System

Abstract

A system is provided.SOLUTION: A system comprising: means for authenticating a user; means for receiving a counseling request from the user; means for analyzing the counseling request using natural language processing; means for invoking an artificial intelligence module to generate an appropriate response based on the analysis; means for providing the response from the artificial intelligence module to the user; and means for receiving and storing feedback from 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 society, the number of people who need mental health care is increasing, but the current system for providing counseling in Japan is not fully developed. As a result, it is difficult for users to receive appropriate counseling when they feel they need someone to listen. In addition, existing online counseling services are expensive, making them difficult for many people to use. Furthermore, the number of professionals providing counseling is limited, creating the challenge of being unable to meet demand. [Means for solving the problem]

[0005] To solve this problem, we provide a system that includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating an artificial intelligence module for generating an appropriate response based on the analysis results, means for providing the response from the artificial intelligence module to the user, and means for receiving and storing feedback from the user. This allows users to easily receive mental health care and enables the provision of services at low cost. By using the artificial intelligence module, this system provides high-quality counseling without relying on the number of experts. Furthermore, it is possible to utilize user feedback to continuously improve the service.

[0006] "User authentication" is the process of verifying that a user accessing a system is a legitimate user.

[0007] A "counseling request" refers to the consultation details or requests that a user sends to the system in order to receive counseling services.

[0008] "Natural language processing" refers to the technology that allows computers to understand and analyze human language.

[0009] "Artificial Intelligence Module" refers to an artificial intelligence program or software designed to perform a specific task.

[0010] "Response" refers to the answer or advice generated by the artificial intelligence module in response to a user's counseling request.

[0011] "Feedback" refers to the opinions and evaluations provided by users after a counseling session has concluded.

[0012] "System" refers to a complex computer-based platform that has functions such as user authentication, receiving counseling requests, natural language processing, invoking artificial intelligence modules, providing responses, and receiving and storing feedback. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] This invention is a system that allows users to easily receive mental health care online. The following explanation describes the specific method for implementing the program for this system and its processing in natural language.

[0035] Server Operation

[0036] 1. User Authentication

[0037] The server performs the authentication process to allow a user to log in to the system. Specifically, it receives the login information (username and password) entered by the user and checks it against a database. If authentication is successful, a user session begins.

[0038] 2. Receiving a Counseling Request

[0039] The server receives a counseling request sent from a user, which includes the content of the consultation and the worries in text format.

[0040] 3. Natural Language Processing

[0041] The server inputs the received counseling request into a natural language processing (NLP) module, which analyzes the consultation content and classifies topics and emotions.

[0042] 4. Launching the AI ​​module

[0043] The server then activates an artificial intelligence module to generate an appropriate response based on the analysis results of the NLP module. The artificial intelligence module generates an answer that is optimal for the user's inquiry.

[0044] 5. Providing a Response

[0045] The server sends the response generated by the artificial intelligence module to the user, which is in text format and displayed on the user's terminal.

[0046] 6. Receiving and storing feedback

[0047] The server receives feedback from the user after the counseling session. The feedback includes an evaluation of the session and suggestions for improvement, and stores it in a database. The stored feedback is used to improve the service in the future.

[0048] Device behavior

[0049] 1. Sending user authentication information

[0050] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[0051] 2. Submit a Counseling Request

[0052] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[0053] 3. View the response

[0054] The terminal displays the response received from the server to the user, who can then check the response content on the terminal.

[0055] 4. Submitting Feedback

[0056] The terminal transmits the feedback input by the user to the server after the session ends.

[0057] User Actions

[0058] 1. Log in

[0059] Users log in to the system using a dedicated app or a web browser, entering their username and password on the login screen to complete the authentication process.

[0060] 2. Submit a Counseling Request

[0061] The user inputs a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[0062] 3. Check the response

[0063] The user can check the response from the server on the terminal, and after reading the response, can enter additional questions or comments as needed.

[0064] 4. Providing Feedback

[0065] After the counseling session, the user inputs feedback and sends it to the server, including an evaluation of the session and suggestions for improvement.

[0066] Specific examples

[0067] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to the natural language processing module for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises." This response is sent to the user's device, where the user can confirm the answer. After the session ends, the user sends feedback saying, "Your advice was helpful. Thank you."

[0068] As described above, this system can implement a series of processes to provide users with mental care easily and effectively.

[0069] The processing flow will be explained below.

[0070] Step 1:

[0071] The user launches the app or web browser, accesses the login screen, enters their username and password, and presses the "Login" button.

[0072] Step 2:

[0073] The terminal transmits the login information entered by the user to the server.

[0074] Step 3:

[0075] The server compares the received login information with the database and authenticates the user. If authentication is successful, it generates a user ID and starts a session. It then sends the authentication result to the terminal.

[0076] Step 4:

[0077] The user enters the content of their consultation, such as "I've been feeling stressed at work lately. How can I relax?" into the form for submitting a counseling request and presses the "Submit" button.

[0078] Step 5:

[0079] The terminal transmits the consultation content to the server.

[0080] Step 6:

[0081] The server receives the consultation content and prepares to launch the AI ​​counselor. The consultation content is input into a natural language processing (NLP) module and topic analysis is performed.

[0082] Step 7:

[0083] The server selects an AI counselor to generate an appropriate response based on the analysis results returned from the NLP module, and causes the AI ​​counselor to generate the appropriate response.

[0084] Step 8:

[0085] The server receives the response generated by the AI ​​counselor, formats it for the user, and sends the formatted response to the device.

[0086] Step 9:

[0087] The terminal displays the AI ​​counselor's response received from the server to the user.

[0088] Step 10:

[0089] The user checks the AI ​​counselor's response, enters further questions or comments, and presses the "Send" button.

[0090] Step 11:

[0091] The terminal sends the user's additional input to the server.

[0092] Step 12:

[0093] The server again has the AI ​​counselor process the user's additional input, generate a new response, and send it back to the user.

[0094] Step 13:

[0095] The user presses the "End" button to end the session, enters their impressions and evaluation in the feedback form, and submits it.

[0096] Step 14:

[0097] The terminal transmits feedback information to the server.

[0098] Step 15:

[0099] The server receives the feedback information, stores it in a database, and analyzes it to help improve the performance of the AI ​​counselor.

[0100] Step 16:

[0101] The server ends the user session and logs the user out.

[0102] Example 1

[0103] 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."

[0104] There is a need for a system that can respond quickly and appropriately to users' needs for easy online mental health care. However, conventional systems have difficulty accurately understanding the content of users' consultations and providing appropriate advice. Furthermore, they lack a mechanism for efficiently collecting feedback from users and using it to improve services. An effective system is needed to solve these issues.

[0105] 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.

[0106] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating a generative AI model for generating an appropriate response based on the analysis results, means for providing the response from the generative AI model to the user, and means for receiving and storing feedback from the user. This allows users to easily receive mental health care online, and the system can generate and provide appropriate responses based on the user's consultation content. Furthermore, efficiently collecting and storing feedback can contribute to improving the quality of services.

[0107] A "means for user authentication" is a mechanism that receives login information (user name and password) entered by a user and verifies the user's identity by comparing it with a database.

[0108] The "means for receiving a counseling request" is a function for receiving the consultation content entered by the user in text format.

[0109] "Means for analyzing counseling requests using natural language processing" refers to a system that uses natural language processing technology to analyze the content of the consultation received, understand the content, and classify it.

[0110] "Means for launching a generative AI model" refers to a function that launches and utilizes an artificial intelligence model to generate an appropriate response to the user's inquiry based on the analysis results of natural language processing.

[0111] The "means for providing a response from the generative AI model to a user" is a mechanism for sending and displaying a text response generated by an artificial intelligence model on a user's device.

[0112] "Means for receiving and storing feedback" is a function that receives evaluations and comments sent by users after the counseling session and stores them in a database.

[0113] This invention is a system that allows users to easily receive mental health care online. This system is realized using the following means. The operations of the user, terminal, and server will be described in detail below.

[0114] Server Operation

[0115] The server first authenticates the user. It receives the login information (username and password) entered by the user, encrypts it using the SHA-256 hash algorithm, and then checks it against the database. If authentication is successful, the server generates a session ID and sends it to the user.

[0116] Next, the server receives a counseling request from the user. The request contains the user's concerns and the details of the consultation in text format. This text is processed using a Python natural language processing library (e.g., spaCy). Specifically, the text is tokenized, sentiment analyzed, and topic extracted.

[0117] Based on the analysis results, the server launches a generative AI model (e.g., OpenAI's GPT-3), which generates an appropriate response to the user's inquiry based on the prompt. The generated response is returned to the server in text format.

[0118] The server generates a text response and sends it to the user's terminal, where it is encoded and formatted according to the appropriate protocol before being served to the user.

[0119] Finally, the server receives feedback from users after the counseling session and stores it in a database, including session ratings and comments, to improve the quality of the service.

[0120] Device behavior

[0121] The terminal first sends the login information entered by the user to the server. The information is encrypted using SSL / TLS. After the authentication result is returned from the server, if the authentication is successful, the terminal proceeds to the next step.

[0122] Next, the terminal sends the counseling request entered by the user in text format to the server, waits for a response from the server, and displays the received response to the user in a chat box or message display area within the application.

[0123] After the counseling session is over, the terminal sends the feedback entered by the user to the server. The feedback is entered through the GUI and sent to the server.

[0124] User Actions

[0125] Users log in to the system using a dedicated application or a web browser. They enter their username and password on the login screen and click the "Login" button.

[0126] Next, the user enters a counseling request by entering the specific details of the consultation in a dedicated text input field and clicking the "Send" button once the request is complete.

[0127] After receiving the response from the server, the user can check the response on the terminal, and after reading the response, can enter additional questions or comments as needed, and then click the send button to send it to the server.

[0128] After the counseling session is over, the user uses the feedback form to enter their ratings and comments, which are then sent to the server by clicking the "Submit" button.

[0129] Examples of concrete examples and prompts

[0130] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to a natural language processing module (e.g., spaCy), which performs text tokenization, sentiment analysis, and topic extraction. Based on the analysis results, a generative AI model (e.g., OpenAI's GPT-3) generates a response such as, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises." This response is sent to the user's device, and the user can confirm the answer on the display screen. After the session ends, the user sends feedback such as, "The advice was helpful. Thank you."

[0131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0132] Step 1:

[0133] The server receives user authentication information. It receives the username and password sent from the terminal, encrypts the password using the SHA-256 hashing algorithm, and checks it against an entry in the database. The input is the username and password, and the output is the authentication result (success or failure).

[0134] Step 2:

[0135] If the server successfully authenticates the user, it generates a session ID and sends it to the user's device. The session ID is unique and is used to track the user's series of requests. The input is the authentication result and the generated session ID, and the output is the session ID sent to the user.

[0136] Step 3:

[0137] After authentication, the user enters a counseling request on a dedicated input screen. Specifically, the user enters the consultation content and worries in text format and clicks the "Send" button. The input is the text of the consultation content, and the output is a counseling request that is sent to the server.

[0138] Step 4:

[0139] The terminal sends the input counseling request to the server. At this time, the request is encrypted using SSL / TLS. The input is the text of the user's consultation content, and the output is the request sent to the server.

[0140] Step 5:

[0141] The server inputs the received counseling request into a natural language processing (NLP) module. It uses a Python NLP library (e.g., spaCy) to tokenize the text and perform sentiment analysis and topic extraction. The input is the text data of the counseling request, and the output is the tokenized text and analysis results.

[0142] Step 6:

[0143] The server launches a generative AI model (e.g., OpenAI's GPT-3) based on the analysis results of the NLP module. The analysis results are input as prompts to the generative AI model, which then generates an appropriate response. The inputs are the NLP analysis results and the generative AI model's prompts, and the output is the response text generated by the AI.

[0144] Step 7:

[0145] The server sends the generated response text to the user's terminal, encoding it if necessary and formatting it according to the appropriate protocol. The input is the generated response text, and the output is the response data sent to the user's terminal.

[0146] Step 8:

[0147] The terminal displays the received response text to the user. The response content is displayed in a chat box or message display area within the application so that the user can check it. The input is the response text from the server, and the output is the response content that the user checks.

[0148] Step 9:

[0149] After the session is over, the user enters their feedback by entering their rating and comments in a dedicated feedback form and clicking the "Submit" button. The input is the feedback rating and comments, and the output is the feedback data sent to the server.

[0150] Step 10:

[0151] The terminal sends the input feedback to the server. The information is encrypted and transmitted securely to the server. The input is the user's feedback information, and the output is the feedback data sent to the server.

[0152] Step 11:

[0153] The server stores the received feedback in a database. The feedback includes session ratings and comments, and is stored in the database. The input is the user's feedback data, and the output is the stored feedback information.

[0154] Through these steps, this system allows users to easily receive mental health care online and provides appropriate responses based on the content of their consultation. Furthermore, by efficiently collecting and storing feedback, it contributes to improving the quality of the service.

[0155] (Application example 1)

[0156] 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."

[0157] Conventional online counseling systems have limited user experiences, particularly lacking realism and immersion. Even with the use of natural language processing and artificial intelligence, the user interface remains flat and monotonous, limiting the effectiveness of stress reduction and psychological care for users. This can potentially lead to lower user satisfaction.

[0158] 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.

[0159] In this invention, the server includes means for performing user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating an artificial intelligence module for generating an appropriate response based on the analysis result, means for providing the response from the artificial intelligence module to the user, means for receiving and storing feedback from the user, and means including a virtual reality system for providing counseling in a virtual space, thereby enabling the user to experience realistic counseling in a virtual space and receive more effective mental health care.

[0160] "User authentication" is the process of verifying the authenticity of a user when they access a system.

[0161] A "counseling request" is a consultation request that a user provides to the system.

[0162] "Natural language processing" is a technology for analyzing text data and understanding its meaning and emotions.

[0163] An "artificial intelligence module" is a software module for generating appropriate responses based on the results of natural language processing.

[0164] "Feedback" refers to the evaluation or impressions provided by the user after the counseling session has ended.

[0165] A "virtual space" is a virtual environment in which users can immerse themselves using virtual reality technology.

[0166] A "virtual reality system" is a system that allows users to experience a virtual space using a head-mounted display or smartphone.

[0167] This invention is a system that allows users to easily receive mental health care online, and aims to enable users to experience realistic counseling in a virtual space. The system includes a server and a user terminal.

[0168] First, let us explain how the server works. The server has the following main functions:

[0169] 1. User Authentication

[0170] When a user accesses the system, the server performs user authentication to verify the authenticity of the user. Authentication is performed by comparing the login information (user name and password) entered by the user with a database.

[0171] 2. Receiving a Counseling Request

[0172] The server receives a counseling request sent from a user, the request including a consultation content input by the user in text format.

[0173] 3. Natural Language Processing

[0174] The server inputs the received counseling request into a natural language processing module, which uses technology to analyze the text data and understand its meaning and sentiment.

[0175] 4. Launching the AI ​​module

[0176] The server then activates an artificial intelligence module to generate an appropriate response based on the results of the natural language processing analysis. This module generates the optimal answer for the user's inquiry.

[0177] 5. Providing a Response

[0178] The server provides the user with a response generated by the artificial intelligence module, which is in text format and sent to a terminal, which will be described later.

[0179] 6. Receiving and storing feedback

[0180] The server receives feedback from the user after the counseling session, including an evaluation of the session and suggestions for improvement, and stores the feedback in a database.

[0181] Next, we will explain the operation of the terminal. The terminal has the following main functions.

[0182] 1. Sending user authentication information

[0183] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[0184] 2. Submit a Counseling Request

[0185] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[0186] 3. View the response

[0187] The terminal displays the response received from the server to the user, who then checks the response from the AI ​​counselor through a virtual reality system or a text display.

[0188] 4. Submitting Feedback

[0189] The terminal transmits the feedback input by the user to the server after the session ends.

[0190] Specific examples

[0191] For example, if the user enters the following prompt text:

[0192] plaintext

[0193] I've been feeling stressed at work lately. How can I relax?

[0194] The server then uses a natural language processing module to analyze the request and activates an artificial intelligence module to generate an appropriate response.

[0195] plaintext

[0196] There are many ways to relieve stress, but we recommend starting by taking deep breaths and trying relaxation exercises. Regular exercise and dedicating time to a hobby can also be effective.

[0197] The responses are provided to the user through a virtual reality system, where the user can view the responses in a virtual counseling room using a head-mounted display, leading to an even more deeply relaxing experience.

[0198] The hardware used includes a smartphone and a head-mounted display, and the software used is TensorFlow, Transformers (Hugging Face), Pygame, and the OpenAI API.

[0199] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0200] Step 1: User authentication

[0201] The server receives login information (username and password) provided by the user. It compares this data with the registered information in a database and starts a user session if authentication is successful. The input is the username and password, and the output is the authentication result. Specifically, the process involves the user entering login information into a terminal, the terminal sending it to the server, and the server checking it against the database.

[0202] Step 2: Submit a Counseling Request

[0203] The terminal sends the counseling request (text data of the consultation content) entered by the user to the server. The input is the text data of the consultation content, and the output is the result of sending the request to the server. The user enters the consultation content as text into the terminal, and the terminal sends the data to the server.

[0204] Step 3: Natural Language Processing

[0205] The server inputs the received counseling request into a natural language processing (NLP) module. The input is the text data of the counseling request, and the output is the analysis result. Specifically, the NLP module analyzes the text data and extracts its meaning and sentiment.

[0206] Step 4: Launching the Artificial Intelligence Module

[0207] Based on the analysis results of the NLP module, the server activates an artificial intelligence (AI) module to generate the optimal response. The input is the analysis results of the NLP module, and the output is the response generated by the AI ​​module. Specifically, the server calls the AI ​​module, passes the analysis results to the AI ​​module, and the process of generating a response is carried out.

[0208] Step 5: Providing a response

[0209] The server sends the generated response to the user's device. The input is the response generated by the AI ​​module, and the output is the response sent to the user's device. The device displays the received response so that the user can check it. Specifically, the server sends the generated response in text format to the device, and the device displays it on the screen.

[0210] Step 6: Submitting User Feedback

[0211] After the counseling session ends, the terminal sends the feedback entered by the user to the server. The input is the text data of the feedback entered by the user, and the output is the result of that data being saved on the server. The user enters the feedback on the terminal, and the terminal sends the data to the server.

[0212] Step 7: Receive and store feedback

[0213] The server receives the feedback provided by the user and stores it in a database. The input is the feedback data sent from the terminal, and the output is the feedback stored in the database. Specifically, the server adds the feedback received from the terminal to the database.

[0214] This series of steps allows users to have a realistic counseling experience in a virtual space.

[0215] 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.

[0216] This invention is a system that processes a user's counseling request and generates an appropriate response according to the user's emotions by using an emotion engine. The following explains in natural language the specific method for implementing the program for this system and its processing.

[0217] Server Operation

[0218] 1. User Authentication

[0219] The server performs the authentication process to allow a user to log in to the system. Specifically, it receives the login information (username and password) entered by the user, checks that information against a database, and if authentication is successful, generates a user ID and starts a session.

[0220] 2. Receiving a Counseling Request

[0221] The server receives a counseling request sent from a user, which includes the content of the consultation and the worries in text format.

[0222] 3. Application of natural language processing and emotion engine

[0223] The server first inputs the received counseling request into a natural language processing (NLP) module to analyze the topic and emotions of the consultation. In addition, an emotion engine recognizes the user's emotions in detail.

