System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving text data input from a user; means for analyzing the received text data and extracting a keyword and an emotional tone; means for searching for related advice data from a database based on the extracted keyword and emotional tone; means for selecting appropriate advice data from a search result and generating information to be provided to the user; and means for transmitting the generated information to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern life, people often face situations where they are hurt or in need of deep comfort. At such times, they may not have a suitable person to talk to, or they may not be able to easily find words or stories of encouragement. In particular, there are almost no services that provide words tailored to their own situations, making it difficult to obtain emotional support or encouragement. This invention aims to solve such problems. [Means for solving the problem]

[0005] In order to solve the above problems, the present invention provides the following means: a system including means for accepting text data input by a user, means for analyzing the accepted text data and extracting keywords and emotional tones, means for searching a database for relevant advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results and generating information to be provided to the user, and means for transmitting the generated information to the user.

[0006] This system allows users to easily obtain appropriate advice and anecdotes tailored to their own situations and concerns, providing emotional support and encouragement. Furthermore, by using natural language processing technology to extract emotional tones from the analyzed text data and to generate the meaning, historical background, and similar words of the selected advice data, it is possible to provide deeper understanding and empathy.

[0007] "User" refers to an individual or group that uses the system to input their own situation and concerns.

[0008] "Input text data" refers to character information that a user inputs into the system via a terminal.

[0009] "Means for receiving" refers to a function or module that allows the system to receive text data entered by the user.

[0010] "Means for analysis" refers to functions and modules that use natural language processing technology to understand accepted text data and extract keywords and emotional tones.

[0011] "Keywords" refer to words or phrases that are considered to be particularly important in the analyzed text data.

[0012] "Emotional tone" refers to information that indicates the type and intensity of emotions extracted from text data.

[0013] "Searching means" refers to a function or module for searching for relevant advice data from a database based on the extracted keywords and emotional tones.

[0014] A "database" refers to a collection of information that stores advice data such as historical figures, myths, and proverbs.

[0015] "Advice data" refers to information related to encouragement or advice for a user's situation.

[0016] "Selection means" refers to functions or modules for selecting the most appropriate advice data from search results.

[0017] "Means for generating information" refers to functions and modules for creating information that includes meanings, historical background, and similar words related to the selected advice data.

[0018] "Transmitting means" refers to a function or module that transmits data to convey the generated information to the user.

[0019] "Natural language processing technology" refers to technology that enables computers to understand and process human language. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] As an embodiment of the present invention, we will specifically explain a system that provides encouraging words and advice appropriate to the user's situation and worries. This system performs a series of operations: accepting and analyzing text data entered by the user, and searching and generating appropriate advice data.

[0042] First, the user accesses the system using a terminal and inputs text about their experiences, worries, and other situations. The text data input by the user is in a format such as, "I recently made a big mistake and have lost confidence. What should I do?"

[0043] The device then sends this text data to a server, which uses natural language processing techniques to analyze the received text data and extract keywords and emotional tones. This analysis step involves morphological analysis and sentiment analysis to understand the user's situation.

[0044] Specifically, the server extracts keywords such as "failure" and "lose confidence" and identifies the user's emotions as negative states such as "disappointment" and "disappointment."

[0045] Next, the server searches for relevant advice data from a database based on the extracted keywords and emotional tone. The database contains advice from historical figures, myths, proverbs, etc. The server then searches for the most appropriate advice data from this database.

[0046] The system selects appropriate advice data from the search results and generates information to provide it to the user. The generated information includes not only the words of advice themselves, but also their meaning, source, historical background, and similar words. For example, if the server selects the proverb "Failure is the mother of success," it generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," and also includes a "Japanese proverb" as the source and "a lesson that has long been rooted in Japanese culture" as the historical background.

[0047] Finally, the generated information is sent to the terminal, which then displays it to the user. The displayed information is in the following format:

[0048] "Failure is the foundation of success"

[0049] Source: Japanese proverb

[0050] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0051] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0052] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0053] This allows users to receive appropriate encouragement and advice, providing emotional support and courage. This series of operations in the system realizes the provision of personalized information that is in line with the user's emotions and situation.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] The user accesses the system through a terminal and inputs their situation and worries as text. For example, the user might input, "I recently made a big mistake and lost confidence. What should I do?"

[0057] Step 2:

[0058] The device sends the entered text data to the server using an HTTP POST request, with the data sent in JSON format.

[0059] Step 3:

[0060] The server receives and analyzes the received text data using natural language processing (NLP) techniques. Specifically, morphological analysis is used to extract keywords and sentiment analysis is used to identify the user's emotional tone.

[0061] Step 4:

[0062] The server searches the database based on the keywords and emotional tones extracted from the analysis, using SQL queries and search algorithms to find relevant advice data.

[0063] Step 5:

[0064] The server selects the most appropriate advice data from the search results, using an algorithm to select words and anecdotes that best fit the user's emotional tone and situation.

[0065] Step 6:

[0066] The server generates additional information (meaning, source, historical background, similar words) related to the selected advice data. For example, it generates the meaning and background information of the proverb "Failure is the mother of success."

[0067] Step 7:

[0068] The server generates the information and sends it to the device, again using an HTTP POST request, with the data sent in JSON format.

[0069] Step 8:

[0070] The device displays the received information to the user via the user interface of a web browser or mobile app. For example, the device displays the proverb "Failure is the mother of success" and related information.

[0071] Example 1

[0072] 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."

[0073] There is a problem that it is difficult for users to get appropriate advice and encouragement for their worries or situations. In particular, there is a lack of systems that provide customized advice based on emotions and specific keywords, so users cannot obtain the information they really need. To solve this problem, it is necessary to provide a system that can accurately analyze users' text data and provide optimal advice.

[0074] 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.

[0075] In this invention, the server includes means for accepting text data input by a user, means for analyzing the accepted text data and using natural language processing technology to extract keywords and emotional tones, means for searching for relevant advice data from information sources based on the extracted keywords and emotional tones, means for selecting optimal advice data from the search results and generating information to be provided to the user, and means for transmitting the generated information to the user's terminal, thereby enabling the user to receive personalized advice and encouragement tailored to their own concerns and situations in real time.

[0076] "Text data" is data in the form of a sentence entered by the user.

[0077] "Natural language processing technology" is a technology that allows computers to understand, analyze, and generate human language.

[0078] "Emotional tone" refers to the emotional trend or state extracted from within text.

[0079] "Keywords" are important words or phrases extracted from text data.

[0080] "Advice data" refers to advice or encouragement provided to the user in response to their concerns or situations.

[0081] "Source" refers to a database or other storage device where advisory data is stored.

[0082] A "server" is a computer system that analyzes text data, searches for advice data, and transmits the generated information.

[0083] A "user terminal" is a device used by a user to access the system and enter text data.

[0084] "Generated information" refers to information that is created based on advice data searched and selected by the server and is to be provided to the user.

[0085] As an embodiment of the present invention, the operation of a system that provides advice and words of encouragement appropriate to a user's situation and worries will be specifically described. Each component of the system and its operation will be described in detail below.

[0086] Hardware and software used

[0087] server

[0088] The server performs the main data processing and database lookup. The server is usually hosted in a cloud environment and has sufficient computing resources. The main software components include:

[0089] Natural language processing engine (morphological analysis engine): Examples include MeCab and Janome

[0090] Sentiment analysis libraries: Examples include Google Cloud Natural Language API and NLTK

[0091] Database Management System (DBMS): Examples include MySQL and PostgreSQL

[0092] Terminal

[0093] The devices used by users are devices such as PCs, smartphones, tablets, etc. These devices are capable of connecting to the Internet and are used to access the system's web applications and mobile applications.

[0094] Processing flow and data processing / calculation

[0095] 1. User text input

[0096] Users access the system using a terminal and input situations such as their own experiences and worries. For example, they might input, "I recently made a big mistake and lost confidence. What should I do?"

[0097] 2. Sending text data

[0098] The terminal sends the entered text data to the server, which converts the data into an appropriate format (e.g., JSON) and sends it as an HTTP POST request.

[0099] 3. Receiving and analyzing text data

[0100] The server parses the received text data. The parsing is done in two stages:

[0101] Morphological analysis: The text is segmented and keywords are extracted. For example, keywords such as "failure" and "lose confidence" are extracted.

[0102] Sentiment analysis: Extracting the emotional tone of text. For example, negative emotional states such as "disappointed" or "disappointed" can be identified.

[0103] 4. Searching for advisory data

[0104] The server searches for appropriate advice data from a database containing proverbs, famous quotes, historical anecdotes, etc. based on the analyzed keywords and emotional tone, and selects the most appropriate advice data from the searched data.

[0105] 5. Generating Advisory Information

[0106] The server generates more detailed information based on the selected advice data. The generated information includes the advice itself, its meaning, its source, historical background, and similar words. For example, for the proverb "Failure is the mother of success," the server generates the following information:

[0107] "Failure is the foundation of success"

[0108] Source: Japanese proverb

[0109] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0110] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0111] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0112] 6. Transmission and display of generated information

[0113] The server sends the generated information to the terminal, which displays the received information on the user's screen, allowing the user to read it and receive appropriate advice and encouragement.

[0114] Specific examples

[0115] If a user types, "I recently made a big mistake and it's ruined my confidence. What should I do?", the system will act as follows:

[0116] 1. The user uses the terminal to input text data.

[0117] 2. The device sends the input data to the server.

[0118] 3. The server analyzes the text data and extracts keywords and emotional tones.

[0119] 4. The server retrieves the relevant advisory data from the database.

[0120] 5. The server selects the most appropriate advice data and generates detailed information.

[0121] 6. The server sends the generated information to the terminal, which displays the information to the user.

[0122] Example prompts for generative AI models

[0123] "If a user types in, 'I recently made a big mistake and I've lost confidence. What should I do?', provide appropriate advice such as the proverb 'Failure is the mother of success,' along with its meaning, source, historical context, and similar phrases."

[0124] The above is a detailed description of the mode for carrying out the invention. The system contributes to obtaining emotional support by providing personalized advice and encouragement to users.

[0125] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0126] Step 1:

[0127] Users access the system using their own terminals and input the worries and situations they have experienced.

[0128] Input: Text data entered by the user (e.g., "I recently made a big mistake and it's really hurt my confidence. What should I do?").

[0129] Output: Text data entered into the user's terminal.

[0130] Specific Actions: A user opens a web or mobile application on the system and enters text into a text input field.

[0131] Step 2:

[0132] The terminal transmits the input text data to the server.

[0133] Input: Text data entered by the user into the terminal.

[0134] Output: The text data sent to the server (e.g., an HTTP POST request in JSON format).

[0135] Specific operation: The terminal converts the text data entered by the user into an appropriate format and sends an HTTP POST request to the server.

[0136] Step 3:

[0137] The server analyzes the received text data and extracts keywords and emotional tones.

[0138] Input: Text data sent from the device to the server.

[0139] Output: Analyzed keywords and emotional tone (e.g., "failure," "losing confidence," "disappointed," "disappointed").

[0140] Data processing: Segment the text and extract keywords using a morphological analysis engine (e.g., MeCab or Janome). Analyze emotional tone using a sentiment analysis library (e.g., Google Cloud Natural Language API or NLTK).

[0141] How it works: The server first uses a morphological analysis engine to segment the text, then uses a sentiment analysis library to identify the emotional tone.

[0142] Step 4:

[0143] The server retrieves relevant advisory data from information sources based on the extracted keywords and emotional tones.

[0144] Input: Extracted keywords and emotional tone.

[0145] Output: Search results with relevant advice (e.g., "Failure is the key to success").

[0146] Data computation: Query the database using a database management system (DBMS) based on keywords and emotional tone.

[0147] Specific operations: The server queries the database to obtain relevant advisory data.

[0148] Step 5:

[0149] The server selects the most suitable advice data from the search results and generates information to provide to the user.

[0150] Input: Advisory data obtained as search results.

[0151] Output: Generated detailed advice (e.g., the phrase "Failure is the mother of success," its meaning, origin, historical context, and similar phrases).

[0152] Data processing: Generate detailed meanings, sources, historical background, and similar words for the selected advice data.

[0153] Specific operation: The server analyzes the acquired advice data and generates detailed information based on its meaning and background information.

[0154] "Failure is the foundation of success"

[0155] Source: Japanese proverb

[0156] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0157] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0158] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0159] Step 6:

[0160] The server transmits the generated information to the user's terminal.

[0161] Input: The generated detailed advisory information.

[0162] Output: Advisory information sent from the server to the device (e.g., HTTP response in JSON format).

[0163] Specific operation: The server formats the generated information appropriately and sends it to the terminal as an HTTP response.

[0164] Step 7:

[0165] The terminal receives the transmitted information and displays it on the user's screen.

[0166] Input: Advisory information sent by the server.

[0167] Output: Detailed advisory information displayed on the user's screen.

[0168] Specific operation: The device analyzes the received information and displays it on the user's screen in an easy-to-read format.

[0169] These are the specific processing steps of the program for this system. Through this series of steps, users can receive personalized advice and encouragement in real time, tailored to their concerns.

[0170] (Application example 1)

[0171] 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."

[0172] This paper deals with a method for providing prompt and appropriate advice to users regarding troubles and difficulties they may encounter while using electronic payment services. Conventional systems lack personalized support tailored to the specific concerns and feelings of users, and this has resulted in the inability to fully alleviate users' anxieties and dissatisfaction.

[0173] 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.

[0174] In this invention, the server includes means for accepting text data entered by a user, means for analyzing the accepted text data and extracting keywords and emotional tones, means for searching a database for relevant advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results and generating information to provide to the user, means for transmitting the generated information to the user, and means for analyzing user troubles and emotions in relation to electronic payment services and providing appropriate advice. This makes it possible to quickly provide appropriate advice that is in line with the user's emotional tones in response to problems that arise while the user is using the electronic payment service.

[0175] "Text data" refers to character information entered by the user.

[0176] "Keywords" are important words or phrases extracted from text data.

[0177] "Emotional tone" indicates the emotional state or tendency that can be read from the user's input.

[0178] A "database" refers to a collection of data in which information such as proverbs and advice is stored.

[0179] "Advice data" is information including encouragement and solutions provided in response to the user's worries or situations.

[0180] "Electronic payment service" refers to a digital service for processing payments online or offline.

[0181] "Natural language processing technology" is a technology that enables computers to understand and analyze human language.

[0182] "Analysis" refers to the act of analyzing input text data to understand its structure and meaning.

[0183] "Generation" refers to the process of creating new information or data.

[0184] "Sending" refers to the act of delivering the generated information to the user's terminal.

[0185] "Search" refers to the act of locating appropriate information from a database based on specified criteria.

[0186] As an embodiment of the present invention, a system for providing appropriate advice to a user for solving their worries or difficulties will be specifically described. This system performs a series of operations to accept and analyze text data entered by the user, search for and generate appropriate advice data, and provide it to the user. The specific processing procedure will be described below.

[0187] System Configuration

[0188] Hardware and Software

[0189] Server: The central computer system for analysis and advice generation. It uses nltk and TextBlob natural language processing technologies.

[0190] User terminal: A device that allows users to input text data and receive appropriate advice. It works on smartphones or smart glasses.

[0191] Database: A storage system for storing advice data, such as quotes, words of encouragement, and other advice data.

[0192] Program processing overview

[0193] The user terminal sends the text data entered by the user to the server, which then analyzes the received text data and extracts keywords and emotional tones using natural language processing techniques.

[0194] Specifically, the server uses TextBlob to extract the emotional tone of the text data, and then performs morphological analysis to extract keywords. Through this process, it is possible to understand the user's concerns and situations.

[0195] The server then searches for relevant advice data from a database based on the extracted keywords and emotional tones. The database contains historical proverbs and words of encouragement, and the server finds the most suitable advice data.

[0196] The server then selects appropriate advice data from the search results, and generates information on the meaning of the word, the historical background, and similar words. This information is structured to be easy for users to understand and to provide encouragement and solutions.

[0197] Finally, the server transmits the generated advice data to the user terminal, which then displays the information to the user. The following is a specific example.

[0198] Specific examples

[0199] User Input: "I was recently scammed and it's really hurt my confidence. What should I do?"

[0200] System response:

[0201] "Failure is the foundation of success"

[0202] Source: Japanese proverb

[0203] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0204] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0205] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0206] Prompt Sentence Examples

[0207] "I was recently scammed and my confidence has been damaged. What should I do?"

[0208] Advice that encourages the person's heart, such as "Failure is the mother of success," "If you keep trying without being afraid of failure, you will eventually achieve success," and "Don't give up after one failure."

[0209] This invention enables users to quickly receive appropriate advice tailored to their emotional tone when encountering problems while using electronic payment services. This system reduces users' anxiety and frustration and provides quick and effective support.

[0210] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0211] Step 1:

[0212] User Input

[0213] The user inputs text data about their worries or difficulties into the terminal. The input data format is something like, "I was recently the victim of a scam and I've lost confidence. What should I do?"

[0214] Input: User's text data

[0215] Output: Text data received by the device

[0216] Step 2:

[0217] Sending text data

[0218] The terminal sends the received text data to the server. At this time, the data is encrypted before being sent.

[0219] Input: Text data entered into the terminal

[0220] Output: Encrypted text data sent to the server

[0221] Step 3:

[0222] Text data analysis

[0223] The server analyzes the received text data, extracts the emotional tone of the text data using TextBlob, and performs morphological analysis to extract keywords, such as "failure" and "lose confidence."

[0224] Input: Text data sent to the server

[0225] Output: Extracted emotional tones and keywords

[0226] Step 4:

[0227] Retrieving advice data from a database

[0228] The server searches the database for relevant advice data based on the extracted keywords and emotional tones, for example, searching for advice data such as "Failure is the mother of success" based on the keyword "failure."

[0229] Input: Extracted emotional tone and keywords

[0230] Output: Retrieved advisory data

[0231] Step 5:

[0232] Selection and generation of appropriate advisory data

[0233] The server selects appropriate advice data from the search results and generates words that reflect its meaning, historical context, and similar expressions. For example, the server generates the meaning of the proverb "Failure is the mother of success" as "If you keep trying without fear of failure, you will eventually achieve success."

[0234] Input: Retrieved advisory data

[0235] Output: Selected advisory data and its details

[0236] Step 6:

[0237] Sending advisory data

[0238] The server sends the generated advice data to the terminal, which receives the data and displays it to the user. The displayed information includes the advice words, meanings, sources, historical background, and similar words.

