1251] For example, if a user enters "My payment has failed due to an error. What should I do?" while using an electronic payment service, the following process will be performed.

[1252] 1. The user enters a question into their smartphone, which is then sent to the server.

[1253] 2. The server receives the question, analyzes it using IBM Watson Tone Analyzer, and extracts the emotion of "troubled."

[1254] 3. The server uses OpenAI's GPT-3 to generate a sentiment-based response, which might say something like, "It looks like you've encountered a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try changing your payment method or contact our support center. We apologize for any inconvenience."

[1255] 4. The server sends the generated response in JSON format to the user's smartphone, where the user confirms the response.

[1256] Prompt Sentence Examples

[1257] Below are some example prompts to input to the generative AI model:

[1258] Please respond appropriately to the following question, taking into consideration the user's feelings.\nUser's question: {{ user_message}}"

[1259] As described above, by combining these means and technologies, we will realize a system that quickly and appropriately resolves technical problems faced by users.

[1260] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1261] Step 1:

[1262] Users use their smartphones or smart glasses to input technical questions about electronic payments. The user's question is sent in text format to the device, which is then sent to the server as an HTTP POST request.

[1263] Input: User's text message

[1264] Output: HTTP POST request

[1265] Step 2:

[1266] The server receives the incoming HTTP POST request and analyzes its contents.

[1267] Input: HTTP POST request (containing the user's text message)

[1268] Output: User's text message

[1269] Step 3:

[1270] The server passes the user's message to IBM Watson Tone Analyzer for sentiment analysis. The sentiment analysis engine detects the tone of the message and extracts the user's emotional information.

[1271] Input: User's text message

[1272] Output: User's emotional state (e.g., troubled, angry, etc.)

[1273] Step 4:

[1274] The server passes the results of the sentiment analysis engine and the user's message to OpenAI GPT-3 to generate an appropriate response. The prompt sentence is used to provide instructions to the generative AI model to generate an emotion-sensitive response.

[1275] Input: User text message, user emotion information

[1276] Output: The response generated by natural language processing

[1277] Step 5:

[1278] The server formats the generated response, removing unnecessary spaces and line breaks, and constructs the response in JSON format.

[1279] Input: A response generated by natural language processing

[1280] Output: Formatted response (JSON format)

[1281] Step 6:

[1282] The server sends the formatted response to the user's terminal, which receives the response, converts it into a format that is displayed to the user, and displays it.

[1283] Input: Formatted response (JSON format)

[1284] Output: A text response in a format that can be viewed by the user

[1285] Specific examples

[1286] For example, the specific processing flow when a user inputs "My payment has not gone through due to an error. What should I do?" is shown below.

[1287] Step 1:

[1288] Enter: "My payment is not going through. What should I do?"

[1289] Output: HTTP POST request

[1290] Step 2:

[1291] Input: HTTP POST request

[1292] Output: "My payment failed due to an error. What should I do?"

[1293] Step 3:

[1294] Enter: "My payment is not going through. What should I do?"

[1295] Output: "I'm in trouble"

[1296] Step 4:

[1297] Input: "My payment is not going through. What should I do?" "I'm in trouble."

[1298] Output: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[1299] Step 5:

[1300] Input: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[1301] Output: JSON response

[1302] Step 6:

[1303] Input: JSON formatted response

[1304] Output: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[1305] 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.

[1306] 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.

[1307] 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.

[1308] [Fourth embodiment]

[1309] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1310] 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.

[1311] 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).

[1312] 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.

[1313] 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.

[1314] 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).

[1315] 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.

[1316] 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.

[1317] 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.

[1318] 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.

[1319] 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.

[1320] 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.

[1321] 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."

[1322] ---

[1323] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes, including receiving input from the user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. An embodiment of the present invention will be described in detail below.

[1324] System Overview

[1325] This system consists of four main functional blocks.

[1326] 1. A means of receiving user input

[1327] 2. A means of processing received user input

[1328] 3. A means of generating appropriate responses through natural language processing

[1329] 4. A means of sending the generated response back to the user

[1330] Specific Description of the Embodiments

[1331] 1. A means of receiving user input

[1332] A user enters technical problems or questions into a terminal and sends them to a server. The user input is primarily in the form of text, and this input is sent to the server over the Internet.

[1333] 2. A means of processing received user input

[1334] The server receives and analyzes user input. It uses natural language processing (NLP) technology to interpret the user input and determine the appropriate response. Specifically, it uses a cloud-based natural language generation API to analyze the intent of the input and the required response.

[1335] 3. A means of generating appropriate responses through natural language processing

[1336] Based on the analysis results, the server calls a cloud-based natural language generation API to generate an appropriate response that is optimized for the user's question and contains the information necessary to solve the problem.