[0224] 4. Launching the AI ​​module

[0225] The server activates an artificial intelligence module to generate an appropriate response based on the analysis results of the NLP module and emotion engine. The artificial intelligence module generates an answer that is optimal for the user's inquiry content and emotions.

[0226] 5. Providing a Response

[0227] The server sends the response generated by the artificial intelligence module to the user, which is in text format and displayed on the user's terminal.

[0228] 6. Receiving and storing feedback and analyzing sentiment

[0229] The server receives feedback from the user after the counseling session ends. The feedback includes an evaluation of the session and suggestions for improvement, and is stored in a database. The server also performs sentiment analysis of the feedback using an emotion engine. The stored feedback and sentiment analysis results are used to improve the service in the future.

[0230] Device behavior

[0231] 1. Sending user authentication information

[0232] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[0233] 2. Submit a Counseling Request

[0234] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[0235] 3. View the response

[0236] The device displays the AI ​​counselor's response received from the server to the user, who can then check the response on the device.

[0237] 4. Submitting Feedback

[0238] The terminal transmits the feedback input by the user to the server after the session ends.

[0239] User Actions

[0240] 1. Log in

[0241] Users log in to the system using a dedicated app or a web browser, entering their username and password on the login screen to complete the authentication process.

[0242] 2. Submit a Counseling Request

[0243] The user inputs a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[0244] 3. Check the response

[0245] The user can check the response from the server on the terminal, and after reading the response, can enter additional questions or comments as needed.

[0246] 4. Providing Feedback

[0247] After the counseling session, the user inputs feedback and sends it to the server, including an evaluation of the session and suggestions for improvement.

[0248] Specific examples

[0249] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to the natural language processing module and emotion engine for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises. This will also help relieve the anxiety you're feeling." This response is sent to the user's device, where the user can confirm the answer. After the session ends, the user sends feedback saying, "The advice was helpful. Thank you," and the emotion engine also analyzes this emotion.

[0250] As described above, this system can implement a series of processes to provide users with mental health care easily and effectively. By combining it with an emotion engine, more personalized responses become possible, improving user satisfaction.

[0251] The processing flow will be explained below.

[0252] Step 1:

[0253] The user launches the app or web browser, accesses the login screen, enters their username and password, and presses the "Login" button.

[0254] Step 2:

[0255] The terminal transmits the login information entered by the user to the server.

[0256] Step 3:

[0257] The server compares the received login information with the database and authenticates the user. If authentication is successful, it generates a user ID and starts a session. It then sends the authentication result to the terminal.

[0258] Step 4:

[0259] The user enters the content of their consultation, such as "I've been feeling stressed at work lately. How can I relax?" into the form for submitting a counseling request and presses the "Submit" button.

[0260] Step 5:

[0261] The terminal transmits the consultation content to the server.

[0262] Step 6:

[0263] The server receives the consultation content and inputs it into the emotion engine and natural language processing (NLP) module. The emotion engine analyzes the user's emotions, and the NLP module analyzes the topic of the consultation content.

[0264] Step 7:

[0265] The server selects an AI counselor module for generating an appropriate response based on the analysis results returned from the emotion engine and the NLP module, and causes the AI ​​counselor to generate an appropriate response.

[0266] Step 8:

[0267] The server receives the response generated by the AI ​​counselor, formats it for the user, and sends the formatted response to the device.

[0268] Step 9:

[0269] The terminal displays the AI ​​counselor's response received from the server to the user.

[0270] Step 10:

[0271] The user checks the AI ​​counselor's response, enters further questions or comments, and presses the "Send" button.

[0272] Step 11:

[0273] The terminal sends the user's additional input to the server.

[0274] Step 12:

[0275] The server again runs the emotion engine and NLP module to analyze the user's additional input. The AI ​​counselor uses this analysis to generate a new response, which the server then sends back to the user.

[0276] Step 13:

[0277] The user presses the "End" button to end the session, enters their impressions and evaluation in the feedback form, and submits it.

[0278] Step 14:

[0279] The terminal transmits feedback information to the server.

[0280] Step 15:

[0281] The server inputs the feedback information into the emotion engine, performs emotion analysis, and stores the results in a database. The analysis results are used to improve the performance of the AI ​​counselor.

[0282] Step 16:

[0283] The server ends the user session and logs the user out.

[0284] Example 2

[0285] 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."

[0286] Conventional counseling systems have difficulty fully understanding users' emotions, resulting in limited quality of responses. Furthermore, they lack a mechanism for effectively utilizing user feedback, making it difficult to continuously improve the quality of their services. Furthermore, the authentication and response generation processes are complex, which can impair user convenience. New technologies are needed to resolve these issues.

[0287] 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.

[0288] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for sentiment analysis of the counseling request, means for activating an artificial intelligence module for generating an appropriate response based on the analysis results, means for generating and inputting a prompt sentence to the artificial intelligence module, means for providing the response from the artificial intelligence module to the user, means for receiving and saving feedback from the user, means for sentiment analysis of the feedback, and means for saving the analysis results in a database. This enables detailed analysis of user sentiment and the provision of personalized responses. Furthermore, by effectively utilizing user feedback, the quality of service can be continuously improved. Furthermore, the authentication and response generation processes are simplified, improving user convenience.

[0289] "User authentication means" refers to the means used by a user when logging into a system, and includes the process of verifying a user name and password against a database to perform authentication.

[0290] The "counseling request receiving means" is a means for receiving the consultation contents, worries, etc. sent by the user in text format.

[0291] The "natural language processing analysis means" is a means used to analyze a counseling request and understand the topic and intent of its content. Specifically, the text is analyzed using natural language processing technology.

[0292] The "emotion analysis means" is a means for analyzing the user's emotions in detail from the text of the counseling request or feedback. The emotional state of the user is understood by using the emotion engine.

[0293] The "artificial intelligence module activation means" is a means for activating an artificial intelligence module for generating an appropriate response based on the results of natural language processing and sentiment analysis.

[0294] The "prompt sentence generating means" is a means for generating a prompt sentence to be input to the artificial intelligence module.

[0295] The "response providing means" is a means for providing the user with a response generated by the artificial intelligence module, and has the role of transmitting the response to the user's terminal.

[0296] The "feedback receiving and storing means" is a means for receiving feedback from the user after the counseling session and storing it in a database.

[0297] The "feedback emotion analysis means" is a means for analyzing the user's emotion from the text of the received feedback.

[0298] The "analysis result storage means" is a means for storing the results of natural language processing and sentiment analysis in a database.

[0299] MODE FOR CARRYING OUT THE INVENTION

[0300] The present invention provides a system for processing a user's counseling request and generating an appropriate response according to the user's emotions by using an emotion engine. Specific embodiments for carrying out the invention will be described in detail below.

[0301] Server Operation

[0302] 1. The server executes the authentication process for the user to log in to the system. Specifically, it receives the login information (username and password) entered by the user and checks that information against the database. A MySQL database is used for authentication. If authentication is successful, a user ID is generated and a session is started. If authentication is successful, a JWT token is generated and used for session management along with the user ID.

[0303] 2. The server receives a counseling request sent by the user. The request contains the consultation content and concerns in text format. This information is received through a REST API built using Python and Flask. The request content is temporarily stored in an in-memory database such as Redis.

[0304] 3. The server first inputs the received counseling request into a natural language processing (NLP) module to analyze the topic and sentiment of the consultation. The specific NLP module used is spaCy or a Transformer-based model (e.g., BERT). The analysis results are stored in an internal data structure (e.g., Pandas DataFrame). Next, the emotion engine uses IBM Watson's Natural Language Understanding API to recognize the user's sentiment in detail.

[0305] 4. The server launches an artificial intelligence module to generate an appropriate response based on the analysis results of the natural language processing module and the emotion engine. Specific generative AI models used are GPT-3 and BERT. In this process, a prompt sentence is generated and input into the generative AI model. The generated response is then stored in the internal data structure.

[0306] 5. The server sends the response generated by the AI ​​module to the user's device. The response is in text format and is sent to the user's device as an HTTP response using the Flask framework.

[0307] 6. The server receives feedback from the user after the counseling session ends. The feedback includes a session evaluation and suggestions for improvement, and stores it in a MySQL database. It also performs sentiment analysis of the feedback using an emotion engine and stores the results in the database.

[0308] Device behavior

[0309] 1. The device sends the login information entered by the user to the server. The user interface is created using JavaScript or Swift, and the information is sent securely using HTTPS. The server receives the authentication result, and if authentication is successful, the device proceeds to the next step.

[0310] 2. The device sends the consultation details entered by the user to the server. The input form is displayed using JavaScript or Swift, and the entered details are sent to the server via HTTPS.

[0311] 3. The device displays the AI ​​counselor's response received from the server to the user. The received response is displayed on the screen, allowing the user to check its content.

[0312] 4. After the session ends, the device sends the feedback entered by the user to the server by displaying a feedback input form and sending it to the server via HTTPS.

[0313] User Actions

[0314] 1. A user logs into the system using a dedicated app or a web browser, enters their username and password on the login screen, and completes the authentication process.

[0315] 2. The user enters a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[0316] 3. The user checks the response from the server on the terminal. After reading the response, the user can enter additional questions or comments as needed.

[0317] 4. After the counseling session, the user enters feedback and sends it to the server. The feedback includes an evaluation of the session and suggestions for improvement.

[0318] Specific examples

[0319] For example, consider the case where a user sends a counseling request saying, "I've been feeling stressed at work lately. What can I do to relax?" The server passes this request to the natural language processing module and emotion engine for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises. This will also help relieve the anxiety you're feeling." This response is sent to the user's device, and the user confirms the answer. After the session ends, the user sends feedback saying, "The advice was helpful. Thank you," and this emotion is also analyzed by the emotion engine.

[0320] Prompt Sentence Examples

[0321] By inputting the following prompt sentence to the generative AI model, you can get a response like the example above:

[0322] A user sent the following counseling request: "I've been feeling stressed at work lately. How can I relax?"

[0323] Generate an appropriate response in natural language, taking into account the user's feelings and the context of their inquiry.

[0324] This system specifically implements the process of providing emotional care to users. By combining an emotion engine with a generative AI model, it is possible to provide personalized responses according to individual needs, thereby improving user satisfaction.

[0325] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0326] Step 1: User enters login information

[0327] Input: Username and Password

[0328] Process: The user logs in to the system using a dedicated app or a web browser. They enter their username and password on the login screen and press the "Login" button. This action causes the device to send the entered information to the server using the HTTPS protocol.

[0329] Output: Login information sent to the server

[0330] Step 2: The server authenticates the user

[0331] Input: User login information

[0332] Processing: The server checks the received login information against its database. It queries the MySQL database for the username and password. If authentication is successful, it generates a user ID and issues a JWT token.

[0333] Output: Authentication result (success / failure), user ID, JWT token (if authentication is successful)

[0334] Step 3: User enters counseling request

[0335] Input: Text of consultation content or worries

[0336] Processing: After successful authentication, the user enters a counseling request into the system. They enter the specific details of their consultation and concerns in text format and press the "Send" button. This operation causes the device to send the input request to the server.

[0337] Output: Counseling request sent to the server

[0338] Step 4: The server receives the counseling request

[0339] Input: Counseling Request

[0340] Processing: The server receives the counseling request sent by the user and temporarily stores it in a data store (e.g., Redis).

[0341] Output: Counseling request saved in temporary store

[0342] Step 5: The server performs natural language processing

[0343] Input: Counseling Request

[0344] Processing: The server inputs the received counseling request into a natural language processing (NLP) module, using spaCy or a Transformer-based model (e.g., BERT) to analyze the text for topic and sentiment.

[0345] Output: Parsed topics and sentiment data

[0346] Step 6: The server performs sentiment analysis

[0347] Input: Counseling Request

[0348] Processing: Based on the analysis results of the NLP module, the server uses IBM Watson's Natural Language Understanding API to perform sentiment analysis using the emotion engine.

[0349] Output: Detailed sentiment analysis data

[0350] Step 7: The server generates a prompt and launches the AI ​​module.

[0351] Input: Parsed topic and sentiment data

[0352] Processing: The server generates a prompt based on the analysis results and inputs it into a generative AI model (e.g., GPT-3, BERT) to generate an appropriate response to the user's counseling request.

[0353] Output: The response generated by the generative AI model

[0354] Step 8: The server generates a response and provides it to the user.

[0355] Input: The response generated by the generative AI model

[0356] Processing: The server generates a response and sends it to the user's device as an HTTP response. The Flask framework is used to build the response and send it to the device.

[0357] Output: The response displayed on the user's terminal

[0358] Step 9: User confirms response

[0359] Input: Response from the server

[0360] Processing: The user checks the response from the server on the terminal. They can read the displayed response and enter additional questions or comments as needed.

[0361] Output: User understanding and satisfaction

[0362] Step 10: User enters feedback

[0363] Input: Session rating and improvement suggestions

[0364] Processing: After the counseling session ends, the user inputs feedback and presses the "Send" button. This operation causes the terminal to send the feedback to the server.

[0365] Output: Feedback sent to the server

[0366] Step 11: Server receives and stores feedback

[0367] Input: User feedback

[0368] Processing: The server receives the feedback sent by the user and stores it in a MySQL database.

[0369] Output: Feedback stored in a database

[0370] Step 12: The server performs sentiment analysis of the feedback

[0371] Input: User feedback

[0372] Processing: The server uses an emotion engine (IBM Watson NLU) to analyze the sentiment of the feedback, and stores the results of this analysis in the database.

[0373] Output: Parsed feedback sentiment data

[0374] Through these processing steps, this invention is a system that can effectively provide psychological care to users. By performing appropriate data processing and calculations at each step, it is possible to provide personalized, high-quality responses.

[0375] (Application example 2)

[0376] 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."

[0377] Conventional counseling systems have difficulty responding in real time to the user's individual emotions and consultation content, and there have been problems, particularly in brick-and-mortar stores, where customer service staff are unable to properly grasp the customer's emotions and respond immediately.In addition, there has been a lack of means to analyze the content of conversations with customers and provide optimal responses based on that analysis, so an effective method for improving customer satisfaction has been sought.

[0378] 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.

[0379] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating an artificial intelligence module for generating an appropriate response based on the analysis result, means for providing the response from the artificial intelligence module to the user, means for receiving and storing feedback from the user, visualization means for providing the analyzed response to staff in a physical store in real time, and analysis means for analyzing conversations with customers in real time and providing the analysis result to staff. This enables immediate and appropriate responses according to customer emotions and the content of the consultation, even in physical stores, thereby improving customer satisfaction.

[0380] 1. "User authentication" is the process of verifying the authentication information (e.g., username and password) required for a user to access a system and confirming that the user is a legitimate user.

[0381] 2. A "counseling request" is an act in which a user inputs the details of their consultation or concerns into the system and transmits that information to the system.

[0382] 3. "Natural language processing" is a set of computer processing techniques for analyzing text data and understanding its meaning and intent.

[0383] 4. "Artificial Intelligence Module" means a program module for generating optimal responses based on the results of natural language processing.

[0384] 5. "Feedback" refers to opinions and evaluations of users regarding the systems and services provided, which are used to improve the systems.

[0385] 6. "Visualization means" refers to the means of displaying analyzed data and information in a form that can be visually confirmed by staff and users.

[0386] 7. "Real-time analysis" refers to an analysis method that processes input data immediately and provides results quickly.

[0387] 8. "Response" refers to the answer or instruction generated by the system to the user or staff.

[0388] A system for implementing this invention includes means for authenticating a user, receiving a counseling request, analyzing it using natural language processing, generating a response using an artificial intelligence module, providing the response, receiving and storing feedback, and visualizing the analyzed response to store staff in real time.

[0389] Server Operation

[0390] The server first authenticates the user by receiving the authentication information (user name and password) used by the user to log in to the system and verifying it against a database.

[0391] Next, a counseling request is received from the user. The request contains the consultation details and worries entered by the user in text format, and is sent to the system.

[0392] The server passes the received request to a natural language processing module, which analyzes the topic and sentiment of the consultation. It then combines this with an emotion engine to perform detailed recognition of the user's emotions.

[0393] Based on the analysis results, an artificial intelligence module is activated to generate the optimal response, which is displayed in real time on smart glasses or other devices worn by store staff.

[0394] After the session ends, the server receives feedback from the user and stores it in a database. The feedback includes an evaluation of the session and suggestions for improvement, and also performs sentiment analysis using an emotion engine.

[0395] Device behavior

[0396] The terminal sends the login information entered by the user to the server and receives the authentication result. Next, it sends the counseling request entered by the user to the server. The response received from the server is then displayed to the user. The user can check the response on the terminal. After the session ends, the feedback entered by the user is also sent from the terminal to the server.

[0397] Smart glasses and other devices used by store staff will analyze conversations with customers in real time and display the results, allowing staff to respond optimally to customers' emotions.

[0398] User Actions

[0399] The user logs in to the system using a dedicated app or web browser, enters their username and password on the login screen, then enters their counseling request on the system and presses the send button.

[0400] The response from the server can be viewed on the terminal, and additional questions or comments can be entered as needed. After the session ends, the user can enter an evaluation of the counseling session and suggestions for improvement, and submit them as feedback.

[0401] Specific examples

[0402] For example, if a customer asks, "I'm looking for a new smartphone. Which one is the most popular?", the staff wearing the smart glasses will analyze the question in real time and provide detailed information, including sentiment analysis. Based on this analysis information, the smart glasses' display will show a response such as, "The XX model is popular these days. Its camera function is particularly excellent, and it has been well received by many customers."

[0403] Prompt Sentence Examples

[0404] "When a customer says, 'I'm looking for a new phone. Which one is the most popular?'"

[0405] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0406] Step 1:

[0407] The server performs user authentication. It receives the username and password entered by the user and checks the information against a database. If authentication is successful, it generates a user ID and starts a session. The input is the user's authentication information, and the output is the user ID and session information.

[0408] Step 2:

[0409] The server receives a counseling request from the user. The user inputs the consultation content and worries in text format from the terminal and sends it. The server receives this text data. The input is the user's text data, and the output is the text data to be analyzed.

[0410] Step 3:

[0411] The server analyzes the counseling request using a natural language processing module. The analysis first extracts topics and emotions from the text data, and then uses an emotion engine to recognize the user's emotions in detail. The input is the text data to be analyzed, and the output is the topic and emotion information.

[0412] Step 4:

[0413] The server then activates an AI module based on the analysis results to generate an appropriate response. The AI ​​module uses the previously obtained topic and emotional information as input and generates the optimal response. The input is the topic and emotional information, and the output is the generated response text.

[0414] Step 5:

[0415] The server sends the response generated by the AI ​​module to the user terminal, where the user can check the response content on the terminal. The input is the generated response text, and the output is the response display on the user terminal.

[0416] Step 6:

[0417] The server receives feedback from the user after the counseling session ends and stores the information in a database. The server then analyzes the feedback using an emotion engine. The input is the user's feedback, and the output is the emotion analysis results and the stored data.

[0418] Step 7:

[0419] The terminal allows store staff to receive questions and requests from customers in real time and displays the analysis results. Speech is converted into text using speech recognition technology and input into a natural language processing module. The input is the customer's voice data, and the output is a display of the analysis results.

[0420] 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.

[0421] 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.

[0422] 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.

[0423] [Second embodiment]

[0424] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0425] 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.

[0426] 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).

[0427] 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.

[0428] 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.

[0429] 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).

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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.

[0435] 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."