[0239] Input: Selected advisory data and its details

[0240] Output: Advisory data sent to the terminal

[0241] Step 7:

[0242] Providing advice to users

[0243] The terminal displays the received advice data to the user in the following format:

[0244] Input: Advisory data sent to the terminal

[0245] Output: Advisory data displayed to the user

[0246] "Failure is the foundation of success"

[0247] Source: Japanese proverb

[0248] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0249] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0250] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0251] 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.

[0252] As an embodiment of the present invention, a system for providing encouraging words and advice tailored to a user's situation and concerns will be specifically described. This system is characterized by incorporating a series of means for accepting, analyzing, searching, generating, and transmitting text data, as well as an emotion engine for recognizing the user's emotions.

[0253] First, the user accesses the system using a terminal and enters specific text about the problem or issue they would like to discuss. For example, the user might enter, "I recently made a big mistake and have lost confidence. What should I do?"

[0254] The device then sends this text data to the server using an HTTP POST request, with the data being sent to the server in JSON format.

[0255] The server analyzes the received text data and uses natural language processing techniques to extract keywords and emotional tones. Morphological analysis extracts keywords such as "failure" and "loss of confidence," while sentiment analysis identifies the user's emotions as "disappointment" and "disappointment."

[0256] The system also incorporates an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the user's input pixel by pixel to identify the intensity and type of emotion. If the emotion engine determines that the intensity of "disappointment" is high, it will take that information into account and proceed to the next step.

[0257] The server searches the database for relevant advice data based on the extracted keywords and emotional tone, for example, the server searches the database for advice related to failure and regaining self-confidence.

[0258] The server then selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine, and for a user who is feeling strong "disappointment," the most effective advice is selected.

[0259] The server generates the meaning, source, historical background, and similar words related to the selected advice data. For example, for the proverb "Failure is the mother of success," the server generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," and includes "Japanese proverbs" as the source and "lessons that have been deeply rooted in Japanese culture since ancient times" as the historical background.

[0260] The generated information is sent to the terminal, which displays it to the user in the following format:

[0261] "Failure is the foundation of success"

[0262] Source: Japanese proverb

[0263] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0264] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0265] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0266] This allows users to receive appropriate encouragement and advice, helping them regain their emotional support and courage.The entire system's operations realize personalized information provision that is tailored to the user's emotions and situation.

[0267] The processing flow will be explained below.

[0268] Step 1:

[0269] The user accesses the system through a terminal and inputs their situation and worries as text. For example, the user might input, "I recently made a big mistake and lost confidence. What should I do?"

[0270] Step 2:

[0271] The device sends the entered text data to the server using an HTTP POST request, and the data is sent to the server in JSON format.

[0272] Step 3:

[0273] The server analyzes the received text data. Using natural language processing (NLP) technology, it extracts keywords through morphological analysis and identifies the user's emotional tone through sentiment analysis. For example, keywords such as "failure" and "loss of confidence" are extracted, and the emotional tone is identified as "disappointment" or "disappointment."

[0274] Step 4:

[0275] The server uses an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the type and intensity of emotions on a pixel-by-pixel basis. For example, it determines that the intensity of "disappointment" is high based on the user's input.

[0276] Step 5:

[0277] The server searches the database for appropriate advice data based on the extracted keywords and the emotional tone recognized by the emotion engine, for example, advice data related to "failure" and "recovering self-confidence" are searched for in the database.

[0278] Step 6:

[0279] The server selects the most appropriate advice data from the search results. This selection also takes into account the emotional information recognized by the emotion engine. For example, if a user is feeling strong disappointment, the most effective advice will be selected.

[0280] Step 7:

[0281] The server generates information related to the selected advice data (meaning, source, historical background, similar words). For example, for the proverb "Failure is the mother of success," it generates meaning and background information. Specifically, it generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," the source "Japanese proverb," ​​and the historical background "a lesson that has been deeply rooted in Japanese culture since ancient times."

[0282] Step 8:

[0283] The server then sends the generated information to the device, again using an HTTP POST request, with the data sent to the device in JSON format.

[0284] Step 9:

[0285] The terminal displays the received information to the user through the user interface in the following format, for example:

[0286] "Failure is the foundation of success"

[0287] Source: Japanese proverb

[0288] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0289] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0290] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0291] In this way, users can receive appropriate encouragement and advice, and regain their emotional support and courage.

[0292] Example 2

[0293] 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."

[0294] Conventional user support systems sometimes fail to provide appropriate advice based on user input. Furthermore, they lack a mechanism for recognizing the user's emotions in detail and selecting appropriate advice, which means that the effective support desired by the user cannot be provided. This increases the likelihood of delays in resolving the user's concerns, leading to a lack of psychological support.

[0295] 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.

[0296] In this invention, the server includes means for accepting text data input by a user, means for transmitting the accepted text data to the server, means for analyzing the received text data and extracting keywords and emotional tones, means for analyzing the extracted emotional tones in more detail using an emotion engine, means for searching a database for related advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results, means for generating meanings, sources, historical backgrounds, and similar words related to the selected advice data, and means for transmitting the generated information to the user. This makes it possible to provide appropriate advice according to emotions analyzed in detail based on the user's worries and consultation contents.

[0297] "User" refers to an individual who uses this system and inputs their concerns or questions in text format.

[0298] "Terminal" refers to a device used by a user, and includes information processing devices such as smartphones, tablets, and personal computers.

[0299] "Text data" refers to character information entered by a user through a terminal, and is language data that includes worries and consultation details.

[0300] A "server" is a computer device that serves as the core of a system that analyzes received text data and processes and provides related information in conjunction with a database.

[0301] An "HTTP POST request" is one of the communication protocols used when sending data from a terminal to a server.

[0302] "JSON format" is a data exchange format for structuring text data for data transmission.

[0303] "Natural language processing technology" is a technology for analyzing human language and converting it into a form that a computer can understand, and includes morphological analysis and sentiment analysis.

[0304] "Morphological analysis" is a technique that breaks down text data into individual words or morphemes and analyzes their meaning and role.

[0305] "Emotional tone" is information that indicates the user's emotions contained in the text data, and refers to emotional attributes such as "disappointment" or "disappointment."

[0306] An "emotion engine" refers to software or algorithms that perform detailed analysis of emotions from text data entered by a user.

[0307] "Database" refers to a collection of information used by the server to look up relevant advisory data; it is a structured collection of data.

[0308] "Advice data" is information including solutions and words of encouragement provided to the user in response to the user's worries or inquiries.

[0309] "Generative AI model" refers to an artificial intelligence algorithm that generates meaning, sources, historical context, and similar words related to selected advisory data.

[0310] This invention relates to a system for providing encouraging words and advice tailored to a user's situation and concerns. This system incorporates a series of means for accepting, analyzing, searching, generating, and transmitting text data, as well as an emotion engine for recognizing the user's emotions.

[0311] First, the user accesses the system using a terminal and enters specific text about the problem or issue they want to discuss. For example, they might enter, "I recently made a big mistake and lost confidence. What should I do?" The terminal then sends this entered text data to the server. An HTTP POST request is used to send the data, and the data is sent to the server in JSON format.

[0312] The server analyzes the received text data and extracts keywords and emotional tones using natural language processing technology. Specifically, it uses a morphological analysis tool (e.g., MeCab) to analyze the text data and extract keywords such as "failure" and "loss of confidence." It also uses a sentiment analysis tool (e.g., Google Cloud Natural Language API) to identify the user's emotions as "disappointment" and "disappointment."

[0313] Additionally, an emotion engine is built in, which performs detailed pixel-by-pixel analysis of the user's input text to determine the emotion. This method identifies the intensity and type of emotion. For example, if the emotion "disappointment" is determined to be strong, this information is also incorporated into the next step.

[0314] The server searches the database for relevant advice data based on the extracted keywords and emotional tone. For example, it searches the database for advice related to failure or regaining confidence. This process uses SQL queries.

[0315] The server then selects the most appropriate advice data from the search results. This selection reflects the user's emotional information recognized by the emotion engine. For example, if a user is feeling strong disappointment, the most effective advice will be selected.

[0316] The server then uses a generative AI model (e.g., GPT-4) to generate meanings, sources, historical contexts, and similar words related to the selected advice data. For example, for the proverb "Failure is the mother of success," the server generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," including a "Japanese proverb" as the source and a "lesson deeply rooted in Japanese culture since ancient times" as the historical context.

[0317] The generated information is sent to the terminal for display to the user. The terminal visually displays this information to the user in the following format:

[0318] "Failure is the foundation of success"

[0319] Source: Japanese proverb

[0320] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0321] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0322] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0323] As a concrete example, let's consider the case where a user types, "I made a mistake at work and I just can't get over it. What should I do?" In this case, the device sends the input text to the server, which then analyzes and searches it after receiving it. Ultimately, the user is provided with appropriate advice, which helps them regain their emotional support and courage.

[0324] Examples of prompts using generative AI models include:

[0325] "I made a mistake at work recently and I just can't get over it. What words of encouragement do you have?"

[0326] The entire system's operations are designed to provide personalized information tailored to the user's emotions and situation.

[0327] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0328] Step 1:

[0329] The user accesses the system using a terminal and enters specific text about the problem or issue they would like to discuss. For example, the user might enter, "I recently made a big mistake and have lost confidence. What should I do?"

[0330] Input: The user enters the consultation content in the text input field.

[0331] Output: The entered text data is saved to the terminal.

[0332] Step 2:

[0333] The device sends the entered text data to the server using an HTTP POST request, and the data is sent to the server in JSON format.

[0334] Input: User-entered text data stored on the device.

[0335] Data processing: Convert text data into JSON format.

[0336] Output: Text data formatted in JSON format is sent to the server.

[0337] Step 3:

[0338] The server analyzes the received text data. Natural language processing technology is used to extract keywords and emotional tones from the text data. Specifically, a morphological analysis tool is used to extract keywords such as "failure" and "loss of confidence," and an emotion analysis tool is used to identify the emotional tones as "disappointment" and "disappointment."

[0339] Input: JSON formatted text data received by the server.

[0340] Data processing: Keywords are extracted using morphological analysis and emotional tones are extracted using sentiment analysis.

[0341] Output: Extracted keywords and emotional tones.

[0342] Step 4:

[0343] The server then uses an emotion engine to perform a detailed analysis of the extracted emotional tone. The emotion engine analyzes emotions pixel by pixel and identifies the intensity and type of emotion. For example, if the intensity of "disappointment" is determined to be high, that information is used in the next step.

[0344] Input: Extracted emotional tone.

[0345] Data computation: Detailed analysis of the intensity and type of emotions through the emotion engine.

[0346] Output: Detailed analyzed emotional information (e.g., high intensity of "disappointment") is obtained.

[0347] Step 5:

[0348] The server searches the database for relevant advice data based on the extracted keywords and the analyzed sentiment information, using SQL queries.

[0349] Input: Keywords and detailed analyzed sentiment information.

[0350] Data Calculation: Retrieving relevant advisory data from a database using SQL queries.

[0351] Output: Relevant advisory data is obtained.

[0352] Step 6:

[0353] The server selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine. For example, if a user is feeling strong "disappointment," the most effective advice will be selected.

[0354] Input: Search result advisory data and detailed analyzed sentiment information.

[0355] Data processing: Select the most appropriate advice data based on emotional information.

[0356] Output: Selected advisory data is obtained.

[0357] Step 7:

[0358] The server generates the meaning, source, historical context, and similar words related to the selected advice data. This generation uses a generative AI model to specifically describe each piece of information. For example, for the proverb "Failure is the mother of success," the server generates the meaning, source, historical context, and similar words.

[0359] Input: Selected advisory data.

[0360] Data Computing: Generative AI models are used to generate relevant information.

[0361] Output: Generated meaning, source, historical context, and similar words are provided.

[0362] Step 8:

[0363] The server sends the generated information to the terminal, which then displays it to the user. The display format is intended to provide the generated information to the user visually. For example, in addition to the proverb "Failure is the mother of success," the meaning, source, historical background, and similar expressions are displayed in detail.

[0364] Input: Generated information (meaning, source, historical context, similar words).

[0365] Output: Provided to the user as visually displayed information.

[0366] "Failure is the foundation of success"

[0367] Source: Japanese proverb

[0368] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0369] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0370] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0371] (Application example 2)

[0372] 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."

[0373] Conventional user assistance systems have difficulty providing appropriate advice based on the emotions and situations expressed by the text data entered by the user. This has resulted in problems such as users not receiving the encouragement or specific advice they need, and not being able to effectively obtain emotional support or a sense of security. Furthermore, due to a lack of means to convert voice input into text data or perform detailed analysis of emotions, improvements to the user experience have been required.

[0374] 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.

[0375] In this invention, the server includes means for accepting text data input by a user, means for analyzing the accepted text data and extracting keywords and emotional tones, means for searching a database for relevant advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results and generating information to be provided to the user, means for transmitting the generated information to the user, speech recognition means for accepting voice input from the user and converting it into text data, and means for analyzing the extracted keywords and emotional tones with an emotion engine and identifying the intensity and type of emotion, thereby making it possible to provide personalized information tailored to the user's emotions and situation.

[0376] "Text data input by the user" refers to character data used when the user inputs a question or request for advice to the system.

[0377] "Analysis" is the process of analyzing input text data and extracting necessary information.

[0378] A "keyword" is a key word or phrase that represents the content of the text data.

[0379] "Emotional tone" is an element that indicates the intensity and type of a user's emotion that can be read from text data.

[0380] "Searching" is the act of searching for information in a database to find the appropriate data.

[0381] "Advice data" is data used to provide appropriate advice to users regarding their problems or inquiries.

[0382] "Selection" is the act of choosing the best option from multiple candidates.

[0383] "Information generation" is the process of using data and algorithms to create new information or content.

[0384] "Sending" is the act of delivering the generated information or data to the user's terminal.

[0385] "Voice input" refers to the act of a user using voice to input instructions or consultation details into the system.

[0386] "Speech recognition" is a technology that converts voice data into text.

[0387] An "emotion engine" is an algorithm or system that determines the intensity and type of emotion from user input data.

[0388] "Intensity and type" refers to the degree of strength of an emotion and the type into which the emotion is classified, such as "joy," "sadness," or "anger."

[0389] As an embodiment of the present invention, a system for providing encouraging words and advice tailored to a user's security concerns will be specifically described. This system is characterized by incorporating a series of means for accepting, analyzing, searching, generating, and transmitting text and voice data, as well as an emotion engine for recognizing the user's emotions.

[0390] First, a user accesses the system using a smartphone or smart glasses and inputs their security-related anxieties or fears by text or voice. For example, the user might input, "Recently, I've been worried about someone breaking into my house and I'm scared," or they can speak a similar message by voice.

[0391] The device then sends the entered text or voice data to the server. In the case of voice data, the device uses a voice recognition means to convert the voice into text data, which is then sent to the server. An HTTP POST request is used for transmission, and the data is sent to the server in JSON format.

[0392] The server analyzes the received text data and uses natural language processing technology to extract keywords and emotional tones. Morphological analysis extracts keywords such as "worry" and "fear," and sentiment analysis identifies the user's emotions as "anxiety" and "fear."

[0393] Additionally, the system incorporates an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the user's input pixel by pixel to identify the intensity and type of emotion. If the emotion engine determines that the intensity of "fear" is high, it will proceed to the next step, taking that information into account.

[0394] The server searches the database for relevant advice data based on the extracted keywords and emotional tone, for example, the server searches the database for advice related to security concerns and providing a sense of security.

[0395] The server then selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine, and for a user who is feeling strong "fear," the most effective advice is selected.

[0396] The server generates the meaning, source, historical context, and similar words related to the selected advice data. For example, for the advice "Strengthen home security measures," the server generates the meaning "Install security cameras and alarm systems to ensure safety," including the source "security experts" and the historical context "increased importance of security in recent years."

[0397] The generated information is sent to the terminal, which displays it to the user in the following format:

[0398] Strengthen your home's security measures

[0399] Source: Security Experts

[0400] Meaning: Install security cameras and alarm systems to ensure safety.

[0401] Historical background: The importance of security has increased in recent years.

[0402] Similar sayings: "Prevention is the best defense" and "Safety is peace of mind."

[0403] The hardware and software used are as follows:

[0404] Hardware: Smartphones, smart glasses

[0405] software:

[0406] Natural language processing engine: BERT (Bidirectional Encoder Representations from Transformers)

[0407] Emotion Recognition Engine: Emotion Recognition API

[0408] Database: MySQL

[0409] Server side: Python framework (e.g. Django)

[0410] Cloud environment: AWS (Amazon Web Services)

[0411] This system can provide users with personalized encouragement and advice that is tailored to their emotions and situations in response to their security concerns and worries.

[0412] An example prompt is:

[0413] "Generate encouraging words for users who are worried about a home invasion. Users have been feeling very anxious about their home security lately."

[0414] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0415] Step 1:

[0416] Users access the system using a smartphone or smart glasses and input their security concerns or fears by text or voice. The input text or voice data is sent directly to the terminal.

[0417] Input: User text or voice input

[0418] Output: Text data or audio data

[0419] Step 2:

[0420] The voice data received by the terminal is converted into text data using a voice recognition means, and the converted input data is sent to the server as an HTTP POST request.

[0421] Input: Audio data

[0422] Output: Text data

[0423] Step 3:

[0424] The server analyzes the received text data, performs morphological analysis to extract keywords, and performs sentiment analysis to extract emotional tones. This analysis uses natural language processing technology and an emotion recognition engine.

[0425] Input: Text data

[0426] Output: Keywords, emotional tone

[0427] Step 4:

[0428] The emotion engine performs detailed analysis of the extracted emotional tones and keywords to identify the intensity and type of emotion, paying particular attention to the analysis of highly intense emotions.

[0429] Input: Keywords, Emotional Tone

[0430] Output: Emotion intensity and type

[0431] Step 5:

[0432] The server searches the database for relevant advice data based on the extracted keywords and emotional tones, as well as the intensity and type of emotions, using the query function of the database.

[0433] Input: Keywords, emotional tone, emotional intensity and type

[0434] Output: relevant advisory data

[0435] Step 6:

[0436] The server selects the most appropriate advice data from the search results. This selection is greatly influenced by the intensity and type of emotion. In order to select appropriate advice data, detailed analysis results from the emotion engine are required.

[0437] Input: Candidate advisory data

[0438] Output: Optimal advice data

[0439] Step 7:

[0440] The server generates detailed information about the meaning, source, historical context, and similar words associated with the selected advice data, using a generative AI model.

[0441] Input: Best advice data

[0442] Output: Related information (meaning, source, historical background, similar words)

[0443] Step 8:

[0444] The generated information is sent to the user's device as an HTTP response. The device receives the information and displays it to the user in the specified format.