[1337] 4. A means of sending the generated response back to the user

[1338] The server then returns the generated response to the user. Specifically, it formats the response in JSON format and sends it to the user's device. The user receives it and checks the information needed to solve the problem.

[1339] Specific examples

[1340] For example, if a user types, "My laptop battery is dying quickly. What should I do?" the following steps are performed:

[1341] 1. The question entered by the user on the terminal is sent to the server.

[1342] 2. The server receives the user's question and analyzes its content.

[1343] 3. The server uses a natural language generation API to generate appropriate solutions to the battery issue, such as "close unnecessary background applications, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[1344] 4. The server sends the generated response back to the user's device, where the user can review it and take specific action to resolve the battery issue.

[1345] In this way, the present invention provides a concrete means for quickly and efficiently resolving technical problems faced by users.

[1346] The processing flow will be explained below.

[1347] ---

[1348] Step 1:

[1349] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[1350] Step 2:

[1351] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[1352] Step 3:

[1353] The server receives the HTTP POST request and extracts the user's message from it.

[1354] Step 4:

[1355] The server passes the extracted user message to a natural language processing module, which performs initial processing to understand the user's intent and analyze the problem.

[1356] Step 5:

[1357] The server sends a request to a cloud-based natural language generation API through a natural language processing module, which includes the user's message and relevant contextual information.

[1358] Step 6:

[1359] A cloud-based natural language generation API processes the incoming request and generates an appropriate response to the user's question.

[1360] Step 7:

[1361] The server receives the generated response from the cloud-based natural language generation API, and then formats the response to remove unnecessary spaces and line breaks.

[1362] Step 8:

[1363] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[1364] Step 9:

[1365] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[1366] Step 10:

[1367] The user checks the response displayed on the terminal and takes specific steps to resolve the problem.

[1368] ---

[1369] These are the specific processing steps in this system, allowing users to receive real-time problem-solving support.

[1370] Example 1

[1371] 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."

[1372] In today's information society, users face a wide variety of technical problems. Systems that can quickly and appropriately resolve these problems are important for improving user convenience. However, conventional systems lack the time and accuracy required to generate responses, making it difficult for many users to resolve their problems efficiently.

[1373] 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.

[1374] In this invention, the server includes means for receiving a user input, means for performing text analysis on the received user input, means for generating an appropriate response based on the analysis result using a natural language processing model, and means for sending the generated response to the user, thereby enabling a fast and highly accurate response to the user input to be provided.

[1375] "User input" is a textual query or information provided by a user to the system.

[1376] The "receiving means" is a function for acquiring input data sent from a user via the Internet.

[1377] "Text analysis" is the process of analyzing received user input to understand its intent and content.

[1378] A "natural language processing model" is an algorithm or technology that understands and analyzes text data and generates appropriate responses in human language.

[1379] "Analysis results" are information obtained as a result of text analysis of received user input.

[1380] The "means for generating a response" is a function that generates an appropriate response to a user's question based on the analysis results.

[1381] The "means for transmitting" is a function for transmitting the generated response to the user's terminal.

[1382] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes, receiving input from the user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. An embodiment of the present invention will be described in detail below.

[1383] Hardware and software used

[1384] The following hardware and software are used to implement this system.

[1385] Device: A device used by a user, such as a computer, smartphone, or tablet.

[1386] Server: Cloud-based server for high-performance data processing.

[1387] Natural language processing models: Open source natural language processing libraries and APIs (e.g., OpenAI's GPT-4).

[1388] Data processing and calculation

[1389] User enters text:

[1390] Users enter their problems or questions in text format into an input form on their device, and this input is sent to a server via the Internet.

[1391] The server receives and parses the input:

[1392] The server receives text data sent by users via the Internet, which is then parsed for text analysis, where a natural language processing model (such as OpenAI's GPT-4) is used to analyze the content and intent of the text.

[1393] Response generation based on analysis results:

[1394] The server then calls a cloud-based natural language generation API based on the analysis results to generate an appropriate response to the user's question. The response is optimized to include the information necessary to solve the problem.

[1395] Send a response to the user:

[1396] The generated response is formatted in JSON and sent to the user's device, where the user can view it on screen and take action to resolve the issue.

[1397] Specific examples

[1398] For example, if a user types, "My laptop battery is dying quickly. What should I do?" the following steps are performed:

[1399] 1. The user enters a question into the terminal and sends it.

[1400] 2. The server receives the user's question and analyzes it using a natural language processing model (e.g., OpenAI's GPT-4).

[1401] 3. Based on the analysis results, the server generates an appropriate solution to the battery problem using a natural language generation API. The response includes specific suggestions such as "close unnecessary applications running in the background, lower the display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[1402] 4. The server generates a response and sends it back to the user's device, where the user can view it and take action to resolve the battery issue.