[0436] This invention is a system that allows users to easily receive mental health care online. The following explanation describes the specific method for implementing the program for this system and its processing in natural language.

[0437] Server Operation

[0438] 1. User Authentication

[0439] The server performs the authentication process to allow a user to log in to the system. Specifically, it receives the login information (username and password) entered by the user and checks it against a database. If authentication is successful, a user session begins.

[0440] 2. Receiving a Counseling Request

[0441] The server receives a counseling request sent from a user, which includes the content of the consultation and the worries in text format.

[0442] 3. Natural Language Processing

[0443] The server inputs the received counseling request into a natural language processing (NLP) module, which analyzes the consultation content and classifies topics and emotions.

[0444] 4. Launching the AI ​​module

[0445] The server then activates an artificial intelligence module to generate an appropriate response based on the analysis results of the NLP module. The artificial intelligence module generates an answer that is optimal for the user's inquiry.

[0446] 5. Providing a Response

[0447] The server sends the response generated by the artificial intelligence module to the user, which is in text format and displayed on the user's terminal.

[0448] 6. Receiving and storing feedback

[0449] The server receives feedback from the user after the counseling session. The feedback includes an evaluation of the session and suggestions for improvement, and stores it in a database. The stored feedback is used to improve the service in the future.

[0450] Device behavior

[0451] 1. Sending user authentication information

[0452] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[0453] 2. Submit a Counseling Request

[0454] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[0455] 3. View the response

[0456] The terminal displays the response received from the server to the user, who can then check the response content on the terminal.

[0457] 4. Submitting Feedback

[0458] The terminal transmits the feedback input by the user to the server after the session ends.

[0459] User Actions

[0460] 1. Log in

[0461] Users log in to the system using a dedicated app or a web browser, entering their username and password on the login screen to complete the authentication process.

[0462] 2. Submit a Counseling Request

[0463] The user inputs a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[0464] 3. Check the response

[0465] The user can check the response from the server on the terminal, and after reading the response, can enter additional questions or comments as needed.

[0466] 4. Providing Feedback

[0467] After the counseling session, the user inputs feedback and sends it to the server, including an evaluation of the session and suggestions for improvement.

[0468] Specific examples

[0469] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to the natural language processing module for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises." This response is sent to the user's device, where the user can confirm the answer. After the session ends, the user sends feedback saying, "Your advice was helpful. Thank you."

[0470] As described above, this system can implement a series of processes to provide users with mental care easily and effectively.

[0471] The processing flow will be explained below.

[0472] Step 1:

[0473] The user launches the app or web browser, accesses the login screen, enters their username and password, and presses the "Login" button.

[0474] Step 2:

[0475] The terminal transmits the login information entered by the user to the server.

[0476] Step 3:

[0477] The server compares the received login information with the database and authenticates the user. If authentication is successful, it generates a user ID and starts a session. It then sends the authentication result to the terminal.

[0478] Step 4:

[0479] The user enters the content of their consultation, such as "I've been feeling stressed at work lately. How can I relax?" into the form for submitting a counseling request and presses the "Submit" button.

[0480] Step 5:

[0481] The terminal transmits the consultation content to the server.

[0482] Step 6:

[0483] The server receives the consultation content and prepares to launch the AI ​​counselor. The consultation content is input into a natural language processing (NLP) module and topic analysis is performed.

[0484] Step 7:

[0485] The server selects an AI counselor to generate an appropriate response based on the analysis results returned from the NLP module, and causes the AI ​​counselor to generate the appropriate response.

[0486] Step 8:

[0487] The server receives the response generated by the AI ​​counselor, formats it for the user, and sends the formatted response to the device.

[0488] Step 9:

[0489] The terminal displays the AI ​​counselor's response received from the server to the user.

[0490] Step 10:

[0491] The user checks the AI ​​counselor's response, enters further questions or comments, and presses the "Send" button.

[0492] Step 11:

[0493] The terminal sends the user's additional input to the server.

[0494] Step 12:

[0495] The server again has the AI ​​counselor process the user's additional input, generate a new response, and send it back to the user.

[0496] Step 13:

[0497] The user presses the "End" button to end the session, enters their impressions and evaluation in the feedback form, and submits it.

[0498] Step 14:

[0499] The terminal transmits feedback information to the server.

[0500] Step 15:

[0501] The server receives the feedback information, stores it in a database, and analyzes it to help improve the performance of the AI ​​counselor.

[0502] Step 16:

[0503] The server ends the user session and logs the user out.

[0504] Example 1

[0505] 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."

[0506] There is a need for a system that can respond quickly and appropriately to users' needs for easy online mental health care. However, conventional systems have difficulty accurately understanding the content of users' consultations and providing appropriate advice. Furthermore, they lack a mechanism for efficiently collecting feedback from users and using it to improve services. An effective system is needed to solve these issues.

[0507] 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.

[0508] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating a generative AI model for generating an appropriate response based on the analysis results, means for providing the response from the generative AI model to the user, and means for receiving and storing feedback from the user. This allows users to easily receive mental health care online, and the system can generate and provide appropriate responses based on the user's consultation content. Furthermore, efficiently collecting and storing feedback can contribute to improving the quality of services.

[0509] A "means for user authentication" is a mechanism that receives login information (user name and password) entered by a user and verifies the user's identity by comparing it with a database.

[0510] The "means for receiving a counseling request" is a function for receiving the consultation content entered by the user in text format.

[0511] "Means for analyzing counseling requests using natural language processing" refers to a system that uses natural language processing technology to analyze the content of the consultation received, understand the content, and classify it.

[0512] "Means for launching a generative AI model" refers to a function that launches and utilizes an artificial intelligence model to generate an appropriate response to the user's inquiry based on the analysis results of natural language processing.

[0513] The "means for providing a response from the generative AI model to a user" is a mechanism for sending and displaying a text response generated by an artificial intelligence model on a user's device.

[0514] "Means for receiving and storing feedback" is a function that receives evaluations and comments sent by users after the counseling session and stores them in a database.

[0515] This invention is a system that allows users to easily receive mental health care online. This system is realized using the following means. The operations of the user, terminal, and server will be described in detail below.

[0516] Server Operation

[0517] The server first authenticates the user. It receives the login information (username and password) entered by the user, encrypts it using the SHA-256 hash algorithm, and then checks it against the database. If authentication is successful, the server generates a session ID and sends it to the user.

[0518] Next, the server receives a counseling request from the user. The request contains the user's concerns and the details of the consultation in text format. This text is processed using a Python natural language processing library (e.g., spaCy). Specifically, the text is tokenized, sentiment analyzed, and topic extracted.

[0519] Based on the analysis results, the server launches a generative AI model (e.g., OpenAI's GPT-3), which generates an appropriate response to the user's inquiry based on the prompt. The generated response is returned to the server in text format.

[0520] The server generates a text response and sends it to the user's terminal, where it is encoded and formatted according to the appropriate protocol before being served to the user.

[0521] Finally, the server receives feedback from users after the counseling session and stores it in a database, including session ratings and comments, to improve the quality of the service.

[0522] Device behavior

[0523] The terminal first sends the login information entered by the user to the server. The information is encrypted using SSL / TLS. After the authentication result is returned from the server, if the authentication is successful, the terminal proceeds to the next step.

[0524] Next, the terminal sends the counseling request entered by the user in text format to the server, waits for a response from the server, and displays the received response to the user in a chat box or message display area within the application.

[0525] After the counseling session is over, the terminal sends the feedback entered by the user to the server. The feedback is entered through the GUI and sent to the server.

[0526] User Actions

[0527] Users log in to the system using a dedicated application or a web browser. They enter their username and password on the login screen and click the "Login" button.

[0528] Next, the user enters a counseling request by entering the specific details of the consultation in a dedicated text input field and clicking the "Send" button once the request is complete.

[0529] After receiving the response from the server, the user can check the response on the terminal, and after reading the response, can enter additional questions or comments as needed, and then click the send button to send it to the server.

[0530] After the counseling session is over, the user uses the feedback form to enter their ratings and comments, which are then sent to the server by clicking the "Submit" button.

[0531] Examples of concrete examples and prompts

[0532] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to a natural language processing module (e.g., spaCy), which performs text tokenization, sentiment analysis, and topic extraction. Based on the analysis results, a generative AI model (e.g., OpenAI's GPT-3) generates a response such as, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises." This response is sent to the user's device, and the user can confirm the answer on the display screen. After the session ends, the user sends feedback such as, "The advice was helpful. Thank you."

[0533] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0534] Step 1:

[0535] The server receives user authentication information. It receives the username and password sent from the terminal, encrypts the password using the SHA-256 hashing algorithm, and checks it against an entry in the database. The input is the username and password, and the output is the authentication result (success or failure).

[0536] Step 2:

[0537] If the server successfully authenticates the user, it generates a session ID and sends it to the user's device. The session ID is unique and is used to track the user's series of requests. The input is the authentication result and the generated session ID, and the output is the session ID sent to the user.

[0538] Step 3:

[0539] After authentication, the user enters a counseling request on a dedicated input screen. Specifically, the user enters the consultation content and worries in text format and clicks the "Send" button. The input is the text of the consultation content, and the output is a counseling request that is sent to the server.

[0540] Step 4:

[0541] The terminal sends the input counseling request to the server. At this time, the request is encrypted using SSL / TLS. The input is the text of the user's consultation content, and the output is the request sent to the server.

[0542] Step 5:

[0543] The server inputs the received counseling request into a natural language processing (NLP) module. It uses a Python NLP library (e.g., spaCy) to tokenize the text and perform sentiment analysis and topic extraction. The input is the text data of the counseling request, and the output is the tokenized text and analysis results.

[0544] Step 6:

[0545] The server launches a generative AI model (e.g., OpenAI's GPT-3) based on the analysis results of the NLP module. The analysis results are input as prompts to the generative AI model, which then generates an appropriate response. The inputs are the NLP analysis results and the generative AI model's prompts, and the output is the response text generated by the AI.

[0546] Step 7:

[0547] The server sends the generated response text to the user's terminal, encoding it if necessary and formatting it according to the appropriate protocol. The input is the generated response text, and the output is the response data sent to the user's terminal.

[0548] Step 8:

[0549] The terminal displays the received response text to the user. The response content is displayed in a chat box or message display area within the application so that the user can check it. The input is the response text from the server, and the output is the response content that the user checks.

[0550] Step 9:

[0551] After the session is over, the user enters their feedback by entering their rating and comments in a dedicated feedback form and clicking the "Submit" button. The input is the feedback rating and comments, and the output is the feedback data sent to the server.

[0552] Step 10:

[0553] The terminal sends the input feedback to the server. The information is encrypted and transmitted securely to the server. The input is the user's feedback information, and the output is the feedback data sent to the server.

[0554] Step 11:

[0555] The server stores the received feedback in a database. The feedback includes session ratings and comments, and is stored in the database. The input is the user's feedback data, and the output is the stored feedback information.

[0556] Through these steps, this system allows users to easily receive mental health care online and provides appropriate responses based on the content of their consultation. Furthermore, by efficiently collecting and storing feedback, it contributes to improving the quality of the service.

[0557] (Application example 1)

[0558] 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."

[0559] Conventional online counseling systems have limited user experiences, particularly lacking realism and immersion. Even with the use of natural language processing and artificial intelligence, the user interface remains flat and monotonous, limiting the effectiveness of stress reduction and psychological care for users. This can potentially lead to lower user satisfaction.

[0560] 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.

[0561] In this invention, the server includes means for performing user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating an artificial intelligence module for generating an appropriate response based on the analysis result, means for providing the response from the artificial intelligence module to the user, means for receiving and storing feedback from the user, and means including a virtual reality system for providing counseling in a virtual space, thereby enabling the user to experience realistic counseling in a virtual space and receive more effective mental health care.

[0562] "User authentication" is the process of verifying the authenticity of a user when they access a system.

[0563] A "counseling request" is a consultation request that a user provides to the system.

[0564] "Natural language processing" is a technology for analyzing text data and understanding its meaning and emotions.

[0565] An "artificial intelligence module" is a software module for generating appropriate responses based on the results of natural language processing.

[0566] "Feedback" refers to the evaluation or impressions provided by the user after the counseling session has ended.

[0567] A "virtual space" is a virtual environment in which users can immerse themselves using virtual reality technology.

[0568] A "virtual reality system" is a system that allows users to experience a virtual space using a head-mounted display or smartphone.

[0569] This invention is a system that allows users to easily receive mental health care online, and aims to enable users to experience realistic counseling in a virtual space. The system includes a server and a user terminal.

[0570] First, let us explain how the server works. The server has the following main functions:

[0571] 1. User Authentication

[0572] When a user accesses the system, the server performs user authentication to verify the authenticity of the user. Authentication is performed by comparing the login information (user name and password) entered by the user with a database.

[0573] 2. Receiving a Counseling Request

[0574] The server receives a counseling request sent from a user, the request including a consultation content input by the user in text format.

[0575] 3. Natural Language Processing

[0576] The server inputs the received counseling request into a natural language processing module, which uses technology to analyze the text data and understand its meaning and sentiment.

[0577] 4. Launching the AI ​​module

[0578] The server then activates an artificial intelligence module to generate an appropriate response based on the results of the natural language processing analysis. This module generates the optimal answer for the user's inquiry.

[0579] 5. Providing a Response

[0580] The server provides the user with a response generated by the artificial intelligence module, which is in text format and sent to a terminal, which will be described later.

[0581] 6. Receiving and storing feedback

[0582] The server receives feedback from the user after the counseling session, including an evaluation of the session and suggestions for improvement, and stores the feedback in a database.

[0583] Next, we will explain the operation of the terminal. The terminal has the following main functions.

[0584] 1. Sending user authentication information

[0585] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[0586] 2. Submit a Counseling Request

[0587] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[0588] 3. View the response

[0589] The terminal displays the response received from the server to the user, who then checks the response from the AI ​​counselor through a virtual reality system or a text display.

[0590] 4. Submitting Feedback

[0591] The terminal transmits the feedback input by the user to the server after the session ends.

[0592] Specific examples

[0593] For example, if the user enters the following prompt text:

[0594] plaintext

[0595] I've been feeling stressed at work lately. How can I relax?

[0596] The server then uses a natural language processing module to analyze the request and activates an artificial intelligence module to generate an appropriate response.

[0597] plaintext

[0598] There are many ways to relieve stress, but we recommend starting by taking deep breaths and trying relaxation exercises. Regular exercise and dedicating time to a hobby can also be effective.

[0599] The responses are provided to the user through a virtual reality system, where the user can view the responses in a virtual counseling room using a head-mounted display, leading to an even more deeply relaxing experience.

[0600] The hardware used includes a smartphone and a head-mounted display, and the software used is TensorFlow, Transformers (Hugging Face), Pygame, and the OpenAI API.

[0601] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0602] Step 1: User authentication

[0603] The server receives login information (username and password) provided by the user. It compares this data with the registered information in a database and starts a user session if authentication is successful. The input is the username and password, and the output is the authentication result. Specifically, the process involves the user entering login information into a terminal, the terminal sending it to the server, and the server checking it against the database.

[0604] Step 2: Submit a Counseling Request

[0605] The terminal sends the counseling request (text data of the consultation content) entered by the user to the server. The input is the text data of the consultation content, and the output is the result of sending the request to the server. The user enters the consultation content as text into the terminal, and the terminal sends the data to the server.

[0606] Step 3: Natural Language Processing

[0607] The server inputs the received counseling request into a natural language processing (NLP) module. The input is the text data of the counseling request, and the output is the analysis result. Specifically, the NLP module analyzes the text data and extracts its meaning and sentiment.

[0608] Step 4: Launching the Artificial Intelligence Module

[0609] Based on the analysis results of the NLP module, the server activates an artificial intelligence (AI) module to generate the optimal response. The input is the analysis results of the NLP module, and the output is the response generated by the AI ​​module. Specifically, the server calls the AI ​​module, passes the analysis results to the AI ​​module, and the process of generating a response is carried out.

[0610] Step 5: Providing a response

[0611] The server sends the generated response to the user's device. The input is the response generated by the AI ​​module, and the output is the response sent to the user's device. The device displays the received response so that the user can check it. Specifically, the server sends the generated response in text format to the device, and the device displays it on the screen.

[0612] Step 6: Submitting User Feedback

[0613] After the counseling session ends, the terminal sends the feedback entered by the user to the server. The input is the text data of the feedback entered by the user, and the output is the result of that data being saved on the server. The user enters the feedback on the terminal, and the terminal sends the data to the server.

[0614] Step 7: Receive and store feedback

[0615] The server receives the feedback provided by the user and stores it in a database. The input is the feedback data sent from the terminal, and the output is the feedback stored in the database. Specifically, the server adds the feedback received from the terminal to the database.

[0616] This series of steps allows users to have a realistic counseling experience in a virtual space.

[0617] 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.

[0618] This invention is a system that processes a user's counseling request and generates an appropriate response according to the user's emotions by using an emotion engine. The following explains in natural language the specific method for implementing the program for this system and its processing.

[0619] Server Operation

[0620] 1. User Authentication

[0621] The server performs the authentication process to allow a user to log in to the system. Specifically, it receives the login information (username and password) entered by the user, checks that information against a database, and if authentication is successful, generates a user ID and starts a session.

[0622] 2. Receiving a Counseling Request

[0623] The server receives a counseling request sent from a user, which includes the content of the consultation and the worries in text format.

[0624] 3. Application of natural language processing and emotion engine

[0625] The server first inputs the received counseling request into a natural language processing (NLP) module to analyze the topic and emotions of the consultation. In addition, an emotion engine recognizes the user's emotions in detail.

[0626] 4. Launching the AI ​​module

[0627] The server activates an artificial intelligence module to generate an appropriate response based on the analysis results of the NLP module and emotion engine. The artificial intelligence module generates an answer that is optimal for the user's inquiry content and emotions.

[0628] 5. Providing a Response

[0629] The server sends the response generated by the artificial intelligence module to the user, which is in text format and displayed on the user's terminal.

[0630] 6. Receiving and storing feedback and analyzing sentiment

[0631] The server receives feedback from the user after the counseling session ends. The feedback includes an evaluation of the session and suggestions for improvement, and is stored in a database. The server also performs sentiment analysis of the feedback using an emotion engine. The stored feedback and sentiment analysis results are used to improve the service in the future.

[0632] Device behavior

[0633] 1. Sending user authentication information

[0634] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[0635] 2. Submit a Counseling Request

[0636] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[0637] 3. View the response

[0638] The device displays the AI ​​counselor's response received from the server to the user, who can then check the response on the device.

[0639] 4. Submitting Feedback

[0640] The terminal transmits the feedback input by the user to the server after the session ends.

[0641] User Actions

[0642] 1. Log in

[0643] Users log in to the system using a dedicated app or a web browser, entering their username and password on the login screen to complete the authentication process.

[0644] 2. Submit a Counseling Request

[0645] The user inputs a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[0646] 3. Check the response

[0647] The user can check the response from the server on the terminal, and after reading the response, can enter additional questions or comments as needed.

[0648] 4. Providing Feedback

[0649] After the counseling session, the user inputs feedback and sends it to the server, including an evaluation of the session and suggestions for improvement.

[0650] Specific examples

[0651] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to the natural language processing module and emotion engine for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises. This will also help relieve the anxiety you're feeling." This response is sent to the user's device, where the user can confirm the answer. After the session ends, the user sends feedback saying, "The advice was helpful. Thank you," and the emotion engine also analyzes this emotion.