[0445] Input: Related Information

[0446] Output: Display on the user's terminal

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

[0448] 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.

[0449] 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.

[0450] [Second embodiment]

[0451] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0452] 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.

[0453] 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).

[0454] 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.

[0455] 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.

[0456] 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).

[0457] 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.

[0458] 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.

[0459] 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.

[0460] 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.

[0461] 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.

[0462] 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."

[0463] As an embodiment of the present invention, we will specifically explain a system that provides encouraging words and advice appropriate to the user's situation and worries. This system performs a series of operations: accepting and analyzing text data entered by the user, and searching and generating appropriate advice data.

[0464] First, the user accesses the system using a terminal and inputs text about their experiences, worries, and other situations. The text data input by the user is in a format such as, "I recently made a big mistake and have lost confidence. What should I do?"

[0465] The device then sends this text data to a server, which uses natural language processing techniques to analyze the received text data and extract keywords and emotional tones. This analysis step involves morphological analysis and sentiment analysis to understand the user's situation.

[0466] Specifically, the server extracts keywords such as "failure" and "lose confidence" and identifies the user's emotions as negative states such as "disappointment" and "disappointment."

[0467] Next, the server searches for relevant advice data from a database based on the extracted keywords and emotional tone. The database contains advice from historical figures, myths, proverbs, etc. The server then searches for the most appropriate advice data from this database.

[0468] The system selects appropriate advice data from the search results and generates information to provide it to the user. The generated information includes not only the words of advice themselves, but also their meaning, source, historical background, and similar words. For example, if the server selects the proverb "Failure is the mother of success," it generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," and also includes a "Japanese proverb" as the source and "a lesson that has long been rooted in Japanese culture" as the historical background.

[0469] Finally, the generated information is sent to the terminal, which then displays it to the user. The displayed information is in the following format:

[0470] "Failure is the foundation of success"

[0471] Source: Japanese proverb

[0472] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0473] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0474] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0475] This allows users to receive appropriate encouragement and advice, providing emotional support and courage. This series of operations in the system realizes the provision of personalized information that is in line with the user's emotions and situation.

[0476] The processing flow will be explained below.

[0477] Step 1:

[0478] The user accesses the system through a terminal and inputs their situation and worries as text. For example, the user might input, "I recently made a big mistake and lost confidence. What should I do?"

[0479] Step 2:

[0480] The device sends the entered text data to the server using an HTTP POST request, with the data sent in JSON format.

[0481] Step 3:

[0482] The server receives and analyzes the received text data using natural language processing (NLP) techniques. Specifically, morphological analysis is used to extract keywords and sentiment analysis is used to identify the user's emotional tone.

[0483] Step 4:

[0484] The server searches the database based on the keywords and emotional tones extracted from the analysis, using SQL queries and search algorithms to find relevant advice data.

[0485] Step 5:

[0486] The server selects the most appropriate advice data from the search results, using an algorithm to select words and anecdotes that best fit the user's emotional tone and situation.

[0487] Step 6:

[0488] The server generates additional information (meaning, source, historical background, similar words) related to the selected advice data. For example, it generates the meaning and background information of the proverb "Failure is the mother of success."

[0489] Step 7:

[0490] The server generates the information and sends it to the device, again using an HTTP POST request, with the data sent in JSON format.

[0491] Step 8:

[0492] The device displays the received information to the user via the user interface of a web browser or mobile app. For example, the device displays the proverb "Failure is the mother of success" and related information.

[0493] Example 1

[0494] 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."

[0495] There is a problem that it is difficult for users to get appropriate advice and encouragement for their worries or situations. In particular, there is a lack of systems that provide customized advice based on emotions and specific keywords, so users cannot obtain the information they really need. To solve this problem, it is necessary to provide a system that can accurately analyze users' text data and provide optimal advice.

[0496] 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.

[0497] In this invention, the server includes means for accepting text data input by a user, means for analyzing the accepted text data and using natural language processing technology to extract keywords and emotional tones, means for searching for relevant advice data from information sources based on the extracted keywords and emotional tones, means for selecting optimal advice data from the search results and generating information to be provided to the user, and means for transmitting the generated information to the user's terminal, thereby enabling the user to receive personalized advice and encouragement tailored to their own concerns and situations in real time.

[0498] "Text data" is data in the form of a sentence entered by the user.

[0499] "Natural language processing technology" is a technology that allows computers to understand, analyze, and generate human language.

[0500] "Emotional tone" refers to the emotional trend or state extracted from within text.

[0501] "Keywords" are important words or phrases extracted from text data.

[0502] "Advice data" refers to advice or encouragement provided to the user in response to their concerns or situations.

[0503] "Source" refers to a database or other storage device where advisory data is stored.

[0504] A "server" is a computer system that analyzes text data, searches for advice data, and transmits the generated information.

[0505] A "user terminal" is a device used by a user to access the system and enter text data.

[0506] "Generated information" refers to information that is created based on advice data searched and selected by the server and is to be provided to the user.

[0507] As an embodiment of the present invention, the operation of a system that provides advice and words of encouragement appropriate to a user's situation and worries will be specifically described. Each component of the system and its operation will be described in detail below.

[0508] Hardware and software used

[0509] server

[0510] The server performs the main data processing and database lookup. The server is usually hosted in a cloud environment and has sufficient computing resources. The main software components include:

[0511] Natural language processing engine (morphological analysis engine): Examples include MeCab and Janome

[0512] Sentiment analysis libraries: Examples include Google Cloud Natural Language API and NLTK

[0513] Database Management System (DBMS): Examples include MySQL and PostgreSQL

[0514] Terminal

[0515] The devices used by users are devices such as PCs, smartphones, tablets, etc. These devices are capable of connecting to the Internet and are used to access the system's web applications and mobile applications.

[0516] Processing flow and data processing / calculation

[0517] 1. User text input

[0518] Users access the system using a terminal and input situations such as their own experiences and worries. For example, they might input, "I recently made a big mistake and lost confidence. What should I do?"

[0519] 2. Sending text data

[0520] The terminal sends the entered text data to the server, which converts the data into an appropriate format (e.g., JSON) and sends it as an HTTP POST request.

[0521] 3. Receiving and analyzing text data

[0522] The server parses the received text data. The parsing is done in two stages:

[0523] Morphological analysis: The text is segmented and keywords are extracted. For example, keywords such as "failure" and "lose confidence" are extracted.

[0524] Sentiment analysis: Extracting the emotional tone of text. For example, negative emotional states such as "disappointed" or "disappointed" can be identified.

[0525] 4. Searching for advisory data

[0526] The server searches for appropriate advice data from a database containing proverbs, famous quotes, historical anecdotes, etc. based on the analyzed keywords and emotional tone, and selects the most appropriate advice data from the searched data.

[0527] 5. Generating Advisory Information

[0528] The server generates more detailed information based on the selected advice data. The generated information includes the advice itself, its meaning, its source, historical background, and similar words. For example, for the proverb "Failure is the mother of success," the server generates the following information:

[0529] "Failure is the foundation of success"

[0530] Source: Japanese proverb

[0531] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0532] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0533] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0534] 6. Transmission and display of generated information

[0535] The server sends the generated information to the terminal, which displays the received information on the user's screen, allowing the user to read it and receive appropriate advice and encouragement.

[0536] Specific examples

[0537] If a user types, "I recently made a big mistake and it's ruined my confidence. What should I do?", the system will act as follows:

[0538] 1. The user uses the terminal to input text data.

[0539] 2. The device sends the input data to the server.

[0540] 3. The server analyzes the text data and extracts keywords and emotional tones.

[0541] 4. The server retrieves the relevant advisory data from the database.

[0542] 5. The server selects the most appropriate advice data and generates detailed information.

[0543] 6. The server sends the generated information to the terminal, which displays the information to the user.

[0544] Example prompts for generative AI models

[0545] "If a user types in, 'I recently made a big mistake and I've lost confidence. What should I do?', provide appropriate advice such as the proverb 'Failure is the mother of success,' along with its meaning, source, historical context, and similar phrases."

[0546] The above is a detailed description of the mode for carrying out the invention. The system contributes to obtaining emotional support by providing personalized advice and encouragement to users.

[0547] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0548] Step 1:

[0549] Users access the system using their own terminals and input the worries and situations they have experienced.

[0550] Input: Text data entered by the user (e.g., "I recently made a big mistake and it's really hurt my confidence. What should I do?").

[0551] Output: Text data entered into the user's terminal.

[0552] Specific Actions: A user opens a web or mobile application on the system and enters text into a text input field.

[0553] Step 2:

[0554] The terminal transmits the input text data to the server.

[0555] Input: Text data entered by the user into the terminal.

[0556] Output: The text data sent to the server (e.g., an HTTP POST request in JSON format).

[0557] Specific operation: The terminal converts the text data entered by the user into an appropriate format and sends an HTTP POST request to the server.

[0558] Step 3:

[0559] The server analyzes the received text data and extracts keywords and emotional tones.

[0560] Input: Text data sent from the device to the server.

[0561] Output: Analyzed keywords and emotional tone (e.g., "failure," "losing confidence," "disappointed," "disappointed").

[0562] Data processing: Segment the text and extract keywords using a morphological analysis engine (e.g., MeCab or Janome). Analyze emotional tone using a sentiment analysis library (e.g., Google Cloud Natural Language API or NLTK).

[0563] How it works: The server first uses a morphological analysis engine to segment the text, then uses a sentiment analysis library to identify the emotional tone.

[0564] Step 4:

[0565] The server retrieves relevant advisory data from information sources based on the extracted keywords and emotional tones.

[0566] Input: Extracted keywords and emotional tone.

[0567] Output: Search results with relevant advice (e.g., "Failure is the key to success").

[0568] Data computation: Query the database using a database management system (DBMS) based on keywords and emotional tone.

[0569] Specific operations: The server queries the database to obtain relevant advisory data.

[0570] Step 5:

[0571] The server selects the most suitable advice data from the search results and generates information to provide to the user.

[0572] Input: Advisory data obtained as search results.

[0573] Output: Generated detailed advice (e.g., the phrase "Failure is the mother of success," its meaning, origin, historical context, and similar phrases).

[0574] Data processing: Generate detailed meanings, sources, historical background, and similar words for the selected advice data.

[0575] Specific operation: The server analyzes the acquired advice data and generates detailed information based on its meaning and background information.

[0576] "Failure is the foundation of success"

[0577] Source: Japanese proverb

[0578] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0579] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0580] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0581] Step 6:

[0582] The server transmits the generated information to the user's terminal.

[0583] Input: The generated detailed advisory information.

[0584] Output: Advisory information sent from the server to the device (e.g., HTTP response in JSON format).

[0585] Specific operation: The server formats the generated information appropriately and sends it to the terminal as an HTTP response.

[0586] Step 7:

[0587] The terminal receives the transmitted information and displays it on the user's screen.

[0588] Input: Advisory information sent by the server.

[0589] Output: Detailed advisory information displayed on the user's screen.

[0590] Specific operation: The device analyzes the received information and displays it on the user's screen in an easy-to-read format.

[0591] These are the specific processing steps of the program for this system. Through this series of steps, users can receive personalized advice and encouragement in real time, tailored to their concerns.

[0592] (Application example 1)

[0593] 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."

[0594] This paper deals with a method for providing prompt and appropriate advice to users regarding troubles and difficulties they may encounter while using electronic payment services. Conventional systems lack personalized support tailored to the specific concerns and feelings of users, and this has resulted in the inability to fully alleviate users' anxieties and dissatisfaction.

[0595] 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.

[0596] In this invention, the server includes means for accepting text data entered by a user, means for analyzing the accepted text data and extracting keywords and emotional tones, means for searching a database for relevant advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results and generating information to provide to the user, means for transmitting the generated information to the user, and means for analyzing user troubles and emotions in relation to electronic payment services and providing appropriate advice. This makes it possible to quickly provide appropriate advice that is in line with the user's emotional tones in response to problems that arise while the user is using the electronic payment service.

[0597] "Text data" refers to character information entered by the user.

[0598] "Keywords" are important words or phrases extracted from text data.

[0599] "Emotional tone" indicates the emotional state or tendency that can be read from the user's input.

[0600] A "database" refers to a collection of data in which information such as proverbs and advice is stored.

[0601] "Advice data" is information including encouragement and solutions provided in response to the user's worries or situations.

[0602] "Electronic payment service" refers to a digital service for processing payments online or offline.

[0603] "Natural language processing technology" is a technology that enables computers to understand and analyze human language.

[0604] "Analysis" refers to the act of analyzing input text data to understand its structure and meaning.

[0605] "Generation" refers to the process of creating new information or data.

[0606] "Sending" refers to the act of delivering the generated information to the user's terminal.

[0607] "Search" refers to the act of locating appropriate information from a database based on specified criteria.

[0608] As an embodiment of the present invention, a system for providing appropriate advice to a user for solving their worries or difficulties will be specifically described. This system performs a series of operations to accept and analyze text data entered by the user, search for and generate appropriate advice data, and provide it to the user. The specific processing procedure will be described below.

[0609] System Configuration

[0610] Hardware and Software

[0611] Server: The central computer system for analysis and advice generation. It uses nltk and TextBlob natural language processing technologies.

[0612] User terminal: A device that allows users to input text data and receive appropriate advice. It works on smartphones or smart glasses.

[0613] Database: A storage system for storing advice data, such as quotes, words of encouragement, and other advice data.

[0614] Program processing overview

[0615] The user terminal sends the text data entered by the user to the server, which then analyzes the received text data and extracts keywords and emotional tones using natural language processing techniques.

[0616] Specifically, the server uses TextBlob to extract the emotional tone of the text data, and then performs morphological analysis to extract keywords. Through this process, it is possible to understand the user's concerns and situations.

[0617] The server then searches for relevant advice data from a database based on the extracted keywords and emotional tones. The database contains historical proverbs and words of encouragement, and the server finds the most suitable advice data.

[0618] The server then selects appropriate advice data from the search results, and generates information on the meaning of the word, the historical background, and similar words. This information is structured to be easy for users to understand and to provide encouragement and solutions.

[0619] Finally, the server transmits the generated advice data to the user terminal, which then displays the information to the user. The following is a specific example.

[0620] Specific examples

[0621] User Input: "I was recently scammed and it's really hurt my confidence. What should I do?"

[0622] System response:

[0623] "Failure is the foundation of success"

[0624] Source: Japanese proverb

[0625] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0626] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0627] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0628] Prompt Sentence Examples

[0629] "I was recently scammed and my confidence has been damaged. What should I do?"

[0630] Advice that encourages the person's heart, such as "Failure is the mother of success," "If you keep trying without being afraid of failure, you will eventually achieve success," and "Don't give up after one failure."

[0631] This invention enables users to quickly receive appropriate advice tailored to their emotional tone when encountering problems while using electronic payment services. This system reduces users' anxiety and frustration and provides quick and effective support.

[0632] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0633] Step 1:

[0634] User Input

[0635] The user inputs text data about their worries or difficulties into the terminal. The input data format is something like, "I was recently the victim of a scam and I've lost confidence. What should I do?"

[0636] Input: User's text data

[0637] Output: Text data received by the device

[0638] Step 2:

[0639] Sending text data

[0640] The terminal sends the received text data to the server. At this time, the data is encrypted before being sent.

[0641] Input: Text data entered into the terminal

[0642] Output: Encrypted text data sent to the server

[0643] Step 3:

[0644] Text data analysis

[0645] The server analyzes the received text data, extracts the emotional tone of the text data using TextBlob, and performs morphological analysis to extract keywords, such as "failure" and "lose confidence."

[0646] Input: Text data sent to the server

[0647] Output: Extracted emotional tones and keywords

[0648] Step 4:

[0649] Retrieving advice data from a database

[0650] The server searches the database for relevant advice data based on the extracted keywords and emotional tones, for example, searching for advice data such as "Failure is the mother of success" based on the keyword "failure."

[0651] Input: Extracted emotional tone and keywords

[0652] Output: Retrieved advisory data

[0653] Step 5:

[0654] Selection and generation of appropriate advisory data

[0655] The server selects appropriate advice data from the search results and generates words that reflect its meaning, historical context, and similar expressions. For example, the server generates the meaning of the proverb "Failure is the mother of success" as "If you keep trying without fear of failure, you will eventually achieve success."

[0656] Input: Retrieved advisory data

[0657] Output: Selected advisory data and its details

[0658] Step 6:

[0659] Sending advisory data

[0660] The server sends the generated advice data to the terminal, which receives the data and displays it to the user. The displayed information includes the advice words, meanings, sources, historical background, and similar words.

[0661] Input: Selected advisory data and its details

[0662] Output: Advisory data sent to the terminal

[0663] Step 7:

[0664] Providing advice to users

[0665] The terminal displays the received advice data to the user in the following format:

[0666] Input: Advisory data sent to the terminal

[0667] Output: Advisory data displayed to the user

[0668] "Failure is the foundation of success"

[0669] Source: Japanese proverb

[0670] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0671] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0672] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0673] 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.

[0674] As an embodiment of the present invention, a system for providing encouraging words and advice tailored to a user's situation and concerns will be specifically described. This system is characterized by incorporating a series of means for accepting, analyzing, searching, generating, and transmitting text data, as well as an emotion engine for recognizing the user's emotions.

[0675] First, the user accesses the system using a terminal and enters specific text about the problem or issue they would like to discuss. For example, the user might enter, "I recently made a big mistake and have lost confidence. What should I do?"

[0676] The device then sends this text data to the server using an HTTP POST request, with the data being sent to the server in JSON format.

[0677] The server analyzes the received text data and uses natural language processing techniques to extract keywords and emotional tones. Morphological analysis extracts keywords such as "failure" and "loss of confidence," while sentiment analysis identifies the user's emotions as "disappointment" and "disappointment."

[0678] The system also incorporates an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the user's input pixel by pixel to identify the intensity and type of emotion. If the emotion engine determines that the intensity of "disappointment" is high, it will take that information into account and proceed to the next step.

[0679] The server searches the database for relevant advice data based on the extracted keywords and emotional tone, for example, the server searches the database for advice related to failure and regaining self-confidence.

[0680] The server then selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine, and for a user who is feeling strong "disappointment," the most effective advice is selected.

[0681] The server generates the meaning, source, historical background, and similar words related to the selected advice data. For example, for the proverb "Failure is the mother of success," the server generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," and includes "Japanese proverbs" as the source and "lessons that have been deeply rooted in Japanese culture since ancient times" as the historical background.