[1403] Prompt Sentence Examples

[1404] Prompt statement:

[1405] User Input: 'My laptop battery keeps dying. What should I do?'

[1406] Response: 'Here are some suggestions to resolve the issue of your battery dying quickly. First, close any unnecessary applications running in the background. Also, reduce the display brightness and turn off Wi-Fi and Bluetooth. Additionally, use a battery diagnostic tool to check the health of your battery and consider a new one.'

[1407] Thus, the present invention provides a specific means for quickly and appropriately resolving technical problems faced by users.

[1408] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1409] Step 1:

[1410] The user provides input

[1411] Input: The user enters a question or problem in text format into an input form on the device.

[1412] What happens: The user types "My laptop battery is dying quickly. What should I do?" and clicks the send button.

[1413] Output: The entered text is sent over the Internet to a server.

[1414] Step 2:

[1415] The server receives the input

[1416] Input: Text data sent by the user over the Internet.

[1417] What happens: The server receives input data from the user, stores it in the database, and forwards it to the next stage of analysis.

[1418] Output: saved text data and raw data ready for analysis.

[1419] Step 3:

[1420] The server parses the input data

[1421] Input: Saved text data.

[1422] How it works: The server uses a natural language processing model (e.g., GPT-4) to analyze the intent and content of the text. For example, it recognizes the input information "My battery is running out soon" as "battery problem."

[1423] Data processing: The input text is tokenized and passed to the analysis engine for semantic analysis.

[1424] Output: The analysis results in the specific information of the user's problem (in this case "battery life problem").

[1425] Step 4:

[1426] The server generates an appropriate response

[1427] Input: Specific information about the analysis results.

[1428] Specific operation: The server uses a natural language generation API (e.g., GPT-4) to generate an appropriate response to the user's question based on the analysis results.

[1429] Data processing: Generate responses based on the analysis results, including specific suggestions to address the identified issues.

[1430] Output: The generated response text (e.g. advice such as "Close unnecessary applications running in the background and reduce the brightness of your display").

[1431] Step 5:

[1432] The server sends a response

[1433] Input: The generated response text.

[1434] Specific operation: The server formats the response text in JSON format and sends it to the user's device.

[1435] Output: The response data sent to the user's device.

[1436] Step 6:

[1437] The user receives and acknowledges the response

[1438] Input: The response data sent by the server.

[1439] Specific behavior: The user's device parses the received response data and displays it on the screen. The user can then confirm the displayed information and take action to resolve the problem.

[1440] Output: Information that allows the user to take specific action to resolve the issue.

[1441] Through these steps, the system of the present invention receives input from users about technical problems, analyzes them, and generates and returns appropriate responses to the users, thereby assisting in quick and effective problem resolution.

[1442] (Application example 1)

[1443] 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."

[1444] In modern electronic payment services, there is a growing need for systems that can quickly and appropriately resolve the wide range of technical issues users face. However, there is a lack of systems that provide solutions to these issues, forcing users to expend a great deal of time and effort. In particular, there are limited means to obtain immediate and effective advice on issues such as balance confirmation and transaction failures.

[1445] 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.

[1446] In this invention, the server includes means for receiving user input, means for analyzing the user input, means for generating a response using natural language generation technology, means for sending the generated response to the user, and means for resolving problems related to electronic payments, thereby enabling problems related to electronic payments to be resolved quickly and accurately.

[1447] The "means for receiving user input" refers to a means by which a user can enter textual information about a problem or question relating to an electronic payment and transmit that input to the server.

[1448] The "means for analyzing user input" refers to a means for analyzing received user input and performing processing to identify the problem or generate an appropriate response.

[1449] "Means for generating a response using natural language generation technology" refers to means for generating an appropriate response using natural language processing technology based on analyzed user input.

[1450] The "means for transmitting the generated response to the user" refers to a means for transmitting the generated response to the user's terminal so that the user can check the response.

[1451] "Means for solving problems related to electronic payments" are means for analyzing technical problems related to electronic payments that users face and providing specific solutions.

[1452] MODE FOR CARRYING OUT THE INVENTION

[1453] The present invention relates to a system that allows users to quickly resolve issues related to electronic payments. The system implements a process that receives user input, analyzes it, and uses natural language generation technology to generate and return an appropriate response to the user. Specific embodiments of the present invention are described in detail below.

[1454] System Overview

[1455] The system consists of the following main functional blocks:

[1456] 1. A means of receiving user input

[1457] 2. A way to parse user input

[1458] 3. A means of generating responses using natural language generation technology

[1459] 4. A means of sending the generated response to the user

[1460] 5. Solutions to problems related to electronic payments

[1461] Hardware and software used

[1462] Hardware: User's smartphone and cloud server

[1463] Software: Natural language processing API (e.g., OpenAI GPT-3), Flask (Python framework)

[1464] Overview of program processing

[1465] The server receives user input from the smartphone, analyzes the received user input using cloud-based natural language generation technology, generates an appropriate response based on the analysis result, and sends the generated response to the user's smartphone.