[0652] As described above, this system can implement a series of processes to provide users with mental health care easily and effectively. By combining it with an emotion engine, more personalized responses become possible, improving user satisfaction.

[0653] The processing flow will be explained below.

[0654] Step 1:

[0655] The user launches the app or web browser, accesses the login screen, enters their username and password, and presses the "Login" button.

[0656] Step 2:

[0657] The terminal transmits the login information entered by the user to the server.

[0658] Step 3:

[0659] The server compares the received login information with the database and authenticates the user. If authentication is successful, it generates a user ID and starts a session. It then sends the authentication result to the terminal.

[0660] Step 4:

[0661] The user enters the content of their consultation, such as "I've been feeling stressed at work lately. How can I relax?" into the form for submitting a counseling request and presses the "Submit" button.

[0662] Step 5:

[0663] The terminal transmits the consultation content to the server.

[0664] Step 6:

[0665] The server receives the consultation content and inputs it into the emotion engine and natural language processing (NLP) module. The emotion engine analyzes the user's emotions, and the NLP module analyzes the topic of the consultation content.

[0666] Step 7:

[0667] The server selects an AI counselor module for generating an appropriate response based on the analysis results returned from the emotion engine and the NLP module, and causes the AI ​​counselor to generate an appropriate response.

[0668] Step 8:

[0669] The server receives the response generated by the AI ​​counselor, formats it for the user, and sends the formatted response to the device.

[0670] Step 9:

[0671] The terminal displays the AI ​​counselor's response received from the server to the user.

[0672] Step 10:

[0673] The user checks the AI ​​counselor's response, enters further questions or comments, and presses the "Send" button.

[0674] Step 11:

[0675] The terminal sends the user's additional input to the server.

[0676] Step 12:

[0677] The server again runs the emotion engine and NLP module to analyze the user's additional input. The AI ​​counselor uses this analysis to generate a new response, which the server then sends back to the user.

[0678] Step 13:

[0679] The user presses the "End" button to end the session, enters their impressions and evaluation in the feedback form, and submits it.

[0680] Step 14:

[0681] The terminal transmits feedback information to the server.

[0682] Step 15:

[0683] The server inputs the feedback information into the emotion engine, performs emotion analysis, and stores the results in a database. The analysis results are used to improve the performance of the AI ​​counselor.

[0684] Step 16:

[0685] The server ends the user session and logs the user out.

[0686] Example 2

[0687] 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."

[0688] Conventional counseling systems have difficulty fully understanding users' emotions, resulting in limited quality of responses. Furthermore, they lack a mechanism for effectively utilizing user feedback, making it difficult to continuously improve the quality of their services. Furthermore, the authentication and response generation processes are complex, which can impair user convenience. New technologies are needed to resolve these issues.

[0689] 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.

[0690] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for sentiment analysis of the counseling request, means for activating an artificial intelligence module for generating an appropriate response based on the analysis results, means for generating and inputting a prompt sentence to the artificial intelligence module, means for providing the response from the artificial intelligence module to the user, means for receiving and saving feedback from the user, means for sentiment analysis of the feedback, and means for saving the analysis results in a database. This enables detailed analysis of user sentiment and the provision of personalized responses. Furthermore, by effectively utilizing user feedback, the quality of service can be continuously improved. Furthermore, the authentication and response generation processes are simplified, improving user convenience.

[0691] "User authentication means" refers to the means used by a user when logging into a system, and includes the process of verifying a user name and password against a database to perform authentication.

[0692] The "counseling request receiving means" is a means for receiving the consultation contents, worries, etc. sent by the user in text format.

[0693] The "natural language processing analysis means" is a means used to analyze a counseling request and understand the topic and intent of its content. Specifically, the text is analyzed using natural language processing technology.

[0694] The "emotion analysis means" is a means for analyzing the user's emotions in detail from the text of the counseling request or feedback. The emotional state of the user is understood by using the emotion engine.

[0695] The "artificial intelligence module activation means" is a means for activating an artificial intelligence module for generating an appropriate response based on the results of natural language processing and sentiment analysis.

[0696] The "prompt sentence generating means" is a means for generating a prompt sentence to be input to the artificial intelligence module.

[0697] The "response providing means" is a means for providing the user with a response generated by the artificial intelligence module, and has the role of transmitting the response to the user's terminal.

[0698] The "feedback receiving and storing means" is a means for receiving feedback from the user after the counseling session and storing it in a database.

[0699] The "feedback emotion analysis means" is a means for analyzing the user's emotion from the text of the received feedback.

[0700] The "analysis result storage means" is a means for storing the results of natural language processing and sentiment analysis in a database.

[0701] MODE FOR CARRYING OUT THE INVENTION

[0702] The present invention provides a system for processing a user's counseling request and generating an appropriate response according to the user's emotions by using an emotion engine. Specific embodiments for carrying out the invention will be described in detail below.

[0703] Server Operation

[0704] 1. The server executes the authentication process for the user to log in to the system. Specifically, it receives the login information (username and password) entered by the user and checks that information against the database. A MySQL database is used for authentication. If authentication is successful, a user ID is generated and a session is started. If authentication is successful, a JWT token is generated and used for session management along with the user ID.

[0705] 2. The server receives a counseling request sent by the user. The request contains the consultation content and concerns in text format. This information is received through a REST API built using Python and Flask. The request content is temporarily stored in an in-memory database such as Redis.

[0706] 3. The server first inputs the received counseling request into a natural language processing (NLP) module to analyze the topic and sentiment of the consultation. The specific NLP module used is spaCy or a Transformer-based model (e.g., BERT). The analysis results are stored in an internal data structure (e.g., Pandas DataFrame). Next, the emotion engine uses IBM Watson's Natural Language Understanding API to recognize the user's sentiment in detail.

[0707] 4. The server launches an artificial intelligence module to generate an appropriate response based on the analysis results of the natural language processing module and the emotion engine. Specific generative AI models used are GPT-3 and BERT. In this process, a prompt sentence is generated and input into the generative AI model. The generated response is then stored in the internal data structure.

[0708] 5. The server sends the response generated by the AI ​​module to the user's device. The response is in text format and is sent to the user's device as an HTTP response using the Flask framework.

[0709] 6. The server receives feedback from the user after the counseling session ends. The feedback includes a session evaluation and suggestions for improvement, and stores it in a MySQL database. It also performs sentiment analysis of the feedback using an emotion engine and stores the results in the database.

[0710] Device behavior

[0711] 1. The device sends the login information entered by the user to the server. The user interface is created using JavaScript or Swift, and the information is sent securely using HTTPS. The server receives the authentication result, and if authentication is successful, the device proceeds to the next step.

[0712] 2. The device sends the consultation details entered by the user to the server. The input form is displayed using JavaScript or Swift, and the entered details are sent to the server via HTTPS.

[0713] 3. The device displays the AI ​​counselor's response received from the server to the user. The received response is displayed on the screen, allowing the user to check its content.

[0714] 4. After the session ends, the device sends the feedback entered by the user to the server by displaying a feedback input form and sending it to the server via HTTPS.

[0715] User Actions

[0716] 1. A user logs into the system using a dedicated app or a web browser, enters their username and password on the login screen, and completes the authentication process.

[0717] 2. The user enters a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[0718] 3. The user checks the response from the server on the terminal. After reading the response, the user can enter additional questions or comments as needed.

[0719] 4. After the counseling session, the user enters feedback and sends it to the server. The feedback includes an evaluation of the session and suggestions for improvement.

[0720] Specific examples

[0721] For example, consider the case where a user sends a counseling request saying, "I've been feeling stressed at work lately. What can I do to relax?" The server passes this request to the natural language processing module and emotion engine for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises. This will also help relieve the anxiety you're feeling." This response is sent to the user's device, and the user confirms the answer. After the session ends, the user sends feedback saying, "The advice was helpful. Thank you," and this emotion is also analyzed by the emotion engine.

[0722] Prompt Sentence Examples

[0723] By inputting the following prompt sentence to the generative AI model, you can get a response like the example above:

[0724] A user sent the following counseling request: "I've been feeling stressed at work lately. How can I relax?"

[0725] Generate an appropriate response in natural language, taking into account the user's feelings and the context of their inquiry.

[0726] This system specifically implements the process of providing emotional care to users. By combining an emotion engine with a generative AI model, it is possible to provide personalized responses according to individual needs, thereby improving user satisfaction.

[0727] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0728] Step 1: User enters login information

[0729] Input: Username and Password

[0730] Process: The user logs in to the system using a dedicated app or a web browser. They enter their username and password on the login screen and press the "Login" button. This action causes the device to send the entered information to the server using the HTTPS protocol.

[0731] Output: Login information sent to the server

[0732] Step 2: The server authenticates the user

[0733] Input: User login information

[0734] Processing: The server checks the received login information against its database. It queries the MySQL database for the username and password. If authentication is successful, it generates a user ID and issues a JWT token.

[0735] Output: Authentication result (success / failure), user ID, JWT token (if authentication is successful)

[0736] Step 3: User enters counseling request

[0737] Input: Text of consultation content or worries

[0738] Processing: After successful authentication, the user enters a counseling request into the system. They enter the specific details of their consultation and concerns in text format and press the "Send" button. This operation causes the device to send the input request to the server.

[0739] Output: Counseling request sent to the server

[0740] Step 4: The server receives the counseling request

[0741] Input: Counseling Request

[0742] Processing: The server receives the counseling request sent by the user and temporarily stores it in a data store (e.g., Redis).

[0743] Output: Counseling request saved in temporary store

[0744] Step 5: The server performs natural language processing

[0745] Input: Counseling Request

[0746] Processing: The server inputs the received counseling request into a natural language processing (NLP) module, using spaCy or a Transformer-based model (e.g., BERT) to analyze the text for topic and sentiment.

[0747] Output: Parsed topics and sentiment data

[0748] Step 6: The server performs sentiment analysis

[0749] Input: Counseling Request

[0750] Processing: Based on the analysis results of the NLP module, the server uses IBM Watson's Natural Language Understanding API to perform sentiment analysis using the emotion engine.

[0751] Output: Detailed sentiment analysis data

[0752] Step 7: The server generates a prompt and launches the AI ​​module.

[0753] Input: Parsed topic and sentiment data

[0754] Processing: The server generates a prompt based on the analysis results and inputs it into a generative AI model (e.g., GPT-3, BERT) to generate an appropriate response to the user's counseling request.

[0755] Output: The response generated by the generative AI model

[0756] Step 8: The server generates a response and provides it to the user.

[0757] Input: The response generated by the generative AI model

[0758] Processing: The server generates a response and sends it to the user's device as an HTTP response. The Flask framework is used to build the response and send it to the device.

[0759] Output: The response displayed on the user's terminal

[0760] Step 9: User confirms response

[0761] Input: Response from the server

[0762] Processing: The user checks the response from the server on the terminal. They can read the displayed response and enter additional questions or comments as needed.

[0763] Output: User understanding and satisfaction

[0764] Step 10: User enters feedback

[0765] Input: Session rating and improvement suggestions

[0766] Processing: After the counseling session ends, the user inputs feedback and presses the "Send" button. This operation causes the terminal to send the feedback to the server.

[0767] Output: Feedback sent to the server

[0768] Step 11: Server receives and stores feedback

[0769] Input: User feedback

[0770] Processing: The server receives the feedback sent by the user and stores it in a MySQL database.

[0771] Output: Feedback stored in a database

[0772] Step 12: The server performs sentiment analysis of the feedback

[0773] Input: User feedback

[0774] Processing: The server uses an emotion engine (IBM Watson NLU) to analyze the sentiment of the feedback, and stores the results of this analysis in the database.

[0775] Output: Parsed feedback sentiment data

[0776] Through these processing steps, this invention is a system that can effectively provide psychological care to users. By performing appropriate data processing and calculations at each step, it is possible to provide personalized, high-quality responses.

[0777] (Application example 2)

[0778] 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."

[0779] Conventional counseling systems have difficulty responding in real time to the user's individual emotions and consultation content, and there have been problems, particularly in brick-and-mortar stores, where customer service staff are unable to properly grasp the customer's emotions and respond immediately.In addition, there has been a lack of means to analyze the content of conversations with customers and provide optimal responses based on that analysis, so an effective method for improving customer satisfaction has been sought.

[0780] 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.

[0781] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating an artificial intelligence module for generating an appropriate response based on the analysis result, means for providing the response from the artificial intelligence module to the user, means for receiving and storing feedback from the user, visualization means for providing the analyzed response to staff in a physical store in real time, and analysis means for analyzing conversations with customers in real time and providing the analysis result to staff. This enables immediate and appropriate responses according to customer emotions and the content of the consultation, even in physical stores, thereby improving customer satisfaction.

[0782] 1. "User authentication" is the process of verifying the authentication information (e.g., username and password) required for a user to access a system and confirming that the user is a legitimate user.

[0783] 2. A "counseling request" is an act in which a user inputs the details of their consultation or concerns into the system and transmits that information to the system.

[0784] 3. "Natural language processing" is a set of computer processing techniques for analyzing text data and understanding its meaning and intent.

[0785] 4. "Artificial Intelligence Module" means a program module for generating optimal responses based on the results of natural language processing.

[0786] 5. "Feedback" refers to opinions and evaluations of users regarding the systems and services provided, which are used to improve the systems.

[0787] 6. "Visualization means" refers to the means of displaying analyzed data and information in a form that can be visually confirmed by staff and users.

[0788] 7. "Real-time analysis" refers to an analysis method that processes input data immediately and provides results quickly.

[0789] 8. "Response" refers to the answer or instruction generated by the system to the user or staff.

[0790] A system for implementing this invention includes means for authenticating a user, receiving a counseling request, analyzing it using natural language processing, generating a response using an artificial intelligence module, providing the response, receiving and storing feedback, and visualizing the analyzed response to store staff in real time.

[0791] Server Operation

[0792] The server first authenticates the user by receiving the authentication information (user name and password) used by the user to log in to the system and verifying it against a database.

[0793] Next, a counseling request is received from the user. The request contains the consultation details and worries entered by the user in text format, and is sent to the system.

[0794] The server passes the received request to a natural language processing module, which analyzes the topic and sentiment of the consultation. It then combines this with an emotion engine to perform detailed recognition of the user's emotions.

[0795] Based on the analysis results, an artificial intelligence module is activated to generate the optimal response, which is displayed in real time on smart glasses or other devices worn by store staff.

[0796] After the session ends, the server receives feedback from the user and stores it in a database. The feedback includes an evaluation of the session and suggestions for improvement, and also performs sentiment analysis using an emotion engine.

[0797] Device behavior

[0798] The terminal sends the login information entered by the user to the server and receives the authentication result. Next, it sends the counseling request entered by the user to the server. The response received from the server is then displayed to the user. The user can check the response on the terminal. After the session ends, the feedback entered by the user is also sent from the terminal to the server.

[0799] Smart glasses and other devices used by store staff will analyze conversations with customers in real time and display the results, allowing staff to respond optimally to customers' emotions.

[0800] User Actions

[0801] The user logs in to the system using a dedicated app or web browser, enters their username and password on the login screen, then enters their counseling request on the system and presses the send button.

[0802] The response from the server can be viewed on the terminal, and additional questions or comments can be entered as needed. After the session ends, the user can enter an evaluation of the counseling session and suggestions for improvement, and submit them as feedback.

[0803] Specific examples

[0804] For example, if a customer asks, "I'm looking for a new smartphone. Which one is the most popular?", the staff wearing the smart glasses will analyze the question in real time and provide detailed information, including sentiment analysis. Based on this analysis information, the smart glasses' display will show a response such as, "The XX model is popular these days. Its camera function is particularly excellent, and it has been well received by many customers."

[0805] Prompt Sentence Examples

[0806] "When a customer says, 'I'm looking for a new phone. Which one is the most popular?'"

[0807] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0808] Step 1:

[0809] The server performs user authentication. It receives the username and password entered by the user and checks the information against a database. If authentication is successful, it generates a user ID and starts a session. The input is the user's authentication information, and the output is the user ID and session information.

[0810] Step 2:

[0811] The server receives a counseling request from the user. The user inputs the consultation content and worries in text format from the terminal and sends it. The server receives this text data. The input is the user's text data, and the output is the text data to be analyzed.

[0812] Step 3:

[0813] The server analyzes the counseling request using a natural language processing module. The analysis first extracts topics and emotions from the text data, and then uses an emotion engine to recognize the user's emotions in detail. The input is the text data to be analyzed, and the output is the topic and emotion information.

[0814] Step 4:

[0815] The server then activates an AI module based on the analysis results to generate an appropriate response. The AI ​​module uses the previously obtained topic and emotional information as input and generates the optimal response. The input is the topic and emotional information, and the output is the generated response text.

[0816] Step 5:

[0817] The server sends the response generated by the AI ​​module to the user terminal, where the user can check the response content on the terminal. The input is the generated response text, and the output is the response display on the user terminal.

[0818] Step 6:

[0819] The server receives feedback from the user after the counseling session ends and stores the information in a database. The server then analyzes the feedback using an emotion engine. The input is the user's feedback, and the output is the emotion analysis results and the stored data.

[0820] Step 7:

[0821] The terminal allows store staff to receive questions and requests from customers in real time and displays the analysis results. Speech is converted into text using speech recognition technology and input into a natural language processing module. The input is the customer's voice data, and the output is a display of the analysis results.

[0822] 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.

[0823] 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.

[0824] 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.

[0825] [Third embodiment]

[0826] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0827] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0828] 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).

[0829] 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.

[0830] 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.

[0831] 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).

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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."

[0838] This invention is a system that allows users to easily receive mental health care online. The following explanation describes the specific method for implementing the program for this system and its processing in natural language.

[0839] Server Operation

[0840] 1. User Authentication

[0841] The server performs the authentication process to allow a user to log in to the system. Specifically, it receives the login information (username and password) entered by the user and checks it against a database. If authentication is successful, a user session begins.

[0842] 2. Receiving a Counseling Request

[0843] The server receives a counseling request sent from a user, which includes the content of the consultation and the worries in text format.

[0844] 3. Natural Language Processing

[0845] The server inputs the received counseling request into a natural language processing (NLP) module, which analyzes the consultation content and classifies topics and emotions.

[0846] 4. Launching the AI ​​module

[0847] The server then activates an artificial intelligence module to generate an appropriate response based on the analysis results of the NLP module. The artificial intelligence module generates an answer that is optimal for the user's inquiry.

[0848] 5. Providing a Response

[0849] The server sends the response generated by the artificial intelligence module to the user, which is in text format and displayed on the user's terminal.

[0850] 6. Receiving and storing feedback

[0851] The server receives feedback from the user after the counseling session. The feedback includes an evaluation of the session and suggestions for improvement, and stores it in a database. The stored feedback is used to improve the service in the future.

[0852] Device behavior

[0853] 1. Sending user authentication information

[0854] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[0855] 2. Submit a Counseling Request

[0856] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[0857] 3. View the response

[0858] The terminal displays the response received from the server to the user, who can then check the response content on the terminal.

[0859] 4. Submitting Feedback

[0860] The terminal transmits the feedback input by the user to the server after the session ends.

[0861] User Actions

[0862] 1. Log in

[0863] Users log in to the system using a dedicated app or a web browser, entering their username and password on the login screen to complete the authentication process.

[0864] 2. Submit a Counseling Request

[0865] The user inputs a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[0866] 3. Check the response

[0867] The user can check the response from the server on the terminal, and after reading the response, can enter additional questions or comments as needed.