[0682] The generated information is sent to the terminal, which displays it to the user in the following format:

[0683] "Failure is the foundation of success"

[0684] Source: Japanese proverb

[0685] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0686] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0687] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0688] This allows users to receive appropriate encouragement and advice, helping them regain their emotional support and courage.The entire system's operations realize personalized information provision that is tailored to the user's emotions and situation.

[0689] The processing flow will be explained below.

[0690] Step 1:

[0691] The user accesses the system through a terminal and inputs their situation and worries as text. For example, the user might input, "I recently made a big mistake and lost confidence. What should I do?"

[0692] Step 2:

[0693] The device sends the entered text data to the server using an HTTP POST request, and the data is sent to the server in JSON format.

[0694] Step 3:

[0695] The server analyzes the received text data. Using natural language processing (NLP) technology, it extracts keywords through morphological analysis and identifies the user's emotional tone through sentiment analysis. For example, keywords such as "failure" and "loss of confidence" are extracted, and the emotional tone is identified as "disappointment" or "disappointment."

[0696] Step 4:

[0697] The server uses an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the type and intensity of emotions on a pixel-by-pixel basis. For example, it determines that the intensity of "disappointment" is high based on the user's input.

[0698] Step 5:

[0699] The server searches the database for appropriate advice data based on the extracted keywords and the emotional tone recognized by the emotion engine, for example, advice data related to "failure" and "recovering self-confidence" are searched for in the database.

[0700] Step 6:

[0701] The server selects the most appropriate advice data from the search results. This selection also takes into account the emotional information recognized by the emotion engine. For example, if a user is feeling strong disappointment, the most effective advice will be selected.

[0702] Step 7:

[0703] The server generates information related to the selected advice data (meaning, source, historical background, similar words). For example, for the proverb "Failure is the mother of success," it generates meaning and background information. Specifically, it generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," the source "Japanese proverb," ​​and the historical background "a lesson that has been deeply rooted in Japanese culture since ancient times."

[0704] Step 8:

[0705] The server then sends the generated information to the device, again using an HTTP POST request, with the data sent to the device in JSON format.

[0706] Step 9:

[0707] The terminal displays the received information to the user through the user interface in the following format, for example:

[0708] "Failure is the foundation of success"

[0709] Source: Japanese proverb

[0710] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0711] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0712] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0713] In this way, users can receive appropriate encouragement and advice, and regain their emotional support and courage.

[0714] Example 2

[0715] 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."

[0716] Conventional user support systems sometimes fail to provide appropriate advice based on user input. Furthermore, they lack a mechanism for recognizing the user's emotions in detail and selecting appropriate advice, which means that the effective support desired by the user cannot be provided. This increases the likelihood of delays in resolving the user's concerns, leading to a lack of psychological support.

[0717] 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.

[0718] In this invention, the server includes means for accepting text data input by a user, means for transmitting the accepted text data to the server, means for analyzing the received text data and extracting keywords and emotional tones, means for analyzing the extracted emotional tones in more detail using an emotion engine, means for searching a database for related advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results, means for generating meanings, sources, historical backgrounds, and similar words related to the selected advice data, and means for transmitting the generated information to the user. This makes it possible to provide appropriate advice according to emotions analyzed in detail based on the user's worries and consultation contents.

[0719] "User" refers to an individual who uses this system and inputs their concerns or questions in text format.

[0720] "Terminal" refers to a device used by a user, and includes information processing devices such as smartphones, tablets, and personal computers.

[0721] "Text data" refers to character information entered by a user through a terminal, and is language data that includes worries and consultation details.

[0722] A "server" is a computer device that serves as the core of a system that analyzes received text data and processes and provides related information in conjunction with a database.

[0723] An "HTTP POST request" is one of the communication protocols used when sending data from a terminal to a server.

[0724] "JSON format" is a data exchange format for structuring text data for data transmission.

[0725] "Natural language processing technology" is a technology for analyzing human language and converting it into a form that a computer can understand, and includes morphological analysis and sentiment analysis.

[0726] "Morphological analysis" is a technique that breaks down text data into individual words or morphemes and analyzes their meaning and role.

[0727] "Emotional tone" is information that indicates the user's emotions contained in the text data, and refers to emotional attributes such as "disappointment" or "disappointment."

[0728] An "emotion engine" refers to software or algorithms that perform detailed analysis of emotions from text data entered by a user.

[0729] "Database" refers to a collection of information used by the server to look up relevant advisory data; it is a structured collection of data.

[0730] "Advice data" is information including solutions and words of encouragement provided to the user in response to the user's worries or inquiries.

[0731] "Generative AI model" refers to an artificial intelligence algorithm that generates meaning, sources, historical context, and similar words related to selected advisory data.

[0732] This invention relates to a system for providing encouraging words and advice tailored to a user's situation and concerns. This system incorporates a series of means for accepting, analyzing, searching, generating, and transmitting text data, as well as an emotion engine for recognizing the user's emotions.

[0733] First, the user accesses the system using a terminal and enters specific text about the problem or issue they want to discuss. For example, they might enter, "I recently made a big mistake and lost confidence. What should I do?" The terminal then sends this entered text data to the server. An HTTP POST request is used to send the data, and the data is sent to the server in JSON format.

[0734] The server analyzes the received text data and extracts keywords and emotional tones using natural language processing technology. Specifically, it uses a morphological analysis tool (e.g., MeCab) to analyze the text data and extract keywords such as "failure" and "loss of confidence." It also uses a sentiment analysis tool (e.g., Google Cloud Natural Language API) to identify the user's emotions as "disappointment" and "disappointment."

[0735] Additionally, an emotion engine is built in, which performs detailed pixel-by-pixel analysis of the user's input text to determine the emotion. This method identifies the intensity and type of emotion. For example, if the emotion "disappointment" is determined to be strong, this information is also incorporated into the next step.

[0736] The server searches the database for relevant advice data based on the extracted keywords and emotional tone. For example, it searches the database for advice related to failure or regaining confidence. This process uses SQL queries.

[0737] The server then selects the most appropriate advice data from the search results. This selection reflects the user's emotional information recognized by the emotion engine. For example, if a user is feeling strong disappointment, the most effective advice will be selected.

[0738] The server then uses a generative AI model (e.g., GPT-4) to generate meanings, sources, historical contexts, and similar words related to the selected advice data. For example, for the proverb "Failure is the mother of success," the server generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," including a "Japanese proverb" as the source and a "lesson deeply rooted in Japanese culture since ancient times" as the historical context.

[0739] The generated information is sent to the terminal for display to the user. The terminal visually displays this information to the user in the following format:

[0740] "Failure is the foundation of success"

[0741] Source: Japanese proverb

[0742] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0743] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0744] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0745] As a concrete example, let's consider the case where a user types, "I made a mistake at work and I just can't get over it. What should I do?" In this case, the device sends the input text to the server, which then analyzes and searches it after receiving it. Ultimately, the user is provided with appropriate advice, which helps them regain their emotional support and courage.

[0746] Examples of prompts using generative AI models include:

[0747] "I made a mistake at work recently and I just can't get over it. What words of encouragement do you have?"

[0748] The entire system's operations are designed to provide personalized information tailored to the user's emotions and situation.

[0749] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0750] Step 1:

[0751] The user accesses the system using a terminal and enters specific text about the problem or issue they would like to discuss. For example, the user might enter, "I recently made a big mistake and have lost confidence. What should I do?"

[0752] Input: The user enters the consultation content in the text input field.

[0753] Output: The entered text data is saved to the terminal.

[0754] Step 2:

[0755] The device sends the entered text data to the server using an HTTP POST request, and the data is sent to the server in JSON format.

[0756] Input: User-entered text data stored on the device.

[0757] Data processing: Convert text data into JSON format.

[0758] Output: Text data formatted in JSON format is sent to the server.

[0759] Step 3:

[0760] The server analyzes the received text data. Natural language processing technology is used to extract keywords and emotional tones from the text data. Specifically, a morphological analysis tool is used to extract keywords such as "failure" and "loss of confidence," and an emotion analysis tool is used to identify the emotional tones as "disappointment" and "disappointment."

[0761] Input: JSON formatted text data received by the server.

[0762] Data processing: Keywords are extracted using morphological analysis and emotional tones are extracted using sentiment analysis.

[0763] Output: Extracted keywords and emotional tones.

[0764] Step 4:

[0765] The server then uses an emotion engine to perform a detailed analysis of the extracted emotional tone. The emotion engine analyzes emotions pixel by pixel and identifies the intensity and type of emotion. For example, if the intensity of "disappointment" is determined to be high, that information is used in the next step.

[0766] Input: Extracted emotional tone.

[0767] Data computation: Detailed analysis of the intensity and type of emotions through the emotion engine.

[0768] Output: Detailed analyzed emotional information (e.g., high intensity of "disappointment") is obtained.

[0769] Step 5:

[0770] The server searches the database for relevant advice data based on the extracted keywords and the analyzed sentiment information, using SQL queries.

[0771] Input: Keywords and detailed analyzed sentiment information.

[0772] Data Calculation: Retrieving relevant advisory data from a database using SQL queries.

[0773] Output: Relevant advisory data is obtained.

[0774] Step 6:

[0775] The server selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine. For example, if a user is feeling strong "disappointment," the most effective advice will be selected.

[0776] Input: Search result advisory data and detailed analyzed sentiment information.

[0777] Data processing: Select the most appropriate advice data based on emotional information.

[0778] Output: Selected advisory data is obtained.

[0779] Step 7:

[0780] The server generates the meaning, source, historical context, and similar words related to the selected advice data. This generation uses a generative AI model to specifically describe each piece of information. For example, for the proverb "Failure is the mother of success," the server generates the meaning, source, historical context, and similar words.

[0781] Input: Selected advisory data.

[0782] Data Computing: Generative AI models are used to generate relevant information.

[0783] Output: Generated meaning, source, historical context, and similar words are provided.

[0784] Step 8:

[0785] The server sends the generated information to the terminal, which then displays it to the user. The display format is intended to provide the generated information to the user visually. For example, in addition to the proverb "Failure is the mother of success," the meaning, source, historical background, and similar expressions are displayed in detail.

[0786] Input: Generated information (meaning, source, historical context, similar words).

[0787] Output: Provided to the user as visually displayed information.

[0788] "Failure is the foundation of success"

[0789] Source: Japanese proverb

[0790] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0791] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0792] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0793] (Application example 2)

[0794] 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."

[0795] Conventional user assistance systems have difficulty providing appropriate advice based on the emotions and situations expressed by the text data entered by the user. This has resulted in problems such as users not receiving the encouragement or specific advice they need, and not being able to effectively obtain emotional support or a sense of security. Furthermore, due to a lack of means to convert voice input into text data or perform detailed analysis of emotions, improvements to the user experience have been required.

[0796] 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.

[0797] In this invention, the server includes means for accepting text data input by a user, means for analyzing the accepted text data and extracting keywords and emotional tones, means for searching a database for relevant advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results and generating information to be provided to the user, means for transmitting the generated information to the user, speech recognition means for accepting voice input from the user and converting it into text data, and means for analyzing the extracted keywords and emotional tones with an emotion engine and identifying the intensity and type of emotion, thereby making it possible to provide personalized information tailored to the user's emotions and situation.

[0798] "Text data input by the user" refers to character data used when the user inputs a question or request for advice to the system.

[0799] "Analysis" is the process of analyzing input text data and extracting necessary information.

[0800] A "keyword" is a key word or phrase that represents the content of the text data.

[0801] "Emotional tone" is an element that indicates the intensity and type of a user's emotion that can be read from text data.

[0802] "Searching" is the act of searching for information in a database to find the appropriate data.

[0803] "Advice data" is data used to provide appropriate advice to users regarding their problems or inquiries.

[0804] "Selection" is the act of choosing the best option from multiple candidates.

[0805] "Information generation" is the process of using data and algorithms to create new information or content.

[0806] "Sending" is the act of delivering the generated information or data to the user's terminal.

[0807] "Voice input" refers to the act of a user using voice to input instructions or consultation details into the system.

[0808] "Speech recognition" is a technology that converts voice data into text.

[0809] An "emotion engine" is an algorithm or system that determines the intensity and type of emotion from user input data.

[0810] "Intensity and type" refers to the degree of strength of an emotion and the type into which the emotion is classified, such as "joy," "sadness," or "anger."

[0811] As an embodiment of the present invention, a system for providing encouraging words and advice tailored to a user's security concerns will be specifically described. This system is characterized by incorporating a series of means for accepting, analyzing, searching, generating, and transmitting text and voice data, as well as an emotion engine for recognizing the user's emotions.

[0812] First, a user accesses the system using a smartphone or smart glasses and inputs their security-related anxieties or fears by text or voice. For example, the user might input, "Recently, I've been worried about someone breaking into my house and I'm scared," or they can speak a similar message by voice.

[0813] The device then sends the entered text or voice data to the server. In the case of voice data, the device uses a voice recognition means to convert the voice into text data, which is then sent to the server. An HTTP POST request is used for transmission, and the data is sent to the server in JSON format.

[0814] The server analyzes the received text data and uses natural language processing technology to extract keywords and emotional tones. Morphological analysis extracts keywords such as "worry" and "fear," and sentiment analysis identifies the user's emotions as "anxiety" and "fear."

[0815] Additionally, the system incorporates an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the user's input pixel by pixel to identify the intensity and type of emotion. If the emotion engine determines that the intensity of "fear" is high, it will proceed to the next step, taking that information into account.

[0816] The server searches the database for relevant advice data based on the extracted keywords and emotional tone, for example, the server searches the database for advice related to security concerns and providing a sense of security.

[0817] The server then selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine, and for a user who is feeling strong "fear," the most effective advice is selected.

[0818] The server generates the meaning, source, historical context, and similar words related to the selected advice data. For example, for the advice "Strengthen home security measures," the server generates the meaning "Install security cameras and alarm systems to ensure safety," including the source "security experts" and the historical context "increased importance of security in recent years."

[0819] The generated information is sent to the terminal, which displays it to the user in the following format:

[0820] Strengthen your home's security measures

[0821] Source: Security Experts

[0822] Meaning: Install security cameras and alarm systems to ensure safety.

[0823] Historical background: The importance of security has increased in recent years.

[0824] Similar sayings: "Prevention is the best defense" and "Safety is peace of mind."

[0825] The hardware and software used are as follows:

[0826] Hardware: Smartphones, smart glasses

[0827] software:

[0828] Natural language processing engine: BERT (Bidirectional Encoder Representations from Transformers)

[0829] Emotion Recognition Engine: Emotion Recognition API

[0830] Database: MySQL

[0831] Server side: Python framework (e.g. Django)

[0832] Cloud environment: AWS (Amazon Web Services)

[0833] This system can provide users with personalized encouragement and advice that is tailored to their emotions and situations in response to their security concerns and worries.

[0834] An example prompt is:

[0835] "Generate encouraging words for users who are worried about a home invasion. Users have been feeling very anxious about their home security lately."

[0836] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0837] Step 1:

[0838] Users access the system using a smartphone or smart glasses and input their security concerns or fears by text or voice. The input text or voice data is sent directly to the terminal.

[0839] Input: User text or voice input

[0840] Output: Text data or audio data

[0841] Step 2:

[0842] The voice data received by the terminal is converted into text data using a voice recognition means, and the converted input data is sent to the server as an HTTP POST request.

[0843] Input: Audio data

[0844] Output: Text data

[0845] Step 3:

[0846] The server analyzes the received text data, performs morphological analysis to extract keywords, and performs sentiment analysis to extract emotional tones. This analysis uses natural language processing technology and an emotion recognition engine.

[0847] Input: Text data

[0848] Output: Keywords, emotional tone

[0849] Step 4:

[0850] The emotion engine performs detailed analysis of the extracted emotional tones and keywords to identify the intensity and type of emotion, paying particular attention to the analysis of highly intense emotions.

[0851] Input: Keywords, Emotional Tone

[0852] Output: Emotion intensity and type

[0853] Step 5:

[0854] The server searches the database for relevant advice data based on the extracted keywords and emotional tones, as well as the intensity and type of emotions, using the query function of the database.

[0855] Input: Keywords, emotional tone, emotional intensity and type

[0856] Output: relevant advisory data

[0857] Step 6:

[0858] The server selects the most appropriate advice data from the search results. This selection is greatly influenced by the intensity and type of emotion. In order to select appropriate advice data, detailed analysis results from the emotion engine are required.

[0859] Input: Candidate advisory data

[0860] Output: Optimal advice data

[0861] Step 7:

[0862] The server generates detailed information about the meaning, source, historical context, and similar words associated with the selected advice data, using a generative AI model.

[0863] Input: Best advice data

[0864] Output: Related information (meaning, source, historical background, similar words)

[0865] Step 8:

[0866] The generated information is sent to the user's device as an HTTP response. The device receives the information and displays it to the user in the specified format.

[0867] Input: Related Information

[0868] Output: Display on the user's terminal

[0869] 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.

[0870] 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.

[0871] 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.

[0872] [Third embodiment]

[0873] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0874] 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.

[0875] 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).

[0876] 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.

[0877] 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.

[0878] 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).

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] 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.

[0884] 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."

[0885] As an embodiment of the present invention, we will specifically explain a system that provides encouraging words and advice appropriate to the user's situation and worries. This system performs a series of operations: accepting and analyzing text data entered by the user, and searching and generating appropriate advice data.

[0886] First, the user accesses the system using a terminal and inputs text about their experiences, worries, and other situations. The text data input by the user is in a format such as, "I recently made a big mistake and have lost confidence. What should I do?"

[0887] The device then sends this text data to a server, which uses natural language processing techniques to analyze the received text data and extract keywords and emotional tones. This analysis step involves morphological analysis and sentiment analysis to understand the user's situation.

[0888] Specifically, the server extracts keywords such as "failure" and "lose confidence" and identifies the user's emotions as negative states such as "disappointment" and "disappointment."

[0889] Next, the server searches for relevant advice data from a database based on the extracted keywords and emotional tone. The database contains advice from historical figures, myths, proverbs, etc. The server then searches for the most appropriate advice data from this database.

[0890] The system selects appropriate advice data from the search results and generates information to provide it to the user. The generated information includes not only the words of advice themselves, but also their meaning, source, historical background, and similar words. For example, if the server selects the proverb "Failure is the mother of success," it generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," and also includes a "Japanese proverb" as the source and "a lesson that has long been rooted in Japanese culture" as the historical background.

[0891] Finally, the generated information is sent to the terminal, which then displays it to the user. The displayed information is in the following format:

[0892] "Failure is the foundation of success"

[0893] Source: Japanese proverb

[0894] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0895] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0896] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0897] This allows users to receive appropriate encouragement and advice, providing emotional support and courage. This series of operations in the system realizes the provision of personalized information that is in line with the user's emotions and situation.