[1466] Specific examples

[1467] For example, if a user types the question "My balance isn't showing on my electronic payment app. What should I do?", the steps are as follows:

[1468] 1. Receiving user input: User input is sent to the server via the smartphone.

[1469] 2. User input analysis: The server uses natural language generation technology to analyze the question "My balance is not displayed."

[1470] 3. Response generation: The server uses the OpenAI model to generate a solution such as "Please clear the app cache or log out and log in again. Also, please check your internet connection."

[1471] 4. Response transmission: The generated response is sent to the user's smartphone, allowing the user to take action to resolve the issue.

[1472] Prompt Sentence Examples

[1473] User input: My balance isn't showing up on my electronic payment app. What should I do?

[1474] Please provide a suitable solution.

[1475] The present invention thus provides a concrete means for efficiently and appropriately resolving the technical problems faced by users in relation to electronic payments.

[1476] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1477] Step 1:

[1478] The user inputs problems related to electronic payment via their smartphone. Specifically, the user inputs problems such as insufficient cash or transaction failure in text format, and this input data is sent from the device to the server. The input is the user's question, and the output is the text data sent to the server.

[1479] Step 2:

[1480] The server receives user input. The received data is in text format and is prepared for analysis. In this step, the input is text data from the user and the output is data ready for analysis.

[1481] Step 3:

[1482] The server analyzes the received user input. It uses cloud-based natural language generation technology (specifically, OpenAI's GPT-3 model) to understand the intent of the input text and identify problems. At this step, the input is data ready for analysis, and the output is the analyzed results.

[1483] Step 4:

[1484] The server generates an appropriate response based on the analysis results. It then calls OpenAI's natural language generation API again to generate a solution to the user's identified problem in natural language. The input is the analysis result data, and the output is the generated response text.

[1485] Step 5:

[1486] The server formats the generated response into JSON format and sends it to the user's smartphone. This step has the generated response text as input and the formatted JSON data that is sent to the user's smartphone as output.

[1487] Step 6:

[1488] The user checks the response received on their smartphone and takes specific action based on the content. For example, they follow the on-screen instructions to perform specific problem-solving actions, such as clearing the app cache or logging out and logging back in. In this step, the received response data is the input, and the action to resolve the problem is the output.

[1489] 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.

[1490] ---

[1491] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes: receiving input from a user, analyzing the input, generating an appropriate response using natural language processing technology, and returning the response to the user. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, the quality of the response can be further improved. An embodiment of the present invention will be described in detail below.

[1492] System Overview

[1493] This system consists of five main functional blocks.

[1494] 1. A means of receiving user input

[1495] 2. A means of processing received user input

[1496] 3. A means of generating appropriate responses through natural language processing

[1497] 4. A means of sending the generated response back to the user

[1498] 5. Emotion engine that recognizes user emotions

[1499] Specific Description of the Embodiments

[1500] 1. A means of receiving user input

[1501] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[1502] 2. A means of processing received user input

[1503] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[1504] The server receives the HTTP POST request and extracts the user's message.

[1505] 3. A means of generating appropriate responses through natural language processing

[1506] The server passes the extracted user message to a natural language processing module to understand the user's intent and analyze the problem, using a cloud-based natural language generation API.

[1507] 4. A means of sending the generated response back to the user

[1508] The server formats the generated response through a natural language processing module, removing unnecessary spaces and line breaks.

[1509] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[1510] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[1511] 5. Emotion engine that recognizes user emotions

[1512] When the server analyzes the user's message, it uses an emotion engine to recognize the user's emotion, which extracts emotions from the user's text and adjusts the response based on the emotion.

[1513] The server incorporates the results of the emotion engine into the response generation process to generate an appropriate response that takes into account the user's emotions.

[1514] Specific examples

[1515] For example, if a user types, "My laptop battery keeps dying. What should I do? I'm so worried," the following steps will be performed:

[1516] 1. The question entered by the user on the terminal is sent to the server.

[1517] 2. The server receives the user's question and analyzes its content.

[1518] 3. The emotion engine extracts the emotion of "I'm in trouble" from the user's message.

[1519] 4. The server uses a natural language generation API to generate appropriate, emotion-sensitive solutions to the battery issue, such as "close unnecessary background applications, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[1520] 5. The server sends the generated response back to the user's device, where the user can review it and take specific action to resolve the battery issue.

[1521] In this way, the present invention provides a specific means for quickly and appropriately resolving technical problems faced by users, while also realizing responses that take into consideration the feelings of users.

[1522] The processing flow will be explained below.

[1523] ---

[1524] Step 1:

[1525] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[1526] Step 2:

[1527] The device constructs the user's message as an HTTP POST request and sends it to the server over the Internet.