[0868] 4. Providing Feedback

[0869] After the counseling session, the user inputs feedback and sends it to the server, including an evaluation of the session and suggestions for improvement.

[0870] Specific examples

[0871] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to the natural language processing module for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises." This response is sent to the user's device, where the user can confirm the answer. After the session ends, the user sends feedback saying, "Your advice was helpful. Thank you."

[0872] As described above, this system can implement a series of processes to provide users with mental care easily and effectively.

[0873] The processing flow will be explained below.

[0874] Step 1:

[0875] The user launches the app or web browser, accesses the login screen, enters their username and password, and presses the "Login" button.

[0876] Step 2:

[0877] The terminal transmits the login information entered by the user to the server.

[0878] Step 3:

[0879] The server compares the received login information with the database and authenticates the user. If authentication is successful, it generates a user ID and starts a session. It then sends the authentication result to the terminal.

[0880] Step 4:

[0881] The user enters the content of their consultation, such as "I've been feeling stressed at work lately. How can I relax?" into the form for submitting a counseling request and presses the "Submit" button.

[0882] Step 5:

[0883] The terminal transmits the consultation content to the server.

[0884] Step 6:

[0885] The server receives the consultation content and prepares to launch the AI ​​counselor. The consultation content is input into a natural language processing (NLP) module and topic analysis is performed.

[0886] Step 7:

[0887] The server selects an AI counselor to generate an appropriate response based on the analysis results returned from the NLP module, and causes the AI ​​counselor to generate the appropriate response.

[0888] Step 8:

[0889] The server receives the response generated by the AI ​​counselor, formats it for the user, and sends the formatted response to the device.

[0890] Step 9:

[0891] The terminal displays the AI ​​counselor's response received from the server to the user.

[0892] Step 10:

[0893] The user checks the AI ​​counselor's response, enters further questions or comments, and presses the "Send" button.

[0894] Step 11:

[0895] The terminal sends the user's additional input to the server.

[0896] Step 12:

[0897] The server again has the AI ​​counselor process the user's additional input, generate a new response, and send it back to the user.

[0898] Step 13:

[0899] The user presses the "End" button to end the session, enters their impressions and evaluation in the feedback form, and submits it.

[0900] Step 14:

[0901] The terminal transmits feedback information to the server.

[0902] Step 15:

[0903] The server receives the feedback information, stores it in a database, and analyzes it to help improve the performance of the AI ​​counselor.

[0904] Step 16:

[0905] The server ends the user session and logs the user out.

[0906] Example 1

[0907] 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."

[0908] There is a need for a system that can respond quickly and appropriately to users' needs for easy online mental health care. However, conventional systems have difficulty accurately understanding the content of users' consultations and providing appropriate advice. Furthermore, they lack a mechanism for efficiently collecting feedback from users and using it to improve services. An effective system is needed to solve these issues.

[0909] 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.

[0910] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating a generative AI model for generating an appropriate response based on the analysis results, means for providing the response from the generative AI model to the user, and means for receiving and storing feedback from the user. This allows users to easily receive mental health care online, and the system can generate and provide appropriate responses based on the user's consultation content. Furthermore, efficiently collecting and storing feedback can contribute to improving the quality of services.

[0911] A "means for user authentication" is a mechanism that receives login information (user name and password) entered by a user and verifies the user's identity by comparing it with a database.

[0912] The "means for receiving a counseling request" is a function for receiving the consultation content entered by the user in text format.

[0913] "Means for analyzing counseling requests using natural language processing" refers to a system that uses natural language processing technology to analyze the content of the consultation received, understand the content, and classify it.

[0914] "Means for launching a generative AI model" refers to a function that launches and utilizes an artificial intelligence model to generate an appropriate response to the user's inquiry based on the analysis results of natural language processing.

[0915] The "means for providing a response from the generative AI model to a user" is a mechanism for sending and displaying a text response generated by an artificial intelligence model on a user's device.

[0916] "Means for receiving and storing feedback" is a function that receives evaluations and comments sent by users after the counseling session and stores them in a database.

[0917] This invention is a system that allows users to easily receive mental health care online. This system is realized using the following means. The operations of the user, terminal, and server will be described in detail below.

[0918] Server Operation

[0919] The server first authenticates the user. It receives the login information (username and password) entered by the user, encrypts it using the SHA-256 hash algorithm, and then checks it against the database. If authentication is successful, the server generates a session ID and sends it to the user.

[0920] Next, the server receives a counseling request from the user. The request contains the user's concerns and the details of the consultation in text format. This text is processed using a Python natural language processing library (e.g., spaCy). Specifically, the text is tokenized, sentiment analyzed, and topic extracted.

[0921] Based on the analysis results, the server launches a generative AI model (e.g., OpenAI's GPT-3), which generates an appropriate response to the user's inquiry based on the prompt. The generated response is returned to the server in text format.

[0922] The server generates a text response and sends it to the user's terminal, where it is encoded and formatted according to the appropriate protocol before being served to the user.

[0923] Finally, the server receives feedback from users after the counseling session and stores it in a database, including session ratings and comments, to improve the quality of the service.

[0924] Device behavior

[0925] The terminal first sends the login information entered by the user to the server. The information is encrypted using SSL / TLS. After the authentication result is returned from the server, if the authentication is successful, the terminal proceeds to the next step.

[0926] Next, the terminal sends the counseling request entered by the user in text format to the server, waits for a response from the server, and displays the received response to the user in a chat box or message display area within the application.

[0927] After the counseling session is over, the terminal sends the feedback entered by the user to the server. The feedback is entered through the GUI and sent to the server.

[0928] User Actions

[0929] Users log in to the system using a dedicated application or a web browser. They enter their username and password on the login screen and click the "Login" button.

[0930] Next, the user enters a counseling request by entering the specific details of the consultation in a dedicated text input field and clicking the "Send" button once the request is complete.

[0931] After receiving the response from the server, the user can check the response on the terminal, and after reading the response, can enter additional questions or comments as needed, and then click the send button to send it to the server.

[0932] After the counseling session is over, the user uses the feedback form to enter their ratings and comments, which are then sent to the server by clicking the "Submit" button.

[0933] Examples of concrete examples and prompts

[0934] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to a natural language processing module (e.g., spaCy), which performs text tokenization, sentiment analysis, and topic extraction. Based on the analysis results, a generative AI model (e.g., OpenAI's GPT-3) generates a response such as, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises." This response is sent to the user's device, and the user can confirm the answer on the display screen. After the session ends, the user sends feedback such as, "The advice was helpful. Thank you."

[0935] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0936] Step 1:

[0937] The server receives user authentication information. It receives the username and password sent from the terminal, encrypts the password using the SHA-256 hashing algorithm, and checks it against an entry in the database. The input is the username and password, and the output is the authentication result (success or failure).

[0938] Step 2:

[0939] If the server successfully authenticates the user, it generates a session ID and sends it to the user's device. The session ID is unique and is used to track the user's series of requests. The input is the authentication result and the generated session ID, and the output is the session ID sent to the user.

[0940] Step 3:

[0941] After authentication, the user enters a counseling request on a dedicated input screen. Specifically, the user enters the consultation content and worries in text format and clicks the "Send" button. The input is the text of the consultation content, and the output is a counseling request that is sent to the server.

[0942] Step 4:

[0943] The terminal sends the input counseling request to the server. At this time, the request is encrypted using SSL / TLS. The input is the text of the user's consultation content, and the output is the request sent to the server.

[0944] Step 5:

[0945] The server inputs the received counseling request into a natural language processing (NLP) module. It uses a Python NLP library (e.g., spaCy) to tokenize the text and perform sentiment analysis and topic extraction. The input is the text data of the counseling request, and the output is the tokenized text and analysis results.

[0946] Step 6:

[0947] The server launches a generative AI model (e.g., OpenAI's GPT-3) based on the analysis results of the NLP module. The analysis results are input as prompts to the generative AI model, which then generates an appropriate response. The inputs are the NLP analysis results and the generative AI model's prompts, and the output is the response text generated by the AI.

[0948] Step 7:

[0949] The server sends the generated response text to the user's terminal, encoding it if necessary and formatting it according to the appropriate protocol. The input is the generated response text, and the output is the response data sent to the user's terminal.

[0950] Step 8:

[0951] The terminal displays the received response text to the user. The response content is displayed in a chat box or message display area within the application so that the user can check it. The input is the response text from the server, and the output is the response content that the user checks.

[0952] Step 9:

[0953] After the session is over, the user enters their feedback by entering their rating and comments in a dedicated feedback form and clicking the "Submit" button. The input is the feedback rating and comments, and the output is the feedback data sent to the server.

[0954] Step 10:

[0955] The terminal sends the input feedback to the server. The information is encrypted and transmitted securely to the server. The input is the user's feedback information, and the output is the feedback data sent to the server.

[0956] Step 11:

[0957] The server stores the received feedback in a database. The feedback includes session ratings and comments, and is stored in the database. The input is the user's feedback data, and the output is the stored feedback information.

[0958] Through these steps, this system allows users to easily receive mental health care online and provides appropriate responses based on the content of their consultation. Furthermore, by efficiently collecting and storing feedback, it contributes to improving the quality of the service.

[0959] (Application example 1)

[0960] 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."

[0961] Conventional online counseling systems have limited user experiences, particularly lacking realism and immersion. Even with the use of natural language processing and artificial intelligence, the user interface remains flat and monotonous, limiting the effectiveness of stress reduction and psychological care for users. This can potentially lead to lower user satisfaction.

[0962] 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.

[0963] In this invention, the server includes means for performing user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating an artificial intelligence module for generating an appropriate response based on the analysis result, means for providing the response from the artificial intelligence module to the user, means for receiving and storing feedback from the user, and means including a virtual reality system for providing counseling in a virtual space, thereby enabling the user to experience realistic counseling in a virtual space and receive more effective mental health care.

[0964] "User authentication" is the process of verifying the authenticity of a user when they access a system.

[0965] A "counseling request" is a consultation request that a user provides to the system.

[0966] "Natural language processing" is a technology for analyzing text data and understanding its meaning and emotions.

[0967] An "artificial intelligence module" is a software module for generating appropriate responses based on the results of natural language processing.

[0968] "Feedback" refers to the evaluation or impressions provided by the user after the counseling session has ended.

[0969] A "virtual space" is a virtual environment in which users can immerse themselves using virtual reality technology.

[0970] A "virtual reality system" is a system that allows users to experience a virtual space using a head-mounted display or smartphone.

[0971] This invention is a system that allows users to easily receive mental health care online, and aims to enable users to experience realistic counseling in a virtual space. The system includes a server and a user terminal.

[0972] First, let us explain how the server works. The server has the following main functions:

[0973] 1. User Authentication

[0974] When a user accesses the system, the server performs user authentication to verify the authenticity of the user. Authentication is performed by comparing the login information (user name and password) entered by the user with a database.

[0975] 2. Receiving a Counseling Request

[0976] The server receives a counseling request sent from a user, the request including a consultation content input by the user in text format.

[0977] 3. Natural Language Processing

[0978] The server inputs the received counseling request into a natural language processing module, which uses technology to analyze the text data and understand its meaning and sentiment.

[0979] 4. Launching the AI ​​module

[0980] The server then activates an artificial intelligence module to generate an appropriate response based on the results of the natural language processing analysis. This module generates the optimal answer for the user's inquiry.

[0981] 5. Providing a Response

[0982] The server provides the user with a response generated by the artificial intelligence module, which is in text format and sent to a terminal, which will be described later.

[0983] 6. Receiving and storing feedback

[0984] The server receives feedback from the user after the counseling session, including an evaluation of the session and suggestions for improvement, and stores the feedback in a database.

[0985] Next, we will explain the operation of the terminal. The terminal has the following main functions.

[0986] 1. Sending user authentication information

[0987] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[0988] 2. Submit a Counseling Request

[0989] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[0990] 3. View the response

[0991] The terminal displays the response received from the server to the user, who then checks the response from the AI ​​counselor through a virtual reality system or a text display.

[0992] 4. Submitting Feedback

[0993] The terminal transmits the feedback input by the user to the server after the session ends.

[0994] Specific examples

[0995] For example, if the user enters the following prompt text:

[0996] plaintext

[0997] I've been feeling stressed at work lately. How can I relax?

[0998] The server then uses a natural language processing module to analyze the request and activates an artificial intelligence module to generate an appropriate response.

[0999] plaintext

[1000] There are many ways to relieve stress, but we recommend starting by taking deep breaths and trying relaxation exercises. Regular exercise and dedicating time to a hobby can also be effective.

[1001] The responses are provided to the user through a virtual reality system, where the user can view the responses in a virtual counseling room using a head-mounted display, leading to an even more deeply relaxing experience.

[1002] The hardware used includes a smartphone and a head-mounted display, and the software used is TensorFlow, Transformers (Hugging Face), Pygame, and the OpenAI API.

[1003] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1004] Step 1: User authentication

[1005] The server receives login information (username and password) provided by the user. It compares this data with the registered information in a database and starts a user session if authentication is successful. The input is the username and password, and the output is the authentication result. Specifically, the process involves the user entering login information into a terminal, the terminal sending it to the server, and the server checking it against the database.

[1006] Step 2: Submit a Counseling Request

[1007] The terminal sends the counseling request (text data of the consultation content) entered by the user to the server. The input is the text data of the consultation content, and the output is the result of sending the request to the server. The user enters the consultation content as text into the terminal, and the terminal sends the data to the server.

[1008] Step 3: Natural Language Processing

[1009] The server inputs the received counseling request into a natural language processing (NLP) module. The input is the text data of the counseling request, and the output is the analysis result. Specifically, the NLP module analyzes the text data and extracts its meaning and sentiment.

[1010] Step 4: Launching the Artificial Intelligence Module

[1011] Based on the analysis results of the NLP module, the server activates an artificial intelligence (AI) module to generate the optimal response. The input is the analysis results of the NLP module, and the output is the response generated by the AI ​​module. Specifically, the server calls the AI ​​module, passes the analysis results to the AI ​​module, and the process of generating a response is carried out.

[1012] Step 5: Providing a response

[1013] The server sends the generated response to the user's device. The input is the response generated by the AI ​​module, and the output is the response sent to the user's device. The device displays the received response so that the user can check it. Specifically, the server sends the generated response in text format to the device, and the device displays it on the screen.

[1014] Step 6: Submitting User Feedback

[1015] After the counseling session ends, the terminal sends the feedback entered by the user to the server. The input is the text data of the feedback entered by the user, and the output is the result of that data being saved on the server. The user enters the feedback on the terminal, and the terminal sends the data to the server.

[1016] Step 7: Receive and store feedback

[1017] The server receives the feedback provided by the user and stores it in a database. The input is the feedback data sent from the terminal, and the output is the feedback stored in the database. Specifically, the server adds the feedback received from the terminal to the database.

[1018] This series of steps allows users to have a realistic counseling experience in a virtual space.

[1019] 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.

[1020] This invention is a system that processes a user's counseling request and generates an appropriate response according to the user's emotions by using an emotion engine. The following explains in natural language the specific method for implementing the program for this system and its processing.

[1021] Server Operation

[1022] 1. User Authentication

[1023] The server performs the authentication process to allow a user to log in to the system. Specifically, it receives the login information (username and password) entered by the user, checks that information against a database, and if authentication is successful, generates a user ID and starts a session.

[1024] 2. Receiving a Counseling Request

[1025] The server receives a counseling request sent from a user, which includes the content of the consultation and the worries in text format.

[1026] 3. Application of natural language processing and emotion engine

[1027] The server first inputs the received counseling request into a natural language processing (NLP) module to analyze the topic and emotions of the consultation. In addition, an emotion engine recognizes the user's emotions in detail.

[1028] 4. Launching the AI ​​module

[1029] The server activates an artificial intelligence module to generate an appropriate response based on the analysis results of the NLP module and emotion engine. The artificial intelligence module generates an answer that is optimal for the user's inquiry content and emotions.

[1030] 5. Providing a Response

[1031] The server sends the response generated by the artificial intelligence module to the user, which is in text format and displayed on the user's terminal.

[1032] 6. Receiving and storing feedback and analyzing sentiment

[1033] The server receives feedback from the user after the counseling session ends. The feedback includes an evaluation of the session and suggestions for improvement, and is stored in a database. The server also performs sentiment analysis of the feedback using an emotion engine. The stored feedback and sentiment analysis results are used to improve the service in the future.

[1034] Device behavior

[1035] 1. Sending user authentication information

[1036] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[1037] 2. Submit a Counseling Request

[1038] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[1039] 3. View the response

[1040] The device displays the AI ​​counselor's response received from the server to the user, who can then check the response on the device.

[1041] 4. Submitting Feedback

[1042] The terminal transmits the feedback input by the user to the server after the session ends.

[1043] User Actions

[1044] 1. Log in

[1045] Users log in to the system using a dedicated app or a web browser, entering their username and password on the login screen to complete the authentication process.

[1046] 2. Submit a Counseling Request

[1047] The user inputs a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[1048] 3. Check the response

[1049] The user can check the response from the server on the terminal, and after reading the response, can enter additional questions or comments as needed.

[1050] 4. Providing Feedback

[1051] After the counseling session, the user inputs feedback and sends it to the server, including an evaluation of the session and suggestions for improvement.

[1052] Specific examples

[1053] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to the natural language processing module and emotion engine for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises. This will also help relieve the anxiety you're feeling." This response is sent to the user's device, where the user can confirm the answer. After the session ends, the user sends feedback saying, "The advice was helpful. Thank you," and the emotion engine also analyzes this emotion.

[1054] As described above, this system can implement a series of processes to provide users with mental health care easily and effectively. By combining it with an emotion engine, more personalized responses become possible, improving user satisfaction.

[1055] The processing flow will be explained below.

[1056] Step 1:

[1057] The user launches the app or web browser, accesses the login screen, enters their username and password, and presses the "Login" button.

[1058] Step 2:

[1059] The terminal transmits the login information entered by the user to the server.

[1060] Step 3:

[1061] The server compares the received login information with the database and authenticates the user. If authentication is successful, it generates a user ID and starts a session. It then sends the authentication result to the terminal.

[1062] Step 4:

[1063] The user enters the content of their consultation, such as "I've been feeling stressed at work lately. How can I relax?" into the form for submitting a counseling request and presses the "Submit" button.

[1064] Step 5:

[1065] The terminal transmits the consultation content to the server.

[1066] Step 6:

[1067] The server receives the consultation content and inputs it into the emotion engine and natural language processing (NLP) module. The emotion engine analyzes the user's emotions, and the NLP module analyzes the topic of the consultation content.

[1068] Step 7:

[1069] The server selects an AI counselor module for generating an appropriate response based on the analysis results returned from the emotion engine and the NLP module, and causes the AI ​​counselor to generate an appropriate response.

[1070] Step 8:

[1071] The server receives the response generated by the AI ​​counselor, formats it for the user, and sends the formatted response to the device.

[1072] Step 9:

[1073] The terminal displays the AI ​​counselor's response received from the server to the user.

[1074] Step 10:

[1075] The user checks the AI ​​counselor's response, enters further questions or comments, and presses the "Send" button.

[1076] Step 11:

[1077] The terminal sends the user's additional input to the server.

[1078] Step 12:

[1079] The server again runs the emotion engine and NLP module to analyze the user's additional input. The AI ​​counselor uses this analysis to generate a new response, which the server then sends back to the user.