[0898] The processing flow will be explained below.

[0899] Step 1:

[0900] The user accesses the system through a terminal and inputs their situation and worries as text. For example, the user might input, "I recently made a big mistake and lost confidence. What should I do?"

[0901] Step 2:

[0902] The device sends the entered text data to the server using an HTTP POST request, with the data sent in JSON format.

[0903] Step 3:

[0904] The server receives and analyzes the received text data using natural language processing (NLP) techniques. Specifically, morphological analysis is used to extract keywords and sentiment analysis is used to identify the user's emotional tone.

[0905] Step 4:

[0906] The server searches the database based on the keywords and emotional tones extracted from the analysis, using SQL queries and search algorithms to find relevant advice data.

[0907] Step 5:

[0908] The server selects the most appropriate advice data from the search results, using an algorithm to select words and anecdotes that best fit the user's emotional tone and situation.

[0909] Step 6:

[0910] The server generates additional information (meaning, source, historical background, similar words) related to the selected advice data. For example, it generates the meaning and background information of the proverb "Failure is the mother of success."

[0911] Step 7:

[0912] The server generates the information and sends it to the device, again using an HTTP POST request, with the data sent in JSON format.

[0913] Step 8:

[0914] The device displays the received information to the user via the user interface of a web browser or mobile app. For example, the device displays the proverb "Failure is the mother of success" and related information.

[0915] Example 1

[0916] 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."

[0917] There is a problem that it is difficult for users to get appropriate advice and encouragement for their worries or situations. In particular, there is a lack of systems that provide customized advice based on emotions and specific keywords, so users cannot obtain the information they really need. To solve this problem, it is necessary to provide a system that can accurately analyze users' text data and provide optimal advice.

[0918] 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.

[0919] In this invention, the server includes means for accepting text data input by a user, means for analyzing the accepted text data and using natural language processing technology to extract keywords and emotional tones, means for searching for relevant advice data from information sources based on the extracted keywords and emotional tones, means for selecting optimal advice data from the search results and generating information to be provided to the user, and means for transmitting the generated information to the user's terminal, thereby enabling the user to receive personalized advice and encouragement tailored to their own concerns and situations in real time.

[0920] "Text data" is data in the form of a sentence entered by the user.

[0921] "Natural language processing technology" is a technology that allows computers to understand, analyze, and generate human language.

[0922] "Emotional tone" refers to the emotional trend or state extracted from within text.

[0923] "Keywords" are important words or phrases extracted from text data.

[0924] "Advice data" refers to advice or encouragement provided to the user in response to their concerns or situations.

[0925] "Source" refers to a database or other storage device where advisory data is stored.

[0926] A "server" is a computer system that analyzes text data, searches for advice data, and transmits the generated information.

[0927] A "user terminal" is a device used by a user to access the system and enter text data.

[0928] "Generated information" refers to information that is created based on advice data searched and selected by the server and is to be provided to the user.

[0929] As an embodiment of the present invention, the operation of a system that provides advice and words of encouragement appropriate to a user's situation and worries will be specifically described. Each component of the system and its operation will be described in detail below.

[0930] Hardware and software used

[0931] server

[0932] The server performs the main data processing and database lookup. The server is usually hosted in a cloud environment and has sufficient computing resources. The main software components include:

[0933] Natural language processing engine (morphological analysis engine): Examples include MeCab and Janome

[0934] Sentiment analysis libraries: Examples include Google Cloud Natural Language API and NLTK

[0935] Database Management System (DBMS): Examples include MySQL and PostgreSQL

[0936] Terminal

[0937] The devices used by users are devices such as PCs, smartphones, tablets, etc. These devices are capable of connecting to the Internet and are used to access the system's web applications and mobile applications.

[0938] Processing flow and data processing / calculation

[0939] 1. User text input

[0940] Users access the system using a terminal and input situations such as their own experiences and worries. For example, they might input, "I recently made a big mistake and lost confidence. What should I do?"

[0941] 2. Sending text data

[0942] The terminal sends the entered text data to the server, which converts the data into an appropriate format (e.g., JSON) and sends it as an HTTP POST request.

[0943] 3. Receiving and analyzing text data

[0944] The server parses the received text data. The parsing is done in two stages:

[0945] Morphological analysis: The text is segmented and keywords are extracted. For example, keywords such as "failure" and "lose confidence" are extracted.

[0946] Sentiment analysis: Extracting the emotional tone of text. For example, negative emotional states such as "disappointed" or "disappointed" can be identified.

[0947] 4. Searching for advisory data

[0948] The server searches for appropriate advice data from a database containing proverbs, famous quotes, historical anecdotes, etc. based on the analyzed keywords and emotional tone, and selects the most appropriate advice data from the searched data.

[0949] 5. Generating Advisory Information

[0950] The server generates more detailed information based on the selected advice data. The generated information includes the advice itself, its meaning, its source, historical background, and similar words. For example, for the proverb "Failure is the mother of success," the server generates the following information:

[0951] "Failure is the foundation of success"

[0952] Source: Japanese proverb

[0953] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[0954] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[0955] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[0956] 6. Transmission and display of generated information

[0957] The server sends the generated information to the terminal, which displays the received information on the user's screen, allowing the user to read it and receive appropriate advice and encouragement.

[0958] Specific examples

[0959] If a user types, "I recently made a big mistake and it's ruined my confidence. What should I do?", the system will act as follows:

[0960] 1. The user uses the terminal to input text data.

[0961] 2. The device sends the input data to the server.

[0962] 3. The server analyzes the text data and extracts keywords and emotional tones.

[0963] 4. The server retrieves the relevant advisory data from the database.

[0964] 5. The server selects the most appropriate advice data and generates detailed information.

[0965] 6. The server sends the generated information to the terminal, which displays the information to the user.

[0966] Example prompts for generative AI models

[0967] "If a user types in, 'I recently made a big mistake and I've lost confidence. What should I do?', provide appropriate advice such as the proverb 'Failure is the mother of success,' along with its meaning, source, historical context, and similar phrases."

[0968] The above is a detailed description of the mode for carrying out the invention. The system contributes to obtaining emotional support by providing personalized advice and encouragement to users.

[0969] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0970] Step 1:

[0971] Users access the system using their own terminals and input the worries and situations they have experienced.

[0972] Input: Text data entered by the user (e.g., "I recently made a big mistake and it's really hurt my confidence. What should I do?").

[0973] Output: Text data entered into the user's terminal.

[0974] Specific Actions: A user opens a web or mobile application on the system and enters text into a text input field.

[0975] Step 2:

[0976] The terminal transmits the input text data to the server.

[0977] Input: Text data entered by the user into the terminal.

[0978] Output: The text data sent to the server (e.g., an HTTP POST request in JSON format).

[0979] Specific operation: The terminal converts the text data entered by the user into an appropriate format and sends an HTTP POST request to the server.

[0980] Step 3:

[0981] The server analyzes the received text data and extracts keywords and emotional tones.

[0982] Input: Text data sent from the device to the server.

[0983] Output: Analyzed keywords and emotional tone (e.g., "failure," "losing confidence," "disappointed," "disappointed").

[0984] Data processing: Segment the text and extract keywords using a morphological analysis engine (e.g., MeCab or Janome). Analyze emotional tone using a sentiment analysis library (e.g., Google Cloud Natural Language API or NLTK).

[0985] How it works: The server first uses a morphological analysis engine to segment the text, then uses a sentiment analysis library to identify the emotional tone.

[0986] Step 4:

[0987] The server retrieves relevant advisory data from information sources based on the extracted keywords and emotional tones.

[0988] Input: Extracted keywords and emotional tone.

[0989] Output: Search results with relevant advice (e.g., "Failure is the key to success").

[0990] Data computation: Query the database using a database management system (DBMS) based on keywords and emotional tone.

[0991] Specific operations: The server queries the database to obtain relevant advisory data.

[0992] Step 5:

[0993] The server selects the most suitable advice data from the search results and generates information to provide to the user.

[0994] Input: Advisory data obtained as search results.

[0995] Output: Generated detailed advice (e.g., the phrase "Failure is the mother of success," its meaning, origin, historical context, and similar phrases).

[0996] Data processing: Generate detailed meanings, sources, historical background, and similar words for the selected advice data.

[0997] Specific operation: The server analyzes the acquired advice data and generates detailed information based on its meaning and background information.

[0998] "Failure is the foundation of success"

[0999] Source: Japanese proverb

[1000] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1001] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1002] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1003] Step 6:

[1004] The server transmits the generated information to the user's terminal.

[1005] Input: The generated detailed advisory information.

[1006] Output: Advisory information sent from the server to the device (e.g., HTTP response in JSON format).

[1007] Specific operation: The server formats the generated information appropriately and sends it to the terminal as an HTTP response.

[1008] Step 7:

[1009] The terminal receives the transmitted information and displays it on the user's screen.

[1010] Input: Advisory information sent by the server.

[1011] Output: Detailed advisory information displayed on the user's screen.

[1012] Specific operation: The device analyzes the received information and displays it on the user's screen in an easy-to-read format.

[1013] These are the specific processing steps of the program for this system. Through this series of steps, users can receive personalized advice and encouragement in real time, tailored to their concerns.

[1014] (Application example 1)

[1015] 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."

[1016] This paper deals with a method for providing prompt and appropriate advice to users regarding troubles and difficulties they may encounter while using electronic payment services. Conventional systems lack personalized support tailored to the specific concerns and feelings of users, and this has resulted in the inability to fully alleviate users' anxieties and dissatisfaction.

[1017] 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.

[1018] In this invention, the server includes means for accepting text data entered by a user, means for analyzing the accepted text data and extracting keywords and emotional tones, means for searching a database for relevant advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results and generating information to provide to the user, means for transmitting the generated information to the user, and means for analyzing user troubles and emotions in relation to electronic payment services and providing appropriate advice. This makes it possible to quickly provide appropriate advice that is in line with the user's emotional tones in response to problems that arise while the user is using the electronic payment service.

[1019] "Text data" refers to character information entered by the user.

[1020] "Keywords" are important words or phrases extracted from text data.

[1021] "Emotional tone" indicates the emotional state or tendency that can be read from the user's input.

[1022] A "database" refers to a collection of data in which information such as proverbs and advice is stored.

[1023] "Advice data" is information including encouragement and solutions provided in response to the user's worries or situations.

[1024] "Electronic payment service" refers to a digital service for processing payments online or offline.

[1025] "Natural language processing technology" is a technology that enables computers to understand and analyze human language.

[1026] "Analysis" refers to the act of analyzing input text data to understand its structure and meaning.

[1027] "Generation" refers to the process of creating new information or data.

[1028] "Sending" refers to the act of delivering the generated information to the user's terminal.

[1029] "Search" refers to the act of locating appropriate information from a database based on specified criteria.

[1030] As an embodiment of the present invention, a system for providing appropriate advice to a user for solving their worries or difficulties will be specifically described. This system performs a series of operations to accept and analyze text data entered by the user, search for and generate appropriate advice data, and provide it to the user. The specific processing procedure will be described below.

[1031] System Configuration

[1032] Hardware and Software

[1033] Server: The central computer system for analysis and advice generation. It uses nltk and TextBlob natural language processing technologies.

[1034] User terminal: A device that allows users to input text data and receive appropriate advice. It works on smartphones or smart glasses.

[1035] Database: A storage system for storing advice data, such as quotes, words of encouragement, and other advice data.

[1036] Program processing overview

[1037] The user terminal sends the text data entered by the user to the server, which then analyzes the received text data and extracts keywords and emotional tones using natural language processing techniques.

[1038] Specifically, the server uses TextBlob to extract the emotional tone of the text data, and then performs morphological analysis to extract keywords. Through this process, it is possible to understand the user's concerns and situations.

[1039] The server then searches for relevant advice data from a database based on the extracted keywords and emotional tones. The database contains historical proverbs and words of encouragement, and the server finds the most suitable advice data.

[1040] The server then selects appropriate advice data from the search results, and generates information on the meaning of the word, the historical background, and similar words. This information is structured to be easy for users to understand and to provide encouragement and solutions.

[1041] Finally, the server transmits the generated advice data to the user terminal, which then displays the information to the user. The following is a specific example.

[1042] Specific examples

[1043] User Input: "I was recently scammed and it's really hurt my confidence. What should I do?"

[1044] System response:

[1045] "Failure is the foundation of success"

[1046] Source: Japanese proverb

[1047] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1048] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1049] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1050] Prompt Sentence Examples

[1051] "I was recently scammed and my confidence has been damaged. What should I do?"

[1052] Advice that encourages the person's heart, such as "Failure is the mother of success," "If you keep trying without being afraid of failure, you will eventually achieve success," and "Don't give up after one failure."

[1053] This invention enables users to quickly receive appropriate advice tailored to their emotional tone when encountering problems while using electronic payment services. This system reduces users' anxiety and frustration and provides quick and effective support.

[1054] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1055] Step 1:

[1056] User Input

[1057] The user inputs text data about their worries or difficulties into the terminal. The input data format is something like, "I was recently the victim of a scam and I've lost confidence. What should I do?"

[1058] Input: User's text data

[1059] Output: Text data received by the device

[1060] Step 2:

[1061] Sending text data

[1062] The terminal sends the received text data to the server. At this time, the data is encrypted before being sent.

[1063] Input: Text data entered into the terminal

[1064] Output: Encrypted text data sent to the server

[1065] Step 3:

[1066] Text data analysis

[1067] The server analyzes the received text data, extracts the emotional tone of the text data using TextBlob, and performs morphological analysis to extract keywords, such as "failure" and "lose confidence."

[1068] Input: Text data sent to the server

[1069] Output: Extracted emotional tones and keywords

[1070] Step 4:

[1071] Retrieving advice data from a database

[1072] The server searches the database for relevant advice data based on the extracted keywords and emotional tones, for example, searching for advice data such as "Failure is the mother of success" based on the keyword "failure."

[1073] Input: Extracted emotional tone and keywords

[1074] Output: Retrieved advisory data

[1075] Step 5:

[1076] Selection and generation of appropriate advisory data

[1077] The server selects appropriate advice data from the search results and generates words that reflect its meaning, historical context, and similar expressions. For example, the server generates the meaning of the proverb "Failure is the mother of success" as "If you keep trying without fear of failure, you will eventually achieve success."

[1078] Input: Retrieved advisory data

[1079] Output: Selected advisory data and its details

[1080] Step 6:

[1081] Sending advisory data

[1082] The server sends the generated advice data to the terminal, which receives the data and displays it to the user. The displayed information includes the advice words, meanings, sources, historical background, and similar words.

[1083] Input: Selected advisory data and its details

[1084] Output: Advisory data sent to the terminal

[1085] Step 7:

[1086] Providing advice to users

[1087] The terminal displays the received advice data to the user in the following format:

[1088] Input: Advisory data sent to the terminal

[1089] Output: Advisory data displayed to the user

[1090] "Failure is the foundation of success"

[1091] Source: Japanese proverb

[1092] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1093] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1094] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1095] 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.

[1096] As an embodiment of the present invention, a system for providing encouraging words and advice tailored to a user's situation and concerns will be specifically described. This system is characterized by incorporating a series of means for accepting, analyzing, searching, generating, and transmitting text data, as well as an emotion engine for recognizing the user's emotions.

[1097] First, the user accesses the system using a terminal and enters specific text about the problem or issue they would like to discuss. For example, the user might enter, "I recently made a big mistake and have lost confidence. What should I do?"

[1098] The device then sends this text data to the server using an HTTP POST request, with the data being sent to the server in JSON format.

[1099] The server analyzes the received text data and uses natural language processing techniques to extract keywords and emotional tones. Morphological analysis extracts keywords such as "failure" and "loss of confidence," while sentiment analysis identifies the user's emotions as "disappointment" and "disappointment."

[1100] The system also incorporates an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the user's input pixel by pixel to identify the intensity and type of emotion. If the emotion engine determines that the intensity of "disappointment" is high, it will take that information into account and proceed to the next step.

[1101] The server searches the database for relevant advice data based on the extracted keywords and emotional tone, for example, the server searches the database for advice related to failure and regaining self-confidence.

[1102] The server then selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine, and for a user who is feeling strong "disappointment," the most effective advice is selected.

[1103] The server generates the meaning, source, historical background, and similar words related to the selected advice data. For example, for the proverb "Failure is the mother of success," the server generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," and includes "Japanese proverbs" as the source and "lessons that have been deeply rooted in Japanese culture since ancient times" as the historical background.

[1104] The generated information is sent to the terminal, which displays it to the user in the following format:

[1105] "Failure is the foundation of success"

[1106] Source: Japanese proverb

[1107] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1108] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1109] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1110] This allows users to receive appropriate encouragement and advice, helping them regain their emotional support and courage.The entire system's operations realize personalized information provision that is tailored to the user's emotions and situation.

[1111] The processing flow will be explained below.

[1112] Step 1:

[1113] The user accesses the system through a terminal and inputs their situation and worries as text. For example, the user might input, "I recently made a big mistake and lost confidence. What should I do?"

[1114] Step 2:

[1115] The device sends the entered text data to the server using an HTTP POST request, and the data is sent to the server in JSON format.

[1116] Step 3:

[1117] The server analyzes the received text data. Using natural language processing (NLP) technology, it extracts keywords through morphological analysis and identifies the user's emotional tone through sentiment analysis. For example, keywords such as "failure" and "loss of confidence" are extracted, and the emotional tone is identified as "disappointment" or "disappointment."

[1118] Step 4:

[1119] The server uses an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the type and intensity of emotions on a pixel-by-pixel basis. For example, it determines that the intensity of "disappointment" is high based on the user's input.

[1120] Step 5:

[1121] The server searches the database for appropriate advice data based on the extracted keywords and the emotional tone recognized by the emotion engine, for example, advice data related to "failure" and "recovering self-confidence" are searched for in the database.

[1122] Step 6:

[1123] The server selects the most appropriate advice data from the search results. This selection also takes into account the emotional information recognized by the emotion engine. For example, if a user is feeling strong disappointment, the most effective advice will be selected.

[1124] Step 7:

[1125] The server generates information related to the selected advice data (meaning, source, historical background, similar words). For example, for the proverb "Failure is the mother of success," it generates meaning and background information. Specifically, it generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," the source "Japanese proverb," ​​and the historical background "a lesson that has been deeply rooted in Japanese culture since ancient times."

[1126] Step 8:

[1127] The server then sends the generated information to the device, again using an HTTP POST request, with the data sent to the device in JSON format.