[1528] Step 3:

[1529] The server receives the HTTP POST request and extracts the user's message from the request body.

[1530] Step 4:

[1531] The server passes the extracted user message to the emotion engine, which analyzes the user's emotions. The emotion engine uses natural language processing technology to extract emotions (e.g., troubled, angry, confused, etc.) from the text.

[1532] Step 5:

[1533] The server passes the user's message to the natural language generation API based on the emotion recognition results from the emotion engine, where the emotion recognition results are used as reference information for generating a response.

[1534] Step 6:

[1535] A cloud-based natural language generation API generates an appropriate response based on the user's message and sentiment. The response generated is tailored to the user's sentiment.

[1536] Step 7:

[1537] The server receives the generated response from the cloud-based natural language generation API, and then formats the response to remove unnecessary spaces and line breaks.

[1538] Step 8:

[1539] The server constructs a formatted response in JSON format and sends it over the Internet to the device.

[1540] Step 9:

[1541] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[1542] Step 10:

[1543] The user checks the response displayed on the device and takes specific steps to resolve the issue, such as closing unnecessary applications running in the background, lowering the display brightness, turning off Wi-Fi and Bluetooth, using the battery diagnostic tool, or replacing the battery.

[1544] ---

[1545] The above are the specific processing steps of this system. In this way, users can receive support for solving problems in real time and receive responses that take their emotions into consideration.

[1546] Example 2

[1547] 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."

[1548] In modern society, users are faced with an increasing number of technical problems, and there is a demand for them to be resolved quickly and accurately. However, conventional systems often provide responses without fully understanding the user's intentions or emotions, which can degrade the quality of the user experience. In particular, when a user is in a difficult situation or in a hurry, not receiving an appropriate response can cause stress. Therefore, a system that can accurately analyze user input, recognize emotions, and provide the most appropriate response is needed.

[1549] 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.

[1550] In this invention, the server includes a means for analyzing user input, a means for performing natural language processing, and a means for recognizing user emotions, which enables the server to accurately understand the user's input and provide an optimal response based on the emotional information.

[1551] "User input" refers to text or questions entered by a user through a terminal.

[1552] "Means for receiving" refers to the function of receiving text entered by a user from a terminal and transmitting that data to a server.

[1553] "Means for analyzing" refers to the analytical function that processes the user's input text received by the server and understands its content and intent.

[1554] "Natural language processing" refers to techniques that allow a server to understand a user's input text and generate a meaningful response in human language.

[1555] "Natural Language Generation API" refers to a cloud-based application programming interface with natural language processing capabilities that generates text.

[1556] An "emotion engine" refers to a software module that extracts emotional information from a user's input text and provides an appropriate response based on the results.

[1557] "Means for generating a response" refers to the server's ability to use natural language processing and an emotion engine to create an appropriate response to a user's question or problem.

[1558] "Means for returning" refers to a function that sends the response generated by the server to the user's terminal so that the user can check the response.

[1559] The present invention relates to a system for quickly and appropriately resolving various technical problems faced by users. The system performs a series of processes: receiving input from a user, analyzing it, generating an appropriate response using natural language processing technology, and returning it to the user. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to further improve the quality of the response. An embodiment of the present invention will be described in detail below.

[1560] System Overview

[1561] The system consists of seven main functional blocks:

[1562] 1. A means of receiving user input

[1563] 2. A means of sending received user input to the server

[1564] 3. A way to parse user input on the server

[1565] 4. How to process natural language on the server

[1566] 5. How to recognize user emotions on the server

[1567] 6. Means of generating a response on the server

[1568] 7. A means of sending the generated response back to the user

[1569] Specific Description of the Embodiments

[1570] 1. A means of receiving user input

[1571] A user types a technical problem or question into a terminal and clicks a submit button, which generates a textual user input.

[1572] 2. A means of sending received user input to the server

[1573] The terminal constructs the entered user message as an HTTP POST request and sends it to the server over the Internet.

[1574] The server receives the HTTP POST request and extracts the user's message.

[1575] 3. A way to parse user input on the server

[1576] The server passes the extracted user message to a natural language processing module to understand the user's intent and analyze the problem, using a cloud-based natural language generation API.

[1577] 4. How to process natural language on the server

[1578] The server obtains a response generated based on the results of the previous analysis using a cloud-based natural language generation API (e.g., a generative AI model).

[1579] 5. How to recognize user emotions on the server

[1580] When the server analyzes the user's message, it uses an emotion engine to recognize the user's emotion, extracting emotions from the user's text and adjusting the response accordingly.

[1581] 6. Means of generating a response on the server

[1582] The server uses the results of the emotion engine and the natural language generation API to generate an optimal response, which takes into account the user's emotions.