[1080] Step 13:

[1081] The user presses the "End" button to end the session, enters their impressions and evaluation in the feedback form, and submits it.

[1082] Step 14:

[1083] The terminal transmits feedback information to the server.

[1084] Step 15:

[1085] The server inputs the feedback information into the emotion engine, performs emotion analysis, and stores the results in a database. The analysis results are used to improve the performance of the AI ​​counselor.

[1086] Step 16:

[1087] The server ends the user session and logs the user out.

[1088] Example 2

[1089] 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."

[1090] Conventional counseling systems have difficulty fully understanding users' emotions, resulting in limited quality of responses. Furthermore, they lack a mechanism for effectively utilizing user feedback, making it difficult to continuously improve the quality of their services. Furthermore, the authentication and response generation processes are complex, which can impair user convenience. New technologies are needed to resolve these issues.

[1091] 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.

[1092] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for sentiment analysis of the counseling request, means for activating an artificial intelligence module for generating an appropriate response based on the analysis results, means for generating and inputting a prompt sentence to the artificial intelligence module, means for providing the response from the artificial intelligence module to the user, means for receiving and saving feedback from the user, means for sentiment analysis of the feedback, and means for saving the analysis results in a database. This enables detailed analysis of user sentiment and the provision of personalized responses. Furthermore, by effectively utilizing user feedback, the quality of service can be continuously improved. Furthermore, the authentication and response generation processes are simplified, improving user convenience.

[1093] "User authentication means" refers to the means used by a user when logging into a system, and includes the process of verifying a user name and password against a database to perform authentication.

[1094] The "counseling request receiving means" is a means for receiving the consultation contents, worries, etc. sent by the user in text format.

[1095] The "natural language processing analysis means" is a means used to analyze a counseling request and understand the topic and intent of its content. Specifically, the text is analyzed using natural language processing technology.

[1096] The "emotion analysis means" is a means for analyzing the user's emotions in detail from the text of the counseling request or feedback. The emotional state of the user is understood by using the emotion engine.

[1097] The "artificial intelligence module activation means" is a means for activating an artificial intelligence module for generating an appropriate response based on the results of natural language processing and sentiment analysis.

[1098] The "prompt sentence generating means" is a means for generating a prompt sentence to be input to the artificial intelligence module.

[1099] The "response providing means" is a means for providing the user with a response generated by the artificial intelligence module, and has the role of transmitting the response to the user's terminal.

[1100] The "feedback receiving and storing means" is a means for receiving feedback from the user after the counseling session and storing it in a database.

[1101] The "feedback emotion analysis means" is a means for analyzing the user's emotion from the text of the received feedback.

[1102] The "analysis result storage means" is a means for storing the results of natural language processing and sentiment analysis in a database.

[1103] MODE FOR CARRYING OUT THE INVENTION

[1104] The present invention provides a system for processing a user's counseling request and generating an appropriate response according to the user's emotions by using an emotion engine. Specific embodiments for carrying out the invention will be described in detail below.

[1105] Server Operation

[1106] 1. The server executes the authentication process for the user to log in to the system. Specifically, it receives the login information (username and password) entered by the user and checks that information against the database. A MySQL database is used for authentication. If authentication is successful, a user ID is generated and a session is started. If authentication is successful, a JWT token is generated and used for session management along with the user ID.

[1107] 2. The server receives a counseling request sent by the user. The request contains the consultation content and concerns in text format. This information is received through a REST API built using Python and Flask. The request content is temporarily stored in an in-memory database such as Redis.

[1108] 3. The server first inputs the received counseling request into a natural language processing (NLP) module to analyze the topic and sentiment of the consultation. The specific NLP module used is spaCy or a Transformer-based model (e.g., BERT). The analysis results are stored in an internal data structure (e.g., Pandas DataFrame). Next, the emotion engine uses IBM Watson's Natural Language Understanding API to recognize the user's sentiment in detail.

[1109] 4. The server launches an artificial intelligence module to generate an appropriate response based on the analysis results of the natural language processing module and the emotion engine. Specific generative AI models used are GPT-3 and BERT. In this process, a prompt sentence is generated and input into the generative AI model. The generated response is then stored in the internal data structure.

[1110] 5. The server sends the response generated by the AI ​​module to the user's device. The response is in text format and is sent to the user's device as an HTTP response using the Flask framework.

[1111] 6. The server receives feedback from the user after the counseling session ends. The feedback includes a session evaluation and suggestions for improvement, and stores it in a MySQL database. It also performs sentiment analysis of the feedback using an emotion engine and stores the results in the database.

[1112] Device behavior

[1113] 1. The device sends the login information entered by the user to the server. The user interface is created using JavaScript or Swift, and the information is sent securely using HTTPS. The server receives the authentication result, and if authentication is successful, the device proceeds to the next step.

[1114] 2. The device sends the consultation details entered by the user to the server. The input form is displayed using JavaScript or Swift, and the entered details are sent to the server via HTTPS.

[1115] 3. The device displays the AI ​​counselor's response received from the server to the user. The received response is displayed on the screen, allowing the user to check its content.

[1116] 4. After the session ends, the device sends the feedback entered by the user to the server by displaying a feedback input form and sending it to the server via HTTPS.

[1117] User Actions

[1118] 1. A user logs into the system using a dedicated app or a web browser, enters their username and password on the login screen, and completes the authentication process.

[1119] 2. The user enters a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[1120] 3. The user checks the response from the server on the terminal. After reading the response, the user can enter additional questions or comments as needed.

[1121] 4. After the counseling session, the user enters feedback and sends it to the server. The feedback includes an evaluation of the session and suggestions for improvement.

[1122] Specific examples

[1123] For example, consider the case where a user sends a counseling request saying, "I've been feeling stressed at work lately. What can I do to relax?" The server passes this request to the natural language processing module and emotion engine for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises. This will also help relieve the anxiety you're feeling." This response is sent to the user's device, and the user confirms the answer. After the session ends, the user sends feedback saying, "The advice was helpful. Thank you," and this emotion is also analyzed by the emotion engine.

[1124] Prompt Sentence Examples

[1125] By inputting the following prompt sentence to the generative AI model, you can get a response like the example above:

[1126] A user sent the following counseling request: "I've been feeling stressed at work lately. How can I relax?"

[1127] Generate an appropriate response in natural language, taking into account the user's feelings and the context of their inquiry.

[1128] This system specifically implements the process of providing emotional care to users. By combining an emotion engine with a generative AI model, it is possible to provide personalized responses according to individual needs, thereby improving user satisfaction.

[1129] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1130] Step 1: User enters login information

[1131] Input: Username and Password

[1132] Process: The user logs in to the system using a dedicated app or a web browser. They enter their username and password on the login screen and press the "Login" button. This action causes the device to send the entered information to the server using the HTTPS protocol.

[1133] Output: Login information sent to the server

[1134] Step 2: The server authenticates the user

[1135] Input: User login information

[1136] Processing: The server checks the received login information against its database. It queries the MySQL database for the username and password. If authentication is successful, it generates a user ID and issues a JWT token.

[1137] Output: Authentication result (success / failure), user ID, JWT token (if authentication is successful)

[1138] Step 3: User enters counseling request

[1139] Input: Text of consultation content or worries

[1140] Processing: After successful authentication, the user enters a counseling request into the system. They enter the specific details of their consultation and concerns in text format and press the "Send" button. This operation causes the device to send the input request to the server.

[1141] Output: Counseling request sent to the server

[1142] Step 4: The server receives the counseling request

[1143] Input: Counseling Request

[1144] Processing: The server receives the counseling request sent by the user and temporarily stores it in a data store (e.g., Redis).

[1145] Output: Counseling request saved in temporary store

[1146] Step 5: The server performs natural language processing

[1147] Input: Counseling Request

[1148] Processing: The server inputs the received counseling request into a natural language processing (NLP) module, using spaCy or a Transformer-based model (e.g., BERT) to analyze the text for topic and sentiment.

[1149] Output: Parsed topics and sentiment data

[1150] Step 6: The server performs sentiment analysis

[1151] Input: Counseling Request

[1152] Processing: Based on the analysis results of the NLP module, the server uses IBM Watson's Natural Language Understanding API to perform sentiment analysis using the emotion engine.

[1153] Output: Detailed sentiment analysis data

[1154] Step 7: The server generates a prompt and launches the AI ​​module.

[1155] Input: Parsed topic and sentiment data

[1156] Processing: The server generates a prompt based on the analysis results and inputs it into a generative AI model (e.g., GPT-3, BERT) to generate an appropriate response to the user's counseling request.

[1157] Output: The response generated by the generative AI model

[1158] Step 8: The server generates a response and provides it to the user.

[1159] Input: The response generated by the generative AI model

[1160] Processing: The server generates a response and sends it to the user's device as an HTTP response. The Flask framework is used to build the response and send it to the device.

[1161] Output: The response displayed on the user's terminal

[1162] Step 9: User confirms response

[1163] Input: Response from the server

[1164] Processing: The user checks the response from the server on the terminal. They can read the displayed response and enter additional questions or comments as needed.

[1165] Output: User understanding and satisfaction

[1166] Step 10: User enters feedback

[1167] Input: Session rating and improvement suggestions

[1168] Processing: After the counseling session ends, the user inputs feedback and presses the "Send" button. This operation causes the terminal to send the feedback to the server.

[1169] Output: Feedback sent to the server

[1170] Step 11: Server receives and stores feedback

[1171] Input: User feedback

[1172] Processing: The server receives the feedback sent by the user and stores it in a MySQL database.

[1173] Output: Feedback stored in a database

[1174] Step 12: The server performs sentiment analysis of the feedback

[1175] Input: User feedback

[1176] Processing: The server uses an emotion engine (IBM Watson NLU) to analyze the sentiment of the feedback, and stores the results of this analysis in the database.

[1177] Output: Parsed feedback sentiment data

[1178] Through these processing steps, this invention is a system that can effectively provide psychological care to users. By performing appropriate data processing and calculations at each step, it is possible to provide personalized, high-quality responses.

[1179] (Application example 2)

[1180] 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."

[1181] Conventional counseling systems have difficulty responding in real time to the user's individual emotions and consultation content, and there have been problems, particularly in brick-and-mortar stores, where customer service staff are unable to properly grasp the customer's emotions and respond immediately.In addition, there has been a lack of means to analyze the content of conversations with customers and provide optimal responses based on that analysis, so an effective method for improving customer satisfaction has been sought.

[1182] 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.

[1183] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating an artificial intelligence module for generating an appropriate response based on the analysis result, means for providing the response from the artificial intelligence module to the user, means for receiving and storing feedback from the user, visualization means for providing the analyzed response to staff in a physical store in real time, and analysis means for analyzing conversations with customers in real time and providing the analysis result to staff. This enables immediate and appropriate responses according to customer emotions and the content of the consultation, even in physical stores, thereby improving customer satisfaction.

[1184] 1. "User authentication" is the process of verifying the authentication information (e.g., username and password) required for a user to access a system and confirming that the user is a legitimate user.

[1185] 2. A "counseling request" is an act in which a user inputs the details of their consultation or concerns into the system and transmits that information to the system.

[1186] 3. "Natural language processing" is a set of computer processing techniques for analyzing text data and understanding its meaning and intent.

[1187] 4. "Artificial Intelligence Module" means a program module for generating optimal responses based on the results of natural language processing.

[1188] 5. "Feedback" refers to opinions and evaluations of users regarding the systems and services provided, which are used to improve the systems.

[1189] 6. "Visualization means" refers to the means of displaying analyzed data and information in a form that can be visually confirmed by staff and users.

[1190] 7. "Real-time analysis" refers to an analysis method that processes input data immediately and provides results quickly.

[1191] 8. "Response" refers to the answer or instruction generated by the system to the user or staff.

[1192] A system for implementing this invention includes means for authenticating a user, receiving a counseling request, analyzing it using natural language processing, generating a response using an artificial intelligence module, providing the response, receiving and storing feedback, and visualizing the analyzed response to store staff in real time.

[1193] Server Operation

[1194] The server first authenticates the user by receiving the authentication information (user name and password) used by the user to log in to the system and verifying it against a database.

[1195] Next, a counseling request is received from the user. The request contains the consultation details and worries entered by the user in text format, and is sent to the system.

[1196] The server passes the received request to a natural language processing module, which analyzes the topic and sentiment of the consultation. It then combines this with an emotion engine to perform detailed recognition of the user's emotions.

[1197] Based on the analysis results, an artificial intelligence module is activated to generate the optimal response, which is displayed in real time on smart glasses or other devices worn by store staff.

[1198] After the session ends, the server receives feedback from the user and stores it in a database. The feedback includes an evaluation of the session and suggestions for improvement, and also performs sentiment analysis using an emotion engine.

[1199] Device behavior

[1200] The terminal sends the login information entered by the user to the server and receives the authentication result. Next, it sends the counseling request entered by the user to the server. The response received from the server is then displayed to the user. The user can check the response on the terminal. After the session ends, the feedback entered by the user is also sent from the terminal to the server.

[1201] Smart glasses and other devices used by store staff will analyze conversations with customers in real time and display the results, allowing staff to respond optimally to customers' emotions.

[1202] User Actions

[1203] The user logs in to the system using a dedicated app or web browser, enters their username and password on the login screen, then enters their counseling request on the system and presses the send button.

[1204] The response from the server can be viewed on the terminal, and additional questions or comments can be entered as needed. After the session ends, the user can enter an evaluation of the counseling session and suggestions for improvement, and submit them as feedback.

[1205] Specific examples

[1206] For example, if a customer asks, "I'm looking for a new smartphone. Which one is the most popular?", the staff wearing the smart glasses will analyze the question in real time and provide detailed information, including sentiment analysis. Based on this analysis information, the smart glasses' display will show a response such as, "The XX model is popular these days. Its camera function is particularly excellent, and it has been well received by many customers."

[1207] Prompt Sentence Examples

[1208] "When a customer says, 'I'm looking for a new phone. Which one is the most popular?'"

[1209] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1210] Step 1:

[1211] The server performs user authentication. It receives the username and password entered by the user and checks the information against a database. If authentication is successful, it generates a user ID and starts a session. The input is the user's authentication information, and the output is the user ID and session information.

[1212] Step 2:

[1213] The server receives a counseling request from the user. The user inputs the consultation content and worries in text format from the terminal and sends it. The server receives this text data. The input is the user's text data, and the output is the text data to be analyzed.

[1214] Step 3:

[1215] The server analyzes the counseling request using a natural language processing module. The analysis first extracts topics and emotions from the text data, and then uses an emotion engine to recognize the user's emotions in detail. The input is the text data to be analyzed, and the output is the topic and emotion information.

[1216] Step 4:

[1217] The server then activates an AI module based on the analysis results to generate an appropriate response. The AI ​​module uses the previously obtained topic and emotional information as input and generates the optimal response. The input is the topic and emotional information, and the output is the generated response text.

[1218] Step 5:

[1219] The server sends the response generated by the AI ​​module to the user terminal, where the user can check the response content on the terminal. The input is the generated response text, and the output is the response display on the user terminal.

[1220] Step 6:

[1221] The server receives feedback from the user after the counseling session ends and stores the information in a database. The server then analyzes the feedback using an emotion engine. The input is the user's feedback, and the output is the emotion analysis results and the stored data.

[1222] Step 7:

[1223] The terminal allows store staff to receive questions and requests from customers in real time and displays the analysis results. Speech is converted into text using speech recognition technology and input into a natural language processing module. The input is the customer's voice data, and the output is a display of the analysis results.

[1224] 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.

[1225] 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.

[1226] 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.

[1227] [Fourth embodiment]

[1228] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1229] 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.

[1230] 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).

[1231] 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.

[1232] 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.

[1233] 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).

[1234] 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.

[1235] 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.

[1236] 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.

[1237] 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.

[1238] 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.

[1239] 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.

[1240] 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."

[1241] This invention is a system that allows users to easily receive mental health care online. The following explanation describes the specific method for implementing the program for this system and its processing in natural language.

[1242] Server Operation

[1243] 1. User Authentication

[1244] The server performs the authentication process to allow a user to log in to the system. Specifically, it receives the login information (username and password) entered by the user and checks it against a database. If authentication is successful, a user session begins.

[1245] 2. Receiving a Counseling Request

[1246] The server receives a counseling request sent from a user, which includes the content of the consultation and the worries in text format.

[1247] 3. Natural Language Processing

[1248] The server inputs the received counseling request into a natural language processing (NLP) module, which analyzes the consultation content and classifies topics and emotions.

[1249] 4. Launching the AI ​​module

[1250] The server then activates an artificial intelligence module to generate an appropriate response based on the analysis results of the NLP module. The artificial intelligence module generates an answer that is optimal for the user's inquiry.

[1251] 5. Providing a Response

[1252] The server sends the response generated by the artificial intelligence module to the user, which is in text format and displayed on the user's terminal.

[1253] 6. Receiving and storing feedback

[1254] The server receives feedback from the user after the counseling session. The feedback includes an evaluation of the session and suggestions for improvement, and stores it in a database. The stored feedback is used to improve the service in the future.

[1255] Device behavior

[1256] 1. Sending user authentication information

[1257] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[1258] 2. Submit a Counseling Request

[1259] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[1260] 3. View the response

[1261] The terminal displays the response received from the server to the user, who can then check the response content on the terminal.

[1262] 4. Submitting Feedback

[1263] The terminal transmits the feedback input by the user to the server after the session ends.

[1264] User Actions

[1265] 1. Log in

[1266] Users log in to the system using a dedicated app or a web browser, entering their username and password on the login screen to complete the authentication process.

[1267] 2. Submit a Counseling Request

[1268] The user inputs a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[1269] 3. Check the response

[1270] The user can check the response from the server on the terminal, and after reading the response, can enter additional questions or comments as needed.

[1271] 4. Providing Feedback

[1272] After the counseling session, the user inputs feedback and sends it to the server, including an evaluation of the session and suggestions for improvement.

[1273] Specific examples

[1274] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to the natural language processing module for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises." This response is sent to the user's device, where the user can confirm the answer. After the session ends, the user sends feedback saying, "Your advice was helpful. Thank you."

[1275] As described above, this system can implement a series of processes to provide users with mental care easily and effectively.

[1276] The processing flow will be explained below.

[1277] Step 1:

[1278] The user launches the app or web browser, accesses the login screen, enters their username and password, and presses the "Login" button.

[1279] Step 2:

[1280] The terminal transmits the login information entered by the user to the server.

[1281] Step 3:

[1282] The server compares the received login information with the database and authenticates the user. If authentication is successful, it generates a user ID and starts a session. It then sends the authentication result to the terminal.

[1283] Step 4:

[1284] The user enters the content of their consultation, such as "I've been feeling stressed at work lately. How can I relax?" into the form for submitting a counseling request and presses the "Submit" button.

[1285] Step 5:

[1286] The terminal transmits the consultation content to the server.

[1287] Step 6:

[1288] The server receives the consultation content and prepares to launch the AI ​​counselor. The consultation content is input into a natural language processing (NLP) module and topic analysis is performed.

[1289] Step 7:

[1290] The server selects an AI counselor to generate an appropriate response based on the analysis results returned from the NLP module, and causes the AI ​​counselor to generate the appropriate response.

[1291] Step 8:

[1292] The server receives the response generated by the AI ​​counselor, formats it for the user, and sends the formatted response to the device.

[1293] Step 9:

[1294] The terminal displays the AI ​​counselor's response received from the server to the user.