[1128] Step 9:

[1129] The terminal displays the received information to the user through the user interface in the following format, for example:

[1130] "Failure is the foundation of success"

[1131] Source: Japanese proverb

[1132] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1133] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1134] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1135] In this way, users can receive appropriate encouragement and advice, and regain their emotional support and courage.

[1136] Example 2

[1137] 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."

[1138] Conventional user support systems sometimes fail to provide appropriate advice based on user input. Furthermore, they lack a mechanism for recognizing the user's emotions in detail and selecting appropriate advice, which means that the effective support desired by the user cannot be provided. This increases the likelihood of delays in resolving the user's concerns, leading to a lack of psychological support.

[1139] 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.

[1140] In this invention, the server includes means for accepting text data input by a user, means for transmitting the accepted text data to the server, means for analyzing the received text data and extracting keywords and emotional tones, means for analyzing the extracted emotional tones in more detail using an emotion engine, means for searching a database for related advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results, means for generating meanings, sources, historical backgrounds, and similar words related to the selected advice data, and means for transmitting the generated information to the user. This makes it possible to provide appropriate advice according to emotions analyzed in detail based on the user's worries and consultation contents.

[1141] "User" refers to an individual who uses this system and inputs their concerns or questions in text format.

[1142] "Terminal" refers to a device used by a user, and includes information processing devices such as smartphones, tablets, and personal computers.

[1143] "Text data" refers to character information entered by a user through a terminal, and is language data that includes worries and consultation details.

[1144] A "server" is a computer device that serves as the core of a system that analyzes received text data and processes and provides related information in conjunction with a database.

[1145] An "HTTP POST request" is one of the communication protocols used when sending data from a terminal to a server.

[1146] "JSON format" is a data exchange format for structuring text data for data transmission.

[1147] "Natural language processing technology" is a technology for analyzing human language and converting it into a form that a computer can understand, and includes morphological analysis and sentiment analysis.

[1148] "Morphological analysis" is a technique that breaks down text data into individual words or morphemes and analyzes their meaning and role.

[1149] "Emotional tone" is information that indicates the user's emotions contained in the text data, and refers to emotional attributes such as "disappointment" or "disappointment."

[1150] An "emotion engine" refers to software or algorithms that perform detailed analysis of emotions from text data entered by a user.

[1151] "Database" refers to a collection of information used by the server to look up relevant advisory data; it is a structured collection of data.

[1152] "Advice data" is information including solutions and words of encouragement provided to the user in response to the user's worries or inquiries.

[1153] "Generative AI model" refers to an artificial intelligence algorithm that generates meaning, sources, historical context, and similar words related to selected advisory data.

[1154] This invention relates to a system for providing encouraging words and advice tailored to a user's situation and concerns. This system incorporates a series of means for accepting, analyzing, searching, generating, and transmitting text data, as well as an emotion engine for recognizing the user's emotions.

[1155] First, the user accesses the system using a terminal and enters specific text about the problem or issue they want to discuss. For example, they might enter, "I recently made a big mistake and lost confidence. What should I do?" The terminal then sends this entered text data to the server. An HTTP POST request is used to send the data, and the data is sent to the server in JSON format.

[1156] The server analyzes the received text data and extracts keywords and emotional tones using natural language processing technology. Specifically, it uses a morphological analysis tool (e.g., MeCab) to analyze the text data and extract keywords such as "failure" and "loss of confidence." It also uses a sentiment analysis tool (e.g., Google Cloud Natural Language API) to identify the user's emotions as "disappointment" and "disappointment."

[1157] Additionally, an emotion engine is built in, which performs detailed pixel-by-pixel analysis of the user's input text to determine the emotion. This method identifies the intensity and type of emotion. For example, if the emotion "disappointment" is determined to be strong, this information is also incorporated into the next step.

[1158] The server searches the database for relevant advice data based on the extracted keywords and emotional tone. For example, it searches the database for advice related to failure or regaining confidence. This process uses SQL queries.

[1159] The server then selects the most appropriate advice data from the search results. This selection reflects the user's emotional information recognized by the emotion engine. For example, if a user is feeling strong disappointment, the most effective advice will be selected.

[1160] The server then uses a generative AI model (e.g., GPT-4) to generate meanings, sources, historical contexts, and similar words related to the selected advice data. For example, for the proverb "Failure is the mother of success," the server generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," including a "Japanese proverb" as the source and a "lesson deeply rooted in Japanese culture since ancient times" as the historical context.

[1161] The generated information is sent to the terminal for display to the user. The terminal visually displays this information to the user in the following format:

[1162] "Failure is the foundation of success"

[1163] Source: Japanese proverb

[1164] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1165] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1166] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1167] As a concrete example, let's consider the case where a user types, "I made a mistake at work and I just can't get over it. What should I do?" In this case, the device sends the input text to the server, which then analyzes and searches it after receiving it. Ultimately, the user is provided with appropriate advice, which helps them regain their emotional support and courage.

[1168] Examples of prompts using generative AI models include:

[1169] "I made a mistake at work recently and I just can't get over it. What words of encouragement do you have?"

[1170] The entire system's operations are designed to provide personalized information tailored to the user's emotions and situation.

[1171] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1172] Step 1:

[1173] The user accesses the system using a terminal and enters specific text about the problem or issue they would like to discuss. For example, the user might enter, "I recently made a big mistake and have lost confidence. What should I do?"

[1174] Input: The user enters the consultation content in the text input field.

[1175] Output: The entered text data is saved to the terminal.

[1176] Step 2:

[1177] The device sends the entered text data to the server using an HTTP POST request, and the data is sent to the server in JSON format.

[1178] Input: User-entered text data stored on the device.

[1179] Data processing: Convert text data into JSON format.

[1180] Output: Text data formatted in JSON format is sent to the server.

[1181] Step 3:

[1182] The server analyzes the received text data. Natural language processing technology is used to extract keywords and emotional tones from the text data. Specifically, a morphological analysis tool is used to extract keywords such as "failure" and "loss of confidence," and an emotion analysis tool is used to identify the emotional tones as "disappointment" and "disappointment."

[1183] Input: JSON formatted text data received by the server.

[1184] Data processing: Keywords are extracted using morphological analysis and emotional tones are extracted using sentiment analysis.

[1185] Output: Extracted keywords and emotional tones.

[1186] Step 4:

[1187] The server then uses an emotion engine to perform a detailed analysis of the extracted emotional tone. The emotion engine analyzes emotions pixel by pixel and identifies the intensity and type of emotion. For example, if the intensity of "disappointment" is determined to be high, that information is used in the next step.

[1188] Input: Extracted emotional tone.

[1189] Data computation: Detailed analysis of the intensity and type of emotions through the emotion engine.

[1190] Output: Detailed analyzed emotional information (e.g., high intensity of "disappointment") is obtained.

[1191] Step 5:

[1192] The server searches the database for relevant advice data based on the extracted keywords and the analyzed sentiment information, using SQL queries.

[1193] Input: Keywords and detailed analyzed sentiment information.

[1194] Data Calculation: Retrieving relevant advisory data from a database using SQL queries.

[1195] Output: Relevant advisory data is obtained.

[1196] Step 6:

[1197] The server selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine. For example, if a user is feeling strong "disappointment," the most effective advice will be selected.

[1198] Input: Search result advisory data and detailed analyzed sentiment information.

[1199] Data processing: Select the most appropriate advice data based on emotional information.

[1200] Output: Selected advisory data is obtained.

[1201] Step 7:

[1202] The server generates the meaning, source, historical context, and similar words related to the selected advice data. This generation uses a generative AI model to specifically describe each piece of information. For example, for the proverb "Failure is the mother of success," the server generates the meaning, source, historical context, and similar words.

[1203] Input: Selected advisory data.

[1204] Data Computing: Generative AI models are used to generate relevant information.

[1205] Output: Generated meaning, source, historical context, and similar words are provided.

[1206] Step 8:

[1207] The server sends the generated information to the terminal, which then displays it to the user. The display format is intended to provide the generated information to the user visually. For example, in addition to the proverb "Failure is the mother of success," the meaning, source, historical background, and similar expressions are displayed in detail.

[1208] Input: Generated information (meaning, source, historical context, similar words).

[1209] Output: Provided to the user as visually displayed information.

[1210] "Failure is the foundation of success"

[1211] Source: Japanese proverb

[1212] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1213] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1214] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1215] (Application example 2)

[1216] 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."

[1217] Conventional user assistance systems have difficulty providing appropriate advice based on the emotions and situations expressed by the text data entered by the user. This has resulted in problems such as users not receiving the encouragement or specific advice they need, and not being able to effectively obtain emotional support or a sense of security. Furthermore, due to a lack of means to convert voice input into text data or perform detailed analysis of emotions, improvements to the user experience have been required.

[1218] 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.

[1219] In this invention, the server includes means for accepting text data input by a user, means for analyzing the accepted text data and extracting keywords and emotional tones, means for searching a database for relevant advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results and generating information to be provided to the user, means for transmitting the generated information to the user, speech recognition means for accepting voice input from the user and converting it into text data, and means for analyzing the extracted keywords and emotional tones with an emotion engine and identifying the intensity and type of emotion, thereby making it possible to provide personalized information tailored to the user's emotions and situation.

[1220] "Text data input by the user" refers to character data used when the user inputs a question or request for advice to the system.

[1221] "Analysis" is the process of analyzing input text data and extracting necessary information.

[1222] A "keyword" is a key word or phrase that represents the content of the text data.

[1223] "Emotional tone" is an element that indicates the intensity and type of a user's emotion that can be read from text data.

[1224] "Searching" is the act of searching for information in a database to find the appropriate data.

[1225] "Advice data" is data used to provide appropriate advice to users regarding their problems or inquiries.

[1226] "Selection" is the act of choosing the best option from multiple candidates.

[1227] "Information generation" is the process of using data and algorithms to create new information or content.

[1228] "Sending" is the act of delivering the generated information or data to the user's terminal.

[1229] "Voice input" refers to the act of a user using voice to input instructions or consultation details into the system.

[1230] "Speech recognition" is a technology that converts voice data into text.

[1231] An "emotion engine" is an algorithm or system that determines the intensity and type of emotion from user input data.

[1232] "Intensity and type" refers to the degree of strength of an emotion and the type into which the emotion is classified, such as "joy," "sadness," or "anger."

[1233] As an embodiment of the present invention, a system for providing encouraging words and advice tailored to a user's security concerns will be specifically described. This system is characterized by incorporating a series of means for accepting, analyzing, searching, generating, and transmitting text and voice data, as well as an emotion engine for recognizing the user's emotions.

[1234] First, a user accesses the system using a smartphone or smart glasses and inputs their security-related anxieties or fears by text or voice. For example, the user might input, "Recently, I've been worried about someone breaking into my house and I'm scared," or they can speak a similar message by voice.

[1235] The device then sends the entered text or voice data to the server. In the case of voice data, the device uses a voice recognition means to convert the voice into text data, which is then sent to the server. An HTTP POST request is used for transmission, and the data is sent to the server in JSON format.

[1236] The server analyzes the received text data and uses natural language processing technology to extract keywords and emotional tones. Morphological analysis extracts keywords such as "worry" and "fear," and sentiment analysis identifies the user's emotions as "anxiety" and "fear."

[1237] Additionally, the system incorporates an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the user's input pixel by pixel to identify the intensity and type of emotion. If the emotion engine determines that the intensity of "fear" is high, it will proceed to the next step, taking that information into account.

[1238] The server searches the database for relevant advice data based on the extracted keywords and emotional tone, for example, the server searches the database for advice related to security concerns and providing a sense of security.

[1239] The server then selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine, and for a user who is feeling strong "fear," the most effective advice is selected.

[1240] The server generates the meaning, source, historical context, and similar words related to the selected advice data. For example, for the advice "Strengthen home security measures," the server generates the meaning "Install security cameras and alarm systems to ensure safety," including the source "security experts" and the historical context "increased importance of security in recent years."

[1241] The generated information is sent to the terminal, which displays it to the user in the following format:

[1242] Strengthen your home's security measures

[1243] Source: Security Experts

[1244] Meaning: Install security cameras and alarm systems to ensure safety.

[1245] Historical background: The importance of security has increased in recent years.

[1246] Similar sayings: "Prevention is the best defense" and "Safety is peace of mind."

[1247] The hardware and software used are as follows:

[1248] Hardware: Smartphones, smart glasses

[1249] software:

[1250] Natural language processing engine: BERT (Bidirectional Encoder Representations from Transformers)

[1251] Emotion Recognition Engine: Emotion Recognition API

[1252] Database: MySQL

[1253] Server side: Python framework (e.g. Django)

[1254] Cloud environment: AWS (Amazon Web Services)

[1255] This system can provide users with personalized encouragement and advice that is tailored to their emotions and situations in response to their security concerns and worries.

[1256] An example prompt is:

[1257] "Generate encouraging words for users who are worried about a home invasion. Users have been feeling very anxious about their home security lately."

[1258] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1259] Step 1:

[1260] Users access the system using a smartphone or smart glasses and input their security concerns or fears by text or voice. The input text or voice data is sent directly to the terminal.

[1261] Input: User text or voice input

[1262] Output: Text data or audio data

[1263] Step 2:

[1264] The voice data received by the terminal is converted into text data using a voice recognition means, and the converted input data is sent to the server as an HTTP POST request.

[1265] Input: Audio data

[1266] Output: Text data

[1267] Step 3:

[1268] The server analyzes the received text data, performs morphological analysis to extract keywords, and performs sentiment analysis to extract emotional tones. This analysis uses natural language processing technology and an emotion recognition engine.

[1269] Input: Text data

[1270] Output: Keywords, emotional tone

[1271] Step 4:

[1272] The emotion engine performs detailed analysis of the extracted emotional tones and keywords to identify the intensity and type of emotion, paying particular attention to the analysis of highly intense emotions.

[1273] Input: Keywords, Emotional Tone

[1274] Output: Emotion intensity and type

[1275] Step 5:

[1276] The server searches the database for relevant advice data based on the extracted keywords and emotional tones, as well as the intensity and type of emotions, using the query function of the database.

[1277] Input: Keywords, emotional tone, emotional intensity and type

[1278] Output: relevant advisory data

[1279] Step 6:

[1280] The server selects the most appropriate advice data from the search results. This selection is greatly influenced by the intensity and type of emotion. In order to select appropriate advice data, detailed analysis results from the emotion engine are required.

[1281] Input: Candidate advisory data

[1282] Output: Optimal advice data

[1283] Step 7:

[1284] The server generates detailed information about the meaning, source, historical context, and similar words associated with the selected advice data, using a generative AI model.

[1285] Input: Best advice data

[1286] Output: Related information (meaning, source, historical background, similar words)

[1287] Step 8:

[1288] The generated information is sent to the user's device as an HTTP response. The device receives the information and displays it to the user in the specified format.

[1289] Input: Related Information

[1290] Output: Display on the user's terminal

[1291] 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.

[1292] 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.

[1293] 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.

[1294] [Fourth embodiment]

[1295] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1296] 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.

[1297] 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).

[1298] 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.

[1299] 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.

[1300] 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).

[1301] 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.

[1302] 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.

[1303] 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.

[1304] 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.

[1305] 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.

[1306] 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.

[1307] 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."

[1308] As an embodiment of the present invention, we will specifically explain a system that provides encouraging words and advice appropriate to the user's situation and worries. This system performs a series of operations: accepting and analyzing text data entered by the user, and searching and generating appropriate advice data.

[1309] First, the user accesses the system using a terminal and inputs text about their experiences, worries, and other situations. The text data input by the user is in a format such as, "I recently made a big mistake and have lost confidence. What should I do?"

[1310] The device then sends this text data to a server, which uses natural language processing techniques to analyze the received text data and extract keywords and emotional tones. This analysis step involves morphological analysis and sentiment analysis to understand the user's situation.

[1311] Specifically, the server extracts keywords such as "failure" and "lose confidence" and identifies the user's emotions as negative states such as "disappointment" and "disappointment."

[1312] Next, the server searches for relevant advice data from a database based on the extracted keywords and emotional tone. The database contains advice from historical figures, myths, proverbs, etc. The server then searches for the most appropriate advice data from this database.

[1313] The system selects appropriate advice data from the search results and generates information to provide it to the user. The generated information includes not only the words of advice themselves, but also their meaning, source, historical background, and similar words. For example, if the server selects the proverb "Failure is the mother of success," it generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," and also includes a "Japanese proverb" as the source and "a lesson that has long been rooted in Japanese culture" as the historical background.

[1314] Finally, the generated information is sent to the terminal, which then displays it to the user. The displayed information is in the following format:

[1315] "Failure is the foundation of success"

[1316] Source: Japanese proverb

[1317] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1318] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1319] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1320] This allows users to receive appropriate encouragement and advice, providing emotional support and courage. This series of operations in the system realizes the provision of personalized information that is in line with the user's emotions and situation.

[1321] The processing flow will be explained below.

[1322] Step 1:

[1323] The user accesses the system through a terminal and inputs their situation and worries as text. For example, the user might input, "I recently made a big mistake and lost confidence. What should I do?"

[1324] Step 2:

[1325] The device sends the entered text data to the server using an HTTP POST request, with the data sent in JSON format.

[1326] Step 3:

[1327] The server receives and analyzes the received text data using natural language processing (NLP) techniques. Specifically, morphological analysis is used to extract keywords and sentiment analysis is used to identify the user's emotional tone.

[1328] Step 4:

[1329] The server searches the database based on the keywords and emotional tones extracted from the analysis, using SQL queries and search algorithms to find relevant advice data.

[1330] Step 5:

[1331] The server selects the most appropriate advice data from the search results, using an algorithm to select words and anecdotes that best fit the user's emotional tone and situation.

[1332] Step 6:

[1333] The server generates additional information (meaning, source, historical background, similar words) related to the selected advice data. For example, it generates the meaning and background information of the proverb "Failure is the mother of success."

[1334] Step 7:

[1335] The server generates the information and sends it to the device, again using an HTTP POST request, with the data sent in JSON format.

[1336] Step 8:

[1337] The device displays the received information to the user via the user interface of a web browser or mobile app. For example, the device displays the proverb "Failure is the mother of success" and related information.

[1338] Example 1

[1339] 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."

[1340] There is a problem that it is difficult for users to get appropriate advice and encouragement for their worries or situations. In particular, there is a lack of systems that provide customized advice based on emotions and specific keywords, so users cannot obtain the information they really need. To solve this problem, it is necessary to provide a system that can accurately analyze users' text data and provide optimal advice.

[1341] 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.