[1583] The server will format the generated response, removing unnecessary spaces and line breaks, and the final response will be constructed in JSON format.

[1584] 7. A means of sending the generated response back to the user

[1585] The server sends the formatted response to the terminal over the Internet.

[1586] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[1587] Specific examples

[1588] For example, if a user types, "My laptop battery keeps dying. What should I do? I'm so worried.", the steps are as follows:

[1589] 1. The user enters the above text into the terminal and presses the send button.

[1590] 2. The device sends this input text to the server as an HTTP POST request.

[1591] 3. The server receives the request and extracts the text content.

[1592] 4. The server uses a natural language processing module to analyze the battery problem and the question.

[1593] 5. The server uses the emotion engine to extract the emotion "troubled."

[1594] 6. The server generates a response suggesting specific battery solutions, such as: "Close unnecessary applications running in the background, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[1595] 7. The server sends the generated response in JSON format to the device.

[1596] 8. The device parses the JSON response and displays solutions to the user, such as closing unnecessary applications running in the background, lowering the display brightness, turning off Wi-Fi and Bluetooth, using a battery diagnostic tool, or replacing the battery.

[1597] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1598] System program processing flow

[1599] Step 1:

[1600] The user enters text

[1601] The user types a technical problem or question into the terminal and clicks the send button.

[1602] Input: A user's textual question or problem (e.g., "My laptop battery keeps dying. What should I do? I'm so frustrated.").

[1603] Output: Text data entered into the terminal.

[1604] Step 2:

[1605] The device sends user input to the server

[1606] The terminal constructs the entered user message as an HTTP POST request.

[1607] The terminal transmits the data to a server via the Internet.

[1608] Input: Text data entered into the terminal.

[1609] Output: User message in the form of an HTTP POST request.

[1610] Step 3:

[1611] The server receives and parses the user input

[1612] The server receives the HTTP POST request and extracts the user's message from the request body.

[1613] Input: HTTP POST request.

[1614] Output: The extracted user's message text.

[1615] Step 4:

[1616] The server processes natural language

[1617] The server passes the extracted user messages to a natural language processing module, which analyzes the intent and subject of the text.

[1618] Input: The extracted user's message text.

[1619] Output: Intent and thematic information resulting from the analysis.

[1620] Step 5:

[1621] The server recognizes the user's emotions

[1622] The server uses an emotion engine to extract emotional information from the user's message, for example, determining whether the user is feeling "troubled."

[1623] Input: The user's message text.

[1624] Output: Extracted emotion information.

[1625] Step 6:

[1626] The server generates a response

[1627] The server uses the natural language generation API to generate the optimal response based on the results of the natural language processing module and the emotion engine.

[1628] As specific actions, the server invokes the generative AI model to generate solutions to the battery problem, such as "close unnecessary applications running in the background, reduce display brightness, turn off Wi-Fi and Bluetooth, use a battery diagnostic tool, or replace the battery."

[1629] Input: Intention, subject matter information, and emotional information.

[1630] Output: The generated response text.

[1631] Step 7:

[1632] The server formats the generated response

[1633] The server formats the generated response, removing unnecessary spaces and line breaks, and constructs the final response in JSON format.

[1634] Input: The generated response text.

[1635] Output: Pretty-printed JSON response.

[1636] Step 8:

[1637] The server sends the response back to the user

[1638] The server sends a JSON-formatted response to the device over the Internet.

[1639] Input: The response in JSON format.

[1640] Output: Data sent to the terminal.

[1641] Step 9:

[1642] The terminal parses and displays the response

[1643] The device parses the JSON response received from the server and converts it into a format that can be displayed to the user.

[1644] Input: The JSON response received from the server.

[1645] Output: The response text that can be displayed to the user.

[1646] Step 10:

[1647] User reviews response and takes action

[1648] The user reviews the response displayed on the device and takes specific action based on the solution provided.

[1649] Input: The response text displayed on the user's terminal.

[1650] Output: User behavior and corresponding actions.

[1651] (Application example 2)

[1652] 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."

[1653] Conventional electronic payment services have difficulty providing prompt and appropriate support for technical problems faced by users. Furthermore, support does not take into consideration the user's feelings, which can lead to a poor user experience. Therefore, a new system is needed that can quickly grasp the user's situation and provide an appropriate solution.

[1654] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1655] In this invention, the server includes means for receiving user input, means for analyzing the user's emotions, means for generating an appropriate response through natural language processing, and means for returning the generated response to the user, thereby enabling technical problems to be resolved quickly and appropriately while taking the user's emotions into consideration.

[1656] "Means for receiving user input" refers to the function by which a terminal or system receives information such as text or voice input by a user and recognizes it as data to be processed.

[1657] The "means for processing received user input" is a function for analyzing received user input information and performing processing to derive an appropriate response based on the content of the information.