[1295] Step 10:

[1296] The user checks the AI ​​counselor's response, enters further questions or comments, and presses the "Send" button.

[1297] Step 11:

[1298] The terminal sends the user's additional input to the server.

[1299] Step 12:

[1300] The server again has the AI ​​counselor process the user's additional input, generate a new response, and send it back to the user.

[1301] Step 13:

[1302] The user presses the "End" button to end the session, enters their impressions and evaluation in the feedback form, and submits it.

[1303] Step 14:

[1304] The terminal transmits feedback information to the server.

[1305] Step 15:

[1306] The server receives the feedback information, stores it in a database, and analyzes it to help improve the performance of the AI ​​counselor.

[1307] Step 16:

[1308] The server ends the user session and logs the user out.

[1309] Example 1

[1310] 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."

[1311] There is a need for a system that can respond quickly and appropriately to users' needs for easy online mental health care. However, conventional systems have difficulty accurately understanding the content of users' consultations and providing appropriate advice. Furthermore, they lack a mechanism for efficiently collecting feedback from users and using it to improve services. An effective system is needed to solve these issues.

[1312] 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.

[1313] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating a generative AI model for generating an appropriate response based on the analysis results, means for providing the response from the generative AI model to the user, and means for receiving and storing feedback from the user. This allows users to easily receive mental health care online, and the system can generate and provide appropriate responses based on the user's consultation content. Furthermore, efficiently collecting and storing feedback can contribute to improving the quality of services.

[1314] A "means for user authentication" is a mechanism that receives login information (user name and password) entered by a user and verifies the user's identity by comparing it with a database.

[1315] The "means for receiving a counseling request" is a function for receiving the consultation content entered by the user in text format.

[1316] "Means for analyzing counseling requests using natural language processing" refers to a system that uses natural language processing technology to analyze the content of the consultation received, understand the content, and classify it.

[1317] "Means for launching a generative AI model" refers to a function that launches and utilizes an artificial intelligence model to generate an appropriate response to the user's inquiry based on the analysis results of natural language processing.

[1318] The "means for providing a response from the generative AI model to a user" is a mechanism for sending and displaying a text response generated by an artificial intelligence model on a user's device.

[1319] "Means for receiving and storing feedback" is a function that receives evaluations and comments sent by users after the counseling session and stores them in a database.

[1320] This invention is a system that allows users to easily receive mental health care online. This system is realized using the following means. The operations of the user, terminal, and server will be described in detail below.

[1321] Server Operation

[1322] The server first authenticates the user. It receives the login information (username and password) entered by the user, encrypts it using the SHA-256 hash algorithm, and then checks it against the database. If authentication is successful, the server generates a session ID and sends it to the user.

[1323] Next, the server receives a counseling request from the user. The request contains the user's concerns and the details of the consultation in text format. This text is processed using a Python natural language processing library (e.g., spaCy). Specifically, the text is tokenized, sentiment analyzed, and topic extracted.

[1324] Based on the analysis results, the server launches a generative AI model (e.g., OpenAI's GPT-3), which generates an appropriate response to the user's inquiry based on the prompt. The generated response is returned to the server in text format.

[1325] The server generates a text response and sends it to the user's terminal, where it is encoded and formatted according to the appropriate protocol before being served to the user.

[1326] Finally, the server receives feedback from users after the counseling session and stores it in a database, including session ratings and comments, to improve the quality of the service.

[1327] Device behavior

[1328] The terminal first sends the login information entered by the user to the server. The information is encrypted using SSL / TLS. After the authentication result is returned from the server, if the authentication is successful, the terminal proceeds to the next step.

[1329] Next, the terminal sends the counseling request entered by the user in text format to the server, waits for a response from the server, and displays the received response to the user in a chat box or message display area within the application.

[1330] After the counseling session is over, the terminal sends the feedback entered by the user to the server. The feedback is entered through the GUI and sent to the server.

[1331] User Actions

[1332] Users log in to the system using a dedicated application or a web browser. They enter their username and password on the login screen and click the "Login" button.

[1333] Next, the user enters a counseling request by entering the specific details of the consultation in a dedicated text input field and clicking the "Send" button once the request is complete.

[1334] After receiving the response from the server, the user can check the response on the terminal, and after reading the response, can enter additional questions or comments as needed, and then click the send button to send it to the server.

[1335] After the counseling session is over, the user uses the feedback form to enter their ratings and comments, which are then sent to the server by clicking the "Submit" button.

[1336] Examples of concrete examples and prompts

[1337] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to a natural language processing module (e.g., spaCy), which performs text tokenization, sentiment analysis, and topic extraction. Based on the analysis results, a generative AI model (e.g., OpenAI's GPT-3) generates a response such as, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises." This response is sent to the user's device, and the user can confirm the answer on the display screen. After the session ends, the user sends feedback such as, "The advice was helpful. Thank you."

[1338] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1339] Step 1:

[1340] The server receives user authentication information. It receives the username and password sent from the terminal, encrypts the password using the SHA-256 hashing algorithm, and checks it against an entry in the database. The input is the username and password, and the output is the authentication result (success or failure).

[1341] Step 2:

[1342] If the server successfully authenticates the user, it generates a session ID and sends it to the user's device. The session ID is unique and is used to track the user's series of requests. The input is the authentication result and the generated session ID, and the output is the session ID sent to the user.

[1343] Step 3:

[1344] After authentication, the user enters a counseling request on a dedicated input screen. Specifically, the user enters the consultation content and worries in text format and clicks the "Send" button. The input is the text of the consultation content, and the output is a counseling request that is sent to the server.

[1345] Step 4:

[1346] The terminal sends the input counseling request to the server. At this time, the request is encrypted using SSL / TLS. The input is the text of the user's consultation content, and the output is the request sent to the server.

[1347] Step 5:

[1348] The server inputs the received counseling request into a natural language processing (NLP) module. It uses a Python NLP library (e.g., spaCy) to tokenize the text and perform sentiment analysis and topic extraction. The input is the text data of the counseling request, and the output is the tokenized text and analysis results.

[1349] Step 6:

[1350] The server launches a generative AI model (e.g., OpenAI's GPT-3) based on the analysis results of the NLP module. The analysis results are input as prompts to the generative AI model, which then generates an appropriate response. The inputs are the NLP analysis results and the generative AI model's prompts, and the output is the response text generated by the AI.

[1351] Step 7:

[1352] The server sends the generated response text to the user's terminal, encoding it if necessary and formatting it according to the appropriate protocol. The input is the generated response text, and the output is the response data sent to the user's terminal.

[1353] Step 8:

[1354] The terminal displays the received response text to the user. The response content is displayed in a chat box or message display area within the application so that the user can check it. The input is the response text from the server, and the output is the response content that the user checks.

[1355] Step 9:

[1356] After the session is over, the user enters their feedback by entering their rating and comments in a dedicated feedback form and clicking the "Submit" button. The input is the feedback rating and comments, and the output is the feedback data sent to the server.

[1357] Step 10:

[1358] The terminal sends the input feedback to the server. The information is encrypted and transmitted securely to the server. The input is the user's feedback information, and the output is the feedback data sent to the server.

[1359] Step 11:

[1360] The server stores the received feedback in a database. The feedback includes session ratings and comments, and is stored in the database. The input is the user's feedback data, and the output is the stored feedback information.

[1361] Through these steps, this system allows users to easily receive mental health care online and provides appropriate responses based on the content of their consultation. Furthermore, by efficiently collecting and storing feedback, it contributes to improving the quality of the service.

[1362] (Application example 1)

[1363] 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."

[1364] Conventional online counseling systems have limited user experiences, particularly lacking realism and immersion. Even with the use of natural language processing and artificial intelligence, the user interface remains flat and monotonous, limiting the effectiveness of stress reduction and psychological care for users. This can potentially lead to lower user satisfaction.

[1365] 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.

[1366] In this invention, the server includes means for performing user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating an artificial intelligence module for generating an appropriate response based on the analysis result, means for providing the response from the artificial intelligence module to the user, means for receiving and storing feedback from the user, and means including a virtual reality system for providing counseling in a virtual space, thereby enabling the user to experience realistic counseling in a virtual space and receive more effective mental health care.

[1367] "User authentication" is the process of verifying the authenticity of a user when they access a system.

[1368] A "counseling request" is a consultation request that a user provides to the system.

[1369] "Natural language processing" is a technology for analyzing text data and understanding its meaning and emotions.

[1370] An "artificial intelligence module" is a software module for generating appropriate responses based on the results of natural language processing.

[1371] "Feedback" refers to the evaluation or impressions provided by the user after the counseling session has ended.

[1372] A "virtual space" is a virtual environment in which users can immerse themselves using virtual reality technology.

[1373] A "virtual reality system" is a system that allows users to experience a virtual space using a head-mounted display or smartphone.

[1374] This invention is a system that allows users to easily receive mental health care online, and aims to enable users to experience realistic counseling in a virtual space. The system includes a server and a user terminal.

[1375] First, let us explain how the server works. The server has the following main functions:

[1376] 1. User Authentication

[1377] When a user accesses the system, the server performs user authentication to verify the authenticity of the user. Authentication is performed by comparing the login information (user name and password) entered by the user with a database.

[1378] 2. Receiving a Counseling Request

[1379] The server receives a counseling request sent from a user, the request including a consultation content input by the user in text format.

[1380] 3. Natural Language Processing

[1381] The server inputs the received counseling request into a natural language processing module, which uses technology to analyze the text data and understand its meaning and sentiment.

[1382] 4. Launching the AI ​​module

[1383] The server then activates an artificial intelligence module to generate an appropriate response based on the results of the natural language processing analysis. This module generates the optimal answer for the user's inquiry.

[1384] 5. Providing a Response

[1385] The server provides the user with a response generated by the artificial intelligence module, which is in text format and sent to a terminal, which will be described later.

[1386] 6. Receiving and storing feedback

[1387] The server receives feedback from the user after the counseling session, including an evaluation of the session and suggestions for improvement, and stores the feedback in a database.

[1388] Next, we will explain the operation of the terminal. The terminal has the following main functions.

[1389] 1. Sending user authentication information

[1390] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[1391] 2. Submit a Counseling Request

[1392] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[1393] 3. View the response

[1394] The terminal displays the response received from the server to the user, who then checks the response from the AI ​​counselor through a virtual reality system or a text display.

[1395] 4. Submitting Feedback

[1396] The terminal transmits the feedback input by the user to the server after the session ends.

[1397] Specific examples

[1398] For example, if the user enters the following prompt text:

[1399] plaintext

[1400] I've been feeling stressed at work lately. How can I relax?

[1401] The server then uses a natural language processing module to analyze the request and activates an artificial intelligence module to generate an appropriate response.

[1402] plaintext

[1403] There are many ways to relieve stress, but we recommend starting by taking deep breaths and trying relaxation exercises. Regular exercise and dedicating time to a hobby can also be effective.

[1404] The responses are provided to the user through a virtual reality system, where the user can view the responses in a virtual counseling room using a head-mounted display, leading to an even more deeply relaxing experience.

[1405] The hardware used includes a smartphone and a head-mounted display, and the software used is TensorFlow, Transformers (Hugging Face), Pygame, and the OpenAI API.

[1406] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1407] Step 1: User authentication

[1408] The server receives login information (username and password) provided by the user. It compares this data with the registered information in a database and starts a user session if authentication is successful. The input is the username and password, and the output is the authentication result. Specifically, the process involves the user entering login information into a terminal, the terminal sending it to the server, and the server checking it against the database.

[1409] Step 2: Submit a Counseling Request

[1410] The terminal sends the counseling request (text data of the consultation content) entered by the user to the server. The input is the text data of the consultation content, and the output is the result of sending the request to the server. The user enters the consultation content as text into the terminal, and the terminal sends the data to the server.

[1411] Step 3: Natural Language Processing

[1412] The server inputs the received counseling request into a natural language processing (NLP) module. The input is the text data of the counseling request, and the output is the analysis result. Specifically, the NLP module analyzes the text data and extracts its meaning and sentiment.

[1413] Step 4: Launching the Artificial Intelligence Module

[1414] Based on the analysis results of the NLP module, the server activates an artificial intelligence (AI) module to generate the optimal response. The input is the analysis results of the NLP module, and the output is the response generated by the AI ​​module. Specifically, the server calls the AI ​​module, passes the analysis results to the AI ​​module, and the process of generating a response is carried out.

[1415] Step 5: Providing a response

[1416] The server sends the generated response to the user's device. The input is the response generated by the AI ​​module, and the output is the response sent to the user's device. The device displays the received response so that the user can check it. Specifically, the server sends the generated response in text format to the device, and the device displays it on the screen.

[1417] Step 6: Submitting User Feedback

[1418] After the counseling session ends, the terminal sends the feedback entered by the user to the server. The input is the text data of the feedback entered by the user, and the output is the result of that data being saved on the server. The user enters the feedback on the terminal, and the terminal sends the data to the server.

[1419] Step 7: Receive and store feedback

[1420] The server receives the feedback provided by the user and stores it in a database. The input is the feedback data sent from the terminal, and the output is the feedback stored in the database. Specifically, the server adds the feedback received from the terminal to the database.

[1421] This series of steps allows users to have a realistic counseling experience in a virtual space.

[1422] 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.

[1423] This invention is a system that processes a user's counseling request and generates an appropriate response according to the user's emotions by using an emotion engine. The following explains in natural language the specific method for implementing the program for this system and its processing.

[1424] Server Operation

[1425] 1. User Authentication

[1426] The server performs the authentication process to allow a user to log in to the system. Specifically, it receives the login information (username and password) entered by the user, checks that information against a database, and if authentication is successful, generates a user ID and starts a session.

[1427] 2. Receiving a Counseling Request

[1428] The server receives a counseling request sent from a user, which includes the content of the consultation and the worries in text format.

[1429] 3. Application of natural language processing and emotion engine

[1430] The server first inputs the received counseling request into a natural language processing (NLP) module to analyze the topic and emotions of the consultation. In addition, an emotion engine recognizes the user's emotions in detail.

[1431] 4. Launching the AI ​​module

[1432] The server activates an artificial intelligence module to generate an appropriate response based on the analysis results of the NLP module and emotion engine. The artificial intelligence module generates an answer that is optimal for the user's inquiry content and emotions.

[1433] 5. Providing a Response

[1434] The server sends the response generated by the artificial intelligence module to the user, which is in text format and displayed on the user's terminal.

[1435] 6. Receiving and storing feedback and analyzing sentiment

[1436] The server receives feedback from the user after the counseling session ends. The feedback includes an evaluation of the session and suggestions for improvement, and is stored in a database. The server also performs sentiment analysis of the feedback using an emotion engine. The stored feedback and sentiment analysis results are used to improve the service in the future.

[1437] Device behavior

[1438] 1. Sending user authentication information

[1439] The terminal sends the login information entered by the user to the server, receives the authentication result from the server, and if the authentication is successful, proceeds to the next step.

[1440] 2. Submit a Counseling Request

[1441] The terminal transmits the consultation content entered by the user to the server and waits for a response from the server.

[1442] 3. View the response

[1443] The device displays the AI ​​counselor's response received from the server to the user, who can then check the response on the device.

[1444] 4. Submitting Feedback

[1445] The terminal transmits the feedback input by the user to the server after the session ends.

[1446] User Actions

[1447] 1. Log in

[1448] Users log in to the system using a dedicated app or a web browser, entering their username and password on the login screen to complete the authentication process.

[1449] 2. Submit a Counseling Request

[1450] The user inputs a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[1451] 3. Check the response

[1452] The user can check the response from the server on the terminal, and after reading the response, can enter additional questions or comments as needed.

[1453] 4. Providing Feedback

[1454] After the counseling session, the user inputs feedback and sends it to the server, including an evaluation of the session and suggestions for improvement.

[1455] Specific examples

[1456] For example, if a user sends a counseling request saying, "I've been feeling stressed at work lately. How can I relax?", the server passes this request to the natural language processing module and emotion engine for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises. This will also help relieve the anxiety you're feeling." This response is sent to the user's device, where the user can confirm the answer. After the session ends, the user sends feedback saying, "The advice was helpful. Thank you," and the emotion engine also analyzes this emotion.

[1457] As described above, this system can implement a series of processes to provide users with mental health care easily and effectively. By combining it with an emotion engine, more personalized responses become possible, improving user satisfaction.

[1458] The processing flow will be explained below.

[1459] Step 1:

[1460] The user launches the app or web browser, accesses the login screen, enters their username and password, and presses the "Login" button.

[1461] Step 2:

[1462] The terminal transmits the login information entered by the user to the server.

[1463] Step 3:

[1464] The server compares the received login information with the database and authenticates the user. If authentication is successful, it generates a user ID and starts a session. It then sends the authentication result to the terminal.

[1465] Step 4:

[1466] The user enters the content of their consultation, such as "I've been feeling stressed at work lately. How can I relax?" into the form for submitting a counseling request and presses the "Submit" button.

[1467] Step 5:

[1468] The terminal transmits the consultation content to the server.

[1469] Step 6:

[1470] The server receives the consultation content and inputs it into the emotion engine and natural language processing (NLP) module. The emotion engine analyzes the user's emotions, and the NLP module analyzes the topic of the consultation content.

[1471] Step 7:

[1472] The server selects an AI counselor module for generating an appropriate response based on the analysis results returned from the emotion engine and the NLP module, and causes the AI ​​counselor to generate an appropriate response.

[1473] Step 8:

[1474] The server receives the response generated by the AI ​​counselor, formats it for the user, and sends the formatted response to the device.

[1475] Step 9:

[1476] The terminal displays the AI ​​counselor's response received from the server to the user.

[1477] Step 10:

[1478] The user checks the AI ​​counselor's response, enters further questions or comments, and presses the "Send" button.

[1479] Step 11:

[1480] The terminal sends the user's additional input to the server.

[1481] Step 12:

[1482] The server again runs the emotion engine and NLP module to analyze the user's additional input. The AI ​​counselor uses this analysis to generate a new response, which the server then sends back to the user.

[1483] Step 13:

[1484] The user presses the "End" button to end the session, enters their impressions and evaluation in the feedback form, and submits it.

[1485] Step 14:

[1486] The terminal transmits feedback information to the server.

[1487] Step 15:

[1488] The server inputs the feedback information into the emotion engine, performs emotion analysis, and stores the results in a database. The analysis results are used to improve the performance of the AI ​​counselor.

[1489] Step 16:

[1490] The server ends the user session and logs the user out.

[1491] Example 2

[1492] 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."

[1493] Conventional counseling systems have difficulty fully understanding users' emotions, resulting in limited quality of responses. Furthermore, they lack a mechanism for effectively utilizing user feedback, making it difficult to continuously improve the quality of their services. Furthermore, the authentication and response generation processes are complex, which can impair user convenience. New technologies are needed to resolve these issues.

[1494] 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.

[1495] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for sentiment analysis of the counseling request, means for activating an artificial intelligence module for generating an appropriate response based on the analysis results, means for generating and inputting a prompt sentence to the artificial intelligence module, means for providing the response from the artificial intelligence module to the user, means for receiving and saving feedback from the user, means for sentiment analysis of the feedback, and means for saving the analysis results in a database. This enables detailed analysis of user sentiment and the provision of personalized responses. Furthermore, by effectively utilizing user feedback, the quality of service can be continuously improved. Furthermore, the authentication and response generation processes are simplified, improving user convenience.