[1342] In this invention, the server includes means for accepting text data input by a user, means for analyzing the accepted text data and using natural language processing technology to extract keywords and emotional tones, means for searching for relevant advice data from information sources based on the extracted keywords and emotional tones, means for selecting optimal advice data from the search results and generating information to be provided to the user, and means for transmitting the generated information to the user's terminal, thereby enabling the user to receive personalized advice and encouragement tailored to their own concerns and situations in real time.

[1343] "Text data" is data in the form of a sentence entered by the user.

[1344] "Natural language processing technology" is a technology that allows computers to understand, analyze, and generate human language.

[1345] "Emotional tone" refers to the emotional trend or state extracted from within text.

[1346] "Keywords" are important words or phrases extracted from text data.

[1347] "Advice data" refers to advice or encouragement provided to the user in response to their concerns or situations.

[1348] "Source" refers to a database or other storage device where advisory data is stored.

[1349] A "server" is a computer system that analyzes text data, searches for advice data, and transmits the generated information.

[1350] A "user terminal" is a device used by a user to access the system and enter text data.

[1351] "Generated information" refers to information that is created based on advice data searched and selected by the server and is to be provided to the user.

[1352] As an embodiment of the present invention, the operation of a system that provides advice and words of encouragement appropriate to a user's situation and worries will be specifically described. Each component of the system and its operation will be described in detail below.

[1353] Hardware and software used

[1354] server

[1355] The server performs the main data processing and database lookup. The server is usually hosted in a cloud environment and has sufficient computing resources. The main software components include:

[1356] Natural language processing engine (morphological analysis engine): Examples include MeCab and Janome

[1357] Sentiment analysis libraries: Examples include Google Cloud Natural Language API and NLTK

[1358] Database Management System (DBMS): Examples include MySQL and PostgreSQL

[1359] Terminal

[1360] The devices used by users are devices such as PCs, smartphones, tablets, etc. These devices are capable of connecting to the Internet and are used to access the system's web applications and mobile applications.

[1361] Processing flow and data processing / calculation

[1362] 1. User text input

[1363] Users access the system using a terminal and input situations such as their own experiences and worries. For example, they might input, "I recently made a big mistake and lost confidence. What should I do?"

[1364] 2. Sending text data

[1365] The terminal sends the entered text data to the server, which converts the data into an appropriate format (e.g., JSON) and sends it as an HTTP POST request.

[1366] 3. Receiving and analyzing text data

[1367] The server parses the received text data. The parsing is done in two stages:

[1368] Morphological analysis: The text is segmented and keywords are extracted. For example, keywords such as "failure" and "lose confidence" are extracted.

[1369] Sentiment analysis: Extracting the emotional tone of text. For example, negative emotional states such as "disappointed" or "disappointed" can be identified.

[1370] 4. Searching for advisory data

[1371] The server searches for appropriate advice data from a database containing proverbs, famous quotes, historical anecdotes, etc. based on the analyzed keywords and emotional tone, and selects the most appropriate advice data from the searched data.

[1372] 5. Generating Advisory Information

[1373] The server generates more detailed information based on the selected advice data. The generated information includes the advice itself, its meaning, its source, historical background, and similar words. For example, for the proverb "Failure is the mother of success," the server generates the following information:

[1374] "Failure is the foundation of success"

[1375] Source: Japanese proverb

[1376] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1377] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1378] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1379] 6. Transmission and display of generated information

[1380] The server sends the generated information to the terminal, which displays the received information on the user's screen, allowing the user to read it and receive appropriate advice and encouragement.

[1381] Specific examples

[1382] If a user types, "I recently made a big mistake and it's ruined my confidence. What should I do?", the system will act as follows:

[1383] 1. The user uses the terminal to input text data.

[1384] 2. The device sends the input data to the server.

[1385] 3. The server analyzes the text data and extracts keywords and emotional tones.

[1386] 4. The server retrieves the relevant advisory data from the database.

[1387] 5. The server selects the most appropriate advice data and generates detailed information.

[1388] 6. The server sends the generated information to the terminal, which displays the information to the user.

[1389] Example prompts for generative AI models

[1390] "If a user types in, 'I recently made a big mistake and I've lost confidence. What should I do?', provide appropriate advice such as the proverb 'Failure is the mother of success,' along with its meaning, source, historical context, and similar phrases."

[1391] The above is a detailed description of the mode for carrying out the invention. The system contributes to obtaining emotional support by providing personalized advice and encouragement to users.

[1392] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1393] Step 1:

[1394] Users access the system using their own terminals and input the worries and situations they have experienced.

[1395] Input: Text data entered by the user (e.g., "I recently made a big mistake and it's really hurt my confidence. What should I do?").

[1396] Output: Text data entered into the user's terminal.

[1397] Specific Actions: A user opens a web or mobile application on the system and enters text into a text input field.

[1398] Step 2:

[1399] The terminal transmits the input text data to the server.

[1400] Input: Text data entered by the user into the terminal.

[1401] Output: The text data sent to the server (e.g., an HTTP POST request in JSON format).

[1402] Specific operation: The terminal converts the text data entered by the user into an appropriate format and sends an HTTP POST request to the server.

[1403] Step 3:

[1404] The server analyzes the received text data and extracts keywords and emotional tones.

[1405] Input: Text data sent from the device to the server.

[1406] Output: Analyzed keywords and emotional tone (e.g., "failure," "losing confidence," "disappointed," "disappointed").

[1407] Data processing: Segment the text and extract keywords using a morphological analysis engine (e.g., MeCab or Janome). Analyze emotional tone using a sentiment analysis library (e.g., Google Cloud Natural Language API or NLTK).

[1408] How it works: The server first uses a morphological analysis engine to segment the text, then uses a sentiment analysis library to identify the emotional tone.

[1409] Step 4:

[1410] The server retrieves relevant advisory data from information sources based on the extracted keywords and emotional tones.

[1411] Input: Extracted keywords and emotional tone.

[1412] Output: Search results with relevant advice (e.g., "Failure is the key to success").

[1413] Data computation: Query the database using a database management system (DBMS) based on keywords and emotional tone.

[1414] Specific operations: The server queries the database to obtain relevant advisory data.

[1415] Step 5:

[1416] The server selects the most suitable advice data from the search results and generates information to provide to the user.

[1417] Input: Advisory data obtained as search results.

[1418] Output: Generated detailed advice (e.g., the phrase "Failure is the mother of success," its meaning, origin, historical context, and similar phrases).

[1419] Data processing: Generate detailed meanings, sources, historical background, and similar words for the selected advice data.

[1420] Specific operation: The server analyzes the acquired advice data and generates detailed information based on its meaning and background information.

[1421] "Failure is the foundation of success"

[1422] Source: Japanese proverb

[1423] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1424] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1425] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1426] Step 6:

[1427] The server transmits the generated information to the user's terminal.

[1428] Input: The generated detailed advisory information.

[1429] Output: Advisory information sent from the server to the device (e.g., HTTP response in JSON format).

[1430] Specific operation: The server formats the generated information appropriately and sends it to the terminal as an HTTP response.

[1431] Step 7:

[1432] The terminal receives the transmitted information and displays it on the user's screen.

[1433] Input: Advisory information sent by the server.

[1434] Output: Detailed advisory information displayed on the user's screen.

[1435] Specific operation: The device analyzes the received information and displays it on the user's screen in an easy-to-read format.

[1436] These are the specific processing steps of the program for this system. Through this series of steps, users can receive personalized advice and encouragement in real time, tailored to their concerns.

[1437] (Application example 1)

[1438] 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."

[1439] This paper deals with a method for providing prompt and appropriate advice to users regarding troubles and difficulties they may encounter while using electronic payment services. Conventional systems lack personalized support tailored to the specific concerns and feelings of users, and this has resulted in the inability to fully alleviate users' anxieties and dissatisfaction.

[1440] 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.

[1441] In this invention, the server includes means for accepting text data entered by a user, means for analyzing the accepted text data and extracting keywords and emotional tones, means for searching a database for relevant advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results and generating information to provide to the user, means for transmitting the generated information to the user, and means for analyzing user troubles and emotions in relation to electronic payment services and providing appropriate advice. This makes it possible to quickly provide appropriate advice that is in line with the user's emotional tones in response to problems that arise while the user is using the electronic payment service.

[1442] "Text data" refers to character information entered by the user.

[1443] "Keywords" are important words or phrases extracted from text data.

[1444] "Emotional tone" indicates the emotional state or tendency that can be read from the user's input.

[1445] A "database" refers to a collection of data in which information such as proverbs and advice is stored.

[1446] "Advice data" is information including encouragement and solutions provided in response to the user's worries or situations.

[1447] "Electronic payment service" refers to a digital service for processing payments online or offline.

[1448] "Natural language processing technology" is a technology that enables computers to understand and analyze human language.

[1449] "Analysis" refers to the act of analyzing input text data to understand its structure and meaning.

[1450] "Generation" refers to the process of creating new information or data.

[1451] "Sending" refers to the act of delivering the generated information to the user's terminal.

[1452] "Search" refers to the act of locating appropriate information from a database based on specified criteria.

[1453] As an embodiment of the present invention, a system for providing appropriate advice to a user for solving their worries or difficulties will be specifically described. This system performs a series of operations to accept and analyze text data entered by the user, search for and generate appropriate advice data, and provide it to the user. The specific processing procedure will be described below.

[1454] System Configuration

[1455] Hardware and Software

[1456] Server: The central computer system for analysis and advice generation. It uses nltk and TextBlob natural language processing technologies.

[1457] User terminal: A device that allows users to input text data and receive appropriate advice. It works on smartphones or smart glasses.

[1458] Database: A storage system for storing advice data, such as quotes, words of encouragement, and other advice data.

[1459] Program processing overview

[1460] The user terminal sends the text data entered by the user to the server, which then analyzes the received text data and extracts keywords and emotional tones using natural language processing techniques.

[1461] Specifically, the server uses TextBlob to extract the emotional tone of the text data, and then performs morphological analysis to extract keywords. Through this process, it is possible to understand the user's concerns and situations.

[1462] The server then searches for relevant advice data from a database based on the extracted keywords and emotional tones. The database contains historical proverbs and words of encouragement, and the server finds the most suitable advice data.

[1463] The server then selects appropriate advice data from the search results, and generates information on the meaning of the word, the historical background, and similar words. This information is structured to be easy for users to understand and to provide encouragement and solutions.

[1464] Finally, the server transmits the generated advice data to the user terminal, which then displays the information to the user. The following is a specific example.

[1465] Specific examples

[1466] User Input: "I was recently scammed and it's really hurt my confidence. What should I do?"

[1467] System response:

[1468] "Failure is the foundation of success"

[1469] Source: Japanese proverb

[1470] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1471] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1472] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1473] Prompt Sentence Examples

[1474] "I was recently scammed and my confidence has been damaged. What should I do?"

[1475] Advice that encourages the person's heart, such as "Failure is the mother of success," "If you keep trying without being afraid of failure, you will eventually achieve success," and "Don't give up after one failure."

[1476] This invention enables users to quickly receive appropriate advice tailored to their emotional tone when encountering problems while using electronic payment services. This system reduces users' anxiety and frustration and provides quick and effective support.

[1477] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1478] Step 1:

[1479] User Input

[1480] The user inputs text data about their worries or difficulties into the terminal. The input data format is something like, "I was recently the victim of a scam and I've lost confidence. What should I do?"

[1481] Input: User's text data

[1482] Output: Text data received by the device

[1483] Step 2:

[1484] Sending text data

[1485] The terminal sends the received text data to the server. At this time, the data is encrypted before being sent.

[1486] Input: Text data entered into the terminal

[1487] Output: Encrypted text data sent to the server

[1488] Step 3:

[1489] Text data analysis

[1490] The server analyzes the received text data, extracts the emotional tone of the text data using TextBlob, and performs morphological analysis to extract keywords, such as "failure" and "lose confidence."

[1491] Input: Text data sent to the server

[1492] Output: Extracted emotional tones and keywords

[1493] Step 4:

[1494] Retrieving advice data from a database

[1495] The server searches the database for relevant advice data based on the extracted keywords and emotional tones, for example, searching for advice data such as "Failure is the mother of success" based on the keyword "failure."

[1496] Input: Extracted emotional tone and keywords

[1497] Output: Retrieved advisory data

[1498] Step 5:

[1499] Selection and generation of appropriate advisory data

[1500] The server selects appropriate advice data from the search results and generates words that reflect its meaning, historical context, and similar expressions. For example, the server generates the meaning of the proverb "Failure is the mother of success" as "If you keep trying without fear of failure, you will eventually achieve success."

[1501] Input: Retrieved advisory data

[1502] Output: Selected advisory data and its details

[1503] Step 6:

[1504] Sending advisory data

[1505] The server sends the generated advice data to the terminal, which receives the data and displays it to the user. The displayed information includes the advice words, meanings, sources, historical background, and similar words.

[1506] Input: Selected advisory data and its details

[1507] Output: Advisory data sent to the terminal

[1508] Step 7:

[1509] Providing advice to users

[1510] The terminal displays the received advice data to the user in the following format:

[1511] Input: Advisory data sent to the terminal

[1512] Output: Advisory data displayed to the user

[1513] "Failure is the foundation of success"

[1514] Source: Japanese proverb

[1515] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1516] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1517] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1518] 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.

[1519] As an embodiment of the present invention, a system for providing encouraging words and advice tailored to a user's situation and concerns will be specifically described. This system is characterized by incorporating a series of means for accepting, analyzing, searching, generating, and transmitting text data, as well as an emotion engine for recognizing the user's emotions.

[1520] First, the user accesses the system using a terminal and enters specific text about the problem or issue they would like to discuss. For example, the user might enter, "I recently made a big mistake and have lost confidence. What should I do?"

[1521] The device then sends this text data to the server using an HTTP POST request, with the data being sent to the server in JSON format.

[1522] The server analyzes the received text data and uses natural language processing techniques to extract keywords and emotional tones. Morphological analysis extracts keywords such as "failure" and "loss of confidence," while sentiment analysis identifies the user's emotions as "disappointment" and "disappointment."

[1523] The system also incorporates an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the user's input pixel by pixel to identify the intensity and type of emotion. If the emotion engine determines that the intensity of "disappointment" is high, it will take that information into account and proceed to the next step.

[1524] The server searches the database for relevant advice data based on the extracted keywords and emotional tone, for example, the server searches the database for advice related to failure and regaining self-confidence.

[1525] The server then selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine, and for a user who is feeling strong "disappointment," the most effective advice is selected.

[1526] The server generates the meaning, source, historical background, and similar words related to the selected advice data. For example, for the proverb "Failure is the mother of success," the server generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," and includes "Japanese proverbs" as the source and "lessons that have been deeply rooted in Japanese culture since ancient times" as the historical background.

[1527] The generated information is sent to the terminal, which displays it to the user in the following format:

[1528] "Failure is the foundation of success"

[1529] Source: Japanese proverb

[1530] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1531] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1532] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1533] This allows users to receive appropriate encouragement and advice, helping them regain their emotional support and courage.The entire system's operations realize personalized information provision that is tailored to the user's emotions and situation.

[1534] The processing flow will be explained below.

[1535] Step 1:

[1536] The user accesses the system through a terminal and inputs their situation and worries as text. For example, the user might input, "I recently made a big mistake and lost confidence. What should I do?"

[1537] Step 2:

[1538] The device sends the entered text data to the server using an HTTP POST request, and the data is sent to the server in JSON format.

[1539] Step 3:

[1540] The server analyzes the received text data. Using natural language processing (NLP) technology, it extracts keywords through morphological analysis and identifies the user's emotional tone through sentiment analysis. For example, keywords such as "failure" and "loss of confidence" are extracted, and the emotional tone is identified as "disappointment" or "disappointment."

[1541] Step 4:

[1542] The server uses an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the type and intensity of emotions on a pixel-by-pixel basis. For example, it determines that the intensity of "disappointment" is high based on the user's input.

[1543] Step 5:

[1544] The server searches the database for appropriate advice data based on the extracted keywords and the emotional tone recognized by the emotion engine, for example, advice data related to "failure" and "recovering self-confidence" are searched for in the database.

[1545] Step 6:

[1546] The server selects the most appropriate advice data from the search results. This selection also takes into account the emotional information recognized by the emotion engine. For example, if a user is feeling strong disappointment, the most effective advice will be selected.

[1547] Step 7:

[1548] The server generates information related to the selected advice data (meaning, source, historical background, similar words). For example, for the proverb "Failure is the mother of success," it generates meaning and background information. Specifically, it generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," the source "Japanese proverb," ​​and the historical background "a lesson that has been deeply rooted in Japanese culture since ancient times."

[1549] Step 8:

[1550] The server then sends the generated information to the device, again using an HTTP POST request, with the data sent to the device in JSON format.

[1551] Step 9:

[1552] The terminal displays the received information to the user through the user interface in the following format, for example:

[1553] "Failure is the foundation of success"

[1554] Source: Japanese proverb

[1555] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1556] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1557] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1558] In this way, users can receive appropriate encouragement and advice, and regain their emotional support and courage.

[1559] Example 2

[1560] 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."

[1561] Conventional user support systems sometimes fail to provide appropriate advice based on user input. Furthermore, they lack a mechanism for recognizing the user's emotions in detail and selecting appropriate advice, which means that the effective support desired by the user cannot be provided. This increases the likelihood of delays in resolving the user's concerns, leading to a lack of psychological support.

[1562] 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.

[1563] In this invention, the server includes means for accepting text data input by a user, means for transmitting the accepted text data to the server, means for analyzing the received text data and extracting keywords and emotional tones, means for analyzing the extracted emotional tones in more detail using an emotion engine, means for searching a database for related advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results, means for generating meanings, sources, historical backgrounds, and similar words related to the selected advice data, and means for transmitting the generated information to the user. This makes it possible to provide appropriate advice according to emotions analyzed in detail based on the user's worries and consultation contents.

[1564] "User" refers to an individual who uses this system and inputs their concerns or questions in text format.

[1565] "Terminal" refers to a device used by a user, and includes information processing devices such as smartphones, tablets, and personal computers.

[1566] "Text data" refers to character information entered by a user through a terminal, and is language data that includes worries and consultation details.

[1567] A "server" is a computer device that serves as the core of a system that analyzes received text data and processes and provides related information in conjunction with a database.

[1568] An "HTTP POST request" is one of the communication protocols used when sending data from a terminal to a server.

[1569] "JSON format" is a data exchange format for structuring text data for data transmission.

[1570] "Natural language processing technology" is a technology for analyzing human language and converting it into a form that a computer can understand, and includes morphological analysis and sentiment analysis.

[1571] "Morphological analysis" is a technique that breaks down text data into individual words or morphemes and analyzes their meaning and role.