[1658] "Means for generating an appropriate response through natural language processing" is a function that uses natural language processing technology to interpret the user's input and generate an appropriate and meaningful response.

[1659] The "means for returning the generated response to the user" is a function for sending the response generated by natural language processing to the user's terminal so that the user can receive and confirm it.

[1660] The "means for analyzing user emotions" is a function that extracts emotions from the user's input and adjusts the content and tone of the response based on those emotions.

[1661] MODE FOR CARRYING OUT THE INVENTION

[1662] System Overview

[1663] This invention is a system that allows users to quickly and appropriately resolve technical problems in electronic payment services. The system aims to generate appropriate responses to problems input by users and to respond in a way that takes into account their emotions.

[1664] Technologies and tools used

[1665] Hardware: Smartphones, smart glasses

[1666] Software: Python-based server, natural language processing API (e.g., OpenAI's GPT-3), sentiment analysis engine (e.g., IBM Watson Tone Analyzer)

[1667] Program Description

[1668] The server implements the system using the following means:

[1669] Ways to receive user input:

[1670] It receives text and voice data entered by the user through a smartphone or smart glasses, and sends this data to the server as an HTTP POST request.

[1671] Ways to analyze user sentiment:

[1672] IBM Watson Tone Analyzer is used to extract sentiment from incoming user input, and this sentiment information is used to tailor responses during subsequent natural language processing.

[1673] A means of generating appropriate responses through natural language processing:

[1674] It uses natural language generation APIs like OpenAI's GPT-3 to generate appropriate responses based on the user's text input, taking into account the emotional information extracted earlier.

[1675] A means of sending the generated response back to the user:

[1676] The server generates a response and sends it in JSON format to the user's device, which parses it and displays it to the user.

[1677] Processing flow

[1678] The server receives user input, passes it to IBM Watson Tone Analyzer to analyze emotions, then uses OpenAI's GPT-3 for natural language processing to generate a response that takes the user's emotions into account, and sends this response in JSON format to the user's device for display.

[1679] Specific examples

[1680] For example, if a user enters "My payment has failed due to an error. What should I do?" while using an electronic payment service, the following process will be performed.

[1681] 1. The user enters a question into their smartphone, which is then sent to the server.

[1682] 2. The server receives the question, analyzes it using IBM Watson Tone Analyzer, and extracts the emotion of "troubled."

[1683] 3. The server uses OpenAI's GPT-3 to generate a sentiment-based response, which might say something like, "It looks like you've encountered a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try changing your payment method or contact our support center. We apologize for any inconvenience."

[1684] 4. The server sends the generated response in JSON format to the user's smartphone, where the user confirms the response.

[1685] Prompt Sentence Examples

[1686] Below are some example prompts to input to the generative AI model:

[1687] Please respond appropriately to the following question, taking into consideration the user's feelings.\nUser's question: {{ user_message}}"

[1688] As described above, by combining these means and technologies, we will realize a system that quickly and appropriately resolves technical problems faced by users.

[1689] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1690] Step 1:

[1691] Users use their smartphones or smart glasses to input technical questions about electronic payments. The user's question is sent in text format to the device, which is then sent to the server as an HTTP POST request.

[1692] Input: User's text message

[1693] Output: HTTP POST request

[1694] Step 2:

[1695] The server receives the incoming HTTP POST request and analyzes its contents.

[1696] Input: HTTP POST request (containing the user's text message)

[1697] Output: User's text message

[1698] Step 3:

[1699] The server passes the user's message to IBM Watson Tone Analyzer for sentiment analysis. The sentiment analysis engine detects the tone of the message and extracts the user's emotional information.

[1700] Input: User's text message

[1701] Output: User's emotional state (e.g., troubled, angry, etc.)

[1702] Step 4:

[1703] The server passes the results of the sentiment analysis engine and the user's message to OpenAI GPT-3 to generate an appropriate response. The prompt sentence is used to provide instructions to the generative AI model to generate an emotion-sensitive response.

[1704] Input: User text message, user emotion information

[1705] Output: The response generated by natural language processing

[1706] Step 5:

[1707] The server formats the generated response, removing unnecessary spaces and line breaks, and constructs the response in JSON format.

[1708] Input: A response generated by natural language processing

[1709] Output: Formatted response (JSON format)

[1710] Step 6:

[1711] The server sends the formatted response to the user's terminal, which receives the response, converts it into a format that is displayed to the user, and displays it.

[1712] Input: Formatted response (JSON format)

[1713] Output: A text response in a format that can be viewed by the user

[1714] Specific examples

[1715] For example, the specific processing flow when a user inputs "My payment has not gone through due to an error. What should I do?" is shown below.

[1716] Step 1:

[1717] Enter: "My payment is not going through. What should I do?"