[1496] "User authentication means" refers to the means used by a user when logging into a system, and includes the process of verifying a user name and password against a database to perform authentication.

[1497] The "counseling request receiving means" is a means for receiving the consultation contents, worries, etc. sent by the user in text format.

[1498] The "natural language processing analysis means" is a means used to analyze a counseling request and understand the topic and intent of its content. Specifically, the text is analyzed using natural language processing technology.

[1499] The "emotion analysis means" is a means for analyzing the user's emotions in detail from the text of the counseling request or feedback. The emotional state of the user is understood by using the emotion engine.

[1500] The "artificial intelligence module activation means" is a means for activating an artificial intelligence module for generating an appropriate response based on the results of natural language processing and sentiment analysis.

[1501] The "prompt sentence generating means" is a means for generating a prompt sentence to be input to the artificial intelligence module.

[1502] The "response providing means" is a means for providing the user with a response generated by the artificial intelligence module, and has the role of transmitting the response to the user's terminal.

[1503] The "feedback receiving and storing means" is a means for receiving feedback from the user after the counseling session and storing it in a database.

[1504] The "feedback emotion analysis means" is a means for analyzing the user's emotion from the text of the received feedback.

[1505] The "analysis result storage means" is a means for storing the results of natural language processing and sentiment analysis in a database.

[1506] MODE FOR CARRYING OUT THE INVENTION

[1507] The present invention provides a system for processing a user's counseling request and generating an appropriate response according to the user's emotions by using an emotion engine. Specific embodiments for carrying out the invention will be described in detail below.

[1508] Server Operation

[1509] 1. The server executes the authentication process for the user to log in to the system. Specifically, it receives the login information (username and password) entered by the user and checks that information against the database. A MySQL database is used for authentication. If authentication is successful, a user ID is generated and a session is started. If authentication is successful, a JWT token is generated and used for session management along with the user ID.

[1510] 2. The server receives a counseling request sent by the user. The request contains the consultation content and concerns in text format. This information is received through a REST API built using Python and Flask. The request content is temporarily stored in an in-memory database such as Redis.

[1511] 3. The server first inputs the received counseling request into a natural language processing (NLP) module to analyze the topic and sentiment of the consultation. The specific NLP module used is spaCy or a Transformer-based model (e.g., BERT). The analysis results are stored in an internal data structure (e.g., Pandas DataFrame). Next, the emotion engine uses IBM Watson's Natural Language Understanding API to recognize the user's sentiment in detail.

[1512] 4. The server launches an artificial intelligence module to generate an appropriate response based on the analysis results of the natural language processing module and the emotion engine. Specific generative AI models used are GPT-3 and BERT. In this process, a prompt sentence is generated and input into the generative AI model. The generated response is then stored in the internal data structure.

[1513] 5. The server sends the response generated by the AI ​​module to the user's device. The response is in text format and is sent to the user's device as an HTTP response using the Flask framework.

[1514] 6. The server receives feedback from the user after the counseling session ends. The feedback includes a session evaluation and suggestions for improvement, and stores it in a MySQL database. It also performs sentiment analysis of the feedback using an emotion engine and stores the results in the database.

[1515] Device behavior

[1516] 1. The device sends the login information entered by the user to the server. The user interface is created using JavaScript or Swift, and the information is sent securely using HTTPS. The server receives the authentication result, and if authentication is successful, the device proceeds to the next step.

[1517] 2. The device sends the consultation details entered by the user to the server. The input form is displayed using JavaScript or Swift, and the entered details are sent to the server via HTTPS.

[1518] 3. The device displays the AI ​​counselor's response received from the server to the user. The received response is displayed on the screen, allowing the user to check its content.

[1519] 4. After the session ends, the device sends the feedback entered by the user to the server by displaying a feedback input form and sending it to the server via HTTPS.

[1520] User Actions

[1521] 1. A user logs into the system using a dedicated app or a web browser, enters their username and password on the login screen, and completes the authentication process.

[1522] 2. The user enters a counseling request into the system, entering the specific details of the consultation and concerns in text, and then presses the "Send" button.

[1523] 3. The user checks the response from the server on the terminal. After reading the response, the user can enter additional questions or comments as needed.

[1524] 4. After the counseling session, the user enters feedback and sends it to the server. The feedback includes an evaluation of the session and suggestions for improvement.

[1525] Specific examples

[1526] For example, consider the case where a user sends a counseling request saying, "I've been feeling stressed at work lately. What can I do to relax?" The server passes this request to the natural language processing module and emotion engine for analysis. Based on the analysis results, the artificial intelligence module generates a response saying, "To relieve stress, I recommend you first take a deep breath and try some relaxation exercises. This will also help relieve the anxiety you're feeling." This response is sent to the user's device, and the user confirms the answer. After the session ends, the user sends feedback saying, "The advice was helpful. Thank you," and this emotion is also analyzed by the emotion engine.

[1527] Prompt Sentence Examples

[1528] By inputting the following prompt sentence to the generative AI model, you can get a response like the example above:

[1529] A user sent the following counseling request: "I've been feeling stressed at work lately. How can I relax?"

[1530] Generate an appropriate response in natural language, taking into account the user's feelings and the context of their inquiry.

[1531] This system specifically implements the process of providing emotional care to users. By combining an emotion engine with a generative AI model, it is possible to provide personalized responses according to individual needs, thereby improving user satisfaction.

[1532] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1533] Step 1: User enters login information

[1534] Input: Username and Password

[1535] Process: The user logs in to the system using a dedicated app or a web browser. They enter their username and password on the login screen and press the "Login" button. This action causes the device to send the entered information to the server using the HTTPS protocol.

[1536] Output: Login information sent to the server

[1537] Step 2: The server authenticates the user

[1538] Input: User login information

[1539] Processing: The server checks the received login information against its database. It queries the MySQL database for the username and password. If authentication is successful, it generates a user ID and issues a JWT token.

[1540] Output: Authentication result (success / failure), user ID, JWT token (if authentication is successful)

[1541] Step 3: User enters counseling request

[1542] Input: Text of consultation content or worries

[1543] Processing: After successful authentication, the user enters a counseling request into the system. They enter the specific details of their consultation and concerns in text format and press the "Send" button. This operation causes the device to send the input request to the server.

[1544] Output: Counseling request sent to the server

[1545] Step 4: The server receives the counseling request

[1546] Input: Counseling Request

[1547] Processing: The server receives the counseling request sent by the user and temporarily stores it in a data store (e.g., Redis).

[1548] Output: Counseling request saved in temporary store

[1549] Step 5: The server performs natural language processing

[1550] Input: Counseling Request

[1551] Processing: The server inputs the received counseling request into a natural language processing (NLP) module, using spaCy or a Transformer-based model (e.g., BERT) to analyze the text for topic and sentiment.

[1552] Output: Parsed topics and sentiment data

[1553] Step 6: The server performs sentiment analysis

[1554] Input: Counseling Request

[1555] Processing: Based on the analysis results of the NLP module, the server uses IBM Watson's Natural Language Understanding API to perform sentiment analysis using the emotion engine.

[1556] Output: Detailed sentiment analysis data

[1557] Step 7: The server generates a prompt and launches the AI ​​module.

[1558] Input: Parsed topic and sentiment data

[1559] Processing: The server generates a prompt based on the analysis results and inputs it into a generative AI model (e.g., GPT-3, BERT) to generate an appropriate response to the user's counseling request.

[1560] Output: The response generated by the generative AI model

[1561] Step 8: The server generates a response and provides it to the user.

[1562] Input: The response generated by the generative AI model

[1563] Processing: The server generates a response and sends it to the user's device as an HTTP response. The Flask framework is used to build the response and send it to the device.

[1564] Output: The response displayed on the user's terminal

[1565] Step 9: User confirms response

[1566] Input: Response from the server

[1567] Processing: The user checks the response from the server on the terminal. They can read the displayed response and enter additional questions or comments as needed.

[1568] Output: User understanding and satisfaction

[1569] Step 10: User enters feedback

[1570] Input: Session rating and improvement suggestions

[1571] Processing: After the counseling session ends, the user inputs feedback and presses the "Send" button. This operation causes the terminal to send the feedback to the server.

[1572] Output: Feedback sent to the server

[1573] Step 11: Server receives and stores feedback

[1574] Input: User feedback

[1575] Processing: The server receives the feedback sent by the user and stores it in a MySQL database.

[1576] Output: Feedback stored in a database

[1577] Step 12: The server performs sentiment analysis of the feedback

[1578] Input: User feedback

[1579] Processing: The server uses an emotion engine (IBM Watson NLU) to analyze the sentiment of the feedback, and stores the results of this analysis in the database.

[1580] Output: Parsed feedback sentiment data

[1581] Through these processing steps, this invention is a system that can effectively provide psychological care to users. By performing appropriate data processing and calculations at each step, it is possible to provide personalized, high-quality responses.

[1582] (Application example 2)

[1583] 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."

[1584] Conventional counseling systems have difficulty responding in real time to the user's individual emotions and consultation content, and there have been problems, particularly in brick-and-mortar stores, where customer service staff are unable to properly grasp the customer's emotions and respond immediately.In addition, there has been a lack of means to analyze the content of conversations with customers and provide optimal responses based on that analysis, so an effective method for improving customer satisfaction has been sought.

[1585] 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.

[1586] In this invention, the server includes means for user authentication, means for receiving a counseling request from a user, means for analyzing the counseling request using natural language processing, means for activating an artificial intelligence module for generating an appropriate response based on the analysis result, means for providing the response from the artificial intelligence module to the user, means for receiving and storing feedback from the user, visualization means for providing the analyzed response to staff in a physical store in real time, and analysis means for analyzing conversations with customers in real time and providing the analysis result to staff. This enables immediate and appropriate responses according to customer emotions and the content of the consultation, even in physical stores, thereby improving customer satisfaction.

[1587] 1. "User authentication" is the process of verifying the authentication information (e.g., username and password) required for a user to access a system and confirming that the user is a legitimate user.

[1588] 2. A "counseling request" is an act in which a user inputs the details of their consultation or concerns into the system and transmits that information to the system.

[1589] 3. "Natural language processing" is a set of computer processing techniques for analyzing text data and understanding its meaning and intent.

[1590] 4. "Artificial Intelligence Module" means a program module for generating optimal responses based on the results of natural language processing.

[1591] 5. "Feedback" refers to opinions and evaluations of users regarding the systems and services provided, which are used to improve the systems.

[1592] 6. "Visualization means" refers to the means of displaying analyzed data and information in a form that can be visually confirmed by staff and users.

[1593] 7. "Real-time analysis" refers to an analysis method that processes input data immediately and provides results quickly.

[1594] 8. "Response" refers to the answer or instruction generated by the system to the user or staff.

[1595] A system for implementing this invention includes means for authenticating a user, receiving a counseling request, analyzing it using natural language processing, generating a response using an artificial intelligence module, providing the response, receiving and storing feedback, and visualizing the analyzed response to store staff in real time.

[1596] Server Operation

[1597] The server first authenticates the user by receiving the authentication information (user name and password) used by the user to log in to the system and verifying it against a database.

[1598] Next, a counseling request is received from the user. The request contains the consultation details and worries entered by the user in text format, and is sent to the system.

[1599] The server passes the received request to a natural language processing module, which analyzes the topic and sentiment of the consultation. It then combines this with an emotion engine to perform detailed recognition of the user's emotions.

[1600] Based on the analysis results, an artificial intelligence module is activated to generate the optimal response, which is displayed in real time on smart glasses or other devices worn by store staff.

[1601] After the session ends, the server receives feedback from the user and stores it in a database. The feedback includes an evaluation of the session and suggestions for improvement, and also performs sentiment analysis using an emotion engine.

[1602] Device behavior

[1603] The terminal sends the login information entered by the user to the server and receives the authentication result. Next, it sends the counseling request entered by the user to the server. The response received from the server is then displayed to the user. The user can check the response on the terminal. After the session ends, the feedback entered by the user is also sent from the terminal to the server.

[1604] Smart glasses and other devices used by store staff will analyze conversations with customers in real time and display the results, allowing staff to respond optimally to customers' emotions.

[1605] User Actions

[1606] The user logs in to the system using a dedicated app or web browser, enters their username and password on the login screen, then enters their counseling request on the system and presses the send button.

[1607] The response from the server can be viewed on the terminal, and additional questions or comments can be entered as needed. After the session ends, the user can enter an evaluation of the counseling session and suggestions for improvement, and submit them as feedback.

[1608] Specific examples

[1609] For example, if a customer asks, "I'm looking for a new smartphone. Which one is the most popular?", the staff wearing the smart glasses will analyze the question in real time and provide detailed information, including sentiment analysis. Based on this analysis information, the smart glasses' display will show a response such as, "The XX model is popular these days. Its camera function is particularly excellent, and it has been well received by many customers."

[1610] Prompt Sentence Examples

[1611] "When a customer says, 'I'm looking for a new phone. Which one is the most popular?'"

[1612] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1613] Step 1:

[1614] The server performs user authentication. It receives the username and password entered by the user and checks the information against a database. If authentication is successful, it generates a user ID and starts a session. The input is the user's authentication information, and the output is the user ID and session information.

[1615] Step 2:

[1616] The server receives a counseling request from the user. The user inputs the consultation content and worries in text format from the terminal and sends it. The server receives this text data. The input is the user's text data, and the output is the text data to be analyzed.

[1617] Step 3:

[1618] The server analyzes the counseling request using a natural language processing module. The analysis first extracts topics and emotions from the text data, and then uses an emotion engine to recognize the user's emotions in detail. The input is the text data to be analyzed, and the output is the topic and emotion information.

[1619] Step 4:

[1620] The server then activates an AI module based on the analysis results to generate an appropriate response. The AI ​​module uses the previously obtained topic and emotional information as input and generates the optimal response. The input is the topic and emotional information, and the output is the generated response text.

[1621] Step 5:

[1622] The server sends the response generated by the AI ​​module to the user terminal, where the user can check the response content on the terminal. The input is the generated response text, and the output is the response display on the user terminal.

[1623] Step 6:

[1624] The server receives feedback from the user after the counseling session ends and stores the information in a database. The server then analyzes the feedback using an emotion engine. The input is the user's feedback, and the output is the emotion analysis results and the stored data.

[1625] Step 7:

[1626] The terminal allows store staff to receive questions and requests from customers in real time and displays the analysis results. Speech is converted into text using speech recognition technology and input into a natural language processing module. The input is the customer's voice data, and the output is a display of the analysis results.

[1627] 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.

[1628] 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.

[1629] 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.

[1630] 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.

[1631] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1632] 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.

[1633] 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).

[1634] 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.

[1635] 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."

[1636] 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.

[1637] 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).

[1638] 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.

[1639] 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.

[1640] 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.

[1641] 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.

[1642] 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.

[1643] 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.

[1644] 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.

[1645] 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.

[1646] 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.

[1647] 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.

[1648] The following is further disclosed regarding the above embodiment.

[1649] (Claim 1)

[1650] means for performing user authentication;

[1651] means for receiving a counseling request from a user;

[1652] means for analyzing the counseling request by natural language processing;

[1653] means for activating an artificial intelligence module for generating an appropriate response based on the analysis results;

[1654] means for providing a response from said artificial intelligence module to a user;

[1655] A means of receiving and storing user feedback;

[1656] A system including:

[1657] (Claim 2)

[1658] 2. The system according to claim 1, wherein the artificial intelligence module includes a natural language processing module that analyzes the content of a user's inquiry and generates a response.

[1659] (Claim 3)

[1660] 2. The system of claim 1, wherein the user authentication means includes a step of checking the user's login information against a database.

[1661] "Example 1"

[1662] (Claim 1)

[1663] means for performing user authentication;

[1664] means for receiving a counseling request from a user;

[1665] means for analyzing the counseling request by natural language processing;

[1666] means for invoking a generative AI model to generate an appropriate response based on the analysis results;

[1667] means for providing a response from the generative AI model to a user;

[1668] A means of receiving and storing user feedback;

[1669] A system including:

[1670] (Claim 2)

[1671] 2. The system of claim 1, wherein the generative AI model includes a natural language processing module that analyzes the user's consultation content and generates a response.

[1672] (Claim 3)

[1673] 2. The system of claim 1, wherein the user authentication means includes a step of checking the user's login information against a database.

[1674] "Application Example 1"

[1675] (Claim 1)

[1676] means for performing user authentication;

[1677] means for receiving a counseling request from a user;

[1678] means for analyzing the counseling request by natural language processing;

[1679] means for activating an artificial intelligence module for generating an appropriate response based on the analysis results;

[1680] means for providing a response from said artificial intelligence module to a user;

[1681] A means of receiving and storing user feedback;

[1682] a means including a virtual reality system for providing counseling in a virtual space;

[1683] A system including:

[1684] (Claim 2)

[1685] 2. The system according to claim 1, wherein the artificial intelligence module includes a natural language processing module that analyzes the content of a user's inquiry and generates a response.

[1686] (Claim 3)

[1687] 2. The system of claim 1, wherein the user authentication means includes a step of checking the user's login information against a database.

[1688] "Example 2: Combining Emotion Engines"

[1689] (Claim 1)

[1690] means for performing user authentication;

[1691] means for receiving a counseling request from a user;

[1692] means for analyzing the counseling request by natural language processing;

[1693] A means of sentiment analysis of counseling requests;

[1694] means for activating an artificial intelligence module for generating an appropriate response based on the analysis results;

[1695] means for generating and inputting a prompt sentence to said artificial intelligence module;

[1696] means for providing a response from said artificial intelligence module to a user;

[1697] A means of receiving and storing user feedback;

[1698] a means for performing sentiment analysis of the feedback;

[1699] a means for storing the analysis results in a database;

[1700] A system including:

[1701] (Claim 2)

[1702] 2. The system according to claim 1, wherein the artificial intelligence module includes a natural language processing module and a sentiment analysis module that analyze the content of the user's consultation and generate a response.

[1703] (Claim 3)

[1704] 2. The system of claim 1, wherein the user authentication means includes a step of checking the user's login information against a database.

[1705] "Application example 2 when combining emotion engines"

[1706] (Claim 1)

[1707] means for performing user authentication;

[1708] means for receiving a counseling request from a user;

[1709] means for analyzing the counseling request by natural language processing;

[1710] means for activating an artificial intelligence module for generating an appropriate response based on the analysis results;

[1711] means for providing a response from said artificial intelligence module to a user;

[1712] A means of receiving and storing user feedback;

[1713] Visualization tools to provide real-time analyzed responses to store staff;

[1714] A system that includes an analytical means for analyzing conversations with customers in real time and providing the analytical results to staff.

[1715] (Claim 2)

[1716] 2. The system according to claim 1, wherein the artificial intelligence module includes a natural language processing module that analyzes the content of a user's inquiry and generates a response.

[1717] (Claim 3)

[1718] 2. The system of claim 1, wherein the user authentication means includes a step of checking the user's login information against a database. [Explanation of symbols]

[1719] 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 performing user authentication; means for receiving a counseling request from a user; means for analyzing the counseling request by natural language processing; means for activating an artificial intelligence module for generating an appropriate response based on the analysis results; means for providing a response from said artificial intelligence module to a user; a means for receiving and storing user feedback; A system including:

2. 2. The system according to claim 1, wherein the artificial intelligence module includes a natural language processing module that analyzes the content of a user's inquiry and generates a response.

3. 2. The system of claim 1, wherein said user authentication means includes a step of checking the user's login information against a database.

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