[1572] "Emotional tone" is information that indicates the user's emotions contained in the text data, and refers to emotional attributes such as "disappointment" or "disappointment."

[1573] An "emotion engine" refers to software or algorithms that perform detailed analysis of emotions from text data entered by a user.

[1574] "Database" refers to a collection of information used by the server to look up relevant advisory data; it is a structured collection of data.

[1575] "Advice data" is information including solutions and words of encouragement provided to the user in response to the user's worries or inquiries.

[1576] "Generative AI model" refers to an artificial intelligence algorithm that generates meaning, sources, historical context, and similar words related to selected advisory data.

[1577] This invention relates to a system for providing encouraging words and advice tailored to a user's situation and concerns. This system incorporates a series of means for accepting, analyzing, searching, generating, and transmitting text data, as well as an emotion engine for recognizing the user's emotions.

[1578] First, the user accesses the system using a terminal and enters specific text about the problem or issue they want to discuss. For example, they might enter, "I recently made a big mistake and lost confidence. What should I do?" The terminal then sends this entered text data to the server. An HTTP POST request is used to send the data, and the data is sent to the server in JSON format.

[1579] The server analyzes the received text data and extracts keywords and emotional tones using natural language processing technology. Specifically, it uses a morphological analysis tool (e.g., MeCab) to analyze the text data and extract keywords such as "failure" and "loss of confidence." It also uses a sentiment analysis tool (e.g., Google Cloud Natural Language API) to identify the user's emotions as "disappointment" and "disappointment."

[1580] Additionally, an emotion engine is built in, which performs detailed pixel-by-pixel analysis of the user's input text to determine the emotion. This method identifies the intensity and type of emotion. For example, if the emotion "disappointment" is determined to be strong, this information is also incorporated into the next step.

[1581] The server searches the database for relevant advice data based on the extracted keywords and emotional tone. For example, it searches the database for advice related to failure or regaining confidence. This process uses SQL queries.

[1582] The server then selects the most appropriate advice data from the search results. This selection reflects the user's emotional information recognized by the emotion engine. For example, if a user is feeling strong disappointment, the most effective advice will be selected.

[1583] The server then uses a generative AI model (e.g., GPT-4) to generate meanings, sources, historical contexts, and similar words related to the selected advice data. For example, for the proverb "Failure is the mother of success," the server generates the meaning "If you keep trying without fear of failure, you will eventually achieve success," including a "Japanese proverb" as the source and a "lesson deeply rooted in Japanese culture since ancient times" as the historical context.

[1584] The generated information is sent to the terminal for display to the user. The terminal visually displays this information to the user in the following format:

[1585] "Failure is the foundation of success"

[1586] Source: Japanese proverb

[1587] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1588] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1589] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1590] As a concrete example, let's consider the case where a user types, "I made a mistake at work and I just can't get over it. What should I do?" In this case, the device sends the input text to the server, which then analyzes and searches it after receiving it. Ultimately, the user is provided with appropriate advice, which helps them regain their emotional support and courage.

[1591] Examples of prompts using generative AI models include:

[1592] "I made a mistake at work recently and I just can't get over it. What words of encouragement do you have?"

[1593] The entire system's operations are designed to provide personalized information tailored to the user's emotions and situation.

[1594] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1595] Step 1:

[1596] The user accesses the system using a terminal and enters specific text about the problem or issue they would like to discuss. For example, the user might enter, "I recently made a big mistake and have lost confidence. What should I do?"

[1597] Input: The user enters the consultation content in the text input field.

[1598] Output: The entered text data is saved to the terminal.

[1599] Step 2:

[1600] The device sends the entered text data to the server using an HTTP POST request, and the data is sent to the server in JSON format.

[1601] Input: User-entered text data stored on the device.

[1602] Data processing: Convert text data into JSON format.

[1603] Output: Text data formatted in JSON format is sent to the server.

[1604] Step 3:

[1605] The server analyzes the received text data. Natural language processing technology is used to extract keywords and emotional tones from the text data. Specifically, a morphological analysis tool is used to extract keywords such as "failure" and "loss of confidence," and an emotion analysis tool is used to identify the emotional tones as "disappointment" and "disappointment."

[1606] Input: JSON formatted text data received by the server.

[1607] Data processing: Keywords are extracted using morphological analysis and emotional tones are extracted using sentiment analysis.

[1608] Output: Extracted keywords and emotional tones.

[1609] Step 4:

[1610] The server then uses an emotion engine to perform a detailed analysis of the extracted emotional tone. The emotion engine analyzes emotions pixel by pixel and identifies the intensity and type of emotion. For example, if the intensity of "disappointment" is determined to be high, that information is used in the next step.

[1611] Input: Extracted emotional tone.

[1612] Data computation: Detailed analysis of the intensity and type of emotions through the emotion engine.

[1613] Output: Detailed analyzed emotional information (e.g., high intensity of "disappointment") is obtained.

[1614] Step 5:

[1615] The server searches the database for relevant advice data based on the extracted keywords and the analyzed sentiment information, using SQL queries.

[1616] Input: Keywords and detailed analyzed sentiment information.

[1617] Data Calculation: Retrieving relevant advisory data from a database using SQL queries.

[1618] Output: Relevant advisory data is obtained.

[1619] Step 6:

[1620] The server selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine. For example, if a user is feeling strong "disappointment," the most effective advice will be selected.

[1621] Input: Search result advisory data and detailed analyzed sentiment information.

[1622] Data processing: Select the most appropriate advice data based on emotional information.

[1623] Output: Selected advisory data is obtained.

[1624] Step 7:

[1625] The server generates the meaning, source, historical context, and similar words related to the selected advice data. This generation uses a generative AI model to specifically describe each piece of information. For example, for the proverb "Failure is the mother of success," the server generates the meaning, source, historical context, and similar words.

[1626] Input: Selected advisory data.

[1627] Data Computing: Generative AI models are used to generate relevant information.

[1628] Output: Generated meaning, source, historical context, and similar words are provided.

[1629] Step 8:

[1630] The server sends the generated information to the terminal, which then displays it to the user. The display format is intended to provide the generated information to the user visually. For example, in addition to the proverb "Failure is the mother of success," the meaning, source, historical background, and similar expressions are displayed in detail.

[1631] Input: Generated information (meaning, source, historical context, similar words).

[1632] Output: Provided to the user as visually displayed information.

[1633] "Failure is the foundation of success"

[1634] Source: Japanese proverb

[1635] Meaning: If you keep trying without fear of failure, you will eventually achieve success.

[1636] Historical background: A lesson that has been deeply rooted in Japanese culture for a long time.

[1637] Similar sayings: "Don't give up after one failure" and "The opposite of success is not failure, it's doing nothing."

[1638] (Application example 2)

[1639] 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."

[1640] Conventional user assistance systems have difficulty providing appropriate advice based on the emotions and situations expressed by the text data entered by the user. This has resulted in problems such as users not receiving the encouragement or specific advice they need, and not being able to effectively obtain emotional support or a sense of security. Furthermore, due to a lack of means to convert voice input into text data or perform detailed analysis of emotions, improvements to the user experience have been required.

[1641] 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.

[1642] In this invention, the server includes means for accepting text data input by a user, means for analyzing the accepted text data and extracting keywords and emotional tones, means for searching a database for relevant advice data based on the extracted keywords and emotional tones, means for selecting appropriate advice data from the search results and generating information to be provided to the user, means for transmitting the generated information to the user, speech recognition means for accepting voice input from the user and converting it into text data, and means for analyzing the extracted keywords and emotional tones with an emotion engine and identifying the intensity and type of emotion, thereby making it possible to provide personalized information tailored to the user's emotions and situation.

[1643] "Text data input by the user" refers to character data used when the user inputs a question or request for advice to the system.

[1644] "Analysis" is the process of analyzing input text data and extracting necessary information.

[1645] A "keyword" is a key word or phrase that represents the content of the text data.

[1646] "Emotional tone" is an element that indicates the intensity and type of a user's emotion that can be read from text data.

[1647] "Searching" is the act of searching for information in a database to find the appropriate data.

[1648] "Advice data" is data used to provide appropriate advice to users regarding their problems or inquiries.

[1649] "Selection" is the act of choosing the best option from multiple candidates.

[1650] "Information generation" is the process of using data and algorithms to create new information or content.

[1651] "Sending" is the act of delivering the generated information or data to the user's terminal.

[1652] "Voice input" refers to the act of a user using voice to input instructions or consultation details into the system.

[1653] "Speech recognition" is a technology that converts voice data into text.

[1654] An "emotion engine" is an algorithm or system that determines the intensity and type of emotion from user input data.

[1655] "Intensity and type" refers to the degree of strength of an emotion and the type into which the emotion is classified, such as "joy," "sadness," or "anger."

[1656] As an embodiment of the present invention, a system for providing encouraging words and advice tailored to a user's security concerns will be specifically described. This system is characterized by incorporating a series of means for accepting, analyzing, searching, generating, and transmitting text and voice data, as well as an emotion engine for recognizing the user's emotions.

[1657] First, a user accesses the system using a smartphone or smart glasses and inputs their security-related anxieties or fears by text or voice. For example, the user might input, "Recently, I've been worried about someone breaking into my house and I'm scared," or they can speak a similar message by voice.

[1658] The device then sends the entered text or voice data to the server. In the case of voice data, the device uses a voice recognition means to convert the voice into text data, which is then sent to the server. An HTTP POST request is used for transmission, and the data is sent to the server in JSON format.

[1659] The server analyzes the received text data and uses natural language processing technology to extract keywords and emotional tones. Morphological analysis extracts keywords such as "worry" and "fear," and sentiment analysis identifies the user's emotions as "anxiety" and "fear."

[1660] Additionally, the system incorporates an emotion engine to recognize the user's emotions in more detail. The emotion engine analyzes the user's input pixel by pixel to identify the intensity and type of emotion. If the emotion engine determines that the intensity of "fear" is high, it will proceed to the next step, taking that information into account.

[1661] The server searches the database for relevant advice data based on the extracted keywords and emotional tone, for example, the server searches the database for advice related to security concerns and providing a sense of security.

[1662] The server then selects the most appropriate advice data from the search results. This selection utilizes the user's emotional information recognized by the emotion engine, and for a user who is feeling strong "fear," the most effective advice is selected.

[1663] The server generates the meaning, source, historical context, and similar words related to the selected advice data. For example, for the advice "Strengthen home security measures," the server generates the meaning "Install security cameras and alarm systems to ensure safety," including the source "security experts" and the historical context "increased importance of security in recent years."

[1664] The generated information is sent to the terminal, which displays it to the user in the following format:

[1665] Strengthen your home's security measures

[1666] Source: Security Experts

[1667] Meaning: Install security cameras and alarm systems to ensure safety.

[1668] Historical background: The importance of security has increased in recent years.

[1669] Similar sayings: "Prevention is the best defense" and "Safety is peace of mind."

[1670] The hardware and software used are as follows:

[1671] Hardware: Smartphones, smart glasses

[1672] software:

[1673] Natural language processing engine: BERT (Bidirectional Encoder Representations from Transformers)

[1674] Emotion Recognition Engine: Emotion Recognition API

[1675] Database: MySQL

[1676] Server side: Python framework (e.g. Django)

[1677] Cloud environment: AWS (Amazon Web Services)

[1678] This system can provide users with personalized encouragement and advice that is tailored to their emotions and situations in response to their security concerns and worries.

[1679] An example prompt is:

[1680] "Generate encouraging words for users who are worried about a home invasion. Users have been feeling very anxious about their home security lately."

[1681] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1682] Step 1:

[1683] Users access the system using a smartphone or smart glasses and input their security concerns or fears by text or voice. The input text or voice data is sent directly to the terminal.

[1684] Input: User text or voice input

[1685] Output: Text data or audio data

[1686] Step 2:

[1687] The voice data received by the terminal is converted into text data using a voice recognition means, and the converted input data is sent to the server as an HTTP POST request.

[1688] Input: Audio data

[1689] Output: Text data

[1690] Step 3:

[1691] The server analyzes the received text data, performs morphological analysis to extract keywords, and performs sentiment analysis to extract emotional tones. This analysis uses natural language processing technology and an emotion recognition engine.

[1692] Input: Text data

[1693] Output: Keywords, emotional tone

[1694] Step 4:

[1695] The emotion engine performs detailed analysis of the extracted emotional tones and keywords to identify the intensity and type of emotion, paying particular attention to the analysis of highly intense emotions.

[1696] Input: Keywords, Emotional Tone

[1697] Output: Emotion intensity and type

[1698] Step 5:

[1699] The server searches the database for relevant advice data based on the extracted keywords and emotional tones, as well as the intensity and type of emotions, using the query function of the database.

[1700] Input: Keywords, emotional tone, emotional intensity and type

[1701] Output: relevant advisory data

[1702] Step 6:

[1703] The server selects the most appropriate advice data from the search results. This selection is greatly influenced by the intensity and type of emotion. In order to select appropriate advice data, detailed analysis results from the emotion engine are required.

[1704] Input: Candidate advisory data

[1705] Output: Optimal advice data

[1706] Step 7:

[1707] The server generates detailed information about the meaning, source, historical context, and similar words associated with the selected advice data, using a generative AI model.

[1708] Input: Best advice data

[1709] Output: Related information (meaning, source, historical background, similar words)

[1710] Step 8:

[1711] The generated information is sent to the user's device as an HTTP response. The device receives the information and displays it to the user in the specified format.

[1712] Input: Related Information

[1713] Output: Display on the user's terminal

[1714] 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.

[1715] 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.

[1716] 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.

[1717] 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.

[1718] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1719] 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.

[1720] 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).

[1721] 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.

[1722] 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."

[1723] 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.

[1724] 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).

[1725] 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.

[1726] 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.

[1727] 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.

[1728] 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.

[1729] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1730] 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.

[1731] 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.

[1732] 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.

[1733] 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.

[1734] 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.

[1735] The following is further disclosed regarding the above embodiment.

[1736] (Claim 1)

[1737] means for accepting text data input by a user;

[1738] means for analyzing the received text data and extracting keywords and emotional tones;

[1739] means for retrieving relevant advice data from a database based on the extracted keywords and emotional tone;

[1740] a means for selecting appropriate advice data from the search results and generating information to be provided to the user;

[1741] means for transmitting the generated information to a user;

[1742] A system including:

[1743] (Claim 2)

[1744] 10. The system of claim 1, further comprising: means for extracting emotional tone from the analyzed text data using natural language processing techniques.

[1745] (Claim 3)

[1746] 2. The system according to claim 1, further comprising means for generating words that are similar to the meaning, historical background, and meaning of the selected advice data.

[1747] "Example 1"

[1748] (Claim 1)

[1749] means for accepting text data input by a user;

[1750] means for analyzing the received text data and using natural language processing techniques to extract keywords and emotional tones;

[1751] means for retrieving relevant advisory data from information sources based on the extracted keywords and emotional tone;

[1752] a means for selecting optimal advice data from the search results and generating information to be provided to the user;

[1753] means for transmitting the generated information to a user terminal;

[1754] A system including:

[1755] (Claim 2)

[1756] 10. The system of claim 1, further comprising: means for using natural language processing techniques to extract emotional tone from the analyzed text data.

[1757] (Claim 3)

[1758] 2. The system according to claim 1, further comprising means for generating the meaning, source, historical background and similar words of the selected advice data and providing them to the user.

[1759] "Application Example 1"

[1760] (Claim 1)

[1761] means for accepting text data input by a user;

[1762] means for analyzing the received text data and extracting keywords and emotional tones;

[1763] means for retrieving relevant advice data from a database based on the extracted keywords and emotional tone;

[1764] a means for selecting appropriate advice data from the search results and generating information to be provided to the user;

[1765] means for transmitting the generated information to a user;

[1766] A system that includes a means for analyzing user troubles and emotions in electronic payment services and providing appropriate advice.

[1767] (Claim 2)

[1768] 10. The system of claim 1, further comprising: means for extracting emotional tone from the analyzed text data using natural language processing techniques.

[1769] (Claim 3)

[1770] 2. The system according to claim 1, further comprising means for generating words that are similar to the meaning, historical background, and meaning of the selected advice data.

[1771] "Example 2: Combining Emotion Engines"

[1772] (Claim 1)

[1773] means for accepting text data input by a user;

[1774] means for transmitting the received text data to a server;

[1775] means for analyzing the received text data and extracting keywords and emotional tones;

[1776] a means for further analyzing the extracted emotional tone using an emotion engine;

[1777] means for retrieving relevant advice data from a database based on the extracted keywords and emotional tone;

[1778] A means for selecting appropriate advisory data from the search results;

[1779] A means for generating meanings, sources, historical contexts, and similar terms related to the selected advisory data;

[1780] means for transmitting the generated information to a user;

[1781] A system including:

[1782] (Claim 2)

[1783] 10. The system of claim 1, further comprising means for extracting emotional tones from the analyzed text data using natural language processing techniques and further analyzing the emotional tones using an emotion engine.

[1784] (Claim 3)

[1785] 2. The system of claim 1, further comprising means for generating the meaning, source, historical context, and similar words of the selected advice data.

[1786] "Application example 2 when combining emotion engines"

[1787] (Claim 1)

[1788] means for accepting text data input by a user;

[1789] means for analyzing the received text data and extracting keywords and emotional tones;

[1790] means for retrieving relevant advice data from a database based on the extracted keywords and emotional tone;

[1791] a means for selecting appropriate advice data from the search results and generating information to be provided to the user;

[1792] means for transmitting the generated information to a user;

[1793] a speech recognition means for accepting speech input from a user and converting it into text data;

[1794] A means for analyzing the extracted keywords and emotional tones with an emotion engine to identify the intensity and type of emotion;

[1795] A system including:

[1796] (Claim 2)

[1797] 10. The system of claim 1, further comprising: means for extracting emotional tone from the analyzed text data using natural language processing techniques.

[1798] (Claim 3)

[1799] 2. The system according to claim 1, further comprising means for generating words that are similar to the meaning, historical background, and meaning of the selected advice data. [Explanation of symbols]

[1800] 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 accepting text data input by a user; means for analyzing the received text data and extracting keywords and emotional tones; means for retrieving relevant advice data from a database based on the extracted keywords and emotional tone; a means for selecting appropriate advice data from the search results and generating information to be provided to the user; means for transmitting the generated information to a user; A system including:

2. 10. The system of claim 1, further comprising means for extracting emotional tone from the analyzed text data using natural language processing techniques.

3. 2. The system according to claim 1, further comprising means for generating words that are similar to the meaning, historical background, and meaning of the selected advice data.

Images