[1718] Output: HTTP POST request

[1719] Step 2:

[1720] Input: HTTP POST request

[1721] Output: "My payment failed due to an error. What should I do?"

[1722] Step 3:

[1723] Enter: "My payment is not going through. What should I do?"

[1724] Output: "I'm in trouble"

[1725] Step 4:

[1726] Input: "My payment is not going through. What should I do?" "I'm in trouble."

[1727] Output: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[1728] Step 5:

[1729] Input: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[1730] Output: JSON response

[1731] Step 6:

[1732] Input: JSON formatted response

[1733] Output: "It looks like you're experiencing a payment error. To resolve this issue, please first check your internet connection. If the issue persists, please try a different payment method or contact our support center. We apologize for any inconvenience."

[1734] 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.

[1735] 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.

[1736] 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.

[1737] 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.

[1738] FIG. 9 illustrates 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 behaviors 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.

[1739] 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.

[1740] 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).

[1741] 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.

[1742] 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."

[1743] 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.

[1744] 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).

[1745] 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.

[1746] 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.

[1747] 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.

[1748] 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.

[1749] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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 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.

[1750] 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.

[1751] 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.

[1752] 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.

[1753] 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.

[1754] 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.

[1755] The following is further disclosed regarding the above embodiment.

[1756] ---

[1757] (Claim 1)

[1758] means for receiving user input;

[1759] means for processing received user input;

[1760] a means for generating appropriate responses through natural language processing;

[1761] means for returning the generated response to the user;

[1762] A system including:

[1763] (Claim 2)

[1764] 10. The system of claim 1, wherein the means for processing the received user input comprises means for generating a response using a cloud-based natural language generation API.

[1765] (Claim 3)

[1766] 10. The system of claim 1, wherein the means for processing the received user input includes, as part of the data, information regarding the user's technical problem.

[1767] "Example 1"

[1768] (Claim 1)

[1769] means for receiving user input;

[1770] means for textually analyzing received user input;

[1771] a means for generating an appropriate response based on the analysis result using a natural language processing model;

[1772] means for transmitting the generated response to a user;

[1773] A system including:

[1774] (Claim 2)

[1775] 2. The system of claim 1, wherein the means for analyzing text uses a cloud-based natural language generation API to generate a response.

[1776] (Claim 3)

[1777] 2. The system of claim 1, wherein the means for analyzing text analyzes information related to a user's technical problem.

[1778] "Application Example 1"

[1779] (Claim 1)

[1780] means for receiving user input;

[1781] means for parsing received user input;

[1782] means for generating a response using natural language generation techniques;

[1783] means for transmitting the generated response to a user;

[1784] Problem-solving measures related to electronic payments;

[1785] A system including:

[1786] (Claim 2)

[1787] 10. The system of claim 1, wherein the means for analyzing the received user input comprises means for generating a response using cloud-based natural language generation technology.

[1788] (Claim 3)

[1789] 10. The system of claim 1, wherein the means for analyzing the received user input includes, as part of the data, information regarding the user's technical problem and information related to electronic payments.

[1790] "Example 2: Combining Emotion Engines"

[1791] (Claim 1)

[1792] means for receiving user input;

[1793] means for transmitting the received user input to a server;

[1794] a means for parsing user input at the server;

[1795] A means for performing natural language processing on the server;

[1796] a means for recognizing user emotions in a server;

[1797] a means for generating a response at the server;

[1798] means for returning the generated response to the user;

[1799] A system including:

[1800] (Claim 2)

[1801] 2. The system of claim 1, wherein the means for performing natural language processing on the server is means for generating responses using a cloud-based natural language generation API.

[1802] (Claim 3)

[1803] 2. The system according to claim 1, wherein the means for recognizing the user's emotion in the server is a means for extracting emotion information from the user's input text using an emotion engine and adjusting the response based on the result.

[1804] "Application example 2 when combining emotion engines"

[1805] (Claim 1)

[1806] means for receiving user input;

[1807] means for processing received user input;

[1808] a means for generating appropriate responses through natural language processing;

[1809] means for returning the generated response to the user;

[1810] A system including means for analyzing user emotions.

[1811] (Claim 2)

[1812] 10. The system of claim 1, wherein the means for processing the received user input comprises means for generating a response using a cloud-based natural language generation API.

[1813] (Claim 3)

[1814] 2. The system of claim 1, wherein the means for processing the received user input includes, as part of the data, information regarding the user's technical issues and emotional information. [Explanation of symbols]

[1815] 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 user input; means for processing received user input; a means for generating appropriate responses through natural language processing; means for returning the generated response to the user; A system including:

2. 10. The system of claim 1, wherein the means for processing the received user input comprises means for generating a response using a cloud-based natural language generation API.

3. 2. The system of claim 1, wherein the means for processing the received user input includes, as part of the data, information regarding the user's technical problem.

Images